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Evolving RBF predictive models to forecast the Portuguese electricity consumption

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dc.contributor.authorFerreira, P. M.
dc.contributor.authorRuano, Antonio
dc.contributor.authorPestana, Rui
dc.contributor.authorKóczy, László T.
dc.date.accessioned2013-02-02T11:54:54Z
dc.date.available2013-02-02T11:54:54Z
dc.date.issued2009
dc.date.updated2013-01-26T17:25:27Z
dc.description.abstractThe Portuguese power grid company wants to improve the accuracy of the electricity load demand (ELD) forecast within an horizon of 24 to 48 hours, in order to identify the need of reserves to be allocated in the Iberian Market. In this work we present some preliminary results about the identi cation of radial basis function (RBF) neural network (NN) ELD predictive models and about the performance of a model selection algorithm. The methodology follows the principles already employed by the authors in di erent applications: the NN models are trained by the Levenberg-Marquardt algorithm using a modi ed training criterion, and the model structure (number of neurons and input terms) is evolved using a Multi-Objective Genetic Algorithm (MOGA). The set of goals and objectives used in the MOGA model optimisation reflect different requirements in the design: obtaining good generalisation ability, good balance between one-step-ahead prediction accuracy and model complexity, and good multi-step prediction accuracy. A number of experiments were carried out, whose results are presented, producing already a number of models whose predictive performance is satisfactory.por
dc.identifier.citationFerreira, P. M.; Ruano, A. E. Evolving RBF predictive models to forecast the Portuguese electricity consumption, Trabalho apresentado em Intelligent Control Systems and Signal Processing, In Proceedings of the 2nd IFAC International Conference on Intelligent Control Systems and Signal Processing (2009), Istambul, 2009.por
dc.identifier.doihttp://dx.doi.org/10.3182/20090921-3-TR-3005.00073
dc.identifier.isbn9783902661661
dc.identifier.otherAUT: ARU00698;
dc.identifier.urihttp://hdl.handle.net/10400.1/2196
dc.language.isoengpor
dc.peerreviewedyespor
dc.publisherElsevier, IFACpor
dc.subjectElectricity load Demandpor
dc.subjectRadial Basis Functionspor
dc.subjectNeural Networkspor
dc.subjectPredictionpor
dc.subjectModellingpor
dc.titleEvolving RBF predictive models to forecast the Portuguese electricity consumptionpor
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferencePlaceIstambulpor
oaire.citation.title2nd IFAC International Conference on Intelligent Control Systems and Signal Processing (2009)por
oaire.citation.volume2
person.familyNameRuano
person.givenNameAntonio
person.identifier.orcid0000-0002-6308-8666
person.identifier.ridB-4135-2008
person.identifier.scopus-author-id7004284159
rcaap.rightsrestrictedAccesspor
rcaap.typeconferenceObjectpor
relation.isAuthorOfPublication13813664-b68b-40aa-97a9-91481a31ebf2
relation.isAuthorOfPublication.latestForDiscovery13813664-b68b-40aa-97a9-91481a31ebf2

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