Performance Evaluation of Grey Wolf Optimizer and P&O MPPT for PV Systems under Shading

MPPT techniques are fundamental for boosting the efficiency of photovoltaic arrays under varying climatic situations. This work evaluates the performance of the Grey Wolf Optimizer (GWO) strategy, and the classic Perturb and Observe (P&O) technique with step sizes of 0.001 and 0.008 in partially shaded PV systems, where shading complicates the tracking process by introducing multiple local maxima. We use MATLAB/Simulink environment to model and simulate the system using different controllers. Simulation results indicate that the GWO strategy identifies the global maximum power point (GMPP) with higher accuracy and effectiveness under dynamic shading conditions and temperature variations. In contrast, the performance of the P&O strategy is highly related to the chosen step size, which should be selected optimally to balance accuracy, stability, and convergence time. In conclusion, GWO is confirmed to be a more robust and reliable method than P&O, with higher efficiency, especially in challenging irradiance scenarios.