Energy management strategy based on receding horizon for a power hybrid system

Autores
Rullo, Pablo Gabriel; Zumoffen, David Alejandro Ramon; Feroldi, Diego Hernán
Año de publicación
2014
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
This paper presents an energy management strategy to operate a hybrid power system with renewable sources (wind and solar), batteries, and polymeric electrolyte membrane fuel cells. The fuel cells are fed with hydrogen from bioethanol reforming. The energy management strategy uses the concept of receding horizon with predictions of the future generation from the renewable sources, the future load, and the state of charge in the battery bank. Several tests are done in order to analyze the performance of the proposed methodology. The results, compared with the case without predictions, show a reduction in the loss of power supply probability (LPSP) up to 88%.
Fil: Rullo, Pablo Gabriel. Universidad Nacional de Rosario. Facultad de Cs.exactas Ingenieria y Agrimensura. Escuela de Cs.exactas y Naturales. Departamento de Ciencias de la Computacion; Argentina
Fil: Zumoffen, David Alejandro Ramon. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y Sistemas; Argentina
Fil: Feroldi, Diego Hernán. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y Sistemas; Argentina
Materia
Renewable Energy Sources
Bioethanol
Wind Energy
Solar Energy
Pem Fuel Cells
Autoregressive Models
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:11336/4801
Acceder
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network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Energy management strategy based on receding horizon for a power hybrid systemRullo, Pablo GabrielZumoffen, David Alejandro RamonFeroldi, Diego HernánRenewable Energy SourcesBioethanolWind EnergySolar EnergyPem Fuel CellsAutoregressive Modelshttps://purl.org/becyt/ford/2.2https://purl.org/becyt/ford/2This paper presents an energy management strategy to operate a hybrid power system with renewable sources (wind and solar), batteries, and polymeric electrolyte membrane fuel cells. The fuel cells are fed with hydrogen from bioethanol reforming. The energy management strategy uses the concept of receding horizon with predictions of the future generation from the renewable sources, the future load, and the state of charge in the battery bank. Several tests are done in order to analyze the performance of the proposed methodology. The results, compared with the case without predictions, show a reduction in the loss of power supply probability (LPSP) up to 88%.Fil: Rullo, Pablo Gabriel. Universidad Nacional de Rosario. Facultad de Cs.exactas Ingenieria y Agrimensura. Escuela de Cs.exactas y Naturales. Departamento de Ciencias de la Computacion; ArgentinaFil: Zumoffen, David Alejandro Ramon. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y Sistemas; ArgentinaFil: Feroldi, Diego Hernán. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y Sistemas; ArgentinaElsevier2014-11info: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/11336/4801Rullo, Pablo Gabriel; Zumoffen, David Alejandro Ramon; Feroldi, Diego Hernán; Energy management strategy based on receding horizon for a power hybrid system; Elsevier; Renewable Energy; 75; 11-2014; 550-5590960-1481enginfo:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0960148114006211info:eu-repo/semantics/altIdentifier/doi/10.1016/j.renene.2014.09.056info:eu-repo/semantics/altIdentifier/issn/0960-1481info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-22T11:34:18Zoai:ri.conicet.gov.ar:11336/4801instacron: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:34982025-10-22 11:34:18.303CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Energy management strategy based on receding horizon for a power hybrid system
title Energy management strategy based on receding horizon for a power hybrid system
spellingShingle Energy management strategy based on receding horizon for a power hybrid system
Rullo, Pablo Gabriel
Renewable Energy Sources
Bioethanol
Wind Energy
Solar Energy
Pem Fuel Cells
Autoregressive Models
title_short Energy management strategy based on receding horizon for a power hybrid system
title_full Energy management strategy based on receding horizon for a power hybrid system
title_fullStr Energy management strategy based on receding horizon for a power hybrid system
title_full_unstemmed Energy management strategy based on receding horizon for a power hybrid system
title_sort Energy management strategy based on receding horizon for a power hybrid system
dc.creator.none.fl_str_mv Rullo, Pablo Gabriel
Zumoffen, David Alejandro Ramon
Feroldi, Diego Hernán
author Rullo, Pablo Gabriel
author_facet Rullo, Pablo Gabriel
Zumoffen, David Alejandro Ramon
Feroldi, Diego Hernán
author_role author
author2 Zumoffen, David Alejandro Ramon
Feroldi, Diego Hernán
author2_role author
author
dc.subject.none.fl_str_mv Renewable Energy Sources
Bioethanol
Wind Energy
Solar Energy
Pem Fuel Cells
Autoregressive Models
topic Renewable Energy Sources
Bioethanol
Wind Energy
Solar Energy
Pem Fuel Cells
Autoregressive Models
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.2
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv This paper presents an energy management strategy to operate a hybrid power system with renewable sources (wind and solar), batteries, and polymeric electrolyte membrane fuel cells. The fuel cells are fed with hydrogen from bioethanol reforming. The energy management strategy uses the concept of receding horizon with predictions of the future generation from the renewable sources, the future load, and the state of charge in the battery bank. Several tests are done in order to analyze the performance of the proposed methodology. The results, compared with the case without predictions, show a reduction in the loss of power supply probability (LPSP) up to 88%.
Fil: Rullo, Pablo Gabriel. Universidad Nacional de Rosario. Facultad de Cs.exactas Ingenieria y Agrimensura. Escuela de Cs.exactas y Naturales. Departamento de Ciencias de la Computacion; Argentina
Fil: Zumoffen, David Alejandro Ramon. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y Sistemas; Argentina
Fil: Feroldi, Diego Hernán. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y Sistemas; Argentina
description This paper presents an energy management strategy to operate a hybrid power system with renewable sources (wind and solar), batteries, and polymeric electrolyte membrane fuel cells. The fuel cells are fed with hydrogen from bioethanol reforming. The energy management strategy uses the concept of receding horizon with predictions of the future generation from the renewable sources, the future load, and the state of charge in the battery bank. Several tests are done in order to analyze the performance of the proposed methodology. The results, compared with the case without predictions, show a reduction in the loss of power supply probability (LPSP) up to 88%.
publishDate 2014
dc.date.none.fl_str_mv 2014-11
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/11336/4801
Rullo, Pablo Gabriel; Zumoffen, David Alejandro Ramon; Feroldi, Diego Hernán; Energy management strategy based on receding horizon for a power hybrid system; Elsevier; Renewable Energy; 75; 11-2014; 550-559
0960-1481
url http://hdl.handle.net/11336/4801
identifier_str_mv Rullo, Pablo Gabriel; Zumoffen, David Alejandro Ramon; Feroldi, Diego Hernán; Energy management strategy based on receding horizon for a power hybrid system; Elsevier; Renewable Energy; 75; 11-2014; 550-559
0960-1481
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0960148114006211
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.renene.2014.09.056
info:eu-repo/semantics/altIdentifier/issn/0960-1481
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
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score 12.982451

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