基于改进松鼠搜索算法的光伏阴影全局MPPT控制  

Global MPPT Control of PV Shadows Based on Improved Squirrel Search Algorithm

作　　者：刘倩 卢尚军 罗子军 金彦兴 刘胜胜 LIU Qian;LU Shangjun;LUO Zijun;JIN Yanxing;LIU Shengsheng(Three Gorges New Energy Jinchang Wind Power Co.,Ltd.,Jinchang 737100,China)

机构地区：[1]三峡新能源金昌风电有限公司,甘肃金昌737100

出　　处：《电工技术》2025年第2期78-81,共4页Electric Engineering

摘　　要：针对局部阴影光伏发电存在功率多峰值问题,提出一种改进的松鼠搜索算法,为提高该算法的全局搜索能力,引入Tent映射和动态折射反向学习策略跳出局部搜索,进入全局搜索范围。通过仿真平台搭建30×50的光伏阵列,进行最大功率点追踪仿真,并且与传统仿生学算法——粒子群优化算法(PSO)进行对比。结果表明,改进SSA算法在保证响应时间短的情况下,调制过程中的波动小,GMPP追踪效果好,有效减少了光伏阵列发电过程中的能量损耗。Aiming at the problem of power multi-peaking in locally shaded photovoltaic power generation,this paper proposes an improved squirrel search algorithm.In order to improve the global search ability of this algorithm,Tent mapping and dynamic refraction reverse learning strategy are introduced to jump out of the local search and enter the global search scope.A 30×50 PV array is built by the simulation platform,and the maximum power point tracking simulation is carried out.And it is compared with the traditional bionic algorithm:particle swarm optimization algorithm(PSO).The results show that the improved SSA algorithm has small fluctuations in the modulation process while ensuring short response time,good GMPP tracking effect,and effectively reduces the energy loss in the power generation process of PV array.

关 键 词：光伏系统 局部阴影 MPPT 改进SSA算法 

分 类 号：TM912[电气工程—电力电子与电力传动]