Optimization of Photovoltaic Systems Under Partial Shading: A Comparative Analysis of PSO and P&O Algorithms

Abstract

Partial shading and variation in irradiation affect the photovoltaic system, especially its maximum power point (MPP); hence the need for effective tracking techniques. Several algorithms have been developed in this direction. The algorithm of Perturb and Observe (noted P&O) is one of the most popular methods for this fact, given its simplicity of implementation. However, this method has some limitations, including oscillations around the MPP and slow response, which leads to a decrease in the value of the extracted maximum power. To overcome this drawback, Particle Swarm Optimization (noted PSO) has emerged like a promising technique, demonstrating enhanced performance in accurately tracking the power point, especially under partial shading scenarios. It allows for higher tracking accuracy. This paper provides a comparative analysis of these two algorithms under two distinct scenarios. The outcomes found reveal that PSO gives very good accuracy in tracking the global maximum power point (noted GMPP) better than the algorithm of P&O.