Identification of coherent synchronous generators in a Multi-Machine Power System using Support Vector Clustering

Rimjhim Agrawal, D. Thukaram
{"title":"Identification of coherent synchronous generators in a Multi-Machine Power System using Support Vector Clustering","authors":"Rimjhim Agrawal, D. Thukaram","doi":"10.1109/ICPES.2011.6156659","DOIUrl":null,"url":null,"abstract":"This paper illustrates the application of a new technique, based on Support Vector Clustering (SVC) for the direct identification of coherent synchronous generators in a large interconnected Multi-Machine Power Systems. The clustering is based on coherency measures, obtained from the time domain responses of the generators following system disturbances. The proposed clustering algorithm could be integrated into a wide-area measurement system that enables fast identification of coherent clusters of generators for the construction of dynamic equivalent models. An application of the proposed method is demonstrated on a practical 15 generators 72-bus system, an equivalent of Indian Southern grid in an attempt to show the effectiveness of this clustering approach. The effects of short circuit fault locations on coherency are also investigated.","PeriodicalId":158903,"journal":{"name":"2011 International Conference on Power and Energy Systems","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 International Conference on Power and Energy Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPES.2011.6156659","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 16

Abstract

This paper illustrates the application of a new technique, based on Support Vector Clustering (SVC) for the direct identification of coherent synchronous generators in a large interconnected Multi-Machine Power Systems. The clustering is based on coherency measures, obtained from the time domain responses of the generators following system disturbances. The proposed clustering algorithm could be integrated into a wide-area measurement system that enables fast identification of coherent clusters of generators for the construction of dynamic equivalent models. An application of the proposed method is demonstrated on a practical 15 generators 72-bus system, an equivalent of Indian Southern grid in an attempt to show the effectiveness of this clustering approach. The effects of short circuit fault locations on coherency are also investigated.
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
基于支持向量聚类的多机电力系统相干同步发电机辨识
本文介绍了一种基于支持向量聚类(SVC)的新技术在大型互联多机电力系统中相干同步发电机直接识别中的应用。聚类是基于从系统扰动后发生器的时域响应中获得的相干度量。所提出的聚类算法可以集成到广域测量系统中,能够快速识别发电机的相干簇,从而构建动态等效模型。将该方法应用于一个实际的15台发电机72总线系统中,该系统相当于印度南部电网,试图证明该方法的有效性。研究了短路故障位置对相干性的影响。
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
On the optimal tuning of FACTS based stabilizers for dynamic stability enhancement in multimachine power systems A new proposal for voltage regulation multi feeders/Multibus systems using MC-DVR Deployment of System Protection Schemes for enhancing reliability of power system: Operational experience of wide area SPS in Northern Regional Power System in India Power quality improvement in DTC based induction motor drive using Minnesota rectifier Neural learning algorithm based power quality enhancement for three phase three wire distribution system utilizing shunt active power filter strategy
×
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