{"title":"计算智能在电能质量干扰诊断中的应用","authors":"M. Faisal, A. Mohamed","doi":"10.1109/APEMC.2012.6237889","DOIUrl":null,"url":null,"abstract":"This paper presents the application of signal processing and artificial intelligence techniques for performing automated power quality (PQ) diagnosis. This new diagnosis system is named as the Power Quality Diagnostic System or PQDS. The PQDS is developed using the S-Transform (ST) and the Support Vector Regression (SVR) techniques. The PQDS has been successfully implemented in Malaysia and has assisted the power utility's engineers in verifying the types, sources and causes of the recorded PQ disturbances by the online power quality monitoring system (PQMS). The PQDS gave perfect (100%) accuracy in diagnosing voltage sags.","PeriodicalId":300639,"journal":{"name":"2012 Asia-Pacific Symposium on Electromagnetic Compatibility","volume":"71 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Application of computational intelligence for diagnosing Power Quality disturbances\",\"authors\":\"M. Faisal, A. Mohamed\",\"doi\":\"10.1109/APEMC.2012.6237889\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents the application of signal processing and artificial intelligence techniques for performing automated power quality (PQ) diagnosis. This new diagnosis system is named as the Power Quality Diagnostic System or PQDS. The PQDS is developed using the S-Transform (ST) and the Support Vector Regression (SVR) techniques. The PQDS has been successfully implemented in Malaysia and has assisted the power utility's engineers in verifying the types, sources and causes of the recorded PQ disturbances by the online power quality monitoring system (PQMS). The PQDS gave perfect (100%) accuracy in diagnosing voltage sags.\",\"PeriodicalId\":300639,\"journal\":{\"name\":\"2012 Asia-Pacific Symposium on Electromagnetic Compatibility\",\"volume\":\"71 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-05-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 Asia-Pacific Symposium on Electromagnetic Compatibility\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/APEMC.2012.6237889\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 Asia-Pacific Symposium on Electromagnetic Compatibility","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APEMC.2012.6237889","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Application of computational intelligence for diagnosing Power Quality disturbances
This paper presents the application of signal processing and artificial intelligence techniques for performing automated power quality (PQ) diagnosis. This new diagnosis system is named as the Power Quality Diagnostic System or PQDS. The PQDS is developed using the S-Transform (ST) and the Support Vector Regression (SVR) techniques. The PQDS has been successfully implemented in Malaysia and has assisted the power utility's engineers in verifying the types, sources and causes of the recorded PQ disturbances by the online power quality monitoring system (PQMS). The PQDS gave perfect (100%) accuracy in diagnosing voltage sags.
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