Large-scale optimization of households with photovoltaic-battery system and demand response

Detalhes bibliográficos
Autor(a) principal: Lezama, Fernando
Data de Publicação: 2020
Outros Autores: Faia, Ricardo, Abrishambaf, Omid, Faria, Pedro, Vale, Zita
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.22/18407
Resumo: The adoption of distributed resources by households, e.g., storage units and renewables, open the possibility of self-consumption (on-site generation), sell energy to the grid as a small producer, or do both according to the context of operation. In this paper, a framework capturing the interactions between an aggregator and a large number of households is envisaged. We consider households equipped with distributed resources and simple smart technologies that look for the reduction of energy bills and can perform demand response actions. A mixed-integer linear programming formulation that provides optimal scheduling of household devices and minimal operation costs is developed. Results show that the model can be applied considering up to 10000 households. Moreover, households can reduce up to 20% of their energy bill on average using storage units and demand response. Besides, the aggregator can attain profits by offering the resulting flexibility to upper-level players of the energy chain, such as the distribution system operator.
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spelling Large-scale optimization of households with photovoltaic-battery system and demand responseEnergy storageEnergy management systemsLinear programmingOptimizationRenewable energy systemsThe adoption of distributed resources by households, e.g., storage units and renewables, open the possibility of self-consumption (on-site generation), sell energy to the grid as a small producer, or do both according to the context of operation. In this paper, a framework capturing the interactions between an aggregator and a large number of households is envisaged. We consider households equipped with distributed resources and simple smart technologies that look for the reduction of energy bills and can perform demand response actions. A mixed-integer linear programming formulation that provides optimal scheduling of household devices and minimal operation costs is developed. Results show that the model can be applied considering up to 10000 households. Moreover, households can reduce up to 20% of their energy bill on average using storage units and demand response. Besides, the aggregator can attain profits by offering the resulting flexibility to upper-level players of the energy chain, such as the distribution system operator.This work has received funding from FEDER Funds through COMPETE program and from National Funds through (FCT) under the projects UID/EEA/00760/2019 and COLORS PTDC/EEI-EEE/28967/2017, and grants CEECIND/02887/2017 and SFRH/BD/133086/2017.ElsevierRepositório Científico do Instituto Politécnico do PortoLezama, FernandoFaia, RicardoAbrishambaf, OmidFaria, PedroVale, Zita2021-09-17T13:10:12Z20202020-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.22/18407eng10.1016/j.ifacol.2020.12.1818info: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:RCAAP2023-03-13T13:09:42Zoai:recipp.ipp.pt:10400.22/18407Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:37:52.056607Repositório 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 Large-scale optimization of households with photovoltaic-battery system and demand response
title Large-scale optimization of households with photovoltaic-battery system and demand response
spellingShingle Large-scale optimization of households with photovoltaic-battery system and demand response
Lezama, Fernando
Energy storage
Energy management systems
Linear programming
Optimization
Renewable energy systems
title_short Large-scale optimization of households with photovoltaic-battery system and demand response
title_full Large-scale optimization of households with photovoltaic-battery system and demand response
title_fullStr Large-scale optimization of households with photovoltaic-battery system and demand response
title_full_unstemmed Large-scale optimization of households with photovoltaic-battery system and demand response
title_sort Large-scale optimization of households with photovoltaic-battery system and demand response
author Lezama, Fernando
author_facet Lezama, Fernando
Faia, Ricardo
Abrishambaf, Omid
Faria, Pedro
Vale, Zita
author_role author
author2 Faia, Ricardo
Abrishambaf, Omid
Faria, Pedro
Vale, Zita
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Repositório Científico do Instituto Politécnico do Porto
dc.contributor.author.fl_str_mv Lezama, Fernando
Faia, Ricardo
Abrishambaf, Omid
Faria, Pedro
Vale, Zita
dc.subject.por.fl_str_mv Energy storage
Energy management systems
Linear programming
Optimization
Renewable energy systems
topic Energy storage
Energy management systems
Linear programming
Optimization
Renewable energy systems
description The adoption of distributed resources by households, e.g., storage units and renewables, open the possibility of self-consumption (on-site generation), sell energy to the grid as a small producer, or do both according to the context of operation. In this paper, a framework capturing the interactions between an aggregator and a large number of households is envisaged. We consider households equipped with distributed resources and simple smart technologies that look for the reduction of energy bills and can perform demand response actions. A mixed-integer linear programming formulation that provides optimal scheduling of household devices and minimal operation costs is developed. Results show that the model can be applied considering up to 10000 households. Moreover, households can reduce up to 20% of their energy bill on average using storage units and demand response. Besides, the aggregator can attain profits by offering the resulting flexibility to upper-level players of the energy chain, such as the distribution system operator.
publishDate 2020
dc.date.none.fl_str_mv 2020
2020-01-01T00:00:00Z
2021-09-17T13:10:12Z
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/10400.22/18407
url http://hdl.handle.net/10400.22/18407
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1016/j.ifacol.2020.12.1818
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.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
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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