diff --git a/.gitignore b/.gitignore index 1b23d90..a78d30b 100644 --- a/.gitignore +++ b/.gitignore @@ -4,4 +4,6 @@ *.log *.pyc build/ -dist/ \ No newline at end of file +dist/ +__pycache__/ +venv/ \ No newline at end of file diff --git a/CANOE.spec b/CANOE.spec index 6bbf1af..5b109f4 100644 --- a/CANOE.spec +++ b/CANOE.spec @@ -2,9 +2,33 @@ import sys from PyInstaller.utils.hooks import collect_all -datas = [('assets', 'assets')] +datas = [ + ('assets', 'assets'), + + # Representative Periods configuration + ( + 'representative_periods/config.yaml', + 'representative_periods' + ), + + # SQL schemas used by Representative Periods + ( + 'representative_periods/canoe_schema_v3_1.sql', + 'representative_periods' + ), + ( + 'representative_periods/canoe_schema_v4_0.sql', + 'representative_periods' + ), + + # Time-series input data + ( + 'representative_periods/timeseries', + 'representative_periods/timeseries' + ), +] binaries = [] -hiddenimports = [] +hiddenimports = ['matplotlib.backends.backend_pdf'] tmp_ret = collect_all('flet') datas += tmp_ret[0]; binaries += tmp_ret[1]; hiddenimports += tmp_ret[2] tmp_ret = collect_all('flet_core') diff --git a/README.md b/README.md index e6bc78f..61664c0 100644 --- a/README.md +++ b/README.md @@ -9,8 +9,9 @@ The app provides a simple graphical interface (built with [Flet](https://flet.de ## Features - **Cross-platform UI:** built with Flet (runs as a Python script or compiled Windows executable). +- **Unified Pipeline:** process database aggregation and representative period clustering (via TSAM) in one tool. - **Automatic logging:** every session writes a timestamped log file for debugging and tracking. -- **Platform-aware directories:** logs, config, and assets are stored in appropriate locations for Python and compiled builds. +- **Platform-aware directories:** logs, config, plots, and assets are stored in appropriate locations for Python and compiled builds. - **Database schema support:** automatically loads a bundled `schema.sql` file used for SQLite setup. - **Config persistence:** saves UI options and state to a JSON configuration file. @@ -26,6 +27,7 @@ The app provides a simple graphical interface (built with [Flet](https://flet.de ├── log_setup.py # Global logging configuration ├── constants.py # Shared enums and constants ├── requirements.txt # Python dependencies +├── representative_periods/# TSAM clustering scripts and logic ├── assets/ │ └── schema.sql # SQL schema used by the database ├── logs/ # Log output (created automatically) @@ -80,11 +82,20 @@ Configuration files will be created in: ## Using the App -When the window opens: -- **Select model directories or inputs** — depending on the UI options available in your version of the interface. +When the window opens, you will have access to two main tabs: + +### 1. Aggregation Tab +- **Select model inputs and outputs** — provide the paths for your input dataset and desired output CANOE database. - **Select region-sector-scenario configurations** — determines the resolution of the output CANOE model. -- **Click submit to process** — The input dataset will be processed into the output database -- **View logs** in the terminal or in the `logs/` folder. +- **Submit** — runs the aggregation pipeline to generate a standard database. + +### 2. Representative Periods Tab +- **Configure Clustering** — define your target Test Periods, Final Periods, Clustering Method (e.g., hierarchical, k_means), and Days per Period. +- **Initialize (Cluster Only)** — executes just the TSAM clustering scripts. +- **Run (Aggregate & Cluster)** — runs an end-to-end pipeline: aggregation -> clustering -> final output database processing. +- **Output Console** — streams all script output (stdout/stderr) so you can watch clustering progress in real-time. + +*Note: Any generated plots (duration curves, timeseries) will be saved directly to the `clustering_plots` directory in your appdata folder.* If you’re running a **compiled executable**, logs and config are stored in your user directories (via `platformdirs`): diff --git a/assets/schema.sql b/assets/schema.sql index 50332e2..1e5d195 100644 --- a/assets/schema.sql +++ b/assets/schema.sql @@ -1,1838 +1,1694 @@ -PRAGMA foreign_keys= OFF; -BEGIN TRANSACTION; - -CREATE TABLE IF NOT EXISTS MetaData -( - element TEXT PRIMARY KEY, - value INT, - notes TEXT -); -REPLACE INTO MetaData -VALUES ('DB_MAJOR', 3, 'DB major version number'); -REPLACE INTO MetaData -VALUES ('DB_MINOR', 1, 'DB minor version number'); -REPLACE INTO MetaData -VALUES ('days_per_period', 365, 'count of days in each period'); - -CREATE TABLE IF NOT EXISTS MetaDataReal -( - element TEXT PRIMARY KEY, - value REAL, - notes TEXT -); -REPLACE INTO MetaDataReal -VALUES ('global_discount_rate', 0.03, 'Canadian social discount rate'); -REPLACE INTO MetaDataReal -VALUES ('default_loan_rate', 0.03, 'Matching GDR'); - -CREATE TABLE IF NOT EXISTS SeasonLabel -( - season TEXT - PRIMARY KEY, - notes TEXT -); -CREATE TABLE IF NOT EXISTS SectorLabel -( - sector TEXT, - notes TEXT, - PRIMARY KEY (sector) -); -CREATE TABLE IF NOT EXISTS CapacityCredit -( - region TEXT, - period INTEGER - REFERENCES TimePeriod (period), - tech TEXT, - vintage INTEGER, - credit REAL, - notes TEXT, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - FOREIGN KEY (tech) REFERENCES Technology (tech), - PRIMARY KEY (region, period, tech, vintage), - CHECK (credit >= 0 AND credit <= 1) -); -CREATE TABLE IF NOT EXISTS CapacityFactorProcess -( - region TEXT, - period INTEGER - REFERENCES TimePeriod (period), - season TEXT - REFERENCES SeasonLabel (season), - tod TEXT - REFERENCES TimeOfDay (tod), - tech TEXT, - vintage INTEGER, - factor REAL, - notes TEXT, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - FOREIGN KEY (tech) REFERENCES Technology (tech), - PRIMARY KEY (region, period, season, tod, tech, vintage), - CHECK (factor >= 0 AND factor <= 1) -); -CREATE TABLE IF NOT EXISTS CapacityFactorTech -( - region TEXT, - period INTEGER - REFERENCES TimePeriod (period), - season TEXT - REFERENCES SeasonLabel (season), - tod TEXT - REFERENCES TimeOfDay (tod), - tech TEXT, - factor REAL, - notes TEXT, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - FOREIGN KEY (tech) REFERENCES Technology (tech), - PRIMARY KEY (region, period, season, tod, tech), - CHECK (factor >= 0 AND factor <= 1) -); -CREATE TABLE IF NOT EXISTS CapacityToActivity -( - region TEXT, - tech TEXT, - c2a REAL, - notes TEXT, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - FOREIGN KEY (tech) REFERENCES Technology (tech), - PRIMARY KEY (region, tech) -); -CREATE TABLE IF NOT EXISTS Commodity -( - name TEXT, - flag TEXT - REFERENCES CommodityType (label), - description TEXT, - data_id TEXT - REFERENCES DataSet (data_id), - PRIMARY KEY (name) -); -CREATE TABLE IF NOT EXISTS CommodityType -( - label TEXT PRIMARY KEY, - description TEXT -); -REPLACE INTO CommodityType -VALUES ('s', 'source commodity'); -REPLACE INTO CommodityType -VALUES ('a', 'annual commodity'); -REPLACE INTO CommodityType -VALUES ('p', 'physical commodity'); -REPLACE INTO CommodityType -VALUES ('d', 'demand commodity'); -REPLACE INTO CommodityType -VALUES ('e', 'emissions commodity'); -REPLACE INTO CommodityType -VALUES ('w', 'waste commodity'); -REPLACE INTO CommodityType -VALUES ('wa', 'waste annual commodity'); -REPLACE INTO CommodityType -VALUES ('wp', 'waste physical commodity'); -CREATE TABLE IF NOT EXISTS ConstructionInput -( - region TEXT, - input_comm TEXT, - tech TEXT, - vintage INTEGER - REFERENCES TimePeriod (period), - value REAL, - units TEXT, - notes TEXT, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - FOREIGN KEY (tech) REFERENCES Technology (tech), - FOREIGN KEY (input_comm) REFERENCES Commodity (name), - PRIMARY KEY (region, input_comm, tech, vintage) -); -CREATE TABLE IF NOT EXISTS CostEmission -( - region TEXT, - period INTEGER - REFERENCES TimePeriod (period), - emis_comm TEXT NOT NULL, - cost REAL NOT NULL, - units TEXT, - notes TEXT, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - FOREIGN KEY (emis_comm) REFERENCES Commodity (name), - PRIMARY KEY (region, period, emis_comm) -); -CREATE TABLE IF NOT EXISTS CostFixed -( - region TEXT NOT NULL, - period INTEGER NOT NULL - REFERENCES TimePeriod (period), - tech TEXT NOT NULL, - vintage INTEGER NOT NULL - REFERENCES TimePeriod (period), - cost REAL, - units TEXT, - notes TEXT, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - FOREIGN KEY (tech) REFERENCES Technology (tech), - PRIMARY KEY (region, period, tech, vintage) -); -CREATE TABLE IF NOT EXISTS CostInvest -( - region TEXT, - tech TEXT, - vintage INTEGER - REFERENCES TimePeriod (period), - cost REAL, - units TEXT, - notes TEXT, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - FOREIGN KEY (tech) REFERENCES Technology (tech), - PRIMARY KEY (region, tech, vintage) -); -CREATE TABLE IF NOT EXISTS CostVariable -( - region TEXT NOT NULL, - period INTEGER NOT NULL - REFERENCES TimePeriod (period), - tech TEXT NOT NULL, - vintage INTEGER NOT NULL - REFERENCES TimePeriod (period), - cost REAL, - units TEXT, - notes TEXT, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - FOREIGN KEY (tech) REFERENCES Technology (tech), - PRIMARY KEY (region, period, tech, vintage) -); -CREATE TABLE IF NOT EXISTS Demand -( - region TEXT, - period INTEGER - REFERENCES TimePeriod (period), - commodity TEXT, - demand REAL, - units TEXT, - notes TEXT, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - FOREIGN KEY (commodity) REFERENCES Commodity (name), - PRIMARY KEY (region, period, commodity) -); -CREATE TABLE IF NOT EXISTS DemandSpecificDistribution -( - region TEXT, - period INTEGER - REFERENCES TimePeriod (period), - season TEXT - REFERENCES SeasonLabel (season), - tod TEXT - REFERENCES TimeOfDay (tod), - demand_name TEXT, - dsd REAL, - notes TEXT, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - FOREIGN KEY (demand_name) REFERENCES Commodity (name), - PRIMARY KEY (region, period, season, tod, demand_name), - CHECK (dsd >= 0 AND dsd <= 1) -); -CREATE TABLE IF NOT EXISTS EndOfLifeOutput -( - region TEXT, - tech TEXT, - vintage INTEGER - REFERENCES TimePeriod (period), - output_comm TEXT, - value REAL, - units TEXT, - notes TEXT, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - FOREIGN KEY (tech) REFERENCES Technology (tech), - FOREIGN KEY (output_comm) REFERENCES Commodity (name), - PRIMARY KEY (region, tech, vintage, output_comm) -); -CREATE TABLE IF NOT EXISTS Efficiency -( - region TEXT, - input_comm TEXT, - tech TEXT, - vintage INTEGER - REFERENCES TimePeriod (period), - output_comm TEXT, - efficiency REAL, - notes TEXT, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - FOREIGN KEY (tech) REFERENCES Technology (tech), - FOREIGN KEY (input_comm) REFERENCES Commodity (name), - FOREIGN KEY (output_comm) REFERENCES Commodity (name), - PRIMARY KEY (region, input_comm, tech, vintage, output_comm), - CHECK (efficiency > 0) -); -CREATE TABLE IF NOT EXISTS EfficiencyVariable -( - region TEXT, - period INTEGER - REFERENCES TimePeriod (period), - season TEXT - REFERENCES SeasonLabel (season), - tod TEXT - REFERENCES TimeOfDay (tod), - input_comm TEXT, - tech TEXT, - vintage INTEGER - REFERENCES TimePeriod (period), - output_comm TEXT, - efficiency REAL, - notes TEXT, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - FOREIGN KEY (tech) REFERENCES Technology (tech), - FOREIGN KEY (input_comm) REFERENCES Commodity (name), - FOREIGN KEY (output_comm) REFERENCES Commodity (name), - PRIMARY KEY (region, period, season, tod, input_comm, tech, vintage, output_comm), - CHECK (efficiency > 0) -); -CREATE TABLE IF NOT EXISTS EmissionActivity -( - region TEXT, - emis_comm TEXT, - input_comm TEXT, - tech TEXT, - vintage INTEGER - REFERENCES TimePeriod (period), - output_comm TEXT, - activity REAL, - units TEXT, - notes TEXT, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - FOREIGN KEY (tech) REFERENCES Technology (tech), - FOREIGN KEY (emis_comm) REFERENCES Commodity (name), - FOREIGN KEY (input_comm) REFERENCES Commodity (name), - FOREIGN KEY (output_comm) REFERENCES Commodity (name), - PRIMARY KEY (region, emis_comm, input_comm, tech, vintage, output_comm) -); -CREATE TABLE IF NOT EXISTS EmissionEmbodied -( - region TEXT, - emis_comm TEXT, - tech TEXT, - vintage INTEGER - REFERENCES TimePeriod (period), - value REAL, - units TEXT, - notes TEXT, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - FOREIGN KEY (tech) REFERENCES Technology (tech), - FOREIGN KEY (emis_comm) REFERENCES Commodity (name), - PRIMARY KEY (region, emis_comm, tech, vintage) -); -CREATE TABLE IF NOT EXISTS EmissionEndOfLife -( - region TEXT, - emis_comm TEXT, - tech TEXT, - vintage INTEGER - REFERENCES TimePeriod (period), - value REAL, - units TEXT, - notes TEXT, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - FOREIGN KEY (tech) REFERENCES Technology (tech), - FOREIGN KEY (emis_comm) REFERENCES Commodity (name), - PRIMARY KEY (region, emis_comm, tech, vintage) -); -CREATE TABLE IF NOT EXISTS ExistingCapacity -( - region TEXT, - tech TEXT, - vintage INTEGER - REFERENCES TimePeriod (period), - capacity REAL, - units TEXT, - notes TEXT, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - FOREIGN KEY (tech) REFERENCES Technology (tech), - PRIMARY KEY (region, tech, vintage) -); -CREATE TABLE IF NOT EXISTS TechGroup -( - group_name TEXT, - notes TEXT, - data_id TEXT - REFERENCES DataSet (data_id), - PRIMARY KEY (group_name) -); -CREATE TABLE IF NOT EXISTS LoanLifetimeProcess -( - region TEXT, - tech TEXT, - vintage INTEGER - REFERENCES TimePeriod (period), - lifetime REAL, - notes TEXT, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - FOREIGN KEY (tech) REFERENCES Technology (tech), - PRIMARY KEY (region, tech, vintage) -); -CREATE TABLE IF NOT EXISTS LoanRate -( - region TEXT, - tech TEXT, - vintage INTEGER - REFERENCES TimePeriod (period), - rate REAL, - notes TEXT, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - FOREIGN KEY (tech) REFERENCES Technology (tech), - PRIMARY KEY (region, tech, vintage) -); -CREATE TABLE IF NOT EXISTS LifetimeProcess -( - region TEXT, - tech TEXT, - vintage INTEGER - REFERENCES TimePeriod (period), - lifetime REAL, - notes TEXT, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - FOREIGN KEY (tech) REFERENCES Technology (tech), - PRIMARY KEY (region, tech, vintage) -); -CREATE TABLE IF NOT EXISTS LifetimeTech -( - region TEXT, - tech TEXT, - lifetime REAL, - notes TEXT, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - FOREIGN KEY (tech) REFERENCES Technology (tech), - PRIMARY KEY (region, tech) -); -CREATE TABLE IF NOT EXISTS Operator -( - operator TEXT PRIMARY KEY, - notes TEXT -); -REPLACE INTO Operator VALUES('e','equal to'); -REPLACE INTO Operator VALUES('le','less than or equal to'); -REPLACE INTO Operator VALUES('ge','greater than or equal to'); -CREATE TABLE IF NOT EXISTS OutputDualVariable -( - scenario TEXT, - constraint_name TEXT, - dual REAL, - PRIMARY KEY (constraint_name, scenario) -); -CREATE TABLE IF NOT EXISTS OutputObjective -( - scenario TEXT, - objective_name TEXT, - total_system_cost REAL -); -CREATE TABLE IF NOT EXISTS OutputCurtailment -( - scenario TEXT, - region TEXT, - sector TEXT, - period INTEGER - REFERENCES TimePeriod (period), - season TEXT - REFERENCES TimePeriod (period), - tod TEXT - REFERENCES TimeOfDay (tod), - input_comm TEXT - REFERENCES Commodity (name), - tech TEXT - REFERENCES Technology (tech), - vintage INTEGER - REFERENCES TimePeriod (period), - output_comm TEXT - REFERENCES Commodity (name), - curtailment REAL, - PRIMARY KEY (region, scenario, period, season, tod, input_comm, tech, vintage, output_comm) -); -CREATE TABLE IF NOT EXISTS OutputNetCapacity -( - scenario TEXT, - region TEXT, - sector TEXT - REFERENCES SectorLabel (sector), - period INTEGER - REFERENCES TimePeriod (period), - tech TEXT - REFERENCES Technology (tech), - vintage INTEGER - REFERENCES TimePeriod (period), - capacity REAL, - PRIMARY KEY (region, scenario, period, tech, vintage) -); -CREATE TABLE IF NOT EXISTS OutputBuiltCapacity -( - scenario TEXT, - region TEXT, - sector TEXT - REFERENCES SectorLabel (sector), - tech TEXT - REFERENCES Technology (tech), - vintage INTEGER - REFERENCES TimePeriod (period), - capacity REAL, - PRIMARY KEY (region, scenario, tech, vintage) -); -CREATE TABLE IF NOT EXISTS OutputRetiredCapacity -( - scenario TEXT, - region TEXT, - sector TEXT - REFERENCES SectorLabel (sector), - period INTEGER - REFERENCES TimePeriod (period), - tech TEXT - REFERENCES Technology (tech), - vintage INTEGER - REFERENCES TimePeriod (period), - cap_eol REAL, - cap_early REAL, - PRIMARY KEY (region, scenario, period, tech, vintage) -); -CREATE TABLE IF NOT EXISTS OutputFlowIn -( - scenario TEXT, - region TEXT, - sector TEXT - REFERENCES SectorLabel (sector), - period INTEGER - REFERENCES TimePeriod (period), - season TEXT - REFERENCES SeasonLabel (season), - tod TEXT - REFERENCES TimeOfDay (tod), - input_comm TEXT - REFERENCES Commodity (name), - tech TEXT - REFERENCES Technology (tech), - vintage INTEGER - REFERENCES TimePeriod (period), - output_comm TEXT - REFERENCES Commodity (name), - flow REAL, - PRIMARY KEY (region, scenario, period, season, tod, input_comm, tech, vintage, output_comm) -); -CREATE TABLE IF NOT EXISTS OutputFlowOut -( - scenario TEXT, - region TEXT, - sector TEXT - REFERENCES SectorLabel (sector), - period INTEGER - REFERENCES TimePeriod (period), - season TEXT - REFERENCES SeasonLabel (season), - tod TEXT - REFERENCES TimeOfDay (tod), - input_comm TEXT - REFERENCES Commodity (name), - tech TEXT - REFERENCES Technology (tech), - vintage INTEGER - REFERENCES TimePeriod (period), - output_comm TEXT - REFERENCES Commodity (name), - flow REAL, - PRIMARY KEY (region, scenario, period, season, tod, input_comm, tech, vintage, output_comm) -); -CREATE TABLE IF NOT EXISTS OutputStorageLevel -( - scenario TEXT, - region TEXT, - sector TEXT - REFERENCES SectorLabel (sector), - period INTEGER - REFERENCES TimePeriod (period), - season TEXT - REFERENCES SeasonLabel (season), - tod TEXT - REFERENCES TimeOfDay (tod), - tech TEXT - REFERENCES Technology (tech), - vintage INTEGER - REFERENCES TimePeriod (period), - level REAL, - PRIMARY KEY (scenario, region, period, season, tod, tech, vintage) -); -CREATE TABLE IF NOT EXISTS OutputEmission -( - scenario TEXT, - region TEXT, - sector TEXT - REFERENCES SectorLabel (sector), - period INTEGER - REFERENCES TimePeriod (period), - emis_comm TEXT - REFERENCES Commodity (name), - tech TEXT - REFERENCES Technology (tech), - vintage INTEGER - REFERENCES TimePeriod (period), - emission REAL, - PRIMARY KEY (region, scenario, period, emis_comm, tech, vintage) -); -CREATE TABLE IF NOT EXISTS OutputCost -( - scenario TEXT, - region TEXT, - sector TEXT REFERENCES SectorLabel (sector), - period INTEGER REFERENCES TimePeriod (period), - tech TEXT REFERENCES Technology (tech), - vintage INTEGER REFERENCES TimePeriod (period), - d_invest REAL, - d_fixed REAL, - d_var REAL, - d_emiss REAL, - invest REAL, - fixed REAL, - var REAL, - emiss REAL, - PRIMARY KEY (scenario, region, period, tech, vintage), - FOREIGN KEY (vintage) REFERENCES TimePeriod (period), - FOREIGN KEY (tech) REFERENCES Technology (tech) -); -CREATE TABLE IF NOT EXISTS LimitGrowthCapacity -( - region TEXT, - tech_or_group TEXT, - operator TEXT NOT NULL DEFAULT "le" - REFERENCES Operator (operator), - rate REAL NOT NULL DEFAULT 0, - seed REAL NOT NULL DEFAULT 0, - seed_units TEXT, - notes TEXT, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - PRIMARY KEY (region, tech_or_group, operator) -); -CREATE TABLE IF NOT EXISTS LimitDegrowthCapacity -( - region TEXT, - tech_or_group TEXT, - operator TEXT NOT NULL DEFAULT "le" - REFERENCES Operator (operator), - rate REAL NOT NULL DEFAULT 0, - seed REAL NOT NULL DEFAULT 0, - seed_units TEXT, - notes TEXT, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - PRIMARY KEY (region, tech_or_group, operator) -); -CREATE TABLE IF NOT EXISTS LimitGrowthNewCapacity -( - region TEXT, - tech_or_group TEXT, - operator TEXT NOT NULL DEFAULT "le" - REFERENCES Operator (operator), - rate REAL NOT NULL DEFAULT 0, - seed REAL NOT NULL DEFAULT 0, - seed_units TEXT, - notes TEXT, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - PRIMARY KEY (region, tech_or_group, operator) -); -CREATE TABLE IF NOT EXISTS LimitDegrowthNewCapacity -( - region TEXT, - tech_or_group TEXT, - operator TEXT NOT NULL DEFAULT "le" - REFERENCES Operator (operator), - rate REAL NOT NULL DEFAULT 0, - seed REAL NOT NULL DEFAULT 0, - seed_units TEXT, - notes TEXT, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - PRIMARY KEY (region, tech_or_group, operator) -); -CREATE TABLE IF NOT EXISTS LimitGrowthNewCapacityDelta -( - region TEXT, - tech_or_group TEXT, - operator TEXT NOT NULL DEFAULT "le" - REFERENCES Operator (operator), - rate REAL NOT NULL DEFAULT 0, - seed REAL NOT NULL DEFAULT 0, - seed_units TEXT, - notes TEXT, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - PRIMARY KEY (region, tech_or_group, operator) -); -CREATE TABLE IF NOT EXISTS LimitDegrowthNewCapacityDelta -( - region TEXT, - tech_or_group TEXT, - operator TEXT NOT NULL DEFAULT "le" - REFERENCES Operator (operator), - rate REAL NOT NULL DEFAULT 0, - seed REAL NOT NULL DEFAULT 0, - seed_units TEXT, - notes TEXT, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - PRIMARY KEY (region, tech_or_group, operator) -); -CREATE TABLE IF NOT EXISTS LimitStorageLevelFraction -( - region TEXT, - period INTEGER - REFERENCES TimePeriod (period), - season TEXT - REFERENCES SeasonLabel (season), - tod TEXT - REFERENCES TimeOfDay (tod), - tech TEXT, - vintage INTEGER - REFERENCES TimePeriod (period), - operator TEXT NOT NULL DEFAULT "le" - REFERENCES Operator (operator), - fraction REAL, - notes TEXT, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - FOREIGN KEY (tech) REFERENCES Technology (tech), - PRIMARY KEY (region, period, season, tod, tech, vintage, operator) -); -CREATE TABLE IF NOT EXISTS LimitActivity -( - region TEXT, - period INTEGER - REFERENCES TimePeriod (period), - tech_or_group TEXT, - operator TEXT NOT NULL DEFAULT "le" - REFERENCES Operator (operator), - activity REAL, - units TEXT, - notes TEXT, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - PRIMARY KEY (region, period, tech_or_group, operator) -); -CREATE TABLE IF NOT EXISTS LimitActivityShare -( - region TEXT, - period INTEGER - REFERENCES TimePeriod (period), - sub_group TEXT, - super_group TEXT, - operator TEXT NOT NULL DEFAULT "le" - REFERENCES Operator (operator), - share REAL, - notes TEXT, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - PRIMARY KEY (region, period, sub_group, super_group, operator) -); -CREATE TABLE IF NOT EXISTS LimitAnnualCapacityFactor -( - region TEXT, - tech TEXT, - vintage INTEGER - REFERENCES TimePeriod (period), - output_comm TEXT, - operator TEXT NOT NULL DEFAULT "le" - REFERENCES Operator (operator), - factor REAL, - notes TEXT, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - FOREIGN KEY (tech) REFERENCES Technology (tech), - FOREIGN KEY (output_comm) REFERENCES Commodity (name), - PRIMARY KEY (region, tech, vintage, output_comm, operator), - CHECK (factor >= 0 AND factor <= 1) -); -CREATE TABLE IF NOT EXISTS LimitCapacity -( - region TEXT, - period INTEGER - REFERENCES TimePeriod (period), - tech_or_group TEXT, - operator TEXT NOT NULL DEFAULT "le" - REFERENCES Operator (operator), - capacity REAL, - units TEXT, - notes TEXT, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - PRIMARY KEY (region, period, tech_or_group, operator) -); -CREATE TABLE IF NOT EXISTS LimitCapacityShare -( - region TEXT, - period INTEGER - REFERENCES TimePeriod (period), - sub_group TEXT, - super_group TEXT, - operator TEXT NOT NULL DEFAULT "le" - REFERENCES Operator (operator), - share REAL, - notes TEXT, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - PRIMARY KEY (region, period, sub_group, super_group, operator) -); -CREATE TABLE IF NOT EXISTS LimitNewCapacity -( - region TEXT, - period INTEGER - REFERENCES TimePeriod (period), - tech_or_group TEXT, - operator TEXT NOT NULL DEFAULT "le" - REFERENCES Operator (operator), - new_cap REAL, - units TEXT, - notes TEXT, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - PRIMARY KEY (region, period, tech_or_group, operator) -); -CREATE TABLE IF NOT EXISTS LimitNewCapacityShare -( - region TEXT, - period INTEGER - REFERENCES TimePeriod (period), - sub_group TEXT, - super_group TEXT, - operator TEXT NOT NULL DEFAULT "le" - REFERENCES Operator (operator), - share REAL, - notes TEXT, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - PRIMARY KEY (region, period, sub_group, super_group, operator) -); -CREATE TABLE IF NOT EXISTS LimitResource -( - region TEXT, - tech_or_group TEXT, - operator TEXT NOT NULL DEFAULT "le" - REFERENCES Operator (operator), - cum_act REAL, - units TEXT, - notes TEXT, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - PRIMARY KEY (region, tech_or_group, operator) -); -CREATE TABLE IF NOT EXISTS LimitSeasonalCapacityFactor -( - region TEXT, - period INTEGER - REFERENCES TimePeriod (period), - season TEXT - REFERENCES SeasonLabel (season), - tech TEXT, - operator TEXT NOT NULL DEFAULT "le" - REFERENCES Operator (operator), - factor REAL, - notes TEXT, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - FOREIGN KEY (region) REFERENCES Region (region), - FOREIGN KEY (tech) REFERENCES Technology (tech), - PRIMARY KEY (region, period, season, tech, operator) -); -CREATE TABLE IF NOT EXISTS LimitTechInputSplit -( - region TEXT, - period INTEGER - REFERENCES TimePeriod (period), - input_comm TEXT, - tech TEXT, - operator TEXT NOT NULL DEFAULT "le" - REFERENCES Operator (operator), - proportion REAL, - notes TEXT, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - FOREIGN KEY (tech) REFERENCES Technology (tech), - FOREIGN KEY (input_comm) REFERENCES Commodity (name), - PRIMARY KEY (region, period, input_comm, tech, operator) -); -CREATE TABLE IF NOT EXISTS LimitTechInputSplitAnnual -( - region TEXT, - period INTEGER - REFERENCES TimePeriod (period), - input_comm TEXT, - tech TEXT, - operator TEXT NOT NULL DEFAULT "le" - REFERENCES Operator (operator), - proportion REAL, - notes TEXT, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - FOREIGN KEY (tech) REFERENCES Technology (tech), - PRIMARY KEY (region, period, input_comm, tech, operator) -); -CREATE TABLE IF NOT EXISTS LimitTechOutputSplit -( - region TEXT, - period INTEGER - REFERENCES TimePeriod (period), - tech TEXT, - output_comm TEXT, - operator TEXT NOT NULL DEFAULT "le" - REFERENCES Operator (operator), - proportion REAL, - notes TEXT, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - FOREIGN KEY (tech) REFERENCES Technology (tech), - FOREIGN KEY (output_comm) REFERENCES Commodity (name), - PRIMARY KEY (region, period, tech, output_comm, operator) -); -CREATE TABLE IF NOT EXISTS LimitTechOutputSplitAnnual -( - region TEXT, - period INTEGER - REFERENCES TimePeriod (period), - tech TEXT, - output_comm TEXT, - operator TEXT NOT NULL DEFAULT "le" - REFERENCES Operator (operator), - proportion REAL, - notes TEXT, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - FOREIGN KEY (tech) REFERENCES Technology (tech), - FOREIGN KEY (output_comm) REFERENCES Commodity (name), - PRIMARY KEY (region, period, tech, output_comm, operator) -); -CREATE TABLE IF NOT EXISTS LimitEmission -( - region TEXT, - period INTEGER - REFERENCES TimePeriod (period), - emis_comm TEXT, - operator TEXT NOT NULL DEFAULT "le" - REFERENCES Operator (operator), - value REAL, - units TEXT, - notes TEXT, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - FOREIGN KEY (emis_comm) REFERENCES Commodity (name), - PRIMARY KEY (region, period, emis_comm, operator) -); -CREATE TABLE IF NOT EXISTS LinkedTech -( - primary_region TEXT, - primary_tech TEXT, - emis_comm TEXT, - driven_tech TEXT, - notes TEXT, - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (primary_tech) REFERENCES Technology (tech), - FOREIGN KEY (driven_tech) REFERENCES Technology (tech), - FOREIGN KEY (emis_comm) REFERENCES Commodity (name), - PRIMARY KEY (primary_region, primary_tech, emis_comm) -); -CREATE TABLE IF NOT EXISTS PlanningReserveMargin -( - region TEXT, - margin REAL, - notes TEXT, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - FOREIGN KEY (region) REFERENCES Region (region), - PRIMARY KEY (region) -); -CREATE TABLE IF NOT EXISTS RampDownHourly -( - region TEXT, - tech TEXT, - rate REAL, - notes TEXT, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - FOREIGN KEY (tech) REFERENCES Technology (tech), - PRIMARY KEY (region, tech) -); -CREATE TABLE IF NOT EXISTS RampUpHourly -( - region TEXT, - tech TEXT, - rate REAL, - notes TEXT, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - FOREIGN KEY (tech) REFERENCES Technology (tech), - PRIMARY KEY (region, tech) -); -CREATE TABLE IF NOT EXISTS Region -( - region TEXT, - notes TEXT, - PRIMARY KEY (region) -); -CREATE TABLE IF NOT EXISTS ReserveCapacityDerate -( - region TEXT, - period INTEGER - REFERENCES TimePeriod (period), - season TEXT - REFERENCES SeasonLabel (season), - tech TEXT, - vintage INTEGER, - factor REAL, - notes TEXT, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - FOREIGN KEY (tech) REFERENCES Technology (tech), - PRIMARY KEY (region, period, season, tech, vintage), - CHECK (factor >= 0 AND factor <= 1) -); -CREATE TABLE IF NOT EXISTS TimeSegmentFraction -( - period INTEGER - REFERENCES TimePeriod (period), - season TEXT - REFERENCES SeasonLabel (season), - tod TEXT - REFERENCES TimeOfDay (tod), - segfrac REAL, - notes TEXT, - PRIMARY KEY (period, season, tod), - CHECK (segfrac >= 0 AND segfrac <= 1) -); -CREATE TABLE IF NOT EXISTS StorageDuration -( - region TEXT, - tech TEXT, - duration REAL, - notes TEXT, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - PRIMARY KEY (region, tech) -); -CREATE TABLE IF NOT EXISTS LifetimeSurvivalCurve -( - region TEXT NOT NULL, - period INTEGER NOT NULL, - tech TEXT NOT NULL, - vintage INTEGER NOT NULL - REFERENCES TimePeriod (period), - fraction REAL, - notes TEXT, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - FOREIGN KEY (tech) REFERENCES Technology (tech), - PRIMARY KEY (region, period, tech, vintage) -); -CREATE TABLE IF NOT EXISTS TechnologyType -( - label TEXT PRIMARY KEY, - description TEXT -); -REPLACE INTO TechnologyType -VALUES ('p', 'production technology'); -REPLACE INTO TechnologyType -VALUES ('pb', 'baseload production technology'); -REPLACE INTO TechnologyType -VALUES ('ps', 'storage production technology'); --- CREATE TABLE IF NOT EXISTS TimeNext --- ( --- period INTEGER --- REFERENCES TimePeriod (period), --- season TEXT --- REFERENCES SeasonLabel (season), --- tod TEXT --- REFERENCES TimeOfDay (tod), --- season_next TEXT --- REFERENCES SeasonLabel (season), --- tod_next TEXT --- REFERENCES TimeOfDay (tod), --- notes TEXT, --- PRIMARY KEY (period, season, tod) --- ); -CREATE TABLE IF NOT EXISTS TimeOfDay -( - sequence INTEGER UNIQUE, - tod TEXT - PRIMARY KEY -); -CREATE TABLE IF NOT EXISTS TimePeriod -( - sequence INTEGER UNIQUE, - period INTEGER - PRIMARY KEY, - flag TEXT - REFERENCES TimePeriodType (label) -); -CREATE TABLE IF NOT EXISTS TimeSeason -( - period INTEGER - REFERENCES TimePeriod (period), - sequence INTEGER, - season TEXT - REFERENCES SeasonLabel (season), - notes TEXT, - PRIMARY KEY (period, sequence, season) -); -CREATE TABLE IF NOT EXISTS TimeSeasonSequential -( - period INTEGER - REFERENCES TimePeriod (period), - sequence INTEGER, - seas_seq TEXT, - season TEXT - REFERENCES SeasonLabel (season), - num_days REAL NOT NULL, - notes TEXT, - PRIMARY KEY (period, sequence, seas_seq, season), - CHECK (num_days > 0) -); -CREATE TABLE IF NOT EXISTS TimePeriodType -( - label TEXT PRIMARY KEY, - description TEXT -); -REPLACE INTO TimePeriodType -VALUES('e', 'existing vintages'); -REPLACE INTO TimePeriodType -VALUES('f', 'future'); -CREATE TABLE IF NOT EXISTS RPSRequirement -( - region TEXT NOT NULL, - period INTEGER NOT NULL - REFERENCES TimePeriod (period), - tech_group TEXT NOT NULL, - requirement REAL NOT NULL, - data_source TEXT, - dq_cred INTEGER - REFERENCES DataQualityCredibility (dq_cred), - dq_geog INTEGER - REFERENCES DataQualityGeography (dq_geog), - dq_struc INTEGER - REFERENCES DataQualityStructure (dq_struc), - dq_tech INTEGER - REFERENCES DataQualityTechnology (dq_tech), - dq_time INTEGER - REFERENCES DataQualityTime (dq_time), - data_id TEXT - REFERENCES DataSet (data_id), - notes TEXT, - FOREIGN KEY (data_source) REFERENCES DataSource (source_id), - FOREIGN KEY (region) REFERENCES Region (region), - FOREIGN KEY (tech_group) REFERENCES TechGroup (group_name), - PRIMARY KEY (region) -); -CREATE TABLE IF NOT EXISTS TechGroupMember -( - group_name TEXT, - tech TEXT, - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (tech) REFERENCES Technology (tech), - FOREIGN KEY (group_name) REFERENCES TechGroup (group_name), - PRIMARY KEY (group_name, tech) -); -CREATE TABLE IF NOT EXISTS Technology -( - tech TEXT NOT NULL, - flag TEXT NOT NULL, - sector TEXT, - category TEXT, - sub_category TEXT, - unlim_cap INTEGER NOT NULL DEFAULT 0, - annual INTEGER NOT NULL DEFAULT 0, - reserve INTEGER NOT NULL DEFAULT 0, - curtail INTEGER NOT NULL DEFAULT 0, - retire INTEGER NOT NULL DEFAULT 0, - flex INTEGER NOT NULL DEFAULT 0, - exchange INTEGER NOT NULL DEFAULT 0, - seas_stor INTEGER NOT NULL DEFAULT 0, - description TEXT, - data_id TEXT - REFERENCES DataSet (data_id), - FOREIGN KEY (flag) REFERENCES TechnologyType (label), - PRIMARY KEY (tech) -); -CREATE TABLE IF NOT EXISTS DataSource -( - source_id TEXT, - source TEXT, - notes TEXT, - data_id TEXT - REFERENCES DataSet (data_id), - PRIMARY KEY (source_id) -); -CREATE TABLE IF NOT EXISTS DataQualityCredibility -( - dq_cred INTEGER PRIMARY KEY, - description TEXT -); -REPLACE INTO DataQualityCredibility VALUES (1,'Excellent - A trustworthy source backed by strong analysis or direct measurements.'); -REPLACE INTO DataQualityCredibility VALUES (2,'Good - Trustworthy source. Partly based on assumptions or imperfect analysis.'); -REPLACE INTO DataQualityCredibility VALUES (3,'Acceptable - Acceptable source. May rely on many assumptions, shallow analysis, or rough measurement.'); -REPLACE INTO DataQualityCredibility VALUES (4,'Lacking - Questionable or unverified source. Poorly measured or weak analysis.'); -REPLACE INTO DataQualityCredibility VALUES (5,'Unacceptable - No or untrustworthy source. Unsupported assumption.'); -CREATE TABLE IF NOT EXISTS DataQualityGeography -( - dq_geog INTEGER PRIMARY KEY, - description TEXT -); -REPLACE INTO DataQualityGeography VALUES (1,'Excellent - From this region and at the correct aggregation level or a directly-applicable generic value.'); -REPLACE INTO DataQualityGeography VALUES (2,'Good - From an analogous region or the modelled region at incorrect aggregation level.'); -REPLACE INTO DataQualityGeography VALUES (3,'Acceptable - From a relevant but non-analogous region or highly aggregated.'); -REPLACE INTO DataQualityGeography VALUES (4,'Lacking - From a non-analogous region with limited relevance or a generic global value.'); -REPLACE INTO DataQualityGeography VALUES (5,'Unacceptable - From a region that is highly dissimilar to the modelled region, or from an unknown region.'); -CREATE TABLE IF NOT EXISTS DataQualityStructure -( - dq_struc INTEGER PRIMARY KEY, - description TEXT -); -REPLACE INTO DataQualityStructure VALUES (1,'Excellent - Excellent representation of the system, as good or better than other models.'); -REPLACE INTO DataQualityStructure VALUES (2,'Good - Well modelled, in line with what others are doing.'); -REPLACE INTO DataQualityStructure VALUES (3,'Acceptable - Room for improved representation but works for now.'); -REPLACE INTO DataQualityStructure VALUES (4,'Lacking - Poorly represented, overly simplified.'); -REPLACE INTO DataQualityStructure VALUES (5,'Unacceptable - Placeholder or dummy representation. Essentially not represented.'); -CREATE TABLE IF NOT EXISTS DataQualityTechnology -( - dq_tech INTEGER PRIMARY KEY, - description TEXT -); -REPLACE INTO DataQualityTechnology VALUES (1,'Excellent - For the modelled technology as represented. Directly applicable.'); -REPLACE INTO DataQualityTechnology VALUES (2,'Good - For the same general technology but not perfectly representative.'); -REPLACE INTO DataQualityTechnology VALUES (3,'Acceptable - For an analogous technology. Possibly a subset or general class. Roughly applicable.'); -REPLACE INTO DataQualityTechnology VALUES (4,'Lacking - Loosely representative. A niche subset or overbroad general class of the technology.'); -REPLACE INTO DataQualityTechnology VALUES (5,'Unacceptable - For a dissimilar or unknown technology. Unknown or poor applicability.'); -CREATE TABLE IF NOT EXISTS DataQualityTime -( - dq_time INTEGER PRIMARY KEY, - description TEXT -); -REPLACE INTO DataQualityTime VALUES (1,'Excellent - From or directly applicable to the modelled time.'); -REPLACE INTO DataQualityTime VALUES (2,'Good - From a different but similar time or only slightly out of date. Still highly relevant.'); -REPLACE INTO DataQualityTime VALUES (3,'Acceptable - From a somewhat similar time or several years out of date but still relevant.'); -REPLACE INTO DataQualityTime VALUES (4,'Lacking - From a time with different conditions or significantly out of date. Questionable relevance.'); -REPLACE INTO DataQualityTime VALUES (5,'Unacceptable - From an irrelevant time or badly out of date.'); -CREATE TABLE IF NOT EXISTS DataSet -( - data_id TEXT PRIMARY KEY, - label TEXT, - version TEXT, - description TEXT, - status TEXT, - author TEXT, - date TEXT, - parent_id TEXT - REFERENCES DataSet (data_id), - changelog TEXT, - notes TEXT -); - -COMMIT; -PRAGMA FOREIGN_KEYS = 1; \ No newline at end of file +PRAGMA foreign_keys = OFF; +BEGIN TRANSACTION; + +-- ============================================================ +-- Metadata +-- ============================================================ + +CREATE TABLE IF NOT EXISTS metadata +( + element TEXT PRIMARY KEY, + value INT, + notes TEXT +); +REPLACE INTO metadata VALUES ('DB_MAJOR', 4, 'DB major version number'); +REPLACE INTO metadata VALUES ('DB_MINOR', 0, 'DB minor version number'); + +CREATE TABLE IF NOT EXISTS metadata_real +( + element TEXT PRIMARY KEY, + value REAL, + notes TEXT +); +REPLACE INTO metadata_real VALUES ('global_discount_rate', 0.03, 'Discount Rate for future costs'); +REPLACE INTO metadata_real VALUES ('default_loan_rate', 0.03, 'Default Loan Rate if not specified in loan_rate table'); + +-- ============================================================ +-- Label / registry tables +-- ============================================================ +CREATE TABLE IF NOT EXISTS commodity_label +( + commodity TEXT PRIMARY KEY, + notes TEXT +); + +CREATE TABLE IF NOT EXISTS technology_label +( + tech TEXT PRIMARY KEY, + notes TEXT +); + +CREATE TABLE IF NOT EXISTS tech_group_label +( + group_name TEXT PRIMARY KEY, + notes TEXT +); + +CREATE TABLE IF NOT EXISTS sector_label +( + sector TEXT PRIMARY KEY, + notes TEXT +); + +-- ============================================================ +-- Enum / type tables +-- ============================================================ +CREATE TABLE IF NOT EXISTS commodity_type +( + label TEXT PRIMARY KEY, + description TEXT +); +REPLACE INTO commodity_type VALUES ('s', 'source commodity'); +REPLACE INTO commodity_type VALUES ('a', 'annual commodity'); +REPLACE INTO commodity_type VALUES ('p', 'physical commodity'); +REPLACE INTO commodity_type VALUES ('d', 'demand commodity'); +REPLACE INTO commodity_type VALUES ('e', 'emissions commodity'); +REPLACE INTO commodity_type VALUES ('w', 'waste commodity'); +REPLACE INTO commodity_type VALUES ('wa', 'waste annual commodity'); +REPLACE INTO commodity_type VALUES ('wp', 'waste physical commodity'); + +CREATE TABLE IF NOT EXISTS technology_type +( + label TEXT PRIMARY KEY, + description TEXT +); +REPLACE INTO technology_type VALUES ('p', 'production technology'); +REPLACE INTO technology_type VALUES ('pb', 'baseload production technology'); +REPLACE INTO technology_type VALUES ('ps', 'storage production technology'); + +CREATE TABLE IF NOT EXISTS time_period_type +( + label TEXT PRIMARY KEY, + description TEXT +); +REPLACE INTO time_period_type VALUES ('e', 'existing vintages'); +REPLACE INTO time_period_type VALUES ('f', 'future'); + +CREATE TABLE IF NOT EXISTS operator +( + operator TEXT PRIMARY KEY, + notes TEXT +); +REPLACE INTO operator VALUES ('e', 'equal to'); +REPLACE INTO operator VALUES ('le', 'less than or equal to'); +REPLACE INTO operator VALUES ('ge', 'greater than or equal to'); + +-- ============================================================ +-- Data quality and data source tables (custom) +-- ============================================================ +CREATE TABLE IF NOT EXISTS data_quality_credibility +( + dq_cred INTEGER PRIMARY KEY, + description TEXT +); +REPLACE INTO data_quality_credibility VALUES (1, 'Excellent - A trustworthy source backed by strong analysis or direct measurements.'); +REPLACE INTO data_quality_credibility VALUES (2, 'Good - Trustworthy source. Partly based on assumptions or imperfect analysis.'); +REPLACE INTO data_quality_credibility VALUES (3, 'Acceptable - Acceptable source. May rely on many assumptions, shallow analysis, or rough measurement.'); +REPLACE INTO data_quality_credibility VALUES (4, 'Lacking - Questionable or unverified source. Poorly measured or weak analysis.'); +REPLACE INTO data_quality_credibility VALUES (5, 'Unacceptable - No or untrustworthy source. Unsupported assumption.'); + +CREATE TABLE IF NOT EXISTS data_quality_geography +( + dq_geog INTEGER PRIMARY KEY, + description TEXT +); +REPLACE INTO data_quality_geography VALUES (1, 'Excellent - From this region and at the correct aggregation level or a directly-applicable generic value.'); +REPLACE INTO data_quality_geography VALUES (2, 'Good - From an analogous region or the modelled region at incorrect aggregation level.'); +REPLACE INTO data_quality_geography VALUES (3, 'Acceptable - From a relevant but non-analogous region or highly aggregated.'); +REPLACE INTO data_quality_geography VALUES (4, 'Lacking - From a non-analogous region with limited relevance or a generic global value.'); +REPLACE INTO data_quality_geography VALUES (5, 'Unacceptable - From a region that is highly dissimilar to the modelled region, or from an unknown region.'); + +CREATE TABLE IF NOT EXISTS data_quality_structure +( + dq_struc INTEGER PRIMARY KEY, + description TEXT +); +REPLACE INTO data_quality_structure VALUES (1, 'Excellent - Excellent representation of the system, as good or better than other models.'); +REPLACE INTO data_quality_structure VALUES (2, 'Good - Well modelled, in line with what others are doing.'); +REPLACE INTO data_quality_structure VALUES (3, 'Acceptable - Room for improved representation but works for now.'); +REPLACE INTO data_quality_structure VALUES (4, 'Lacking - Poorly represented, overly simplified.'); +REPLACE INTO data_quality_structure VALUES (5, 'Unacceptable - Placeholder or dummy representation. Essentially not represented.'); + +CREATE TABLE IF NOT EXISTS data_quality_technology +( + dq_tech INTEGER PRIMARY KEY, + description TEXT +); +REPLACE INTO data_quality_technology VALUES (1, 'Excellent - For the modelled technology as represented. Directly applicable.'); +REPLACE INTO data_quality_technology VALUES (2, 'Good - For the same general technology but not perfectly representative.'); +REPLACE INTO data_quality_technology VALUES (3, 'Acceptable - For an analogous technology. Possibly a subset or general class. Roughly applicable.'); +REPLACE INTO data_quality_technology VALUES (4, 'Lacking - Loosely representative. A niche subset or overbroad general class of the technology.'); +REPLACE INTO data_quality_technology VALUES (5, 'Unacceptable - For a dissimilar or unknown technology. Unknown or poor applicability.'); + +CREATE TABLE IF NOT EXISTS data_quality_time +( + dq_time INTEGER PRIMARY KEY, + description TEXT +); +REPLACE INTO data_quality_time VALUES (1, 'Excellent - From or directly applicable to the modelled time.'); +REPLACE INTO data_quality_time VALUES (2, 'Good - From a different but similar time or only slightly out of date. Still highly relevant.'); +REPLACE INTO data_quality_time VALUES (3, 'Acceptable - From a somewhat similar time or several years out of date but still relevant.'); +REPLACE INTO data_quality_time VALUES (4, 'Lacking - From a time with different conditions or significantly out of date. Questionable relevance.'); +REPLACE INTO data_quality_time VALUES (5, 'Unacceptable - From an irrelevant time or badly out of date.'); + +CREATE TABLE IF NOT EXISTS data_source_label +( + source_id TEXT PRIMARY KEY, + notes TEXT +); + +CREATE TABLE IF NOT EXISTS data_set +( + data_id TEXT PRIMARY KEY, + label TEXT, + version TEXT, + description TEXT, + status TEXT, + author TEXT, + date TEXT, + parent_id TEXT + REFERENCES data_set (data_id), + changelog TEXT, + notes TEXT +); + +CREATE TABLE IF NOT EXISTS data_source +( + source_id TEXT, + source TEXT, + notes TEXT, + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (source_id) REFERENCES data_source_label (source_id), + PRIMARY KEY (source_id) +); + +-- ============================================================ +-- Time tables +-- ============================================================ +CREATE TABLE IF NOT EXISTS time_period +( + sequence INTEGER UNIQUE, + period INTEGER PRIMARY KEY, + flag TEXT + REFERENCES time_period_type (label) +); + +CREATE TABLE IF NOT EXISTS time_of_day +( + sequence INTEGER UNIQUE, + tod TEXT PRIMARY KEY, + hours REAL NOT NULL DEFAULT 1, + notes TEXT, + CHECK (hours > 0) +); + +CREATE TABLE IF NOT EXISTS time_season +( + sequence INTEGER UNIQUE, + season TEXT PRIMARY KEY, + segment_fraction REAL NOT NULL, + notes TEXT, + CHECK (segment_fraction >= 0 AND segment_fraction <= 1) +); + +CREATE TABLE IF NOT EXISTS time_season_sequential +( + sequence INTEGER UNIQUE, + seas_seq TEXT PRIMARY KEY, + season TEXT + REFERENCES time_season (season), + segment_fraction REAL NOT NULL, + notes TEXT, + CHECK (segment_fraction >= 0 AND segment_fraction <= 1) +); + +-- ============================================================ +-- Region +-- ============================================================ +CREATE TABLE IF NOT EXISTS region +( + region TEXT PRIMARY KEY, + notes TEXT +); + +-- ============================================================ +-- Core model definition tables +-- ============================================================ +CREATE TABLE IF NOT EXISTS commodity +( + name TEXT, + flag TEXT + REFERENCES commodity_type (label), + description TEXT, + units TEXT, + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (name) REFERENCES commodity_label (commodity), + PRIMARY KEY (name) +); + +CREATE TABLE IF NOT EXISTS technology +( + tech TEXT NOT NULL, + flag TEXT NOT NULL, + sector TEXT, + category TEXT, + sub_category TEXT, + unlim_cap INTEGER NOT NULL DEFAULT 0, + annual INTEGER NOT NULL DEFAULT 0, + reserve INTEGER NOT NULL DEFAULT 0, + curtail INTEGER NOT NULL DEFAULT 0, + retire INTEGER NOT NULL DEFAULT 0, + flex INTEGER NOT NULL DEFAULT 0, + exchange INTEGER NOT NULL DEFAULT 0, + seas_stor INTEGER NOT NULL DEFAULT 0, + description TEXT, + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (flag) REFERENCES technology_type (label), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + PRIMARY KEY (tech) +); + +CREATE TABLE IF NOT EXISTS tech_group +( + group_name TEXT, + notes TEXT, + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (group_name) REFERENCES tech_group_label (group_name), + PRIMARY KEY (group_name) +); + +CREATE TABLE IF NOT EXISTS tech_group_member +( + group_name TEXT, + tech TEXT, + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + FOREIGN KEY (group_name) REFERENCES tech_group_label (group_name), + PRIMARY KEY (group_name, tech) +); + +-- ============================================================ +-- Data tables +-- All include: data_id (in PK), data_source, dq_cred/geog/struc/tech/time +-- ============================================================ +CREATE TABLE IF NOT EXISTS capacity_credit +( + region TEXT, + period INTEGER + REFERENCES time_period (period), + tech TEXT, + vintage INTEGER, + credit REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + PRIMARY KEY (region, period, tech, vintage), + CHECK (credit >= 0 AND credit <= 1) +); + +CREATE TABLE IF NOT EXISTS capacity_factor_process +( + region TEXT, + season TEXT + REFERENCES time_season (season), + tod TEXT + REFERENCES time_of_day (tod), + tech TEXT, + vintage INTEGER, + factor REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + PRIMARY KEY (region, season, tod, tech, vintage), + CHECK (factor >= 0 AND factor <= 1) +); + +CREATE TABLE IF NOT EXISTS capacity_factor_tech +( + region TEXT, + season TEXT + REFERENCES time_season (season), + tod TEXT + REFERENCES time_of_day (tod), + tech TEXT, + factor REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + PRIMARY KEY (region, season, tod, tech), + CHECK (factor >= 0 AND factor <= 1) +); + +CREATE TABLE IF NOT EXISTS capacity_to_activity +( + region TEXT, + tech TEXT, + c2a REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + PRIMARY KEY (region, tech) +); + +CREATE TABLE IF NOT EXISTS construction_input +( + region TEXT, + input_comm TEXT, + tech TEXT, + vintage INTEGER + REFERENCES time_period (period), + value REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + FOREIGN KEY (input_comm) REFERENCES commodity_label (commodity), + PRIMARY KEY (region, input_comm, tech, vintage) +); + +CREATE TABLE IF NOT EXISTS cost_emission +( + region TEXT, + period INTEGER + REFERENCES time_period (period), + emis_comm TEXT NOT NULL, + cost REAL NOT NULL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (emis_comm) REFERENCES commodity_label (commodity), + PRIMARY KEY (region, period, emis_comm) +); + +CREATE TABLE IF NOT EXISTS cost_fixed +( + region TEXT NOT NULL, + period INTEGER NOT NULL + REFERENCES time_period (period), + tech TEXT NOT NULL, + vintage INTEGER NOT NULL + REFERENCES time_period (period), + cost REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + PRIMARY KEY (region, period, tech, vintage) +); + +CREATE TABLE IF NOT EXISTS cost_invest +( + region TEXT, + tech TEXT, + vintage INTEGER + REFERENCES time_period (period), + cost REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + PRIMARY KEY (region, tech, vintage) +); + +CREATE TABLE IF NOT EXISTS cost_variable +( + region TEXT NOT NULL, + period INTEGER NOT NULL + REFERENCES time_period (period), + tech TEXT NOT NULL, + vintage INTEGER NOT NULL + REFERENCES time_period (period), + cost REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + PRIMARY KEY (region, period, tech, vintage) +); + +CREATE TABLE IF NOT EXISTS demand +( + region TEXT, + period INTEGER + REFERENCES time_period (period), + commodity TEXT, + demand REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (commodity) REFERENCES commodity_label (commodity), + PRIMARY KEY (region, period, commodity) +); + +CREATE TABLE IF NOT EXISTS demand_specific_distribution +( + region TEXT, + period INTEGER + REFERENCES time_period (period), + season TEXT + REFERENCES time_season (season), + tod TEXT + REFERENCES time_of_day (tod), + demand_name TEXT, + dsd REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (demand_name) REFERENCES commodity_label (commodity), + PRIMARY KEY (region, period, season, tod, demand_name), + CHECK (dsd >= 0 AND dsd <= 1) +); + +CREATE TABLE IF NOT EXISTS end_of_life_output +( + region TEXT, + tech TEXT, + vintage INTEGER + REFERENCES time_period (period), + output_comm TEXT, + value REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + FOREIGN KEY (output_comm) REFERENCES commodity_label (commodity), + PRIMARY KEY (region, tech, vintage, output_comm) +); + +CREATE TABLE IF NOT EXISTS efficiency +( + region TEXT, + input_comm TEXT, + tech TEXT, + vintage INTEGER + REFERENCES time_period (period), + output_comm TEXT, + efficiency REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + FOREIGN KEY (input_comm) REFERENCES commodity_label (commodity), + FOREIGN KEY (output_comm) REFERENCES commodity_label (commodity), + PRIMARY KEY (region, input_comm, tech, vintage, output_comm), + CHECK (efficiency > 0) +); + +CREATE TABLE IF NOT EXISTS efficiency_variable +( + region TEXT, + season TEXT + REFERENCES time_season (season), + tod TEXT + REFERENCES time_of_day (tod), + input_comm TEXT, + tech TEXT, + vintage INTEGER + REFERENCES time_period (period), + output_comm TEXT, + efficiency REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + FOREIGN KEY (input_comm) REFERENCES commodity_label (commodity), + FOREIGN KEY (output_comm) REFERENCES commodity_label (commodity), + PRIMARY KEY (region, season, tod, input_comm, tech, vintage, output_comm), + CHECK (efficiency > 0) +); + +CREATE TABLE IF NOT EXISTS emission_activity +( + region TEXT, + emis_comm TEXT, + input_comm TEXT, + tech TEXT, + vintage INTEGER + REFERENCES time_period (period), + output_comm TEXT, + activity REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + FOREIGN KEY (emis_comm) REFERENCES commodity_label (commodity), + FOREIGN KEY (input_comm) REFERENCES commodity_label (commodity), + FOREIGN KEY (output_comm) REFERENCES commodity_label (commodity), + PRIMARY KEY (region, emis_comm, input_comm, tech, vintage, output_comm) +); + +CREATE TABLE IF NOT EXISTS emission_embodied +( + region TEXT, + emis_comm TEXT, + tech TEXT, + vintage INTEGER + REFERENCES time_period (period), + value REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + FOREIGN KEY (emis_comm) REFERENCES commodity_label (commodity), + PRIMARY KEY (region, emis_comm, tech, vintage) +); + +CREATE TABLE IF NOT EXISTS emission_end_of_life +( + region TEXT, + emis_comm TEXT, + tech TEXT, + vintage INTEGER + REFERENCES time_period (period), + value REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + FOREIGN KEY (emis_comm) REFERENCES commodity_label (commodity), + PRIMARY KEY (region, emis_comm, tech, vintage) +); + +CREATE TABLE IF NOT EXISTS existing_capacity +( + region TEXT, + tech TEXT, + vintage INTEGER + REFERENCES time_period (period), + capacity REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + PRIMARY KEY (region, tech, vintage) +); + +CREATE TABLE IF NOT EXISTS loan_lifetime_process +( + region TEXT, + tech TEXT, + vintage INTEGER + REFERENCES time_period (period), + lifetime REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + PRIMARY KEY (region, tech, vintage) +); + +CREATE TABLE IF NOT EXISTS loan_rate +( + region TEXT, + tech TEXT, + vintage INTEGER + REFERENCES time_period (period), + rate REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + PRIMARY KEY (region, tech, vintage) +); + +CREATE TABLE IF NOT EXISTS lifetime_process +( + region TEXT, + tech TEXT, + vintage INTEGER + REFERENCES time_period (period), + lifetime REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + PRIMARY KEY (region, tech, vintage) +); + +CREATE TABLE IF NOT EXISTS lifetime_tech +( + region TEXT, + tech TEXT, + lifetime REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + PRIMARY KEY (region, tech) +); + +CREATE TABLE IF NOT EXISTS limit_growth_capacity +( + region TEXT, + tech_or_group TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES operator (operator), + rate REAL NOT NULL DEFAULT 0, + seed REAL NOT NULL DEFAULT 0, + seed_units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + PRIMARY KEY (region, tech_or_group, operator) +); + +CREATE TABLE IF NOT EXISTS limit_degrowth_capacity +( + region TEXT, + tech_or_group TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES operator (operator), + rate REAL NOT NULL DEFAULT 0, + seed REAL NOT NULL DEFAULT 0, + seed_units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + PRIMARY KEY (region, tech_or_group, operator) +); + +CREATE TABLE IF NOT EXISTS limit_growth_new_capacity +( + region TEXT, + tech_or_group TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES operator (operator), + rate REAL NOT NULL DEFAULT 0, + seed REAL NOT NULL DEFAULT 0, + seed_units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + PRIMARY KEY (region, tech_or_group, operator) +); + +CREATE TABLE IF NOT EXISTS limit_degrowth_new_capacity +( + region TEXT, + tech_or_group TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES operator (operator), + rate REAL NOT NULL DEFAULT 0, + seed REAL NOT NULL DEFAULT 0, + seed_units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + PRIMARY KEY (region, tech_or_group, operator) +); + +CREATE TABLE IF NOT EXISTS limit_growth_new_capacity_delta +( + region TEXT, + tech_or_group TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES operator (operator), + rate REAL NOT NULL DEFAULT 0, + seed REAL NOT NULL DEFAULT 0, + seed_units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + PRIMARY KEY (region, tech_or_group, operator) +); + +CREATE TABLE IF NOT EXISTS limit_degrowth_new_capacity_delta +( + region TEXT, + tech_or_group TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES operator (operator), + rate REAL NOT NULL DEFAULT 0, + seed REAL NOT NULL DEFAULT 0, + seed_units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + PRIMARY KEY (region, tech_or_group, operator) +); + +CREATE TABLE IF NOT EXISTS limit_storage_level_fraction +( + region TEXT, + season TEXT + REFERENCES time_season (season), + tod TEXT + REFERENCES time_of_day (tod), + tech TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES operator (operator), + fraction REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + CHECK (fraction >= 0 AND fraction <= 1), + PRIMARY KEY (region, season, tod, tech, operator) +); + +CREATE TABLE IF NOT EXISTS limit_activity +( + region TEXT, + period INTEGER + REFERENCES time_period (period), + tech_or_group TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES operator (operator), + activity REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + PRIMARY KEY (region, period, tech_or_group, operator) +); + +CREATE TABLE IF NOT EXISTS limit_activity_share +( + region TEXT, + period INTEGER + REFERENCES time_period (period), + sub_group TEXT, + super_group TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES operator (operator), + share REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + PRIMARY KEY (region, period, sub_group, super_group, operator) +); + +CREATE TABLE IF NOT EXISTS limit_annual_capacity_factor +( + region TEXT, + tech_or_group TEXT, + vintage INTEGER + REFERENCES time_period (period), + output_comm TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES operator (operator), + factor REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (output_comm) REFERENCES commodity_label (commodity), + PRIMARY KEY (region, tech_or_group, vintage, output_comm, operator), + CHECK (factor >= 0 AND factor <= 1) +); + +CREATE TABLE IF NOT EXISTS limit_capacity +( + region TEXT, + period INTEGER + REFERENCES time_period (period), + tech_or_group TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES operator (operator), + capacity REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + PRIMARY KEY (region, period, tech_or_group, operator) +); + +CREATE TABLE IF NOT EXISTS limit_capacity_share +( + region TEXT, + period INTEGER + REFERENCES time_period (period), + sub_group TEXT, + super_group TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES operator (operator), + share REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + PRIMARY KEY (region, period, sub_group, super_group, operator) +); + +CREATE TABLE IF NOT EXISTS limit_new_capacity +( + region TEXT, + tech_or_group TEXT, + vintage INTEGER + REFERENCES time_period (period), + operator TEXT NOT NULL DEFAULT "le" + REFERENCES operator (operator), + new_cap REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + PRIMARY KEY (region, tech_or_group, vintage, operator) +); + +CREATE TABLE IF NOT EXISTS limit_new_capacity_share +( + region TEXT, + sub_group TEXT, + super_group TEXT, + vintage INTEGER + REFERENCES time_period (period), + operator TEXT NOT NULL DEFAULT "le" + REFERENCES operator (operator), + share REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + PRIMARY KEY (region, sub_group, super_group, vintage, operator) +); + +CREATE TABLE IF NOT EXISTS limit_resource +( + region TEXT, + tech_or_group TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES operator (operator), + cum_act REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + PRIMARY KEY (region, tech_or_group, operator) +); + +CREATE TABLE IF NOT EXISTS limit_seasonal_capacity_factor +( + region TEXT + REFERENCES region (region), + season TEXT + REFERENCES time_season (season), + tech_or_group TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES operator (operator), + factor REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + PRIMARY KEY (region, season, tech_or_group, operator) +); + +CREATE TABLE IF NOT EXISTS limit_tech_input_split +( + region TEXT, + period INTEGER + REFERENCES time_period (period), + input_comm TEXT, + tech TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES operator (operator), + proportion REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + FOREIGN KEY (input_comm) REFERENCES commodity_label (commodity), + PRIMARY KEY (region, period, input_comm, tech, operator) +); + +CREATE TABLE IF NOT EXISTS limit_tech_input_split_annual +( + region TEXT, + period INTEGER + REFERENCES time_period (period), + input_comm TEXT, + tech TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES operator (operator), + proportion REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + PRIMARY KEY (region, period, input_comm, tech, operator) +); + +CREATE TABLE IF NOT EXISTS limit_tech_output_split +( + region TEXT, + period INTEGER + REFERENCES time_period (period), + tech TEXT, + output_comm TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES operator (operator), + proportion REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + FOREIGN KEY (output_comm) REFERENCES commodity_label (commodity), + PRIMARY KEY (region, period, tech, output_comm, operator) +); + +CREATE TABLE IF NOT EXISTS limit_tech_output_split_annual +( + region TEXT, + period INTEGER + REFERENCES time_period (period), + tech TEXT, + output_comm TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES operator (operator), + proportion REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + FOREIGN KEY (output_comm) REFERENCES commodity_label (commodity), + PRIMARY KEY (region, period, tech, output_comm, operator) +); + +CREATE TABLE IF NOT EXISTS limit_emission +( + region TEXT, + period INTEGER + REFERENCES time_period (period), + emis_comm TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES operator (operator), + value REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (emis_comm) REFERENCES commodity_label (commodity), + PRIMARY KEY (region, period, emis_comm, operator) +); + +CREATE TABLE IF NOT EXISTS linked_tech +( + primary_region TEXT, + primary_tech TEXT, + emis_comm TEXT, + driven_tech TEXT, + notes TEXT, + data_source TEXT, + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (primary_tech) REFERENCES technology_label (tech), + FOREIGN KEY (driven_tech) REFERENCES technology_label (tech), + FOREIGN KEY (emis_comm) REFERENCES commodity_label (commodity), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + PRIMARY KEY (primary_region, primary_tech, emis_comm) +); + +CREATE TABLE IF NOT EXISTS planning_reserve_margin +( + region TEXT, + margin REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (region) REFERENCES region (region), + PRIMARY KEY (region) +); + +CREATE TABLE IF NOT EXISTS ramp_down_hourly +( + region TEXT, + tech TEXT, + rate REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + PRIMARY KEY (region, tech) +); + +CREATE TABLE IF NOT EXISTS ramp_up_hourly +( + region TEXT, + tech TEXT, + rate REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + PRIMARY KEY (region, tech) +); + +CREATE TABLE IF NOT EXISTS reserve_capacity_derate +( + region TEXT, + season TEXT + REFERENCES time_season (season), + tech TEXT, + vintage INTEGER, + factor REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + PRIMARY KEY (region, season, tech, vintage), + CHECK (factor >= 0 AND factor <= 1) +); + +CREATE TABLE IF NOT EXISTS storage_duration +( + region TEXT, + tech TEXT, + duration REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + PRIMARY KEY (region, tech) +); + +CREATE TABLE IF NOT EXISTS lifetime_survival_curve +( + region TEXT NOT NULL, + period INTEGER NOT NULL, + tech TEXT NOT NULL, + vintage INTEGER NOT NULL + REFERENCES time_period (period), + fraction REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + PRIMARY KEY (region, period, tech, vintage) +); + +CREATE TABLE IF NOT EXISTS rps_requirement +( + region TEXT NOT NULL + REFERENCES region (region), + period INTEGER NOT NULL + REFERENCES time_period (period), + tech_group TEXT NOT NULL, + requirement REAL NOT NULL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech_group) REFERENCES tech_group_label (group_name), + PRIMARY KEY (region, period, tech_group) +); + +CREATE TABLE IF NOT EXISTS output_dual_variable +( + scenario TEXT, + constraint_name TEXT, + dual REAL, + PRIMARY KEY (constraint_name, scenario) +); +CREATE TABLE IF NOT EXISTS output_objective +( + scenario TEXT, + objective_name TEXT, + total_system_cost REAL +); +CREATE TABLE IF NOT EXISTS output_curtailment +( + scenario TEXT, + region TEXT, + sector TEXT, + period INTEGER + REFERENCES time_period (period), + season TEXT + REFERENCES time_season (season), + tod TEXT + REFERENCES time_of_day (tod), + input_comm TEXT + REFERENCES commodity_label (commodity), + tech TEXT + REFERENCES technology_label (tech), + vintage INTEGER + REFERENCES time_period (period), + output_comm TEXT + REFERENCES commodity_label (commodity), + curtailment REAL, + units TEXT, + PRIMARY KEY (region, scenario, period, season, tod, input_comm, tech, vintage, output_comm) +); +CREATE TABLE IF NOT EXISTS output_net_capacity +( + scenario TEXT, + region TEXT, + sector TEXT + REFERENCES sector_label (sector), + period INTEGER + REFERENCES time_period (period), + tech TEXT + REFERENCES technology_label (tech), + vintage INTEGER + REFERENCES time_period (period), + capacity REAL, + units TEXT, + PRIMARY KEY (region, scenario, period, tech, vintage) +); +CREATE TABLE IF NOT EXISTS output_built_capacity +( + scenario TEXT, + region TEXT, + sector TEXT + REFERENCES sector_label (sector), + tech TEXT + REFERENCES technology_label (tech), + vintage INTEGER + REFERENCES time_period (period), + capacity REAL, + units TEXT, + PRIMARY KEY (region, scenario, tech, vintage) +); +CREATE TABLE IF NOT EXISTS output_retired_capacity +( + scenario TEXT, + region TEXT, + sector TEXT + REFERENCES sector_label (sector), + period INTEGER + REFERENCES time_period (period), + tech TEXT + REFERENCES technology_label (tech), + vintage INTEGER + REFERENCES time_period (period), + cap_eol REAL, + cap_early REAL, + units TEXT, + PRIMARY KEY (region, scenario, period, tech, vintage) +); +CREATE TABLE IF NOT EXISTS output_flow_in +( + scenario TEXT, + region TEXT, + sector TEXT + REFERENCES sector_label (sector), + period INTEGER + REFERENCES time_period (period), + season TEXT + REFERENCES time_season (season), + tod TEXT + REFERENCES time_of_day (tod), + input_comm TEXT + REFERENCES commodity_label (commodity), + tech TEXT + REFERENCES technology_label (tech), + vintage INTEGER + REFERENCES time_period (period), + output_comm TEXT + REFERENCES commodity_label (commodity), + flow REAL, + units TEXT, + PRIMARY KEY (region, scenario, period, season, tod, input_comm, tech, vintage, output_comm) +); +CREATE TABLE IF NOT EXISTS output_flow_out +( + scenario TEXT, + region TEXT, + sector TEXT + REFERENCES sector_label (sector), + period INTEGER + REFERENCES time_period (period), + season TEXT + REFERENCES time_season (season), + tod TEXT + REFERENCES time_of_day (tod), + input_comm TEXT + REFERENCES commodity_label (commodity), + tech TEXT + REFERENCES technology_label (tech), + vintage INTEGER + REFERENCES time_period (period), + output_comm TEXT + REFERENCES commodity_label (commodity), + flow REAL, + units TEXT, + PRIMARY KEY (region, scenario, period, season, tod, input_comm, tech, vintage, output_comm) +); +CREATE TABLE IF NOT EXISTS output_storage_level +( + scenario TEXT, + region TEXT, + sector TEXT + REFERENCES sector_label (sector), + period INTEGER + REFERENCES time_period (period), + season TEXT, + tod TEXT + REFERENCES time_of_day (tod), + tech TEXT + REFERENCES technology_label (tech), + vintage INTEGER + REFERENCES time_period (period), + level REAL, + units TEXT, + PRIMARY KEY (scenario, region, period, season, tod, tech, vintage) +); +CREATE TABLE IF NOT EXISTS output_emission +( + scenario TEXT, + region TEXT, + sector TEXT + REFERENCES sector_label (sector), + period INTEGER + REFERENCES time_period (period), + emis_comm TEXT + REFERENCES commodity_label (commodity), + tech TEXT + REFERENCES technology_label (tech), + vintage INTEGER + REFERENCES time_period (period), + emission REAL, + units TEXT, + PRIMARY KEY (region, scenario, period, emis_comm, tech, vintage) +); +CREATE TABLE IF NOT EXISTS output_cost +( + scenario TEXT, + region TEXT, + sector TEXT REFERENCES sector_label (sector), + period INTEGER REFERENCES time_period (period), + tech TEXT REFERENCES technology_label (tech), + vintage INTEGER REFERENCES time_period (period), + d_invest REAL, + d_fixed REAL, + d_var REAL, + d_emiss REAL, + invest REAL, + fixed REAL, + var REAL, + emiss REAL, + units TEXT, + PRIMARY KEY (scenario, region, period, tech, vintage), + FOREIGN KEY (vintage) REFERENCES time_period (period), + FOREIGN KEY (tech) REFERENCES technology_label (tech) +); +CREATE TABLE IF NOT EXISTS myopic_efficiency +( + base_year integer, + region text, + input_comm TEXT + REFERENCES commodity_label (commodity), + tech TEXT + REFERENCES technology_label (tech), + vintage INTEGER + REFERENCES time_period (period), + output_comm TEXT + REFERENCES commodity_label (commodity), + efficiency real, + lifetime integer, + PRIMARY KEY (region, input_comm, tech, vintage, output_comm) +); +-- for efficient searching by rtv: +-- CREATE INDEX IF NOT EXISTS region_tech_vintage ON myopic_efficiency (region, tech, vintage); + +CREATE TABLE IF NOT EXISTS output_flow_out_summary +( + scenario TEXT, + region TEXT, + sector TEXT + REFERENCES sector_label (sector), + period INTEGER + REFERENCES time_period (period), + input_comm TEXT + REFERENCES commodity_label (commodity), + tech TEXT + REFERENCES technology_label (tech), + vintage INTEGER + REFERENCES time_period (period), + output_comm TEXT + REFERENCES commodity_label (commodity), + flow REAL, + PRIMARY KEY (scenario, region, period, input_comm, tech, vintage, output_comm) +); + +COMMIT; +PRAGMA foreign_keys = ON; diff --git a/constants.py b/constants.py index 1f43990..3db045c 100644 --- a/constants.py +++ b/constants.py @@ -1,129 +1,129 @@ -""" -Some Enums to avoid hard coding strings elsewhere. -For readability, maintainability, and to reduce typos. -""" - -######################################### -# Enumerators for CANOE data sets -######################################### - -from enum import Enum -from typing import Set, List - -class SortableEnum(Enum): - """ - An Enum that supports less-than comparisons based on value. - """ - def __lt__(self, other): - if not isinstance(other, self.__class__): - return NotImplemented - return self.value < other.value - -class Region(SortableEnum): - """ - Viable regions in CANOE data sets. - """ - ALBERTA = 'AB' - BRITISH_COLUMBIA = 'BC' - MANITOBA = 'MB' - NEW_BRUNSWICK = 'NB' - NEWFOUNDLAND_AND_LABRADOR = 'NLLAB' - NOVA_SCOTIA = 'NS' - ONTARIO = 'ON' - PRINCE_EDWARD_ISLAND = 'PEI' - QUEBEC = 'QC' - SASKATCHEWAN = 'SK' - USA = 'USA' - NONE = '' - -class Sector(SortableEnum): - """ - Viable sectors in CANOE data sets. - """ - AGRICULTURE = 'AGRI' - COMMERCIAL = 'COM' - ELECTRICITY = 'ELC' - FUEL = 'FUEL' - INDUSTRY = 'IND' - RESIDENTIAL = 'RES' - TRANSPORTATION = 'TRP' - -class Variant(SortableEnum): - """ - Viable sector variants in CANOE data sets. - """ - HIGH_RESOLUTION = 'HR' - CURRENT_MEASURES = 'CM' - NET_ZERO = 'NZ' - -class Feature(SortableEnum): - """ - Viable additional features in CANOE data sets. - """ - DEMAND = 'DEM' - ENDOGENOUS_INTERTIE = 'EINT' - BOUNDARY_INTERTIE = 'BINT' - NONE = '' - -class Level(SortableEnum): - """ - Sector resolution levels for UI - """ - HIGH_RESOLUTION = 'HIGH' - LOW_RESOLUTION = 'LOW' - EXCLUDED = '-' - -######################################### -# UI constants -######################################### - -LOW_SCENARIOS: List[str] = [ - "Current Measures", - "Global Net Zero" -] -"""UI naming for low resolution scenarios""" - -DEFAULT_LOW: str = 'Current Measures' -"""Default low resolution scenario (UI name)""" - -TABLE_SECTORS: List[Sector] = sorted( - s.value for s in [ - Sector.COMMERCIAL, - Sector.ELECTRICITY, - Sector.INDUSTRY, - Sector.RESIDENTIAL, - Sector.TRANSPORTATION - ] -) -"""Sectors that are included in UI options matrix""" - -TABLE_REGIONS: List[Region] = sorted( - r.value for r in [ - Region.ALBERTA, - Region.BRITISH_COLUMBIA, - Region.MANITOBA, - Region.NEW_BRUNSWICK, - Region.NEWFOUNDLAND_AND_LABRADOR, - Region.NOVA_SCOTIA, - Region.ONTARIO, - Region.PRINCE_EDWARD_ISLAND, - Region.QUEBEC, - Region.SASKATCHEWAN - ] -) -"""Regions that are included in UI options matrix""" - -######################################### -# Database processing constants -######################################### - -INDEX_TABLES: Set[str] = { - 'CommodityType','Operator','TechnologyType','TimePeriodType', - 'DataQualityCredibility','DataQualityGeography', - 'DataQualityStructure','DataQualityTechnology','DataQualityTime', - 'TechnologyLabel','CommodityLabel','DataSourceLabel' -} -"""SQLite tables that are handled by the schema and need not be transferred""" - -LTT_DEFAULT: int = 40 +""" +Some Enums to avoid hard coding strings elsewhere. +For readability, maintainability, and to reduce typos. +""" + +######################################### +# Enumerators for CANOE data sets +######################################### + +from enum import Enum +from typing import Set, List + +class SortableEnum(Enum): + """ + An Enum that supports less-than comparisons based on value. + """ + def __lt__(self, other): + if not isinstance(other, self.__class__): + return NotImplemented + return self.value < other.value + +class Region(SortableEnum): + """ + Viable regions in CANOE data sets. + """ + ALBERTA = 'AB' + BRITISH_COLUMBIA = 'BC' + MANITOBA = 'MB' + NEW_BRUNSWICK = 'NB' + NEWFOUNDLAND_AND_LABRADOR = 'NLLAB' + NOVA_SCOTIA = 'NS' + ONTARIO = 'ON' + PRINCE_EDWARD_ISLAND = 'PEI' + QUEBEC = 'QC' + SASKATCHEWAN = 'SK' + USA = 'USA' + NONE = '' + +class Sector(SortableEnum): + """ + Viable sectors in CANOE data sets. + """ + AGRICULTURE = 'AGRI' + COMMERCIAL = 'COM' + ELECTRICITY = 'ELC' + FUEL = 'FUEL' + INDUSTRY = 'IND' + RESIDENTIAL = 'RES' + TRANSPORTATION = 'TRP' + +class Variant(SortableEnum): + """ + Viable sector variants in CANOE data sets. + """ + HIGH_RESOLUTION = 'HR' + CURRENT_MEASURES = 'CM' + NET_ZERO = 'NZ' + +class Feature(SortableEnum): + """ + Viable additional features in CANOE data sets. + """ + DEMAND = 'DEM' + ENDOGENOUS_INTERTIE = 'EINT' + BOUNDARY_INTERTIE = 'BINT' + NONE = '' + +class Level(SortableEnum): + """ + Sector resolution levels for UI + """ + HIGH_RESOLUTION = 'HIGH' + LOW_RESOLUTION = 'LOW' + EXCLUDED = '-' + +######################################### +# UI constants +######################################### + +LOW_SCENARIOS: List[str] = [ + "Current Measures", + "Global Net Zero" +] +"""UI naming for low resolution scenarios""" + +DEFAULT_LOW: str = 'Current Measures' +"""Default low resolution scenario (UI name)""" + +TABLE_SECTORS: List[Sector] = sorted( + s.value for s in [ + Sector.COMMERCIAL, + Sector.ELECTRICITY, + Sector.INDUSTRY, + Sector.RESIDENTIAL, + Sector.TRANSPORTATION + ] +) +"""Sectors that are included in UI options matrix""" + +TABLE_REGIONS: List[Region] = sorted( + r.value for r in [ + Region.ALBERTA, + Region.BRITISH_COLUMBIA, + Region.MANITOBA, + Region.NEW_BRUNSWICK, + Region.NEWFOUNDLAND_AND_LABRADOR, + Region.NOVA_SCOTIA, + Region.ONTARIO, + Region.PRINCE_EDWARD_ISLAND, + Region.QUEBEC, + Region.SASKATCHEWAN + ] +) +"""Regions that are included in UI options matrix""" + +######################################### +# Database processing constants +######################################### + +INDEX_TABLES: Set[str] = { + 'commodity_type', 'operator', 'technology_type', 'time_period_type', + 'data_quality_credibility', 'data_quality_geography', + 'data_quality_structure', 'data_quality_technology', 'data_quality_time', + 'metadata', 'metadata_real' +} +"""SQLite tables that are handled by the schema and need not be transferred""" + +LTT_DEFAULT: int = 40 """Default lifetime for technologies in Temoa if not specified elsewhere""" \ No newline at end of file diff --git a/database_processing.py b/database_processing.py index 21515c3..092ef8d 100644 --- a/database_processing.py +++ b/database_processing.py @@ -1,431 +1,460 @@ -""" -CANOE UI database processing elements -By David Turnbull -""" - -import sqlite3 -from typing import Dict, Set, Tuple, Any -from log_setup import setup_logging -import os -import pandas as pd - -from constants import INDEX_TABLES, LTT_DEFAULT -from directories import SCHEMA_FILE - -# Get logger for this module -logger = setup_logging("database_processing") - -######################################### -# Helpers -######################################### - -def vers_to_str(v: int) -> str: - """ - Convert version integer to zero-padded string - """ - return '0'*(3-len(str(v))) + str(v) - -def snap5_max2045(year: int): - """ - Snap year to nearest prior 5-year period, max 2045 - """ - return min(2045, ((year-1) // 5) * 5) - -######################################### -# Initialisation -######################################### - -def collect_db_data_ids(db_path: str) -> Set[str]: - """ - Get available data IDs from the dataset - """ - ids: Set[str] = set() - try: - conn = sqlite3.connect(db_path) - cur = conn.cursor() - cur.execute("SELECT data_id FROM DataSet") - ids = {id[0][0:-3] for id in cur.fetchall()} - except Exception as e: - logger.exception("collect_db_data_ids failed for %s: %s", db_path, e) - raise RuntimeError(f"collect_db_data_ids failed for {db_path}: {e}") - return ids - -def collect_latest_id(db_path: str, base_id: str) -> str: - """ - Get latest versioned data ID from the dataset for a given base ID - """ - latest_id = "" - latest_version = -1 - try: - conn = sqlite3.connect(db_path) - cur = conn.cursor() - cur.execute("SELECT data_id FROM DataSet WHERE data_id LIKE ?", (f"{base_id}%",)) - for id in cur.fetchall(): - version = int(id[0][-3:]) - if version > latest_version: - latest_version = version - latest_id = id[0] - except Exception as e: - logger.exception("collect_latest_id failed for %s and base_id %s: %s", db_path, base_id, e) - raise RuntimeError(f"collect_latest_id failed for {db_path} and base_id {base_id}: {e}") - return latest_id - -def get_viable_data_ids( - input_filename: str, - desired_ids: Set[str] -) -> Set[str]: - """ - Get intersection of desired data IDs and those available in the input DB - """ - - available_ids = collect_db_data_ids(input_filename) - if not available_ids: - msg = "No data_id values found in the input database." - logger.error(msg) - raise RuntimeError(msg) - - if not desired_ids: - msg = "Got no selected data IDs to merge" - logger.error(msg) - raise RuntimeError(msg) - - good_ids = desired_ids.intersection(available_ids) - if not good_ids: - msg = "No selected data_id values found in the input database." - logger.error(msg) - raise RuntimeError(msg) - - return good_ids - -def get_latest_data_ids( - input_filename: str, - desired_ids: Set[str] - ) -> Set[str]: - """ - From a set of data IDs without versions, get the latest versioned IDs available in the input DB - """ - viable_ids = get_viable_data_ids(input_filename, desired_ids) - latest_ids = sorted(set( - collect_latest_id(input_filename, base_id) - for base_id in viable_ids - )) - logger.debug("Transferring the following data_IDs: %s", latest_ids) - return latest_ids - -def initialize_output_database(output_filename: str) -> Tuple[sqlite3.Connection, sqlite3.Cursor]: - """ - Create output database and initialize schema - """ - try: - if os.path.exists(output_filename): - os.remove(output_filename) - conn = sqlite3.connect(output_filename) - curs = conn.cursor() - with open(SCHEMA_FILE, 'r') as file: - curs.executescript(file.read()) - logger.info("Initialized output database schema: %s", output_filename) - return conn, curs - except Exception as e: - logger.exception("initialize_output_filename failed for %s: %s", output_filename, e) - raise RuntimeError(f"initialize_output_filename failed for {output_filename}: {e}") - -######################################### -# SQLite Aggregation -######################################### - -def aggregate_sqlite_files( - input_filename: str, - output_filename: str, - global_settings: Dict[str, Any], - desired_ids: Set[str], -) -> None: - """ - Order of operations: - 1) Get viable data IDs - 2) Initialise database connections - 3) Copy tables (filter by data_id where present) - 4) Final cleanup post_process - """ - - conn = None - curs = None - - try: - cmd: str = None # initialise for error logging if needed - - # 1) Get viable data IDs to transfer - data_ids = get_latest_data_ids(input_filename, desired_ids) - - # 2) Initialise database connections - conn, curs = initialize_output_database(output_filename) - conn.execute(f'ATTACH "{input_filename}" AS dataset') - conn.execute("PRAGMA foreign_keys = OFF;") - - # 3) Copy data table by table (data_id-filtered where present) - curs.execute('SELECT name FROM dataset.sqlite_master WHERE type="table";') - tables = {t[0] for t in curs.fetchall()} - tables -= INDEX_TABLES # exclude label/index-only tables handled by schema - tables = sorted(tables) - - logger.debug("Executing SQLite transfers:") - for t in tables: - - if not global_settings.get("is_processing", True): - conn.close() - return - - cols = [c[1] for c in curs.execute(f"PRAGMA dataset.table_info({t});")] - if 'data_id' in cols: - for data_id in data_ids: - - if not global_settings.get("is_processing", True): - conn.close() - return - - cmd = f"INSERT OR IGNORE INTO {t} SELECT * FROM dataset.{t} WHERE data_id == '{data_id}';" - curs.execute(cmd) - conn.commit() - else: - cmd = f"INSERT OR IGNORE INTO {t} SELECT * FROM dataset.