Optimal Storage Technology Selection and Sizing for Providing Reserve to Power Systems with High Penetration of Wind Generation

Autores
Martinez, Maximiliano; Molina, Marcelo Gustavo; Mercado, Pedro Enrique
Año de publicación
2015
Idioma
español castellano
Tipo de recurso
artículo
Estado
versión publicada
Descripción
This paper proposes a methodology to determine both the technology of Energy Storage System (ESS) and its optimal sizing in order to provide secondary frequency control (SFC) to power systems with high penetration of wind generation. The objective is to determine the optimal investment in an ESS,considering the impact of the energy storage device on the costs of the electrical system and on the quality of frequency. The methodology allows calculating probabilistically the variable investment and operation costs of the ESS, considering the uncertainties associated with the stochastic behavior of the wind generation, conventional generation availability, network topology and the demand for energy. To this aim, a hybrid optimization using a meta-heuristic algorithm called Mean-Variance Mapping Optimization (MVMO) is utilized, whose control variable is the size vector (maximum power and energy capacity of the storage device), and an optimization model to compute the optimal power flow (OPF).
Fil: Martinez, Maximiliano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Energía Eléctrica. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Energía Eléctrica; Argentina
Fil: Molina, Marcelo Gustavo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Energía Eléctrica. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Energía Eléctrica; Argentina
Fil: Mercado, Pedro Enrique. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Energía Eléctrica. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Energía Eléctrica; Argentina
Materia
Energy Storage
Optimization
Power Quality
Wind Power Generation
Secondary Frequency Control
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/42178
Acceder
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repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Optimal Storage Technology Selection and Sizing for Providing Reserve to Power Systems with High Penetration of Wind GenerationMartinez, MaximilianoMolina, Marcelo GustavoMercado, Pedro EnriqueEnergy StorageOptimizationPower QualityWind Power GenerationSecondary Frequency Controlhttps://purl.org/becyt/ford/2.2https://purl.org/becyt/ford/2This paper proposes a methodology to determine both the technology of Energy Storage System (ESS) and its optimal sizing in order to provide secondary frequency control (SFC) to power systems with high penetration of wind generation. The objective is to determine the optimal investment in an ESS,considering the impact of the energy storage device on the costs of the electrical system and on the quality of frequency. The methodology allows calculating probabilistically the variable investment and operation costs of the ESS, considering the uncertainties associated with the stochastic behavior of the wind generation, conventional generation availability, network topology and the demand for energy. To this aim, a hybrid optimization using a meta-heuristic algorithm called Mean-Variance Mapping Optimization (MVMO) is utilized, whose control variable is the size vector (maximum power and energy capacity of the storage device), and an optimization model to compute the optimal power flow (OPF).Fil: Martinez, Maximiliano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Energía Eléctrica. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Energía Eléctrica; ArgentinaFil: Molina, Marcelo Gustavo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Energía Eléctrica. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Energía Eléctrica; ArgentinaFil: Mercado, Pedro Enrique. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Energía Eléctrica. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Energía Eléctrica; ArgentinaInstitute of Electrical and Electronics Engineers2015-12info: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/11336/42178Martinez, Maximiliano; Molina, Marcelo Gustavo; Mercado, Pedro Enrique; Optimal Storage Technology Selection and Sizing for Providing Reserve to Power Systems with High Penetration of Wind Generation; Institute of Electrical and Electronics Engineers; IEEE Latin America Transactions; 13; 9; 12-2015; 2983-29901548-0992CONICET DigitalCONICETspainfo:eu-repo/semantics/altIdentifier/doi/10.1109/TLA.2015.7350049info:eu-repo/semantics/altIdentifier/url/https://ieeexplore.ieee.org/document/7350049/info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:35:33Zoai:ri.conicet.gov.ar:11336/42178instacron: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 09:35:34.1CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Optimal Storage Technology Selection and Sizing for Providing Reserve to Power Systems with High Penetration of Wind Generation
title Optimal Storage Technology Selection and Sizing for Providing Reserve to Power Systems with High Penetration of Wind Generation
spellingShingle Optimal Storage Technology Selection and Sizing for Providing Reserve to Power Systems with High Penetration of Wind Generation
