{"title":"Simple algorithm for identification of unbalanced sag type","authors":"S. Murkute, M. Chaudhari","doi":"10.1109/ICETEESES.2016.7581345","DOIUrl":null,"url":null,"abstract":"This paper proposes a simple algorithm to detect and identify the unbalanced three phase voltage sag. The technique is based Features extracted from space vector magnitude. For normal system operation the space vector magnitude is constant dc, and during unbalanced sag it oscillates. The features of space vector magnitude are identified to investigate the sag type. S-Transform is used as a tool for feature extraction from SVM. The sag type is identified based on Symmetrical component classification is used The sag types are classified in to six types as given by symmetrical component classification. The technique is tested using simulated sag data. The results show that space vector magnitude S-transform technique is able to identify all types of three phase sags correctly. It avoids the need to calculate sequence components. The main advantage of using the technique is its simplicity and reliability.","PeriodicalId":322442,"journal":{"name":"2016 International Conference on Emerging Trends in Electrical Electronics & Sustainable Energy Systems (ICETEESES)","volume":"98 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Conference on Emerging Trends in Electrical Electronics & Sustainable Energy Systems (ICETEESES)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICETEESES.2016.7581345","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This paper proposes a simple algorithm to detect and identify the unbalanced three phase voltage sag. The technique is based Features extracted from space vector magnitude. For normal system operation the space vector magnitude is constant dc, and during unbalanced sag it oscillates. The features of space vector magnitude are identified to investigate the sag type. S-Transform is used as a tool for feature extraction from SVM. The sag type is identified based on Symmetrical component classification is used The sag types are classified in to six types as given by symmetrical component classification. The technique is tested using simulated sag data. The results show that space vector magnitude S-transform technique is able to identify all types of three phase sags correctly. It avoids the need to calculate sequence components. The main advantage of using the technique is its simplicity and reliability.