Performance comparison of GA and DEA in solving distribution system reconfiguration problem

Saeed Jazebi, S. Hosseinian, M. Pooyan, B. Vahidi
{"title":"Performance comparison of GA and DEA in solving distribution system reconfiguration problem","authors":"Saeed Jazebi, S. Hosseinian, M. Pooyan, B. Vahidi","doi":"10.1109/OPTIM.2008.4602364","DOIUrl":null,"url":null,"abstract":"Distribution network reconfiguration (DNR) is a crucial issue in the operating horizon of distribution systems. In distribution networks tie switches will be changed to obtain an appropriate network configuration with minimum losses. Distribution networks have hundreds of switches and determining the best status of switches is a complicated combinatorial, non-differentiable constrained optimization problem, which can be solved using heuristic optimization algorithms. Many researches have been focused on introducing appropriate search algorithms to this real-time optimization problem. To judge which method is best suited for this particular problem, performance comparison is necessary. In this paper GA and DEA are compared solving reconfiguration problem from convergence rate and computational time point of view.","PeriodicalId":244464,"journal":{"name":"2008 11th International Conference on Optimization of Electrical and Electronic Equipment","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2008-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 11th International Conference on Optimization of Electrical and Electronic Equipment","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/OPTIM.2008.4602364","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8

Abstract

Distribution network reconfiguration (DNR) is a crucial issue in the operating horizon of distribution systems. In distribution networks tie switches will be changed to obtain an appropriate network configuration with minimum losses. Distribution networks have hundreds of switches and determining the best status of switches is a complicated combinatorial, non-differentiable constrained optimization problem, which can be solved using heuristic optimization algorithms. Many researches have been focused on introducing appropriate search algorithms to this real-time optimization problem. To judge which method is best suited for this particular problem, performance comparison is necessary. In this paper GA and DEA are compared solving reconfiguration problem from convergence rate and computational time point of view.
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
遗传算法与DEA在解决配电系统重构问题中的性能比较
配电网重构(DNR)是配电网运行领域的一个关键问题。在配电网中,配电网的连接开关将被改变,以获得损耗最小的适当网络配置。配电网中有数百个交换机,确定交换机的最佳状态是一个复杂的组合、不可微约束优化问题,可采用启发式优化算法求解。许多研究都集中在引入合适的搜索算法来解决这一实时优化问题。为了判断哪种方法最适合这个特定的问题,性能比较是必要的。本文从收敛速度和计算时间的角度比较了遗传算法和DEA算法在求解重构问题中的应用。
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
Stand-alone power system with synchronous and asynchronous generators Analysis of permanent magnet claw-pole synchronous machine Control methods on unstable periodic orbits of a chaotic dynamical system — control chaos in buck converter Modular test bench for a hybrid electric vehicle with multiples energy sources Improvement of voltage stability and reduce power system losses by optimal GA-based allocation of multi-type FACTS devices
×
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