{"title":"Swarm Assisted Positive Sequence Current Component based Directional Relaying for Transmission Line Protection","authors":"C. Prasad, M. Biswal, P. K. Nayak","doi":"10.1109/PIICON49524.2020.9112960","DOIUrl":null,"url":null,"abstract":"In this paper, swarm assisted positive sequence current based directional relaying is proposed for detection and direction estimation of faults in power transmission network. For this classification, two different thresholds are identified through particle swarm optimization (PSO) algorithm. The available methods used to adopt trial-and-error based threshold setting approaches for detection and classification of fault direction and have limitation for certain fault and non-fault events. On the other hand, the proposed swarm intelligence assisted optimal threshold setting obtained from a set of randomly generated solutions using PSO ensures reliable estimation of fault direction even for extreme fault and non-fault events. This is evident from the extensive case studies generated on a 2-bus test power system using MATLAB-SIMULINK.","PeriodicalId":422853,"journal":{"name":"2020 IEEE 9th Power India International Conference (PIICON)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 9th Power India International Conference (PIICON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PIICON49524.2020.9112960","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
In this paper, swarm assisted positive sequence current based directional relaying is proposed for detection and direction estimation of faults in power transmission network. For this classification, two different thresholds are identified through particle swarm optimization (PSO) algorithm. The available methods used to adopt trial-and-error based threshold setting approaches for detection and classification of fault direction and have limitation for certain fault and non-fault events. On the other hand, the proposed swarm intelligence assisted optimal threshold setting obtained from a set of randomly generated solutions using PSO ensures reliable estimation of fault direction even for extreme fault and non-fault events. This is evident from the extensive case studies generated on a 2-bus test power system using MATLAB-SIMULINK.