Global against divided optimization for the participation of an EV aggregator in the day-ahead electricity market. Part I: Theory

Detalhes bibliográficos
Autor(a) principal: Ricardo Jorge Bessa
Data de Publicação: 2013
Outros Autores: Manuel Matos
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/123456789/4170
http://dx.doi.org/10.1016/j.epsr.2012.08.007
Resumo: This paper addresses the bidding problem faced by an electric vehicles (EV) aggregation agent when participating in the day-ahead electrical energy market. Two alternative optimization approaches, global and divided, with the same goal (i.e. solve the same problem) are described. The difference is on how information about EV is modeled. The global approach uses aggregated values of the EV variables and the optimization model determines the bids exclusively based on total values. The divided approach uses individual information from each EV. In both approaches, statistical forecasting methods are formulated for the EV variables. After the day-ahead bidding, a second phase (named operational management) is required for mitigating the deviation between accepted bids and consumed electrical energy for EV charging. A sequential linear optimization problem is formulated for minimizing the deviation costs. This chain of algorithms provides to the EV aggregation agent a pathway to move to the smart-grid paradigm where load dispatch is a possibility.
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spelling Global against divided optimization for the participation of an EV aggregator in the day-ahead electricity market. Part I: TheoryThis paper addresses the bidding problem faced by an electric vehicles (EV) aggregation agent when participating in the day-ahead electrical energy market. Two alternative optimization approaches, global and divided, with the same goal (i.e. solve the same problem) are described. The difference is on how information about EV is modeled. The global approach uses aggregated values of the EV variables and the optimization model determines the bids exclusively based on total values. The divided approach uses individual information from each EV. In both approaches, statistical forecasting methods are formulated for the EV variables. After the day-ahead bidding, a second phase (named operational management) is required for mitigating the deviation between accepted bids and consumed electrical energy for EV charging. A sequential linear optimization problem is formulated for minimizing the deviation costs. This chain of algorithms provides to the EV aggregation agent a pathway to move to the smart-grid paradigm where load dispatch is a possibility.2017-12-16T15:08:02Z2013-01-01T00:00:00Z2013info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://repositorio.inesctec.pt/handle/123456789/4170http://dx.doi.org/10.1016/j.epsr.2012.08.007engRicardo Jorge BessaManuel Matosinfo: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:RCAAP2023-05-15T10:19:57Zoai:repositorio.inesctec.pt:123456789/4170Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:52:28.961289Repositório 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 Global against divided optimization for the participation of an EV aggregator in the day-ahead electricity market. Part I: Theory
title Global against divided optimization for the participation of an EV aggregator in the day-ahead electricity market. Part I: Theory
spellingShingle Global against divided optimization for the participation of an EV aggregator in the day-ahead electricity market. Part I: Theory
Ricardo Jorge Bessa
title_short Global against divided optimization for the participation of an EV aggregator in the day-ahead electricity market. Part I: Theory
title_full Global against divided optimization for the participation of an EV aggregator in the day-ahead electricity market. Part I: Theory
title_fullStr Global against divided optimization for the participation of an EV aggregator in the day-ahead electricity market. Part I: Theory
title_full_unstemmed Global against divided optimization for the participation of an EV aggregator in the day-ahead electricity market. Part I: Theory
title_sort Global against divided optimization for the participation of an EV aggregator in the day-ahead electricity market. Part I: Theory
author Ricardo Jorge Bessa
author_facet Ricardo Jorge Bessa
Manuel Matos
author_role author
author2 Manuel Matos
author2_role author
dc.contributor.author.fl_str_mv Ricardo Jorge Bessa
Manuel Matos
description This paper addresses the bidding problem faced by an electric vehicles (EV) aggregation agent when participating in the day-ahead electrical energy market. Two alternative optimization approaches, global and divided, with the same goal (i.e. solve the same problem) are described. The difference is on how information about EV is modeled. The global approach uses aggregated values of the EV variables and the optimization model determines the bids exclusively based on total values. The divided approach uses individual information from each EV. In both approaches, statistical forecasting methods are formulated for the EV variables. After the day-ahead bidding, a second phase (named operational management) is required for mitigating the deviation between accepted bids and consumed electrical energy for EV charging. A sequential linear optimization problem is formulated for minimizing the deviation costs. This chain of algorithms provides to the EV aggregation agent a pathway to move to the smart-grid paradigm where load dispatch is a possibility.
publishDate 2013
dc.date.none.fl_str_mv 2013-01-01T00:00:00Z
2013
2017-12-16T15:08:02Z
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http://dx.doi.org/10.1016/j.epsr.2012.08.007
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http://dx.doi.org/10.1016/j.epsr.2012.08.007
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