Performance analyses of various photovoltaic power plant based on local spectral irradiances in Malaysia using genetic algorithm - Lim, Song Wei (2023)
Solar Photovoltaic (PV) technology is a method that converts solar energy or sunlight into electricity using semiconductor materials. Solar PV technology is renewable and sustainable, and it is environmentally friendly. However, The quantity of solar energy gathered by the fixed tilt solar photovoltaic (PV) system depends significantly on its orientation with respect to the sun, it is because the solar PV system can harvest the most solar radiation when the panel surface is perpendicular to the sunray. In order to harvest maximum amount of solar irradiance, a fixed tilt solar PV system must be set up with the optimal tilt angle and orientation angle so that it is efficient and able to generate maximum amount of energy. This project aims to measure the performances of various photovoltaic power plants in Malaysia based on local spectral irradiances using genetic algorithm. A Python computational model that uses genetic algorithms will be developed to estimate the optimal tilt angle and orientation angle as well as the solar power received for the solar sites. The solar sites will be evaluated based on their annual average solar irradiation and the optimal tilt angle and orientation angle for solar panel at the solar sites can be estimated using the computational model. Based on the analysis result, by comparing the simulation result of tilt angle and orientation angle with the actual on-site experiment result of tilt angle and orientation angle, the model in this project is able to achieve 75% accuracy. Besides, the genetic algorithm has showed that it is an effective and efficient way to perform estimation of optimal tilt angle and orientation angle for solar sites with genetic algorithm as it is able to produce correct and accurate result in a short amount of time.