Stabilization of Photovoltaic Power System Using GA and PSO Techniques Under Varying Solar Irradiance

This study offers a comparative analysis of two independent optimization techniques: Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) in a PID Controller Utilized in a photovoltaic system to enhance power stability under conditions of fluctuating solar irradiation. The study investigates the performance of each method based on their impact on system stability, overshoot, and undershoot during sudden irradiance changes. Case 1 examines a conventional PID controller, which shows significant overshoot (11.963%) and undershoot (78.463%). In contrast, the GA-optimized system in Case 2 exhibits a notably lower overshoot of 2.104% and undershoot of 51.618%, with faster stabilization. Case 3, using PSO, further improves performance with minimal overshoot (2.142%) and undershoot (51.066%), demonstrating superior system stability. The proportional, integral, and derivative parameters for each case are analyzed, with Case 3 emerging as the most balanced approach. This study highlights the effectiveness of advanced optimization algorithms like GA and PSO in enhancing the reliability and efficiency of PV systems.