Global against divided optimization for the participation of an EV aggregator in the day-ahead electricity market. Part II: Numerical analysis
Autor(a) principal: | |
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Data de Publicação: | 2013 |
Outros Autores: | |
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/123456789/4172 http://dx.doi.org/10.1016/j.epsr.2012.08.013 |
Resumo: | This paper presents numerical analysis of two alternative optimization approaches intended to support an EV aggregation agent in optimizing buying bids for the day-ahead electricity market. A study with market data from the Iberian electricity market is used for comparison and validation of the forecasting and optimization performance of the global and divided optimization approaches. The results show that evaluating the forecast quality separately from its impact in the optimization results is misleading, because a forecast with a low error might result in a higher cost than a forecast with higher error. Both bidding approaches were also compared with an inflexible EV load approach where the EV are not controlled by an aggregator and start charging when they plug-in. Results show that optimized bids allow a considerable cost reduction when compared to an inflexible load approach, and the computational performance of the algorithms satisfies the requirements for operational use by a future real EV aggregation agent. |
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Global against divided optimization for the participation of an EV aggregator in the day-ahead electricity market. Part II: Numerical analysisThis paper presents numerical analysis of two alternative optimization approaches intended to support an EV aggregation agent in optimizing buying bids for the day-ahead electricity market. A study with market data from the Iberian electricity market is used for comparison and validation of the forecasting and optimization performance of the global and divided optimization approaches. The results show that evaluating the forecast quality separately from its impact in the optimization results is misleading, because a forecast with a low error might result in a higher cost than a forecast with higher error. Both bidding approaches were also compared with an inflexible EV load approach where the EV are not controlled by an aggregator and start charging when they plug-in. Results show that optimized bids allow a considerable cost reduction when compared to an inflexible load approach, and the computational performance of the algorithms satisfies the requirements for operational use by a future real EV aggregation agent.2017-12-16T15:08:11Z2013-01-01T00:00:00Z2013info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://repositorio.inesctec.pt/handle/123456789/4172http://dx.doi.org/10.1016/j.epsr.2012.08.013engRicardo 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:RCAAP2023-05-15T10:20:47Zoai:repositorio.inesctec.pt:123456789/4172Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:53:38.021446Repositório 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 II: Numerical analysis |
title |
Global against divided optimization for the participation of an EV aggregator in the day-ahead electricity market. Part II: Numerical analysis |
spellingShingle |
Global against divided optimization for the participation of an EV aggregator in the day-ahead electricity market. Part II: Numerical analysis Ricardo Jorge Bessa |
title_short |
Global against divided optimization for the participation of an EV aggregator in the day-ahead electricity market. Part II: Numerical analysis |
title_full |
Global against divided optimization for the participation of an EV aggregator in the day-ahead electricity market. Part II: Numerical analysis |
title_fullStr |
Global against divided optimization for the participation of an EV aggregator in the day-ahead electricity market. Part II: Numerical analysis |
title_full_unstemmed |
Global against divided optimization for the participation of an EV aggregator in the day-ahead electricity market. Part II: Numerical analysis |
title_sort |
Global against divided optimization for the participation of an EV aggregator in the day-ahead electricity market. Part II: Numerical analysis |
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 presents numerical analysis of two alternative optimization approaches intended to support an EV aggregation agent in optimizing buying bids for the day-ahead electricity market. A study with market data from the Iberian electricity market is used for comparison and validation of the forecasting and optimization performance of the global and divided optimization approaches. The results show that evaluating the forecast quality separately from its impact in the optimization results is misleading, because a forecast with a low error might result in a higher cost than a forecast with higher error. Both bidding approaches were also compared with an inflexible EV load approach where the EV are not controlled by an aggregator and start charging when they plug-in. Results show that optimized bids allow a considerable cost reduction when compared to an inflexible load approach, and the computational performance of the algorithms satisfies the requirements for operational use by a future real EV aggregation agent. |
publishDate |
2013 |
dc.date.none.fl_str_mv |
2013-01-01T00:00:00Z 2013 2017-12-16T15:08:11Z |
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://repositorio.inesctec.pt/handle/123456789/4172 http://dx.doi.org/10.1016/j.epsr.2012.08.013 |
url |
http://repositorio.inesctec.pt/handle/123456789/4172 http://dx.doi.org/10.1016/j.epsr.2012.08.013 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
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.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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1799131610479591424 |