A mixed-integer convex model for the optimal placement and sizing of distributed generators in power distribution networks

The optimal placement and sizing of distributed generators is a classical problem in power distribution networks that is usually solved using heuristic algorithms due to its high complexity. This paper proposes a different approach based on a mixed-integer second-order cone programming (MI-SOCP) mod...

Descripción completa

Detalles Bibliográficos
Autores: Gil-González,, Walter, Garces, Alejandro, Montoya, Oscar Danilo, Hernández, Jesus C.
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2021
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:10953/6630
Acceso en línea:https://www.mdpi.com/2076-3417/11/2/627
https://doi.org/10.3390/app11020627
https://hdl.handle.net/10953/6630
Access Level:acceso abierto
Palabra clave:distributed generators
convex optimization
second-order cone programming
branch & bound method
integer optimization
power losses minimization
621.35
id ES_e99b2ccc08cb6bb9c9dfe047a54863d5
oai_identifier_str oai:ruja.ujaen.es:10953/6630
network_acronym_str ES
network_name_str España
repository_id_str
spelling A mixed-integer convex model for the optimal placement and sizing of distributed generators in power distribution networksGil-González,, WalterGarces, AlejandroMontoya, Oscar DaniloHernández, Jesus C.distributed generatorsconvex optimizationsecond-order cone programmingbranch & bound methodinteger optimizationpower losses minimization621.35The optimal placement and sizing of distributed generators is a classical problem in power distribution networks that is usually solved using heuristic algorithms due to its high complexity. This paper proposes a different approach based on a mixed-integer second-order cone programming (MI-SOCP) model that ensures the global optimum of the relaxed optimization model. Second-order cone programming (SOCP) has demonstrated to be an efficient alternative to cope with the non-convexity of the power flow equations in power distribution networks. Of relatively new interest to the power systems community is the extension to MI-SOCP models. The proposed model is an approximation. However, numerical validations in the IEEE 33-bus and IEEE 69-bus test systems for unity and variable power factor confirm that the proposed MI-SOCP finds the best solutions reported in the literature. Being an exact technique, the proposed model allows minimum processing times and zero standard deviation, i.e., the same optimum is guaranteed at each time that the MI-SOCP model is solved (a significant advantage in comparison to metaheuristics). Additionally, load and photovoltaic generation curves for the IEEE 69-node test system are included to demonstrate the applicability of the proposed MI-SOCP to solve the problem of the optimal location and sizing of renewable generators using the multi-period optimal power flow formulation. Therefore, the proposed MI-SOCP also guarantees the global optimum finding, in contrast to local solutions achieved with mixed-integer nonlinear programming solvers available in the GAMS optimization software. All the simulations were carried out via MATLAB software with the CVX package and Gurobi solver.MDPI202520252021info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://www.mdpi.com/2076-3417/11/2/627https://doi.org/10.3390/app11020627https://hdl.handle.net/10953/6630reponame:RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaéninstname:Universidad de JaénInglésApplied Sciences-BaselAttribution 3.0 Spainhttp://creativecommons.org/licenses/by/3.0/es/info:eu-repo/semantics/openAccessoai:ruja.ujaen.es:10953/66302026-06-24T12:41:07Z
dc.title.none.fl_str_mv A mixed-integer convex model for the optimal placement and sizing of distributed generators in power distribution networks
title A mixed-integer convex model for the optimal placement and sizing of distributed generators in power distribution networks
spellingShingle A mixed-integer convex model for the optimal placement and sizing of distributed generators in power distribution networks
Gil-González,, Walter
distributed generators
convex optimization
second-order cone programming
branch & bound method
integer optimization
power losses minimization
621.35
title_short A mixed-integer convex model for the optimal placement and sizing of distributed generators in power distribution networks
title_full A mixed-integer convex model for the optimal placement and sizing of distributed generators in power distribution networks
title_fullStr A mixed-integer convex model for the optimal placement and sizing of distributed generators in power distribution networks
title_full_unstemmed A mixed-integer convex model for the optimal placement and sizing of distributed generators in power distribution networks
title_sort A mixed-integer convex model for the optimal placement and sizing of distributed generators in power distribution networks
dc.creator.none.fl_str_mv Gil-González,, Walter
Garces, Alejandro
Montoya, Oscar Danilo
Hernández, Jesus C.
author Gil-González,, Walter
author_facet Gil-González,, Walter
Garces, Alejandro
Montoya, Oscar Danilo
Hernández, Jesus C.
author_role author
author2 Garces, Alejandro
Montoya, Oscar Danilo
Hernández, Jesus C.
author2_role author
author
author
dc.subject.none.fl_str_mv distributed generators
convex optimization
second-order cone programming
branch & bound method
integer optimization
power losses minimization
621.35
topic distributed generators
convex optimization
second-order cone programming
branch & bound method
integer optimization
power losses minimization
621.35
description The optimal placement and sizing of distributed generators is a classical problem in power distribution networks that is usually solved using heuristic algorithms due to its high complexity. This paper proposes a different approach based on a mixed-integer second-order cone programming (MI-SOCP) model that ensures the global optimum of the relaxed optimization model. Second-order cone programming (SOCP) has demonstrated to be an efficient alternative to cope with the non-convexity of the power flow equations in power distribution networks. Of relatively new interest to the power systems community is the extension to MI-SOCP models. The proposed model is an approximation. However, numerical validations in the IEEE 33-bus and IEEE 69-bus test systems for unity and variable power factor confirm that the proposed MI-SOCP finds the best solutions reported in the literature. Being an exact technique, the proposed model allows minimum processing times and zero standard deviation, i.e., the same optimum is guaranteed at each time that the MI-SOCP model is solved (a significant advantage in comparison to metaheuristics). Additionally, load and photovoltaic generation curves for the IEEE 69-node test system are included to demonstrate the applicability of the proposed MI-SOCP to solve the problem of the optimal location and sizing of renewable generators using the multi-period optimal power flow formulation. Therefore, the proposed MI-SOCP also guarantees the global optimum finding, in contrast to local solutions achieved with mixed-integer nonlinear programming solvers available in the GAMS optimization software. All the simulations were carried out via MATLAB software with the CVX package and Gurobi solver.
publishDate 2021
dc.date.none.fl_str_mv 2021
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/2076-3417/11/2/627
https://doi.org/10.3390/app11020627
https://hdl.handle.net/10953/6630
url https://www.mdpi.com/2076-3417/11/2/627
https://doi.org/10.3390/app11020627
https://hdl.handle.net/10953/6630
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Applied Sciences-Basel
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
_version_ 1869423066242613248
score 15,811543

Similares en LA Referencia