用萤火虫算法辨识太阳能电池参数

M. Louzazni, A. Craciunescu, E. Aroudam, A. Dumitrache
{"title":"用萤火虫算法辨识太阳能电池参数","authors":"M. Louzazni, A. Craciunescu, E. Aroudam, A. Dumitrache","doi":"10.1109/MCSI.2015.37","DOIUrl":null,"url":null,"abstract":"Due to the non-linearity, multivariable and multimodal features of current-voltage of solar cell models, the conventional methods are incapable to estimating the parameters of solar cell with high accuracy. Recently, the bio-inspired algorithms have attracted the attention. The firefly algorithm is nature-inspired stochastic optimization algorithm is among the most powerful algorithms in solving modern global optimization for nonlinear and complex system, based on the flashing patterns and behavior of fireflies swarm. In this paper, a firefly algorithm is proposed to extract the parameters of single diode model solar cell from experimental I-V characteristics. The results obtained by firefly algorithm are quite promising and outperform those found by the other methods.","PeriodicalId":371635,"journal":{"name":"2015 Second International Conference on Mathematics and Computers in Sciences and in Industry (MCSI)","volume":"9 5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Identification of Solar Cell Parameters with Firefly Algorithm\",\"authors\":\"M. Louzazni, A. Craciunescu, E. Aroudam, A. Dumitrache\",\"doi\":\"10.1109/MCSI.2015.37\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Due to the non-linearity, multivariable and multimodal features of current-voltage of solar cell models, the conventional methods are incapable to estimating the parameters of solar cell with high accuracy. Recently, the bio-inspired algorithms have attracted the attention. The firefly algorithm is nature-inspired stochastic optimization algorithm is among the most powerful algorithms in solving modern global optimization for nonlinear and complex system, based on the flashing patterns and behavior of fireflies swarm. In this paper, a firefly algorithm is proposed to extract the parameters of single diode model solar cell from experimental I-V characteristics. The results obtained by firefly algorithm are quite promising and outperform those found by the other methods.\",\"PeriodicalId\":371635,\"journal\":{\"name\":\"2015 Second International Conference on Mathematics and Computers in Sciences and in Industry (MCSI)\",\"volume\":\"9 5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-08-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 Second International Conference on Mathematics and Computers in Sciences and in Industry (MCSI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MCSI.2015.37\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 Second International Conference on Mathematics and Computers in Sciences and in Industry (MCSI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MCSI.2015.37","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12

摘要

由于太阳电池模型的非线性、多变量和多模态特性,传统方法无法对太阳电池参数进行高精度估计。最近,仿生算法引起了人们的关注。萤火虫算法是一种自然启发的随机优化算法,它基于萤火虫群的闪烁模式和行为,是解决现代非线性复杂系统全局优化问题最强大的算法之一。本文提出了一种从实验I-V特性中提取单二极管模型太阳能电池参数的萤火虫算法。萤火虫算法得到的结果很有希望,优于其他方法的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identification of Solar Cell Parameters with Firefly Algorithm
Due to the non-linearity, multivariable and multimodal features of current-voltage of solar cell models, the conventional methods are incapable to estimating the parameters of solar cell with high accuracy. Recently, the bio-inspired algorithms have attracted the attention. The firefly algorithm is nature-inspired stochastic optimization algorithm is among the most powerful algorithms in solving modern global optimization for nonlinear and complex system, based on the flashing patterns and behavior of fireflies swarm. In this paper, a firefly algorithm is proposed to extract the parameters of single diode model solar cell from experimental I-V characteristics. The results obtained by firefly algorithm are quite promising and outperform those found by the other methods.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信