Sun Tracking Solar Panel Using Machine Learning

Abstract

Increasing demand for electricity will gradually lead to depletion of coal and fossil fuel resources in the near future. Solar energy can be advantageous to a great extent as it is the most abundant form of non-renewable resource. To make most of the power from photovoltaic cells, development should focus on getting greater efficiencies using solar panel arrays. This chapter proposes a sun tracking solar panel system that utilizes machine learning algorithms to optimize the orientation of the solar panels towards the sun. The system is designed to improve the efficiency of energy production by reducing the shading effect and maximizing the amount of sunlight received by the solar panels. Linear regression, polynomial regression, ridge regression, and lasso regression models were used to predict the optimal angle for the solar panels. The results of the study demonstrate that the proposed system using machine learning algorithms can improve the performance of the solar panel system and increase energy production.