Short-term electricity prices forecasting in a competitive market by a hybrid PSO-ANFIS approach
Autor(a) principal: | |
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Data de Publicação: | 2012 |
Outros Autores: | , |
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. |
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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 |
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1799136605732077568 |