基于粒子群优化算法和变步长扰动观察法的局部阴影情况下MPPT控制

针对光伏阵列的输出特性在局部阴影情况下具有高度非线性、时变性以及多个局部功率极值点等特点,并导致传统MPPT(maximum power point tracking)算法失效的问题,提出一种基于粒子群优化算法和变步长扰动观察法的改进MPPT算法。其中粒子群优化算法用于系统启动和光照情况发生突变后迅速定位近似最大功率点,变步长扰动观察法则根据实际状况使光伏阵列精确稳定在最大功率点,以克服使用数学模型与实际输出特性偏差或微小扰动所导致的功率损失。通过建立Matlab/Simulink模型进行仿真实验,实验结果表明所提算法使光伏阵列在不同阴影情况下以及发生光照强度突变时都具有迅速精确的跟踪能力。

MPPT Control Under Partial Shading Condition Based on PSO and Variable Step Size P&O

For the photovoltaic array in the case of partial shading has high nonlinearity, time-varying uncertainty and several local peak power characteristics, which resulting in conventional MPPT (maximum power point tracking)algorithms failing to work, an algorithm was proposed based on particle swarm optimization (PSO) and variable step size perturbation and observation (P&O) method. PSO was used to quickly locate approximate maximum power point (MPP)when the MPPT system started or illumination intensity motution occurred, and variable step size P&O method could find precise MPP based on the actual status to overcome power loss caused by the deviation between mathematical model and the actual output or small pertubarions. Matlab/Simulink simulation model was established. The results show that this method has a high precision and rapidity tracking capabilities in the case of partial shading as well as illumination intensity motution.