{"title":"考虑模型误差影响的状态估计算法","authors":"Y. Liao","doi":"10.1109/SECON.2007.342943","DOIUrl":null,"url":null,"abstract":"To consider model inaccuracies, existing state estimation approaches augment the state vector by adding the suspicious model parameters. In this paper, the extended least squares estimation approach is applied to design a more general state estimation algorithm for considering power network model errors, without adding the uncertain model parameters to the state vector. Preliminary studies have demonstrated that the method may enhance estimation accuracy when model errors exist.","PeriodicalId":423683,"journal":{"name":"Proceedings 2007 IEEE SoutheastCon","volume":"86 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"State estimation algorithm considering effects of model inaccuracies\",\"authors\":\"Y. Liao\",\"doi\":\"10.1109/SECON.2007.342943\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To consider model inaccuracies, existing state estimation approaches augment the state vector by adding the suspicious model parameters. In this paper, the extended least squares estimation approach is applied to design a more general state estimation algorithm for considering power network model errors, without adding the uncertain model parameters to the state vector. Preliminary studies have demonstrated that the method may enhance estimation accuracy when model errors exist.\",\"PeriodicalId\":423683,\"journal\":{\"name\":\"Proceedings 2007 IEEE SoutheastCon\",\"volume\":\"86 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-03-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings 2007 IEEE SoutheastCon\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SECON.2007.342943\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 2007 IEEE SoutheastCon","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SECON.2007.342943","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
State estimation algorithm considering effects of model inaccuracies
To consider model inaccuracies, existing state estimation approaches augment the state vector by adding the suspicious model parameters. In this paper, the extended least squares estimation approach is applied to design a more general state estimation algorithm for considering power network model errors, without adding the uncertain model parameters to the state vector. Preliminary studies have demonstrated that the method may enhance estimation accuracy when model errors exist.