Efficient reallocation of BESS in monopolar DC networks for annual operating costs minimization: a combinatorial-convex approach

This article deals with the solution of a mixed-integer nonlinear programming (MINLP) problem related to the efficient reallocation of battery energy storage systems (BESS) in monopolar direct current (DC) grids through a master–slave optimization approach. The master stage solves the integer nature...

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Detalles Bibliográficos
Autores: Grisales-Noreña, Luis Fernando, Montoya, Oscar Danilo, Hernández
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2023
País:España
Institución:Universidad de Jaén
Repositorio:RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaén
OAI Identifier:oai:ruja.ujaen.es:10953/6582
Acceso en línea:https://www.mdpi.com/2313-0105/9/3/190
https://doi.org/10.3390/batteries9030190
https://hdl.handle.net/10953/6582
Access Level:acceso abierto
Palabra clave:expected annual energy loss costs
expected annual energy purchasing costs
battery energy storage systems
renewable energy resources
621.35
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spelling Efficient reallocation of BESS in monopolar DC networks for annual operating costs minimization: a combinatorial-convex approachGrisales-Noreña, Luis FernandoMontoya, Oscar DaniloHernándezexpected annual energy loss costsexpected annual energy purchasing costsbattery energy storage systemsrenewable energy resources621.35This article deals with the solution of a mixed-integer nonlinear programming (MINLP) problem related to the efficient reallocation of battery energy storage systems (BESS) in monopolar direct current (DC) grids through a master–slave optimization approach. The master stage solves the integer nature of the MINLP model, which is related to the nodes where the BESS will be located. In this stage, the discrete version of the vortex search algorithm is implemented. To determine the objective function value, a recursive convex approximation is implemented to solve the nonlinear component of the MINLP model (multi-period optimal power flow problem) in the slave stage. Two objective functions are considered performance indicators regarding the efficient reallocation of BESS in monopolar DC systems. The first objective function corresponds to the expected costs of the annual energy losses, and the second is associated with the annual expected energy generation costs. Numerical results for the DC version of the IEEE 33 bus grid confirm the effectiveness and robustness of the proposed master–slave optimization approach in comparison with the solution of the exact MINLP model in the General Algebraic Modeling System (GAMS) software. The proposed master–slave optimizer was programmed in the MATLAB software. The recursive convex solution of the multi-period optimal power flow problem was implemented in the convex discipline tool (CVX) with the SDPT3 and SEDUMI solvers. The numerical reductions achieved with respect to the benchmark case in terms of energy loss costs and energy purchasing costs were 7.2091% and 3.2105% , which surpassed the results reached by the GAMS software, with reductions of about 6.0316% and 1.5736% .MDPI202520252023info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://www.mdpi.com/2313-0105/9/3/190https://doi.org/10.3390/batteries9030190https://hdl.handle.net/10953/6582reponame:RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaéninstname:Universidad de JaénInglésBatteriesAttribution 3.0 Spainhttp://creativecommons.org/licenses/by/3.0/es/info:eu-repo/semantics/openAccessoai:ruja.ujaen.es:10953/65822026-06-24T12:41:07Z
dc.title.none.fl_str_mv Efficient reallocation of BESS in monopolar DC networks for annual operating costs minimization: a combinatorial-convex approach
title Efficient reallocation of BESS in monopolar DC networks for annual operating costs minimization: a combinatorial-convex approach
spellingShingle Efficient reallocation of BESS in monopolar DC networks for annual operating costs minimization: a combinatorial-convex approach
Grisales-Noreña, Luis Fernando
expected annual energy loss costs
expected annual energy purchasing costs
battery energy storage systems
renewable energy resources
621.35
title_short Efficient reallocation of BESS in monopolar DC networks for annual operating costs minimization: a combinatorial-convex approach
title_full Efficient reallocation of BESS in monopolar DC networks for annual operating costs minimization: a combinatorial-convex approach
title_fullStr Efficient reallocation of BESS in monopolar DC networks for annual operating costs minimization: a combinatorial-convex approach
title_full_unstemmed Efficient reallocation of BESS in monopolar DC networks for annual operating costs minimization: a combinatorial-convex approach
title_sort Efficient reallocation of BESS in monopolar DC networks for annual operating costs minimization: a combinatorial-convex approach
dc.creator.none.fl_str_mv Grisales-Noreña, Luis Fernando
Montoya, Oscar Danilo
Hernández
author Grisales-Noreña, Luis Fernando
author_facet Grisales-Noreña, Luis Fernando
Montoya, Oscar Danilo
Hernández
author_role author
author2 Montoya, Oscar Danilo
Hernández
author2_role author
author
dc.subject.none.fl_str_mv expected annual energy loss costs
expected annual energy purchasing costs
battery energy storage systems
renewable energy resources
621.35
topic expected annual energy loss costs
expected annual energy purchasing costs
battery energy storage systems
renewable energy resources
621.35
description This article deals with the solution of a mixed-integer nonlinear programming (MINLP) problem related to the efficient reallocation of battery energy storage systems (BESS) in monopolar direct current (DC) grids through a master–slave optimization approach. The master stage solves the integer nature of the MINLP model, which is related to the nodes where the BESS will be located. In this stage, the discrete version of the vortex search algorithm is implemented. To determine the objective function value, a recursive convex approximation is implemented to solve the nonlinear component of the MINLP model (multi-period optimal power flow problem) in the slave stage. Two objective functions are considered performance indicators regarding the efficient reallocation of BESS in monopolar DC systems. The first objective function corresponds to the expected costs of the annual energy losses, and the second is associated with the annual expected energy generation costs. Numerical results for the DC version of the IEEE 33 bus grid confirm the effectiveness and robustness of the proposed master–slave optimization approach in comparison with the solution of the exact MINLP model in the General Algebraic Modeling System (GAMS) software. The proposed master–slave optimizer was programmed in the MATLAB software. The recursive convex solution of the multi-period optimal power flow problem was implemented in the convex discipline tool (CVX) with the SDPT3 and SEDUMI solvers. The numerical reductions achieved with respect to the benchmark case in terms of energy loss costs and energy purchasing costs were 7.2091% and 3.2105% , which surpassed the results reached by the GAMS software, with reductions of about 6.0316% and 1.5736% .
publishDate 2023
dc.date.none.fl_str_mv 2023
2025
2025
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://www.mdpi.com/2313-0105/9/3/190
https://doi.org/10.3390/batteries9030190
https://hdl.handle.net/10953/6582
url https://www.mdpi.com/2313-0105/9/3/190
https://doi.org/10.3390/batteries9030190
https://hdl.handle.net/10953/6582
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Batteries
dc.rights.none.fl_str_mv Attribution 3.0 Spain
http://creativecommons.org/licenses/by/3.0/es/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Attribution 3.0 Spain
http://creativecommons.org/licenses/by/3.0/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv reponame:RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaén
instname:Universidad de Jaén
instname_str Universidad de Jaén
reponame_str RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaén
collection RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaén
repository.name.fl_str_mv
repository.mail.fl_str_mv
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