{t};" - curs.execute(cmd) - conn.commit() - - # Get parent IDs all the way up as well - n = 0 # loop breaker - while n < 100: - n += 1 - new_parents = { - d[0] for d in curs.execute(( - "SELECT parent_id FROM DataSet " - "WHERE parent_id NOT IN " - "(SELECT data_id FROM DataSet);" - )).fetchall() - } - if len(new_parents) == 0: - break - for data_id in new_parents: - cmd = f"INSERT OR IGNORE INTO DataSet SELECT * FROM dataset.DataSet WHERE data_id == '{data_id}';" - curs.execute(cmd) - conn.commit() - - conn.execute("PRAGMA foreign_keys = ON;") - conn.execute('DETACH dataset') - conn.close() - - # 4) Final cleanup - post_process(output_filename = output_filename, global_settings = global_settings) - - logger.info("Aggregation complete. Output: %s", output_filename) - - except Exception as e: - logger.exception("Unhandled error during aggregation (input=%s output=%s): %s", input_filename, output_filename, e) - if cmd: - logger.debug("Last SQLite command: %s", cmd) - if conn: - conn.execute('DETACH dataset') - conn.close() - raise RuntimeError(f"Unhandled error during aggregation: {e}") - -######################################### -# Post-Aggregation Filter / Cleanup -######################################### - -def post_process( - output_filename: str, - global_settings: Dict[str, Any] - ) -> None: - """ - Removes supply-side orphans (region-tech combos that lead nowhere because - of excluded regions/sectors/resolutions or lifetime pruning). - """ - - MAX_ITERS = 20 - conn = None - - try: - conn = sqlite3.connect(output_filename) - curs = conn.cursor() - - curs.execute("PRAGMA foreign_keys = OFF;") - - # ---- Pass 1: Remove supply orphans by region (lifetime naive) ---- - for iter in range(MAX_ITERS): - - if not global_settings.get("is_processing", True): - conn.close() - return - - bad_rt = curs.execute( - """ - SELECT DISTINCT region, tech - FROM Efficiency - WHERE output_comm NOT IN (SELECT name FROM Commodity WHERE flag = 'd') - AND (region, output_comm) NOT IN (SELECT region, input_comm FROM Efficiency) - """ - ).fetchall() - if not bad_rt: - logger.debug( - "Lifetime-naive supply-side orphan removal complete after %d iterations.", - iter - ) - break - else: - logger.debug( - "Removing the following region-tech orphans: %s", - bad_rt - ) - - deleted_total = 0 - tables = [t[0] for t in curs.execute("SELECT name FROM sqlite_master WHERE type='table';").fetchall()] - for table in tables: - cols = [c[1] for c in curs.execute(f'PRAGMA table_info({table});')] - if 'region' in cols and 'tech' in cols: - for region, tech in bad_rt: - - if not global_settings.get("is_processing", True): - conn.close() - return - - try: - curs.execute(f"DELETE FROM {table} WHERE region = ? AND tech = ?", (region, tech)) - if curs.rowcount and curs.rowcount > 0: - deleted_total += curs.rowcount - except sqlite3.Error: - pass - - tech_remaining = {t[0] for t in curs.execute('SELECT DISTINCT tech FROM Efficiency').fetchall()} - tech_before = {t[0] for t in curs.execute('SELECT DISTINCT tech FROM Technology').fetchall()} - tech_gone = tech_before - tech_remaining - if tech_gone: - logger.debug( - "Removing the following orphan techs: %s", - tech_gone - ) - for table in tables: - cols = [c[1] for c in curs.execute(f'PRAGMA table_info({table});')] - if 'tech' in cols: - for tech in tech_gone: - - if not global_settings.get("is_processing", True): - conn.close() - return - - try: - curs.execute(f"DELETE FROM {table} WHERE tech = ?", (tech,)) - if curs.rowcount and curs.rowcount > 0: - deleted_total += curs.rowcount - except sqlite3.Error: - pass - - conn.commit() - if deleted_total == 0: - logger.debug( - "Lifetime-naive supply-side orphan removal complete after %d iterations.", - iter - ) - break - - # ---- Pass 2: Remove supply orphans due to lifetime pruning ---- - for iter in range(MAX_ITERS): - - if not global_settings.get("is_processing", True): - conn.close() - return - - time_all = [int(p[0]) for p in curs.execute('SELECT period FROM TimePeriod').fetchall()] - - lifetime_process: Dict[Tuple[str,str,int], int] = {} - - for r, t, v in curs.execute('SELECT region, tech, vintage FROM Efficiency').fetchall(): - lifetime_process[(r, t, int(v))] = LTT_DEFAULT - - for r, t, ltt in curs.execute('SELECT region, tech, lifetime FROM LifetimeTech').fetchall(): - for v in time_all: - lifetime_process[(r, t, int(v))] = int(ltt) - - for r, t, v, ltp in curs.execute('SELECT region, tech, vintage, lifetime FROM LifetimeProcess').fetchall(): - lifetime_process[(r, t, int(v))] = int(ltp) - - df_eff = pd.read_sql_query('SELECT * FROM Efficiency', conn) - df_eff['vintage'] = pd.to_numeric(df_eff['vintage'], errors='coerce').fillna(0).astype(int) - - df_eff['last_out'] = [ - snap5_max2045(v + int(lifetime_process[r, t, v])) - for r, t, v in df_eff[['region','tech','vintage']].itertuples(index=False, name=None) - ] - - df_last_in = df_eff.groupby(['region','input_comm'], as_index=True)['last_out'].max().rename('last_in') - df_eff = df_eff.merge(df_last_in, left_on=['region','output_comm'], right_index=True, how='left') - df_eff['last_in'] = pd.to_numeric(df_eff['last_in'], errors='coerce').fillna(0).astype(int) - - demand_comms = {c[0] for c in curs.execute("SELECT name FROM Commodity WHERE flag = 'd'").fetchall()} - df_eff = df_eff.loc[~df_eff['output_comm'].isin(demand_comms)].copy() - - df_remove = df_eff.loc[df_eff['last_in'] < df_eff['last_out']].copy() - ritvo_remove = list(df_remove[['region','input_comm','tech','vintage','output_comm']].itertuples(index=False, name=None)) - - if ritvo_remove: - logger.debug( - "Removing the following ritvo orphans: %s", - ritvo_remove - ) - - deleted_total = 0 - for region, input_comm, tech, vintage, output_comm in ritvo_remove: - - if not global_settings.get("is_processing", True): - conn.close() - return - - curs.execute( - """ - DELETE FROM Efficiency - WHERE region = ? AND input_comm = ? AND tech = ? - AND CAST(vintage AS INTEGER) = ? - AND output_comm = ? - """, (region, input_comm, tech, int(vintage), output_comm) - ) - if curs.rowcount and curs.rowcount > 0: deleted_total += curs.rowcount - for tbl in ("CostVariable", "CostFixed", "EmissionActivity"): - - if not global_settings.get("is_processing", True): - conn.close() - return - - curs.execute( - f"DELETE FROM {tbl} WHERE region = ? AND tech = ? AND CAST(vintage AS INTEGER) = ?", - (region, tech, int(vintage)) - ) - if curs.rowcount and curs.rowcount > 0: deleted_total += curs.rowcount - - conn.commit() - if deleted_total == 0: - logger.debug( - "Lifetime-aware supply-side orphan removal complete after %d iterations.", - iter - ) - break - - if not global_settings.get("is_processing", True): - conn.close() - return - - # Delete any unused commodities (techs already cleaned up) - curs.execute( - "DELETE FROM Commodity " - "WHERE flag != 'e' " - "AND name NOT IN (SELECT DISTINCT input_comm FROM Efficiency) " - "AND name NOT IN (SELECT DISTINCT output_comm FROM Efficiency)" - ) - conn.commit() - - curs.execute("PRAGMA foreign_keys = ON;") - - conn.commit() - conn.close() - - except Exception as e: - logger.exception("post processing failed for %s: %s", output_filename, e) - if conn: - conn.close() +""" +CANOE UI database processing elements +By David Turnbull +""" + +import sqlite3 +from typing import Dict, Set, Tuple, Any +from log_setup import setup_logging +import os +import pandas as pd + +from constants import INDEX_TABLES, LTT_DEFAULT +from directories import SCHEMA_FILE + +# Get logger for this module +logger = setup_logging("database_processing") + +######################################### +# Helpers +######################################### + +def vers_to_str(v: int) -> str: + """ + Convert version integer to zero-padded string + """ + return '0'*(3-len(str(v))) + str(v) + +def snap5_max2045(year: int): + """ + Snap year to nearest prior 5-year period, max 2045 + """ + return min(2045, ((year-1) // 5) * 5) + +######################################### +# Initialisation +######################################### + +def collect_db_data_ids(db_path: str) -> Set[str]: + """ + Get available data IDs from the dataset + """ + ids: Set[str] = set() + try: + conn = sqlite3.connect(db_path) + cur = conn.cursor() + cur.execute("SELECT data_id FROM data_set") + ids = {id[0][0:-3] for id in cur.fetchall()} + except Exception as e: + logger.exception("collect_db_data_ids failed for %s: %s", db_path, e) + raise RuntimeError(f"collect_db_data_ids failed for {db_path}: {e}") + return ids + +def collect_latest_id(db_path: str, base_id: str) -> str: + """ + Get latest versioned data ID from the dataset for a given base ID + """ + latest_id = "" + latest_version = -1 + try: + conn = sqlite3.connect(db_path) + cur = conn.cursor() + cur.execute("SELECT data_id FROM data_set WHERE data_id LIKE ?", (f"{base_id}%",)) + for id in cur.fetchall(): + version = int(id[0][-3:]) + if version > latest_version: + latest_version = version + latest_id = id[0] + except Exception as e: + logger.exception("collect_latest_id failed for %s and base_id %s: %s", db_path, base_id, e) + raise RuntimeError(f"collect_latest_id failed for {db_path} and base_id {base_id}: {e}") + return latest_id + +def get_viable_data_ids( + input_filename: str, + desired_ids: Set[str] +) -> Set[str]: + """ + Get intersection of desired data IDs and those available in the input DB + """ + + available_ids = collect_db_data_ids(input_filename) + if not available_ids: + msg = "No data_id values found in the input database." + logger.error(msg) + raise RuntimeError(msg) + + if not desired_ids: + msg = "Got no selected data IDs to merge" + logger.error(msg) + raise RuntimeError(msg) + + good_ids = desired_ids.intersection(available_ids) + if not good_ids: + msg = "No selected data_id values found in the input database." + logger.error(msg) + raise RuntimeError(msg) + + return good_ids + +def get_latest_data_ids( + input_filename: str, + desired_ids: Set[str] + ) -> Set[str]: + """ + From a set of data IDs without versions, get the latest versioned IDs available in the input DB + """ + viable_ids = get_viable_data_ids(input_filename, desired_ids) + def data_id_priority(data_id: str) -> tuple: + """ + Define insertion priority for CANOE data sets. + Lower numbers are inserted first and therefore take precedence + when INSERT OR IGNORE encounters duplicate primary keys. + """ + priorities = { + "ELC": 1, + "IND": 2, + "COM": 3, + "RES": 4, + "TRP": 5, + "AGRI": 6, + "FUEL": 7, + } + + for prefix, priority in priorities.items(): + if data_id.startswith(prefix): + return priority, data_id + + return 999, data_id + + latest_ids = sorted( + set( + collect_latest_id(input_filename, base_id) + for base_id in viable_ids + ), + key=data_id_priority + ) + logger.debug("Transferring the following data_IDs: %s", latest_ids) + return latest_ids + +def initialize_output_database(output_filename: str) -> Tuple[sqlite3.Connection, sqlite3.Cursor]: + """ + Create output database and initialize schema + """ + try: + if os.path.exists(output_filename): + os.remove(output_filename) + conn = sqlite3.connect(output_filename) + curs = conn.cursor() + with open(SCHEMA_FILE, 'r') as file: + curs.executescript(file.read()) + logger.info("Initialized output database schema: %s", output_filename) + return conn, curs + except Exception as e: + logger.exception("initialize_output_filename failed for %s: %s", output_filename, e) + raise RuntimeError(f"initialize_output_filename failed for {output_filename}: {e}") + +######################################### +# SQLite Aggregation +######################################### + +def aggregate_sqlite_files( + input_filename: str, + output_filename: str, + global_settings: Dict[str, Any], + desired_ids: Set[str], +) -> None: + """ + Order of operations: + 1) Get viable data IDs + 2) Initialise database connections + 3) Copy tables (filter by data_id where present) + 4) Final cleanup post_process + """ + + conn = None + curs = None + + try: + cmd: str = None # initialise for error logging if needed + + # 1) Get viable data IDs to transfer + data_ids = get_latest_data_ids(input_filename, desired_ids) + + # 2) Initialise database connections + conn, curs = initialize_output_database(output_filename) + conn.execute(f'ATTACH "{input_filename}" AS dataset') + conn.execute("PRAGMA foreign_keys = OFF;") + + # 3) Copy data table by table (data_id-filtered where present) + curs.execute('SELECT name FROM dataset.sqlite_master WHERE type="table";') + tables = {t[0] for t in curs.fetchall()} + tables -= INDEX_TABLES # exclude label/index-only tables handled by schema + tables = sorted(tables) + + logger.debug("Executing SQLite transfers:") + for t in tables: + + if not global_settings.get("is_processing", True): + conn.close() + return + + cols = [c[1] for c in curs.execute(f"PRAGMA dataset.table_info({t});")] + if 'data_id' in cols: + for data_id in data_ids: + + if not global_settings.get("is_processing", True): + conn.close() + return + + cmd = f"INSERT OR IGNORE INTO {t} SELECT * FROM dataset.{t} WHERE data_id == '{data_id}';" + curs.execute(cmd) + conn.commit() + else: + cmd = f"INSERT OR IGNORE INTO {t} SELECT * FROM dataset.{t};" + curs.execute(cmd) + conn.commit() + + # Get parent IDs all the way up as well + n = 0 # loop breaker + while n < 100: + n += 1 + new_parents = { + d[0] for d in curs.execute(( + "SELECT parent_id FROM data_set " + "WHERE parent_id NOT IN " + "(SELECT data_id FROM data_set);" + )).fetchall() if d[0] is not None + } + if len(new_parents) == 0: + break + for data_id in new_parents: + cmd = f"INSERT OR IGNORE INTO data_set SELECT * FROM dataset.data_set WHERE data_id == '{data_id}';" + curs.execute(cmd) + conn.commit() + + conn.execute("PRAGMA foreign_keys = ON;") + conn.execute('DETACH dataset') + conn.close() + + # 4) Final cleanup + post_process(output_filename = output_filename, global_settings = global_settings) + + logger.info("Aggregation complete. Output: %s", output_filename) + + except Exception as e: + logger.exception("Unhandled error during aggregation (input=%s output=%s): %s", input_filename, output_filename, e) + if cmd: + logger.debug("Last SQLite command: %s", cmd) + if conn: + conn.execute('DETACH dataset') + conn.close() + raise RuntimeError(f"Unhandled error during aggregation: {e}") + +######################################### +# Post-Aggregation Filter / Cleanup +######################################### + +def post_process( + output_filename: str, + global_settings: Dict[str, Any] + ) -> None: + """ + Removes supply-side orphans (region-tech combos that lead nowhere because + of excluded regions/sectors/resolutions or lifetime pruning). + """ + + MAX_ITERS = 20 + conn = None + + try: + conn = sqlite3.connect(output_filename) + curs = conn.cursor() + + curs.execute("PRAGMA foreign_keys = OFF;") + + # ---- Pass 1: Remove supply orphans by region (lifetime naive) ---- + for iter in range(MAX_ITERS): + + if not global_settings.get("is_processing", True): + conn.close() + return + + bad_rt = curs.execute( + """ + SELECT DISTINCT region, tech + FROM efficiency + WHERE output_comm NOT IN ( + SELECT name FROM commodity WHERE flag = 'd' + ) + AND (region, output_comm) NOT IN ( + SELECT region, input_comm FROM efficiency + ) + """ + ).fetchall() + if not bad_rt: + logger.debug( + "Lifetime-naive supply-side orphan removal complete after %d iterations.", + iter + ) + break + else: + logger.debug( + "Removing the following region-tech orphans: %s", + bad_rt + ) + + deleted_total = 0 + tables = [t[0] for t in curs.execute("SELECT name FROM sqlite_master WHERE type='table';").fetchall()] + for table in tables: + cols = [c[1] for c in curs.execute(f'PRAGMA table_info({table});')] + if 'region' in cols and 'tech' in cols: + for region, tech in bad_rt: + + if not global_settings.get("is_processing", True): + conn.close() + return + + try: + curs.execute(f"DELETE FROM {table} WHERE region = ? AND tech = ?", (region, tech)) + if curs.rowcount and curs.rowcount > 0: + deleted_total += curs.rowcount + except sqlite3.Error: + pass + + tech_remaining = {t[0] for t in curs.execute('SELECT DISTINCT tech FROM efficiency').fetchall()} + tech_before = {t[0] for t in curs.execute('SELECT DISTINCT tech FROM technology').fetchall()} + tech_gone = tech_before - tech_remaining + if tech_gone: + logger.debug( + "Removing the following orphan techs: %s", + tech_gone + ) + for table in tables: + cols = [c[1] for c in curs.execute(f'PRAGMA table_info({table});')] + if 'tech' in cols: + for tech in tech_gone: + + if not global_settings.get("is_processing", True): + conn.close() + return + + try: + curs.execute(f"DELETE FROM {table} WHERE tech = ?", (tech,)) + if curs.rowcount and curs.rowcount > 0: + deleted_total += curs.rowcount + except sqlite3.Error: + pass + + conn.commit() + if deleted_total == 0: + logger.debug( + "Lifetime-naive supply-side orphan removal complete after %d iterations.", + iter + ) + break + + # ---- Pass 2: Remove supply orphans due to lifetime pruning ---- + for iter in range(MAX_ITERS): + + if not global_settings.get("is_processing", True): + conn.close() + return + + time_all = [int(p[0]) for p in curs.execute('SELECT period FROM time_period').fetchall()] + + lifetime_process: Dict[Tuple[str,str,int], int] = {} + + for r, t, v in curs.execute('SELECT region, tech, vintage FROM efficiency').fetchall(): + lifetime_process[(r, t, int(v))] = LTT_DEFAULT + + for r, t, ltt in curs.execute('SELECT region, tech, lifetime FROM lifetime_tech').fetchall(): + for v in time_all: + lifetime_process[(r, t, int(v))] = int(ltt) + + for r, t, v, ltp in curs.execute('SELECT region, tech, vintage, lifetime FROM lifetime_process').fetchall(): + lifetime_process[(r, t, int(v))] = int(ltp) + + df_eff = pd.read_sql_query('SELECT * FROM efficiency', conn) + df_eff['vintage'] = pd.to_numeric(df_eff['vintage'], errors='coerce').fillna(0).astype(int) + + df_eff['last_out'] = [ + snap5_max2045(v + int(lifetime_process.get((r, t, v), LTT_DEFAULT))) + for r, t, v in df_eff[['region','tech','vintage']].itertuples(index=False, name=None) + ] + + df_last_in = df_eff.groupby(['region','input_comm'], as_index=True)['last_out'].max().rename('last_in') + df_eff = df_eff.merge(df_last_in, left_on=['region','output_comm'], right_index=True, how='left') + df_eff['last_in'] = pd.to_numeric(df_eff['last_in'], errors='coerce').fillna(0).astype(int) + + demand_comms = {c[0] for c in curs.execute("SELECT name FROM commodity WHERE flag = 'd'").fetchall()} + df_eff = df_eff.loc[~df_eff['output_comm'].isin(demand_comms)].copy() + + df_remove = df_eff.loc[df_eff['last_in'] < df_eff['last_out']].copy() + ritvo_remove = list(df_remove[['region','input_comm','tech','vintage','output_comm']].itertuples(index=False, name=None)) + + if ritvo_remove: + logger.debug( + "Removing the following ritvo orphans: %s", + ritvo_remove + ) + + deleted_total = 0 + for region, input_comm, tech, vintage, output_comm in ritvo_remove: + + if not global_settings.get("is_processing", True): + conn.close() + return + + curs.execute( + """ + DELETE FROM efficiency + WHERE region = ? AND input_comm = ? AND tech = ? + AND CAST(vintage AS INTEGER) = ? + AND output_comm = ? + """, (region, input_comm, tech, int(vintage), output_comm) + ) + if curs.rowcount and curs.rowcount > 0: deleted_total += curs.rowcount + for tbl in ("cost_variable", "cost_fixed", "emission_activity"): + + if not global_settings.get("is_processing", True): + conn.close() + return + + curs.execute( + f"DELETE FROM {tbl} WHERE region = ? AND tech = ? AND CAST(vintage AS INTEGER) = ?", + (region, tech, int(vintage)) + ) + if curs.rowcount and curs.rowcount > 0: deleted_total += curs.rowcount + + conn.commit() + if deleted_total == 0: + logger.debug( + "Lifetime-aware supply-side orphan removal complete after %d iterations.", + iter + ) + break + + if not global_settings.get("is_processing", True): + conn.close() + return + + # Delete any unused commodities (techs already cleaned up) + curs.execute( + "DELETE FROM commodity " + "WHERE flag != 'e' " + "AND name NOT IN (SELECT DISTINCT input_comm FROM efficiency) " + "AND name NOT IN (SELECT DISTINCT output_comm FROM efficiency)" + ) + conn.commit() + + curs.execute("PRAGMA foreign_keys = ON;") + + conn.commit() + conn.close() + + except Exception as e: + logger.exception("post processing failed for %s: %s", output_filename, e) + if conn: + conn.close() raise RuntimeError(f"post processing failed for {output_filename}: {e}") \ No newline at end of file diff --git a/log_setup.py b/log_setup.py index a63e638..b856230 100644 --- a/log_setup.py +++ b/log_setup.py @@ -3,44 +3,76 @@ """ import os -from datetime import datetime +import sys import logging + +from datetime import datetime from logging.handlers import RotatingFileHandler from directories import LOG_DIR + def setup_logging(name: str = "canoe_app") -> logging.Logger: """ Creates or returns a logger with consistent configuration. + Args: name: The logger name (defaults to "canoe_app") + Returns: A configured logger instance """ - # Get or create logger + logger = logging.getLogger(name) - - # Only add handlers if none exist (prevents duplicate handlers) + + # Only add handlers if none exist if not logger.handlers: logger.setLevel(logging.DEBUG) # Build logfile name with current datetime - timestamp = datetime.now().strftime("%Y-%m-%d_%H-%M-%S") - log_file = os.path.join(LOG_DIR, f"canoe_app_{timestamp}.log") + timestamp = datetime.now().strftime( + "%Y-%m-%d_%H-%M-%S" + ) + + log_file = os.path.join( + LOG_DIR, + f"canoe_app_{timestamp}.log" + ) + + # File handler + fh = RotatingFileHandler( + log_file, + maxBytes=5 * 1024 * 1024, + backupCount=3, + encoding="utf-8", + ) - # Rotating file handler - fh = RotatingFileHandler(log_file, maxBytes=5 * 1024 * 1024, backupCount=3, encoding="utf-8") fh.setLevel(logging.DEBUG) - fh_formatter = logging.Formatter("%(asctime)s %(levelname)s %(name)s %(module)s:%(lineno)d - %(message)s") + + fh_formatter = logging.Formatter( + "%(asctime)s %(levelname)s %(name)s " + "%(module)s:%(lineno)d - %(message)s" + ) + fh.setFormatter(fh_formatter) logger.addHandler(fh) # Console handler - ch = logging.StreamHandler() - ch.setLevel(logging.INFO) - ch_formatter = logging.Formatter("%(asctime)s %(levelname)s - %(message)s", "%H:%M:%S") - ch.setFormatter(ch_formatter) - logger.addHandler(ch) + # + # PyInstaller console=False sets sys.stderr to None + # on Windows, so only create this handler when a + # console stream actually exists. + if sys.stderr is not None: + ch = logging.StreamHandler(sys.stderr) + ch.setLevel(logging.INFO) + + ch_formatter = logging.Formatter( + "%(asctime)s %(levelname)s - %(message)s", + "%H:%M:%S", + ) + + ch.setFormatter(ch_formatter) + logger.addHandler(ch) # Avoid duplicate logs logger.propagate = False diff --git a/main.py b/main.py index da9f43c..6bd7c55 100644 --- a/main.py +++ b/main.py @@ -1,654 +1,1068 @@ -# -*- coding: utf-8 -*- -""" -CANOE UI Script -By David Turnbull -""" - -from __future__ import annotations - -import subprocess -import json -import os -import sys -import atexit -from typing import Any, Dict, Set, Tuple -import flet as ft -from time import sleep -from itertools import product -from log_setup import setup_logging -import database_processing as dbp - -from constants import ( - Region, - Sector, - Variant, - Feature, - Level, - LOW_SCENARIOS, - DEFAULT_LOW, - TABLE_REGIONS, - TABLE_SECTORS, -) -from directories import CONFIG_FILE, ASSETS_DIR - -# Get logger for this module -logger = setup_logging("main") - -######################################### -# Helpers -######################################### - -# SECTVARR1R2 -def make_id( - sector: Sector, - variant: Variant, - subvariant: Feature, - region_1: Region, - region_2: Region = Region.NONE, -) -> str: - return f"{sector.value}{variant.value}{subvariant.value}{region_1.value}{region_2.value}" - -######################################### -# Initialisation -######################################### - -# New: lightweight config loader (returns dict) -def load_config() -> Dict: - try: - if os.path.exists(CONFIG_FILE): - with open(CONFIG_FILE, "r", encoding="utf-8") as fh: - cfg = json.load(fh) - logger.debug("Loaded config from %s", CONFIG_FILE) - return cfg - except Exception as e: - logger.exception("Failed to load config %s: %s", CONFIG_FILE, e) - raise RuntimeError(f"Failed to load config: {e}") - return {} - -######################################### -# Desired IDs Builder -######################################### - -def rs_active( - matrix: Dict[Tuple[str, str], ft.Dropdown], - r: str, - s: str -) -> bool: - if all(( - dd := matrix.get((r, s)), - not dd.disabled, - str(dd.value) != Level.EXCLUDED.value - )): - return dd - else: - return False - -def get_matrix_selection( - matrix: Dict[Tuple[str, str], ft.Dropdown], - global_settings: Dict[str, Any], -) -> Set[Sector, Variant, Feature, Region, Region]: - """ - 1. Get the active region-sector combos and their generic (non-regional) variant - 2. If only electricity in a region, add grid demand - 3. Add endogenous and boundary interties based on selected regions - 4. Add fuels for all active regions - 5. Add agriculture for active regions where anything but electricity is present - """ - - # Get the low-res scenario - low_scenario = global_settings.get("low_scenario", DEFAULT_LOW) - - selections: Set[Sector, Variant, Feature, Region, Region] = set() - regions: Set[Region] = set() - for r in TABLE_REGIONS: - for s in TABLE_SECTORS: - if not (dd := rs_active(matrix, r, s)): - continue - - if str(dd.value) == Level.HIGH_RESOLUTION.value: - v = Variant.HIGH_RESOLUTION - elif low_scenario == "Current Measures": - v = Variant.CURRENT_MEASURES - else: - v = Variant.NET_ZERO - - regions.add(Region(r)) - - # Add variant-region data and variant-generic (no region) data - selections.add(( - Sector(s), - v, - Feature.NONE, - Region(r), - Region.NONE, - )) - selections.add(( - Sector(s), - v, - Feature.NONE, - Region.NONE, - Region.NONE, - )) - - # Special case: if only Elc is active for a region, add electricity demand - if s == Sector.ELECTRICITY.value and not any(( - rs_active(matrix, r, _s) for _s in TABLE_SECTORS if _s != s - )): - selections.add(( - Sector.ELECTRICITY, - v, - Feature.DEMAND, - Region(r), - Region.NONE, - )) - - # Add agriculture if any sector other than electricity active in this region - if any(( - rs_active(matrix, r, _s) - for _s in TABLE_SECTORS if _s != Sector.ELECTRICITY.value - )): - # Generic non-regional components - selections.add(( - Sector.AGRICULTURE, - Variant.HIGH_RESOLUTION, - Feature.NONE, - Region.NONE, - Region.NONE - )) - # Regional components - selections.add(( - Sector.AGRICULTURE, - Variant.HIGH_RESOLUTION, - Feature.NONE, - Region(r), - Region.NONE - )) - - # Endogenous intertie only if both regions selected - region_combos = { - tuple(sorted((r1, r2))) - for r1 in regions - for r2 in regions if r1 != r2 - } - for r1, r2 in region_combos: - selections.add(( - Sector.ELECTRICITY, - Variant.HIGH_RESOLUTION, - Feature.ENDOGENOUS_INTERTIE, - r1, - r2, - )) - - # Boundary intertie only if origin region selected and dest not selected - region_combos = { - (r1, r2) - for r1 in regions - for r2 in Region if r1 != r2 - } - for r1, r2 in region_combos: - if r2 not in regions: - selections.add(( - Sector.ELECTRICITY, - Variant.HIGH_RESOLUTION, - Feature.BOUNDARY_INTERTIE, - r1, - r2, - )) - - # Fuels generic non-regional components always - selections.add(( - Sector.FUEL, - Variant.HIGH_RESOLUTION, - Feature.NONE, - Region.NONE, - Region.NONE - )) - # Fuels for all active regions - for r in regions: - selections.add(( - Sector.FUEL, - Variant.HIGH_RESOLUTION, - Feature.NONE, - r, - Region.NONE - )) - - logger.debug('Selections for aggregation:') - desired_ids: Set[str] = set() - for sector, variant, subvariant, region_1, region_2 in sorted(selections): - logger.debug( - "Sector=%s Variant=%s SubVariant=%s Region1=%s Region2=%s", - sector.value, variant.value, subvariant.value, region_1.value, region_2.value - ) - desired_ids.add( - make_id( - sector, - variant, - subvariant, - region_1, - region_2 - ) - ) - - return desired_ids - - -def infer_selected_regions_from_matrix(matrix: Dict[Tuple[str, str], ft.Dropdown]) -> Set[str]: - """Regions that have any sector set to something other than 'NA'.""" - picked: Set[str] = set() - for r in TABLE_REGIONS: - if any( - (dd := matrix.get((r, s))) is not None and str(dd.value).upper() != Level.EXCLUDED.value - for s in TABLE_SECTORS - ): - picked.add(r) - return picked - -######################################### -# Flet UI -######################################### - -def main(page: ft.Page) -> None: - page.title = "CANOE UI" - page.vertical_alignment = ft.CrossAxisAlignment.START - page.horizontal_alignment = ft.CrossAxisAlignment.CENTER - if sys.platform != "darwin": - icon_path = os.path.join(os.path.dirname(__file__), "assets", "icon.ico") - page.window.icon = icon_path - page.window_width = 1200 - page.window_height = 700 - - # UI storage - matrix: Dict[Tuple[str, str], ft.Dropdown] = {} - - # Global flags - global_settings = { - "low_scenario": DEFAULT_LOW, - "power_system_model": False, - "is_processing": False - } - - # Stop everything if window closed - def on_window_event(e: ft.WindowEvent): - if ( - getattr(e, "type", None) == "close_request" - or getattr(e, "data", None) in ("close", "close_request") - ): - status_text.value = "Exiting..." - page.update() - sleep(0.05) - if global_settings['is_processing']: - logger.info("Processing cancelled due to window close") - global_settings['is_processing'] = False - page.window.destroy() - - page.window.prevent_close = True - page.window.on_event = on_window_event - - # Widgets - status_text = ft.Text("") - in_filename_text_field = ft.TextField(label="Input file path (e.g. dataset.sqlite)", value="", width=260) - out_filename_text_field = ft.TextField(label="Output file path (e.g. canoe.sqlite)", value="", width=260) - - # Scenario Dropdown - scenario_dropdown = ft.Dropdown( - label="Low-level Scenario", - options=[ - ft.dropdown.Option(scen) - for scen in LOW_SCENARIOS - ], - value=DEFAULT_LOW, # Default - width=200, - ) - - # RE-ADDED: Power System Checkbox - power_system_checkbox = ft.Checkbox(label="Power system model", value=False) - - image = ft.Container( - content=ft.Image( - src=os.path.join("assets", "logo.png"), - height=50, - width=60 - ), - alignment=ft.alignment.top_right - ) - - # load saved config (will be applied once UI elements are created) - saved_cfg = load_config() - - def save_config() -> None: - """Persist current UI state to CONFIG_FILE (JSON).""" - try: - cfg = { - "input_filename": os.path.normpath( - (in_filename_text_field.value or "").strip().strip("'").strip('"') - ), - "output_filename": os.path.normpath( - (out_filename_text_field.value or "").strip().strip("'").strip('"') - ), - "low_scenario": (scenario_dropdown.value or DEFAULT_LOW), - "power_system_model": bool(power_system_checkbox.value), # RE-ADDED - "matrix": { - f"{r}|{s}": ( - matrix[(r, s)].value - if (r, s) in matrix and matrix[(r, s)] is not None - else None - ) - for (r, s) in matrix.keys() - }, - } - os.makedirs(os.path.dirname(CONFIG_FILE), exist_ok=True) - with open(CONFIG_FILE, "w", encoding="utf-8") as fh: - json.dump(cfg, fh, indent=2, ensure_ascii=False) - logger.debug("Saved config to %s", CONFIG_FILE) - except Exception as e: - logger.exception("Failed to save config %s: %s", CONFIG_FILE, e) - raise RuntimeError(f"Failed to save config: {e}") - - # --- UI builders / updaters --- - - def on_sector_dropdown_change(e: ft.ControlEvent) -> None: - """Auto-fill sensible defaults when user selects a sector (normal mode).""" - r, s = e.control.data - is_na_selected = (e.control.value == Level.EXCLUDED.value) - - sleep(0.05) # slight delay to allow UI update - - # RE-ADDED: Do not auto-fill if in power system mode - if not global_settings["power_system_model"]: - if is_na_selected: - if s == Sector.ELECTRICITY.value: - for _s in TABLE_SECTORS: - if _s == s: continue - dd = matrix.get((r, _s)) - if not dd: - continue - dd.value = Level.EXCLUDED.value - else: - # if demand is active in this region cant have an inactive demand sector - row_is_active = any( - (matrix.get((r, _s)) - and matrix[(r, _s)].value != Level.EXCLUDED.value) - for _s in TABLE_SECTORS if _s != Sector.ELECTRICITY.value - ) - if row_is_active: - e.control.value = Level.LOW_RESOLUTION.value - e.control.update() - elif s != Sector.ELECTRICITY.value: - # If any sector other than elc activated, all must be active. Default to low-res - for _s in TABLE_SECTORS: - if _s == s: continue - dd = matrix.get((r, _s)) - if not dd: - continue - - if _s != Sector.ELECTRICITY.value and dd.value == Level.EXCLUDED.value: - dd.value = e.control.value - elif _s == Sector.ELECTRICITY.value and dd.value == Level.EXCLUDED.value: - dd.value = Level.HIGH_RESOLUTION.value - - # persist change - save_config() - page.update() - - def update_ui_matrix() -> None: - """Rebuild the matrix rows.""" - - for region, sector in product(TABLE_REGIONS, TABLE_SECTORS): - - dd = matrix.get((region, sector)) - if not dd: - continue - - # RE-ADDED: Enforce power-system rule AFTER loading saved value - try: - if global_settings.get("power_system_model", False) and sector != Sector.ELECTRICITY.value: - dd.disabled = True - else: - dd.disabled = False - except Exception as e: - logger.exception("Failed enforcing power-system rule for %s|%s: %s", region, sector, e) - raise RuntimeError(f"Failed enforcing power-system rule for {region}|{sector}: {e}") - - page.update() - save_config() - - def reset_matrix(e: ft.ControlEvent | None = None) -> None: - """Hard reset: reset all settings, set all cells to 'NA', re-enable controls, - clear status text, and overwrite the saved config.""" - - # 1) Reset global flags / controls - global_settings["low_scenario"] = DEFAULT_LOW - global_settings["power_system_model"] = False # RE-ADDED - scenario_dropdown.value = DEFAULT_LOW - power_system_checkbox.value = False # RE-ADDED - - # 2) Reset all dropdowns in the current matrix - for (r, s), dd in matrix.items(): - dd.disabled = False - dd.value = Level.EXCLUDED.value - - # 3) Clear any status message - status_text.value = "" - - # 4) Rebuild UI and re-apply disabling logic (PSM is off, so all enabled) - update_ui_matrix() - save_config() - - # 5) Final paint - try: - page.update() - except Exception: - pass - - # --- Settings events --- - def on_scenario_change(e: ft.ControlEvent) -> None: - """Handle change for the scenario dropdown.""" - global_settings["low_scenario"] = str(e.control.value) - save_config() - - scenario_dropdown.on_change = on_scenario_change - - # RE-ADDED: Handler for power system checkbox - def on_power_system_change(e: ft.ControlEvent) -> None: - global_settings["power_system_model"] = bool(e.control.value) - update_ui_matrix() - save_config() - - power_system_checkbox.on_change = on_power_system_change - - # --- Submit / run aggregation --- - - # attach saving to text field changes - in_filename_text_field.on_change = lambda e: save_config - out_filename_text_field.on_change = lambda e: save_config - - def on_submit(e: ft.ControlEvent) -> None: - - if global_settings["is_processing"]: - # Cancel button action - global_settings["is_processing"] = False - logger.info("Processing cancelled by user") - submit_button.text = "Submit" - status_text.value = "Processing cancelled." - page.update() - return - - global_settings["is_processing"] = True - submit_button.text = "Cancel" - status_text.value = "Processing..." - page.update() - - input_filename = in_filename_text_field.value.strip().strip("'").strip('"') - if not input_filename: - status_text.value = "Error: Filename cannot be empty." - page.update() - return - - output_filename = out_filename_text_field.value.strip().strip("'").strip('"') - if not output_filename: - status_text.value = "Error: Filename cannot be empty." - page.update() - return - - try: - # persist current config before running - save_config() - desired_ids = get_matrix_selection(matrix, global_settings) - # Send to processing module - dbp.aggregate_sqlite_files( - input_filename = input_filename, - output_filename = output_filename, - global_settings = global_settings, - desired_ids = desired_ids, - ) - if global_settings.get("is_processing", True): - status_text.value = f"Aggregation complete. Output: {output_filename}" - logger.info("Aggregation finished successfully (input=%s output=%s)", input_filename, output_filename) - except Exception as ex: - logger.exception("Aggregation failed (input=%s output=%s): %s", input_filename, output_filename, ex) - status_text.value = f"Error processing database. Check log file." - finally: - # Reset processing state - global_settings["is_processing"] = False - submit_button.text = "Submit" - page.update() - - page.update() - - - # --- Build initial matrix UI (all regions from the start) --- - header_row = [ft.Text("Region/Sector", weight=ft.FontWeight.BOLD, width=120)] + [ - ft.Text(s, weight=ft.FontWeight.BOLD, text_align=ft.TextAlign.CENTER, width=100) for s in TABLE_SECTORS - ] - matrix_rows = [ft.Row(header_row, alignment=ft.MainAxisAlignment.CENTER)] - - for region in TABLE_REGIONS: - row_elements = [ft.Text(region, weight=ft.FontWeight.BOLD, width=120)] - for sector in TABLE_SECTORS: - - # Update matrix values - key = f"{region}|{sector}" - val = Level.EXCLUDED.value - if saved_cfg and saved_cfg.get("matrix") and key in saved_cfg["matrix"]: - try: - val = saved_cfg["matrix"].get(key) - if val is None: - val = Level.EXCLUDED.value - except Exception as e: - logger.exception("Failed applying saved value for %s|%s: %s", region, sector, e) - raise RuntimeError(f"Failed applying saved value for {region}|{sector}: {e}") - - if sector == Sector.ELECTRICITY.value: - level_options = [ - Level.HIGH_RESOLUTION, - Level.EXCLUDED - ] - else: - level_options = Level - # All sectors use same options - dd = ft.Dropdown( - options=[ft.dropdown.Option(l.value) for l in level_options], - value=val, - width=100, - content_padding=ft.padding.only(left=5, right=5), - disabled=False, - ) - matrix[(region, sector)] = dd - row_elements.append(dd) - dd.data = (region, sector) - dd.on_change = on_sector_dropdown_change - matrix_rows.append(ft.Row(row_elements, alignment=ft.MainAxisAlignment.CENTER)) - - # Apply saved text inputs / controls if present - try: - if saved_cfg: - in_filename_text_field.value = saved_cfg.get("input_filename", in_filename_text_field.value) - out_filename_text_field.value = saved_cfg.get("output_filename", out_filename_text_field.value) - - # Apply saved scenario - scenario_saved = saved_cfg.get("low_scenario", scenario_dropdown.value) - scenario_dropdown.value = scenario_saved - global_settings["low_scenario"] = scenario_saved - - # Apply saved PSM checkbox - psm_saved = bool(saved_cfg.get("power_system_model", power_system_checkbox.value)) - power_system_checkbox.value = psm_saved - global_settings["power_system_model"] = psm_saved - - except Exception: - logger.exception("Failed applying saved configuration on load") - pass - - # Controls - reset_button = ft.ElevatedButton("Reset Matrix", on_click=reset_matrix, width=200, height=40) - submit_button = ft.ElevatedButton("Submit", on_click=on_submit, width=80, height=40) - - # Settings column - settings_column = ft.Column( - [ - ft.Text("Aggregation Settings", size=18, weight=ft.FontWeight.BOLD), - ft.Divider(), - scenario_dropdown, - power_system_checkbox, # RE-ADDED - ft.Divider(), - reset_button, - ], - alignment=ft.MainAxisAlignment.START, - horizontal_alignment=ft.CrossAxisAlignment.START, - spacing=10, - width=300, - ) - - # Main content layout (structure/spacing preserved) - middle_row = ft.Row( - [ - ft.Column( - matrix_rows, - expand=True, # take remaining width in the row - scroll=ft.ScrollMode.ADAPTIVE, # or ALWAYS - # remove fixed height here - horizontal_alignment=ft.CrossAxisAlignment.START, - ), - ft.VerticalDivider(), - settings_column, # give this a fixed width internally if needed - ], - expand=True, # <-- this row grows vertically to fill space - alignment=ft.MainAxisAlignment.CENTER, - vertical_alignment=ft.CrossAxisAlignment.START, - ) - - footer = ft.Container( - height=50, # <-- fixed footer height - content=ft.Row( - [in_filename_text_field, out_filename_text_field, submit_button, status_text], - alignment=ft.MainAxisAlignment.CENTER, - spacing=30, - ), - alignment=ft.alignment.center, - ) - - main_content = ft.Column( - [ - image, - ft.Text("CANOE RSS Selector", size=24, weight=ft.FontWeight.BOLD), - ft.Text("Read accompanying document for details about choices and instructions", size=18), - ft.Divider(), - middle_row, # expands - ft.Divider(), - footer, # fixed height - ], - expand=True, # <-- make the whole layout fill the window - alignment=ft.MainAxisAlignment.START, - horizontal_alignment=ft.CrossAxisAlignment.CENTER, - spacing=10, - ) - - page.add(main_content) - page.update() - - # Build matrix from saved state first, then enforce disabling rules - update_ui_matrix() - -if __name__ == "__main__": +# -*- coding: utf-8 -*- +""" +CANOE UI Script +By David Turnbull +""" + +from __future__ import annotations + +import matplotlib +matplotlib.use('Agg') + +from representative_periods import clustering as rep_clustering +from representative_periods import process_all as rep_process_all +from representative_periods import utils as rep_utils +import json +import os +import sys +import atexit +import shutil +import glob +import yaml +import threading +from typing import Any, Dict, Set, Tuple +import flet as ft +from time import sleep +from itertools import product +from log_setup import setup_logging +import database_processing as dbp + +from constants import ( + Region, + Sector, + Variant, + Feature, + Level, + LOW_SCENARIOS, + DEFAULT_LOW, + TABLE_REGIONS, + TABLE_SECTORS, +) +from directories import CONFIG_FILE, ASSETS_DIR + +# Get logger for this module +logger = setup_logging("main") + +######################################### +# Helpers +######################################### + +# SECTVARR1R2 +def make_id( + sector: Sector, + variant: Variant, + subvariant: Feature, + region_1: Region, + region_2: Region = Region.NONE, +) -> str: + return f"{sector.value}{variant.value}{subvariant.value}{region_1.value}{region_2.value}" + +######################################### +# Initialisation +######################################### + +# New: lightweight config loader (returns dict) +def load_config() -> Dict: + try: + if os.path.exists(CONFIG_FILE): + with open(CONFIG_FILE, "r", encoding="utf-8") as fh: + cfg = json.load(fh) + logger.debug("Loaded config from %s", CONFIG_FILE) + return cfg + except Exception as e: + logger.exception("Failed to load config %s: %s", CONFIG_FILE, e) + raise RuntimeError(f"Failed to load config: {e}") + return {} + +######################################### +# Desired IDs Builder +######################################### + +def rs_active( + matrix: Dict[Tuple[str, str], ft.Dropdown], + r: str, + s: str +) -> bool: + if all(( + dd := matrix.get((r, s)), + not dd.disabled, + str(dd.value) != Level.EXCLUDED.value + )): + return dd + else: + return False + +def get_matrix_selection( + matrix: Dict[Tuple[str, str], ft.Dropdown], + global_settings: Dict[str, Any], +) -> Set[str]: + """ + 1. Get the active region-sector combos and their generic (non-regional) variant + 2. If only electricity in a region, add grid demand + 3. Add endogenous and boundary interties based on selected regions + 4. Add fuels for all active regions + 5. Add agriculture for active regions where anything but electricity is present + """ + + # Get the low-res scenario + low_scenario = global_settings.get("low_scenario", DEFAULT_LOW) + + selections: Set[Tuple[Sector, Variant, Feature, Region, Region]] = set() + regions: Set[Region] = set() + for r in TABLE_REGIONS: + for s in TABLE_SECTORS: + if not (dd := rs_active(matrix, r, s)): + continue + + if str(dd.value) == Level.HIGH_RESOLUTION.value: + v = Variant.HIGH_RESOLUTION + elif low_scenario == "Current Measures": + v = Variant.CURRENT_MEASURES + else: + v = Variant.NET_ZERO + + regions.add(Region(r)) + + # Add variant-region data and variant-generic (no region) data + selections.add(( + Sector(s), + v, + Feature.NONE, + Region(r), + Region.NONE, + )) + selections.add(( + Sector(s), + v, + Feature.NONE, + Region.NONE, + Region.NONE, + )) + + # Special case: if only Elc is active for a region, add electricity demand + if s == Sector.ELECTRICITY.value and not any(( + rs_active(matrix, r, _s) for _s in TABLE_SECTORS if _s != s + )): + selections.add(( + Sector.ELECTRICITY, + v, + Feature.DEMAND, + Region(r), + Region.NONE, + )) + + # Add agriculture if any sector other than electricity active in this region + if any(( + rs_active(matrix, r, _s) + for _s in TABLE_SECTORS if _s != Sector.ELECTRICITY.value + )): + # Generic non-regional components + selections.add(( + Sector.AGRICULTURE, + Variant.HIGH_RESOLUTION, + Feature.NONE, + Region.NONE, + Region.NONE + )) + # Regional components + selections.add(( + Sector.AGRICULTURE, + Variant.HIGH_RESOLUTION, + Feature.NONE, + Region(r), + Region.NONE + )) + + # Endogenous intertie only if both regions selected + region_combos = { + tuple(sorted((r1, r2))) + for r1 in regions + for r2 in regions if r1 != r2 + } + for r1, r2 in region_combos: + selections.add(( + Sector.ELECTRICITY, + Variant.HIGH_RESOLUTION, + Feature.ENDOGENOUS_INTERTIE, + r1, + r2, + )) + + # Boundary intertie only if origin region selected and dest not selected + region_combos = { + (r1, r2) + for r1 in regions + for r2 in Region if r1 != r2 + } + for r1, r2 in region_combos: + if r2 not in regions: + selections.add(( + Sector.ELECTRICITY, + Variant.HIGH_RESOLUTION, + Feature.BOUNDARY_INTERTIE, + r1, + r2, + )) + + # Fuels generic non-regional components always + selections.add(( + Sector.FUEL, + Variant.HIGH_RESOLUTION, + Feature.NONE, + Region.NONE, + Region.NONE + )) + # Fuels for all active regions + for r in regions: + selections.add(( + Sector.FUEL, + Variant.HIGH_RESOLUTION, + Feature.NONE, + r, + Region.NONE + )) + + logger.debug('Selections for aggregation:') + desired_ids: Set[str] = set() + for sector, variant, subvariant, region_1, region_2 in sorted(selections): + logger.debug( + "Sector=%s Variant=%s SubVariant=%s Region1=%s Region2=%s", + sector.value, variant.value, subvariant.value, region_1.value, region_2.value + ) + desired_ids.add( + make_id( + sector, + variant, + subvariant, + region_1, + region_2 + ) + ) + + return desired_ids + + +def infer_selected_regions_from_matrix(matrix: Dict[Tuple[str, str], ft.Dropdown]) -> Set[str]: + """Regions that have any sector set to something other than 'NA'.""" + picked: Set[str] = set() + for r in TABLE_REGIONS: + if any( + (dd := matrix.get((r, s))) is not None and str(dd.value).upper() != Level.EXCLUDED.value + for s in TABLE_SECTORS + ): + picked.add(r) + return picked + +######################################### +# Flet UI +######################################### + +def main(page: ft.Page) -> None: + page.title = "CANOE UI" + page.vertical_alignment = ft.CrossAxisAlignment.START + page.horizontal_alignment = ft.CrossAxisAlignment.CENTER + if sys.platform != "darwin": + icon_path = os.path.join(os.path.dirname(__file__), "assets", "icon.ico") + page.window.icon = icon_path + page.window_width = 1200 + page.window_height = 700 + + # UI storage + matrix: Dict[Tuple[str, str], ft.Dropdown] = {} + + # Global flags + global_settings = { + "low_scenario": DEFAULT_LOW, + "power_system_model": False, + "is_processing": False + } + + # Stop everything if window closed + def on_window_event(e: ft.WindowEvent): + if ( + getattr(e, "type", None) == "close_request" + or getattr(e, "data", None) in ("close", "close_request") + ): + status_text.value = "Exiting..." + page.update() + sleep(0.05) + if global_settings['is_processing']: + logger.info("Processing cancelled due to window close") + global_settings['is_processing'] = False + page.window.destroy() + + page.window.prevent_close = True + page.window.on_event = on_window_event + + # Widgets + status_text = ft.Text("") + in_filename_text_field = ft.TextField(label="Input file path (e.g. dataset.sqlite)", value="", width=260) + out_filename_text_field = ft.TextField(label="Output file path (e.g. canoe.sqlite)", value="", width=260) + + # Scenario Dropdown + scenario_dropdown = ft.Dropdown( + label="Low-level Scenario", + options=[ + ft.dropdown.Option(scen) + for scen in LOW_SCENARIOS + ], + value=DEFAULT_LOW, # Default + width=200, + ) + + # RE-ADDED: Power System Checkbox + power_system_checkbox = ft.Checkbox(label="Power system model", value=False) + + image = ft.Container( + content=ft.Image( + src=os.path.join("assets", "logo.png"), + height=50, + width=60 + ), + alignment=ft.alignment.top_right + ) + + # load saved config (will be applied once UI elements are created) + saved_cfg = load_config() + + def save_config() -> None: + """Persist current UI state to CONFIG_FILE (JSON).""" + try: + cfg = { + "input_filename": os.path.normpath( + (in_filename_text_field.value or "").strip().strip("'").strip('"') + ), + "output_filename": os.path.normpath( + (out_filename_text_field.value or "").strip().strip("'").strip('"') + ), + "low_scenario": (scenario_dropdown.value or DEFAULT_LOW), + "power_system_model": bool(power_system_checkbox.value), # RE-ADDED + "matrix": { + f"{r}|{s}": ( + matrix[(r, s)].value + if (r, s) in matrix and matrix[(r, s)] is not None + else None + ) + for (r, s) in