Multi-objective differential evolution for optimal power flow

M. A. Abido, N. A. Al-Ali
{"title":"Multi-objective differential evolution for optimal power flow","authors":"M. A. Abido, N. A. Al-Ali","doi":"10.1109/POWERENG.2009.4915212","DOIUrl":null,"url":null,"abstract":"This paper presents a multiobjective differential evolution (MODE) based approach to solve the optimal power flow (OPF) problem. OPF problem has been treated as a true multiobjective constrained optimization problem. Different objective functions and different operational constraints have been considered in the problem formulation. A clustering algorithm is applied to manage the size of the Pareto set. Also, an algorithm based on fuzzy set theory is used to extract the best compromise solution. Simulation results on IEEE-30 bus test system show the effectiveness of the proposed approach in solving true multi-objective OPF and also finding well distributed Pareto solutions.","PeriodicalId":246039,"journal":{"name":"2009 International Conference on Power Engineering, Energy and Electrical Drives","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"56","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Conference on Power Engineering, Energy and Electrical Drives","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/POWERENG.2009.4915212","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 56

Abstract

This paper presents a multiobjective differential evolution (MODE) based approach to solve the optimal power flow (OPF) problem. OPF problem has been treated as a true multiobjective constrained optimization problem. Different objective functions and different operational constraints have been considered in the problem formulation. A clustering algorithm is applied to manage the size of the Pareto set. Also, an algorithm based on fuzzy set theory is used to extract the best compromise solution. Simulation results on IEEE-30 bus test system show the effectiveness of the proposed approach in solving true multi-objective OPF and also finding well distributed Pareto solutions.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
最优潮流的多目标差分进化
提出了一种基于多目标差分进化(MODE)的最优潮流求解方法。将OPF问题视为一个真正的多目标约束优化问题。在问题的表述中考虑了不同的目标函数和不同的操作约束。采用聚类算法来管理Pareto集合的大小。同时,采用基于模糊集理论的算法提取最佳妥协解。在IEEE-30总线测试系统上的仿真结果表明,该方法在求解真多目标OPF和找到分布良好的Pareto解方面是有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
An advanced three phase five level PWM rectifier Game based strategic bidding in pay as bid markets considering incomplete information and risk factor Novel flux weakening control algorithm for PMSMS Dynamics analysis of 220 V DC auxiliary system in power plant using different mathematical models Efficient system parameter selection to prevent oscillatory voltage instability
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1