Improved time representation model for the simultaneous energy supply and demand management in microgrids

Autores
Silvente, Javier; Aguirre, Adrian Marcelo; Zamarripa, Miguel A.; Mendez, Carlos Alberto; Graells, Moisés; Espuña, Antonio
Año de publicación
2015
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
This paper analyses the operational decision making procedures required to address the simultaneous management of energy supplies and requests in a microgrid scenario, in order to best accommodate arbitrary energy availability profiles resulting from an intensive use of renewable energy sources, and to extensively exploit the eventual flexibility of the energy requirements to be fulfilled. The optimization of the resulting short term scheduling problem in deterministic scenarios is addressed through a MILP (Mixed-Integer Linear Programming) mathematical model, which includes a new hybrid time formulation developed to take profit of the advantages of the procedures based on discrete time representations, while maintaining the ability to identify solutions requiring a continuous time representation, which might be qualitatively different to the ones constrained to consider a fixed time grid for decision-making. The performance of this new time representation has been studied, taking into account the granularity of the model and analyzing the associated trade-offs in front of other alternatives. The promising results obtained with this new formulation encourage further research regarding the development of decision-making tools for the enhanced operation of microgrids.
Fil: Silvente, Javier. Universidad Politécnica de Catalunya; España
Fil: Aguirre, Adrian Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química (i); Argentina
Fil: Zamarripa, Miguel A.. Universidad Politécnica de Catalunya; España
Fil: Mendez, Carlos Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química (i); Argentina
Fil: Graells, Moisés. Universidad Politécnica de Catalunya; España
Fil: Espuña, Antonio. Universidad Politécnica de Catalunya; España
Materia
Microgrid
Management
Energy Storage
Scheduling
Milp
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/9904
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/9904
network_acronym_str CONICETDig
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network_name_str CONICET Digital (CONICET)
spelling Improved time representation model for the simultaneous energy supply and demand management in microgridsSilvente, JavierAguirre, Adrian MarceloZamarripa, Miguel A.Mendez, Carlos AlbertoGraells, MoisésEspuña, AntonioMicrogridManagementEnergy StorageSchedulingMilphttps://purl.org/becyt/ford/2.4https://purl.org/becyt/ford/2This paper analyses the operational decision making procedures required to address the simultaneous management of energy supplies and requests in a microgrid scenario, in order to best accommodate arbitrary energy availability profiles resulting from an intensive use of renewable energy sources, and to extensively exploit the eventual flexibility of the energy requirements to be fulfilled. The optimization of the resulting short term scheduling problem in deterministic scenarios is addressed through a MILP (Mixed-Integer Linear Programming) mathematical model, which includes a new hybrid time formulation developed to take profit of the advantages of the procedures based on discrete time representations, while maintaining the ability to identify solutions requiring a continuous time representation, which might be qualitatively different to the ones constrained to consider a fixed time grid for decision-making. The performance of this new time representation has been studied, taking into account the granularity of the model and analyzing the associated trade-offs in front of other alternatives. The promising results obtained with this new formulation encourage further research regarding the development of decision-making tools for the enhanced operation of microgrids.Fil: Silvente, Javier. Universidad Politécnica de Catalunya; EspañaFil: Aguirre, Adrian Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química (i); ArgentinaFil: Zamarripa, Miguel A.. Universidad Politécnica de Catalunya; EspañaFil: Mendez, Carlos Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química (i); ArgentinaFil: Graells, Moisés. Universidad Politécnica de Catalunya; EspañaFil: Espuña, Antonio. Universidad Politécnica de Catalunya; EspañaElsevier2015-08info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/9904Silvente, Javier; Aguirre, Adrian Marcelo; Zamarripa, Miguel A.; Mendez, Carlos Alberto; Graells, Moisés; et al.; Improved time representation model for the simultaneous energy supply and demand management in microgrids; Elsevier; Energy; 87; 8-2015; 615-6270360-5442enginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.energy.2015.05.028info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S036054421500609Xinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:54:31Zoai:ri.conicet.gov.ar:11336/9904instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 09:54:32.06CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Improved time representation model for the simultaneous energy supply and demand management in microgrids
title Improved time representation model for the simultaneous energy supply and demand management in microgrids
spellingShingle Improved time representation model for the simultaneous energy supply and demand management in microgrids
Silvente, Javier
Microgrid
Management
Energy Storage
Scheduling
Milp
title_short Improved time representation model for the simultaneous energy supply and demand management in microgrids
title_full Improved time representation model for the simultaneous energy supply and demand management in microgrids
title_fullStr Improved time representation model for the simultaneous energy supply and demand management in microgrids
title_full_unstemmed Improved time representation model for the simultaneous energy supply and demand management in microgrids
title_sort Improved time representation model for the simultaneous energy supply and demand management in microgrids
dc.creator.none.fl_str_mv Silvente, Javier
Aguirre, Adrian Marcelo
Zamarripa, Miguel A.
