A computational intelligence based maximum power point tracking for photovoltaic power generation system with small‐signal analysis

Abstract There are multiple peak functions in its output power characteristic curve of a photovoltaic (PV) array under partial shading conditions (PSCs), the perturb and observe (P&O) may fail to track global maximum point (GMPP). Therefore, reliable tracking (MPPT) technique is essential GMPP within an appropriate time. This article proposes hybrid by combining evolutionary optimization technique, namely modified invasive weed (MIWO) with conventional P&O algorithm enhance search performance for PV system. MIWO executes initial stages followed at final MPPT process. The combined approach ensures faster convergence better rapid climate change PSCs. MIWO+P&O examined on standalone system through both MATLAB/Simulink environment experimentally using dSPACE (DS1103)‐based real‐time microcontroller hardware setup. proposed scheme compared recent state‐of‐the‐art MPPPT techniques. In addition, small‐signal analysis carried out evaluate loop robustness controller design. For given set parameters, simulations model studies analyzed verify results. overall results justify efficacy algorithm.