matrix.keys() + }, + } + os.makedirs(os.path.dirname(CONFIG_FILE), exist_ok=True) + with open(CONFIG_FILE, "w", encoding="utf-8") as fh: + json.dump(cfg, fh, indent=2, ensure_ascii=False) + logger.debug("Saved config to %s", CONFIG_FILE) + except Exception as e: + logger.exception("Failed to save config %s: %s", CONFIG_FILE, e) + raise RuntimeError(f"Failed to save config: {e}") + + # --- UI builders / updaters --- + + def on_sector_dropdown_change(e: ft.ControlEvent) -> None: + """Auto-fill sensible defaults when user selects a sector (normal mode).""" + r, s = e.control.data + is_na_selected = (e.control.value == Level.EXCLUDED.value) + + sleep(0.05) # slight delay to allow UI update + + # RE-ADDED: Do not auto-fill if in power system mode + if not global_settings["power_system_model"]: + if is_na_selected: + if s == Sector.ELECTRICITY.value: + for _s in TABLE_SECTORS: + if _s == s: continue + dd = matrix.get((r, _s)) + if not dd: + continue + dd.value = Level.EXCLUDED.value + else: + # if demand is active in this region cant have an inactive demand sector + row_is_active = any( + (matrix.get((r, _s)) + and matrix[(r, _s)].value != Level.EXCLUDED.value) + for _s in TABLE_SECTORS if _s != Sector.ELECTRICITY.value + ) + if row_is_active: + e.control.value = Level.LOW_RESOLUTION.value + e.control.update() + elif s != Sector.ELECTRICITY.value: + # If any sector other than elc activated, all must be active. Default to low-res + for _s in TABLE_SECTORS: + if _s == s: continue + dd = matrix.get((r, _s)) + if not dd: + continue + + if _s != Sector.ELECTRICITY.value and dd.value == Level.EXCLUDED.value: + dd.value = e.control.value + elif _s == Sector.ELECTRICITY.value and dd.value == Level.EXCLUDED.value: + dd.value = Level.HIGH_RESOLUTION.value + + # persist change + save_config() + page.update() + + def update_ui_matrix() -> None: + """Rebuild the matrix rows.""" + + for region, sector in product(TABLE_REGIONS, TABLE_SECTORS): + + dd = matrix.get((region, sector)) + if not dd: + continue + + # RE-ADDED: Enforce power-system rule AFTER loading saved value + try: + if global_settings.get("power_system_model", False) and sector != Sector.ELECTRICITY.value: + dd.disabled = True + else: + dd.disabled = False + except Exception as e: + logger.exception("Failed enforcing power-system rule for %s|%s: %s", region, sector, e) + raise RuntimeError(f"Failed enforcing power-system rule for {region}|{sector}: {e}") + + page.update() + save_config() + + def reset_matrix(e: ft.ControlEvent | None = None) -> None: + """Hard reset: reset all settings, set all cells to 'NA', re-enable controls, + clear status text, and overwrite the saved config.""" + + # 1) Reset global flags / controls + global_settings["low_scenario"] = DEFAULT_LOW + global_settings["power_system_model"] = False # RE-ADDED + scenario_dropdown.value = DEFAULT_LOW + power_system_checkbox.value = False # RE-ADDED + + # 2) Reset all dropdowns in the current matrix + for (r, s), dd in matrix.items(): + dd.disabled = False + dd.value = Level.EXCLUDED.value + + # 3) Clear any status message + status_text.value = "" + + # 4) Rebuild UI and re-apply disabling logic (PSM is off, so all enabled) + update_ui_matrix() + save_config() + + # 5) Final paint + try: + page.update() + except Exception: + pass + + # --- Settings events --- + def on_scenario_change(e: ft.ControlEvent) -> None: + """Handle change for the scenario dropdown.""" + global_settings["low_scenario"] = str(e.control.value) + save_config() + + scenario_dropdown.on_change = on_scenario_change + + # RE-ADDED: Handler for power system checkbox + def on_power_system_change(e: ft.ControlEvent) -> None: + global_settings["power_system_model"] = bool(e.control.value) + update_ui_matrix() + save_config() + + power_system_checkbox.on_change = on_power_system_change + + # --- Submit / run aggregation --- + + # attach saving to text field changes + in_filename_text_field.on_change = lambda e: save_config + out_filename_text_field.on_change = lambda e: save_config + + def on_submit(e: ft.ControlEvent) -> None: + + if global_settings["is_processing"]: + # Cancel button action + global_settings["is_processing"] = False + logger.info("Processing cancelled by user") + submit_button.text = "Submit" + status_text.value = "Processing cancelled." + page.update() + return + + global_settings["is_processing"] = True + submit_button.text = "Cancel" + status_text.value = "Processing..." + page.update() + + input_filename = in_filename_text_field.value.strip().strip("'").strip('"') + if not input_filename: + status_text.value = "Error: Filename cannot be empty." + page.update() + return + + output_filename = out_filename_text_field.value.strip().strip("'").strip('"') + if not output_filename: + status_text.value = "Error: Filename cannot be empty." + page.update() + return + + try: + # persist current config before running + save_config() + desired_ids = get_matrix_selection(matrix, global_settings) + # Send to processing module + dbp.aggregate_sqlite_files( + input_filename = input_filename, + output_filename = output_filename, + global_settings = global_settings, + desired_ids = desired_ids, + ) + if global_settings.get("is_processing", True): + status_text.value = f"Aggregation complete. Output: {output_filename}" + logger.info("Aggregation finished successfully (input=%s output=%s)", input_filename, output_filename) + except Exception as ex: + logger.exception("Aggregation failed (input=%s output=%s): %s", input_filename, output_filename, ex) + status_text.value = f"Error processing database. Check log file." + finally: + # Reset processing state + global_settings["is_processing"] = False + submit_button.text = "Submit" + page.update() + + page.update() + + + # --- Build initial matrix UI (all regions from the start) --- + header_row = [ft.Text("Region/Sector", weight=ft.FontWeight.BOLD, width=120)] + [ + ft.Text(s, weight=ft.FontWeight.BOLD, text_align=ft.TextAlign.CENTER, width=100) for s in TABLE_SECTORS + ] + matrix_rows = [ft.Row(header_row, alignment=ft.MainAxisAlignment.CENTER)] + + for region in TABLE_REGIONS: + row_elements = [ft.Text(region, weight=ft.FontWeight.BOLD, width=120)] + for sector in TABLE_SECTORS: + + # Update matrix values + key = f"{region}|{sector}" + val = Level.EXCLUDED.value + if saved_cfg and saved_cfg.get("matrix") and key in saved_cfg["matrix"]: + try: + val = saved_cfg["matrix"].get(key) + if val is None: + val = Level.EXCLUDED.value + except Exception as e: + logger.exception("Failed applying saved value for %s|%s: %s", region, sector, e) + raise RuntimeError(f"Failed applying saved value for {region}|{sector}: {e}") + + if sector == Sector.ELECTRICITY.value: + level_options = [ + Level.HIGH_RESOLUTION, + Level.EXCLUDED + ] + else: + level_options = Level + # All sectors use same options + dd = ft.Dropdown( + options=[ft.dropdown.Option(l.value) for l in level_options], + value=val, + width=100, + content_padding=ft.padding.only(left=5, right=5), + disabled=False, + ) + matrix[(region, sector)] = dd + row_elements.append(dd) + dd.data = (region, sector) + dd.on_change = on_sector_dropdown_change + matrix_rows.append(ft.Row(row_elements, alignment=ft.MainAxisAlignment.CENTER)) + + # Apply saved text inputs / controls if present + try: + if saved_cfg: + in_filename_text_field.value = saved_cfg.get("input_filename", in_filename_text_field.value) + out_filename_text_field.value = saved_cfg.get("output_filename", out_filename_text_field.value) + + # Apply saved scenario + scenario_saved = saved_cfg.get("low_scenario", scenario_dropdown.value) + scenario_dropdown.value = scenario_saved + global_settings["low_scenario"] = scenario_saved + + # Apply saved PSM checkbox + psm_saved = bool(saved_cfg.get("power_system_model", power_system_checkbox.value)) + power_system_checkbox.value = psm_saved + global_settings["power_system_model"] = psm_saved + + except Exception: + logger.exception("Failed applying saved configuration on load") + pass + + # Controls + reset_button = ft.ElevatedButton("Reset Matrix", on_click=reset_matrix, width=200, height=40) + submit_button = ft.ElevatedButton("Submit", on_click=on_submit, width=80, height=40) + submit_label = ft.Text("Runs without representative periods", size=12, italic=True) + + # Settings column + settings_column = ft.Column( + [ + ft.Text("Aggregation Settings", size=18, weight=ft.FontWeight.BOLD), + ft.Divider(), + scenario_dropdown, + power_system_checkbox, # RE-ADDED + ft.Divider(), + reset_button, + ], + alignment=ft.MainAxisAlignment.START, + horizontal_alignment=ft.CrossAxisAlignment.START, + spacing=10, + width=300, + ) + + # Main content layout (structure/spacing preserved) + middle_row = ft.Row( + [ + ft.Column( + matrix_rows, + expand=True, # take remaining width in the row + scroll=ft.ScrollMode.ADAPTIVE, # or ALWAYS + # remove fixed height here + horizontal_alignment=ft.CrossAxisAlignment.START, + ), + ft.VerticalDivider(), + settings_column, # give this a fixed width internally if needed + ], + expand=True, # <-- this row grows vertically to fill space + alignment=ft.MainAxisAlignment.CENTER, + vertical_alignment=ft.CrossAxisAlignment.START, + ) + + footer = ft.Container( + height=50, # <-- fixed footer height + content=ft.Row( + [in_filename_text_field, out_filename_text_field, submit_button, submit_label, status_text], + alignment=ft.MainAxisAlignment.CENTER, + spacing=30, + ), + alignment=ft.alignment.center, + ) + + rep_dir = os.path.abspath( + os.path.join( + os.path.dirname(__file__), + "representative_periods" + ) + ) + + rep_config_path = os.path.join( + rep_dir, + "config.yaml" + ) + + rep_input_dir = os.path.join( + rep_dir, + "input_sqlite" + ) + + rep_output_dir = os.path.join( + rep_dir, + "output_sqlite" + ) + + rep_clustering_output_dir = os.path.join( + rep_dir, + "clustering_output_data" + ) + + # PyInstaller does not preserve empty directories, + # so create working directories at runtime. + os.makedirs(rep_input_dir, exist_ok=True) + os.makedirs(rep_output_dir, exist_ok=True) + os.makedirs(rep_clustering_output_dir, exist_ok=True) + + def load_rep_config(): + try: + with open(rep_config_path, "r", encoding="utf-8") as f: + return yaml.load(f, Loader=yaml.Loader) + except Exception: + return {} + + def save_rep_config(cfg): + with open(rep_config_path, "w", encoding="utf-8") as f: + yaml.dump(cfg, f, default_flow_style=False, sort_keys=False) + + rep_cfg = load_rep_config() + + default_test_periods = rep_cfg.get("test_periods", [1, 2, 4, 8, 16, 32]) + if not isinstance(default_test_periods, list): + default_test_periods = [1, 2, 4, 8, 16, 32] + + rep_test_periods = ft.TextField( + label="Test Periods (comma separated)", + value=", ".join(map(str, default_test_periods)), + width=300 + ) + + rep_final_periods = ft.Dropdown( + label="Final Periods", + value=str(rep_cfg.get("final_periods", 16)), + width=150, + options=[ft.dropdown.Option(str(p)) for p in default_test_periods] + ) + + def on_test_periods_change(e): + try: + val_str = rep_test_periods.value + new_periods = [int(x.strip()) for x in val_str.split(",") if x.strip().isdigit()] + if new_periods: + rep_final_periods.options = [ft.dropdown.Option(str(p)) for p in new_periods] + if rep_final_periods.value not in [str(p) for p in new_periods]: + rep_final_periods.value = str(new_periods[0]) + page.update() + except Exception: + pass + + rep_test_periods.on_change = on_test_periods_change + + rep_clustering_method = ft.Dropdown( + label="Clustering Method", + options=[ft.dropdown.Option(o) for o in ["hierarchical", "k_means", "k_medoids", "k_maxoids", "adjacent_periods"]], + value=rep_cfg.get("clustering_method", "hierarchical"), + width=200 + ) + rep_days_per_period = ft.TextField(label="Days Per Period", value=str(rep_cfg.get("days_per_period", 1)), width=150) + rep_rerun_clustering = ft.Checkbox(label="Rerun Clustering", value=rep_cfg.get("rerun_clustering", False)) + rep_show_plots = ft.Checkbox(label="Show Plots", value=rep_cfg.get("show_plots", False)) + rep_use_pca = ft.Checkbox(label="Use PCA", value=rep_cfg.get("use_pca", True)) + + pca_cols_in_cfg = [] + if "pca_groups" in rep_cfg and len(rep_cfg["pca_groups"]) > 0: + pca_cols_in_cfg = rep_cfg["pca_groups"][0].get("columns", []) + + master_weather_cols = [] + for region, cols in rep_cfg.get("timeseries", {}).items(): + if cols: + for col in cols: + if any(x in col for x in ["wind_speed", "irradiance", "humidity", "temperature"]): + if col not in master_weather_cols: + master_weather_cols.append(col) + + weather_checkboxes = {} + checkbox_list = [] + for col in master_weather_cols: + is_checked = col in pca_cols_in_cfg if pca_cols_in_cfg else True + cb = ft.Checkbox(label=col, value=is_checked) + weather_checkboxes[col] = cb + checkbox_list.append(cb) + + weather_dropdown = ft.ExpansionTile( + title=ft.Text("Select Weather Columns for PCA"), + controls=[ft.Container( + content=ft.Column(checkbox_list, scroll=ft.ScrollMode.ADAPTIVE, height=200), + padding=10 + )], + width=400 + ) + + rep_status_text = ft.Text("") + + console_output = ft.ListView(expand=True, auto_scroll=True, spacing=2) + console_container = ft.Container( + content=console_output, + margin=10, + padding=10, + alignment=ft.alignment.top_left, + bgcolor="black87", + border_radius=5, + expand=True + ) + + class ConsoleRedirector: + def __init__(self, list_view, page): + self.list_view = list_view + self.page = page + self.buffer = "" + def write(self, text): + if not text: return + self.buffer += text + if "\n" in self.buffer: + lines = self.buffer.split("\n") + for line in lines[:-1]: + self.list_view.controls.append(ft.Text(line, color="white", font_family="Consolas", size=12)) + self.buffer = lines[-1] + self.page.update() + def flush(self): + pass + + def apply_rep_ui_to_config(): + cfg = load_rep_config() + try: + cfg["final_periods"] = int(rep_final_periods.value) + except: pass + try: + val_str = rep_test_periods.value + cfg["test_periods"] = [int(x.strip()) for x in val_str.split(",") if x.strip().isdigit()] + except: pass + cfg["clustering_method"] = rep_clustering_method.value + try: + cfg["days_per_period"] = int(rep_days_per_period.value) + except: pass + cfg["rerun_clustering"] = rep_rerun_clustering.value + cfg["show_plots"] = rep_show_plots.value + cfg["use_pca"] = rep_use_pca.value + + selected_cols = [col for col, cb in weather_checkboxes.items() if cb.value] + if "pca_groups" not in cfg or not cfg["pca_groups"]: + cfg["pca_groups"] = [{"name": "weather", "columns": selected_cols, "n_components": 6}] + else: + cfg["pca_groups"][0]["columns"] = selected_cols + + save_rep_config(cfg) + + def on_initialize(e): + if global_settings["is_processing"]: return + global_settings["is_processing"] = True + rep_status_text.value = "Initializing Clustering..." + console_output.controls.clear() + page.update() + apply_rep_ui_to_config() + + def runner(): + old_stdout = sys.stdout + old_stderr = sys.stderr + + redirector = ConsoleRedirector(console_output, page) + + sys.stdout = redirector + sys.stderr = redirector + + try: + # config.yaml was just updated by apply_rep_ui_to_config() + rep_utils.reload_config() + + # Previously the subprocess gave us a fresh module each run. + rep_clustering.reset() + + rep_clustering.run( + show_plots=rep_utils.config.get("show_plots", False) + ) + + rep_status_text.value = "Clustering initialized successfully!" + + except Exception as ex: + rep_status_text.value = f"Error during clustering: {ex}" + + finally: + sys.stdout = old_stdout + sys.stderr = old_stderr + + global_settings["is_processing"] = False + page.update() + + threading.Thread(target=runner, daemon=True).start() + + def on_run_all(e): + if global_settings["is_processing"]: + return + + rep_status_text.value = "Running Aggregation..." + console_output.controls.clear() + page.update() + + global_settings["is_processing"] = True + + input_filename = ( + in_filename_text_field.value + .strip() + .strip("'") + .strip('"') + ) + + output_filename = ( + out_filename_text_field.value + .strip() + .strip("'") + .strip('"') + ) + if not output_filename.lower().endswith('.sqlite'): + output_filename += '.sqlite' + + def runner(): + old_stdout = sys.stdout + old_stderr = sys.stderr + + redirector = ConsoleRedirector( + console_output, + page + ) + + sys.stdout = redirector + sys.stderr = redirector + + try: + # --------------------------------------- + # 1. Run normal CANOE aggregation + # --------------------------------------- + + save_config() + + desired_ids = get_matrix_selection( + matrix, + global_settings + ) + + dbp.aggregate_sqlite_files( + input_filename=input_filename, + output_filename=output_filename, + global_settings=global_settings, + desired_ids=desired_ids, + ) + + aggregated_db = os.path.abspath( + output_filename + ) + + if not os.path.isfile(aggregated_db): + raise FileNotFoundError( + "CANOE aggregation did not produce " + f"the expected database: {aggregated_db}" + ) + + print( + f"Aggregation complete: {aggregated_db}" + ) + + rep_status_text.value = ( + "Aggregation complete. " + "Running Representative Periods..." + ) + page.update() + + # --------------------------------------- + # 2. Save Representative Period settings + # --------------------------------------- + + apply_rep_ui_to_config() + + # --------------------------------------- + # 3. Determine output path + # --------------------------------------- + + final_p = rep_final_periods.value + + if output_filename.lower().endswith( + ".sqlite" + ): + new_out_path = ( + output_filename[:-7] + + f"_{final_p}d.sqlite" + ) + else: + new_out_path = ( + output_filename + + f"_{final_p}d.sqlite" + ) + + # --------------------------------------- + # 4. Run Representative Period processing + # --------------------------------------- + + print( + f"Representative Periods input: " + f"{aggregated_db}" + ) + + rep_process_all.run( + run_clustering=False, + input_path=aggregated_db, + output_path=new_out_path + ) + + if not os.path.isfile(new_out_path): + raise FileNotFoundError( + "Representative Period processing " + "completed but no output SQLite " + f"database was found at {new_out_path}" + ) + + res_db = new_out_path + + rep_status_text.value = ( + f"Success! Output at: {new_out_path}" + ) + + print( + f"Representative Periods complete: " + f"{new_out_path}" + ) + + except Exception as ex: + import traceback + rep_status_text.value = ( + f"Error during Run All: {ex}\n\n{traceback.format_exc()}" + ) + + print( + f"ERROR during Run All: {ex}" + ) + + finally: + sys.stdout = old_stdout + sys.stderr = old_stderr + + global_settings["is_processing"] = False + page.update() + + threading.Thread( + target=runner, + daemon=True + ).start() + + btn_init = ft.ElevatedButton("Initialize (Cluster Only)", on_click=on_initialize) + btn_run = ft.ElevatedButton("Run (Aggregate & Process)", on_click=on_run_all) + + rep_content = ft.Column([ + ft.Container(height=10), + ft.Row([rep_test_periods, rep_final_periods], alignment=ft.MainAxisAlignment.CENTER), + ft.Row([rep_days_per_period, rep_clustering_method], alignment=ft.MainAxisAlignment.CENTER), + ft.Row([rep_rerun_clustering, rep_show_plots, rep_use_pca], alignment=ft.MainAxisAlignment.CENTER), + ft.Row([weather_dropdown], alignment=ft.MainAxisAlignment.CENTER), + ft.Divider(), + ft.Row([btn_init, btn_run], alignment=ft.MainAxisAlignment.CENTER, spacing=30), + ft.Row([rep_status_text], alignment=ft.MainAxisAlignment.CENTER), + console_container + ], expand=True, spacing=10, alignment=ft.MainAxisAlignment.START, horizontal_alignment=ft.CrossAxisAlignment.CENTER) + + tabs = ft.Tabs( + selected_index=0, + animation_duration=300, + tabs=[ + ft.Tab( + text="Aggregation", + content=ft.Column([ + ft.Text("CANOE RSS Selector", size=24, weight=ft.FontWeight.BOLD), + ft.Text("Read accompanying document for details about choices and instructions", size=18), + ft.Divider(), + middle_row, + ft.Divider(), + footer, + ], expand=True, horizontal_alignment=ft.CrossAxisAlignment.CENTER) + ), + ft.Tab( + text="Representative Periods", + content=rep_content + ), + ], + expand=True, + ) + + main_content = ft.Column( + [ + image, + tabs, + ], + expand=True, + alignment=ft.MainAxisAlignment.START, + horizontal_alignment=ft.CrossAxisAlignment.CENTER, + spacing=10, + ) + + page.add(main_content) + page.update() + + # Build matrix from saved state first, then enforce disabling rules + update_ui_matrix() + +if __name__ == "__main__": ft.app(target=main, assets_dir=ASSETS_DIR) \ No newline at end of file diff --git a/representative_periods/.gitignore b/representative_periods/.gitignore new file mode 100644 index 0000000..cb07526 --- /dev/null +++ b/representative_periods/.gitignore @@ -0,0 +1,5 @@ +__pycache__/ +clustering_output_data/*/ +*.sqlite +periods.csv +sequence.csv \ No newline at end of file diff --git a/representative_periods/LICENSE.txt b/representative_periods/LICENSE.txt new file mode 100644 index 0000000..f288702 --- /dev/null +++ b/representative_periods/LICENSE.txt @@ -0,0 +1,674 @@ + GNU GENERAL PUBLIC LICENSE + Version 3, 29 June 2007 + + Copyright (C) 2007 Free Software Foundation, Inc. + Everyone is permitted to copy and distribute verbatim copies + of this license document, but changing it is not allowed. + + Preamble + + The GNU General Public License is a free, copyleft license for +software and other kinds of works. + + The licenses for most software and other practical works are designed +to take away your freedom to share and change the works. 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It is safest +to attach them to the start of each source file to most effectively +state the exclusion of warranty; and each file should have at least +the "copyright" line and a pointer to where the full notice is found. + + + Copyright (C) + + This program is free software: you can redistribute it and/or modify + it under the terms of the GNU General Public License as published by + the Free Software Foundation, either version 3 of the License, or + (at your option) any later version. + + This program is distributed in the hope that it will be useful, + but WITHOUT ANY WARRANTY; without even the implied warranty of + MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the + GNU General Public License for more details. + + You should have received a copy of the GNU General Public License + along with this program. If not, see . + +Also add information on how to contact you by electronic and paper mail. + + If the program does terminal interaction, make it output a short +notice like this when it starts in an interactive mode: + + Copyright (C) + This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'. + This is free software, and you are welcome to redistribute it + under certain conditions; type `show c' for details. + +The hypothetical commands `show w' and `show c' should show the appropriate +parts of the General Public License. Of course, your program's commands +might be different; for a GUI interface, you would use an "about box". + + You should also get your employer (if you work as a programmer) or school, +if any, to sign a "copyright disclaimer" for the program, if necessary. +For more information on this, and how to apply and follow the GNU GPL, see +. + + The GNU General Public License does not permit incorporating your program +into proprietary programs. If your program is a subroutine library, you +may consider it more useful to permit linking proprietary applications with +the library. If this is what you want to do, use the GNU Lesser General +Public License instead of this License. But first, please read +. diff --git a/representative_periods/README.md b/representative_periods/README.md new file mode 100644 index 0000000..4a4ae20 --- /dev/null +++ b/representative_periods/README.md @@ -0,0 +1,96 @@ +# CANOE Representative Periods Processor + +A toolkit for processing CANOE databases to apply representative periods using clustering algorithms. This tool supports multiple versions of the Temoa schema (v2, v3, v3.1). + +## Features + +- **Time Series Clustering**: Generates representative periods from raw time series data (`clustering.py`). + - Supports Principal Component Analysis (PCA) for dimensionality reduction (`pca.py`). + - Allows custom feature selection strategies (`feature_selection.py`). +- **Database Processing**: Applies generated representative periods to SQLite databases for: + - Temoa Legacy Schema (`database_processing.py`) + - Temoa Schema v3 (`database_processing_v3.py`) + - Temoa Schema v3.1 (`database_processing_v3_1.py` - uses `canoe_schema_v3_1.sql`) +- **Automated Workflow**: `process_all.py` orchestrates the entire flow. +- **Configurable**: Highly customizable via `config.yaml`. + +## Installation + +1. **Clone the repository** (if you haven't already). + +2. **Set up the environment**: + It is recommended to use Conda/Mamba. + ```bash + conda env create -f environment.yml + conda activate canoe-backend + ``` + Alternatively, you can install dependencies via pip: + ```bash + pip install -r requirements.txt + ``` + +3. **CRITICAL: Patch `tsam` library**: + The `tsam` library requires a custom modification for this tool to work correctly. + You must replace the `timeseriesaggregation.py` file in your Python environment's `tsam` package with the one provided in this repository. + + **Source file:** `./timeseriesaggregation.py` (in this root directory) + + **Destination:** + Find where `tsam` is installed. You can find the exact path by running: + ```bash + python -c "import tsam, os; print(os.path.dirname(tsam.__file__))" + ``` + It is typically located at: + - **Windows**: `C:\Users\\miniconda3\envs\canoe-backend\Lib\site-packages\tsam\` + - **macOS / Linux**: `~/miniconda3/envs/canoe-backend/lib/python3.12/site-packages/tsam/` + *(Note: On Apple Silicon Macs, this might be under `miniforge3` instead of `miniconda3`)* + + *Replace the existing `timeseriesaggregation.py` file in that directory with the one from this repo.* + + **macOS / Linux Shortcut:** + If you have your conda environment activated, you can run this command from the `representative_periods` directory to automatically patch the file: + ```bash + cp ./timeseriesaggregation.py $(python -c "import tsam, os; print(os.path.dirname(tsam.__file__))")/ + ``` + +## Usage + +1. **Prepare Input Data**: + - Place your source SQLite databases (`.sqlite`) in the `input_sqlite/` directory. + - Ensure your time series data is correctly structured in `timeseries/` as referenced in `config.yaml`. + +2. **Configuration**: + - Edit `config.yaml` to adjust clustering parameters, select time series columns, and define output settings. + +3. **Run the Processor**: + To run the full workflow (clustering + database updating): + ```bash + python process_all.py + ``` + + Or run individual steps: + ```bash + # Step 1: Generate representative periods + python clustering.py + + # Step 2: Update databases (choose the script matching your schema version) + python database_processing_v3_1.py + ``` + +4. **Outputs**: + - **Processed Databases**: Found in `output_sqlite/`. + - **Clustering Data**: Debugging and visualization data in `clustering_output_data/`. + - **Periods File**: `periods.csv` (the raw representative periods). + +## Project Structure + +- `process_all.py`: Main entry point. +- `clustering.py`: Logic for time series clustering. +- `pca.py`: Utilities for performing PCA on time series groups before clustering. +- `feature_selection.py`: Contains custom strategies for selecting specific periods (e.g. max mean). +- `database_processing*.py`: Scripts to update SQLite databases with new periods. +- `canoe_schema_v3_1.sql`: SQL schema definition for Temoa v3.1 databases. +- `config.yaml`: Main configuration file. +- `timeseries/`: Directory containing raw input data for clustering. +- `input_sqlite/`: Drop your raw databases here. +- `output_sqlite/`: Pick up your processed databases from here. diff --git a/representative_periods/SUPPORT.md b/representative_periods/SUPPORT.md new file mode 100644 index 0000000..602fd52 --- /dev/null +++ b/representative_periods/SUPPORT.md @@ -0,0 +1,24 @@ +# Support for CANOE (Alpha Release) + +Thank you for trying out the CANOE project in its early alpha stage! +At this point, we are focusing on gathering feedback, fixing bugs, and shaping the project for a stable release. + +## How to Get Help + +- **Questions**: Please open a GitHub Issue with the question label. + +- **Bugs**: Open a GitHub Issue with the bug label. Include as much detail as possible (steps to reproduce, environment, error messages). + +- **Feature Requests**: Use the enhancement label in Issues. We may not implement everything right away, but your ideas help guide our roadmap. + +## What to Expect + +- Response times may be slower during alpha as we prioritize critical bug fixes. + +- Breaking changes may occur between releases — APIs and file formats are not yet stable. + +- Pull requests are not yet accepted for major code contributions. For now, we encourage bug reports and feature requests only. + +## Contact + +For urgent issues (e.g., security concerns), please email: canoe-support@googlegroups.com diff --git a/representative_periods/__init__/py b/representative_periods/__init__/py new file mode 100644 index 0000000..f629673 --- /dev/null +++ b/representative_periods/__init__/py @@ -0,0 +1 @@ +"""Representative period processing for CANOE.""" \ No newline at end of file diff --git a/representative_periods/canoe_schema_v3_1.sql b/representative_periods/canoe_schema_v3_1.sql new file mode 100644 index 0000000..50332e2 --- /dev/null +++ b/representative_periods/canoe_schema_v3_1.sql @@ -0,0 +1,1838 @@ +PRAGMA foreign_keys= OFF; +BEGIN TRANSACTION; + +CREATE TABLE IF NOT EXISTS MetaData +( + element TEXT PRIMARY KEY, + value INT, + notes TEXT +); +REPLACE INTO MetaData +VALUES ('DB_MAJOR', 3, 'DB major version number'); +REPLACE INTO MetaData +VALUES ('DB_MINOR', 1, 'DB minor version number'); +REPLACE INTO MetaData +VALUES ('days_per_period', 365, 'count of days in each period'); + +CREATE TABLE IF NOT EXISTS MetaDataReal +( + element TEXT PRIMARY KEY, + value REAL, + notes TEXT +); +REPLACE INTO MetaDataReal +VALUES ('global_discount_rate', 0.03, 'Canadian social discount rate'); +REPLACE INTO MetaDataReal +VALUES ('default_loan_rate', 0.03, 'Matching GDR'); + +CREATE TABLE IF NOT EXISTS SeasonLabel +( + season TEXT + PRIMARY KEY, + notes TEXT +); +CREATE TABLE IF NOT EXISTS SectorLabel +( + sector TEXT, + notes TEXT, + PRIMARY KEY (sector) +); +CREATE TABLE IF NOT EXISTS CapacityCredit +( + region TEXT, + period INTEGER + REFERENCES TimePeriod (period), + tech TEXT, + vintage INTEGER, + credit REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + FOREIGN KEY (tech) REFERENCES Technology (tech), + PRIMARY KEY (region, period, tech, vintage), + CHECK (credit >= 0 AND credit <= 1) +); +CREATE TABLE IF NOT EXISTS CapacityFactorProcess +( + region TEXT, + period INTEGER + REFERENCES TimePeriod (period), + season TEXT + REFERENCES SeasonLabel (season), + tod TEXT + REFERENCES TimeOfDay (tod), + tech TEXT, + vintage INTEGER, + factor REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + FOREIGN KEY (tech) REFERENCES Technology (tech), + PRIMARY KEY (region, period, season, tod, tech, vintage), + CHECK (factor >= 0 AND factor <= 1) +); +CREATE TABLE IF NOT EXISTS CapacityFactorTech +( + region TEXT, + period INTEGER + REFERENCES TimePeriod (period), + season TEXT + REFERENCES SeasonLabel (season), + tod TEXT + REFERENCES TimeOfDay (tod), + tech TEXT, + factor REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + FOREIGN KEY (tech) REFERENCES Technology (tech), + PRIMARY KEY (region, period, season, tod, tech), + CHECK (factor >= 0 AND factor <= 1) +); +CREATE TABLE IF NOT EXISTS CapacityToActivity +( + region TEXT, + tech TEXT, + c2a REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + FOREIGN KEY (tech) REFERENCES Technology (tech), + PRIMARY KEY (region, tech) +); +CREATE TABLE IF NOT EXISTS Commodity +( + name TEXT, + flag TEXT + REFERENCES CommodityType (label), + description TEXT, + data_id TEXT + REFERENCES DataSet (data_id), + PRIMARY KEY (name) +); +CREATE TABLE IF NOT EXISTS CommodityType +( + label TEXT PRIMARY KEY, + description TEXT +); +REPLACE INTO CommodityType +VALUES ('s', 'source commodity'); +REPLACE INTO CommodityType +VALUES ('a', 'annual commodity'); +REPLACE INTO CommodityType +VALUES ('p', 'physical commodity'); +REPLACE INTO CommodityType +VALUES ('d', 'demand commodity'); +REPLACE INTO CommodityType +VALUES ('e', 'emissions commodity'); +REPLACE INTO CommodityType +VALUES ('w', 'waste commodity'); +REPLACE INTO CommodityType +VALUES ('wa', 'waste annual commodity'); +REPLACE INTO CommodityType +VALUES ('wp', 'waste physical commodity'); +CREATE TABLE IF NOT EXISTS ConstructionInput +( + region TEXT, + input_comm TEXT, + tech TEXT, + vintage INTEGER + REFERENCES TimePeriod (period), + value REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + FOREIGN KEY (tech) REFERENCES Technology (tech), + FOREIGN KEY (input_comm) REFERENCES Commodity (name), + PRIMARY KEY (region, input_comm, tech, vintage) +); +CREATE TABLE IF NOT EXISTS CostEmission +( + region TEXT, + period INTEGER + REFERENCES TimePeriod (period), + emis_comm TEXT NOT NULL, + cost REAL NOT NULL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + FOREIGN KEY (emis_comm) REFERENCES Commodity (name), + PRIMARY KEY (region, period, emis_comm) +); +CREATE TABLE IF NOT EXISTS CostFixed +( + region TEXT NOT NULL, + period INTEGER NOT NULL + REFERENCES TimePeriod (period), + tech TEXT NOT NULL, + vintage INTEGER NOT NULL + REFERENCES TimePeriod (period), + cost REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + FOREIGN KEY (tech) REFERENCES Technology (tech), + PRIMARY KEY (region, period, tech, vintage) +); +CREATE TABLE IF NOT EXISTS CostInvest +( + region TEXT, + tech TEXT, + vintage INTEGER + REFERENCES TimePeriod (period), + cost REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + FOREIGN KEY (tech) REFERENCES Technology (tech), + PRIMARY KEY (region, tech, vintage) +); +CREATE TABLE IF NOT EXISTS CostVariable +( + region TEXT NOT NULL, + period INTEGER NOT NULL + REFERENCES TimePeriod (period), + tech TEXT NOT NULL, + vintage INTEGER NOT NULL + REFERENCES TimePeriod (period), + cost REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + FOREIGN KEY (tech) REFERENCES Technology (tech), + PRIMARY KEY (region, period, tech, vintage) +); +CREATE TABLE IF NOT EXISTS Demand +( + region TEXT, + period INTEGER + REFERENCES TimePeriod (period), + commodity TEXT, + demand REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + FOREIGN KEY (commodity) REFERENCES Commodity (name), + PRIMARY KEY (region, period, commodity) +); +CREATE TABLE IF NOT EXISTS DemandSpecificDistribution +( + region TEXT, + period INTEGER + REFERENCES TimePeriod (period), + season TEXT + REFERENCES SeasonLabel (season), + tod TEXT + REFERENCES TimeOfDay (tod), + demand_name TEXT, + dsd REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + FOREIGN KEY (demand_name) REFERENCES Commodity (name), + PRIMARY KEY (region, period, season, tod, demand_name), + CHECK (dsd >= 0 AND dsd <= 1) +); +CREATE TABLE IF NOT EXISTS EndOfLifeOutput +( + region TEXT, + tech TEXT, + vintage INTEGER + REFERENCES TimePeriod (period), + output_comm TEXT, + value REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + FOREIGN KEY (tech) REFERENCES Technology (tech), + FOREIGN KEY (output_comm) REFERENCES Commodity (name), + PRIMARY KEY (region, tech, vintage, output_comm) +); +CREATE TABLE IF NOT EXISTS Efficiency +( + region TEXT, + input_comm TEXT, + tech TEXT, + vintage INTEGER + REFERENCES TimePeriod (period), + output_comm TEXT, + efficiency REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + FOREIGN KEY (tech) REFERENCES Technology (tech), + FOREIGN KEY (input_comm) REFERENCES Commodity (name), + FOREIGN KEY (output_comm) REFERENCES Commodity (name), + PRIMARY KEY (region, input_comm, tech, vintage, output_comm), + CHECK (efficiency > 0) +); +CREATE TABLE IF NOT EXISTS EfficiencyVariable +( + region TEXT, + period INTEGER + REFERENCES TimePeriod (period), + season TEXT + REFERENCES SeasonLabel (season), + tod TEXT + REFERENCES TimeOfDay (tod), + input_comm TEXT, + tech TEXT, + vintage INTEGER + REFERENCES TimePeriod (period), + output_comm TEXT, + efficiency REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + FOREIGN KEY (tech) REFERENCES Technology (tech), + FOREIGN KEY (input_comm) REFERENCES Commodity (name), + FOREIGN KEY (output_comm) REFERENCES Commodity (name), + PRIMARY KEY (region, period, season, tod, input_comm, tech, vintage, output_comm), + CHECK (efficiency > 0) +); +CREATE TABLE IF NOT EXISTS EmissionActivity +( + region TEXT, + emis_comm TEXT, + input_comm TEXT, + tech TEXT, + vintage INTEGER + REFERENCES TimePeriod (period), + output_comm TEXT, + activity REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + FOREIGN KEY (tech) REFERENCES Technology (tech), + FOREIGN KEY (emis_comm) REFERENCES Commodity (name), + FOREIGN KEY (input_comm) REFERENCES Commodity (name), + FOREIGN KEY (output_comm) REFERENCES Commodity (name), + PRIMARY KEY (region, emis_comm, input_comm, tech, vintage, output_comm) +); +CREATE TABLE IF NOT EXISTS EmissionEmbodied +( + region TEXT, + emis_comm TEXT, + tech TEXT, + vintage INTEGER + REFERENCES TimePeriod (period), + value REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + FOREIGN KEY (tech) REFERENCES Technology (tech), + FOREIGN KEY (emis_comm) REFERENCES Commodity (name), + PRIMARY KEY (region, emis_comm, tech, vintage) +); +CREATE TABLE IF NOT EXISTS EmissionEndOfLife +( + region TEXT, + emis_comm TEXT, + tech TEXT, + vintage INTEGER + REFERENCES TimePeriod (period), + value REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + FOREIGN KEY (tech) REFERENCES Technology (tech), + FOREIGN KEY (emis_comm) REFERENCES Commodity (name), + PRIMARY KEY (region, emis_comm, tech, vintage) +); +CREATE TABLE IF NOT EXISTS ExistingCapacity +( + region TEXT, + tech TEXT, + vintage INTEGER + REFERENCES TimePeriod (period), + capacity REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + FOREIGN KEY (tech) REFERENCES Technology (tech), + PRIMARY KEY (region, tech, vintage) +); +CREATE TABLE IF NOT EXISTS TechGroup +( + group_name TEXT, + notes TEXT, + data_id TEXT + REFERENCES DataSet (data_id), + PRIMARY KEY (group_name) +); +CREATE TABLE IF NOT EXISTS LoanLifetimeProcess +( + region TEXT, + tech TEXT, + vintage INTEGER + REFERENCES TimePeriod (period), + lifetime REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + FOREIGN KEY (tech) REFERENCES Technology (tech), + PRIMARY KEY (region, tech, vintage) +); +CREATE TABLE IF NOT EXISTS LoanRate +( + region TEXT, + tech TEXT, + vintage INTEGER + REFERENCES TimePeriod (period), + rate REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + FOREIGN KEY (tech) REFERENCES Technology (tech), + PRIMARY KEY (region, tech, vintage) +); +CREATE TABLE IF NOT EXISTS LifetimeProcess +( + region TEXT, + tech TEXT, + vintage INTEGER + REFERENCES TimePeriod (period), + lifetime REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + FOREIGN KEY (tech) REFERENCES Technology (tech), + PRIMARY KEY (region, tech, vintage) +); +CREATE TABLE IF NOT EXISTS LifetimeTech +( + region TEXT, + tech TEXT, + lifetime REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + FOREIGN KEY (tech) REFERENCES Technology (tech), + PRIMARY KEY (region, tech) +); +CREATE TABLE IF NOT EXISTS Operator +( + operator TEXT PRIMARY KEY, + notes TEXT +); +REPLACE INTO Operator VALUES('e','equal to'); +REPLACE INTO Operator VALUES('le','less than or equal to'); +REPLACE INTO Operator VALUES('ge','greater than or equal to'); +CREATE TABLE IF NOT EXISTS OutputDualVariable +( + scenario TEXT, + constraint_name TEXT, + dual REAL, + PRIMARY KEY (constraint_name, scenario) +); +CREATE TABLE IF NOT EXISTS OutputObjective +( + scenario TEXT, + objective_name TEXT, + total_system_cost REAL +); +CREATE TABLE IF NOT EXISTS OutputCurtailment +( + scenario TEXT, + region TEXT, + sector TEXT, + period INTEGER + REFERENCES TimePeriod (period), + season TEXT + REFERENCES TimePeriod (period), + tod TEXT + REFERENCES TimeOfDay (tod), + input_comm TEXT + REFERENCES Commodity (name), + tech TEXT + REFERENCES Technology (tech), + vintage INTEGER + REFERENCES TimePeriod (period), + output_comm TEXT + REFERENCES Commodity (name), + curtailment REAL, + PRIMARY KEY (region, scenario, period, season, tod, input_comm, tech, vintage, output_comm) +); +CREATE TABLE IF NOT EXISTS OutputNetCapacity +( + scenario TEXT, + region TEXT, + sector TEXT + REFERENCES SectorLabel (sector), + period INTEGER + REFERENCES TimePeriod (period), + tech TEXT + REFERENCES Technology (tech), + vintage INTEGER + REFERENCES TimePeriod (period), + capacity REAL, + PRIMARY KEY (region, scenario, period, tech, vintage) +); +CREATE TABLE IF NOT EXISTS OutputBuiltCapacity +( + scenario TEXT, + region TEXT, + sector TEXT + REFERENCES SectorLabel (sector), + tech TEXT + REFERENCES Technology (tech), + vintage INTEGER + REFERENCES TimePeriod (period), + capacity REAL, + PRIMARY KEY (region, scenario, tech, vintage) +); +CREATE TABLE IF NOT EXISTS OutputRetiredCapacity +( + scenario TEXT, + region TEXT, + sector TEXT + REFERENCES SectorLabel (sector), + period INTEGER + REFERENCES TimePeriod (period), + tech TEXT + REFERENCES Technology (tech), + vintage INTEGER + REFERENCES TimePeriod (period), + cap_eol REAL, + cap_early REAL, + PRIMARY KEY (region, scenario, period, tech, vintage) +); +CREATE TABLE IF NOT EXISTS OutputFlowIn +( + scenario TEXT, + region TEXT, + sector TEXT + REFERENCES SectorLabel (sector), + period INTEGER + REFERENCES TimePeriod (period), + season TEXT + REFERENCES SeasonLabel (season), + tod TEXT + REFERENCES TimeOfDay (tod), + input_comm TEXT + REFERENCES Commodity (name), + tech TEXT + REFERENCES Technology (tech), + vintage INTEGER + REFERENCES TimePeriod (period), + output_comm TEXT + REFERENCES Commodity (name), + flow REAL, + PRIMARY KEY (region, scenario, period, season, tod, input_comm, tech, vintage, output_comm) +); +CREATE TABLE IF NOT EXISTS OutputFlowOut +( + scenario TEXT, + region TEXT, + sector TEXT + REFERENCES SectorLabel (sector), + period INTEGER + REFERENCES TimePeriod (period), + season TEXT + REFERENCES SeasonLabel (season), + tod TEXT + REFERENCES TimeOfDay (tod), + input_comm TEXT + REFERENCES Commodity (name), + tech TEXT + REFERENCES Technology (tech), + vintage INTEGER + REFERENCES TimePeriod (period), + output_comm TEXT + REFERENCES Commodity (name), + flow REAL, + PRIMARY KEY (region, scenario, period, season, tod, input_comm, tech, vintage, output_comm) +); +CREATE TABLE IF NOT EXISTS OutputStorageLevel +( + scenario TEXT, + region TEXT, + sector TEXT + REFERENCES SectorLabel (sector), + period INTEGER + REFERENCES TimePeriod (period), + season TEXT + REFERENCES SeasonLabel (season), + tod TEXT + REFERENCES TimeOfDay (tod), + tech TEXT + REFERENCES Technology (tech), + vintage INTEGER + REFERENCES TimePeriod (period), + level REAL, + PRIMARY KEY (scenario, region, period, season, tod, tech, vintage) +); +CREATE TABLE IF NOT EXISTS OutputEmission +( + scenario TEXT, + region TEXT, + sector TEXT + REFERENCES SectorLabel (sector), + period INTEGER + REFERENCES TimePeriod (period), + emis_comm TEXT + REFERENCES Commodity (name), + tech TEXT + REFERENCES Technology (tech), + vintage INTEGER + REFERENCES TimePeriod (period), + emission REAL, + PRIMARY KEY (region, scenario, period, emis_comm, tech, vintage) +); +CREATE TABLE IF NOT EXISTS OutputCost +( + scenario TEXT, + region TEXT, + sector TEXT REFERENCES SectorLabel (sector), + period INTEGER REFERENCES TimePeriod (period), + tech TEXT REFERENCES Technology (tech), + vintage INTEGER REFERENCES TimePeriod (period), + d_invest REAL, + d_fixed REAL, + d_var REAL, + d_emiss REAL, + invest REAL, + fixed REAL, + var REAL, + emiss REAL, + PRIMARY KEY (scenario, region, period, tech, vintage), + FOREIGN KEY (vintage) REFERENCES TimePeriod (period), + FOREIGN KEY (tech) REFERENCES Technology (tech) +); +CREATE TABLE IF NOT EXISTS LimitGrowthCapacity +( + region