A modified artificial neural network based Distribution System reconfiguration for loss minimization

K. S. Kumar, K. Rajalakshmi, S. Karthikeyan
{"title":"A modified artificial neural network based Distribution System reconfiguration for loss minimization","authors":"K. S. Kumar, K. Rajalakshmi, S. Karthikeyan","doi":"10.1109/ICAEE.2014.6838513","DOIUrl":null,"url":null,"abstract":"In this paper a new method for identifying best switching option in reconfiguration of Radial Distribution Systems (RDS) is presented. Feeder reconfiguration is defined as the technique to alter the structures in the distribution feeder by opening and closing the sectionalizing and tie switches. The reconfiguration includes selecting of set of sectional switches to be opened and tie switch to be closed such that the RDS has desired performance. Among several criteria considered in optimal system configuration, loss reduction criterion is very widely used. In this project a novel method is presented which utilizes feeder reconfiguration as a planning and real time control tool in order to restructure the primary feeders for the loss minimization. The mathematical formulation of the proposed method is given; the solution procedure is illustrated with an example. Here neural network approach for Optimal Reconfiguration of RDS is proposed.","PeriodicalId":151739,"journal":{"name":"2014 International Conference on Advances in Electrical Engineering (ICAEE)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 International Conference on Advances in Electrical Engineering (ICAEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAEE.2014.6838513","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6

Abstract

In this paper a new method for identifying best switching option in reconfiguration of Radial Distribution Systems (RDS) is presented. Feeder reconfiguration is defined as the technique to alter the structures in the distribution feeder by opening and closing the sectionalizing and tie switches. The reconfiguration includes selecting of set of sectional switches to be opened and tie switch to be closed such that the RDS has desired performance. Among several criteria considered in optimal system configuration, loss reduction criterion is very widely used. In this project a novel method is presented which utilizes feeder reconfiguration as a planning and real time control tool in order to restructure the primary feeders for the loss minimization. The mathematical formulation of the proposed method is given; the solution procedure is illustrated with an example. Here neural network approach for Optimal Reconfiguration of RDS is proposed.
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
一种基于改进人工神经网络的配电系统重构方法
提出了一种确定径向配电系统重构中最佳开关选择的新方法。馈线重新配置是指通过打开和关闭分段和连接开关来改变配电馈线结构的技术。重新配置包括选择要打开的一组分段开关和要关闭的一组tie开关,以使RDS具有所需的性能。在系统优化配置的几种准则中,损耗减少准则的应用非常广泛。本课题提出了一种利用馈线重构作为规划和实时控制工具的新方法,以重构主馈线以实现损耗最小化。给出了该方法的数学表达式;通过实例说明了求解过程。本文提出了RDS最优重构的神经网络方法。
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
Analysis of Linear Switched Reluctance Motor having gashed pole Economic load dispatch of thermal power plants using evolution technique including transmission losses Analysis and design of Peak Current controlled IBFC for high power factor and tight voltage regulation Automatic traffic control system for single lane tunnels Assessment of satellite image segmentation in RGB and HSV color space using image quality measures
×
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