<![CDATA[Maximum Power Point Tracking (MPPT) is very important to enhance the energy harvesting capability of photovoltaic (PV) systems under various environmental conditions. But, under dynamic irradiance and partial shading conditions, conventional MPPT architectures may be plagued by poor tracking performance and energy extraction. This study investigates the use of a fuzzy logic controller (FLC) for MPPT and evaluates its performance in both Centralized Maximum Power Point Tracking (CMPPT) and Distributed Maximum Power Point Tracking (DMPPT) architectures. The key outcome of the present study is the comparison of FLC based CMPPT and DMPPT configurations under dynamic irradiance. MATLAB/Simulink based models are established to evaluate the performance measurement with irradiance profiles of 500-1000 W/m2. The assessment included tracking efficiency, convergence behavior, steady state oscillations and recuperating energy capability under various operating scenarios. The simulation results demonstrate that the proposed FLC exhibits a faster response to changes and better tracking capability compared to the baseline MPPT methods considered in this study. The controller achieved tracking performance up to 97% and reduced stable-state oscillations by above 60%. The DMPPT configuration with fuzzy logic control harvested significantly greater amounts of energy than the respective CMPPT configuration under partial shading conditions. The results show that the use of fuzzy logic control with distributed MPPT architectures can improve the robustness and energy harvesting in irregular irradiance conditions, and therefore, this method can be applied to modern photovoltaic systems.]]>
