Performance And Optimization Of Solar Photovoltaic-Wind Hybrid Energy Systems

Abstract

Solar photovoltaic-wind hybrid energy systems have been developed in response to the growing global demand for sustainable energy. They provide a dependable and effective substitute for conventional power generation. Through the integration of solar PV panels, wind turbines, energy storage, and energy management systems, this study investigates the performance and optimization of such hybrid systems. The project aims to increase energy output, enhance efficiency, and minimize costs using cutting-edge optimization approaches like Genetic Algorithms (GA) and Particle Swarm Optimization (PSO). The findings show that hybrid systems perform better in terms of energy generation and cost-effectiveness than standalone solar or wind systems when they are appropriately tuned. Solar PV-wind hybrid systems are a viable option for sustainable energy development since they lessen dependency on fossil fuels and increase system reliability, especially in regions with diverse environmental circumstances.