A hybrid MPPT controller for enhanced efficiency of solar photovoltaic systems under partial shading conditions

This paper proposes a hybrid maximum power point tracking (MPPT) controller that integrates Modified Particle Swarm Optimization (MPSO) with Adaptive Fuzzy Logic Control (AFLC) for robust and efficient power tracking under partial shading conditions (PSC). The MPSO component initially explores the global search space to locate the approximate MPP, effectively navigating through the local MPPs. Once the MPP is identified, the AFLC component fine-tunes the duty cycle using linguistic rules, ensuring rapid convergence to the global MPP with minimal oscillations. MATLAB/Simulink tests across five different partial shading patterns demonstrated that the MPSO-AFLC achieves a tracking efficiency of 99.92% ± 0.03%, convergence times between 0.006 and 0.011 s, an average settling time ≤ 0.011 s, and steady-state power oscillations below 5 W. When compared to meta-heuristic algorithms (MPSO, CSA, and GWO) and five recent hybrid methods, the proposed controller demonstrates superior robustness, faster convergence, and smaller steady-state oscillations.