基于IGWO-IP&O混合算法的光伏MPPT控制  

Photovoltaic MPPT Control Based on IGWO-IP&O Hybrid Algorithm

作　　者：郭思桐 粟时平[1] 刘桂英[1] 王辰浩 陈亮 GUO Sitong;SU Shiping;LIU Guiying;WANG Chenhao;CHEN Liang(School of Electrical and Information Engineering,Changsha University of Science&Technology,Changsha 410114,China)

机构地区：[1]长沙理工大学电气与信息工程学院,湖南长沙410114

出　　处：《电力科学与工程》2025年第4期35-42,共8页Electric Power Science and Engineering

基　　金：湖南省自然科学基金资助项目(2023JJ40053)。

摘　　要：针对在局部阴影环境下光伏阵列输出功率呈现多峰特性时,采用传统灰狼优化算法实现最大功率点跟踪存在追踪精度低且易陷于局部最优的问题,提出了一种将多策略改进灰狼优化和变步长扰动观察相结合的方法。在全局搜索中,调整非线性收敛因子策略以提升算法的收敛速度和搜索精度;引入混沌Tent映射和反向学习策略生成以提高算法搜索效率;引入自适应t分布变异和一种基于权值的位置更新策略,以平衡算法收敛性能与跳出局部最优能力;在局部搜索中采用变步长扰动观察法对最大功率点进行快速精确跟踪。仿真结果表明,相较其他优化算法,在不同工况下,用所提出的优化算法能够更快速、精确地追踪到最大功率点,有效避免陷入局部最优解。Aiming at the problem of low tracking accuracy and susceptibility to be trapped in the local optium when the output power of photovoltaic arrays exhibits multi-peak characteristics in local shadow environments by using traditional grey wolf optimization(GWO)algorithm optima in achieving to acheive maximum power point tracking(MPPT),a method combining multi-strategy improved grey wolf optimization(IGWO)and improved perturbation and observation method(IP&O)is proposed.In the global search,the nonlinear convergence factor strategy is adjusted to improve the convergence speed and search accuracy of algorithm;chaotic Tent mapping and reverse learning strategy generation are introduced to improve the search efficiency of algorithm;the adaptive t-distribution variation and a weighted position update strategy are introduced to balance the convergence performance and the ability to jump out of the local optimum.In local search,the IP&O is used to track the maximum power point quickly and accurately.The simulation results show that the proposed optimization algorithm can track the maximum power point more quickly and accurately than other optimization algorithms under different working conditions,and effectively avoid falling into the local optimum solution.

关 键 词：光伏发电 灰狼算法 最大功率点跟踪 局部阴影 扰动观察法 

分 类 号：TM615[电气工程—电力系统及自动化]