基于相量测量单元的分散电力系统状态估计

Neelabh Kashyap, S. Werner, Yih-Fang Huang, R. Arablouei
{"title":"基于相量测量单元的分散电力系统状态估计","authors":"Neelabh Kashyap, S. Werner, Yih-Fang Huang, R. Arablouei","doi":"10.1109/SAM.2016.7569719","DOIUrl":null,"url":null,"abstract":"This paper presents a privacy preserving approach to decentralized state estimation in multi-area power systems. By formulating state estimation as a model-distributed regularized least-squares (MDRLS) problem, we ensure that the state variables and system matrix of each area are hidden from all other areas in order to protect privacy and sensitive information. We present a scheme that solves the primal MDRLS problem using the alternating direction method of multipliers, and a second method that solves the dual problem using a distributed form of the coordinate descent algorithm. Only information related to current measurements on tie-lines linking neighboring areas is exchanged between those areas. The proposed schemes enable the local state estimator in each area to estimate the voltage magnitude and phase angle of each bus in its own control area from phasor measurement units (PMU) without the need for full local PMU-observability. The novelty of the proposed methods is in that they employ the inherently hierarchical architecture of the wide-area monitoring system to perform decentralized state estimation. Our simulation results show that the estimation error of both methods converges to that of the centralized approach.","PeriodicalId":159236,"journal":{"name":"2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Privacy preserving decentralized power system state estimation with phasor measurement units\",\"authors\":\"Neelabh Kashyap, S. Werner, Yih-Fang Huang, R. Arablouei\",\"doi\":\"10.1109/SAM.2016.7569719\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a privacy preserving approach to decentralized state estimation in multi-area power systems. By formulating state estimation as a model-distributed regularized least-squares (MDRLS) problem, we ensure that the state variables and system matrix of each area are hidden from all other areas in order to protect privacy and sensitive information. We present a scheme that solves the primal MDRLS problem using the alternating direction method of multipliers, and a second method that solves the dual problem using a distributed form of the coordinate descent algorithm. Only information related to current measurements on tie-lines linking neighboring areas is exchanged between those areas. The proposed schemes enable the local state estimator in each area to estimate the voltage magnitude and phase angle of each bus in its own control area from phasor measurement units (PMU) without the need for full local PMU-observability. The novelty of the proposed methods is in that they employ the inherently hierarchical architecture of the wide-area monitoring system to perform decentralized state estimation. Our simulation results show that the estimation error of both methods converges to that of the centralized approach.\",\"PeriodicalId\":159236,\"journal\":{\"name\":\"2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)\",\"volume\":\"36 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-09-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SAM.2016.7569719\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SAM.2016.7569719","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

摘要

提出了一种保护隐私的多区域电力系统分散状态估计方法。通过将状态估计表述为一个模型分布正则化最小二乘(MDRLS)问题,我们确保每个区域的状态变量和系统矩阵对所有其他区域都是隐藏的,以保护隐私和敏感信息。我们提出了一种使用乘法器交替方向法解决原始MDRLS问题的方案,以及使用坐标下降算法的分布式形式解决对偶问题的第二种方法。这些地区之间只交换与连接邻近地区的联络线当前测量值有关的信息。提出的方案使每个区域的局部状态估计器能够从相量测量单元(PMU)估计其控制区域内每个母线的电压幅度和相角,而无需完全的局部PMU可观测性。所提方法的新颖之处在于它们利用广域监测系统固有的层次结构来执行分散的状态估计。仿真结果表明,两种方法的估计误差都收敛于集中式方法的估计误差。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Privacy preserving decentralized power system state estimation with phasor measurement units
This paper presents a privacy preserving approach to decentralized state estimation in multi-area power systems. By formulating state estimation as a model-distributed regularized least-squares (MDRLS) problem, we ensure that the state variables and system matrix of each area are hidden from all other areas in order to protect privacy and sensitive information. We present a scheme that solves the primal MDRLS problem using the alternating direction method of multipliers, and a second method that solves the dual problem using a distributed form of the coordinate descent algorithm. Only information related to current measurements on tie-lines linking neighboring areas is exchanged between those areas. The proposed schemes enable the local state estimator in each area to estimate the voltage magnitude and phase angle of each bus in its own control area from phasor measurement units (PMU) without the need for full local PMU-observability. The novelty of the proposed methods is in that they employ the inherently hierarchical architecture of the wide-area monitoring system to perform decentralized state estimation. Our simulation results show that the estimation error of both methods converges to that of the centralized approach.
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
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信