基于差分进化算法的阴影影响下光伏阵列MPPT控制研究

当光伏模块受到阴影影响时，其功率-电压（P-V）特性曲线有多个峰值点，传统最大功率跟踪控制（MPPT）算法，如扰动观察法（P&O），由于采用局部搜索范围，无法准确跟踪全局最大功率点（GMPP）。提出一种基于差分进化（DE）最优算法的全局最大功率点跟踪方法，同时修正了算法的变异方向，使得所有变异算子总能收敛到最优，有助于算法快速收敛。采用Matlab/Simulink对所述算法进行了仿真分析，并与传统扰动观察法进行了对比，本文所述MPPT方法具有更高的效率和功率输出。

Research on MPPT Control of Partially Shaded Photovoltaic Array Based on Differential Evolution Algorithm

When PV module is partially shaded, there will be multi peeks in the power-voltage(P-V) characteristic curve. And conventional maximum power point tracking (MPPT) algorithm, such as perturbation and observation(P&O), cannot accurately track global maximum power point(GMPP) due to its local searching area. This paper proposes a differential evolution(DE) based GMPP tracking algorithm which makes all particles converging to the best solution by modifying the direction of mutation. This helps the algorithm to converge rapidly. Simulation of the proposed algorithm is carried out in Matlab/Simulink and is compared to P&O algorithm.