Abstract：Aimed at solving the failure problem of the maximum power point tracking (MPPT) algorithm caused by partially shaded condition in the photovoltaic power generation system, a global maximum power point tracking (GMPPT) algorithm based on δ-potential well is proposed. Based on the photovoltaic multi-peak output characteristics when the illumination intensity is changing, the reason of searching blind spot in conventional MPPT algorithm is analyzed in terms of maximum power point transition, and the necessity of GMPPT optimization is explained. A quantum-behaved particle swarm optimization (QPSO) algorithm is proposed to improve the particle diversity and increase the search speed and convergence accuracy. The algorithm was verified by MATLAB/SIMSCAPE and compared with the standard particle swarm optimization (PSO) algorithm. The results show that the proposed algorithm can track the global maximum power point effectively with fast searching speed, reducing the dependency on parameters and avoiding premature convergence of the algorithm.
陈明轩, 武建文, 马速良, 黄炼. 复杂遮蔽条件下光伏多峰出力特征及GMPPT控制[J]. 北京航空航天大学学报, 2017, 43(6): 1141-1148.
CHEN Mingxuan, WU Jianwen, MA Suliang, HUANG Lian. Photovoltaic multi-peak output characteristics and GMPPT control under complex shaded condition. JOURNAL OF BEIJING UNIVERSITY OF AERONAUTICS AND A, 2017, 43(6): 1141-1148.