关键词: 光伏阵列, 最大功率点追踪, 粒子群算法, 学习因子

Abstract:

Due to the influence of the external environment,PV arrays are prone to local shading.At this time,the P-V characteristic curve of the battery will be converted from the original unipolar value to the multipole value,and the traditional maximum power point tracking (MPPT) control method is easy to fall into the local extremum.To this end,this paper introduces an improved particle swarm optimization algorithm that combines asynchronous time-varying learning factors with linear time-varying inertia weights.The simulation by MATLAB/Simulink shows that the improved particle swarm optimization algorithm can achieve MPPT better under the multi-extreme P-V characteristic curve.

Key words: PV array, maximum power point tracking (MPPT), PSO, learning factor