基于LGPSO_P&O混合算法的光伏多峰MPPT研究

RESEARCH ON PHOTOVOLTAIC MULTI-PEAK MPPT BASED ON LGPSO_P&O HYBRID ALGORITHM

针对复杂遮阴环境下光伏阵列P-U曲线呈现多个峰值而导致传统最大功率点跟踪(MPPT)算法易陷入局部最优解的问题,提出一种新的控制算法模型——LGPSO_P&O模型。该模型结合Levy飞行、高斯变异策略和粒子群算法,并对粒子群算法惯性权重进行改进,构建LGPSO算法搜索全局最大功率点(MPP)。同时,改进扰动观察法(P&O)对MPP进行局部跟踪,进一步提高跟踪精度。在Matlab/Simulink中进行仿真实验,并与改进PSO、BPSHO和GA_ACO算法作对比,仿真结果表明该模型具有较高的鲁棒性,收敛速度快,跟踪精度高,最高可达99.8%。

Aiming at the problem that the P-U curve of photovoltaic array presents multiple peaks in complex shading environment,which causes the traditional maximum power point tracking(MPPT)algorithm to fall into the local optimal solution,a new control algorithm model,LGPSO_P&O model,is proposed.The model combines Levy flight,Gaussian variation strategy and particle swarm algorithm,and improves the inertial weights of particle swarm algorithm to construct the LGPSO algorithm to search for global maximum power points(MPP).At the same time,the disturbance observation method(P&O)is improved to track MPP locally to further improve the tracking accuracy.Simulation experiments are carried out in MATLAB/Simulink,and compared with improved PSO,BPSHO and GA_ACO algorithms,the simulation results show that the model has high robustness,fast convergence speed,high tracking accuracy,up to 99.8%.