Improved Photovoltaic Maximum Power Point Tracking Algorithm Integrating Intelligent Fuzzy Control with the Variable-Step-Size Method

To address the inadequate tracking performance of the traditional perturb-and-observe (P&O) method, commonly employed for the maximum power point tracking (MPPT) of photovoltaic (PV) systems, particularly under rapidly changing environmental conditions, this paper proposes an improved MPPT algorithm that combines fuzzy control logic with the variable-step-size method. Here, the fuzzy controller first addresses the uncertainties associated with light-intensity and temperature variations, then predicts the MPP position, and dynamically adjusts the perturbation step size to realize rapid and precise tracking of the MPP. Simulation results demonstrate the superiority of the proposed algorithm over the traditional P&O method and the variable-step-size algorithm in terms of its tracking speed and stability. In particular, the proposed algorithm quickly responds to rapid environmental changes, mitigates power loss, and improves the overall efficiency of the PV system.