一种基于人工智能求解器和多准则决策的光伏组件I-V特性曲线混合建模方法

IF 1.9 4区 工程技术 Q4 ENERGY & FUELS
Ruqayah Dheyauldeen A. Almunem, Dhiaa Halboot Muhsen, Haider Tarish Haider, Tamer Khatib
{"title":"一种基于人工智能求解器和多准则决策的光伏组件I-V特性曲线混合建模方法","authors":"Ruqayah Dheyauldeen A. Almunem, Dhiaa Halboot Muhsen, Haider Tarish Haider, Tamer Khatib","doi":"10.1177/01445987231211609","DOIUrl":null,"url":null,"abstract":"In this research, hybrid method is proposed to model the I–V characteristic curve of a photovoltaic (PV) module. The method is represented by a multi-objective arithmetic optimization and cuckoo search with multi-criteria decision-making approach. The proposed model generates first a number of I–V curves as candidates. This phase is conducted through multi-objective optimization algorithm. The optimization algorithm is assessed by a non-dominated ranking scheme and crowding distance framework. After that, the best I–V curve candidate is chosen from the result of Pareto front by using the VIKOR multi-criteria decision-making method. Moreover, the analytic hierarchy approach is employed to select the appropriate weight for each criterion. The proposed method is validated by using an experimental data under various operational conditions. This validation is done by extracting different I–V characteristic for PV modules. The proposed method is compared to a number of methods in the literature. Results show that the proposed method exceeds other methods in the literature considering the accuracy of generating the I–V curves. In addition, results show that the proposed method requires less computational power as compared to other hybridized methods.","PeriodicalId":11606,"journal":{"name":"Energy Exploration & Exploitation","volume":null,"pages":null},"PeriodicalIF":1.9000,"publicationDate":"2023-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A novel hybrid method for modeling of photovoltaic module I–V characteristic curve by using artificial intelligence-based solver and multi-criteria decision making\",\"authors\":\"Ruqayah Dheyauldeen A. Almunem, Dhiaa Halboot Muhsen, Haider Tarish Haider, Tamer Khatib\",\"doi\":\"10.1177/01445987231211609\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this research, hybrid method is proposed to model the I–V characteristic curve of a photovoltaic (PV) module. The method is represented by a multi-objective arithmetic optimization and cuckoo search with multi-criteria decision-making approach. The proposed model generates first a number of I–V curves as candidates. This phase is conducted through multi-objective optimization algorithm. The optimization algorithm is assessed by a non-dominated ranking scheme and crowding distance framework. After that, the best I–V curve candidate is chosen from the result of Pareto front by using the VIKOR multi-criteria decision-making method. Moreover, the analytic hierarchy approach is employed to select the appropriate weight for each criterion. The proposed method is validated by using an experimental data under various operational conditions. This validation is done by extracting different I–V characteristic for PV modules. The proposed method is compared to a number of methods in the literature. Results show that the proposed method exceeds other methods in the literature considering the accuracy of generating the I–V curves. In addition, results show that the proposed method requires less computational power as compared to other hybridized methods.\",\"PeriodicalId\":11606,\"journal\":{\"name\":\"Energy Exploration & Exploitation\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2023-11-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Energy Exploration & Exploitation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1177/01445987231211609\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENERGY & FUELS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Energy Exploration & Exploitation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/01445987231211609","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 0

摘要

本文提出了光伏组件I-V特性曲线的混合建模方法。该方法采用多目标算法优化和多准则决策的布谷鸟搜索方法。该模型首先生成若干I-V曲线作为候选曲线。这一阶段通过多目标优化算法进行。采用非支配排序方案和拥挤距离框架对优化算法进行评价。然后,利用VIKOR多准则决策方法从Pareto前沿结果中选择最佳的I-V曲线候选者。并采用层次分析法为各指标选择合适的权重。通过不同工况下的实验数据验证了该方法的有效性。该验证是通过提取PV组件的不同I-V特征来完成的。所提出的方法与文献中的许多方法进行了比较。结果表明,考虑到生成I-V曲线的精度,该方法优于文献中其他方法。此外,研究结果表明,与其他杂交方法相比,该方法所需的计算能力更小。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A novel hybrid method for modeling of photovoltaic module I–V characteristic curve by using artificial intelligence-based solver and multi-criteria decision making
In this research, hybrid method is proposed to model the I–V characteristic curve of a photovoltaic (PV) module. The method is represented by a multi-objective arithmetic optimization and cuckoo search with multi-criteria decision-making approach. The proposed model generates first a number of I–V curves as candidates. This phase is conducted through multi-objective optimization algorithm. The optimization algorithm is assessed by a non-dominated ranking scheme and crowding distance framework. After that, the best I–V curve candidate is chosen from the result of Pareto front by using the VIKOR multi-criteria decision-making method. Moreover, the analytic hierarchy approach is employed to select the appropriate weight for each criterion. The proposed method is validated by using an experimental data under various operational conditions. This validation is done by extracting different I–V characteristic for PV modules. The proposed method is compared to a number of methods in the literature. Results show that the proposed method exceeds other methods in the literature considering the accuracy of generating the I–V curves. In addition, results show that the proposed method requires less computational power as compared to other hybridized 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
Energy Exploration & Exploitation
Energy Exploration & Exploitation 工程技术-能源与燃料
CiteScore
5.40
自引率
3.70%
发文量
78
审稿时长
3.9 months
期刊介绍: Energy Exploration & Exploitation is a peer-reviewed, open access journal that provides up-to-date, informative reviews and original articles on important issues in the exploration, exploitation, use and economics of the world’s energy resources.
×
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