Development of a machine learning model for the assessment of PV panel efficiency.

Abstract

The purpose of this study was to assess the efficiencies of solar PV panels. We were able to undertake this by training a machine learning model using solar irradiance, windspeed, ambient temperature and panel manufacturer as the independent variables from which we predicted the efficiencies for the respective PV panels. The model was able to perform well based on the used dataset. However, the model would have been more practical if the dataset used was wide enough to account for climatic change and if less assumptions on the panels were made during model development. We were also able to deploy the model for use in a web application