基于PMU-ANN的电力系统机电振荡实时监测

Abhilasha Gupta, K. Verma
{"title":"基于PMU-ANN的电力系统机电振荡实时监测","authors":"Abhilasha Gupta, K. Verma","doi":"10.1109/ICPEICES.2016.7853073","DOIUrl":null,"url":null,"abstract":"Power system oscillations monitoring is a vital issue in operation of modern interconnected power systems. The existing methods for identifying the electromechanical modes are time-consuming and require modelling of the entire system that includes a large number of states and are performed offline. In this paper, an integrated Phasor Measurement Unit and Artificial Neural Network (PMU-ANN) based approach for online and real time monitoring of power system electromechanical oscillations is proposed. The placement of PMU is obtained using Integer Linear Programming (ILP). The data obtained from PMU is given as input to a multilayer Feedforward Neural Network (FFNN) and its output gives all the information related to the modes of the system and the mode ranking. The effectiveness of the proposed approach is investigated on IEEE 39-bus test system. The results show that the proposed approach is fast with less computational burden and is suitable for online and real time oscillations monitoring of the power systems under varying operating conditions.","PeriodicalId":305942,"journal":{"name":"2016 IEEE 1st International Conference on Power Electronics, Intelligent Control and Energy Systems (ICPEICES)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2016-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"PMU-ANN based real time monitoring of power system electromechanical oscillations\",\"authors\":\"Abhilasha Gupta, K. Verma\",\"doi\":\"10.1109/ICPEICES.2016.7853073\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Power system oscillations monitoring is a vital issue in operation of modern interconnected power systems. The existing methods for identifying the electromechanical modes are time-consuming and require modelling of the entire system that includes a large number of states and are performed offline. In this paper, an integrated Phasor Measurement Unit and Artificial Neural Network (PMU-ANN) based approach for online and real time monitoring of power system electromechanical oscillations is proposed. The placement of PMU is obtained using Integer Linear Programming (ILP). The data obtained from PMU is given as input to a multilayer Feedforward Neural Network (FFNN) and its output gives all the information related to the modes of the system and the mode ranking. The effectiveness of the proposed approach is investigated on IEEE 39-bus test system. The results show that the proposed approach is fast with less computational burden and is suitable for online and real time oscillations monitoring of the power systems under varying operating conditions.\",\"PeriodicalId\":305942,\"journal\":{\"name\":\"2016 IEEE 1st International Conference on Power Electronics, Intelligent Control and Energy Systems (ICPEICES)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-07-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE 1st International Conference on Power Electronics, Intelligent Control and Energy Systems (ICPEICES)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICPEICES.2016.7853073\",\"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 1st International Conference on Power Electronics, Intelligent Control and Energy Systems (ICPEICES)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPEICES.2016.7853073","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 13

摘要

电力系统振荡监测是现代互联电力系统运行中的一个重要问题。现有的机电模式识别方法耗时长,并且需要对包含大量状态的整个系统进行建模,并且需要离线执行。本文提出了一种基于相量测量单元和人工神经网络(PMU-ANN)的电力系统机电振荡在线实时监测方法。采用整数线性规划(ILP)方法求解PMU的位置。PMU获得的数据作为多层前馈神经网络(FFNN)的输入,其输出给出了与系统模式和模式排序相关的所有信息。在IEEE 39总线测试系统上验证了该方法的有效性。结果表明,该方法速度快,计算量小,适用于各种运行工况下电力系统的在线和实时振荡监测。
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
PMU-ANN based real time monitoring of power system electromechanical oscillations
Power system oscillations monitoring is a vital issue in operation of modern interconnected power systems. The existing methods for identifying the electromechanical modes are time-consuming and require modelling of the entire system that includes a large number of states and are performed offline. In this paper, an integrated Phasor Measurement Unit and Artificial Neural Network (PMU-ANN) based approach for online and real time monitoring of power system electromechanical oscillations is proposed. The placement of PMU is obtained using Integer Linear Programming (ILP). The data obtained from PMU is given as input to a multilayer Feedforward Neural Network (FFNN) and its output gives all the information related to the modes of the system and the mode ranking. The effectiveness of the proposed approach is investigated on IEEE 39-bus test system. The results show that the proposed approach is fast with less computational burden and is suitable for online and real time oscillations monitoring of the power systems under varying operating conditions.
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
Renewable energy systems for generating electric power: A review A novel design of circular fractal antenna using inset line feed for multiband applications Integrated control of active front steer angle and direct yaw moment using Second Order Sliding Mode technique Voltage differencing buffered amplifier based quadrature oscillator Identification of higher order critically damped systems using relay feedback test
×
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