Maximum Power Point Tracking of Photovoltaic Power Generation System Based on Improved Gray Wolf Optimization

PV arrays under local shading, their output P-U curves are characterized by nonlinear multi-peaks, and there are problems of insufficient maximum power point tracking (MPPT) accuracy and slow convergence, for which a two-layer control strategy combining the improved Gray Wolf optimization (GWO) and perturb and observe method (P&O) is proposed. The upper-layer control strategy is based on the improved gray wolf algorithm with nonlinear factors and Levy flights for global searching and narrowing the maximum power point (MPP) range, and the lower-layer control strategy is based on the P&O for local searching, which improves the probability of jumping out of the local peaks and improves the searching speed in comparison with the traditional gray wolf algorithm. Through the establishment of simulation verification and comparison with the gray wolf algorithm, both whether it is static shading or dynamic shading search accuracy can reach 99.9%, which verifies the superiority of the algorithm.