多策略混合改进樽海鞘群算法的光伏MPPT控制研究  

Research on photovoltaic MPPT control based on multi⁃strategy hybrid improved SSA

作　　者：罗善峰 陈芳芳[1,2] 徐天奇[1] 李华鑫[1] 程三榜 LUO Shanfeng;CHEN Fangfang;XU Tianqi;LI Huaxin;CHENG Sanbang(School of Electrical and Information Technology,Yunnan Minzu University,Kunming 650504,China;Yunnan Provincial Key Laboratory of Unmanned Autonomous Systems,Yunnan Minzu University,Kunming 650504,China)

机构地区：[1]云南民族大学电气信息工程学院,云南昆明650504 [2]云南民族大学云南省无人自主系统重点实验室,云南昆明650504

出　　处：《现代电子技术》2025年第8期109-114,共6页Modern Electronics Technique

基　　金：国家自然科学基金项目(61761049)。

摘　　要：针对传统光伏最大功率点追踪(MPPT)方法在光伏阵列因环境因素处于局部遮阴时出现陷入局部最优的情况,为实现对太阳能的高效利用,基于樽海鞘群算法对低维度优化问题的优势,提出一种多策略混合改进樽海鞘群算法的MPPT控制。该控制采用改进型Logistic混沌映射对樽海鞘种群进行初始化,提高了樽海鞘种群的多样性。同时,利用麻雀搜索算法发现者行为代替樽海鞘领导者行为,提升了算法的全局探索能力,避免了算法陷入局部最优解。Matlab/Simulink仿真实验表明,所提方法在静态局部遮阴和动态局部遮阴两种情况下都具有较好的收敛性,并且相较于粒子群算法和樽海鞘群算法,其在收敛速度和寻优精度等方面都有明显提升。The traditional photovoltaic maximum power point tracking(MPPT)method falls into the local optimum when the photovoltaic array is in local shading due to environmental factors.In order to realize efficient utilization of solar energy,a multi-strategy hybrid improved MPPT control of the salp swarm algorithm(SSA)is proposed based on the SSA advantages in low-dimensional optimization problems.In this control,the improved Logistic chaotic mapping is used for the initialization of the salp swarm population to enhance its diversity.The explorer behavior of sparrow search algorithm is used to replace the leader behavior of salp,so as to improve the algorithm's global exploration capability,and avoiding falling into local optima.Matlab/Simulink simulation experimental results demonstrate that the proposed method can exhibit good convergence in both static and dynamic partial shading scenarios,and its convergence speed and optimization accuracy is significantly improved compared with particle swarm optimization and traditional SSA.

关 键 词：最大功率点追踪 樽海鞘群算法 光伏阵列 改进Logistic混沌映射 局部遮阴 麻雀搜索算法 

分 类 号：TN86-34[电子电信—信息与通信工程] TM615[电气工程—电力系统及自动化]