{"title":"基于正序分量的非均匀分接三端传输网故障定位算法","authors":"Purushotham Reddy Chegireddy, R. Bhimasingu","doi":"10.1109/ICPS52420.2021.9670201","DOIUrl":null,"url":null,"abstract":"The research work presents a new positive sequence components based fault location estimation algorithm for three terminal non-homogeneous transmission network. The algorithm utilises the data corresponding to pre-fault and during fault for calculating line parameters and determines the faulted line section and fault location. The simulations are carried in PSCAD® and the algorithm is evaluated through MATLAB for a 161kV network. The algorithm has been evaluated for all fault types with different values of fault resistances at various fault locations. Out of 144 test cases 142 cases have resulted % error less than 1.5% i.e. the % error is less than 1.5% for 98.6% cases.","PeriodicalId":153735,"journal":{"name":"2021 9th IEEE International Conference on Power Systems (ICPS)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Positive Sequence Components based Fault Location Algorithm For Three Terminal Transmission Network with Non-Homogeneous Tapping\",\"authors\":\"Purushotham Reddy Chegireddy, R. Bhimasingu\",\"doi\":\"10.1109/ICPS52420.2021.9670201\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The research work presents a new positive sequence components based fault location estimation algorithm for three terminal non-homogeneous transmission network. The algorithm utilises the data corresponding to pre-fault and during fault for calculating line parameters and determines the faulted line section and fault location. The simulations are carried in PSCAD® and the algorithm is evaluated through MATLAB for a 161kV network. The algorithm has been evaluated for all fault types with different values of fault resistances at various fault locations. Out of 144 test cases 142 cases have resulted % error less than 1.5% i.e. the % error is less than 1.5% for 98.6% cases.\",\"PeriodicalId\":153735,\"journal\":{\"name\":\"2021 9th IEEE International Conference on Power Systems (ICPS)\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 9th IEEE International Conference on Power Systems (ICPS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICPS52420.2021.9670201\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 9th IEEE International Conference on Power Systems (ICPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPS52420.2021.9670201","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Positive Sequence Components based Fault Location Algorithm For Three Terminal Transmission Network with Non-Homogeneous Tapping
The research work presents a new positive sequence components based fault location estimation algorithm for three terminal non-homogeneous transmission network. The algorithm utilises the data corresponding to pre-fault and during fault for calculating line parameters and determines the faulted line section and fault location. The simulations are carried in PSCAD® and the algorithm is evaluated through MATLAB for a 161kV network. The algorithm has been evaluated for all fault types with different values of fault resistances at various fault locations. Out of 144 test cases 142 cases have resulted % error less than 1.5% i.e. the % error is less than 1.5% for 98.6% cases.