Export Ready — 

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

Bibliographic Details
Main Author: Pousinho, Hugo Miguel Inácio
Publication Date: 2012
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/10400.21/1878
Summary: In this paper, a novel hybrid approach is proposed for electricity prices forecasting in a competitive market, considering a time horizon of 1 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. (C) 2012 Elsevier Ltd. All rights reserved.
id RCAP_f7f36ba0aaacbd12432ef9d5b2c0e1f9
oai_identifier_str oai:repositorio.ipl.pt:10400.21/1878
network_acronym_str RCAP
network_name_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository_id_str https://opendoar.ac.uk/repository/7160
spelling Short-term electricity prices forecasting in a competitive market by a hybrid PSO-ANFIS approachElectricity MarketPrice ForecastingSwarm OptimizationNeural NetworksFuzzy LogicNeural-NetworkARIMA ModelsSystemIn this paper, a novel hybrid approach is proposed for electricity prices forecasting in a competitive market, considering a time horizon of 1 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. (C) 2012 Elsevier Ltd. All rights reserved.Elsevier Sci LTDRCIPLPousinho, Hugo Miguel InácioMendes, VictorCatalão, João Paulo da Silva2012-11-02T17:04:54Z2012-062012-06-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.21/1878eng0142-0615info: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:RCAAP2025-02-12T10:04:29Zoai:repositorio.ipl.pt:10400.21/1878Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T20:04:06.877332Repositórios 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 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
Pousinho, Hugo Miguel Inácio
Electricity Market
Price Forecasting
Swarm Optimization
Neural Networks
Fuzzy Logic
Neural-Network
ARIMA Models
System
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 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 Electricity Market
Price Forecasting
Swarm Optimization
Neural Networks
Fuzzy Logic
Neural-Network
ARIMA Models
System
topic Electricity Market
Price Forecasting
Swarm Optimization
Neural Networks
Fuzzy Logic
Neural-Network
ARIMA Models
System
description In this paper, a novel hybrid approach is proposed for electricity prices forecasting in a competitive market, considering a time horizon of 1 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. (C) 2012 Elsevier Ltd. All rights reserved.
publishDate 2012
dc.date.none.fl_str_mv 2012-11-02T17:04:54Z
2012-06
2012-06-01T00:00:00Z
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/10400.21/1878
url http://hdl.handle.net/10400.21/1878
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 0142-0615
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier Sci LTD
publisher.none.fl_str_mv Elsevier Sci 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
instacron:RCAAP
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
_version_ 1833598473357754368

Similar Items