Maximum power point tracking in partially shaded photovoltaic systems using grasshopper optimization algorithm

The P-V curve of photovoltaic (PV) arrays has several peaks under partial shading conditions (PSCs). Therefore, to extract maximum power, it is necessary to detect its global maximum power point (GMPP). The conventional maximum power point tracking (MPPT) algorithms are trapped in local maximum power point (LMPP) under PSCs. In this paper, a MPPT method based on grasshopper optimization algorithm (GOA) has been presented. A PV system has been implemented in Matlab/Simulink and different operating conditions have been investigated to compare the performance of the proposed method with two well-known grey wolf optimization (GWO) and particle swarm optimization (PSO) algorithms. Furthermore, an experimental setup has been developed to verify the efficiency of the proposed MPPT method. The simulation and experimental results confirmed the speed and accuracy of convergence compared to GWO and PSO algorithms.