PV maximum power-point tracking using modified particle swarm optimization under partial shading conditions

Abstract

A novel maximum power-point tracking approach is proposed based on studies investigating the output characteristics of photovoltaic (PV) systems under partial shading conditions. The existence of partially shaded conditions leads to the presence of several peaks on PV curves, which decrease the efficiency of conventional techniques. Hence, the proposed algorithm, which is based on the modified particle-swarm optimization (MPSO) technique, increases the output power of PV systems under such abnormal conditions and has a better performance compared to other methods. The proposed method is examined under several scenarios for partial shading condition and non-uniform irradiation levels using Matlab, and to investigate its effectiveness adequately, the results of the proposed method are compared with those of the neural network technique. The experimental results show that the proposed method can decrease the interference of the local maximum power-point to cause the PV system to operate at a global maximum power-point. The efficiency of the MPSO is achieved with the least number of steady-state oscillations under partial shading conditions compared with the neural network method.