A Comparative Study of PSO, GWO, and HOA Algorithms for Maximum Power Point Tracking in Partially Shaded Photovoltaic Systems
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LGEB, University of Mohamed Khidar , Biskra, Algeria
LGEB, University of Mohamed Khidar , Biskra, Alger
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Fares Bettahar Fares   

LGEB, University of Mohamed Khidar , Biskra, Algeria
Power Electronics and Drives 2024;9 (44)
Solar energy harnessed through photovoltaic technology plays a crucial role in generating electrical energy. Maximizing the power output of so-lar modules requires optimal solar radiation. However, challenges arise due to obstacles such as stationary objects, buildings, and sand-laden winds, resulting in multiple points of maximum power on the P-V curve. This problem requires the use of MPPT (Maximum Power Point Track-ing) algorithms, especially in unstable climatic conditions and partial shading scenarios. In this study, we propose a comparative analysis of three MPPT methods: Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), and Hybrid Optimization Algorithm (HOA) under dynamic partial shading conditions. We evaluate the accuracy of these methods using Matlab/Simulink simulations. The results show that all three meth-ods solve partial shading problems effectively and with high precision. Furthermore, the HOA approach has superior tracking accuracy and faster convergence compared to the other proposed methods.
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