Maximum power point tracking for solar water pumping system under partial shading conditions

Abstract

This report presents innovative approaches to maximize the power output of photovoltaic (PV) systems for water-pumping applications based on BLDC motor, specificall yaddress- ing challenges posed by partial shading, which occurs when certain parts of the PV array are shaded while others are exposed to sunlight. Traditional Maximum Power Point Tracking (MPPT) algorithms, such as the Perturb and Observe (P&O) method, have limitations when it comes to dealing with partial shading, as these algorithms struggle to accurately identify the global maximum power point (GMPP), which is important for achieving optimal power generation. To overcome these limitations, this work introduces advanced metaheuristic algorithms, including Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), and the Marine Predator Algorithm (MPA), to robustly track the GMPP, thus ensuring optimal performance despite variations in solar exposure. Furthermore, the efficienc yo feac halgorith mis compared using simulation models generated in MATLAB/Simulink, where the results demonstrate that these algorithms significantly improve power extraction under partial shading conditions.