Optimized Bidding of a EV Aggregation Agent in the Electricity Market

Detalhes bibliográficos
Autor(a) principal: Ricardo Jorge Bessa
Data de Publicação: 2012
Outros Autores: João Peças Lopes, Manuel Matos, Filipe Joel Soares
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://repositorio.inesctec.pt/handle/123456789/2134
Resumo: An electric vehicle (EV) aggregation agent, as a commercial middleman between electricity market and EV owners, participates with bids for purchasing electrical energy and selling secondary reserve. This paper presents an optimization approach to support the aggregation agent participating in the day-ahead and secondary reserve sessions, and identifies the input variables that need to be forecasted or estimated. Results are presented for two years (2009 and 2010) of the Iberian market, and considering perfect and naïve forecast for all variables of the problem.
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spelling Optimized Bidding of a EV Aggregation Agent in the Electricity MarketAn electric vehicle (EV) aggregation agent, as a commercial middleman between electricity market and EV owners, participates with bids for purchasing electrical energy and selling secondary reserve. This paper presents an optimization approach to support the aggregation agent participating in the day-ahead and secondary reserve sessions, and identifies the input variables that need to be forecasted or estimated. Results are presented for two years (2009 and 2010) of the Iberian market, and considering perfect and naïve forecast for all variables of the problem.2017-11-16T13:15:26Z2012-01-01T00:00:00Z2012info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://repositorio.inesctec.pt/handle/123456789/2134engRicardo Jorge BessaJoão Peças LopesManuel MatosFilipe Joel Soaresinfo:eu-repo/semantics/embargoedAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-05-15T10:20:32Zoai:repositorio.inesctec.pt:123456789/2134Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:53:17.229227Repositório 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 Optimized Bidding of a EV Aggregation Agent in the Electricity Market
title Optimized Bidding of a EV Aggregation Agent in the Electricity Market
spellingShingle Optimized Bidding of a EV Aggregation Agent in the Electricity Market
Ricardo Jorge Bessa
title_short Optimized Bidding of a EV Aggregation Agent in the Electricity Market
title_full Optimized Bidding of a EV Aggregation Agent in the Electricity Market
title_fullStr Optimized Bidding of a EV Aggregation Agent in the Electricity Market
title_full_unstemmed Optimized Bidding of a EV Aggregation Agent in the Electricity Market
title_sort Optimized Bidding of a EV Aggregation Agent in the Electricity Market
author Ricardo Jorge Bessa
author_facet Ricardo Jorge Bessa
João Peças Lopes
Manuel Matos
Filipe Joel Soares
author_role author
author2 João Peças Lopes
Manuel Matos
Filipe Joel Soares
author2_role author
author
author
dc.contributor.author.fl_str_mv Ricardo Jorge Bessa
João Peças Lopes
Manuel Matos
Filipe Joel Soares
description An electric vehicle (EV) aggregation agent, as a commercial middleman between electricity market and EV owners, participates with bids for purchasing electrical energy and selling secondary reserve. This paper presents an optimization approach to support the aggregation agent participating in the day-ahead and secondary reserve sessions, and identifies the input variables that need to be forecasted or estimated. Results are presented for two years (2009 and 2010) of the Iberian market, and considering perfect and naïve forecast for all variables of the problem.
publishDate 2012
dc.date.none.fl_str_mv 2012-01-01T00:00:00Z
2012
2017-11-16T13:15:26Z
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dc.identifier.uri.fl_str_mv http://repositorio.inesctec.pt/handle/123456789/2134
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dc.language.iso.fl_str_mv eng
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