{"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}
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.