Comparison Between Global MPPT Techniques for PV Array Systems Subjected to Different Partially Shaded Conditions

Abstract

Solar photovoltaic (PV) has been shown to be the most reliable source for harvest solar energy. Under varying temperatures and sunshine irradiation, a maximum power point tracking (MPPT) controller was used to make the PV module operate at its maximum power point (MPP). One global MPP and several local MPPs comprise the properties of a solar array under partial shade. Conventional MPPT methods are incapable of reaching global MPP. In this order, the optimization techniques were utilized to extract the GMPP under partial shade conditions (PSCs). Particle Swarm Optimization (PSO), Flower Pollination Algorithm (FPA), and Cuckoo Search (CS) are three frequently utilized optimization techniques that are compared in this paper. The simulation was developed using Matlab/Simulink software to evaluate the tracking performance of MPPT under different partial shading patterns. The results indicate that PSO, FPA and CS-based trackers ensure converging to the global MPP. In addition, In terms of tracking speed, accuracy, and efficiency, the three algorithms' performance is compared. Among the three algorithms, the CS MPPT method had the best tracking efficiency.