Martinez, Maximiliano
Energy Storage
Optimization
Power Quality
Wind Power Generation
Secondary Frequency Control
title_short Optimal Storage Technology Selection and Sizing for Providing Reserve to Power Systems with High Penetration of Wind Generation
title_full Optimal Storage Technology Selection and Sizing for Providing Reserve to Power Systems with High Penetration of Wind Generation
title_fullStr Optimal Storage Technology Selection and Sizing for Providing Reserve to Power Systems with High Penetration of Wind Generation
title_full_unstemmed Optimal Storage Technology Selection and Sizing for Providing Reserve to Power Systems with High Penetration of Wind Generation
title_sort Optimal Storage Technology Selection and Sizing for Providing Reserve to Power Systems with High Penetration of Wind Generation
dc.creator.none.fl_str_mv Martinez, Maximiliano
Molina, Marcelo Gustavo
Mercado, Pedro Enrique
author Martinez, Maximiliano
author_facet Martinez, Maximiliano
Molina, Marcelo Gustavo
Mercado, Pedro Enrique
author_role author
author2 Molina, Marcelo Gustavo
Mercado, Pedro Enrique
author2_role author
author
dc.subject.none.fl_str_mv Energy Storage
Optimization
Power Quality
Wind Power Generation
Secondary Frequency Control
topic Energy Storage
Optimization
Power Quality
Wind Power Generation
Secondary Frequency Control
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 proposes a methodology to determine both the technology of Energy Storage System (ESS) and its optimal sizing in order to provide secondary frequency control (SFC) to power systems with high penetration of wind generation. The objective is to determine the optimal investment in an ESS,considering the impact of the energy storage device on the costs of the electrical system and on the quality of frequency. The methodology allows calculating probabilistically the variable investment and operation costs of the ESS, considering the uncertainties associated with the stochastic behavior of the wind generation, conventional generation availability, network topology and the demand for energy. To this aim, a hybrid optimization using a meta-heuristic algorithm called Mean-Variance Mapping Optimization (MVMO) is utilized, whose control variable is the size vector (maximum power and energy capacity of the storage device), and an optimization model to compute the optimal power flow (OPF).
Fil: Martinez, Maximiliano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Energía Eléctrica. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Energía Eléctrica; Argentina
Fil: Molina, Marcelo Gustavo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Energía Eléctrica. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Energía Eléctrica; Argentina
Fil: Mercado, Pedro Enrique. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Energía Eléctrica. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Energía Eléctrica; Argentina
description This paper proposes a methodology to determine both the technology of Energy Storage System (ESS) and its optimal sizing in order to provide secondary frequency control (SFC) to power systems with high penetration of wind generation. The objective is to determine the optimal investment in an ESS,considering the impact of the energy storage device on the costs of the electrical system and on the quality of frequency. The methodology allows calculating probabilistically the variable investment and operation costs of the ESS, considering the uncertainties associated with the stochastic behavior of the wind generation, conventional generation availability, network topology and the demand for energy. To this aim, a hybrid optimization using a meta-heuristic algorithm called Mean-Variance Mapping Optimization (MVMO) is utilized, whose control variable is the size vector (maximum power and energy capacity of the storage device), and an optimization model to compute the optimal power flow (OPF).
publishDate 2015
dc.date.none.fl_str_mv 2015-12
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/11336/42178
Martinez, Maximiliano; Molina, Marcelo Gustavo; Mercado, Pedro Enrique; Optimal Storage Technology Selection and Sizing for Providing Reserve to Power Systems with High Penetration of Wind Generation; Institute of Electrical and Electronics Engineers; IEEE Latin America Transactions; 13; 9; 12-2015; 2983-2990
1548-0992
CONICET Digital
CONICET
url http://hdl.handle.net/11336/42178
identifier_str_mv Martinez, Maximiliano; Molina, Marcelo Gustavo; Mercado, Pedro Enrique; Optimal Storage Technology Selection and Sizing for Providing Reserve to Power Systems with High Penetration of Wind Generation; Institute of Electrical and Electronics Engineers; IEEE Latin America Transactions; 13; 9; 12-2015; 2983-2990
1548-0992
CONICET Digital
CONICET
dc.language.none.fl_str_mv spa
language spa
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1109/TLA.2015.7350049
info:eu-repo/semantics/altIdentifier/url/https://ieeexplore.ieee.org/document/7350049/
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers
publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers
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 13.070432

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