Intelligent Modeling of a Solar Photovoltaic System Located in a Bioclimatic Home

Abstract

The use of renewable energy is expanding globally, driven by the need to reduce greenhouse gas emissions and mitigate climate change. This study focuses on modelling the electrical power generated by photovoltaic panels in a bioclimatic home, analyzing the performance of linear regression and multilayer perceptron models, while considering atmospheric factors such as solar radiation and ambient temperature. The process includes a correlation analysis to select the most relevant variables, followed by dataset preprocessing techniques. Finally, performance metrics of the models are evaluated, which indicate a strong correlation between solar radiation and the power generated, resulting in robust regression models.