{"title":"A digital detector of the frequency of power system with noisy signals","authors":"J. Wu","doi":"10.1109/ICIT.2004.1490736","DOIUrl":null,"url":null,"abstract":"This paper presents two methods for frequency estimation of power systems in noisy condition. One method is applied to the cases with sinusoidal signals in power systems corrupted by sine noises basing on central numerical differentiation with 7 points. Another method is applied to the cases with non-sinusoidal signals in power systems corrupted by Gaussian white noises basing on digital band-pass FIR filters. The proposed algorithm requires at most one cycle in sine noises, and takes one and half cycle in Gaussian white noises. Carried out in Matlab, the simulation results show more advantage than other existing techniques.","PeriodicalId":136064,"journal":{"name":"2004 IEEE International Conference on Industrial Technology, 2004. IEEE ICIT '04.","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2004 IEEE International Conference on Industrial Technology, 2004. IEEE ICIT '04.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIT.2004.1490736","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper presents two methods for frequency estimation of power systems in noisy condition. One method is applied to the cases with sinusoidal signals in power systems corrupted by sine noises basing on central numerical differentiation with 7 points. Another method is applied to the cases with non-sinusoidal signals in power systems corrupted by Gaussian white noises basing on digital band-pass FIR filters. The proposed algorithm requires at most one cycle in sine noises, and takes one and half cycle in Gaussian white noises. Carried out in Matlab, the simulation results show more advantage than other existing techniques.