{"title":"Improved recursive Newton type algorithm for real-time frequency estimation in power systems","authors":"V. Terzija","doi":"10.1109/IMTC.1997.603992","DOIUrl":null,"url":null,"abstract":"In this paper a new improved recursive Newton type algorithm suitable for measurement applications in power systems is presented. It is used for power system frequency, phasors and spectra estimation. The recursive form of Newton type algorithm is improved with a strategy of sequentially tuning the forgetting factor. By this, the main algorithm properties, speed of convergence and accuracy, are significantly improved. The results of computer simulation, laboratory testing and off-line full-scale real-life data processing are given to show the main algorithm features.","PeriodicalId":124893,"journal":{"name":"IEEE Instrumentation and Measurement Technology Conference Sensing, Processing, Networking. IMTC Proceedings","volume":"80 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Instrumentation and Measurement Technology Conference Sensing, Processing, Networking. IMTC Proceedings","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IMTC.1997.603992","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
In this paper a new improved recursive Newton type algorithm suitable for measurement applications in power systems is presented. It is used for power system frequency, phasors and spectra estimation. The recursive form of Newton type algorithm is improved with a strategy of sequentially tuning the forgetting factor. By this, the main algorithm properties, speed of convergence and accuracy, are significantly improved. The results of computer simulation, laboratory testing and off-line full-scale real-life data processing are given to show the main algorithm features.