Multi-peak MPPT control of PV array based on improved ALO algorithm

被引：0
|
作者：
Zhao B. [1 ,2 ]
Yuan Q. [1 ]
Wang L. [1 ]
Tan H. [1 ]
Zeng X. [1 ]
机构：
[1] College of Electrical and Information Engineering, Changsha University of Science & Technology, Changsha
[2] Energy Research and Demonstration Center of Tibet, Lhasa
来源：
Taiyangneng Xuebao/Acta Energiae Solaris Sinica | 2021年 / 42卷 / 09期
关键词：
Ant lion optimization; Maximum power point tracking; Optimization algorithm; Partial shadow; Photovoltaic power generation;
D O I：
10.19912/j.0254-0096.tynxb.2020-0517
中图分类号：
学科分类号：
摘要：
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 multi-peak 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. © 2021, Solar Energy Periodical Office Co., Ltd. All right reserved.
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页码：132 / 139
页数：7
相关论文
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