{"title":"基于线性规划的电力系统状态估计中的多重不良数据检测","authors":"W. L. Peterson, A. Girgis","doi":"10.1109/SSST.1988.17085","DOIUrl":null,"url":null,"abstract":"The authors describe a method of identifying multiple bad measurements in power-system state estimators using linear programming. Linear programming automatically rejects bad measurements and provides an excellent set of bus voltages and angles which can be used as initial values in a weighted least-squares algorithm if filtering of Gaussian noise is desired. The performance of the linear program in the presence of multiple bad measurements is shown to be superior to the weighted-least-squares technique. The efficiency of the method is independent of the number of bad measurements and the magnitude of the error.<<ETX>>","PeriodicalId":345412,"journal":{"name":"[1988] Proceedings. The Twentieth Southeastern Symposium on System Theory","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1988-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"Multiple bad data detection in power system state estimation using linear programming\",\"authors\":\"W. L. Peterson, A. Girgis\",\"doi\":\"10.1109/SSST.1988.17085\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The authors describe a method of identifying multiple bad measurements in power-system state estimators using linear programming. Linear programming automatically rejects bad measurements and provides an excellent set of bus voltages and angles which can be used as initial values in a weighted least-squares algorithm if filtering of Gaussian noise is desired. The performance of the linear program in the presence of multiple bad measurements is shown to be superior to the weighted-least-squares technique. The efficiency of the method is independent of the number of bad measurements and the magnitude of the error.<<ETX>>\",\"PeriodicalId\":345412,\"journal\":{\"name\":\"[1988] Proceedings. The Twentieth Southeastern Symposium on System Theory\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1988-03-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[1988] Proceedings. The Twentieth Southeastern Symposium on System Theory\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SSST.1988.17085\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1988] Proceedings. The Twentieth Southeastern Symposium on System Theory","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SSST.1988.17085","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multiple bad data detection in power system state estimation using linear programming
The authors describe a method of identifying multiple bad measurements in power-system state estimators using linear programming. Linear programming automatically rejects bad measurements and provides an excellent set of bus voltages and angles which can be used as initial values in a weighted least-squares algorithm if filtering of Gaussian noise is desired. The performance of the linear program in the presence of multiple bad measurements is shown to be superior to the weighted-least-squares technique. The efficiency of the method is independent of the number of bad measurements and the magnitude of the error.<>
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