TEXT, + tech_or_group TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES Operator (operator), + rate REAL NOT NULL DEFAULT 0, + seed REAL NOT NULL DEFAULT 0, + seed_units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + PRIMARY KEY (region, tech_or_group, operator) +); +CREATE TABLE IF NOT EXISTS LimitDegrowthCapacity +( + region TEXT, + tech_or_group TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES Operator (operator), + rate REAL NOT NULL DEFAULT 0, + seed REAL NOT NULL DEFAULT 0, + seed_units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + PRIMARY KEY (region, tech_or_group, operator) +); +CREATE TABLE IF NOT EXISTS LimitGrowthNewCapacity +( + region TEXT, + tech_or_group TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES Operator (operator), + rate REAL NOT NULL DEFAULT 0, + seed REAL NOT NULL DEFAULT 0, + seed_units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + PRIMARY KEY (region, tech_or_group, operator) +); +CREATE TABLE IF NOT EXISTS LimitDegrowthNewCapacity +( + region TEXT, + tech_or_group TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES Operator (operator), + rate REAL NOT NULL DEFAULT 0, + seed REAL NOT NULL DEFAULT 0, + seed_units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + PRIMARY KEY (region, tech_or_group, operator) +); +CREATE TABLE IF NOT EXISTS LimitGrowthNewCapacityDelta +( + region TEXT, + tech_or_group TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES Operator (operator), + rate REAL NOT NULL DEFAULT 0, + seed REAL NOT NULL DEFAULT 0, + seed_units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + PRIMARY KEY (region, tech_or_group, operator) +); +CREATE TABLE IF NOT EXISTS LimitDegrowthNewCapacityDelta +( + region TEXT, + tech_or_group TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES Operator (operator), + rate REAL NOT NULL DEFAULT 0, + seed REAL NOT NULL DEFAULT 0, + seed_units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + PRIMARY KEY (region, tech_or_group, operator) +); +CREATE TABLE IF NOT EXISTS LimitStorageLevelFraction +( + region TEXT, + period INTEGER + REFERENCES TimePeriod (period), + season TEXT + REFERENCES SeasonLabel (season), + tod TEXT + REFERENCES TimeOfDay (tod), + tech TEXT, + vintage INTEGER + REFERENCES TimePeriod (period), + operator TEXT NOT NULL DEFAULT "le" + REFERENCES Operator (operator), + fraction REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + FOREIGN KEY (tech) REFERENCES Technology (tech), + PRIMARY KEY (region, period, season, tod, tech, vintage, operator) +); +CREATE TABLE IF NOT EXISTS LimitActivity +( + region TEXT, + period INTEGER + REFERENCES TimePeriod (period), + tech_or_group TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES Operator (operator), + activity REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + PRIMARY KEY (region, period, tech_or_group, operator) +); +CREATE TABLE IF NOT EXISTS LimitActivityShare +( + region TEXT, + period INTEGER + REFERENCES TimePeriod (period), + sub_group TEXT, + super_group TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES Operator (operator), + share REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + PRIMARY KEY (region, period, sub_group, super_group, operator) +); +CREATE TABLE IF NOT EXISTS LimitAnnualCapacityFactor +( + region TEXT, + tech TEXT, + vintage INTEGER + REFERENCES TimePeriod (period), + output_comm TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES Operator (operator), + factor REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + FOREIGN KEY (tech) REFERENCES Technology (tech), + FOREIGN KEY (output_comm) REFERENCES Commodity (name), + PRIMARY KEY (region, tech, vintage, output_comm, operator), + CHECK (factor >= 0 AND factor <= 1) +); +CREATE TABLE IF NOT EXISTS LimitCapacity +( + region TEXT, + period INTEGER + REFERENCES TimePeriod (period), + tech_or_group TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES Operator (operator), + capacity REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + PRIMARY KEY (region, period, tech_or_group, operator) +); +CREATE TABLE IF NOT EXISTS LimitCapacityShare +( + region TEXT, + period INTEGER + REFERENCES TimePeriod (period), + sub_group TEXT, + super_group TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES Operator (operator), + share REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + PRIMARY KEY (region, period, sub_group, super_group, operator) +); +CREATE TABLE IF NOT EXISTS LimitNewCapacity +( + region TEXT, + period INTEGER + REFERENCES TimePeriod (period), + tech_or_group TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES Operator (operator), + new_cap REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + PRIMARY KEY (region, period, tech_or_group, operator) +); +CREATE TABLE IF NOT EXISTS LimitNewCapacityShare +( + region TEXT, + period INTEGER + REFERENCES TimePeriod (period), + sub_group TEXT, + super_group TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES Operator (operator), + share REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + PRIMARY KEY (region, period, sub_group, super_group, operator) +); +CREATE TABLE IF NOT EXISTS LimitResource +( + region TEXT, + tech_or_group TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES Operator (operator), + cum_act REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + PRIMARY KEY (region, tech_or_group, operator) +); +CREATE TABLE IF NOT EXISTS LimitSeasonalCapacityFactor +( + region TEXT, + period INTEGER + REFERENCES TimePeriod (period), + season TEXT + REFERENCES SeasonLabel (season), + tech TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES Operator (operator), + factor REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + FOREIGN KEY (region) REFERENCES Region (region), + FOREIGN KEY (tech) REFERENCES Technology (tech), + PRIMARY KEY (region, period, season, tech, operator) +); +CREATE TABLE IF NOT EXISTS LimitTechInputSplit +( + region TEXT, + period INTEGER + REFERENCES TimePeriod (period), + input_comm TEXT, + tech TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES Operator (operator), + proportion REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + FOREIGN KEY (tech) REFERENCES Technology (tech), + FOREIGN KEY (input_comm) REFERENCES Commodity (name), + PRIMARY KEY (region, period, input_comm, tech, operator) +); +CREATE TABLE IF NOT EXISTS LimitTechInputSplitAnnual +( + region TEXT, + period INTEGER + REFERENCES TimePeriod (period), + input_comm TEXT, + tech TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES Operator (operator), + proportion REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + FOREIGN KEY (tech) REFERENCES Technology (tech), + PRIMARY KEY (region, period, input_comm, tech, operator) +); +CREATE TABLE IF NOT EXISTS LimitTechOutputSplit +( + region TEXT, + period INTEGER + REFERENCES TimePeriod (period), + tech TEXT, + output_comm TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES Operator (operator), + proportion REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + FOREIGN KEY (tech) REFERENCES Technology (tech), + FOREIGN KEY (output_comm) REFERENCES Commodity (name), + PRIMARY KEY (region, period, tech, output_comm, operator) +); +CREATE TABLE IF NOT EXISTS LimitTechOutputSplitAnnual +( + region TEXT, + period INTEGER + REFERENCES TimePeriod (period), + tech TEXT, + output_comm TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES Operator (operator), + proportion REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + FOREIGN KEY (tech) REFERENCES Technology (tech), + FOREIGN KEY (output_comm) REFERENCES Commodity (name), + PRIMARY KEY (region, period, tech, output_comm, operator) +); +CREATE TABLE IF NOT EXISTS LimitEmission +( + region TEXT, + period INTEGER + REFERENCES TimePeriod (period), + emis_comm TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES Operator (operator), + value REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + FOREIGN KEY (emis_comm) REFERENCES Commodity (name), + PRIMARY KEY (region, period, emis_comm, operator) +); +CREATE TABLE IF NOT EXISTS LinkedTech +( + primary_region TEXT, + primary_tech TEXT, + emis_comm TEXT, + driven_tech TEXT, + notes TEXT, + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (primary_tech) REFERENCES Technology (tech), + FOREIGN KEY (driven_tech) REFERENCES Technology (tech), + FOREIGN KEY (emis_comm) REFERENCES Commodity (name), + PRIMARY KEY (primary_region, primary_tech, emis_comm) +); +CREATE TABLE IF NOT EXISTS PlanningReserveMargin +( + region TEXT, + margin REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + FOREIGN KEY (region) REFERENCES Region (region), + PRIMARY KEY (region) +); +CREATE TABLE IF NOT EXISTS RampDownHourly +( + region TEXT, + tech TEXT, + rate REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + FOREIGN KEY (tech) REFERENCES Technology (tech), + PRIMARY KEY (region, tech) +); +CREATE TABLE IF NOT EXISTS RampUpHourly +( + region TEXT, + tech TEXT, + rate REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + FOREIGN KEY (tech) REFERENCES Technology (tech), + PRIMARY KEY (region, tech) +); +CREATE TABLE IF NOT EXISTS Region +( + region TEXT, + notes TEXT, + PRIMARY KEY (region) +); +CREATE TABLE IF NOT EXISTS ReserveCapacityDerate +( + region TEXT, + period INTEGER + REFERENCES TimePeriod (period), + season TEXT + REFERENCES SeasonLabel (season), + tech TEXT, + vintage INTEGER, + factor REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + FOREIGN KEY (tech) REFERENCES Technology (tech), + PRIMARY KEY (region, period, season, tech, vintage), + CHECK (factor >= 0 AND factor <= 1) +); +CREATE TABLE IF NOT EXISTS TimeSegmentFraction +( + period INTEGER + REFERENCES TimePeriod (period), + season TEXT + REFERENCES SeasonLabel (season), + tod TEXT + REFERENCES TimeOfDay (tod), + segfrac REAL, + notes TEXT, + PRIMARY KEY (period, season, tod), + CHECK (segfrac >= 0 AND segfrac <= 1) +); +CREATE TABLE IF NOT EXISTS StorageDuration +( + region TEXT, + tech TEXT, + duration REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + PRIMARY KEY (region, tech) +); +CREATE TABLE IF NOT EXISTS LifetimeSurvivalCurve +( + region TEXT NOT NULL, + period INTEGER NOT NULL, + tech TEXT NOT NULL, + vintage INTEGER NOT NULL + REFERENCES TimePeriod (period), + fraction REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + FOREIGN KEY (tech) REFERENCES Technology (tech), + PRIMARY KEY (region, period, tech, vintage) +); +CREATE TABLE IF NOT EXISTS TechnologyType +( + label TEXT PRIMARY KEY, + description TEXT +); +REPLACE INTO TechnologyType +VALUES ('p', 'production technology'); +REPLACE INTO TechnologyType +VALUES ('pb', 'baseload production technology'); +REPLACE INTO TechnologyType +VALUES ('ps', 'storage production technology'); +-- CREATE TABLE IF NOT EXISTS TimeNext +-- ( +-- period INTEGER +-- REFERENCES TimePeriod (period), +-- season TEXT +-- REFERENCES SeasonLabel (season), +-- tod TEXT +-- REFERENCES TimeOfDay (tod), +-- season_next TEXT +-- REFERENCES SeasonLabel (season), +-- tod_next TEXT +-- REFERENCES TimeOfDay (tod), +-- notes TEXT, +-- PRIMARY KEY (period, season, tod) +-- ); +CREATE TABLE IF NOT EXISTS TimeOfDay +( + sequence INTEGER UNIQUE, + tod TEXT + PRIMARY KEY +); +CREATE TABLE IF NOT EXISTS TimePeriod +( + sequence INTEGER UNIQUE, + period INTEGER + PRIMARY KEY, + flag TEXT + REFERENCES TimePeriodType (label) +); +CREATE TABLE IF NOT EXISTS TimeSeason +( + period INTEGER + REFERENCES TimePeriod (period), + sequence INTEGER, + season TEXT + REFERENCES SeasonLabel (season), + notes TEXT, + PRIMARY KEY (period, sequence, season) +); +CREATE TABLE IF NOT EXISTS TimeSeasonSequential +( + period INTEGER + REFERENCES TimePeriod (period), + sequence INTEGER, + seas_seq TEXT, + season TEXT + REFERENCES SeasonLabel (season), + num_days REAL NOT NULL, + notes TEXT, + PRIMARY KEY (period, sequence, seas_seq, season), + CHECK (num_days > 0) +); +CREATE TABLE IF NOT EXISTS TimePeriodType +( + label TEXT PRIMARY KEY, + description TEXT +); +REPLACE INTO TimePeriodType +VALUES('e', 'existing vintages'); +REPLACE INTO TimePeriodType +VALUES('f', 'future'); +CREATE TABLE IF NOT EXISTS RPSRequirement +( + region TEXT NOT NULL, + period INTEGER NOT NULL + REFERENCES TimePeriod (period), + tech_group TEXT NOT NULL, + requirement REAL NOT NULL, + data_source TEXT, + dq_cred INTEGER + REFERENCES DataQualityCredibility (dq_cred), + dq_geog INTEGER + REFERENCES DataQualityGeography (dq_geog), + dq_struc INTEGER + REFERENCES DataQualityStructure (dq_struc), + dq_tech INTEGER + REFERENCES DataQualityTechnology (dq_tech), + dq_time INTEGER + REFERENCES DataQualityTime (dq_time), + data_id TEXT + REFERENCES DataSet (data_id), + notes TEXT, + FOREIGN KEY (data_source) REFERENCES DataSource (source_id), + FOREIGN KEY (region) REFERENCES Region (region), + FOREIGN KEY (tech_group) REFERENCES TechGroup (group_name), + PRIMARY KEY (region) +); +CREATE TABLE IF NOT EXISTS TechGroupMember +( + group_name TEXT, + tech TEXT, + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (tech) REFERENCES Technology (tech), + FOREIGN KEY (group_name) REFERENCES TechGroup (group_name), + PRIMARY KEY (group_name, tech) +); +CREATE TABLE IF NOT EXISTS Technology +( + tech TEXT NOT NULL, + flag TEXT NOT NULL, + sector TEXT, + category TEXT, + sub_category TEXT, + unlim_cap INTEGER NOT NULL DEFAULT 0, + annual INTEGER NOT NULL DEFAULT 0, + reserve INTEGER NOT NULL DEFAULT 0, + curtail INTEGER NOT NULL DEFAULT 0, + retire INTEGER NOT NULL DEFAULT 0, + flex INTEGER NOT NULL DEFAULT 0, + exchange INTEGER NOT NULL DEFAULT 0, + seas_stor INTEGER NOT NULL DEFAULT 0, + description TEXT, + data_id TEXT + REFERENCES DataSet (data_id), + FOREIGN KEY (flag) REFERENCES TechnologyType (label), + PRIMARY KEY (tech) +); +CREATE TABLE IF NOT EXISTS DataSource +( + source_id TEXT, + source TEXT, + notes TEXT, + data_id TEXT + REFERENCES DataSet (data_id), + PRIMARY KEY (source_id) +); +CREATE TABLE IF NOT EXISTS DataQualityCredibility +( + dq_cred INTEGER PRIMARY KEY, + description TEXT +); +REPLACE INTO DataQualityCredibility VALUES (1,'Excellent - A trustworthy source backed by strong analysis or direct measurements.'); +REPLACE INTO DataQualityCredibility VALUES (2,'Good - Trustworthy source. Partly based on assumptions or imperfect analysis.'); +REPLACE INTO DataQualityCredibility VALUES (3,'Acceptable - Acceptable source. May rely on many assumptions, shallow analysis, or rough measurement.'); +REPLACE INTO DataQualityCredibility VALUES (4,'Lacking - Questionable or unverified source. Poorly measured or weak analysis.'); +REPLACE INTO DataQualityCredibility VALUES (5,'Unacceptable - No or untrustworthy source. Unsupported assumption.'); +CREATE TABLE IF NOT EXISTS DataQualityGeography +( + dq_geog INTEGER PRIMARY KEY, + description TEXT +); +REPLACE INTO DataQualityGeography VALUES (1,'Excellent - From this region and at the correct aggregation level or a directly-applicable generic value.'); +REPLACE INTO DataQualityGeography VALUES (2,'Good - From an analogous region or the modelled region at incorrect aggregation level.'); +REPLACE INTO DataQualityGeography VALUES (3,'Acceptable - From a relevant but non-analogous region or highly aggregated.'); +REPLACE INTO DataQualityGeography VALUES (4,'Lacking - From a non-analogous region with limited relevance or a generic global value.'); +REPLACE INTO DataQualityGeography VALUES (5,'Unacceptable - From a region that is highly dissimilar to the modelled region, or from an unknown region.'); +CREATE TABLE IF NOT EXISTS DataQualityStructure +( + dq_struc INTEGER PRIMARY KEY, + description TEXT +); +REPLACE INTO DataQualityStructure VALUES (1,'Excellent - Excellent representation of the system, as good or better than other models.'); +REPLACE INTO DataQualityStructure VALUES (2,'Good - Well modelled, in line with what others are doing.'); +REPLACE INTO DataQualityStructure VALUES (3,'Acceptable - Room for improved representation but works for now.'); +REPLACE INTO DataQualityStructure VALUES (4,'Lacking - Poorly represented, overly simplified.'); +REPLACE INTO DataQualityStructure VALUES (5,'Unacceptable - Placeholder or dummy representation. Essentially not represented.'); +CREATE TABLE IF NOT EXISTS DataQualityTechnology +( + dq_tech INTEGER PRIMARY KEY, + description TEXT +); +REPLACE INTO DataQualityTechnology VALUES (1,'Excellent - For the modelled technology as represented. Directly applicable.'); +REPLACE INTO DataQualityTechnology VALUES (2,'Good - For the same general technology but not perfectly representative.'); +REPLACE INTO DataQualityTechnology VALUES (3,'Acceptable - For an analogous technology. Possibly a subset or general class. Roughly applicable.'); +REPLACE INTO DataQualityTechnology VALUES (4,'Lacking - Loosely representative. A niche subset or overbroad general class of the technology.'); +REPLACE INTO DataQualityTechnology VALUES (5,'Unacceptable - For a dissimilar or unknown technology. Unknown or poor applicability.'); +CREATE TABLE IF NOT EXISTS DataQualityTime +( + dq_time INTEGER PRIMARY KEY, + description TEXT +); +REPLACE INTO DataQualityTime VALUES (1,'Excellent - From or directly applicable to the modelled time.'); +REPLACE INTO DataQualityTime VALUES (2,'Good - From a different but similar time or only slightly out of date. Still highly relevant.'); +REPLACE INTO DataQualityTime VALUES (3,'Acceptable - From a somewhat similar time or several years out of date but still relevant.'); +REPLACE INTO DataQualityTime VALUES (4,'Lacking - From a time with different conditions or significantly out of date. Questionable relevance.'); +REPLACE INTO DataQualityTime VALUES (5,'Unacceptable - From an irrelevant time or badly out of date.'); +CREATE TABLE IF NOT EXISTS DataSet +( + data_id TEXT PRIMARY KEY, + label TEXT, + version TEXT, + description TEXT, + status TEXT, + author TEXT, + date TEXT, + parent_id TEXT + REFERENCES DataSet (data_id), + changelog TEXT, + notes TEXT +); + +COMMIT; +PRAGMA FOREIGN_KEYS = 1; \ No newline at end of file diff --git a/representative_periods/canoe_schema_v4_0.sql b/representative_periods/canoe_schema_v4_0.sql new file mode 100644 index 0000000..0f51def --- /dev/null +++ b/representative_periods/canoe_schema_v4_0.sql @@ -0,0 +1,1694 @@ +PRAGMA foreign_keys = OFF; +BEGIN TRANSACTION; + +-- ============================================================ +-- Metadata +-- ============================================================ + +CREATE TABLE IF NOT EXISTS metadata +( + element TEXT PRIMARY KEY, + value INT, + notes TEXT +); +REPLACE INTO metadata VALUES ('DB_MAJOR', 4, 'DB major version number'); +REPLACE INTO metadata VALUES ('DB_MINOR', 0, 'DB minor version number'); + +CREATE TABLE IF NOT EXISTS metadata_real +( + element TEXT PRIMARY KEY, + value REAL, + notes TEXT +); +REPLACE INTO metadata_real VALUES ('global_discount_rate', 0.03, 'Discount Rate for future costs'); +REPLACE INTO metadata_real VALUES ('default_loan_rate', 0.03, 'Default Loan Rate if not specified in loan_rate table'); + +-- ============================================================ +-- Label / registry tables +-- ============================================================ +CREATE TABLE IF NOT EXISTS commodity_label +( + commodity TEXT PRIMARY KEY, + notes TEXT +); + +CREATE TABLE IF NOT EXISTS technology_label +( + tech TEXT PRIMARY KEY, + notes TEXT +); + +CREATE TABLE IF NOT EXISTS tech_group_label +( + group_name TEXT PRIMARY KEY, + notes TEXT +); + +CREATE TABLE IF NOT EXISTS sector_label +( + sector TEXT PRIMARY KEY, + notes TEXT +); + +-- ============================================================ +-- Enum / type tables +-- ============================================================ +CREATE TABLE IF NOT EXISTS commodity_type +( + label TEXT PRIMARY KEY, + description TEXT +); +REPLACE INTO commodity_type VALUES ('s', 'source commodity'); +REPLACE INTO commodity_type VALUES ('a', 'annual commodity'); +REPLACE INTO commodity_type VALUES ('p', 'physical commodity'); +REPLACE INTO commodity_type VALUES ('d', 'demand commodity'); +REPLACE INTO commodity_type VALUES ('e', 'emissions commodity'); +REPLACE INTO commodity_type VALUES ('w', 'waste commodity'); +REPLACE INTO commodity_type VALUES ('wa', 'waste annual commodity'); +REPLACE INTO commodity_type VALUES ('wp', 'waste physical commodity'); + +CREATE TABLE IF NOT EXISTS technology_type +( + label TEXT PRIMARY KEY, + description TEXT +); +REPLACE INTO technology_type VALUES ('p', 'production technology'); +REPLACE INTO technology_type VALUES ('pb', 'baseload production technology'); +REPLACE INTO technology_type VALUES ('ps', 'storage production technology'); + +CREATE TABLE IF NOT EXISTS time_period_type +( + label TEXT PRIMARY KEY, + description TEXT +); +REPLACE INTO time_period_type VALUES ('e', 'existing vintages'); +REPLACE INTO time_period_type VALUES ('f', 'future'); + +CREATE TABLE IF NOT EXISTS operator +( + operator TEXT PRIMARY KEY, + notes TEXT +); +REPLACE INTO operator VALUES ('e', 'equal to'); +REPLACE INTO operator VALUES ('le', 'less than or equal to'); +REPLACE INTO operator VALUES ('ge', 'greater than or equal to'); + +-- ============================================================ +-- Data quality and data source tables (custom) +-- ============================================================ +CREATE TABLE IF NOT EXISTS data_quality_credibility +( + dq_cred INTEGER PRIMARY KEY, + description TEXT +); +REPLACE INTO data_quality_credibility VALUES (1, 'Excellent - A trustworthy source backed by strong analysis or direct measurements.'); +REPLACE INTO data_quality_credibility VALUES (2, 'Good - Trustworthy source. Partly based on assumptions or imperfect analysis.'); +REPLACE INTO data_quality_credibility VALUES (3, 'Acceptable - Acceptable source. May rely on many assumptions, shallow analysis, or rough measurement.'); +REPLACE INTO data_quality_credibility VALUES (4, 'Lacking - Questionable or unverified source. Poorly measured or weak analysis.'); +REPLACE INTO data_quality_credibility VALUES (5, 'Unacceptable - No or untrustworthy source. Unsupported assumption.'); + +CREATE TABLE IF NOT EXISTS data_quality_geography +( + dq_geog INTEGER PRIMARY KEY, + description TEXT +); +REPLACE INTO data_quality_geography VALUES (1, 'Excellent - From this region and at the correct aggregation level or a directly-applicable generic value.'); +REPLACE INTO data_quality_geography VALUES (2, 'Good - From an analogous region or the modelled region at incorrect aggregation level.'); +REPLACE INTO data_quality_geography VALUES (3, 'Acceptable - From a relevant but non-analogous region or highly aggregated.'); +REPLACE INTO data_quality_geography VALUES (4, 'Lacking - From a non-analogous region with limited relevance or a generic global value.'); +REPLACE INTO data_quality_geography VALUES (5, 'Unacceptable - From a region that is highly dissimilar to the modelled region, or from an unknown region.'); + +CREATE TABLE IF NOT EXISTS data_quality_structure +( + dq_struc INTEGER PRIMARY KEY, + description TEXT +); +REPLACE INTO data_quality_structure VALUES (1, 'Excellent - Excellent representation of the system, as good or better than other models.'); +REPLACE INTO data_quality_structure VALUES (2, 'Good - Well modelled, in line with what others are doing.'); +REPLACE INTO data_quality_structure VALUES (3, 'Acceptable - Room for improved representation but works for now.'); +REPLACE INTO data_quality_structure VALUES (4, 'Lacking - Poorly represented, overly simplified.'); +REPLACE INTO data_quality_structure VALUES (5, 'Unacceptable - Placeholder or dummy representation. Essentially not represented.'); + +CREATE TABLE IF NOT EXISTS data_quality_technology +( + dq_tech INTEGER PRIMARY KEY, + description TEXT +); +REPLACE INTO data_quality_technology VALUES (1, 'Excellent - For the modelled technology as represented. Directly applicable.'); +REPLACE INTO data_quality_technology VALUES (2, 'Good - For the same general technology but not perfectly representative.'); +REPLACE INTO data_quality_technology VALUES (3, 'Acceptable - For an analogous technology. Possibly a subset or general class. Roughly applicable.'); +REPLACE INTO data_quality_technology VALUES (4, 'Lacking - Loosely representative. A niche subset or overbroad general class of the technology.'); +REPLACE INTO data_quality_technology VALUES (5, 'Unacceptable - For a dissimilar or unknown technology. Unknown or poor applicability.'); + +CREATE TABLE IF NOT EXISTS data_quality_time +( + dq_time INTEGER PRIMARY KEY, + description TEXT +); +REPLACE INTO data_quality_time VALUES (1, 'Excellent - From or directly applicable to the modelled time.'); +REPLACE INTO data_quality_time VALUES (2, 'Good - From a different but similar time or only slightly out of date. Still highly relevant.'); +REPLACE INTO data_quality_time VALUES (3, 'Acceptable - From a somewhat similar time or several years out of date but still relevant.'); +REPLACE INTO data_quality_time VALUES (4, 'Lacking - From a time with different conditions or significantly out of date. Questionable relevance.'); +REPLACE INTO data_quality_time VALUES (5, 'Unacceptable - From an irrelevant time or badly out of date.'); + +CREATE TABLE IF NOT EXISTS data_source_label +( + source_id TEXT PRIMARY KEY, + notes TEXT +); + +CREATE TABLE IF NOT EXISTS data_set +( + data_id TEXT PRIMARY KEY, + label TEXT, + version TEXT, + description TEXT, + status TEXT, + author TEXT, + date TEXT, + parent_id TEXT + REFERENCES data_set (data_id), + changelog TEXT, + notes TEXT +); + +CREATE TABLE IF NOT EXISTS data_source +( + source_id TEXT, + source TEXT, + notes TEXT, + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (source_id) REFERENCES data_source_label (source_id), + PRIMARY KEY (source_id, data_id) +); + +-- ============================================================ +-- Time tables +-- ============================================================ +CREATE TABLE IF NOT EXISTS time_period +( + sequence INTEGER UNIQUE, + period INTEGER PRIMARY KEY, + flag TEXT + REFERENCES time_period_type (label) +); + +CREATE TABLE IF NOT EXISTS time_of_day +( + sequence INTEGER UNIQUE, + tod TEXT PRIMARY KEY, + hours REAL NOT NULL DEFAULT 1, + notes TEXT, + CHECK (hours > 0) +); + +CREATE TABLE IF NOT EXISTS time_season +( + sequence INTEGER UNIQUE, + season TEXT PRIMARY KEY, + segment_fraction REAL NOT NULL, + notes TEXT, + CHECK (segment_fraction >= 0 AND segment_fraction <= 1) +); + +CREATE TABLE IF NOT EXISTS time_season_sequential +( + sequence INTEGER UNIQUE, + seas_seq TEXT PRIMARY KEY, + season TEXT + REFERENCES time_season (season), + segment_fraction REAL NOT NULL, + notes TEXT, + CHECK (segment_fraction >= 0 AND segment_fraction <= 1) +); + +-- ============================================================ +-- Region +-- ============================================================ +CREATE TABLE IF NOT EXISTS region +( + region TEXT PRIMARY KEY, + notes TEXT +); + +-- ============================================================ +-- Core model definition tables +-- ============================================================ +CREATE TABLE IF NOT EXISTS commodity +( + name TEXT, + flag TEXT + REFERENCES commodity_type (label), + description TEXT, + units TEXT, + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (name) REFERENCES commodity_label (commodity), + PRIMARY KEY (name, data_id) +); + +CREATE TABLE IF NOT EXISTS technology +( + tech TEXT NOT NULL, + flag TEXT NOT NULL, + sector TEXT, + category TEXT, + sub_category TEXT, + unlim_cap INTEGER NOT NULL DEFAULT 0, + annual INTEGER NOT NULL DEFAULT 0, + reserve INTEGER NOT NULL DEFAULT 0, + curtail INTEGER NOT NULL DEFAULT 0, + retire INTEGER NOT NULL DEFAULT 0, + flex INTEGER NOT NULL DEFAULT 0, + exchange INTEGER NOT NULL DEFAULT 0, + seas_stor INTEGER NOT NULL DEFAULT 0, + description TEXT, + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (flag) REFERENCES technology_type (label), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + PRIMARY KEY (tech, data_id) +); + +CREATE TABLE IF NOT EXISTS tech_group +( + group_name TEXT, + notes TEXT, + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (group_name) REFERENCES tech_group_label (group_name), + PRIMARY KEY (group_name, data_id) +); + +CREATE TABLE IF NOT EXISTS tech_group_member +( + group_name TEXT, + tech TEXT, + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + FOREIGN KEY (group_name) REFERENCES tech_group_label (group_name), + PRIMARY KEY (group_name, tech, data_id) +); + +-- ============================================================ +-- Data tables +-- All include: data_id (in PK), data_source, dq_cred/geog/struc/tech/time +-- ============================================================ +CREATE TABLE IF NOT EXISTS capacity_credit +( + region TEXT, + period INTEGER + REFERENCES time_period (period), + tech TEXT, + vintage INTEGER, + credit REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + PRIMARY KEY (region, period, tech, vintage, data_id), + CHECK (credit >= 0 AND credit <= 1) +); + +CREATE TABLE IF NOT EXISTS capacity_factor_process +( + region TEXT, + season TEXT + REFERENCES time_season (season), + tod TEXT + REFERENCES time_of_day (tod), + tech TEXT, + vintage INTEGER, + factor REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + PRIMARY KEY (region, season, tod, tech, vintage, data_id), + CHECK (factor >= 0 AND factor <= 1) +); + +CREATE TABLE IF NOT EXISTS capacity_factor_tech +( + region TEXT, + season TEXT + REFERENCES time_season (season), + tod TEXT + REFERENCES time_of_day (tod), + tech TEXT, + factor REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + PRIMARY KEY (region, season, tod, tech, data_id), + CHECK (factor >= 0 AND factor <= 1) +); + +CREATE TABLE IF NOT EXISTS capacity_to_activity +( + region TEXT, + tech TEXT, + c2a REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + PRIMARY KEY (region, tech, data_id) +); + +CREATE TABLE IF NOT EXISTS construction_input +( + region TEXT, + input_comm TEXT, + tech TEXT, + vintage INTEGER + REFERENCES time_period (period), + value REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + FOREIGN KEY (input_comm) REFERENCES commodity_label (commodity), + PRIMARY KEY (region, input_comm, tech, vintage, data_id) +); + +CREATE TABLE IF NOT EXISTS cost_emission +( + region TEXT, + period INTEGER + REFERENCES time_period (period), + emis_comm TEXT NOT NULL, + cost REAL NOT NULL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (emis_comm) REFERENCES commodity_label (commodity), + PRIMARY KEY (region, period, emis_comm, data_id) +); + +CREATE TABLE IF NOT EXISTS cost_fixed +( + region TEXT NOT NULL, + period INTEGER NOT NULL + REFERENCES time_period (period), + tech TEXT NOT NULL, + vintage INTEGER NOT NULL + REFERENCES time_period (period), + cost REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + PRIMARY KEY (region, period, tech, vintage, data_id) +); + +CREATE TABLE IF NOT EXISTS cost_invest +( + region TEXT, + tech TEXT, + vintage INTEGER + REFERENCES time_period (period), + cost REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + PRIMARY KEY (region, tech, vintage, data_id) +); + +CREATE TABLE IF NOT EXISTS cost_variable +( + region TEXT NOT NULL, + period INTEGER NOT NULL + REFERENCES time_period (period), + tech TEXT NOT NULL, + vintage INTEGER NOT NULL + REFERENCES time_period (period), + cost REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + PRIMARY KEY (region, period, tech, vintage, data_id) +); + +CREATE TABLE IF NOT EXISTS demand +( + region TEXT, + period INTEGER + REFERENCES time_period (period), + commodity TEXT, + demand REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (commodity) REFERENCES commodity_label (commodity), + PRIMARY KEY (region, period, commodity, data_id) +); + +CREATE TABLE IF NOT EXISTS demand_specific_distribution +( + region TEXT, + period INTEGER + REFERENCES time_period (period), + season TEXT + REFERENCES time_season (season), + tod TEXT + REFERENCES time_of_day (tod), + demand_name TEXT, + dsd REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (demand_name) REFERENCES commodity_label (commodity), + PRIMARY KEY (region, period, season, tod, demand_name, data_id), + CHECK (dsd >= 0 AND dsd <= 1) +); + +CREATE TABLE IF NOT EXISTS end_of_life_output +( + region TEXT, + tech TEXT, + vintage INTEGER + REFERENCES time_period (period), + output_comm TEXT, + value REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + FOREIGN KEY (output_comm) REFERENCES commodity_label (commodity), + PRIMARY KEY (region, tech, vintage, output_comm, data_id) +); + +CREATE TABLE IF NOT EXISTS efficiency +( + region TEXT, + input_comm TEXT, + tech TEXT, + vintage INTEGER + REFERENCES time_period (period), + output_comm TEXT, + efficiency REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + FOREIGN KEY (input_comm) REFERENCES commodity_label (commodity), + FOREIGN KEY (output_comm) REFERENCES commodity_label (commodity), + PRIMARY KEY (region, input_comm, tech, vintage, output_comm, data_id), + CHECK (efficiency > 0) +); + +CREATE TABLE IF NOT EXISTS efficiency_variable +( + region TEXT, + season TEXT + REFERENCES time_season (season), + tod TEXT + REFERENCES time_of_day (tod), + input_comm TEXT, + tech TEXT, + vintage INTEGER + REFERENCES time_period (period), + output_comm TEXT, + efficiency REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + FOREIGN KEY (input_comm) REFERENCES commodity_label (commodity), + FOREIGN KEY (output_comm) REFERENCES commodity_label (commodity), + PRIMARY KEY (region, season, tod, input_comm, tech, vintage, output_comm, data_id), + CHECK (efficiency > 0) +); + +CREATE TABLE IF NOT EXISTS emission_activity +( + region TEXT, + emis_comm TEXT, + input_comm TEXT, + tech TEXT, + vintage INTEGER + REFERENCES time_period (period), + output_comm TEXT, + activity REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + FOREIGN KEY (emis_comm) REFERENCES commodity_label (commodity), + FOREIGN KEY (input_comm) REFERENCES commodity_label (commodity), + FOREIGN KEY (output_comm) REFERENCES commodity_label (commodity), + PRIMARY KEY (region, emis_comm, input_comm, tech, vintage, output_comm, data_id) +); + +CREATE TABLE IF NOT EXISTS emission_embodied +( + region TEXT, + emis_comm TEXT, + tech TEXT, + vintage INTEGER + REFERENCES time_period (period), + value REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + FOREIGN KEY (emis_comm) REFERENCES commodity_label (commodity), + PRIMARY KEY (region, emis_comm, tech, vintage, data_id) +); + +CREATE TABLE IF NOT EXISTS emission_end_of_life +( + region TEXT, + emis_comm TEXT, + tech TEXT, + vintage INTEGER + REFERENCES time_period (period), + value REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + FOREIGN KEY (emis_comm) REFERENCES commodity_label (commodity), + PRIMARY KEY (region, emis_comm, tech, vintage, data_id) +); + +CREATE TABLE IF NOT EXISTS existing_capacity +( + region TEXT, + tech TEXT, + vintage INTEGER + REFERENCES time_period (period), + capacity REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + PRIMARY KEY (region, tech, vintage, data_id) +); + +CREATE TABLE IF NOT EXISTS loan_lifetime_process +( + region TEXT, + tech TEXT, + vintage INTEGER + REFERENCES time_period (period), + lifetime REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + PRIMARY KEY (region, tech, vintage, data_id) +); + +CREATE TABLE IF NOT EXISTS loan_rate +( + region TEXT, + tech TEXT, + vintage INTEGER + REFERENCES time_period (period), + rate REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + PRIMARY KEY (region, tech, vintage, data_id) +); + +CREATE TABLE IF NOT EXISTS lifetime_process +( + region TEXT, + tech TEXT, + vintage INTEGER + REFERENCES time_period (period), + lifetime REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + PRIMARY KEY (region, tech, vintage, data_id) +); + +CREATE TABLE IF NOT EXISTS lifetime_tech +( + region TEXT, + tech TEXT, + lifetime REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + PRIMARY KEY (region, tech, data_id) +); + +CREATE TABLE IF NOT EXISTS limit_growth_capacity +( + region TEXT, + tech_or_group TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES operator (operator), + rate REAL NOT NULL DEFAULT 0, + seed REAL NOT NULL DEFAULT 0, + seed_units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + PRIMARY KEY (region, tech_or_group, operator, data_id) +); + +CREATE TABLE IF NOT EXISTS limit_degrowth_capacity +( + region TEXT, + tech_or_group TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES operator (operator), + rate REAL NOT NULL DEFAULT 0, + seed REAL NOT NULL DEFAULT 0, + seed_units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + PRIMARY KEY (region, tech_or_group, operator, data_id) +); + +CREATE TABLE IF NOT EXISTS limit_growth_new_capacity +( + region TEXT, + tech_or_group TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES operator (operator), + rate REAL NOT NULL DEFAULT 0, + seed REAL NOT NULL DEFAULT 0, + seed_units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + PRIMARY KEY (region, tech_or_group, operator, data_id) +); + +CREATE TABLE IF NOT EXISTS limit_degrowth_new_capacity +( + region TEXT, + tech_or_group TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES operator (operator), + rate REAL NOT NULL DEFAULT 0, + seed REAL NOT NULL DEFAULT 0, + seed_units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + PRIMARY KEY (region, tech_or_group, operator, data_id) +); + +CREATE TABLE IF NOT EXISTS limit_growth_new_capacity_delta +( + region TEXT, + tech_or_group TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES operator (operator), + rate REAL NOT NULL DEFAULT 0, + seed REAL NOT NULL DEFAULT 0, + seed_units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + PRIMARY KEY (region, tech_or_group, operator, data_id) +); + +CREATE TABLE IF NOT EXISTS limit_degrowth_new_capacity_delta +( + region TEXT, + tech_or_group TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES operator (operator), + rate REAL NOT NULL DEFAULT 0, + seed REAL NOT NULL DEFAULT 0, + seed_units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + PRIMARY KEY (region, tech_or_group, operator, data_id) +); + +CREATE TABLE IF NOT EXISTS limit_storage_level_fraction +( + region TEXT, + season TEXT + REFERENCES time_season (season), + tod TEXT + REFERENCES time_of_day (tod), + tech TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES operator (operator), + fraction REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + CHECK (fraction >= 0 AND fraction <= 1), + PRIMARY KEY (region, season, tod, tech, operator, data_id) +); + +CREATE TABLE IF NOT EXISTS limit_activity +( + region TEXT, + period INTEGER + REFERENCES time_period (period), + tech_or_group TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES operator (operator), + activity REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + PRIMARY KEY (region, period, tech_or_group, operator, data_id) +); + +CREATE TABLE IF NOT EXISTS limit_activity_share +( + region TEXT, + period INTEGER + REFERENCES time_period (period), + sub_group TEXT, + super_group TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES operator (operator), + share REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + PRIMARY KEY (region, period, sub_group, super_group, operator, data_id) +); + +CREATE TABLE IF NOT EXISTS limit_annual_capacity_factor +( + region TEXT, + tech_or_group TEXT, + vintage INTEGER + REFERENCES time_period (period), + output_comm TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES operator (operator), + factor REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (output_comm) REFERENCES commodity_label (commodity), + PRIMARY KEY (region, tech_or_group, vintage, output_comm, operator, data_id), + CHECK (factor >= 0 AND factor <= 1) +); + +CREATE TABLE IF NOT EXISTS limit_capacity +( + region TEXT, + period INTEGER + REFERENCES time_period (period), + tech_or_group TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES operator (operator), + capacity REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + PRIMARY KEY (region, period, tech_or_group, operator, data_id) +); + +CREATE TABLE IF NOT EXISTS limit_capacity_share +( + region TEXT, + period INTEGER + REFERENCES time_period (period), + sub_group TEXT, + super_group TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES operator (operator), + share REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + PRIMARY KEY (region, period, sub_group, super_group, operator, data_id) +); + +CREATE TABLE IF NOT EXISTS limit_new_capacity +( + region TEXT, + tech_or_group TEXT, + vintage INTEGER + REFERENCES time_period (period), + operator TEXT NOT NULL DEFAULT "le" + REFERENCES operator (operator), + new_cap REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + PRIMARY KEY (region, tech_or_group, vintage, operator, data_id) +); + +CREATE TABLE IF NOT EXISTS limit_new_capacity_share +( + region TEXT, + sub_group TEXT, + super_group TEXT, + vintage INTEGER + REFERENCES time_period (period), + operator TEXT NOT NULL DEFAULT "le" + REFERENCES operator (operator), + share REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + PRIMARY KEY (region, sub_group, super_group, vintage, operator, data_id) +); + +CREATE TABLE IF NOT EXISTS limit_resource +( + region TEXT, + tech_or_group TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES operator (operator), + cum_act REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + PRIMARY KEY (region, tech_or_group, operator, data_id) +); + +CREATE TABLE IF NOT EXISTS limit_seasonal_capacity_factor +( + region TEXT + REFERENCES region (region), + season TEXT + REFERENCES time_season (season), + tech_or_group TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES operator (operator), + factor REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + PRIMARY KEY (region, season, tech_or_group, operator, data_id) +); + +CREATE TABLE IF NOT EXISTS limit_tech_input_split +( + region TEXT, + period INTEGER + REFERENCES time_period (period), + input_comm TEXT, + tech TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES operator (operator), + proportion REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + FOREIGN KEY (input_comm) REFERENCES commodity_label (commodity), + PRIMARY KEY (region, period, input_comm, tech, operator, data_id) +); + +CREATE TABLE IF NOT EXISTS limit_tech_input_split_annual +( + region TEXT, + period INTEGER + REFERENCES time_period (period), + input_comm TEXT, + tech TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES operator (operator), + proportion REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + PRIMARY KEY (region, period, input_comm, tech, operator, data_id) +); + +CREATE TABLE IF NOT EXISTS limit_tech_output_split +( + region TEXT, + period INTEGER + REFERENCES time_period (period), + tech TEXT, + output_comm TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES operator (operator), + proportion REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + FOREIGN KEY (output_comm) REFERENCES commodity_label (commodity), + PRIMARY KEY (region, period, tech, output_comm, operator, data_id) +); + +CREATE TABLE IF NOT EXISTS limit_tech_output_split_annual +( + region TEXT, + period INTEGER + REFERENCES time_period (period), + tech TEXT, + output_comm TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES operator (operator), + proportion REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + FOREIGN KEY (output_comm) REFERENCES commodity_label (commodity), + PRIMARY KEY (region, period, tech, output_comm, operator, data_id) +); + +CREATE TABLE IF NOT EXISTS limit_emission +( + region TEXT, + period INTEGER + REFERENCES time_period (period), + emis_comm TEXT, + operator TEXT NOT NULL DEFAULT "le" + REFERENCES operator (operator), + value REAL, + units TEXT, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (emis_comm) REFERENCES commodity_label (commodity), + PRIMARY KEY (region, period, emis_comm, operator, data_id) +); + +CREATE TABLE IF NOT EXISTS linked_tech +( + primary_region TEXT, + primary_tech TEXT, + emis_comm TEXT, + driven_tech TEXT, + notes TEXT, + data_source