Optimized Maximum Power Point Tracking Algorithm for Solar Photovoltaic with Dissimilar Environmental Conditions

The requirement for renewable energy especially solar is growing rapidly day by day. Solar Photovoltaic (PV) is a major type of solar power production in all over the world. A proper simulation studies are required for a solar PV system before implementing them into real time applications to avoid the unwanted errors and drop in system performance. Maximum Power Point Tracking (MPPT) is a technique to capture the maximum power from incident light under dissimilar environmental conditions. In this research work four different types of MPPT algorithms namely Genetic Algorithm (GA), Particle Swarm Optimization (PSO), BAT optimization, and Grey Wolf Optimization (GWO) are used to analyze the performance of Single Diode Model (SDM) solar PV under different solar irradiations with Matlab Simulink. 5 panels are considered and 3 different cases are framed with dissimilar irradiations to study system performance like maximum power and MPPT Power (MPPTP). From the findings of this study, it is confirmed that out of four mentioned algorithms, GWO based MPPT algorithms provides better performance in terms of maximum power and MPPTP.