Optimization of PV Array Using Particle Swarm Optimization (PSO)

This research investigates the implementation of the Maximum Power Point Tracking (MPPT) method using the Particle Swarm Optimization (PSO) algorithm in photovoltaic systems to optimize output power under various irradiance conditions, including normal, fluctuating, and partially shaded scenarios. The research methodology includes photovoltaic framework modeling and recreation in MATLAB Simulink environment, counting the plan of boost converter to extend output voltage as well as the implementation of PSO calculation to maximize power tracking efficiency. Simulation results show that MPPT with PSO has a higher tracking efficiency than the conventional method, which is 97% under normal and changing irradiance conditions, and 85% under partially shaded conditions. The PSO algorithm proved to be effective in overcoming the local maximum phenomenon in partially shaded conditions. Simulations moreover show that PSO MPPT is able to extend output power significantly compared to ordinary methods. This research contributes to optimizing renewable energy systems, especially in photovoltaic applications, by integrating the PSO algorithm into the MPPT system to increase the efficiency of the energy produced, especially in non-ideal lighting conditions