A novel Elite Opposition-based Jaya algorithm for parameter estimation of photovoltaic cell models

被引：76
作者：
Wang, Long [1 ,2 ,3 ]
Huang, Chao [3 ]
机构：
[1] Univ Sci & Technol Beijing, Sch Comp & Commun Engn, Beijing 100083, Peoples R China
[2] Beijing Key Lab Knowledge Engn Mat Sci, Beijing 100083, Peoples R China
[3] City Univ Hong Kong, Dept Syst Engn & Engn Management, 83 Tat Chee Ave, Kowloon, Hong Kong, Peoples R China
来源：
OPTIK | 2018年 / 155卷
基金：
中国国家自然科学基金;
关键词：
Photovoltaic cell; Parameter estimation; Jaya algorithm; Meta-heuristic search; I-V CHARACTERISTICS; SOLAR-CELLS; OPTIMIZATION; IDENTIFICATION;
D O I：
10.1016/j.ijleo.2017.10.081
中图分类号：
O43 [光学];
学科分类号：
070207 ; 0803 ;
摘要：
Parameter estimation of photovoltaic (PV) cell models using a novel Elite Opposition-based Jaya (EO-Jaya) algorithm is studied in this letter. The EO-Jaya is a swarm intelligence algorithm without algorithm specific parameters. Compared with the generic Jaya algorithm, the Elite Opposition Learning strategy is incorporated into the solution updating phase, which increases the solution diversity. The effectiveness of the EO-Jaya algorithm is validated via estimating model parameters of a real PV cell. The computational results prove the superiority of the proposed algorithm compared to newly published estimation methods. (C) 2017 Elsevier GmbH. All rights reserved.
引用
收藏
页码：351 / 356
页数：6
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