Mendez, Carlos Alberto
Graells, Moisés
Espuña, Antonio
author Silvente, Javier
author_facet Silvente, Javier
Aguirre, Adrian Marcelo
Zamarripa, Miguel A.
Mendez, Carlos Alberto
Graells, Moisés
Espuña, Antonio
author_role author
author2 Aguirre, Adrian Marcelo
Zamarripa, Miguel A.
Mendez, Carlos Alberto
Graells, Moisés
Espuña, Antonio
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Microgrid
Management
Energy Storage
Scheduling
Milp
topic Microgrid
Management
Energy Storage
Scheduling
Milp
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.4
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv This paper analyses the operational decision making procedures required to address the simultaneous management of energy supplies and requests in a microgrid scenario, in order to best accommodate arbitrary energy availability profiles resulting from an intensive use of renewable energy sources, and to extensively exploit the eventual flexibility of the energy requirements to be fulfilled. The optimization of the resulting short term scheduling problem in deterministic scenarios is addressed through a MILP (Mixed-Integer Linear Programming) mathematical model, which includes a new hybrid time formulation developed to take profit of the advantages of the procedures based on discrete time representations, while maintaining the ability to identify solutions requiring a continuous time representation, which might be qualitatively different to the ones constrained to consider a fixed time grid for decision-making. The performance of this new time representation has been studied, taking into account the granularity of the model and analyzing the associated trade-offs in front of other alternatives. The promising results obtained with this new formulation encourage further research regarding the development of decision-making tools for the enhanced operation of microgrids.
Fil: Silvente, Javier. Universidad Politécnica de Catalunya; España
Fil: Aguirre, Adrian Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química (i); Argentina
Fil: Zamarripa, Miguel A.. Universidad Politécnica de Catalunya; España
Fil: Mendez, Carlos Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química (i); Argentina
Fil: Graells, Moisés. Universidad Politécnica de Catalunya; España
Fil: Espuña, Antonio. Universidad Politécnica de Catalunya; España
description This paper analyses the operational decision making procedures required to address the simultaneous management of energy supplies and requests in a microgrid scenario, in order to best accommodate arbitrary energy availability profiles resulting from an intensive use of renewable energy sources, and to extensively exploit the eventual flexibility of the energy requirements to be fulfilled. The optimization of the resulting short term scheduling problem in deterministic scenarios is addressed through a MILP (Mixed-Integer Linear Programming) mathematical model, which includes a new hybrid time formulation developed to take profit of the advantages of the procedures based on discrete time representations, while maintaining the ability to identify solutions requiring a continuous time representation, which might be qualitatively different to the ones constrained to consider a fixed time grid for decision-making. The performance of this new time representation has been studied, taking into account the granularity of the model and analyzing the associated trade-offs in front of other alternatives. The promising results obtained with this new formulation encourage further research regarding the development of decision-making tools for the enhanced operation of microgrids.
publishDate 2015
dc.date.none.fl_str_mv 2015-08
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/9904
Silvente, Javier; Aguirre, Adrian Marcelo; Zamarripa, Miguel A.; Mendez, Carlos Alberto; Graells, Moisés; et al.; Improved time representation model for the simultaneous energy supply and demand management in microgrids; Elsevier; Energy; 87; 8-2015; 615-627
0360-5442
url http://hdl.handle.net/11336/9904
identifier_str_mv Silvente, Javier; Aguirre, Adrian Marcelo; Zamarripa, Miguel A.; Mendez, Carlos Alberto; Graells, Moisés; et al.; Improved time representation model for the simultaneous energy supply and demand management in microgrids; Elsevier; Energy; 87; 8-2015; 615-627
0360-5442
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1016/j.energy.2015.05.028
info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S036054421500609X
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
_version_ 1844613656015273984
score 13.070432

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