Maximum Power Point Tracking of PV Systems Using TFPSO

Abstract

This paper proposes Taguchi Fuzzy Particle Swarm Optimization (TFPSO), and develops a buck converter as the Maximum Power Point Tracker (MPPT) for the photovoltaic (PV) system. The method proposed in this paper can automatically judge the buck mode of this buck converter, in order that the PV panel can implement maximum power output in ideal environments or partially shaded conditions (PSC). First, the Taguchi method is used for the optimization training of the influencing parameters of Fuzzy Particle Swarm Optimization (PSO), and the optimum parameters are obtained from the tracking of the precision-tracking speed trade-off. Afterwards, Matlab/simulink simulation experiments, single-peak power curve, two-peak power curve, three-peak power curve, and computer simulation in different atmospheric environments are conducted. Finally, the fuzzy PSO, PSO, and Perturbation and Observation (P&O) are used for comparison. The results show that TFPSO has the best performance in unimodal and multimodal power curves.