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A hybrid PSO-ANFIS approach for short-term wind power prediction in Portugal

dc.contributor.authorPousinho, Hugo Miguel Inácio
dc.contributor.authorMendes, Victor
dc.contributor.authorCatalão, João Paulo da Silva
dc.date.accessioned2011-11-24T11:34:00Z
dc.date.available2011-11-24T11:34:00Z
dc.date.issued2011-01
dc.description.abstractThe increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Wind power prediction plays a key role in tackling these challenges. The contribution of this paper is to propose a new hybrid approach, combining particle swarm optimization and adaptive-network-based fuzzy inference system, for short-term wind power prediction in Portugal. Significant improvements regarding forecasting accuracy are attainable using the proposed approach, in comparison with the results obtained with five other approaches.por
dc.identifier.citationPousinho M, Mendes V, Catalão J. A hybrid PSO-ANFIS approach for short-term wind power prediction in Portugal. Energy Conversion and Management. 2011; 52(1).por
dc.identifier.issn0196-8904
dc.identifier.urihttp://hdl.handle.net/10400.21/523
dc.language.isoengpor
dc.peerreviewedyespor
dc.publisherPERGAMON-ELSEVIER SCIENCE LTDpor
dc.relation.ispartofseries1;
dc.subjectWind powerpor
dc.subjectPredictionpor
dc.subjectSwarm optimizationpor
dc.subjectNeuro-fuzzypor
dc.titleA hybrid PSO-ANFIS approach for short-term wind power prediction in Portugalpor
dc.typejournal article
dspace.entity.typePublication
oaire.citation.conferencePlaceOxfordpor
oaire.citation.endPage402por
oaire.citation.issue52por
oaire.citation.startPage397por
oaire.citation.titleENERGY CONVERSION AND MANAGEMENTpor
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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