{"title":"Robust phase detection in distribution systems","authors":"M. S. Modarresi, Tong Huang, Hao Ming, Le Xie","doi":"10.1109/TPEC.2017.7868279","DOIUrl":null,"url":null,"abstract":"This paper proposes an on-line algorithm to detect the phase connection for end users in a power distribution system. In distribution systems, feeder switching often changes the phase connection information of end users in the real-time operation. Recently, Advanced Metering infrastructure (AMI) are being installed in distribution systems. They enable utilities to record end-point voltages in defined intervals. This paper first presents a method to find phases belonging to same phase using synchronized data and fixed topology of distribution grid. Then, this paper presents a method to clean the noisy data through Artificial Neural Network (ANN) trained by the historical data. The proposed methods is tested using modified 13-bus IEEE distribution test system on the low-voltage side.","PeriodicalId":391980,"journal":{"name":"2017 IEEE Texas Power and Energy Conference (TPEC)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE Texas Power and Energy Conference (TPEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TPEC.2017.7868279","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12
Abstract
This paper proposes an on-line algorithm to detect the phase connection for end users in a power distribution system. In distribution systems, feeder switching often changes the phase connection information of end users in the real-time operation. Recently, Advanced Metering infrastructure (AMI) are being installed in distribution systems. They enable utilities to record end-point voltages in defined intervals. This paper first presents a method to find phases belonging to same phase using synchronized data and fixed topology of distribution grid. Then, this paper presents a method to clean the noisy data through Artificial Neural Network (ANN) trained by the historical data. The proposed methods is tested using modified 13-bus IEEE distribution test system on the low-voltage side.