摘要
针对局部阴影下光伏阵列的多峰特性以及传统蚁狮算法的缺陷,提出一种基于改进蚁狮优化的MPPT控制算法。通过针对性的初始化蚁狮位置、将蚂蚁的位置更新公式引入自适应变权重系数调整策略、优化蚁狮陷阱范围大小的改进措施,运用仿真并通过统计分析将提出的算法与传统蚁狮、粒子群、鸡群、蛙跳、花粉授粉和扰动观察法、电导增量法等多种算法进行静态和动态MPPT控制性能对比。仿真和实验结果表明,该算法在静态和动态环境下均具备很好的跟踪精度与跟踪速度,可有效提高局部阴影下光伏阵列发电效率。
Aiming at the multi-peak characteristics of PV array under partial shadow conditions and the defects of traditional ant lion optimization algorithm,this paper presents a control algorithm for MPPT in PV system base on improving ant lion optimization algorithm.The improvements include targeted initialization of the ant lion position,introduced an weight coefficient adaptive adjustment strategy into the position update formula of ants,and trap range optimization of ant lion.Through simulation and statistical analysis,the multipeak MPPT comparison is carried out between the proposed algorithm is compared with ALO,PSO,CSO,SFLA,FPA,P&O and InC.The simulation and experimental results demonstrate that in both static and dynamic environments the IALO provides much better tracking accuracy and rapidity and it can effectively improve the efficiency of PV power generation under partial shadow.
作者
赵斌
袁清
王力
谭恒
曾祥君
Zhao Bin;Yuan Qing;Wang Li;Tan Hen;Zeng Xiangjun(College of Electrical and Information Engineering,Changsha University of Science&Technology,Changsha 410114,China;Energy Research and Demonstration Center of Tibet,Lhasa 850000,China)
出处
《太阳能学报》
EI
CAS
CSCD
北大核心
2021年第9期132-139,共8页
Acta Energiae Solaris Sinica
基金
西藏重大科技专项(XZ201901-GA-09)
西藏自治区自然科学基金重点项目(XZ2019ZRG-194)
湖南省教育厅项目(18C0222)。
关键词
光伏发电
最大功率点跟踪
优化算法
局部阴影
蚁狮算法
photovoltaic power generation
maximum power point tracking
optimization algorithm
partial shadow
ant lion optimization
