Global maximum power point tracking method based on sorting particle swarm optimizer

Abstract

ABSTRACTThis paper presents a novel global maximum power point tracking (MPPT) method based on the sorting particle swarm optimizer (PSO). At first, the output characteristics of photovoltaic (PV) array under the partial shading conditions are analyzed. As an artificial intelligence algorithm, the sorting PSO is proposed for global MPPT of PV array under partial shading conditions. The principle of the proposed algorithm is illustrated in detail. Second, a stand-alone PV system based on Z-source inverter (ZSI) is simulated to validate the proposed global MPPT method. Then, the experiments are implemented based on the established ZSI. Compared with the conventional PSO for MPPT, simulation and experimental results both reveal that the proposed global MPPT method based on the sorting PSO can reduce the fluctuation of voltage of PV array during MPPT. Simulation results reveal that 61.53% and 51.81% energy consumption during MPPT is reduced under two different typical partial shading conditions. The proposed MPPT method can also track the global maximum power point more rapidly. Approximately 21.21–39.96% time consumptions during MPPT are saved.