A novel neural model to electrical load forecasting in transformers

dc.contributorUniversidade Estadual Paulista (UNESP)
dc.creatorDe Souza, A. N.
dc.creatorDa Silva, I. N.
dc.creatorUlson, Jose Alfredo Covolan
dc.creatorBordon, M. E.
dc.date2014-05-20T13:27:12Z
dc.date2014-05-20T13:27:12Z
dc.date2001-01-01
dc.date.accessioned2017-04-05T20:07:41Z
dc.date.available2017-04-05T20:07:41Z
dc.identifierWorld Multiconference on Systemics, Cybernetics and Informatics, Vol 1, Proceedings. Orlando: Int Inst Informatics & Systemics, p. 19-23, 2001.
dc.identifierhttp://hdl.handle.net/11449/8880
dc.identifierWOS:000175785900004
dc.identifier0000-0001-8510-8245
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/857142
dc.descriptionThe paper describes a novel neural model to electrical load forecasting in transformers. The network acts as identifier of structural features to forecast process. So that output parameters can be estimated and generalized from an input parameter set. The model was trained and assessed through load data extracted from a Brazilian Electric Utility taking into account time, current, tension, active power in the three phases of the system. The results obtained in the simulations show that the developed technique can be used as an alternative tool to become more appropriate for planning of electric power systems.
dc.languageeng
dc.publisherInt Inst Informatics & Systemics
dc.relationWorld Multiconference on Systemics, Cybernetics and Informatics, Vol 1, Proceedings
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjecttransformer
dc.subjectload forecasting
dc.subjectartificial neural network
dc.titleA novel neural model to electrical load forecasting in transformers
dc.typeOtro


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