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An artificial neural network approach for short-term wind power forecasting in Portugal

dc.contributor.authorCatalão, João Paulo da Silva
dc.contributor.authorPousinho, Hugo Miguel Inácio
dc.contributor.authorMendes, Victor
dc.date.accessioned2012-03-13T13:05:19Z
dc.date.available2012-03-13T13:05:19Z
dc.date.issued2009-03
dc.description.abstractThis paper presents an artificial neural network approach for short-term wind power forecasting in Portugal. The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Hence, good forecasting tools play a key role in tackling these challenges. The accuracy of the wind power forecasting attained with the proposed approach is evaluated against persistence and ARIMA approaches, reporting the numerical results from a real-world case study.por
dc.identifier.citationCatalão J P S, Pousinho H M I, Mendes V M F.An artificial neural network approach for short-term wind power forecasting in Portugal. Engineering Intelligent Systems for Electrical Engineering and Communications. 2009; 17 (1): 5-11.por
dc.identifier.issn1472-8915
dc.identifier.urihttp://hdl.handle.net/10400.21/1272
dc.language.isoengpor
dc.peerreviewedyespor
dc.publisherC R L Publishing LTDpor
dc.relation.ispartofseries1;
dc.subjectArtificial neural networkspor
dc.subjectForecastingpor
dc.subjectWind powerpor
dc.subjectModelspor
dc.subjectPredictionpor
dc.subjectSpeedpor
dc.titleAn artificial neural network approach for short-term wind power forecasting in Portugalpor
dc.typejournal article
dspace.entity.typePublication
oaire.citation.conferencePlaceLeicesterpor
oaire.citation.endPage11por
oaire.citation.issue17por
oaire.citation.startPage5por
oaire.citation.titleEngineering Intelligent Systems for Electrical Engineering and Communicationspor
person.familyNameMendes
person.givenNameVictor
person.identifier.orcid0000-0002-4599-477X
person.identifier.ridD-2332-2012
person.identifier.scopus-author-id55138675600
rcaap.rightsrestrictedAccesspor
rcaap.typearticlepor
relation.isAuthorOfPublicationa86b9291-f23c-4f09-83d7-9ee691696705
relation.isAuthorOfPublication.latestForDiscoverya86b9291-f23c-4f09-83d7-9ee691696705

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