TEXT, + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (primary_tech) REFERENCES technology_label (tech), + FOREIGN KEY (driven_tech) REFERENCES technology_label (tech), + FOREIGN KEY (emis_comm) REFERENCES commodity_label (commodity), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + PRIMARY KEY (primary_region, primary_tech, emis_comm, data_id) +); + +CREATE TABLE IF NOT EXISTS planning_reserve_margin +( + region TEXT, + margin REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (region) REFERENCES region (region), + PRIMARY KEY (region, data_id) +); + +CREATE TABLE IF NOT EXISTS ramp_down_hourly +( + region TEXT, + tech TEXT, + rate REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + PRIMARY KEY (region, tech, data_id) +); + +CREATE TABLE IF NOT EXISTS ramp_up_hourly +( + region TEXT, + tech TEXT, + rate REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + PRIMARY KEY (region, tech, data_id) +); + +CREATE TABLE IF NOT EXISTS reserve_capacity_derate +( + region TEXT, + season TEXT + REFERENCES time_season (season), + tech TEXT, + vintage INTEGER, + factor REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + PRIMARY KEY (region, season, tech, vintage, data_id), + CHECK (factor >= 0 AND factor <= 1) +); + +CREATE TABLE IF NOT EXISTS storage_duration +( + region TEXT, + tech TEXT, + duration REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + PRIMARY KEY (region, tech, data_id) +); + +CREATE TABLE IF NOT EXISTS lifetime_survival_curve +( + region TEXT NOT NULL, + period INTEGER NOT NULL, + tech TEXT NOT NULL, + vintage INTEGER NOT NULL + REFERENCES time_period (period), + fraction REAL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech) REFERENCES technology_label (tech), + PRIMARY KEY (region, period, tech, vintage, data_id) +); + +CREATE TABLE IF NOT EXISTS rps_requirement +( + region TEXT NOT NULL + REFERENCES region (region), + period INTEGER NOT NULL + REFERENCES time_period (period), + tech_group TEXT NOT NULL, + requirement REAL NOT NULL, + notes TEXT, + data_source TEXT, + dq_cred INTEGER REFERENCES data_quality_credibility (dq_cred), + dq_geog INTEGER REFERENCES data_quality_geography (dq_geog), + dq_struc INTEGER REFERENCES data_quality_structure (dq_struc), + dq_tech INTEGER REFERENCES data_quality_technology (dq_tech), + dq_time INTEGER REFERENCES data_quality_time (dq_time), + data_id TEXT + REFERENCES data_set (data_id), + FOREIGN KEY (data_source) REFERENCES data_source_label (source_id), + FOREIGN KEY (tech_group) REFERENCES tech_group_label (group_name), + PRIMARY KEY (region, period, tech_group, data_id) +); + +CREATE TABLE IF NOT EXISTS output_dual_variable +( + scenario TEXT, + constraint_name TEXT, + dual REAL, + PRIMARY KEY (constraint_name, scenario) +); +CREATE TABLE IF NOT EXISTS output_objective +( + scenario TEXT, + objective_name TEXT, + total_system_cost REAL +); +CREATE TABLE IF NOT EXISTS output_curtailment +( + scenario TEXT, + region TEXT, + sector TEXT, + period INTEGER + REFERENCES time_period (period), + season TEXT + REFERENCES time_season (season), + tod TEXT + REFERENCES time_of_day (tod), + input_comm TEXT + REFERENCES commodity_label (commodity), + tech TEXT + REFERENCES technology_label (tech), + vintage INTEGER + REFERENCES time_period (period), + output_comm TEXT + REFERENCES commodity_label (commodity), + curtailment REAL, + units TEXT, + PRIMARY KEY (region, scenario, period, season, tod, input_comm, tech, vintage, output_comm) +); +CREATE TABLE IF NOT EXISTS output_net_capacity +( + scenario TEXT, + region TEXT, + sector TEXT + REFERENCES sector_label (sector), + period INTEGER + REFERENCES time_period (period), + tech TEXT + REFERENCES technology_label (tech), + vintage INTEGER + REFERENCES time_period (period), + capacity REAL, + units TEXT, + PRIMARY KEY (region, scenario, period, tech, vintage) +); +CREATE TABLE IF NOT EXISTS output_built_capacity +( + scenario TEXT, + region TEXT, + sector TEXT + REFERENCES sector_label (sector), + tech TEXT + REFERENCES technology_label (tech), + vintage INTEGER + REFERENCES time_period (period), + capacity REAL, + units TEXT, + PRIMARY KEY (region, scenario, tech, vintage) +); +CREATE TABLE IF NOT EXISTS output_retired_capacity +( + scenario TEXT, + region TEXT, + sector TEXT + REFERENCES sector_label (sector), + period INTEGER + REFERENCES time_period (period), + tech TEXT + REFERENCES technology_label (tech), + vintage INTEGER + REFERENCES time_period (period), + cap_eol REAL, + cap_early REAL, + units TEXT, + PRIMARY KEY (region, scenario, period, tech, vintage) +); +CREATE TABLE IF NOT EXISTS output_flow_in +( + scenario TEXT, + region TEXT, + sector TEXT + REFERENCES sector_label (sector), + period INTEGER + REFERENCES time_period (period), + season TEXT + REFERENCES time_season (season), + tod TEXT + REFERENCES time_of_day (tod), + input_comm TEXT + REFERENCES commodity_label (commodity), + tech TEXT + REFERENCES technology_label (tech), + vintage INTEGER + REFERENCES time_period (period), + output_comm TEXT + REFERENCES commodity_label (commodity), + flow REAL, + units TEXT, + PRIMARY KEY (region, scenario, period, season, tod, input_comm, tech, vintage, output_comm) +); +CREATE TABLE IF NOT EXISTS output_flow_out +( + scenario TEXT, + region TEXT, + sector TEXT + REFERENCES sector_label (sector), + period INTEGER + REFERENCES time_period (period), + season TEXT + REFERENCES time_season (season), + tod TEXT + REFERENCES time_of_day (tod), + input_comm TEXT + REFERENCES commodity_label (commodity), + tech TEXT + REFERENCES technology_label (tech), + vintage INTEGER + REFERENCES time_period (period), + output_comm TEXT + REFERENCES commodity_label (commodity), + flow REAL, + units TEXT, + PRIMARY KEY (region, scenario, period, season, tod, input_comm, tech, vintage, output_comm) +); +CREATE TABLE IF NOT EXISTS output_storage_level +( + scenario TEXT, + region TEXT, + sector TEXT + REFERENCES sector_label (sector), + period INTEGER + REFERENCES time_period (period), + season TEXT, + tod TEXT + REFERENCES time_of_day (tod), + tech TEXT + REFERENCES technology_label (tech), + vintage INTEGER + REFERENCES time_period (period), + level REAL, + units TEXT, + PRIMARY KEY (scenario, region, period, season, tod, tech, vintage) +); +CREATE TABLE IF NOT EXISTS output_emission +( + scenario TEXT, + region TEXT, + sector TEXT + REFERENCES sector_label (sector), + period INTEGER + REFERENCES time_period (period), + emis_comm TEXT + REFERENCES commodity_label (commodity), + tech TEXT + REFERENCES technology_label (tech), + vintage INTEGER + REFERENCES time_period (period), + emission REAL, + units TEXT, + PRIMARY KEY (region, scenario, period, emis_comm, tech, vintage) +); +CREATE TABLE IF NOT EXISTS output_cost +( + scenario TEXT, + region TEXT, + sector TEXT REFERENCES sector_label (sector), + period INTEGER REFERENCES time_period (period), + tech TEXT REFERENCES technology_label (tech), + vintage INTEGER REFERENCES time_period (period), + d_invest REAL, + d_fixed REAL, + d_var REAL, + d_emiss REAL, + invest REAL, + fixed REAL, + var REAL, + emiss REAL, + units TEXT, + PRIMARY KEY (scenario, region, period, tech, vintage), + FOREIGN KEY (vintage) REFERENCES time_period (period), + FOREIGN KEY (tech) REFERENCES technology_label (tech) +); +CREATE TABLE IF NOT EXISTS myopic_efficiency +( + base_year integer, + region text, + input_comm TEXT + REFERENCES commodity_label (commodity), + tech TEXT + REFERENCES technology_label (tech), + vintage INTEGER + REFERENCES time_period (period), + output_comm TEXT + REFERENCES commodity_label (commodity), + efficiency real, + lifetime integer, + PRIMARY KEY (region, input_comm, tech, vintage, output_comm) +); +-- for efficient searching by rtv: +-- CREATE INDEX IF NOT EXISTS region_tech_vintage ON myopic_efficiency (region, tech, vintage); + +CREATE TABLE IF NOT EXISTS output_flow_out_summary +( + scenario TEXT, + region TEXT, + sector TEXT + REFERENCES sector_label (sector), + period INTEGER + REFERENCES time_period (period), + input_comm TEXT + REFERENCES commodity_label (commodity), + tech TEXT + REFERENCES technology_label (tech), + vintage INTEGER + REFERENCES time_period (period), + output_comm TEXT + REFERENCES commodity_label (commodity), + flow REAL, + PRIMARY KEY (scenario, region, period, input_comm, tech, vintage, output_comm) +); + +COMMIT; +PRAGMA foreign_keys = ON; diff --git a/representative_periods/clustering.py b/representative_periods/clustering.py new file mode 100644 index 0000000..5d7e7d9 --- /dev/null +++ b/representative_periods/clustering.py @@ -0,0 +1,342 @@ +import pandas as pd +import matplotlib +matplotlib.use('Agg') +import matplotlib.pyplot as pp +from . import feature_selection as fi +from . import utils +from . import pca + +import tsam.timeseriesaggregation as tsam +import os + +this_dir = os.path.realpath(os.path.dirname(__file__)) + "/" +out_data = this_dir + "clustering_output_data/" + +initialised = False +def reset(): + global initialised + initialised = False + + +def init(): + + global initialised # safety! only do this once + + if initialised: return + + if not os.path.isdir(out_data): os.mkdir(out_data) + + ## Make output data directories or clear them out + out_dirs = [ + 'reduced_timeseries/', + 'accuracy_indicators/', + 'recreated_timeseries/', + 'representative_periods/', + 'duration_curve_plots/', + 'timeseries_plots/' + ] + + for dir in out_dirs: + if not os.path.isdir(out_data + dir): os.mkdir(out_data + dir) + + # Empty output data directories + for file in os.listdir(out_data + dir): + try: os.remove(out_data + dir + file) + except Exception as e: print(e) + + initialised = True + print("\nInitialised clustering.\n") + + + +def run(show_plots=False): + + init() + + # If not rerunning clustering, try to fetch from cache + if not utils.config.get('rerun_clustering', True): + import shutil + method = utils.config.get('clustering_method', 'hierarchical') + final_periods = utils.config['final_periods'] + csv_name = f"{method}_{final_periods}p.csv" + seq_name = f"sequence_{final_periods}p.csv" + + periods_path = out_data + "representative_periods/" + csv_name + sequence_path = out_data + "representative_periods/" + seq_name + + if os.path.exists(periods_path) and os.path.exists(sequence_path): + print(f"Skipping clustering. Loading {final_periods} periods from cache.") + shutil.copy(periods_path, this_dir + "periods.csv") + shutil.copy(sequence_path, this_dir + "sequence.csv") + return + else: + print("Cached clustering results not found. Running clustering.") + + # Get selected timeseries to cluster over + df_timeseries = collect_timeseries() + + if utils.config['use_pca']: + # Using PCA to get principal components first, then clustering over those + print("Input timeseries to PCA:\n") + print(df_timeseries) + df_pca = pca.get_principal_components(df_timeseries, utils.config['pca_groups']) + print("Clustering over principal components:\n") + print(df_pca) + + df_ts_std = pca.standardise(df_timeseries) + + for group in utils.config['pca_groups']: + pp.figure() + pp.title(f"principal components for {group['name']}") + pp.xlabel('time (h)') + for ts in group['columns']: + pp.plot(df_ts_std[ts], label=ts) + for col in df_pca.columns: + if col.split('_pc')[0] == group['name']: + pp.plot(df_pca[col], linewidth=4, label=col) + pp.legend() + else: + # Clustering directly on input timeseries + print("Clustering over timeseries:\n") + print(df_timeseries) + + # Get the list of test numbers of periods for plotting + test_periods = set(utils.config['test_periods']) if utils.config['test_periods'] is not None else set() + test_periods.add(utils.config['final_periods']) # in case it wasn't already in the set + test_periods = list(test_periods) + test_periods.sort() + + # Build figures and plot original timeseries and duration curves + dur_axes = dict() + dur_figs = dict() + ts_axes = dict() + ts_figs = dict() + for ts in df_timeseries.columns: + dur_figs[ts], dur_axes[ts] = pp.subplots(figsize = [10, 6], dpi = 100, nrows = 1, ncols = 1) + df_timeseries[ts].sort_values(ascending=False).reset_index(drop=True).plot(label='original', lw=3, style='k-', ax=dur_axes[ts]) + dur_axes[ts].set_title(f"duration curve of original {ts} and weighted representative periods") + dur_axes[ts].set_xlabel('duration (h)') + dur_axes[ts].set_ylabel(ts) + + ts_figs[ts], ts_axes[ts] = pp.subplots(figsize = [10, 6], dpi = 100, nrows = 1, ncols = 1) + df_timeseries[ts].reset_index(drop=True).plot(label='original', lw=2, style='b-', ax=ts_axes[ts]) + ts_axes[ts].set_title(f"timeseries of original {ts} and weighted representative periods") + ts_axes[ts].set_xlabel('time (h)') + ts_axes[ts].set_ylabel(ts) + + # Plot each set of test periods on both figures going from red -> blue with increasing n periods. Green if final number of periods + colour = [1, 0, 0] + for n_periods in test_periods: + + if utils.config['use_pca']: df_predicted, sequence = cluster_days(df_timeseries=df_pca, n_periods=n_periods) + else: df_predicted, sequence = cluster_days(df_timeseries=df_timeseries, n_periods=n_periods) + if df_predicted is None: continue # How does this happen? + + if utils.config['use_pca']: + # Have to manually reconstruct the representative timeseries because TSAM only ever saw principal components + data = [] + for d in sequence: data.extend(df_timeseries.values[d*24:d*24+24]) + df_predicted = pd.DataFrame(columns=df_timeseries.columns, data=data, index=df_timeseries.index) + + for ts in df_timeseries.columns: + if n_periods == utils.config['final_periods']: + df_predicted[ts].sort_values(ascending=False).reset_index(drop=True).plot(label=f"*{n_periods} periods", ax=dur_axes[ts], lw=2, color=(0, 0.8, 0)) + df_predicted[ts].reset_index(drop=True).plot(label=f"*{n_periods} periods", ax=ts_axes[ts], color='red') + else: + df_predicted[ts].sort_values(ascending=False).reset_index(drop=True).plot(label=f"{n_periods} periods", ax=dur_axes[ts], color=tuple(colour)) + + # This transitions linearly from red to blue + if len(test_periods) <= 1: break + if colour[2] < 1: colour[2] = min(1, colour[2] + 2/(len(test_periods)-1)) + else: colour[0] = colour[0] = max(0, colour[0] - 2/(len(test_periods)-1)) + + # Add the legend and save the figure to output data directory + from platformdirs import PlatformDirs + dirs = PlatformDirs("RSSSelector", "CANOE") + plot_out = os.path.join(dirs.user_config_path, "clustering_plots") + os.makedirs(os.path.join(plot_out, "duration_curve_plots"), exist_ok=True) + os.makedirs(os.path.join(plot_out, "timeseries_plots"), exist_ok=True) + + for ts in df_timeseries.columns: + dur_axes[ts].legend() + dur_figs[ts].savefig(os.path.join(plot_out, "duration_curve_plots", f"{ts}.pdf")) + ts_axes[ts].legend() + ts_figs[ts].savefig(os.path.join(plot_out, "timeseries_plots", f"{ts}.pdf")) + + # Close figures to avoid memory leaks + pp.close(dur_figs[ts]) + pp.close(ts_figs[ts]) + + print("\nClustering complete.\n") + + if show_plots: + print("Showing plots.") + pp.show() + + + +def cluster_days(df_timeseries: pd.DataFrame, n_periods: int) -> pd.DataFrame: + + method = utils.config['clustering_method'] + csv_name = f"{method}_{n_periods}p.csv" + + print(f"\nClustering {n_periods} periods using {method} method...\n") + + # Get any configured forced days, make index conversion and convert to period indices (if multiday periods) + if utils.config['force_days'] is None: forced_periods = [] + else: + forced_days = [day + utils.config['day_to_index'] for day in utils.config['force_days']] + forced_periods = [day // utils.config['days_per_period'] for day in forced_days] # does nothing if one-day periods + + # Collect custom feature periods based on any configured in the list + forced_periods.extend([p for p in collect_custom_feature_periods() if p not in forced_periods]) + + # Making room for extreme periods + extreme_periods = utils.config['extreme_periods'] + n_clusters = n_periods - len(forced_periods) - sum(len(val) for val in extreme_periods.values() if val) + + if n_clusters < 1: + print("Too many feature periods! Nothing left for clustering. Skipping.") + return + + # Execute the clustering + ts_agg = tsam.TimeSeriesAggregation( + df_timeseries, + noTypicalPeriods = n_clusters, + hoursPerPeriod = 24*utils.config['days_per_period'], + clusterMethod = method, + extremePeriodMethod='new_cluster_center', + addManual=forced_periods, + addPeakMax=extreme_periods['max_peak'], + addPeakMin=extreme_periods['min_peak'], + addMeanMax=extreme_periods['max_mean'], + addMeanMin=extreme_periods['min_mean'], + resolution=1, + solver='gurobi', + ) + + # Get the indices of chosen periods and their weights of the year + weights = ts_agg.clusterPeriodNoOccur + indices = ts_agg.clusterCenterIndices + + if len(ts_agg.extremePeriods.values()) < n_periods - n_clusters: + print(f"Overlap between feature periods! Lost {n_periods - n_clusters - len(ts_agg.extremePeriods.values())} period(s).") + + # Add feature period indices + if n_periods == utils.config['final_periods']: print("Selected feature periods:") + for name, period in ts_agg.extremePeriods.items(): + index = period['stepNo'] + if n_periods == utils.config['final_periods']: print(utils.index_to_season(index), name) + if index not in indices: indices.append(index) + else: print(f"Feature period {utils.index_to_season(index)} overlapped with typical periods! Lost one period.") + + # Convert period indices to string period names as in the database + days = [utils.index_to_season(d) for d in indices] + + # Saving day selection and weights for all test numbers of periods to output data directory + df_days = pd.DataFrame(index=days, data=weights.values(), columns=['weight']).sort_index() + df_days.to_csv(out_data + "representative_periods/" + csv_name) + + sequence = [ts_agg.clusterCenterIndices[i] for i in ts_agg.clusterOrder] + day_sequence = [utils.index_to_season(i) for i in sequence] + df_sequence = pd.DataFrame(index=range(len(day_sequence)), data=day_sequence, columns=['period']) + df_sequence.to_csv(out_data + f"representative_periods/sequence_{n_periods}p.csv") + + # For the final number of periods, output to periods.csv for database processing + if n_periods == utils.config['final_periods']: + print("\nOutput representative periods:\n") + print(df_days.head(50), '\n') + df_days.to_csv(this_dir + "periods.csv") + + # Also output the representative sequence + df_sequence.to_csv(this_dir + "sequence.csv") + + # Output the timeseries data for the periods selected + df_typ_periods = ts_agg.createTypicalPeriods() + df_typ_periods.index = df_typ_periods.index.set_levels(df_typ_periods.index.levels[0].map(lambda i: days[i]), level=0) + df_typ_periods = df_typ_periods.sort_index(level=0) + df_typ_periods.to_csv(out_data + "reduced_timeseries/" + csv_name) + + # Output accuracy indicators for clustering + df_accuracy = ts_agg.accuracyIndicators() + df_accuracy.to_csv(out_data + "accuracy_indicators/" + csv_name) + + # Output recreated full-length timeseries based on selected periods + df_predicted = ts_agg.predictOriginalData() + df_predicted.to_csv(out_data + "recreated_timeseries/" + csv_name) + + return df_predicted, sequence + + + +# Collects all selected timeseries and puts them into a dataframe for clustering +def collect_timeseries() -> pd.DataFrame: + + dfs = [] + cols = [] + files = get_all_files() # gets a list of paths to selected timeseries csv files + + for path in files: + + file = this_dir + "/".join(path) + '.csv' # turn path list into actual file path + df = pd.read_csv(file, index_col=0).astype(float) + df.index = range(len(df.index)) + cols.append(file.split('/')[-1].split('.')[0]) + dfs.append(df) # read the csv and add to the list + + # Concatenate all found csv files into a single dataframe for TSAM + df_timeseries = pd.concat(dfs, axis='columns') + df_timeseries.columns = cols + return df_timeseries + + + +# Collects and returns custom feature periods identified by feature identification based on list configured in config +def collect_custom_feature_periods() -> list[int]: + + custom_feature_periods = [] + + if utils.config['custom_features'] is None: return custom_feature_periods + + # For each feature configured in the list, pass that dictionary to the relevant + # feature identification method and get period indices in return + for feature in utils.config['custom_features']: + + match feature['method']: + case 'max_mean_period': custom_feature_periods.extend(fi.max_mean_period(feature)) + + return custom_feature_periods + + + +# Walks the timeseries nested dictionary to find all selected csv files +def get_all_files() -> list[list[str]]: + + files = [] # just a collector that the recursive method can add into + get_files(['timeseries'], utils.config['timeseries'], files) + + return files + +# Recursively walks a dictionary to find more dictionaries or, otherwise, a list of files +def get_files(dir: list, dictionary: dict, files): + + for key, value in dictionary.items(): + + _dir = dir.copy() + _dir.append(key) + + # Found a nested dictionary, go one level deeper + if isinstance(value, dict): + get_files(_dir, dictionary[key], files) # si chiama a se stesso + + # Found a list of files. Append them to the files list + elif isinstance(value, list): + for item in value: + if isinstance(item, str): files.append([*_dir, item]) + + + +if __name__ == "__main__": + + init() + run(show_plots=utils.config['show_plots']) \ No newline at end of file diff --git a/representative_periods/config.yaml b/representative_periods/config.yaml new file mode 100644 index 0000000..1752f11 --- /dev/null +++ b/representative_periods/config.yaml @@ -0,0 +1,128 @@ +rerun_clustering: false +show_plots: false +days_per_period: 1 +disaggregate_multiday: true +demand_preservation: hourly +dsd_threshold: 0.01 +final_periods: 16 +test_periods: +- 1 +- 2 +- 4 +- 8 +- 16 +- 32 +use_pca: true +pca_groups: +- name: weather + columns: + - ab_irradiance_surface + - ab_humidity + - ab_temperature + - ab_wind_speed + - bc_irradiance_surface + - bc_humidity + - bc_temperature + - bc_wind_speed + - mb_irradiance_surface + - mb_humidity + - mb_temperature + - mb_wind_speed + - nb_irradiance_surface + - nb_humidity + - nb_temperature + - nb_wind_speed + - nllab_irradiance_surface + - nllab_humidity + - nllab_temperature + - nllab_wind_speed + - ns_irradiance_surface + - ns_humidity + - ns_temperature + - ns_wind_speed + - on_irradiance_surface + - on_humidity + - on_temperature + - on_wind_speed + - pei_irradiance_surface + - pei_humidity + - pei_temperature + - pei_wind_speed + - qc_irradiance_surface + - qc_humidity + - qc_temperature + - qc_wind_speed + - sk_irradiance_surface + - sk_humidity + - sk_temperature + - sk_wind_speed + n_components: 6 +force_days: null +extreme_periods: + max_peak: null + min_peak: null + max_mean: null + min_mean: null +custom_features: null +day_to_index: -1 +clustering_method: hierarchical +timeseries: + ab: + - ab_irradiance_surface + - ab_humidity + - ab_temperature + - ab_wind_speed + bc: + - bc_irradiance_surface + - bc_humidity + - bc_temperature + - bc_wind_speed + mb: + - mb_irradiance_surface + - mb_humidity + - mb_temperature + - mb_wind_speed + nb: + - nb_irradiance_surface + - nb_humidity + - nb_temperature + - nb_wind_speed + nllab: + - nllab_irradiance_surface + - nllab_humidity + - nllab_temperature + - nllab_wind_speed + ns: + - ns_irradiance_surface + - ns_humidity + - ns_temperature + - ns_wind_speed + 'on': + - on_irradiance_surface + - on_humidity + - on_temperature + - on_wind_speed + pei: + - pei_irradiance_surface + - pei_humidity + - pei_temperature + - pei_wind_speed + qc: + - qc_irradiance_surface + - qc_humidity + - qc_temperature + - qc_wind_speed + sk: + - sk_irradiance_surface + - sk_humidity + - sk_temperature + - sk_wind_speed + ontario: + - ldv_charging + temoa-canada: null +model_years: +- 2025 +- 2030 +- 2035 +- 2040 +- 2045 diff --git a/representative_periods/database_processing.py b/representative_periods/database_processing.py new file mode 100644 index 0000000..557f7c2 --- /dev/null +++ b/representative_periods/database_processing.py @@ -0,0 +1,304 @@ +""" +Aligns a Temoa database with representative days configured in days.csv +""" + +import sqlite3 +import os +import pandas as pd +import shutil +from . import utils + +this_dir = os.path.realpath(os.path.dirname(__file__)) + "/" +input_dir = this_dir + "input_sqlite/" +output_dir = this_dir + "output_sqlite/" +def reset(): + global initialised + initialised = False +df_periods: pd.DataFrame +initialised = False + + +def init(): + + global df_periods, initialised + if initialised: return + + df_periods = pd.read_csv(this_dir + "periods.csv", index_col=0).astype(float) + df_periods['weight'] = df_periods['weight'] / df_periods['weight'].sum() + + if utils.config['disaggregate_multiday'] and utils.config['days_per_period'] > 1: + for period, wgt in df_periods.iterrows(): + days = period_to_days(period) + weight = wgt.iloc[0] / len(days) + + for day in days: + df_periods.loc[day, 'weight'] = weight + + df_periods = df_periods.drop(period, axis='index') + + print("\nApplying the following periods to old databases:\n") + print(df_periods) + + initialised = True + print("\nInitialised database processing.\n") + + + +def process_all(input_path: str = None, output_path: str = None): + + init() + + if input_path and output_path: + # Check schema + ver = _get_schema_version_for_path(input_path) + if ver != 0: return False + print(f"Processing {input_path}...") + process_database(database=None, input_path=input_path, output_path=output_path) + return True + + databases = _get_sqlite_databases() + + for database in databases: + + if _get_schema_version(database) != 0: continue + + print(f"Processing {database}...") + process_database(database) + + print("\nFinished.\n") + + + +def process_database(database: str, input_path: str = None, output_path: str = None): + + init() + + # Copy the input database to the output directory and connect + if input_path and output_path: + shutil.copy(input_path, output_path) + db_path = output_path + else: + shutil.copy(input_dir + f"{database}.sqlite", output_dir + f"{database}.sqlite") + db_path = output_dir + f"{database}.sqlite" + + + if utils.config['disaggregate_multiday']: n_hours = 24 + else: n_hours = 24*utils.config['days_per_period'] + + if n_hours < 100: hours = [utils.stringify_hour(hour+1) for hour in range(n_hours)] + else: hours = [utils.stringify_day(hour+1).replace("D","H") for hour in range(n_hours)] + + if utils.config['days_per_period'] == 1 or utils.config['disaggregate_multiday']: process_single_day_periods(database, hours, db_path) + elif utils.config['days_per_period'] > 1: process_multiday_periods(database, hours, db_path) + + # Vacuum to clean up empty data + conn = sqlite3.connect(db_path) + conn.execute("VACUUM;") + conn.commit() + conn.close() + + + +def process_multiday_periods(database, hours, db_path): + + conn = sqlite3.connect(db_path) + curs = conn.cursor() + + # Tables that reference time season + season_tables = [ + 'DemandSpecificDistribution', + 'CapacityFactorTech', + 'CapacityFactorProcess', + 'MinSeasonalActivity', + 'MaxSeasonalActivity' + ] + + # Empty the season reference table and add representative days back in + curs.execute(f"DELETE FROM time_season") + curs.execute(f"DELETE FROM time_of_day") + curs.execute(f"DELETE FROM SegFrac") + + for hour in hours: curs.execute(f"INSERT INTO time_of_day(t_day) VALUES('{hour}')") + + # Delete unnecessary days for starters + all_days = [] + for period in df_periods.index: + for period in period_to_days(period): all_days.append(period) + + for table in season_tables: + curs.execute(f"DELETE FROM {table} WHERE season_name NOT IN {tuple(all_days)}") + + for period, weight in df_periods.iterrows(): + + period_days = period_to_days(period) + + # Aggregate Seasonal Activity tables by new periods + for table in ['MinSeasonalActivity','MaxSeasonalActivity']: + val_col = table[:3].lower() + 'act' + df_seas = pd.read_sql_query(f"SELECT * FROM {table} WHERE season_name IN {period_days}", conn) + df_seas = df_seas.groupby(['regions','periods','tech']) + for grp in df_seas.groups: + curs.execute(f"""UPDATE {table} + SET {val_col} = (SELECT SUM({val_col}) FROM {table} WHERE + season_name IN {period_days} + AND regions == '{grp[0]}' + AND periods == {grp[1]} + AND tech == '{grp[2]}'), + season_name = '{period}' + WHERE season_name == '{period_days[0]}'""") + + curs.execute(f"INSERT INTO time_season(t_season) VALUES('{period}')") + + # SegFrac + for hour in hours: + curs.execute(f"""REPLACE INTO + SegFrac(season_name, time_of_day_name, segfrac, segfrac_notes) + VALUES('{period}', '{hour}', {weight.iloc[0] / len(hours)}, "Weight from clustering")""") + + curs.execute(f"""UPDATE DemandSpecificDistribution + SET dsd = dsd * {weight.iloc[0]} + WHERE season_name IN {period_days}""") + + # Rename days and hours + for table in ['DemandSpecificDistribution', 'CapacityFactorTech', 'CapacityFactorProcess']: + + for d in range(len(period_days)): + for h in range(24): + curs.execute(f"""UPDATE {table} + SET time_of_day_name = '{hours[24*d + h]}' + WHERE season_name == '{period_days[d]}' + AND time_of_day_name == '{utils.stringify_hour(h+1)}'""") + + curs.execute(f"""UPDATE {table} + SET season_name = '{period}' + WHERE season_name IN {period_days}""") + + + # Delete any seasons that aren't in the representative periods + for table in season_tables: + curs.execute(f"DELETE FROM {table} WHERE season_name NOT IN (SELECT t_season from time_season)") + + # Renormalise DSD + df_dsd = pd.read_sql_query("SELECT * FROM DemandSpecificDistribution", conn) + df_dsd = df_dsd.groupby(['regions','demand_name']) + for grp in df_dsd.groups: + total_dsd = df_dsd.get_group(grp)['dsd'].sum() + curs.execute(f"""UPDATE DemandSpecificDistribution + SET dsd = dsd / {total_dsd} + WHERE regions = '{grp[0]}' + AND demand_name == '{grp[1]}'""") + + conn.commit() + conn.close() + + + +def process_single_day_periods(database, hours, db_path): + + conn = sqlite3.connect(db_path) + curs = conn.cursor() + + # Empty the season reference table and add representative days back in + curs.execute(f"DELETE FROM time_season") + curs.execute(f"DELETE FROM SegFrac") + + # Update SegFrac and DSD based on rep day weights + for period, weight in df_periods.iterrows(): + + curs.execute(f"INSERT INTO time_season(t_season) VALUES('{period}')") + + # SegFrac + for hour in hours: + curs.execute(f"""REPLACE INTO + SegFrac(season_name, time_of_day_name, segfrac, segfrac_notes) + VALUES('{period}', '{hour}', {weight.iloc[0] / 24}, "Weight from clustering")""") + + # DemandSpecificDistribution + curs.execute(f"""UPDATE DemandSpecificDistribution + SET dsd = dsd * {weight.iloc[0]} + WHERE season_name == '{period}'""") + + # Delete any seasons that aren't in the representative days + for table in [ + 'DemandSpecificDistribution', + 'CapacityFactorTech', + 'CapacityFactorProcess', + 'MinSeasonalActivity', + 'MaxSeasonalActivity', + ]: + curs.execute(f"DELETE FROM {table} WHERE season_name NOT IN (SELECT t_season from time_season)") + + # Renormalise DSD + df_dsd = pd.read_sql_query("SELECT * FROM DemandSpecificDistribution", conn) + df_dsd = df_dsd.groupby(['regions','demand_name']) + for grp in df_dsd.groups: + total_dsd = df_dsd.get_group(grp)['dsd'].sum() + curs.execute(f"""UPDATE DemandSpecificDistribution + SET dsd = dsd / {total_dsd} + WHERE regions = '{grp[0]}' + AND demand_name == '{grp[1]}'""") + + conn.commit() + conn.close() + + + +# Collects sqlite databases into a dictionary of form {name: path} +def _get_sqlite_databases(): + + databases = [] + + for dirs in os.walk(input_dir): + files = dirs[2] + + for file in files: + split = os.path.splitext(file) + if split[1] == '.sqlite': databases.append(split[0]) + + return databases + + + +def _get_schema_version(database): + + conn = sqlite3.connect(input_dir + f"{database}.sqlite") + curs = conn.cursor() + + tables = {t[0].lower() for t in curs.execute("SELECT name FROM sqlite_schema").fetchall()} + if 'metadata' not in tables: return 0 + + try: + mj_vers = curs.execute("SELECT value FROM metadata WHERE element = 'DB_MAJOR' COLLATE NOCASE").fetchone() + if mj_vers is None: return 0 + return int(mj_vers[0]) + except Exception: + return 0 + + + +def period_to_days(period: str): + + if "-" not in period: return (period,) + else: + + days = [utils.destringify_day(day) for day in period.split("-")] + days = [utils.stringify_day(day) for day in range(days[0],days[1]+1,1)] + return tuple(days) + + + +if __name__ == "__main__": + + process_all() + +def _get_schema_version_for_path(path): + conn = sqlite3.connect(path) + curs = conn.cursor() + tables = {t[0].lower() for t in curs.execute("SELECT name FROM sqlite_schema").fetchall()} + if 'metadata' not in tables: return 0 + try: + mj_vers = curs.execute("SELECT value FROM metadata WHERE element = 'DB_MAJOR' COLLATE NOCASE").fetchone() + if mj_vers is None: return 0 + return int(mj_vers[0]) + except Exception: + return 0 diff --git a/representative_periods/database_processing_v3.py b/representative_periods/database_processing_v3.py new file mode 100644 index 0000000..afd07ca --- /dev/null +++ b/representative_periods/database_processing_v3.py @@ -0,0 +1,342 @@ +""" +Aligns a Temoa database with representative days configured in days.csv +""" + +import sqlite3 +import os +import pandas as pd +import shutil +from . import utils +import sys +def reset(): + global initialised + initialised = False +this_dir = os.path.realpath(os.path.dirname(__file__)) + "/" +input_dir = this_dir + "input_sqlite/" +output_dir = this_dir + "output_sqlite/" + +df_period: pd.DataFrame +initialised = False + + +def init(): + + global df_period, initialised + if initialised: return + + df_period = pd.read_csv(this_dir + "periods.csv", index_col=0).astype(float) + df_period['weight'] = df_period['weight'] / df_period['weight'].sum() + + if utils.config['disaggregate_multiday'] and utils.config['days_per_period'] > 1: + for period, wgt in df_period.iterrows(): + days = period_to_days(period) + weight = wgt.iloc[0] / len(days) + + for day in days: + df_period.loc[day, 'weight'] = weight + + df_period = df_period.drop(period, axis='index') + + print("\nApplying the following periods to v3 databases:\n") + print(df_period) + + initialised = True + print("\nInitialised database processing.\n") + + + +def process_all(input_path: str = None, output_path: str = None): + init() + + if input_path and output_path: + ver = _get_schema_version_for_path(input_path) + if ver != (3, 0): return False + print(f"Processing {input_path}...") + process_database(database=None, input_path=input_path, output_path=output_path) + return True + + databases = _get_sqlite_databases() + for database in databases: process_database(database) + print("\nFinished.\n") + + + +def process_database(database: str, input_path: str = None, output_path: str = None): + + if not input_path and _get_schema_version(database) != (3, 0): return + + init() + + print(f"Processing {database}...") + + # Copy the input database to the output directory and connect + + if input_path and output_path: + shutil.copy(input_path, output_path) + db_path = output_path + else: + shutil.copy(input_dir + f"{database}.sqlite", output_dir + f"{database}.sqlite") + db_path = output_dir + f"{database}.sqlite" + + + if utils.config['disaggregate_multiday']: n_hours = 24 + else: n_hours = 24*utils.config['days_per_period'] + + if n_hours < 100: hours = [utils.stringify_hour(hour+1) for hour in range(n_hours)] + else: hours = [utils.stringify_day(hour+1).replace("D","H") for hour in range(n_hours)] + + if utils.config['days_per_period'] == 1 or utils.config['disaggregate_multiday']: process_single_day_period(database, hours, input_path, output_path) + elif utils.config['days_per_period'] > 1: process_multiday_period(database, hours, db_path) + + # Vacuum to clean up empty data + conn = sqlite3.connect(db_path) + conn.execute("VACUUM;") + conn.commit() + conn.close() + + + +def process_multiday_period(database, hours, db_path): + + conn = sqlite3.connect(db_path) + curs = conn.cursor() + + # Horrible how can this curse live on + dsd_columns = [c[1] for c in curs.execute('PRAGMA table_info(DemandSpecificDistribution);').fetchall()] + dsd = 'dds' if 'dds' in dsd_columns else 'dsd' + + # Tables that reference time season + season_tables = [ + 'DemandSpecificDistribution', + 'CapacityFactorTech', + 'CapacityFactorProcess', + 'MinSeasonalActivity', + 'MaxSeasonalActivity', + 'MinDailyCapacityFactor', + 'MaxDailyCapacityFactor', + ] + + + # Empty the season reference table and add representative days back in + curs.execute(f"DELETE FROM TimeSeason") + curs.execute(f"DELETE FROM TimeOfDay") + curs.execute(f"DELETE FROM TimeSegmentFraction") + + for hour in hours: curs.execute(f"INSERT INTO TimeOfDay(tod) VALUES('{hour}')") + + + # Delete unnecessary days for starters + all_days = [] + for period in df_period.index: + for period in period_to_days(period): all_days.append(period) + + all_tables = [t[0] for t in curs.execute("SELECT name FROM sqlite_master WHERE type='table';").fetchall()] + for table in season_tables: + if table in all_tables: curs.execute(f"DELETE FROM {table} WHERE season NOT IN {tuple(all_days)}") + + + for period, weight in df_period.iterrows(): + + period_days = period_to_days(period) + + # Aggregate Seasonal Activity tables by new period + for table in ['MinSeasonalActivity','MaxSeasonalActivity']: + val_col = table[:3].lower() + '_act' + df_seas = pd.read_sql_query(f"SELECT * FROM {table} WHERE season IN {period_days}", conn) + df_seas = df_seas.groupby(['region','period','tech']) + for grp in df_seas.groups: + curs.execute(f"""UPDATE {table} + SET {val_col} = (SELECT SUM({val_col}) FROM {table} WHERE + season IN {period_days} + AND region == '{grp[0]}' + AND period == {grp[1]} + AND tech == '{grp[2]}'), + season = '{period}' + WHERE season == '{period_days[0]}'""") + + curs.execute(f"INSERT INTO TimeSeason(season) VALUES('{period}')") + + # TimeSegmentFraction + for hour in hours: + curs.execute(f"""REPLACE INTO + TimeSegmentFraction(season, tod, segfrac, notes) + VALUES('{period}', '{hour}', {weight.iloc[0] / len(hours)}, "Weight from clustering")""") + + curs.execute(f"""UPDATE DemandSpecificDistribution + SET {dsd} = {dsd} * {weight.iloc[0]} * 365 + WHERE season IN {period_days}""") + + # Rename days and hours + for table in ['DemandSpecificDistribution', 'CapacityFactorTech', 'CapacityFactorProcess']: + + for d in range(len(period_days)): + for h in range(24): + curs.execute(f"""UPDATE {table} + SET tod = '{hours[24*d + h]}' + WHERE season == '{period_days[d]}' + AND tod == '{utils.stringify_hour(h+1)}'""") + + curs.execute(f"""UPDATE {table} + SET season = '{period}' + WHERE season IN {period_days}""") + + + # Delete any seasons that aren't in the representative period + for table in season_tables: + curs.execute(f"DELETE FROM {table} WHERE season NOT IN (SELECT season from TimeSeason)") + + + # Renormalise DSD + df_dsd = pd.read_sql_query("SELECT * FROM DemandSpecificDistribution", conn) + df_dsd = df_dsd.groupby(['region','demand_name']) + for grp in df_dsd.groups: + total_dsd = df_dsd.get_group(grp)[dsd].sum() + curs.execute(f"""UPDATE DemandSpecificDistribution + SET {dsd} = {dsd} / {total_dsd} + WHERE region = '{grp[0]}' + AND demand_name == '{grp[1]}'""") + + # If preserving absolute hourly values, adjust annual totals to sum of clustered periods + if utils.config['demand_preservation'] == 'hourly': + curs.execute(f"""UPDATE Demand SET demand = demand * {total_dsd} + WHERE region = '{grp[0]}' + AND commodity == '{grp[1]}'""") + + + conn.commit() + conn.close() + + + +def process_single_day_period(database, hours, input_path, output_path): + + conn = sqlite3.connect(db_path) + curs = conn.cursor() + + # Horrible how can this curse live on + dsd_columns = [c[1] for c in curs.execute('PRAGMA table_info(DemandSpecificDistribution);').fetchall()] + dsd = 'dds' if 'dds' in dsd_columns else 'dsd' + + # Empty the season reference table and add representative days back in + curs.execute(f"DELETE FROM TimeSeason") + curs.execute(f"DELETE FROM TimeSegmentFraction") + + # Update TimeSegmentFraction and DSD based on rep day weights + for period, weight in df_period.iterrows(): + + curs.execute(f"INSERT INTO TimeSeason(season) VALUES('{period}')") + + # TimeSegmentFraction + for hour in hours: + curs.execute(f"""REPLACE INTO + TimeSegmentFraction(season, tod, segfrac, notes) + VALUES('{period}', '{hour}', {weight.iloc[0] / 24}, "Weight from clustering")""") + + # DemandSpecificDistribution + curs.execute(f"""UPDATE DemandSpecificDistribution + SET {dsd} = {dsd} * {weight.iloc[0]} * 365 + WHERE season == '{period}'""") + + # Delete any seasons that aren't in the representative days + season_tables = [ + 'DemandSpecificDistribution', + 'CapacityFactorTech', + 'CapacityFactorProcess', + 'MinSeasonalActivity', + 'MaxSeasonalActivity', + 'MinDailyCapacityFactor', + 'MaxDailyCapacityFactor', + ] + + all_tables = [t[0] for t in curs.execute("SELECT name FROM sqlite_master WHERE type='table';").fetchall()] + for table in season_tables: + if table in all_tables: curs.execute(f"DELETE FROM {table} WHERE season NOT IN (SELECT season from TimeSeason)") + + + # Renormalise DSD + df_dsd = pd.read_sql_query("SELECT * FROM DemandSpecificDistribution", conn) + df_dsd = df_dsd.groupby(['region','demand_name']) + for grp in df_dsd.groups: + total_dsd = df_dsd.get_group(grp)[dsd].sum() + curs.execute(f"""UPDATE DemandSpecificDistribution + SET {dsd} = {dsd} / {total_dsd} + WHERE region = '{grp[0]}' + AND demand_name == '{grp[1]}'""") + + # If preserving absolute hourly values, adjust annual totals to sum of clustered periods + if utils.config['demand_preservation'] == 'hourly': + curs.execute(f"""UPDATE Demand SET demand = demand * {total_dsd} + WHERE region = '{grp[0]}' + AND commodity == '{grp[1]}'""") + + conn.commit() + conn.close() + + + +# Collects sqlite databases into a dictionary of form {name: path} +def _get_sqlite_databases(): + + databases = [] + + for dirs in os.walk(input_dir): + files = dirs[2] + + for file in files: + split = os.path.splitext(file) + if split[1] == '.sqlite': databases.append(split[0]) + + return databases + + + +def _get_schema_version(database): + + conn = sqlite3.connect(input_dir + f"{database}.sqlite") + curs = conn.cursor() + + tables = {t[0].lower() for t in curs.execute("SELECT name FROM sqlite_schema").fetchall()} + if 'metadata' not in tables: + print(f"Could not get schema version for {database}. Skipped.") + return 0 + + try: + mj_vers = curs.execute("SELECT value FROM metadata WHERE element = 'DB_MAJOR' COLLATE NOCASE").fetchone() + mn_vers = curs.execute("SELECT value FROM metadata WHERE element = 'DB_MINOR' COLLATE NOCASE").fetchone() + if mj_vers is None or mn_vers is None: return 0 + return int(mj_vers[0]), int(mn_vers[0]) + except Exception: + return 0 + + + +def period_to_days(period: str): + + if "-" not in period: return (period,) + else: + days = [utils.destringify_day(day) for day in period.split("-")] + days = [utils.stringify_day(day) for day in range(days[0],days[1]+1,1)] + return tuple(days) + + + +if __name__ == "__main__": + + if len(sys.argv) <= 1: process_all() + else: + process_database(sys.argv[1]) + print("Finished.") + +def _get_schema_version_for_path(path): + conn = sqlite3.connect(path) + curs = conn.cursor() + tables = {t[0].lower() for t in curs.execute("SELECT name FROM sqlite_schema").fetchall()} + if 'metadata' not in tables: + return 0 + try: + mj_vers = curs.execute("SELECT value FROM metadata WHERE element = 'DB_MAJOR' COLLATE NOCASE").fetchone() + mn_vers = curs.execute("SELECT value FROM metadata WHERE element = 'DB_MINOR' COLLATE NOCASE").fetchone() + if mj_vers is None or mn_vers is None: return 0 + return int(mj_vers[0]), int(mn_vers[0]) + except Exception: + return 0 diff --git a/representative_periods/database_processing_v3_1.py b/representative_periods/database_processing_v3_1.py new file mode 100644 index 0000000..240730f --- /dev/null +++ b/representative_periods/database_processing_v3_1.py @@ -0,0 +1,398 @@ +""" +Aligns a Temoa database with representative days configured in days.csv +""" + +import sqlite3 +import os +import pandas as pd +from . import utils +import sys +import math + +this_dir = os.path.realpath(os.path.dirname(__file__)) + "/" +input_dir = input_dir = this_dir + "input_sqlite/" +output_dir = this_dir + "output_sqlite/" +def reset(): + global initialised + initialised = False +schema = this_dir + "canoe_schema_v3_1.sql" + +df_period: pd.DataFrame +initialised = False + +# Need to copy these over first (and in order) +index_tables = { + 'DataSet', + 'DataSource', + 'CommodityType', + 'Commodity', + 'Region', + 'Technology', + 'TimeOfDay', + 'TimePeriod', +} + +direct_copy_tables = { + 'CapacityCredit', + 'CapacityToActivity', + 'ConstructionInput', + 'CostEmission', + 'CostFixed', + 'CostInvest', + 'CostVariable', + 'Demand', + 'Efficiency', + 'EmissionActivity', + 'EmissionEmbodied', + 'EmissionEndOfLife', + 'EndOfLifeOutput', + 'ExistingCapacity', + 'LifetimeProcess', + 'LifetimeSurvivalCurve', + 'LifetimeTech', + 'LimitActivity', + 'LimitActivityShare', + 'LimitAnnualCapacityFactor', + 'LimitCapacity', + 'LimitCapacityShare', + 'LimitDegrowthCapacity', + 'LimitDegrowthNewCapacity', + 'LimitDegrowthNewCapacityDelta', + 'LimitNewCapacity', + 'LimitNewCapacityShare', + 'LimitResource', + 'LimitTechInputSplit', + 'LimitTechInputSplitAnnual', + 'LimitTechOutputSplit', + 'LimitTechOutputSplitAnnual', + 'LinkedTech', + 'LoanLifetimeProcess', + 'LoanRate', + 'PlanningReserveMargin', + 'RampDownHourly', + 'RampUpHourly', + 'RPSRequirement', + 'StorageDuration', + 'TechGroup', + 'TechGroupMember', +} + +# For season tables, only copy where the season is in the rep day set +season_tables = { + 'DemandSpecificDistribution', + 'CapacityFactorTech', + 'CapacityFactorProcess', + 'EfficiencyVariable', + 'LimitSeasonalCapacityFactor', + 'LimitStorageLevelFraction', + 'ReserveCapacityDerate', + 'SeasonLabel', +} + + +def init(): + + global df_period, df_sequence, initialised + if initialised: return + + df_period = pd.read_csv(this_dir + "periods.csv", index_col=0) + + df_sequence = pd.read_csv(this_dir + "sequence.csv", index_col=0) + change_points = df_sequence['period'] != df_sequence['period'].shift() + group_id = change_points.cumsum() + collapsed = df_sequence.groupby(group_id, as_index=False).agg({'period': 'first'}) + collapsed['count'] = df_sequence.groupby(group_id).size().values + df_sequence = collapsed + + # Split e.g. D001-D003 into D001, D002, D003 + if utils.config['disaggregate_multiday'] and utils.config['days_per_period'] > 1: + for period, wgt in df_period.iterrows(): + days = period_to_days(period) + weight = wgt.iloc[0] / len(days) + + for day in days: + df_period.loc[day, 'weight'] = weight + + df_period = df_period.drop(period, axis='index') + + print("\nApplying the following periods to v3.1 databases:\n") + print(df_period) + + initialised = True + print("\nInitialised database processing.