Peng Li, Liqiang Fei, J. Qian, Jing Chen, Xiaochu Li
{"title":"Based on the improved HHT and its application in the power quality detection of microgrid","authors":"Peng Li, Liqiang Fei, J. Qian, Jing Chen, Xiaochu Li","doi":"10.1109/ICEMS.2011.6073708","DOIUrl":null,"url":null,"abstract":"This paper presents a new power quality detection method based on the improved HHT in microgrid. Hilbert-Huang Transform (HHT) can distill these disturbing signals automatically and time-frequency spectrum can be obtained. However, in the application of this method there are serious end effects that mixed mode phenomenon will appear, affecting the detecting results. In order to suppress the end effects, the original data is extended by Least Squares Support Vector Machine (LS-SVM). The results show that the improved HHT method is effective to control the end effects and the frequency and amplitude of disturbing signal will be detected quickly and effectively.","PeriodicalId":101507,"journal":{"name":"2011 International Conference on Electrical Machines and Systems","volume":"120 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 International Conference on Electrical Machines and Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEMS.2011.6073708","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
This paper presents a new power quality detection method based on the improved HHT in microgrid. Hilbert-Huang Transform (HHT) can distill these disturbing signals automatically and time-frequency spectrum can be obtained. However, in the application of this method there are serious end effects that mixed mode phenomenon will appear, affecting the detecting results. In order to suppress the end effects, the original data is extended by Least Squares Support Vector Machine (LS-SVM). The results show that the improved HHT method is effective to control the end effects and the frequency and amplitude of disturbing signal will be detected quickly and effectively.