Optimizing Daily Operation of Battery Energy Storage Systems Under Real-Time Pricing Schemes
Autor(a) principal: | |
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Data de Publicação: | 2017 |
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/123456789/4808 http://dx.doi.org/10.1109/tsg.2016.2602268 |
Resumo: | Modernization of electricity networks is currently being carried out using the concept of the smart grid; hence, the active participation of end-user consumers and distributed generators will be allowed in order to increase system efficiency and renewable power accommodation. In this context, this paper proposes a comprehensive methodology to optimally control lead-acid batteries operating under dynamic pricing schemes in both independent and aggregated ways, taking into account the effects of the charge controller operation, the variable efficiency of the power converter, and the maximum capacity of the electricity network. A genetic algorithm is used to solve the optimization problem in which the daily net cost is minimized. The effectiveness and computational efficiency of the proposed methodology is illustrated using real data from the Spanish electricity market during 2014 and 2015 in order to evaluate the effects of forecasting error of energy prices, observing an important reduction in the estimated benefit as a result of both factors: 1) forecasting error and 2) power system limitations. |
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Optimizing Daily Operation of Battery Energy Storage Systems Under Real-Time Pricing SchemesModernization of electricity networks is currently being carried out using the concept of the smart grid; hence, the active participation of end-user consumers and distributed generators will be allowed in order to increase system efficiency and renewable power accommodation. In this context, this paper proposes a comprehensive methodology to optimally control lead-acid batteries operating under dynamic pricing schemes in both independent and aggregated ways, taking into account the effects of the charge controller operation, the variable efficiency of the power converter, and the maximum capacity of the electricity network. A genetic algorithm is used to solve the optimization problem in which the daily net cost is minimized. The effectiveness and computational efficiency of the proposed methodology is illustrated using real data from the Spanish electricity market during 2014 and 2015 in order to evaluate the effects of forecasting error of energy prices, observing an important reduction in the estimated benefit as a result of both factors: 1) forecasting error and 2) power system limitations.2017-12-22T17:58:27Z2017-01-01T00:00:00Z2017info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://repositorio.inesctec.pt/handle/123456789/4808http://dx.doi.org/10.1109/tsg.2016.2602268engLujano Rojas,JMDufo Lopez,RBernal Agustin,JLJoão Catalãoinfo: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:RCAAP2023-05-15T10:19:42Zoai:repositorio.inesctec.pt:123456789/4808Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:52:06.853617Repositório 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 |
Optimizing Daily Operation of Battery Energy Storage Systems Under Real-Time Pricing Schemes |
title |
Optimizing Daily Operation of Battery Energy Storage Systems Under Real-Time Pricing Schemes |
spellingShingle |
Optimizing Daily Operation of Battery Energy Storage Systems Under Real-Time Pricing Schemes Lujano Rojas,JM |
title_short |
Optimizing Daily Operation of Battery Energy Storage Systems Under Real-Time Pricing Schemes |
title_full |
Optimizing Daily Operation of Battery Energy Storage Systems Under Real-Time Pricing Schemes |
title_fullStr |
Optimizing Daily Operation of Battery Energy Storage Systems Under Real-Time Pricing Schemes |
title_full_unstemmed |
Optimizing Daily Operation of Battery Energy Storage Systems Under Real-Time Pricing Schemes |
title_sort |
Optimizing Daily Operation of Battery Energy Storage Systems Under Real-Time Pricing Schemes |
author |
Lujano Rojas,JM |
author_facet |
Lujano Rojas,JM Dufo Lopez,R Bernal Agustin,JL João Catalão |
author_role |
author |
author2 |
Dufo Lopez,R Bernal Agustin,JL João Catalão |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Lujano Rojas,JM Dufo Lopez,R Bernal Agustin,JL João Catalão |
description |
Modernization of electricity networks is currently being carried out using the concept of the smart grid; hence, the active participation of end-user consumers and distributed generators will be allowed in order to increase system efficiency and renewable power accommodation. In this context, this paper proposes a comprehensive methodology to optimally control lead-acid batteries operating under dynamic pricing schemes in both independent and aggregated ways, taking into account the effects of the charge controller operation, the variable efficiency of the power converter, and the maximum capacity of the electricity network. A genetic algorithm is used to solve the optimization problem in which the daily net cost is minimized. The effectiveness and computational efficiency of the proposed methodology is illustrated using real data from the Spanish electricity market during 2014 and 2015 in order to evaluate the effects of forecasting error of energy prices, observing an important reduction in the estimated benefit as a result of both factors: 1) forecasting error and 2) power system limitations. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-12-22T17:58:27Z 2017-01-01T00:00:00Z 2017 |
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/123456789/4808 http://dx.doi.org/10.1109/tsg.2016.2602268 |
url |
http://repositorio.inesctec.pt/handle/123456789/4808 http://dx.doi.org/10.1109/tsg.2016.2602268 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/embargoedAccess |
eu_rights_str_mv |
embargoedAccess |
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 |
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1799131597888290816 |