Electricity Price Forecasting Methods Applied to Spanish Electricity Market

Detalhes bibliográficos
Autor(a) principal: Ortiz, M.
Data de Publicação: 2013
Outros Autores: Ukar, O., Azevedo, Filipe, Mugica, A.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.22/9365
Resumo: Forecasting electricity prices is a fundamental task for all type of markets participants including electricity markets. There are factors that bring unce1tainty to price formation, such as demand forecasting, fuel prices, player's strategies, regulatory changes, weather conditions and technical restrictions and generation availability. In addition, the particular characteristics of electricity (supply must be in balance with demand) make this task more complicated. So, it is necessary to develop accurate and robust techniques on a sho1t-term (days) and long-term basis (months). This work presents two methodologies to be applied to long-term electricity prices forecasting (months) in Spanish electricity market for a glven period. A study case with real data is presented and discussed in detail.
id RCAP_1c86e1b2b86c7279a5b604d1ca5c14a4
oai_identifier_str oai:recipp.ipp.pt:10400.22/9365
network_acronym_str RCAP
network_name_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository_id_str 7160
spelling Electricity Price Forecasting Methods Applied to Spanish Electricity MarketArtificial neural networksElectricity MarketsPrice ForecastingRegression ModelsForecasting electricity prices is a fundamental task for all type of markets participants including electricity markets. There are factors that bring unce1tainty to price formation, such as demand forecasting, fuel prices, player's strategies, regulatory changes, weather conditions and technical restrictions and generation availability. In addition, the particular characteristics of electricity (supply must be in balance with demand) make this task more complicated. So, it is necessary to develop accurate and robust techniques on a sho1t-term (days) and long-term basis (months). This work presents two methodologies to be applied to long-term electricity prices forecasting (months) in Spanish electricity market for a glven period. A study case with real data is presented and discussed in detail.Purple Gate PublishingRepositório Científico do Instituto Politécnico do PortoOrtiz, M.Ukar, O.Azevedo, FilipeMugica, A.2013-042117-01-01T00:00:00Z2013-04-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.22/9365eng1889-7762metadata only accessinfo: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:RCAAP2023-03-13T12:49:58Zoai:recipp.ipp.pt:10400.22/9365Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:29:31.322466Repositório 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 Electricity Price Forecasting Methods Applied to Spanish Electricity Market
title Electricity Price Forecasting Methods Applied to Spanish Electricity Market
spellingShingle Electricity Price Forecasting Methods Applied to Spanish Electricity Market
Ortiz, M.
Artificial neural networks
Electricity Markets
Price Forecasting
Regression Models
title_short Electricity Price Forecasting Methods Applied to Spanish Electricity Market
title_full Electricity Price Forecasting Methods Applied to Spanish Electricity Market
title_fullStr Electricity Price Forecasting Methods Applied to Spanish Electricity Market
title_full_unstemmed Electricity Price Forecasting Methods Applied to Spanish Electricity Market
title_sort Electricity Price Forecasting Methods Applied to Spanish Electricity Market
author Ortiz, M.
author_facet Ortiz, M.
Ukar, O.
Azevedo, Filipe
Mugica, A.
author_role author
author2 Ukar, O.
Azevedo, Filipe
Mugica, A.
author2_role author
author
author
dc.contributor.none.fl_str_mv Repositório Científico do Instituto Politécnico do Porto
dc.contributor.author.fl_str_mv Ortiz, M.
Ukar, O.
Azevedo, Filipe
Mugica, A.
dc.subject.por.fl_str_mv Artificial neural networks
Electricity Markets
Price Forecasting
Regression Models
topic Artificial neural networks
Electricity Markets
Price Forecasting
Regression Models
description Forecasting electricity prices is a fundamental task for all type of markets participants including electricity markets. There are factors that bring unce1tainty to price formation, such as demand forecasting, fuel prices, player's strategies, regulatory changes, weather conditions and technical restrictions and generation availability. In addition, the particular characteristics of electricity (supply must be in balance with demand) make this task more complicated. So, it is necessary to develop accurate and robust techniques on a sho1t-term (days) and long-term basis (months). This work presents two methodologies to be applied to long-term electricity prices forecasting (months) in Spanish electricity market for a glven period. A study case with real data is presented and discussed in detail.
publishDate 2013
dc.date.none.fl_str_mv 2013-04
2013-04-01T00:00:00Z
2117-01-01T00:00:00Z
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/10400.22/9365
url http://hdl.handle.net/10400.22/9365
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 1889-7762
dc.rights.driver.fl_str_mv metadata only access
info:eu-repo/semantics/openAccess
rights_invalid_str_mv metadata only access
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Purple Gate Publishing
publisher.none.fl_str_mv Purple Gate Publishing
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_ 1799131390947622912

Registros relacionados