It is an R-package allows a reproducible research for non-parametric clustering and downscaling of daily solar irradiation time-series. The current version includes:
-
SIR_DataConstructor function of objects ofSIRDataclass. Once the user creates aSIRDataobject from his data, he no longer need other inputs, ALL the rest work will done automatically. -
DPGMMclusS3 Method for non-parametric Bayesian Dirichlet-Gaussian mixture model clustering of daily clearness index distributions. It can be also used to perform any data clustering of class matrix other than irradiance data. It generate an object of classclusDatacontaining the clustering outputs. -
parClusGenConstructor function of objects ofgenDataclass, needed for the generation of hight resolution solar irradiance data. -
GenDataFunction to generate high resolution solar irradiance time-series. It requires object ofgenDataclass as input. -
clPlotFunction to generate plots of the resulting classes.
The author is happy to answer your questions and is open to future collaborations on this topic. Please contact: azeddine.frimane@yahoo.com or azeddine.frimane@uit.ac.ma.
Users can install the development version of SolarClusGnr:
with either the remotes package:
remotes::install_github("frimane/SolarClusGnr")
or with the devtools package:
devtools::install_github("frimane/SolarClusGnr")
The original paper describing the methods implemented in SolarClusGnr is:
Frimane, Â., Soubdhan, T., Bright, J.M., Aggour, M., 2019. Nonparametric bayesian-based recognition of solar irradiance conditions: Application to the generation of high temporal resolution synthetic solar irradiance data. Solar Energy 182, 462-479. URL:http://www.sciencedirect.com/science/article/pii/S0038092X19301781, doi:https://doi.org/10.1016/j.solener.2019.02.052.
The BibTex entry:
@article{Frimane2019,
title = "Nonparametric Bayesian-based recognition of solar irradiance conditions: Application to the generation of high temporal resolution synthetic solar irradiance data",
journal = "Solar Energy",
volume = "182",
pages = "462-479",
year = "2019",
issn = "0038-092X",
doi = "https://doi.org/10.1016/j.solener.2019.02.052",
url = "http://www.sciencedirect.com/science/article/pii/S0038092X19301781",
author = "{\^A}zeddine Frimane and Ted Soubdhan and Jamie M. Bright and Mohammed Aggour",
keywords = "Solar irradiance, Clustering, Clearness index, Bayesian nonparametric, Synthetic irradiance",
}
This package is free and open source software under MIT-license.