Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/54494
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dc.titleA new approach to monitoring electric power quality
dc.contributor.authorDash, P.K.
dc.contributor.authorPanda, S.K.
dc.contributor.authorLiew, A.C.
dc.contributor.authorMishra, B.
dc.contributor.authorJena, R.K.
dc.date.accessioned2014-06-16T09:31:43Z
dc.date.available2014-06-16T09:31:43Z
dc.date.issued1998-07
dc.identifier.citationDash, P.K.,Panda, S.K.,Liew, A.C.,Mishra, B.,Jena, R.K. (1998-07). A new approach to monitoring electric power quality. Electric Power Systems Research 46 (1) : 11-20. ScholarBank@NUS Repository.
dc.identifier.issn03787796
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/54494
dc.description.abstractThe paper presents an adaptive neural network approach for the estimation of harmonic distortions and power quality in power networks. The neural estimator is based on the use of linear adaptive neural elements called adalines The learning parameter of the proposed algorithm is suitably adjusted to provide fast convergence and noise rejection for tracking distorted signals in the power networks. Several numerical tests have been conducted for the adaptive estimation of harmonic components, total harmonic distortions, power quality of simulated waveforms in power networks supplying converter loads and switched capacitors. Laboratory test results are also presented in support of the performance of the new algorithm. © 1998 Elsevier Science S.A. All rights reserved.
dc.sourceScopus
dc.subjectElectric power quality
dc.subjectHarmonic distortions
dc.subjectNeural network
dc.typeArticle
dc.contributor.departmentELECTRICAL ENGINEERING
dc.description.sourcetitleElectric Power Systems Research
dc.description.volume46
dc.description.issue1
dc.description.page11-20
dc.description.codenEPSRD
dc.identifier.isiutNOT_IN_WOS
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