J. J. González de la Rosa, J. Sierra-Fernandez, A. Aguera-Perez, J. Palomares-Salas, A. Moreno-Muñoz
{"title":"Power quality events detection using fourth-order spectra","authors":"J. J. González de la Rosa, J. Sierra-Fernandez, A. Aguera-Perez, J. Palomares-Salas, A. Moreno-Muñoz","doi":"10.1109/CPE.2013.6601121","DOIUrl":null,"url":null,"abstract":"This paper introduces the use of a fourth-order frequency-domain statistical estimator, the spectral kurtosis (SK), in the field of power-quality analysis. The research has been organized in the frame of a research national project and points towards the implementation of these techniques into an automatic platform to perform PQ analysis in power plants and power inverters. Higher-order statistics in the frequency domain manage to distinguish 3 types of electrical anomalies (sags, swells and transients), with an accuracy of 83%.","PeriodicalId":128620,"journal":{"name":"2013 International Conference-Workshop Compatibility And Power Electronics","volume":"21 8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 International Conference-Workshop Compatibility And Power Electronics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CPE.2013.6601121","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 introduces the use of a fourth-order frequency-domain statistical estimator, the spectral kurtosis (SK), in the field of power-quality analysis. The research has been organized in the frame of a research national project and points towards the implementation of these techniques into an automatic platform to perform PQ analysis in power plants and power inverters. Higher-order statistics in the frequency domain manage to distinguish 3 types of electrical anomalies (sags, swells and transients), with an accuracy of 83%.
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