Optimization of Solar Panel Efficiency using Genetic Algorithms

Abstract

Maximizing the efficiency of solar panels is crucial for enhancing the viability of solar energy in both residential and commercial sectors. In this study, we employ Genetic Algorithms (GAs) to optimize various parameters affecting solar panel performance, such as tilt angle, azimuth angle, and environmental conditions like temperature and solar irradiance. We develop a model that simulates the efficiency of solar panels under varying conditions and apply GAs to find the optimal configuration. The results demonstrate a significant improvement in energy output, with optimized parameters yielding up to a 15% increase in solar panel efficiency. This research shows the potential of GAs in solving complex optimization problems in renewable energy systems.