利用子空间识别进行电力系统监控

A. Mohammadi, H. Khaloozadeh, R. Amjadifard
{"title":"利用子空间识别进行电力系统监控","authors":"A. Mohammadi, H. Khaloozadeh, R. Amjadifard","doi":"10.1109/ICCIAUTOM.2011.6356624","DOIUrl":null,"url":null,"abstract":"In this paper, we proposed a novel index for monitoring and prediction of oscillatory instability (Hopf Bifurcation) in power systems. Considering modern control techniques, the index uses damping information of the whole power system. Therefore, we call it as DMI (Damping Matrix Index). It easily uses power system available signals such as electro-mechanical torques, speeds and angles of synchronous machines to predict oscillatory instability. Since the values of each monitoring index hides behind its estimation method and the proposed index is based on state space model of power system, we use Subspace System Identification (SSI) algorithms to estimate the proposed index. Based on SSI techniques and the proposed index, we suggest an algorithm for power system monitoring. Tests and simulations have been conducted using the proposed index on simulated measurements of a two-area 4-machine power system. Results express good performance of DMI in comparison with other well-known oscillatory instability indices.","PeriodicalId":438427,"journal":{"name":"The 2nd International Conference on Control, Instrumentation and Automation","volume":"68 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Power system monitoring using subspace identification\",\"authors\":\"A. Mohammadi, H. Khaloozadeh, R. Amjadifard\",\"doi\":\"10.1109/ICCIAUTOM.2011.6356624\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we proposed a novel index for monitoring and prediction of oscillatory instability (Hopf Bifurcation) in power systems. Considering modern control techniques, the index uses damping information of the whole power system. Therefore, we call it as DMI (Damping Matrix Index). It easily uses power system available signals such as electro-mechanical torques, speeds and angles of synchronous machines to predict oscillatory instability. Since the values of each monitoring index hides behind its estimation method and the proposed index is based on state space model of power system, we use Subspace System Identification (SSI) algorithms to estimate the proposed index. Based on SSI techniques and the proposed index, we suggest an algorithm for power system monitoring. Tests and simulations have been conducted using the proposed index on simulated measurements of a two-area 4-machine power system. Results express good performance of DMI in comparison with other well-known oscillatory instability indices.\",\"PeriodicalId\":438427,\"journal\":{\"name\":\"The 2nd International Conference on Control, Instrumentation and Automation\",\"volume\":\"68 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The 2nd International Conference on Control, Instrumentation and Automation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCIAUTOM.2011.6356624\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The 2nd International Conference on Control, Instrumentation and Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCIAUTOM.2011.6356624","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

本文提出了一种监测和预测电力系统振荡不稳定性的新指标(Hopf分岔)。考虑到现代控制技术,该指标利用了整个电力系统的阻尼信息。因此,我们称其为DMI (Damping Matrix Index)。它很容易使用电力系统可用的信号,如机电扭矩,同步电机的速度和角度来预测振荡不稳定性。由于每个监测指标的值隐藏在其估计方法之后,并且所提出的指标是基于电力系统的状态空间模型,因此我们使用子空间系统识别(SSI)算法来估计所提出的指标。基于SSI技术和提出的指标,提出了一种电力系统监测算法。利用所提出的指标对两区四机电力系统的模拟测量进行了测试和仿真。结果表明,与其他已知的振荡不稳定性指标相比,DMI具有良好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
Power system monitoring using subspace identification
In this paper, we proposed a novel index for monitoring and prediction of oscillatory instability (Hopf Bifurcation) in power systems. Considering modern control techniques, the index uses damping information of the whole power system. Therefore, we call it as DMI (Damping Matrix Index). It easily uses power system available signals such as electro-mechanical torques, speeds and angles of synchronous machines to predict oscillatory instability. Since the values of each monitoring index hides behind its estimation method and the proposed index is based on state space model of power system, we use Subspace System Identification (SSI) algorithms to estimate the proposed index. Based on SSI techniques and the proposed index, we suggest an algorithm for power system monitoring. Tests and simulations have been conducted using the proposed index on simulated measurements of a two-area 4-machine power system. Results express good performance of DMI in comparison with other well-known oscillatory instability indices.
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
自引率
0.00%
发文量
0
期刊最新文献
Optimal design of adaptive interval type-2 fuzzy sliding mode control using Genetic algorithm Constrained model predictive control of PEM fuel cell with guaranteed stability Optimal control of an autonomous underwater vehicle using IPSO_SQP algorithm Design of an on-line recurrent wavelet network controller for a class of nonlinear systems Exact pupil and iris boundary detection
×
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