\n") + + + +def process_all(input_path: str = None, output_path: str = None): + init() + + if input_path and output_path: + ver = _get_schema_version_for_path(input_path) + if ver != (3, 1): return False + print(f"Processing {input_path}...") + process_database(database=None, input_path=input_path, output_path=output_path) + return True + + databases = _get_sqlite_databases() + for database in databases: process_database(database) + print("\nFinished.\n") + + + +def process_database(database: str, input_path: str = None, output_path: str = None): + + if not input_path and _get_schema_version(database) != (3, 1): return + + init() + + print(f"Processing {database}...") + + if utils.config['disaggregate_multiday']: n_hours = 24 + else: n_hours = 24*utils.config['days_per_period'] + + if n_hours < 100: hours = [utils.stringify_hour(hour+1) for hour in range(n_hours)] + else: hours = [utils.stringify_day(hour+1).replace("D","H") for hour in range(n_hours)] + + if utils.config['days_per_period'] == 1 or utils.config['disaggregate_multiday']: process_single_day_period(database, hours, input_path, output_path) + elif utils.config['days_per_period'] > 1: + print("Multiday periods are not currently supported by Temoa. Turn on dissaggregate_multiday.") + return + #process_multiday_period(db_file, hours) + + + +def process_single_day_period(database: str, hours: list, input_path: str = None, output_path: str = None): + + if output_path: + out_file = output_path + else: + out_file = output_dir + database + f"_{len(df_period)}d.sqlite" + + # Check if database exists or needs to be built + build_db = not os.path.exists(out_file) + + # Connect to the new database file + conn = sqlite3.connect(out_file) + curs = conn.cursor() # Cursor object interacts with the sqlite db + + # Build the database if it doesn't exist. Otherwise clear all data if forced + if build_db: curs.executescript(open(schema, 'r').read()) + else: + tables = [t[0] for t in curs.execute("""SELECT name FROM sqlite_master WHERE type='table';""").fetchall()] + for table in tables: curs.execute(f"DELETE FROM '{table}'") + curs.executescript(open(schema, 'r').read()) + + conn.commit() + if input_path: + conn.execute(f"ATTACH DATABASE '{input_path}' AS dbin") + else: + conn.execute(f"ATTACH DATABASE '{input_dir + database + '.sqlite'}' AS dbin") # Attach the input database + conn.execute('PRAGMA foreign_keys = 0;') # Turn off foreign keys while copying over + + in_tables = [t[0] for t in curs.execute("SELECT name FROM dbin.sqlite_master WHERE type='table';").fetchall()] + + for table in index_tables: + if table not in in_tables: continue + cols = str([row[1] for row in curs.execute(f"PRAGMA table_info({table})").fetchall()])[1:-1].replace("'","") + curs.execute(f"REPLACE INTO main.{table}({cols}) SELECT {cols} FROM dbin.{table}") + + for table in direct_copy_tables: + if table not in in_tables: continue # might be a db variant without the table + cols = str([row[1] for row in curs.execute(f"PRAGMA table_info({table})").fetchall()])[1:-1].replace("'","") + curs.execute(f"REPLACE INTO main.{table}({cols}) SELECT {cols} FROM dbin.{table}") + + periods = tuple(df_period.index.unique()) + for table in season_tables: + if table not in in_tables: continue # might be a db variant without the table + cols = str([row[1] for row in curs.execute(f"PRAGMA table_info({table})").fetchall()])[1:-1].replace("'","") + curs.execute(f"REPLACE INTO main.{table}({cols}) SELECT {cols} FROM dbin.{table} WHERE season IN {periods}") + + total_days = df_period['weight'].sum() + curs.execute(f"REPLACE INTO MetaData VALUES('days_per_period', {total_days}, 'count of days in each period')") + + for year in utils.config['model_years']: + for i, (period, weight) in enumerate(df_period.iterrows()): + for hour in hours: + + # TimeSegmentFraction + curs.execute(f"""REPLACE INTO + TimeSegmentFraction(period, season, tod, segfrac, notes) + VALUES({year}, '{period}', '{hour}', {weight.iloc[0] / (24 * total_days)}, "Weight from clustering")""") + + # TimeSeason + curs.execute(f"""REPLACE INTO + TimeSeason(period, sequence, season) + VALUES({year}, {i}, '{period}')""") + + # TimeSeasonSequential + for i, row in df_sequence.iterrows(): + zeros = math.floor(math.log10(len(df_sequence))) - (0 if i==0 else math.floor(math.log10(i))) + period_seq = f"S{'0'*zeros}{i}" + curs.execute(f"""REPLACE INTO + TimeSeasonSequential(period, sequence, seas_seq, season, num_days, notes) + VALUES({year}, {i}, '{period_seq}', '{row['period']}', {row['count']}, 'Reconstructed original year from clustering')""") + + # TimeOfDay + for h in range(24): + tod = f"H0{h+1}" if h+1 < 10 else f"H{h+1}" + curs.execute(f'REPLACE INTO TimeOfDay(sequence, tod) VALUES({h+1}, "{tod}")') + + # DemandSpecificDistribution + # This is renormalised to sum to 1 below + for period, weight in df_period.iterrows(): + curs.execute(f"""UPDATE DemandSpecificDistribution + SET dsd = dsd * {weight.iloc[0]} + WHERE season == '{period}'""") + + # Renormalise DSD + df_dsd = pd.read_sql_query("SELECT * FROM DemandSpecificDistribution", conn) + df_dsd = df_dsd.groupby(['region','period','demand_name']) + for rpd in df_dsd.groups: + + # Drop threshold lower percentile + df = df_dsd.get_group(rpd).sort_values('dsd').reset_index() + + # This is a safety net for low numbers of clusters where you might catch + # a day with zero demand throughout, which is not normalisable + if df['dsd'].sum() == 0: + print( + f"There was no DSD remaining for demand {rpd}! " + "Filling with flatline demand for now but different periods " + "should be used!" + ) + flatline_fill = 1 / len(df) + df['dsd'] = flatline_fill + curs.execute( + f"""UPDATE DemandSpecificDistribution + SET dsd = {flatline_fill} + WHERE region = '{rpd[0]}' + AND period = '{rpd[1]}' + AND demand_name == '{rpd[2]}'""" + ) + + # Get a running proportion sum of DSD + df['run_sum'] = df['dsd'].cumsum()/df['dsd'].sum() + # Get the smallest DSD above thresh to zero out actual table + thresh_dsd = df['dsd'].loc[df['run_sum'] < utils.config['dsd_threshold']].max() + + # There might be nothing under the threshold if using few rep days + if not pd.isna(thresh_dsd): + + thresh_dsd += 1e-12 # Small buffer to avoid floating point issues + + # Set to zero where the proportion exceeds the threshold + # If there are duplicate dsd values on the threshold these are all left in + # This leaves everything in in the case of a flatline demand + df['dsd'] = df['dsd'].where(df['dsd'] >= thresh_dsd, 0) + + curs.execute( + f"""UPDATE DemandSpecificDistribution + SET dsd = 0 + WHERE region = '{rpd[0]}' + AND period = '{rpd[1]}' + AND demand_name == '{rpd[2]}' + AND dsd < {thresh_dsd}""" + ) + + # Renormalise + total_dsd = df['dsd'].sum() + curs.execute(f"""UPDATE DemandSpecificDistribution + SET dsd = dsd / {total_dsd} + WHERE region = '{rpd[0]}' + AND period = '{rpd[1]}' + AND demand_name == '{rpd[2]}'""") + + # If preserving absolute hourly values, adjust annual demand to sum of representative periods + if utils.config['demand_preservation'] == 'hourly': + curs.execute(f"""UPDATE Demand SET demand = demand * {total_dsd} + WHERE region = '{rpd[0]}' + AND period = '{rpd[1]}' + AND commodity == '{rpd[2]}'""") + + conn.commit() + + conn.execute("VACUUM;") + conn.commit() + + conn.execute('PRAGMA FOREIGN_KEYS=1;') + try: + data = conn.execute('PRAGMA FOREIGN_KEY_CHECK;').fetchall() + if data: + for row in data: + print(f'{row}') + print('(Table, Row ID, Reference Table, (fkid) )') + print(f'The above foreign keys failed to validate for {out_file}') + except sqlite3.OperationalError as e: + print(f'Foreign keys failed on activation for {out_file}. Something may be wrong with the schema.') + print(e) + + conn.close() + + + +# Collects sqlite databases into a dictionary of form {name: path} +def _get_sqlite_databases(): + + databases = [] + + for dirs in os.walk(input_dir): + files = dirs[2] + + for file in files: + split = os.path.splitext(file) + if split[1] == '.sqlite': databases.append(split[0]) + + return databases + + + +def _get_schema_version(database): + + conn = sqlite3.connect(input_dir + f"{database}.sqlite") + curs = conn.cursor() + + tables = {t[0].lower() for t in curs.execute("SELECT name FROM sqlite_schema").fetchall()} + if 'metadata' not in tables: + print(f"Could not get schema version for {database}. Skipped.") + return 0 + + try: + mj_vers = curs.execute("SELECT value FROM metadata WHERE element = 'DB_MAJOR' COLLATE NOCASE").fetchone() + mn_vers = curs.execute("SELECT value FROM metadata WHERE element = 'DB_MINOR' COLLATE NOCASE").fetchone() + if mj_vers is None or mn_vers is None: return 0 + return int(mj_vers[0]), int(mn_vers[0]) + except Exception: + return 0 + + + +def period_to_days(period: str): + + if "-" not in period: return (period,) + else: + days = [utils.destringify_day(day) for day in period.split("-")] + days = [utils.stringify_day(day) for day in range(days[0],days[1]+1,1)] + return tuple(days) + + + +if __name__ == "__main__": + + if len(sys.argv) <= 1: process_all() + else: + process_database(sys.argv[1]) + print("Finished.") + +def _get_schema_version_for_path(path): + conn = sqlite3.connect(path) + curs = conn.cursor() + tables = {t[0].lower() for t in curs.execute("SELECT name FROM sqlite_schema").fetchall()} + if 'metadata' not in tables: + return 0 + try: + mj_vers = curs.execute("SELECT value FROM metadata WHERE element = 'DB_MAJOR' COLLATE NOCASE").fetchone() + mn_vers = curs.execute("SELECT value FROM metadata WHERE element = 'DB_MINOR' COLLATE NOCASE").fetchone() + if mj_vers is None or mn_vers is None: return 0 + return int(mj_vers[0]), int(mn_vers[0]) + except Exception: + return 0 diff --git a/representative_periods/database_processing_v4_0.py b/representative_periods/database_processing_v4_0.py new file mode 100644 index 0000000..b62cb10 --- /dev/null +++ b/representative_periods/database_processing_v4_0.py @@ -0,0 +1,403 @@ +""" +Aligns a Temoa database with representative days configured in days.csv +""" + +import sqlite3 +import os +import pandas as pd +from . import utils +import sys +import math +def reset(): + global initialised + initialised = False +this_dir = os.path.realpath(os.path.dirname(__file__)) + "/" +input_dir = input_dir = this_dir + "input_sqlite/" +output_dir = this_dir + "output_sqlite/" + +schema = this_dir + "canoe_schema_v4_0.sql" + +df_period: pd.DataFrame +initialised = False + +# Need to copy these over first (and in order) +index_tables = { + 'data_set', + 'data_source', + 'commodity_type', + 'commodity', + 'region', + 'technology', + 'time_of_day', + 'time_period', + 'metadata', + 'sector_label', + 'tech_group_label', + 'data_source_label', + 'operator', + 'time_period_type', + 'data_quality_credibility', + 'data_quality_geography', + 'data_quality_structure', + 'data_quality_technology', + 'data_quality_time', + 'technology_type', +} + +direct_copy_tables = { + 'capacity_credit', + 'capacity_to_activity', + 'construction_input', + 'cost_emission', + 'technology_label', + 'commodity_label', + 'cost_fixed', + 'cost_invest', + 'cost_variable', + 'demand', + 'metadata_real', + 'efficiency', + 'emission_activity', + 'emission_embodied', + 'emission_end_of_life', + 'end_of_life_output', + 'existing_capacity', + 'lifetime_process', + 'lifetime_survival_curve', + 'lifetime_tech', + 'limit_activity', + 'limit_activity_share', + 'limit_annual_capacity_factor', + 'limit_capacity', + 'limit_capacity_share', + 'limit_degrowth_capacity', + 'limit_degrowth_new_capacity', + 'limit_degrowth_new_capacity_delta', + 'limit_new_capacity', + 'limit_new_capacity_share', + 'limit_resource', + 'limit_tech_input_split', + 'limit_tech_input_split_annual', + 'limit_tech_output_split', + 'limit_tech_output_split_annual', + 'linked_tech', + 'loan_lifetime_process', + 'loan_rate', + 'planning_reserve_margin', + 'ramp_down_hourly', + 'ramp_up_hourly', + 'rps_requirement', + 'storage_duration', + 'tech_group', + 'tech_group_member', +} + +# For season tables, only copy where the season is in the rep day set +season_tables = { + 'demand_specific_distribution', + 'capacity_factor_tech', + 'capacity_factor_process', + 'efficiency_variable', + 'limit_seasonal_capacity_factor', + 'limit_storage_level_fraction', + 'reserve_capacity_derate', + 'time_season', +} + + +def init(): + + global df_period, df_sequence, initialised + if initialised: return + + df_period = pd.read_csv(this_dir + "periods.csv", index_col=0) + + df_sequence = pd.read_csv(this_dir + "sequence.csv", index_col=0) + change_points = df_sequence['period'] != df_sequence['period'].shift() + group_id = change_points.cumsum() + collapsed = df_sequence.groupby(group_id, as_index=False).agg({'period': 'first'}) + collapsed['count'] = df_sequence.groupby(group_id).size().values + df_sequence = collapsed + + # Split e.g. D001-D003 into D001, D002, D003 + if utils.config['disaggregate_multiday'] and utils.config['days_per_period'] > 1: + for period, wgt in df_period.iterrows(): + days = period_to_days(period) + weight = wgt.iloc[0] / len(days) + + for day in days: + df_period.loc[day, 'weight'] = weight + + df_period = df_period.drop(period, axis='index') + + print("\nApplying the following periods to v4.0 databases:\n") + print(df_period) + + initialised = True + print("\nInitialised database processing.\n") + + + +def process_all(input_path: str = None, output_path: str = None): + init() + + if input_path and output_path: + ver = _get_schema_version_for_path(input_path) + if ver != (4, 0): return False + print(f"Processing {input_path}...") + process_database(database=None, input_path=input_path, output_path=output_path) + return True + + databases = _get_sqlite_databases() + for database in databases: process_database(database) + print("\nFinished.\n") + + + +def process_database(database: str, input_path: str = None, output_path: str = None): + + if not input_path and _get_schema_version(database) != (4, 0): return + + init() + + print(f"Processing {database}...") + + if utils.config['disaggregate_multiday']: n_hours = 24 + else: n_hours = 24*utils.config['days_per_period'] + + if n_hours < 100: hours = [utils.stringify_hour(hour+1) for hour in range(n_hours)] + else: hours = [utils.stringify_day(hour+1).replace("D","H") for hour in range(n_hours)] + + if utils.config['days_per_period'] == 1 or utils.config['disaggregate_multiday']: process_single_day_period(database, hours, input_path, output_path) + elif utils.config['days_per_period'] > 1: + print("Multiday periods are not currently supported by Temoa. Turn on dissaggregate_multiday.") + return + #process_multiday_period(db_file, hours) + + + +def process_single_day_period(database: str, hours: list, input_path: str = None, output_path: str = None): + + if output_path: + out_file = output_path + else: + out_file = output_dir + database + f"_{len(df_period)}d.sqlite" + + # Check if database exists or needs to be built + build_db = not os.path.exists(out_file) + + # Connect to the new database file + conn = sqlite3.connect(out_file) + curs = conn.cursor() # Cursor object interacts with the sqlite db + + # Build the database if it doesn't exist. Otherwise clear all data if forced + if build_db: curs.executescript(open(schema, 'r').read()) + else: + tables = [t[0] for t in curs.execute("""SELECT name FROM sqlite_master WHERE type='table';""").fetchall()] + for table in tables: curs.execute(f"DELETE FROM '{table}'") + curs.executescript(open(schema, 'r').read()) + + conn.commit() + if input_path: + conn.execute(f"ATTACH DATABASE '{input_path}' AS dbin") + else: + conn.execute(f"ATTACH DATABASE '{input_dir + database + '.sqlite'}' AS dbin") # Attach the input database + conn.execute('PRAGMA foreign_keys = 0;') # Turn off foreign keys while copying over + + in_tables = [t[0] for t in curs.execute("SELECT name FROM dbin.sqlite_master WHERE type='table';").fetchall()] + + for table in index_tables: + if table not in in_tables: continue + cols = str([row[1] for row in curs.execute(f"PRAGMA table_info({table})").fetchall()])[1:-1].replace("'","") + curs.execute(f"REPLACE INTO main.{table}({cols}) SELECT {cols} FROM dbin.{table}") + + for table in direct_copy_tables: + if table not in in_tables: continue # might be a db variant without the table + cols = str([row[1] for row in curs.execute(f"PRAGMA table_info({table})").fetchall()])[1:-1].replace("'","") + curs.execute(f"REPLACE INTO main.{table}({cols}) SELECT {cols} FROM dbin.{table}") + + periods = tuple(df_period.index.unique()) + for table in season_tables: + if table not in in_tables: continue # might be a db variant without the table + cols = str([row[1] for row in curs.execute(f"PRAGMA table_info({table})").fetchall()])[1:-1].replace("'","") + curs.execute(f"REPLACE INTO main.{table}({cols}) SELECT {cols} FROM dbin.{table} WHERE season IN {periods}") + + total_days = df_period['weight'].sum() + + for i, (period, weight) in enumerate(df_period.iterrows()): + # time_season + curs.execute(f"""REPLACE INTO + time_season(sequence, season, segment_fraction, notes) + VALUES({i}, '{period}', {weight.iloc[0] / total_days}, "Weight from clustering")""") + + # time_season_sequential + for i, row in df_sequence.iterrows(): + zeros = math.floor(math.log10(len(df_sequence))) - (0 if i==0 else math.floor(math.log10(i))) + period_seq = f"S{'0'*zeros}{i}" + curs.execute(f"""REPLACE INTO + time_season_sequential(sequence, seas_seq, season, segment_fraction, notes) + VALUES({i}, '{period_seq}', '{row['period']}', {row['count'] / total_days}, 'Reconstructed original year from clustering')""") + + # time_of_day + for h in range(24): + tod = f"H0{h+1}" if h+1 < 10 else f"H{h+1}" + curs.execute(f'REPLACE INTO time_of_day(sequence, tod, hours) VALUES({h+1}, "{tod}", 1)') + + # demand_specific_distribution + # This is renormalised to sum to 1 below + for period, weight in df_period.iterrows(): + curs.execute(f"""UPDATE demand_specific_distribution + SET dsd = dsd * {weight.iloc[0]} + WHERE season == '{period}'""") + + # Renormalise DSD + df_dsd = pd.read_sql_query("SELECT * FROM demand_specific_distribution", conn) + df_dsd = df_dsd.groupby(['region','period','demand_name']) + for rpd in df_dsd.groups: + + # Drop threshold lower percentile + df = df_dsd.get_group(rpd).sort_values('dsd').reset_index() + + # This is a safety net for low numbers of clusters where you might catch + # a day with zero demand throughout, which is not normalisable + if df['dsd'].sum() == 0: + print( + f"There was no DSD remaining for demand {rpd}! " + "Filling with flatline demand for now but different periods " + "should be used!" + ) + flatline_fill = 1 / len(df) + df['dsd'] = flatline_fill + curs.execute( + f"""UPDATE demand_specific_distribution + SET dsd = {flatline_fill} + WHERE region = '{rpd[0]}' + AND period = '{rpd[1]}' + AND demand_name == '{rpd[2]}'""" + ) + + # Get a running proportion sum of DSD + df['run_sum'] = df['dsd'].cumsum()/df['dsd'].sum() + # Get the largest DSD whose cumulative proportion is still below the threshold + thresh_dsd = df["dsd"].loc[df["run_sum"] < utils.config["dsd_threshold"]].max() + thresh_dsd -= 1e-10 # Small buffer to avoid floating point issues + + # There might be nothing under the threshold if using few rep days + if not pd.isna(thresh_dsd) and thresh_dsd < df["dsd"].max(): + + # Set to zero where the proportion exceeds the threshold + # If there are duplicate dsd values on the threshold these are all left in + # This leaves everything in in the case of a flatline demand + df['dsd'] = df['dsd'].where(df['dsd'] >= thresh_dsd, 0) + + curs.execute( + f"""UPDATE demand_specific_distribution + SET dsd = 0 + WHERE region = '{rpd[0]}' + AND period = '{rpd[1]}' + AND demand_name == '{rpd[2]}' + AND dsd < {thresh_dsd}""" + ) + + # Renormalise + total_dsd = df['dsd'].sum() + curs.execute(f"""UPDATE demand_specific_distribution + SET dsd = dsd / {total_dsd} + WHERE region = '{rpd[0]}' + AND period = '{rpd[1]}' + AND demand_name == '{rpd[2]}'""") + + # If preserving absolute hourly values, adjust annual demand to sum of representative periods + if utils.config['demand_preservation'] == 'hourly': + curs.execute(f"""UPDATE demand SET demand = demand * {total_dsd} + WHERE region = '{rpd[0]}' + AND period = '{rpd[1]}' + AND commodity == '{rpd[2]}'""") + + conn.commit() + + conn.execute("VACUUM;") + conn.commit() + + conn.execute('PRAGMA FOREIGN_KEYS=1;') + try: + data = conn.execute('PRAGMA FOREIGN_KEY_CHECK;').fetchall() + if data: + for row in data: + print(f'{row}') + print('(Table, Row ID, Reference Table, (fkid) )') + print(f'The above foreign keys failed to validate for {out_file}') + except sqlite3.OperationalError as e: + print(f'Foreign keys failed on activation for {out_file}. Something may be wrong with the schema.') + print(e) + + conn.close() + + + +# Collects sqlite databases into a dictionary of form {name: path} +def _get_sqlite_databases(): + + databases = [] + + for dirs in os.walk(input_dir): + files = dirs[2] + + for file in files: + split = os.path.splitext(file) + if split[1] == '.sqlite': databases.append(split[0]) + + return databases + + + +def _get_schema_version(database): + + conn = sqlite3.connect(input_dir + f"{database}.sqlite") + curs = conn.cursor() + + tables = {t[0].lower() for t in curs.execute("SELECT name FROM sqlite_schema").fetchall()} + if 'metadata' not in tables: + print(f"Could not get schema version for {database}. Skipped.") + return 0 + + try: + mj_vers = curs.execute("SELECT value FROM metadata WHERE element = 'DB_MAJOR' COLLATE NOCASE").fetchone() + mn_vers = curs.execute("SELECT value FROM metadata WHERE element = 'DB_MINOR' COLLATE NOCASE").fetchone() + if mj_vers is None or mn_vers is None: return 0 + return int(mj_vers[0]), int(mn_vers[0]) + except Exception: + return 0 + + + +def period_to_days(period: str): + + if "-" not in period: return (period,) + else: + days = [utils.destringify_day(day) for day in period.split("-")] + days = [utils.stringify_day(day) for day in range(days[0],days[1]+1,1)] + return tuple(days) + + + +if __name__ == "__main__": + + if len(sys.argv) <= 1: process_all() + else: + process_database(sys.argv[1]) + print("Finished.") + +def _get_schema_version_for_path(path): + conn = sqlite3.connect(path) + curs = conn.cursor() + tables = {t[0].lower() for t in curs.execute("SELECT name FROM sqlite_schema").fetchall()} + if 'metadata' not in tables: + return 0 + try: + mj_vers = curs.execute("SELECT value FROM metadata WHERE element = 'DB_MAJOR' COLLATE NOCASE").fetchone() + mn_vers = curs.execute("SELECT value FROM metadata WHERE element = 'DB_MINOR' COLLATE NOCASE").fetchone() + if mj_vers is None or mn_vers is None: return 0 + return int(mj_vers[0]), int(mn_vers[0]) + except Exception: + return 0 diff --git a/representative_periods/environment.yml b/representative_periods/environment.yml new file mode 100644 index 0000000..a6764b0 --- /dev/null +++ b/representative_periods/environment.yml @@ -0,0 +1,16 @@ +name: canoe-backend +channels: + - defaults + - conda-forge +dependencies: + - python=3.12 + - matplotlib + - pandas + - numpy + - xmltodict + - openpyxl + - requests + - pyyaml + - xlsxwriter + - scipy + - tsam # WARNING: this is for representative period selection and requires modification. See README in representative_periods \ No newline at end of file diff --git a/representative_periods/feature_selection.py b/representative_periods/feature_selection.py new file mode 100644 index 0000000..c1a9b1a --- /dev/null +++ b/representative_periods/feature_selection.py @@ -0,0 +1,62 @@ +import pandas as pd +from . import utils +import os + + + + + + +# Returns the period index (may be multi-day) with the highest mean value of a given timeseries +def max_mean_period(feature_config: dict): + + this_dir = os.path.realpath(os.path.dirname(__file__)) + + df_timeseries = pd.read_csv( + os.path.join( + this_dir, + "timeseries", + f"{feature_config['timeseries']}.csv", + ), + index_col=0, + ) + + n_days = feature_config['days_in_period'] + total_periods = len(df_timeseries) // (24*n_days) # number of n-day periods in the timeseries + + if n_days % utils.config['days_per_period'] != 0: + print("Tried to add a max_mean_period feature but length of typical periods did not fit " + "neatly inside length of feature period. Would cause indexing issues. Feature skipped.") + return [] + else: typ_per_feature = n_days // utils.config['days_per_period'] # how many typical periods fit inside this feature period? + + # Get the n_day period with highest mean value + max_mean = 0 + max_index = 0 + for p in range(total_periods): + + mean = period_mean(p, df_timeseries, n_days) + + # New high score + if mean > max_mean: + max_index = p + max_mean = mean + + # Convert to indices in the context of typical periods -> may be different length periods + indices = list(range(typ_per_feature*max_index, typ_per_feature*max_index+typ_per_feature)) + return indices + + +# Get the mean value of a timeseries +def period_mean(p, df_timeseries, days_per_period): + + start_index = 24*days_per_period*p + end_index = start_index + 24*days_per_period - 1 + + # This period goes beyond the end of the timeseries so quit + if (end_index >= len(df_timeseries)): + print(p, end_index, len(df_timeseries)) + return + + # Otherwise return the mean + return df_timeseries.iloc[start_index:end_index].mean().iloc[0] \ No newline at end of file diff --git a/representative_periods/input_sqlite/README.txt b/representative_periods/input_sqlite/README.txt new file mode 100644 index 0000000..8c02979 --- /dev/null +++ b/representative_periods/input_sqlite/README.txt @@ -0,0 +1,5 @@ +Any sqlite databases in here will be processed. + +All days are removed except those listed in days.csv, along with any data that references those unused days. + +DemandSpecificDistribution and SegFrac will be processed to match the provided weights per day. \ No newline at end of file diff --git a/representative_periods/output_sqlite/Processed databases output here.txt b/representative_periods/output_sqlite/Processed databases output here.txt new file mode 100644 index 0000000..e69de29 diff --git a/representative_periods/pca.py b/representative_periods/pca.py new file mode 100644 index 0000000..88afbe6 --- /dev/null +++ b/representative_periods/pca.py @@ -0,0 +1,155 @@ + +"""pca_utils.py +Utilities for computing principal components from groups of time series in a DataFrame. + +Assumptions (per user request): +- Group columns are provided as **string column names** (no integer positions). +- **No imputation** is performed. If NaNs exist in a group's columns, a ValueError is raised. + +Example config: +---------------- +config = { + "groups": [ + { + "name": "grp123", + "columns": ["ts1", "ts2", "ts3"], + "n_components": 2, + "scale": True # optional (default True) + }, + { + "name": "single", + "columns": ["ts4"], + "n_components": 1 + } + ] +} + +Usage: +------ +from pca_utils import get_principal_components +pcs_df = get_principal_components(df, config) +""" +from typing import Dict, List +import numpy as np +import pandas as pd + + +def standardise(X: pd.DataFrame) -> tuple[pd.DataFrame, pd.Series, pd.Series]: + """Center (and optionally scale) the columns of X. + + Returns standardised frame, means, stds used. + stds for constant columns are set to 1 to avoid division by zero. + """ + mu = X.mean(axis=0) + Xc = X - mu + + std = X.std(axis=0, ddof=0) + std_replaced = std.replace(0.0, 1.0) # avoid division by zero + return Xc / std_replaced + + +def _pca_scores_via_svd(X: np.ndarray, k: int) -> tuple[np.ndarray, np.ndarray]: + """Compute first k principal component scores and loadings via SVD. + + X should already be centered (and scaled if desired). + Returns (scores, loadings) where: + - scores shape: (n_samples, k) = U[:, :k] * S[:k] + - loadings shape: (k, n_features) = Vt[:k, :] + Also flips signs to make each component's loadings sum positive (deterministic sign). + """ + U, S, Vt = np.linalg.svd(X, full_matrices=False) + k = max(0, min(k, U.shape[1])) + if k == 0: + return np.zeros((X.shape[0], 0)), np.zeros((0, X.shape[1])) + scores = U[:, :k] * S[:k] + loadings = Vt[:k, :] + # Deterministic sign: flip so sum of loadings for each component is >= 0 + for i in range(k): + if np.nansum(loadings[i]) < 0: + loadings[i] *= -1 + scores[:, i] *= -1 + return scores, loadings + + +def get_principal_components(df: pd.DataFrame, groups: list[Dict]) -> pd.DataFrame: + """Compute principal components for groups of time series in `df`. + + Parameters + ---------- + df : pd.DataFrame + A DataFrame indexed by time (or any index) with time series columns. + config : dict + Configuration dict with a "groups" key, a list of group configs. + Each group config is a dict with keys: + - name (str, optional): Used to prefix output columns. If omitted, + a default name like "group0" is used. + - columns (List[str]): Column names in `df` (strings only). + - n_components (int): Number of principal components to return for this group. + - scale (bool, optional): If True (default), z-score each series within the group + prior to PCA. If False, only mean-centers. + + Returns + ------- + pd.DataFrame + DataFrame of principal component scores with the same index as `df`. + Columns are named "{group_name}_pc{1..k}". + + Notes + ----- + - No imputation is performed. If NaNs exist in a group's columns, a ValueError is raised. + - All specified columns must exist and be numeric; otherwise a ValueError is raised. + - If `n_components` exceeds the number of available numeric columns, it is clipped. + """ + + if not isinstance(groups, list) or len(groups) == 0: + raise ValueError("config['groups'] must be a non-empty list") + + out_parts: List[pd.DataFrame] = [] + + for gi, g in enumerate(groups): + name = g.get('name', f'group{gi}') + cols = g.get('columns', []) + k = int(g.get('n_components', 0)) + if k <= 0: + continue # nothing to do + + # Validate columns are strings and exist + if not all(isinstance(c, str) for c in cols): + raise ValueError(f"Group '{name}': all 'columns' must be string names.") + missing = [c for c in cols if c not in df.columns] + if missing: + raise ValueError(f"Group '{name}': columns not found in df: {missing}") + + # Ensure all are numeric + non_numeric = [c for c in cols if not pd.api.types.is_numeric_dtype(df[c])] + if non_numeric: + raise ValueError(f"Group '{name}': non-numeric columns: {non_numeric}") + + X = df[cols].copy().interpolate('linear') + + # Check for NaNs + if X.isna().any().any(): + na_cols = [c for c in cols if X[c].isna().any()] + raise ValueError( + f"Group '{name}': NaNs present in columns {na_cols}. " + "Please drop or impute NaNs before calling get_principal_components." + ) + + # Standardise (center and optionally scale) + X_std = standardise(X) + + # PCA via SVD + k_eff = int(np.clip(k, 0, X_std.shape[1])) + scores, loadings = _pca_scores_via_svd(X_std.to_numpy(), k_eff) + + # Create output columns + col_names = [f"{name}_pc{i+1}" for i in range(k_eff)] + pcs_df = pd.DataFrame(scores, index=df.index, columns=col_names) + out_parts.append(pcs_df) + + if not out_parts: + # Return empty frame with same index if nothing computed + print(f"Got no PCs for {name}") + return pd.DataFrame(index=df.index) + + return pd.concat(out_parts, axis=1) \ No newline at end of file diff --git a/representative_periods/process_all.py b/representative_periods/process_all.py new file mode 100644 index 0000000..17b703a --- /dev/null +++ b/representative_periods/process_all.py @@ -0,0 +1,62 @@ +""" +Runs clustering and processes all databases to selected representative periods. +""" + +import sys +import os +from matplotlib import pyplot as pp + +# Add root directory to path to allow running standalone +sys.path.insert(0, os.path.abspath(os.path.dirname(os.path.dirname(__file__)))) + +from representative_periods import database_processing_v4_0 as dbp_v4 +from representative_periods import clustering +from representative_periods import utils + +def reset_state(): + clustering.reset() + dbp_v4.reset() + +def run(run_clustering=True, input_path=None, output_path=None): + # Reload config so changes made by the CANOE UI are picked up + utils.reload_config() + + # Reset module state because we are no longer starting + # a fresh Python subprocess for every run + reset_state() + + if run_clustering: + clustering.run() + + if input_path and output_path: + dbp_v4.process_all(input_path, output_path) + else: + root_dir = os.path.abspath(os.path.dirname(os.path.dirname(__file__))) + # process all sqlite files in the root + processed_any = False + for file in os.listdir(root_dir): + if file.endswith(".sqlite"): + input_file = os.path.join(root_dir, file) + output_file = os.path.join(root_dir, file.replace(".sqlite", "_processed.sqlite")) + if dbp_v4._get_schema_version_for_path(input_file) == 4: + print(f"Processing {input_file}...") + dbp_v4.process_database(database=None, input_path=input_file, output_path=output_file) + processed_any = True + + if not processed_any: + # Fallback to the original v4_0 parameterless method if no valid v4 databases in root + dbp_v4.process_all() + + print("All processing completed.") + + if utils.config.get("show_plots", False): + print("Showing plots.") + pp.show() + +if __name__ == "__main__": + run_clustering = True + + if len(sys.argv) > 1 and sys.argv[1] == "--no-cluster": + run_clustering = False + + run(run_clustering) \ No newline at end of file diff --git a/representative_periods/requirements.txt b/representative_periods/requirements.txt new file mode 100644 index 0000000..f168da0 --- /dev/null +++ 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21:00:00-05:00,3.264 +2018-12-30 22:00:00-05:00,3.22 +2018-12-30 23:00:00-05:00,3.158 diff --git a/representative_periods/timeseries/process_rninja.py b/representative_periods/timeseries/process_rninja.py new file mode 100644 index 0000000..bb8794d --- /dev/null +++ b/representative_periods/timeseries/process_rninja.py @@ -0,0 +1,52 @@ +import utils +import os +import pandas as pd + + +def get_csvs(): + this_dir = os.path.realpath(os.path.dirname(__file__)) + "/" + filenames = os.listdir(this_dir) + return [filename + for filename in filenames + if filename.endswith('csv') + and filename.startswith('renewables_ninja_country_CA')] + +csvs = [ + # 'ninja-weather-country-CA-irradiance_surface_pop_wtd-merra2.csv', + # 'ninja-weather-country-CA-precipitation_pop_wtd-merra2.csv', + # 'ninja-weather-country-CA-temperature_pop_wtd-merra2.csv', + # 'ninja-weather-country-CA-wind_speed_pop_wtd-merra2.csv', + 'ninja-weather-country-CA-humidity_pop_wtd-merra2.csv', + 'ninja-weather-country-CA-cloud_cover_pop_wtd-merra2.csv' +] + +regions = { + 'AB': 'ab', + 'BC': 'bc', + 'MB': 'mb', + 'NB': 'nb', + 'NF': 'nllab', + 'NS': 'ns', + 'ON': 'on', + 'PE': 'pei', + 'QC': 'qc', + 'SK': 'sk', +} + +for csv in csvs: + for rn_region, region in regions.items(): + + df = pd.read_csv('timeseries/'+csv, skiprows=3, index_col=0)['CA.'