Adaptive differential evolution with linear population reduction for parameter estimation of solar cell models

被引:0
|
作者
Yan, Zhen [1 ]
Gong, Wenyin [1 ]
Li, Shuijia [1 ]
机构
[1] China Univ Geosci, Sch Comp Sci, Wuhan 430074, Peoples R China
基金
中国国家自然科学基金;
关键词
parameter estimation; solar cell models; differential evolution; adaptation; PHOTOVOLTAIC MODELS; SEARCH ALGORITHM; OPTIMIZATION; IDENTIFICATION; EXTRACTION;
D O I
10.1504/IJAAC.2022.10050112
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Parameter estimation of solar cell models is an important part of photovoltaic power generation system. However, it is still a challenging problem. In this study, an adaptive differential evolution with linear population reduction, called LRJADE, is developed to accurately estimate solar cell models parameters. In LRJADE, the linear population reduction strategy is employed to accelerate convergence speed. Additionally, the crossover rate repairing is also used. The performance of proposed LRJADE is verified by 13 benchmark functions and two solar cell model parameter estimation problems. Simulated results show that LRJADE not only obtains promising results in benchmark functions, but also achieves the very accurate solutions to solar cell model parameter estimation problems.
引用
收藏
页码:716 / 739
页数:25
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