Yuki Tsujii, Kentaro Kawakita, M. Kumagai, Akira Kikuchi, Masahiro Watanabe
{"title":"在线动态安全评估状态估计误差检测系统","authors":"Yuki Tsujii, Kentaro Kawakita, M. Kumagai, Akira Kikuchi, Masahiro Watanabe","doi":"10.1109/ISGT.2017.8086079","DOIUrl":null,"url":null,"abstract":"Online Dynamic Security Assessment (DSA) is a dynamical system widely used for assessing and analyzing an electrical power system. The outcomes of DSA are used in many aspects of the operation of power system, from monitoring the system to determining remedial action schemes (e.g. the amount of generators to be shed at the event of a fault). Measurement from supervisory control and data acquisition (SCADA) and state estimation (SE) results are the inputs for online-DSA, however, the SE error, caused by sudden change in power flow or low convergence rate, could be unnoticed and skew the outcome. Therefore, generator shedding scheme cannot achieve optimum but must have some margin because we don't know how SE error caused by these problems will impact power system stability control. As a method for solving the problem, we developed SE error detection system (EDS), which is enabled by detecting the SE error that will impact power system transient stability. The method is comparing a threshold value and an index calculated by the difference between SE results and PMU observation data, using the distance from the fault point and the power flow value. Using the index, the reliability of the SE results can be verified. As a result, online-DSA can use the SE results while avoiding the bad SE results, assuring the outcome of the DSA assessment and analysis, such as the amount of generator shedding in order to prevent the power system's instability.","PeriodicalId":296398,"journal":{"name":"2017 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"State estimation error detection system for online dynamic security assessment\",\"authors\":\"Yuki Tsujii, Kentaro Kawakita, M. Kumagai, Akira Kikuchi, Masahiro Watanabe\",\"doi\":\"10.1109/ISGT.2017.8086079\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Online Dynamic Security Assessment (DSA) is a dynamical system widely used for assessing and analyzing an electrical power system. The outcomes of DSA are used in many aspects of the operation of power system, from monitoring the system to determining remedial action schemes (e.g. the amount of generators to be shed at the event of a fault). Measurement from supervisory control and data acquisition (SCADA) and state estimation (SE) results are the inputs for online-DSA, however, the SE error, caused by sudden change in power flow or low convergence rate, could be unnoticed and skew the outcome. Therefore, generator shedding scheme cannot achieve optimum but must have some margin because we don't know how SE error caused by these problems will impact power system stability control. As a method for solving the problem, we developed SE error detection system (EDS), which is enabled by detecting the SE error that will impact power system transient stability. The method is comparing a threshold value and an index calculated by the difference between SE results and PMU observation data, using the distance from the fault point and the power flow value. Using the index, the reliability of the SE results can be verified. As a result, online-DSA can use the SE results while avoiding the bad SE results, assuring the outcome of the DSA assessment and analysis, such as the amount of generator shedding in order to prevent the power system's instability.\",\"PeriodicalId\":296398,\"journal\":{\"name\":\"2017 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)\",\"volume\":\"92 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISGT.2017.8086079\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISGT.2017.8086079","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
State estimation error detection system for online dynamic security assessment
Online Dynamic Security Assessment (DSA) is a dynamical system widely used for assessing and analyzing an electrical power system. The outcomes of DSA are used in many aspects of the operation of power system, from monitoring the system to determining remedial action schemes (e.g. the amount of generators to be shed at the event of a fault). Measurement from supervisory control and data acquisition (SCADA) and state estimation (SE) results are the inputs for online-DSA, however, the SE error, caused by sudden change in power flow or low convergence rate, could be unnoticed and skew the outcome. Therefore, generator shedding scheme cannot achieve optimum but must have some margin because we don't know how SE error caused by these problems will impact power system stability control. As a method for solving the problem, we developed SE error detection system (EDS), which is enabled by detecting the SE error that will impact power system transient stability. The method is comparing a threshold value and an index calculated by the difference between SE results and PMU observation data, using the distance from the fault point and the power flow value. Using the index, the reliability of the SE results can be verified. As a result, online-DSA can use the SE results while avoiding the bad SE results, assuring the outcome of the DSA assessment and analysis, such as the amount of generator shedding in order to prevent the power system's instability.