Comparative Assessment of MPPT Techniques for Solar PV Systems Under Uniform Insolation and Partial Shading Conditions

This research focuses on a comparative assessment of various Maximum Power Point Tracking (MPPT) techniques for solar photovoltaic (PV) systems under uniform insolation and partial shading conditions. iSolar PV technology is a key alternative to fossil fuels due to its non-polluting operation. However, conventional MPPT methods fail to track the global maximum power point under partial shading, where the PV curve presents multiple local maxima. To address this, the study evaluates four MPPT algorithms: Perturb and Observe (P&O), Incremental Conductance (IC), Particle Swarm Optimization (PSO), and Fuzzy Logic Control. These techniques were simulated in MATLAB/Simulink to assess their performance under varying environmental conditions. Results show that the Fuzzy Logic algorithm outperforms the others, achieving 97.2% tracking efficiency and delivering 350W of power from a 365W panel at 1000W/m² irradiance. In contrast, PSO, IC, and P&O achieved 255W, 195W, and 130W, respectively, with lower tracking efficiencies. The Fuzzy Logic method alsoi exhibited faster response times and fewer oscillations. These findings demonstrate the superiority of Fuzzy Logic Control, making it the most suitable MPPT technique for solar PV systems under partial shading.