HVAC Energy Predictor Final Project

Background

Heating, Ventilation, and Air Conditioning (HVAC) systems account for approximately 25% to 50% of the total energy consumption in residential buildings. Architectural design factors, including building size, shape, and orientation, significantly impact heating and cooling loads. A detailed analysis of these relationships can lead to the development of more energy-efficient home designs.

For a detailed description of the dataset used in this project, please refer to the dataset documentation here.

Objectives

1. Literature Review:

   • Investigate the challenges associated with minimizing HVAC energy consumption in residential settings.
   • Assess the benefits of using data models for predicting HVAC energy requirements compared to traditional methods.

2. Data Analysis and Modeling:

   • Analyze the provided dataset to build models predicting heating and cooling loads.
   • Develop and validate these models based on various architectural features.

3. User Interface Development:

   • Create an interface that allows users to input data and receive estimates for heating and cooling loads.
   • Implement functionality for users to add new observations to the database, with automatic updates to the data models.

Tasks

1. Literature Research:

   • Describe the challenges of reducing HVAC energy consumption.
   • Summarize the advantages of using data models for HVAC energy prediction compared to conventional methods.

2. Database Analysis:

   • Explore and analyze the dataset to build predictive models for heating and cooling loads.
   • Evaluate the impact of architectural features on energy consumption.

3. Interface Design:

   • Develop a user interface for estimating HVAC energy loads.
   • Include features for users to add new data entries and ensure that the models are updated automatically.

Contributions

This project is part of the coursework for [Course Name] at [University Name]. Contributions are primarily from the course team, and external contributions are not accepted at this time.

License

This project is intended for educational purposes in accordance with the academic guidelines of Texas Tech University. Refer to the university's academic integrity policies for more details.