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

Bibliographic Details
Main Author: Pousinho, Hugo Miguel Inácio
Publication Date: 2011
Other Authors: Mendes, Victor, Catalão, João Paulo da Silva
Format: Article
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10400.21/523
Summary: The 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.
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spelling A hybrid PSO-ANFIS approach for short-term wind power prediction in PortugalWind powerPredictionSwarm optimizationNeuro-fuzzyThe 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.PERGAMON-ELSEVIER SCIENCE LTDRCIPLPousinho, Hugo Miguel InácioMendes, VictorCatalão, João Paulo da Silva2011-11-24T11:34:00Z2011-012011-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfapplication/pdfhttp://hdl.handle.net/10400.21/523eng0196-8904info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-02-12T11:03:14Zoai:repositorio.ipl.pt:10400.21/523Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T20:10:01.445564Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv A hybrid PSO-ANFIS approach for short-term wind power prediction in Portugal
title A hybrid PSO-ANFIS approach for short-term wind power prediction in Portugal
spellingShingle A hybrid PSO-ANFIS approach for short-term wind power prediction in Portugal
Pousinho, Hugo Miguel Inácio
Wind power
Prediction
Swarm optimization
Neuro-fuzzy
title_short A hybrid PSO-ANFIS approach for short-term wind power prediction in Portugal
title_full A hybrid PSO-ANFIS approach for short-term wind power prediction in Portugal
title_fullStr A hybrid PSO-ANFIS approach for short-term wind power prediction in Portugal
title_full_unstemmed A hybrid PSO-ANFIS approach for short-term wind power prediction in Portugal
title_sort A hybrid PSO-ANFIS approach for short-term wind power prediction in Portugal
author Pousinho, Hugo Miguel Inácio
author_facet Pousinho, Hugo Miguel Inácio
Mendes, Victor
Catalão, João Paulo da Silva
author_role author
author2 Mendes, Victor
Catalão, João Paulo da Silva
author2_role author
author
dc.contributor.none.fl_str_mv RCIPL
dc.contributor.author.fl_str_mv Pousinho, Hugo Miguel Inácio
Mendes, Victor
Catalão, João Paulo da Silva
dc.subject.por.fl_str_mv Wind power
Prediction
Swarm optimization
Neuro-fuzzy
topic Wind power
Prediction
Swarm optimization
Neuro-fuzzy
description The 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.
publishDate 2011
dc.date.none.fl_str_mv 2011-11-24T11:34:00Z
2011-01
2011-01-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.21/523
url http://hdl.handle.net/10400.21/523
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 0196-8904
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv PERGAMON-ELSEVIER SCIENCE LTD
publisher.none.fl_str_mv PERGAMON-ELSEVIER SCIENCE LTD
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
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instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
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