Optimal allocation of distributed generation for improving chargeability and voltage profile under different operative scenarios

ABSTRACT: This paper presents an application of a GRASP metaheuristic for the optimal allocation of distributed generation (DG) in electric power systems. Four indexes indicating the system performance in normal operation and under contingency were designed to guide the search. The proposed indexes...

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Autores:
Sánchez Mora, Martín Miguel
Tamayo, Carlos
López Lezama, Jesús María
Tipo de recurso:
Article of investigation
Fecha de publicación:
2018
Institución:
Universidad de Antioquia
Repositorio:
Repositorio UdeA
Idioma:
eng
OAI Identifier:
oai:bibliotecadigital.udea.edu.co:10495/22565
Acceso en línea:
http://hdl.handle.net/10495/22565
Palabra clave:
Sistemas de energía eléctrica
Electric power distribution
Distribución de energía eléctrica
Electric power distribution
Cargabilidad (electricidad)
Sistemas eléctricos de potencia
Sistemas de distribución
Rights
openAccess
License
http://creativecommons.org/licenses/by/2.5/co/
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dc.title.spa.fl_str_mv Optimal allocation of distributed generation for improving chargeability and voltage profile under different operative scenarios
title Optimal allocation of distributed generation for improving chargeability and voltage profile under different operative scenarios
spellingShingle Optimal allocation of distributed generation for improving chargeability and voltage profile under different operative scenarios
Sistemas de energía eléctrica
Electric power distribution
Distribución de energía eléctrica
Electric power distribution
Cargabilidad (electricidad)
Sistemas eléctricos de potencia
Sistemas de distribución
title_short Optimal allocation of distributed generation for improving chargeability and voltage profile under different operative scenarios
title_full Optimal allocation of distributed generation for improving chargeability and voltage profile under different operative scenarios
title_fullStr Optimal allocation of distributed generation for improving chargeability and voltage profile under different operative scenarios
title_full_unstemmed Optimal allocation of distributed generation for improving chargeability and voltage profile under different operative scenarios
title_sort Optimal allocation of distributed generation for improving chargeability and voltage profile under different operative scenarios
dc.creator.fl_str_mv Sánchez Mora, Martín Miguel
Tamayo, Carlos
López Lezama, Jesús María
dc.contributor.author.none.fl_str_mv Sánchez Mora, Martín Miguel
Tamayo, Carlos
López Lezama, Jesús María
dc.contributor.researchgroup.spa.fl_str_mv Grupo de Manejo Eficiente de la Energía (GIMEL)
dc.subject.lemb.none.fl_str_mv Sistemas de energía eléctrica
Electric power distribution
Distribución de energía eléctrica
Electric power distribution
topic Sistemas de energía eléctrica
Electric power distribution
Distribución de energía eléctrica
Electric power distribution
Cargabilidad (electricidad)
Sistemas eléctricos de potencia
Sistemas de distribución
dc.subject.proposal.spa.fl_str_mv Cargabilidad (electricidad)
Sistemas eléctricos de potencia
Sistemas de distribución
description ABSTRACT: This paper presents an application of a GRASP metaheuristic for the optimal allocation of distributed generation (DG) in electric power systems. Four indexes indicating the system performance in normal operation and under contingency were designed to guide the search. The proposed indexes indicate violations in chargeability and voltage limits for different operative scenarios. The objective function consists on minimizing the impacts of single contingencies in the chargeability and voltage profile of a network. To show the applicability and effectiveness of the proposed approach several tests were performed on the IEEE 30 and 57 bus tests systems. Results show that the proposed approach allows to find the allocation of DG that maximizes its positive impacts in terms of voltage profile and chargeability.
publishDate 2018
dc.date.issued.none.fl_str_mv 2018
dc.date.accessioned.none.fl_str_mv 2021-09-22T21:07:48Z
dc.date.available.none.fl_str_mv 2021-09-22T21:07:48Z
dc.type.spa.fl_str_mv Artículo de investigación
dc.type.coar.spa.fl_str_mv http://purl.org/coar/resource_type/c_2df8fbb1
dc.type.redcol.spa.fl_str_mv https://purl.org/redcol/resource_type/ART
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dc.identifier.issn.none.fl_str_mv 1313-6569
dc.identifier.uri.none.fl_str_mv http://hdl.handle.net/10495/22565
dc.identifier.doi.none.fl_str_mv 10.12988/ces.2018.85257
dc.identifier.eissn.none.fl_str_mv 1314-7641
identifier_str_mv 1313-6569
10.12988/ces.2018.85257
1314-7641
url http://hdl.handle.net/10495/22565
dc.language.iso.spa.fl_str_mv eng
language eng
dc.relation.ispartofjournalabbrev.spa.fl_str_mv Contemp. Eng. Sci.
dc.relation.citationendpage.spa.fl_str_mv 2511
dc.relation.citationissue.spa.fl_str_mv 51
dc.relation.citationstartpage.spa.fl_str_mv 2503
dc.relation.citationvolume.spa.fl_str_mv 11
dc.relation.ispartofjournal.spa.fl_str_mv Contemporary Engineering Sciences
dc.rights.uri.*.fl_str_mv http://creativecommons.org/licenses/by/2.5/co/
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dc.publisher.spa.fl_str_mv Hikari
dc.publisher.place.spa.fl_str_mv Ruse, Bulgaria
institution Universidad de Antioquia
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spelling Sánchez Mora, Martín MiguelTamayo, CarlosLópez Lezama, Jesús MaríaGrupo de Manejo Eficiente de la Energía (GIMEL)2021-09-22T21:07:48Z2021-09-22T21:07:48Z20181313-6569http://hdl.handle.net/10495/2256510.12988/ces.2018.852571314-7641ABSTRACT: This paper presents an application of a GRASP metaheuristic for the optimal allocation of distributed generation (DG) in electric power systems. Four indexes indicating the system performance in normal operation and under contingency were designed to guide the search. The proposed indexes indicate violations in chargeability and voltage limits for different operative scenarios. The objective function consists on minimizing the impacts of single contingencies in the chargeability and voltage profile of a network. To show the applicability and effectiveness of the proposed approach several tests were performed on the IEEE 30 and 57 bus tests systems. 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