An intelligent algorithm for maximum power point tracking in photovoltaic system under partial shading conditions

In a photovoltaic (PV) system, maximum power point tracking (MPPT) under partial shading (PS) conditions is a challenging task due to the presence of multiple peaks in the power voltage characteristics. This paper puts forward a novel artificial fish-swarm algorithm (FSA), which is optimized by particle swarm optimization with extended memory (PSOEM-FSA). In this algorithm, both the velocity inertia factor and the memory and learning capacity of PSOEM are introduced into the FSA. To validate the effectiveness of the novel algorithm, the PV system along with the proposed MPPT algorithm was simulated using Matlab/Simulink Simscape tool box. The simulation results show that the proposed approach is effective in MPPT under PS conditions and has a more stable performance when compared with the traditional methods in convergence speed and searching precision.