Numerical performance evaluation of solar photovoltaic water pumping system under partial shading condition using modern optimization

Renewable energy is an attractive solution for water pumping systems particularly in isolated regions where the utility grid is unavailable. An attempt is made to improve the performance of solar photovoltaic water pumping system (SPVWPS) under partial shading condition. Under this condition, the power versus voltage curve has more than one maximum power point (MPP), which makes the tracking of global MPP not an easy task. Two MPP tracking (MPPT) strategies are proposed and compared for tracking MPP of SPVWPS under shading condition. The first method is based on the classical perturb and observe (P&O) and the other method is based on a Salp Swarm Algorithm (SSA). Based on extensive MATLAB simulation, it is found that the SSA method can provide higher photovoltaic (PV) generated power than the P&O method under shading condition. Consequently, the pump flowrate is increased. But, under normal distribution of solar radiation, both MPPT techniques can extract the maximum power but SSA is considered a time-consuming approach. Moreover, SSA is compared with particle swarm optimization (PSO) and genetic algorithm (GA). The obtained results ensure the superiority of SSA compared with PSO and GA. SSA has high successful rate of reaching true global MPP.