Optimization of Large-Scale Solar Panels Distribution Using Genetic Algorithm

Renewable energy is rapidly growing, and solar power systems are a significant contributor. By 2050, the UAE aims to generate 50% of electric energy from carbon-free sources such as solar photovoltaic (PV). PV panel system's maximum output power varies over time, depending on external elements such as the sun's radiation, the surrounding temperature, dust, wind, etc., which is highly associated with the panel positioning. As of now, there is no well-defined methodology for determining the optimal distribution and positioning of large-scale solar panels to maximize energy output. To tackle this issue, our research investigates the impact of solar panel positioning and distribution on energy efficiency using a Genetic Algorithm (GA). GA is an optimization technique inspired by the principles of natural selection and genetics, known for its effectiveness in solving intricate problems across various domains. We anticipate that this study will contribute to the optimization of distribution and positioning in large-scale solar power plants, ultimately enhancing their performance.