Short-term electricity prices forecasting in a competitive market by a hybrid PSO-ANFIS approach

Detalhes bibliográficos
Autor(a) principal: Catalao, J. P. S.
Data de Publicação: 2012
Outros Autores: Pousinho, H. M. I., Mendes, V. M. F.
Tipo de documento: Artigo
Idioma: por
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10174/21178
Resumo: In this paper, a novel hybrid approach is proposed for electricity prices forecasting in a competitive market, considering a time horizon of one week. The proposed approach is based on the combination of particle swarm optimization and adaptive-network based fuzzy inference system. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications, to demonstrate its effectiveness regarding forecasting accuracy and computation time. Finally, conclusions are duly drawn. © 2011 Elsevier Ltd. All rights reserved.
id RCAP_64527526d9620c1993d850d24c01a288
oai_identifier_str oai:dspace.uevora.pt:10174/21178
network_acronym_str RCAP
network_name_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository_id_str 7160
spelling Short-term electricity prices forecasting in a competitive market by a hybrid PSO-ANFIS approachElectricity marketFuzzy logicNeural networksPrice forecastingSwarm optimizationIn this paper, a novel hybrid approach is proposed for electricity prices forecasting in a competitive market, considering a time horizon of one week. The proposed approach is based on the combination of particle swarm optimization and adaptive-network based fuzzy inference system. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications, to demonstrate its effectiveness regarding forecasting accuracy and computation time. Finally, conclusions are duly drawn. © 2011 Elsevier Ltd. All rights reserved.2017-07-13T15:11:48Z2017-07-132012-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10174/21178http://hdl.handle.net/10174/21178por0142-0615Catalao, J. P. S.; Pousinho, H. M. I.; Mendes, V. M. F.Short-term electricity prices forecasting in a competitive market by a hybrid PSO-ANFIS approach, INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 39, 1, 29-35, 2012.ndndndCatalao, J. P. S.Pousinho, H. M. I.Mendes, V. M. F.info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-01-03T19:11:22Zoai:dspace.uevora.pt:10174/21178Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T01:12:22.216838Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Short-term electricity prices forecasting in a competitive market by a hybrid PSO-ANFIS approach
title Short-term electricity prices forecasting in a competitive market by a hybrid PSO-ANFIS approach
spellingShingle Short-term electricity prices forecasting in a competitive market by a hybrid PSO-ANFIS approach
Catalao, J. P. S.
Electricity market
Fuzzy logic
Neural networks
Price forecasting
Swarm optimization
title_short Short-term electricity prices forecasting in a competitive market by a hybrid PSO-ANFIS approach
title_full Short-term electricity prices forecasting in a competitive market by a hybrid PSO-ANFIS approach
title_fullStr Short-term electricity prices forecasting in a competitive market by a hybrid PSO-ANFIS approach
title_full_unstemmed Short-term electricity prices forecasting in a competitive market by a hybrid PSO-ANFIS approach
title_sort Short-term electricity prices forecasting in a competitive market by a hybrid PSO-ANFIS approach
author Catalao, J. P. S.
author_facet Catalao, J. P. S.
Pousinho, H. M. I.
Mendes, V. M. F.
author_role author
author2 Pousinho, H. M. I.
Mendes, V. M. F.
author2_role author
author
dc.contributor.author.fl_str_mv Catalao, J. P. S.
Pousinho, H. M. I.
Mendes, V. M. F.
dc.subject.por.fl_str_mv Electricity market
Fuzzy logic
Neural networks
Price forecasting
Swarm optimization
topic Electricity market
Fuzzy logic
Neural networks
Price forecasting
Swarm optimization
description In this paper, a novel hybrid approach is proposed for electricity prices forecasting in a competitive market, considering a time horizon of one week. The proposed approach is based on the combination of particle swarm optimization and adaptive-network based fuzzy inference system. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications, to demonstrate its effectiveness regarding forecasting accuracy and computation time. Finally, conclusions are duly drawn. © 2011 Elsevier Ltd. All rights reserved.
publishDate 2012
dc.date.none.fl_str_mv 2012-01-01T00:00:00Z
2017-07-13T15:11:48Z
2017-07-13
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/10174/21178
http://hdl.handle.net/10174/21178
url http://hdl.handle.net/10174/21178
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv 0142-0615
Catalao, J. P. S.; Pousinho, H. M. I.; Mendes, V. M. F.Short-term electricity prices forecasting in a competitive market by a hybrid PSO-ANFIS approach, INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 39, 1, 29-35, 2012.
nd
nd
nd
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
_version_ 1799136605732077568

Registros relacionados