Development of Optimized Maximum PowerPoint Tracking Scheme for A Partially Shaded Photovoltaic System

Solar energy harnessed through photovoltaic (PV) technology plays a pivotal role in generating electrical energy. Maximizing the power output of solar modules requires optimal solar radiation. However challenges arise due to obstacles such as stationary objects, building, tree leaves and winds, which can result in the presence of multiple points of maximum power on the PV curve. This problem necessitates the use of maximum power point tracking (MPPT) tracking algorithms, especially in unstable climatic conditions and partial shading scenario. To this effect, five MPPT Algorithms were employed namely perturb and observe (P&O), particle swarm optimization (PSO), flower pollination algorithm (FPA), grey wolf optimization (GWO) and Improved grey wolf optimization (IGWO), taking into consideration, tracking time, efficiency and global maximum power point. The best performance that was observed was Improved Grey Wolf Optimization (IGWO) algorithm, which tracked the Global Maximum Power Point (GMPP) at 975.50 W from an input power of 977.06 W within a very short tracking time of 0.0052 seconds and an efficiency of 99.84%. This shows that IGWO algorithm has improved efficiency by 5.79%, 6.06%, 4.98%, and 3.91% compared to P&O, PSO, FPA, and the baseline (GWO). Similarly, their corresponding tracking times are 0.2918 seconds, 0.7928 seconds, 0.9108 seconds, and 0.7998 seconds more than the IGWO.