+rn_region] + df = utils.realign_timezone(df, 'UTC', 'EST') + df = df.loc[df.index.year == 2018] + df = df.loc[(df.index.dayofyear != 1) & (df.index.dayofyear != 365)] + + name = region + '_' + csv.split("-")[4][0:-8] + df.name = name + print(region, name) + + dir = f'timeseries/{region}' + if not os.path.isdir(dir): + os.mkdir(dir) + + df.to_csv(f"{dir}/{name}.csv") \ No newline at end of file diff --git a/representative_periods/timeseries/qc/qc_cloud_cover.csv b/representative_periods/timeseries/qc/qc_cloud_cover.csv new file mode 100644 index 0000000..6951621 --- /dev/null +++ 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import load_workbook +import sqlite3 +import pandas as pd +import requests +import xmltodict +import urllib.request +import zipfile +import datetime +import pytz +import pickle + + + +# Identify existing or tech variants +def is_exs(tech: str) -> bool: return tech.endswith('-EXS') + + + +def fill_references_table(): + + conn = sqlite3.connect(config.database_file) + curs = conn.cursor() + + references = set() + + # Get all tables + all_tables = [fetch[0] for fetch in curs.execute("SELECT name FROM sqlite_master WHERE type='table';").fetchall()] + + for table in all_tables: + if table == 'references': continue + + # For any table with a reference column + cols = [description[0] for description in curs.execute(f"SELECT * FROM '{table}'").description] + if 'reference' in cols: + + # Get all the unique references and add them to the set + refs = curs.execute(f"SELECT DISTINCT reference FROM '{table}' WHERE length(reference) > 1") + for ref in refs: + for r in ref[0].split('; '): + references.add(r) + + # Add all references in the set to the references tables + for reference in references: + if len(reference) > 1: curs.execute(f"REPLACE INTO 'references'(reference) VALUES('{reference}')") + + conn.commit() + conn.close() + + + +# Cleans up strings for filenames, databases, etc. +def string_cleaner(string): + + return ''.join(letter for letter in string if letter in '- /()–' or letter.isalnum()) + + + +def string_letters(string): + + return ''.join(letter for letter in string_cleaner(string) if letter not in '123456789') + + + +def clean_index(df): + + df.index = [string_letters(idx).lower() for idx in df.index] + + +# Converts the timezone of a dataframe then shifts rows around so that row 0 is hour 0 again +def realign_timezone(df: pd.DataFrame, from_timezone:str=None, to_timezone:str=None, from_utc_offset:int=None, to_utc_offset:int=None, time_col=None): + + df_shifted = df.copy() + + # Get the timestamp column or assume it is the index if not specified + if time_col is None: + time = pd.to_datetime(df_shifted.index) + df_shifted.index = time + else: + time = pd.DatetimeIndex(pd.to_datetime(df_shifted[time_col])) + df_shifted[time_col] = time + + # Get the original timezone, if specified that first otherwise from the data itself + if from_timezone is not None: tz = from_timezone + elif from_utc_offset is not None: tz = pytz.FixedOffset(from_utc_offset*60) + else: tz = time.tz + + if tz is None: raise Exception("Could not identify the original timezone. Try specifying one instead.") + + # Localise if not already timezone aware + if time.tzinfo is None: time = time.tz_localize(tz) + + # Convert to base timezone + if to_timezone is not None: new_tz = to_timezone + elif to_utc_offset is not None: new_tz = tz = pytz.FixedOffset(to_utc_offset*60) + else: new_tz = 'EST' + new_time = time.tz_convert(new_tz) + + # Find where the zeroeth hour ended up + zero_hour = new_time[(new_time.month == 1) & (new_time.day == 1) & (new_time.time == datetime.time(0,0))] + if len(zero_hour) == 0: zero_hour = new_time[new_time.time == datetime.time(0,0)] # workaround in case we have 8760 hours of a leap year (8784) + n_shift = new_time.get_loc(zero_hour[-1]) # [-1] as there is only one value when things are working properly but take last in leap year workaround + + if n_shift == 0: return df_shifted # already aligned + + # Update the time column + if time_col is None: df_shifted.index = new_time + else: df_shifted[time_col] = new_time + + # Rearrange the hours so it starts at 00:00 in this new timezone, depending on which end of the year rolled over + df_shifted = pd.concat([df_shifted.iloc[n_shift:], df_shifted.iloc[0:n_shift]]) + + return df_shifted + \ No newline at end of file diff --git a/representative_periods/timeseriesaggregation.py b/representative_periods/timeseriesaggregation.py new file mode 100644 index 0000000..db0d654 --- /dev/null +++ b/representative_periods/timeseriesaggregation.py @@ -0,0 +1,1366 @@ +# -*- coding: utf-8 -*- + +import copy +import time +import warnings + +import pandas as pd +import numpy as np + +from sklearn.metrics import mean_squared_error, mean_absolute_error +from sklearn.metrics.pairwise import euclidean_distances +from sklearn import preprocessing + +from tsam.periodAggregation import aggregatePeriods +from tsam.representations import representations + +pd.set_option("mode.chained_assignment", None) + +# max iterator while resacling cluster profiles +MAX_ITERATOR = 20 + +# tolerance while rescaling cluster periods to meet the annual sum of the original profile +TOLERANCE = 1e-6 + + +# minimal weight that overwrites a weighting of zero in order to carry the profile through the aggregation process +MIN_WEIGHT = 1e-6 + + +def unstackToPeriods(timeSeries, timeStepsPerPeriod): + """ + Extend the timeseries to an integer multiple of the period length and + groups the time series to the periods. + + :param timeSeries: + :type timeSeries: pandas DataFrame + + :param timeStepsPerPeriod: The number of discrete timesteps which describe one period. required + :type timeStepsPerPeriod: integer + + :returns: - **unstackedTimeSeries** (pandas DataFrame) -- is stacked such that each row represents a + candidate period + - **timeIndex** (pandas Series index) -- is the modification of the original + timeseriesindex in case an integer multiple was created + """ + # init new grouped timeindex + unstackedTimeSeries = timeSeries.copy() + + # initialize new indices + periodIndex = [] + stepIndex = [] + + # extend to inger multiple of period length + if len(timeSeries) % timeStepsPerPeriod == 0: + attached_timesteps = 0 + else: + # calculate number of timesteps which get attached + attached_timesteps = timeStepsPerPeriod - len(timeSeries) % timeStepsPerPeriod + + # take these from the head of the original time series + rep_data = unstackedTimeSeries.head(attached_timesteps) + + # append them at the end of the time series + unstackedTimeSeries = pd.concat([unstackedTimeSeries, rep_data]) + + # create period and step index + for ii in range(0, len(unstackedTimeSeries)): + periodIndex.append(int(ii / timeStepsPerPeriod)) + stepIndex.append(ii - int(ii / timeStepsPerPeriod) * timeStepsPerPeriod) + + # save old index + timeIndex = copy.deepcopy(unstackedTimeSeries.index) + + # create new double index and unstack the time series + unstackedTimeSeries.index = pd.MultiIndex.from_arrays( + [stepIndex, periodIndex], names=["TimeStep", "PeriodNum"] + ) + unstackedTimeSeries = unstackedTimeSeries.unstack(level="TimeStep") + + return unstackedTimeSeries, timeIndex + + + +class TimeSeriesAggregation(object): + """ + Clusters time series data to typical periods. + """ + + CLUSTER_METHODS = [ + "averaging", + "k_means", + "k_medoids", + "k_maxoids", + "hierarchical", + "adjacent_periods", + ] + + REPRESENTATION_METHODS = [ + "meanRepresentation", + "medoidRepresentation", + "maxoidRepresentation", + "minmaxmeanRepresentation", + "durationRepresentation", + "distributionRepresentation", + "distributionAndMinMaxRepresentation", + ] + + EXTREME_PERIOD_METHODS = [ + "None", + "append", + "new_cluster_center", + "replace_cluster_center", + ] + + def __init__( + self, + timeSeries, + resolution=None, + noTypicalPeriods=10, + noSegments=10, + hoursPerPeriod=24, + clusterMethod="hierarchical", + evalSumPeriods=False, + sortValues=False, + sameMean=False, + rescaleClusterPeriods=True, + weightDict=None, + segmentation=False, + extremePeriodMethod="None", + representationMethod=None, + representationDict=None, + distributionPeriodWise=True, + segmentRepresentationMethod=None, + predefClusterOrder=None, + predefClusterCenterIndices=None, + solver="highs", + roundOutput=None, + addPeakMin=None, + addPeakMax=None, + addMeanMin=None, + addMeanMax=None, + addManual=None + ): + """ + Initialize the periodly clusters. + + :param timeSeries: DataFrame with the datetime as index and the relevant + time series parameters as columns. required + :type timeSeries: pandas.DataFrame() or dict + + :param resolution: Resolution of the time series in hours [h]. If timeSeries is a + pandas.DataFrame() the resolution is derived from the datetime + index. optional, default: delta_T in timeSeries + :type resolution: float + + :param hoursPerPeriod: Value which defines the length of a cluster period. optional, default: 24 + :type hoursPerPeriod: integer + + :param noTypicalPeriods: Number of typical Periods - equivalent to the number of clusters. optional, default: 10 + :type noTypicalPeriods: integer + + :param noSegments: Number of segments in which the typical periods shoul be subdivided - equivalent to the + number of inner-period clusters. optional, default: 10 + :type noSegments: integer + + :param clusterMethod: Chosen clustering method. optional, default: 'hierarchical' + |br| Options are: + + * 'averaging' + * 'k_means' + * 'k_medoids' + * 'k_maxoids' + * 'hierarchical' + * 'adjacent_periods' + :type clusterMethod: string + + :param evalSumPeriods: Boolean if in the clustering process also the averaged periodly values + shall be integrated additional to the periodly profiles as parameters. optional, default: False + :type evalSumPeriods: boolean + + :param sameMean: Boolean which is used in the normalization procedure. If true, all time series get normalized + such that they have the same mean value. optional, default: False + :type sameMean: boolean + + :param sortValues: Boolean if the clustering should be done by the periodly duration + curves (true) or the original shape of the data. optional (default: False) + :type sortValues: boolean + + :param rescaleClusterPeriods: Decides if the cluster Periods shall get rescaled such that their + weighted mean value fits the mean value of the original time series. optional (default: True) + :type rescaleClusterPeriods: boolean + + :param weightDict: Dictionary which weights the profiles. It is done by scaling + the time series while the normalization process. Normally all time + series have a scale from 0 to 1. By scaling them, the values get + different distances to each other and with this, they are + differently evaluated while the clustering process. optional (default: None ) + :type weightDict: dict + + :param extremePeriodMethod: Method how to integrate extreme Periods (peak demand, lowest temperature etc.) + into to the typical period profiles. optional, default: 'None' + |br| Options are: + + * None: No integration at all. + * 'append': append typical Periods to cluster centers + * 'new_cluster_center': add the extreme period as additional cluster center. It is checked then for all + Periods if they fit better to the this new center or their original cluster center. + * 'replace_cluster_center': replaces the cluster center of the + cluster where the extreme period belongs to with the periodly profile of the extreme period. (Worst + case system design) + :type extremePeriodMethod: string + + :param representationMethod: Chosen representation. If specified, the clusters are represented in the chosen + way. Otherwise, each clusterMethod has its own commonly used default representation method. + |br| Options are: + + * 'meanRepresentation' (default of 'averaging' and 'k_means') + * 'medoidRepresentation' (default of 'k_medoids', 'hierarchical' and 'adjacent_periods') + * 'minmaxmeanRepresentation' + * 'durationRepresentation'/ 'distributionRepresentation' + * 'distribtionAndMinMaxRepresentation' + :type representationMethod: string + + :param representationDict: Dictionary which states for each attribute whether the profiles in each cluster + should be represented by the minimum value or maximum value of each time step. This enables estimations + to the safe side. This dictionary is needed when 'minmaxmeanRepresentation' is chosen. If not specified, the + dictionary is set to containing 'mean' values only. + :type representationDict: dict + + :param distributionPeriodWise: If durationRepresentation is chosen, you can choose whether the distribution of + each cluster should be separately preserved or that of the original time series only (default: True) + :type distributionPeriodWise: + + :param segmentRepresentationMethod: Chosen representation for the segments. If specified, the segments are + represented in the chosen way. Otherwise, it is inherited from the representationMethod. + |br| Options are: + + * 'meanRepresentation' (default of 'averaging' and 'k_means') + * 'medoidRepresentation' (default of 'k_medoids', 'hierarchical' and 'adjacent_periods') + * 'minmaxmeanRepresentation' + * 'durationRepresentation'/ 'distributionRepresentation' + * 'distribtionAndMinMaxRepresentation' + :type segmentRepresentationMethod: string + + :param predefClusterOrder: Instead of aggregating a time series, a predefined grouping is taken + which is given by this list. optional (default: None) + :type predefClusterOrder: list or array + + :param predefClusterCenterIndices: If predefClusterOrder is give, this list can define the representative + cluster candidates. Otherwise the medoid is taken. optional (default: None) + :type predefClusterCenterIndices: list or array + + :param solver: Solver that is used for k_medoids clustering. optional (default: 'cbc' ) + :type solver: string + + :param roundOutput: Decimals to what the output time series get round. optional (default: None ) + :type roundOutput: integer + + :param addPeakMin: List of column names which's minimal value shall be added to the + typical periods. E.g.: ['Temperature']. optional, default: [] + :type addPeakMin: list + + :param addPeakMax: List of column names which's maximal value shall be added to the + typical periods. E.g. ['EDemand', 'HDemand']. optional, default: [] + :type addPeakMax: list + + :param addMeanMin: List of column names where the period with the cumulative minimal value + shall be added to the typical periods. E.g. ['Photovoltaic']. optional, default: [] + :type addMeanMin: list + + :param addMeanMax: List of column names where the period with the cumulative maximal value + shall be added to the typical periods. optional, default: [] + :type addMeanMax: list + """ + if addMeanMin is None: + addMeanMin = [] + if addMeanMax is None: + addMeanMax = [] + if addPeakMax is None: + addPeakMax = [] + if addPeakMin is None: + addPeakMin = [] + if addManual is None: + addManual = [] + if weightDict is None: + weightDict = {} + self.timeSeries = timeSeries + + self.resolution = resolution + + self.hoursPerPeriod = hoursPerPeriod + + self.noTypicalPeriods = noTypicalPeriods + + self.noSegments = noSegments + + self.clusterMethod = clusterMethod + + self.extremePeriodMethod = extremePeriodMethod + + self.evalSumPeriods = evalSumPeriods + + self.sortValues = sortValues + + self.sameMean = sameMean + + self.rescaleClusterPeriods = rescaleClusterPeriods + + self.weightDict = weightDict + + self.representationMethod = representationMethod + + self.representationDict = representationDict + + self.distributionPeriodWise = distributionPeriodWise + + self.segmentRepresentationMethod = segmentRepresentationMethod + + self.predefClusterOrder = predefClusterOrder + + self.predefClusterCenterIndices = predefClusterCenterIndices + + self.solver = solver + + self.segmentation = segmentation + + self.roundOutput = roundOutput + + self.addPeakMin = addPeakMin + + self.addPeakMax = addPeakMax + + self.addMeanMin = addMeanMin + + self.addMeanMax = addMeanMax + + self.addManual = addManual + + self._check_init_args() + + # internal attributes + self._normalizedMean = None + + return + + def _check_init_args(self): + + # check timeSeries and set it as pandas DataFrame + if not isinstance(self.timeSeries, pd.DataFrame): + if isinstance(self.timeSeries, dict): + self.timeSeries = pd.DataFrame(self.timeSeries) + elif isinstance(self.timeSeries, np.ndarray): + self.timeSeries = pd.DataFrame(self.timeSeries) + else: + raise ValueError( + "timeSeries has to be of type pandas.DataFrame() " + + "or of type np.array() " + "in initialization of object of class " + type(self).__name__ + ) + + # check if extreme periods exist in the dataframe + for peak in self.addPeakMin: + if peak not in self.timeSeries.columns: + raise ValueError( + peak + + ' listed in "addPeakMin"' + + " does not occur as timeSeries column" + ) + for peak in self.addPeakMax: + if peak not in self.timeSeries.columns: + raise ValueError( + peak + + ' listed in "addPeakMax"' + + " does not occur as timeSeries column" + ) + for peak in self.addMeanMin: + if peak not in self.timeSeries.columns: + raise ValueError( + peak + + ' listed in "addMeanMin"' + + " does not occur as timeSeries column" + ) + for peak in self.addMeanMax: + if peak not in self.timeSeries.columns: + raise ValueError( + peak + + ' listed in "addMeanMax"' + + " does not occur as timeSeries column" + ) + + # derive resolution from date time index if not provided + if self.resolution is None: + try: + timedelta = self.timeSeries.index[1] - self.timeSeries.index[0] + self.resolution = float(timedelta.total_seconds()) / 3600 + except AttributeError: + raise ValueError( + "'resolution' argument has to be nonnegative float or int" + + " or the given timeseries needs a datetime index" + ) + except TypeError: + try: + self.timeSeries.index = pd.to_datetime(self.timeSeries.index) + timedelta = self.timeSeries.index[1] - self.timeSeries.index[0] + self.resolution = float(timedelta.total_seconds()) / 3600 + except: + raise ValueError( + "'resolution' argument has to be nonnegative float or int" + + " or the given timeseries needs a datetime index" + ) + + if not (isinstance(self.resolution, int) or isinstance(self.resolution, float)): + raise ValueError("resolution has to be nonnegative float or int") + + # check hoursPerPeriod + if self.hoursPerPeriod is None or self.hoursPerPeriod <= 0: + raise ValueError("hoursPerPeriod has to be nonnegative float or int") + + # check typical Periods + if ( + self.noTypicalPeriods is None + or self.noTypicalPeriods <= 0 + or not isinstance(self.noTypicalPeriods, int) + ): + raise ValueError("noTypicalPeriods has to be nonnegative integer") + self.timeStepsPerPeriod = int(self.hoursPerPeriod / self.resolution) + if not self.timeStepsPerPeriod == self.hoursPerPeriod / self.resolution: + raise ValueError( + "The combination of hoursPerPeriod and the " + + "resulution does not result in an integer " + + "number of time steps per period" + ) + if self.segmentation: + if self.noSegments > self.timeStepsPerPeriod: + warnings.warn( + "The number of segments must be less than or equal to the number of time steps per period. " + "Segment number is decreased to number of time steps per period." + ) + self.noSegments = self.timeStepsPerPeriod + + # check clusterMethod + if self.clusterMethod not in self.CLUSTER_METHODS: + raise ValueError( + "clusterMethod needs to be one of " + + "the following: " + + "{}".format(self.CLUSTER_METHODS) + ) + + # check representationMethod + if ( + self.representationMethod is not None + and self.representationMethod not in self.REPRESENTATION_METHODS + ): + raise ValueError( + "If specified, representationMethod needs to be one of " + + "the following: " + + "{}".format(self.REPRESENTATION_METHODS) + ) + + # check representationMethod + if self.segmentRepresentationMethod is None: + self.segmentRepresentationMethod = self.representationMethod + else: + if self.segmentRepresentationMethod not in self.REPRESENTATION_METHODS: + raise ValueError( + "If specified, segmentRepresentationMethod needs to be one of " + + "the following: " + + "{}".format(self.REPRESENTATION_METHODS) + ) + + # if representationDict None, represent by maximum time steps in each cluster + if self.representationDict is None: + self.representationDict = {i: "mean" for i in list(self.timeSeries.columns)} + # sort representationDict alphabetically to make sure that the min, max or mean function is applied to the right + # column + self.representationDict = ( + pd.Series(self.representationDict).sort_index(axis=0).to_dict() + ) + + # check extremePeriods + if self.extremePeriodMethod not in self.EXTREME_PERIOD_METHODS: + raise ValueError( + "extremePeriodMethod needs to be one of " + + "the following: " + + "{}".format(self.EXTREME_PERIOD_METHODS) + ) + + # check evalSumPeriods + if not isinstance(self.evalSumPeriods, bool): + raise ValueError("evalSumPeriods has to be boolean") + # check sortValues + if not isinstance(self.sortValues, bool): + raise ValueError("sortValues has to be boolean") + # check sameMean + if not isinstance(self.sameMean, bool): + raise ValueError("sameMean has to be boolean") + # check rescaleClusterPeriods + if not isinstance(self.rescaleClusterPeriods, bool): + raise ValueError("rescaleClusterPeriods has to be boolean") + + # check predefClusterOrder + if self.predefClusterOrder is not None: + if not isinstance(self.predefClusterOrder, (list, np.ndarray)): + raise ValueError("predefClusterOrder has to be an array or list") + if self.predefClusterCenterIndices is not None: + # check predefClusterCenterIndices + if not isinstance(self.predefClusterCenterIndices, (list, np.ndarray)): + raise ValueError( + "predefClusterCenterIndices has to be an array or list" + ) + elif self.predefClusterCenterIndices is not None: + raise ValueError( + 'If "predefClusterCenterIndices" is defined, "predefClusterOrder" needs to be defined as well' + ) + + return + + def _normalizeTimeSeries(self, sameMean=False): + """ + Normalizes each time series independently. + + :param sameMean: Decides if the time series should have all the same mean value. + Relevant for weighting time series. optional (default: False) + :type sameMean: boolean + + :returns: normalized time series + """ + min_max_scaler = preprocessing.MinMaxScaler() + normalizedTimeSeries = pd.DataFrame( + min_max_scaler.fit_transform(self.timeSeries), + columns=self.timeSeries.columns, + index=self.timeSeries.index, + ) + + self._normalizedMean = normalizedTimeSeries.mean() + if sameMean: + normalizedTimeSeries /= self._normalizedMean + + return normalizedTimeSeries + + def _unnormalizeTimeSeries(self, normalizedTimeSeries, sameMean=False): + """ + Equivalent to '_normalizeTimeSeries'. Just does the back + transformation. + + :param normalizedTimeSeries: Time series which should get back transformated. required + :type normalizedTimeSeries: pandas.DataFrame() + + :param sameMean: Has to have the same value as in _normalizeTimeSeries. optional (default: False) + :type sameMean: boolean + + :returns: unnormalized time series + """ + from sklearn import preprocessing + + min_max_scaler = preprocessing.MinMaxScaler() + min_max_scaler.fit(self.timeSeries) + + if sameMean: + normalizedTimeSeries *= self._normalizedMean + + unnormalizedTimeSeries = pd.DataFrame( + min_max_scaler.inverse_transform(normalizedTimeSeries), + columns=normalizedTimeSeries.columns, + index=normalizedTimeSeries.index, + ) + + return unnormalizedTimeSeries + + def _preProcessTimeSeries(self): + """ + Normalize the time series, weight them based on the weight dict and + puts them into the correct matrix format. + """ + # first sort the time series in order to avoid bug mention in #18 + self.timeSeries = self.timeSeries.sort_index(axis=1) + + # convert the dataframe to floats + self.timeSeries = self.timeSeries.astype(float) + + # normalize the time series and group them to periodly profiles + self.normalizedTimeSeries = self._normalizeTimeSeries(sameMean=self.sameMean) + + for column in self.weightDict: + if self.weightDict[column] < MIN_WEIGHT: + print( + 'weight of "' + + str(column) + + '" set to the minmal tolerable weighting' + ) + self.weightDict[column] = MIN_WEIGHT + self.normalizedTimeSeries[column] = ( + self.normalizedTimeSeries[column] * self.weightDict[column] + ) + + self.normalizedPeriodlyProfiles, self.timeIndex = unstackToPeriods( + self.normalizedTimeSeries, self.timeStepsPerPeriod + ) + + # check if no NaN is in the resulting profiles + if self.normalizedPeriodlyProfiles.isnull().values.any(): + raise ValueError( + "Pre processed data includes NaN. Please check the timeSeries input data." + ) + + def _postProcessTimeSeries(self, normalizedTimeSeries, applyWeighting=True): + """ + Neutralizes the weighting the time series back and unnormalizes them. + """ + if applyWeighting: + for column in self.weightDict: + normalizedTimeSeries[column] = ( + normalizedTimeSeries[column] / self.weightDict[column] + ) + + unnormalizedTimeSeries = self._unnormalizeTimeSeries( + normalizedTimeSeries, sameMean=self.sameMean + ) + + if self.roundOutput is not None: + unnormalizedTimeSeries = unnormalizedTimeSeries.round( + decimals=self.roundOutput + ) + + return unnormalizedTimeSeries + + def _addExtremePeriods( + self, + groupedSeries, + clusterCenters, + clusterOrder, + extremePeriodMethod="new_cluster_center", + addPeakMin=None, + addPeakMax=None, + addMeanMin=None, + addMeanMax=None, + addManual=None, + ): + """ + Adds different extreme periods based on the to the clustered data, + decribed by the clusterCenters and clusterOrder. + + :param groupedSeries: periodly grouped groupedSeries on which basis it should be decided, + which period is an extreme period. required + :type groupedSeries: pandas.DataFrame() + + :param clusterCenters: Output from clustering with sklearn. required + :type clusterCenters: dict + + :param clusterOrder: Output from clsutering with sklearn. required + :type clusterOrder: dict + + :param extremePeriodMethod: Chosen extremePeriodMethod. The method. optional(default: 'new_cluster_center' ) + :type extremePeriodMethod: string + + :returns: - **newClusterCenters** -- The new cluster centers extended with the extreme periods. + - **newClusterOrder** -- The new cluster order including the extreme periods. + - **extremeClusterIdx** -- A list of indices where in the newClusterCenters are the extreme + periods located. + """ + + # init required dicts and lists + self.extremePeriods = {} + extremePeriodNo = [] + + ccList = [center.tolist() for center in clusterCenters] + + ## Add manually forced extreme periods + for stepNo in addManual: + # add only if stepNo is not already in extremePeriods + # if it is not already a cluster center + if ( + stepNo not in extremePeriodNo + and groupedSeries.loc[stepNo, :].values.tolist() not in ccList + ): + man_col = f"Manual {stepNo}." + self.extremePeriods[man_col] = { + "stepNo": stepNo, + "profile": groupedSeries.loc[stepNo, :].values, + "column": self.timeSeries.columns[0], # not used if recalculating cluster centres + } + extremePeriodNo.append(stepNo) + + # check which extreme periods exist in the profile and add them to + # self.extremePeriods dict + for column in self.timeSeries.columns: + + if column in addPeakMax: + stepNo = groupedSeries[column].max(axis=1).idxmax() + # add only if stepNo is not already in extremePeriods + # if it is not already a cluster center + if ( + stepNo not in extremePeriodNo + and groupedSeries.loc[stepNo, :].values.tolist() not in ccList + ): + max_col = self._append_col_with(column, " max.") + self.extremePeriods[max_col] = { + "stepNo": stepNo, + "profile": groupedSeries.loc[stepNo, :].values, + "column": column, + } + extremePeriodNo.append(stepNo) + + if column in addPeakMin: + stepNo = groupedSeries[column].min(axis=1).idxmin() + # add only if stepNo is not already in extremePeriods + # if it is not already a cluster center + if ( + stepNo not in extremePeriodNo + and groupedSeries.loc[stepNo, :].values.tolist() not in ccList + ): + min_col = self._append_col_with(column, " min.") + self.extremePeriods[min_col] = { + "stepNo": stepNo, + "profile": groupedSeries.loc[stepNo, :].values, + "column": column, + } + extremePeriodNo.append(stepNo) + + if column in addMeanMax: + stepNo = groupedSeries[column].mean(axis=1).idxmax() + # add only if stepNo is not already in extremePeriods + # if it is not already a cluster center + if ( + stepNo not in extremePeriodNo + and groupedSeries.loc[stepNo, :].values.tolist() not in ccList + ): + mean_max_col = self._append_col_with(column, " daily max.") + self.extremePeriods[mean_max_col] = { + "stepNo": stepNo, + "profile": groupedSeries.loc[stepNo, :].values, + "column": column, + } + extremePeriodNo.append(stepNo) + + if column in addMeanMin: + stepNo = groupedSeries[column].mean(axis=1).idxmin() + # add only if stepNo is not already in extremePeriods and + # if it is not already a cluster center + if ( + stepNo not in extremePeriodNo + and groupedSeries.loc[stepNo, :].values.tolist() not in ccList + ): + mean_min_col = self._append_col_with(column, " daily min.") + self.extremePeriods[mean_min_col] = { + "stepNo": stepNo, + "profile": groupedSeries.loc[stepNo, :].values, + "column": column, + } + extremePeriodNo.append(stepNo) + + for periodType in self.extremePeriods: + # get current related clusters of extreme periods + self.extremePeriods[periodType]["clusterNo"] = clusterOrder[ + self.extremePeriods[periodType]["stepNo"] + ] + + # init new cluster structure + newClusterCenters = [] + newClusterOrder = clusterOrder + extremeClusterIdx = [] + + # integrate extreme periods to clusters + if extremePeriodMethod == "append": + # attach extreme periods to cluster centers + for i, cluster_center in enumerate(clusterCenters): + newClusterCenters.append(cluster_center) + for i, periodType in enumerate(self.extremePeriods): + extremeClusterIdx.append(len(newClusterCenters)) + newClusterCenters.append(self.extremePeriods[periodType]["profile"]) + newClusterOrder[self.extremePeriods[periodType]["stepNo"]] = i + len( + clusterCenters + ) + + elif extremePeriodMethod == "new_cluster_center": + for i, cluster_center in enumerate(clusterCenters): + newClusterCenters.append(cluster_center) + # attach extrem periods to cluster centers and consider for all periods + # if the fit better to the cluster or the extrem period + for i, periodType in enumerate(self.extremePeriods): + extremeClusterIdx.append(len(newClusterCenters)) + newClusterCenters.append(self.extremePeriods[periodType]["profile"]) + self.extremePeriods[periodType]["newClusterNo"] = i + len( + clusterCenters + ) + + for i, cPeriod in enumerate(newClusterOrder): + # caclulate euclidean distance to cluster center + cluster_dist = sum( + (groupedSeries.iloc[i].values - clusterCenters[cPeriod]) ** 2 + ) + for ii, extremPeriodType in enumerate(self.extremePeriods): + # exclude other extreme periods from adding to the new + # cluster center + isOtherExtreme = False + for otherExPeriod in self.extremePeriods: + if ( + i == self.extremePeriods[otherExPeriod]["stepNo"] + and otherExPeriod != extremPeriodType + ): + isOtherExtreme = True + # calculate distance to extreme periods + extperiod_dist = sum( + ( + groupedSeries.iloc[i].values + - self.extremePeriods[extremPeriodType]["profile"] + ) + ** 2 + ) + # choose new cluster relation + if extperiod_dist < cluster_dist and not isOtherExtreme: + newClusterOrder[i] = self.extremePeriods[extremPeriodType][ + "newClusterNo" + ] + + elif extremePeriodMethod == "replace_cluster_center": + # Worst Case Clusterperiods + newClusterCenters = clusterCenters + for periodType in self.extremePeriods: + index = groupedSeries.columns.get_loc( + self.extremePeriods[periodType]["column"] + ) + newClusterCenters[self.extremePeriods[periodType]["clusterNo"]][ + index + ] = self.extremePeriods[periodType]["profile"][index] + if ( + not self.extremePeriods[periodType]["clusterNo"] + in extremeClusterIdx + ): + extremeClusterIdx.append( + self.extremePeriods[periodType]["clusterNo"] + ) + + return newClusterCenters, newClusterOrder, extremeClusterIdx + + def _append_col_with(self, column, append_with=" max."): + """Appends a string to the column name. For MultiIndexes, which turn out to be + tuples when this method is called, only last level is changed""" + if isinstance(column, str): + return column + append_with + elif isinstance(column, tuple): + col = list(column) + col[-1] = col[-1] + append_with + return tuple(col) + + def _rescaleClusterPeriods(self, clusterOrder, clusterPeriods, extremeClusterIdx): + """ + Rescale the values of the clustered Periods such that mean of each time + series in the typical Periods fits the mean value of the original time + series, without changing the values of the extremePeriods. + """ + weightingVec = pd.Series(self._clusterPeriodNoOccur).values + typicalPeriods = pd.concat([ + pd.Series(s, index=self.normalizedPeriodlyProfiles.columns) + for s in self.clusterPeriods + ], axis=1).T + idx_wo_peak = np.delete(typicalPeriods.index, extremeClusterIdx) + for column in self.timeSeries.columns: + diff = 1 + sum_raw = self.normalizedPeriodlyProfiles[column].sum().sum() + sum_peak = np.sum( + weightingVec[extremeClusterIdx] + * typicalPeriods[column].loc[extremeClusterIdx, :].sum(axis=1) + ) + sum_clu_wo_peak = np.sum( + weightingVec[idx_wo_peak] + * typicalPeriods[column].loc[idx_wo_peak, :].sum(axis=1) + ) + + # define the upper scale dependent on the weighting of the series + scale_ub = 1.0 + if self.sameMean: + scale_ub = ( + scale_ub + * self.timeSeries[column].max() + / self.timeSeries[column].mean() + ) + if column in self.weightDict: + scale_ub = scale_ub * self.weightDict[column] + + # difference between predicted and original sum + diff = abs(sum_raw - (sum_clu_wo_peak + sum_peak)) + + # use while loop to rescale cluster periods + a = 0 + while diff > sum_raw * TOLERANCE and a < MAX_ITERATOR: + # rescale values + typicalPeriods.loc[idx_wo_peak, column] = ( + typicalPeriods[column].loc[idx_wo_peak, :].values + * (sum_raw - sum_peak) + / sum_clu_wo_peak + ) + + # reset values higher than the upper sacle or less than zero + typicalPeriods[column] = typicalPeriods[column].clip(lower=0, upper=scale_ub) + + typicalPeriods[column] = typicalPeriods[column].fillna(0.0) + + # calc new sum and new diff to orig data + sum_clu_wo_peak = np.sum( + weightingVec[idx_wo_peak] + * typicalPeriods[column].loc[idx_wo_peak, :].sum(axis=1) + ) + diff = abs(sum_raw - (sum_clu_wo_peak + sum_peak)) + a += 1 + if a == MAX_ITERATOR: + deviation = str(round((diff / sum_raw) * 100, 2)) + warnings.warn( + 'Max iteration number reached for "' + + str(column) + + '" while rescaling the cluster periods.' + + " The integral of the aggregated time series deviates by: " + + deviation + + "%" + ) + return typicalPeriods.values + + def _clusterSortedPeriods(self, candidates, n_init=20): + """ + Runs the clustering algorithms for the sorted profiles within the period + instead of the original profiles. (Duration curve clustering) + """ + # initialize + normalizedSortedPeriodlyProfiles = copy.deepcopy( + self.normalizedPeriodlyProfiles + ) + for column in self.timeSeries.columns: + # sort each period individually + df = normalizedSortedPeriodlyProfiles[column] + values = df.values + values.sort(axis=1) + values = values[:, ::-1] + normalizedSortedPeriodlyProfiles[column] = pd.DataFrame( + values, df.index, df.columns + ) + sortedClusterValues = normalizedSortedPeriodlyProfiles.values + + ( + altClusterCenters, + self.clusterCenterIndices, + clusterOrders_C, + ) = aggregatePeriods( + sortedClusterValues, + n_clusters=self.noTypicalPeriods, + n_iter=30, + solver=self.solver, + clusterMethod=self.clusterMethod, + representationMethod=self.representationMethod, + representationDict=self.representationDict, + distributionPeriodWise=self.distributionPeriodWise, + timeStepsPerPeriod=self.timeStepsPerPeriod, + ) + + clusterCenters_C = [] + + # take the clusters and determine the most representative sorted + # period as cluster center + for clusterNum in np.unique(clusterOrders_C): + indice = np.where(clusterOrders_C == clusterNum)[0] + if len(indice) > 1: + # mean value for each time step for each time series over + # all Periods in the cluster + currentMean_C = sortedClusterValues[indice].mean(axis=0) + # index of the period with the lowest distance to the cluster + # center + mindistIdx_C = np.argmin( + np.square(sortedClusterValues[indice] - currentMean_C).sum(axis=1) + ) + # append original time series of this period + medoid_C = candidates[indice][mindistIdx_C] + + # append to cluster center + clusterCenters_C.append(medoid_C) + + else: + # if only on period is part of the cluster, add this index + clusterCenters_C.append(candidates[indice][0]) + + return clusterCenters_C, clusterOrders_C + + def createTypicalPeriods(self): + """ + Clusters the Periods. + + :returns: **self.typicalPeriods** -- All typical Periods in scaled form. + """ + self._preProcessTimeSeries() + + # check for additional cluster parameters + if self.evalSumPeriods: + evaluationValues = ( + self.normalizedPeriodlyProfiles.stack(level=0) + .sum(axis=1) + .unstack(level=1) + ) + # how many values have to get deleted later + delClusterParams = -len(evaluationValues.columns) + candidates = np.concatenate( + (self.normalizedPeriodlyProfiles.values, evaluationValues.values), + axis=1, + ) + else: + delClusterParams = None + candidates = self.normalizedPeriodlyProfiles.values + + # skip aggregation procedure for the case of a predefined cluster sequence and get only the correct representation + if not self.predefClusterOrder is None: + self._clusterOrder = self.predefClusterOrder + # check if representatives are defined + if not self.predefClusterCenterIndices is None: + self.clusterCenterIndices = self.predefClusterCenterIndices + self.clusterCenters = candidates[self.predefClusterCenterIndices] + else: + # otherwise take the medoids + self.clusterCenters, self.clusterCenterIndices = representations( + candidates, + self._clusterOrder, + default="medoidRepresentation", + representationMethod=self.representationMethod, + representationDict=self.representationDict, + timeStepsPerPeriod=self.timeStepsPerPeriod, + ) + else: + cluster_duration = time.time() + if not self.sortValues: + # cluster the data + ( + self.clusterCenters, + self.clusterCenterIndices, + self._clusterOrder, + ) = aggregatePeriods( + candidates, + n_clusters=self.noTypicalPeriods, + n_iter=100, + solver=self.solver, + clusterMethod=self.clusterMethod, + representationMethod=self.representationMethod, + representationDict=self.representationDict, + distributionPeriodWise=self.distributionPeriodWise, + timeStepsPerPeriod=self.timeStepsPerPeriod, + ) + else: + self.clusterCenters, self._clusterOrder = self._clusterSortedPeriods( + candidates + ) + self.clusteringDuration = time.time() - cluster_duration + + # get cluster centers without additional evaluation values + self.clusterPeriods = [] + for i, cluster_center in enumerate(self.clusterCenters): + self.clusterPeriods.append(cluster_center[:delClusterParams]) + + if not self.extremePeriodMethod == "None": + # overwrite clusterPeriods and clusterOrder + ( + self.clusterPeriods, + self._clusterOrder, + self.extremeClusterIdx, + ) = self._addExtremePeriods( + self.normalizedPeriodlyProfiles, + self.clusterPeriods, + self._clusterOrder, + extremePeriodMethod=self.extremePeriodMethod, + addPeakMin=self.addPeakMin, + addPeakMax=self.addPeakMax, + addMeanMin=self.addMeanMin, + addMeanMax=self.addMeanMax, + addManual=self.addManual + ) + else: + self.extremeClusterIdx = [] + + # get number of appearance of the the typical periods + nums, counts = np.unique(self._clusterOrder, return_counts=True) + self._clusterPeriodNoOccur = {num: counts[ii] for ii, num in enumerate(nums)} + + if self.rescaleClusterPeriods: + self.clusterPeriods = self._rescaleClusterPeriods( + self._clusterOrder, self.clusterPeriods, self.extremeClusterIdx + ) + + # if additional time steps have been added, reduce the number of occurrence of the typical period + # which is related to these time steps + if not len(self.timeSeries) % self.timeStepsPerPeriod == 0: + self._clusterPeriodNoOccur[self._clusterOrder[-1]] -= ( + 1 + - float(len(self.timeSeries) % self.timeStepsPerPeriod) + / self.timeStepsPerPeriod + ) + + # put the clustered data in pandas format and scale back + self.normalizedTypicalPeriods = pd.concat([ + pd.Series(s, index=self.normalizedPeriodlyProfiles.columns) + for s in self.clusterPeriods + ], axis=1).unstack("TimeStep").T + + if self.segmentation: + from tsam.utils.segmentation import segmentation + + ( + self.segmentedNormalizedTypicalPeriods, + self.predictedSegmentedNormalizedTypicalPeriods, + ) = segmentation( + self.normalizedTypicalPeriods, + self.noSegments, + self.timeStepsPerPeriod, + representationMethod=self.segmentRepresentationMethod, + representationDict=self.representationDict, + distributionPeriodWise=self.distributionPeriodWise, + ) + self.normalizedTypicalPeriods = ( + self.segmentedNormalizedTypicalPeriods.reset_index(level=3, drop=True) + ) + + self.typicalPeriods = self._postProcessTimeSeries(self.normalizedTypicalPeriods) + + # check if original time series boundaries are not exceeded + if np.array( + self.typicalPeriods.max(axis=0) > self.timeSeries.max(axis=0) + ).any(): + warning_list = self.typicalPeriods.max(axis=0) < self.timeSeries.max(axis=0) + warnings.warn( + "Something went wrong... At least one maximal value of the " + + "aggregated time series exceeds the maximal value " + + "the input time series for: " + + "{}".format(list(warning_list[warning_list>0].index)) + ) + if np.array( + self.typicalPeriods.min(axis=0) < self.timeSeries.min(axis=0) + ).any(): + warning_list = self.typicalPeriods.min(axis=0) < self.timeSeries.min(axis=0) + warnings.warn( + "Something went wrong... At least one minimal value of the " + + "aggregated time series exceeds the minimal value " + + "the input time series for: " + + "{}".format(list(warning_list[warning_list>0].index)) + ) + return self.typicalPeriods + + def prepareEnersysInput(self): + """ + Creates all dictionaries and lists which are required for the energy system + optimization input. + """ + warnings.warn( + '"prepareEnersysInput" is deprecated, since the created attributes can be directly accessed as properties', + DeprecationWarning, + ) + return + + @property + def stepIdx(self): + """ + Index inside a single cluster + """ + if self.segmentation: + return [ix for ix in range(0, self.noSegments)] + else: + return [ix for ix in range(0, self.timeStepsPerPeriod)] + + @property + def clusterPeriodIdx(self): + """ + Index of the clustered periods + """ + if not hasattr(self, "clusterOrder"): + self.createTypicalPeriods() + return np.sort(np.unique(self._clusterOrder)) + + @property + def clusterOrder(self): + """ + The sequence/order of the typical period to represent + the original time series + """ + if not hasattr(self, "_clusterOrder"): + self.createTypicalPeriods() + return self._clusterOrder + + @property + def clusterPeriodNoOccur(self): + """ + How often does a typical period occur in the original time series + """ + if not hasattr(self, "clusterOrder"): + self.createTypicalPeriods() + return self._clusterPeriodNoOccur + + @property + def clusterPeriodDict(self): + """ + Time series data for each period index as dictionary + """ + if not hasattr(self, "_clusterOrder"): + self.createTypicalPeriods() + if not hasattr(self, "_clusterPeriodDict"): + self._clusterPeriodDict = {} + for column in self.typicalPeriods: + self._clusterPeriodDict[column] = self.typicalPeriods[column].to_dict() + return self._clusterPeriodDict + + @property + def segmentDurationDict(self): + """ + Segment duration in time steps for each period index as dictionary + """ + if not hasattr(self, "_clusterOrder"): + self.createTypicalPeriods() + if not hasattr(self, "_segmentDurationDict"): + if self.segmentation: + self._segmentDurationDict = ( + self.segmentedNormalizedTypicalPeriods.drop( + self.segmentedNormalizedTypicalPeriods.columns, axis=1 + ) + .reset_index(level=3, drop=True) + .reset_index(2) + .to_dict() + ) + else: + self._segmentDurationDict = self.typicalPeriods.drop( + self.typicalPeriods.columns, axis=1 + ) + self._segmentDurationDict["Segment Duration"] = 1 + self._segmentDurationDict = self._segmentDurationDict.to_dict() + warnings.warn( + "Segmentation is turned off. All segments are consistent the time steps." + ) + return self._segmentDurationDict + + def predictOriginalData(self): + """ + Predicts the overall time series if every period would be placed in the + related cluster center + + :returns: **predictedData** (pandas.DataFrame) -- DataFrame which has the same shape as the original one. + """ + if not hasattr(self, "_clusterOrder"): + self.createTypicalPeriods() + + # list up typical periods according to their order of occurrence using the _clusterOrder. + new_data = [] + for label in self._clusterOrder: + # if segmentation is used, use the segmented typical periods with predicted time steps with the same number + # of time steps as unsegmented typical periods + if self.segmentation: + new_data.append( + self.predictedSegmentedNormalizedTypicalPeriods.loc[label, :] + .unstack() + .values + ) + else: + # new_data.append(self.clusterPeriods[label]) + new_data.append( + self.normalizedTypicalPeriods.loc[label, :].unstack().values + ) + + # back in matrix + clustered_data_df = pd.DataFrame( + new_data, + columns=self.normalizedPeriodlyProfiles.columns, + index=self.normalizedPeriodlyProfiles.index, + ) + clustered_data_df = clustered_data_df.stack(level="TimeStep", future_stack=True) + + # back in form + self.normalizedPredictedData = pd.DataFrame( + clustered_data_df.values[: len(self.timeSeries)], + index=self.timeSeries.index, + columns=self.timeSeries.columns, + ) + # normalize again if sameMean = True to avoid doubled unnormalization when using _postProcessTimeSeries after + # createTypicalPeriods has been called + if self.sameMean: + self.normalizedPredictedData /= self._normalizedMean + self.predictedData = self._postProcessTimeSeries( + self.normalizedPredictedData, applyWeighting=False + ) + + return self.predictedData + + def indexMatching(self): + """ + Relates the index of the original time series with the indices + represented by the clusters + + :returns: **timeStepMatching** (pandas.DataFrame) -- DataFrame which has the same shape as the original one. + """ + if not hasattr(self, "_clusterOrder"): + self.createTypicalPeriods() + + # create aggregated period and time step index lists + periodIndex = [] + stepIndex = [] + for label in self._clusterOrder: + for step in range(self.timeStepsPerPeriod): + periodIndex.append(label) + stepIndex.append(step) + + # create a dataframe + timeStepMatching = pd.DataFrame( + [periodIndex, stepIndex], + index=["PeriodNum", "TimeStep"], + columns=self.timeIndex, + ).T + + # if segmentation is chosen, append another column stating which + if self.segmentation: + segmentIndex = [] + for label in self._clusterOrder: + segmentIndex.extend( + np.repeat( + self.segmentedNormalizedTypicalPeriods.loc[ + label, : + ].index.get_level_values(0), + self.segmentedNormalizedTypicalPeriods.loc[ + label, : + ].index.get_level_values(1), + ).values + ) + timeStepMatching = pd.DataFrame( + [periodIndex, stepIndex, segmentIndex], + index=["PeriodNum", "TimeStep", "SegmentIndex"], + columns=self.timeIndex, + ).T + + return timeStepMatching + + def accuracyIndicators(self): + """ + Compares the predicted data with the original time series. + + :returns: **pd.DataFrame(indicatorRaw)** (pandas.DataFrame) -- Dataframe containing indicators evaluating the + accuracy of the + aggregation + """ + if not hasattr(self, "predictedData"): + self.predictOriginalData() + + indicatorRaw = { + "RMSE": {}, + "RMSE_duration": {}, + "MAE": {}, + } # 'Silhouette score':{}, + + for column in self.normalizedTimeSeries.columns: + if self.weightDict: + origTS = self.normalizedTimeSeries[column] / self.weightDict[column] + else: + origTS = self.normalizedTimeSeries[column] + predTS = self.normalizedPredictedData[column] + indicatorRaw["RMSE"][column] = np.sqrt(mean_squared_error(origTS, predTS)) + indicatorRaw["RMSE_duration"][column] = np.sqrt( + mean_squared_error( + origTS.sort_values(ascending=False).reset_index(drop=True), + predTS.sort_values(ascending=False).reset_index(drop=True), + ) + ) + indicatorRaw["MAE"][column] = mean_absolute_error(origTS, predTS) + + return pd.DataFrame(indicatorRaw) + + def totalAccuracyIndicators(self): + """ + Derives the accuracy indicators over all time series + """ + return np.sqrt(self.accuracyIndicators().pow(2).sum()/len(self.normalizedTimeSeries.columns)) diff --git a/representative_periods/utils.py b/representative_periods/utils.py new file mode 100644 index 0000000..f65633f --- /dev/null +++ b/representative_periods/utils.py @@ -0,0 +1,60 @@ +""" +Common utility scripts +""" + +import os +import yaml + +this_dir = os.path.realpath(os.path.dirname(__file__)) + "/" +config_path = os.path.join(this_dir, "config.yaml") + + +def load_config() -> dict: + with open(config_path, "r", encoding="utf-8") as stream: + loaded = yaml.load(stream, Loader=yaml.Loader) + + return dict(loaded or {}) + + +def reload_config() -> dict: + global config + + config = load_config() + return config + + +config: dict = load_config() + + +def stringify_hour(hour: int) -> str: + + hour = int(hour) + return f"H0{hour}" if hour<10 else f"H{hour}" + + +def stringify_day(day: int) -> str: + + day = int(day) + return f"D00{day}" if day<10 else f"D0{day}" if day<100 else f"D{day}" + + +def destringify_day(day: str) -> str: + + return int(day[1:]) + + +def index_to_season(idx: int): + + day = index_to_day(idx) + + if config['days_per_period'] == 1: return stringify_day(day) + elif config['days_per_period'] > 1: + day_2 = day + config['days_per_period'] - 1 + + return f"{stringify_day(day)}-{stringify_day(day_2)}" + + +def index_to_day(idx: int): + + d = idx * config['days_per_period'] - config['day_to_index'] + return d \ No newline at end of file diff --git a/requirements.txt b/requirements.txt index 8c5bb43..8114eec 100644 --- a/requirements.txt +++ b/requirements.txt @@ -15,4 +15,12 @@ pytz==2025.2 repath==0.9.0 six==1.17.0 sniffio==1.3.1 -tzdata==2025.2 \ No newline at end of file +tzdata==2025.2 +matplotlib +xmltodict +openpyxl +requests +PyYAML +XlsxWriter +scipy +tsam==3.4.2