Advanced Global Maximum Power Point Tracking (GMPPT) in PV Systems Using a Triangular Four-Subset Fuzzy Logic and P&O Hybrid Approach

Environmental concerns and the need for sustainable development are driving the global demand for renewable energy solutions. Photovoltaic (PV) systems, which convert sunlight directly into electricity, play a significant role in meeting this growing demand and align with the global goals to attain net-zero energy. However, the efficiency of PV systems is influenced by various factors such as atmospheric fluctuations and partial shading of the PV panels. Partial shaded PV panels significantly affect the accuracy of tracking techniques, leading to several local maximum power points (LMPPs), thereby complicating the tracking of the global maximum power point (GMPP). This research proposes a triangular four-subset fuzzy logic controller (T-4 FLC) integrated with the traditional P&O technique, forming an optimized Global Maximum Power Point Tracking (GMPPT) approach. A comparative simulation study was conducted against the traditional P&O technique and an advanced (SOFT) MPPT, the result demonstrates that the proposed hybrid T-4 FLC-P&O method significantly outperformed standard approaches by enhancing the tracking accuracy, which was validated using the EN 50530 standard test, and by reducing the system complexity in achieving optimal power tracking. The study concluded that the proposed hybrid T-4 FLC-P&O improves response time to dynamic irradiance changes, with the system achieving global maximum power point stabilization 30% faster than the conventional approach and 10% faster than the SOFT-MPPT.