{"title":"Measurement loss effect on power system state estimation","authors":"K. Greyson, A. Oonsivilai","doi":"10.1109/ROBIO.2009.4913116","DOIUrl":null,"url":null,"abstract":"The main objective of this research work is to classify measurements units in optimal measurement environments in the power system network. Firstly, the use of singular value decomposition is used to find the optimal measurements placement. This is the optimum environment where each measurement unit is given weight upon its effect on the state estimation accuracy. Loss of the measurement unit can be due to the bad data received and the measurement is discarded or not telemetered due to the communication link error. In this case the respective relative error in state estimation is obtained by using MATLAB simulation. The higher weighted as considered to be critical and less weighted are considered non critical measurements are identified in the power system. In this paper related quantities that are more affected are identified.","PeriodicalId":321332,"journal":{"name":"2008 IEEE International Conference on Robotics and Biomimetics","volume":"140 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 IEEE International Conference on Robotics and Biomimetics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ROBIO.2009.4913116","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
The main objective of this research work is to classify measurements units in optimal measurement environments in the power system network. Firstly, the use of singular value decomposition is used to find the optimal measurements placement. This is the optimum environment where each measurement unit is given weight upon its effect on the state estimation accuracy. Loss of the measurement unit can be due to the bad data received and the measurement is discarded or not telemetered due to the communication link error. In this case the respective relative error in state estimation is obtained by using MATLAB simulation. The higher weighted as considered to be critical and less weighted are considered non critical measurements are identified in the power system. In this paper related quantities that are more affected are identified.