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dc.contributor.authorSusanto, Julius
dc.contributor.authorIslam, Syed
dc.contributor.editorMichael Negnevitsky
dc.date.accessioned2017-01-30T12:35:31Z
dc.date.available2017-01-30T12:35:31Z
dc.date.created2014-02-13T20:00:38Z
dc.date.issued2013
dc.identifier.citationSusanto, Julius and Islam, Syed. 2013. Estimation of Induction Motor Parameters Using Hybrid Algorithms for Power System Dynamic Studies, in Negnevitsky, M. (ed), Proceedings of the Australasian Universities Power Engineering Conference (AUPEC), Sep 29-Oct 3 2013. Hobart, Tasmania: University of Tasmania.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/23117
dc.identifier.doi10.1109/AUPEC.2013.6725462
dc.description.abstract

This paper proposes a hybrid Newton-Raphson and genetic algorithm for the estimation of double cage induction motor parameters from commonly available manufacturer data. The hybrid algorithm was tested on a large data set of 6,380 IEC and NEMA motors and then compared with a baseline Newton-Raphson algorithm. The simulation results show that while the proposed hybrid algorithm is more computationally intensive, it does make significant improvements to convergence and error rates.

dc.publisherUniversity of Tasmania
dc.subjecthybrid algorithm
dc.subjectparameter estimation
dc.subjectInduction motor
dc.titleEstimation of Induction Motor Parameters Using Hybrid Algorithms for Power System Dynamic Studies
dc.typeConference Paper
dcterms.source.titleProceedings of the 2013 Australasian Universities Power Engineering Conference
dcterms.source.seriesProceedings of the 2013 Australasian Universities Power Engineering Conference
dcterms.source.isbn9781862959132
dcterms.source.conference2013 Australasian Universities Power Engineering Conference
dcterms.source.conference-start-dateSep 29 2013
dcterms.source.conferencelocationHobart, Tasmania, Australia
dcterms.source.placeHobart, Tasmania
curtin.department
curtin.accessStatusFulltext not available


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