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...
- 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 |
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http://purl.org/coar/resource_type/c_2df8fbb1 |
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https://purl.org/redcol/resource_type/ART |
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http://purl.org/coar/version/c_970fb48d4fbd8a85 |
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info:eu-repo/semantics/article |
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info:eu-repo/semantics/publishedVersion |
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http://purl.org/coar/resource_type/c_2df8fbb1 |
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publishedVersion |
| 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 |
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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/ |
| dc.rights.uri.spa.fl_str_mv |
https://creativecommons.org/licenses/by/4.0/ |
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info:eu-repo/semantics/openAccess |
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http://purl.org/coar/access_right/c_abf2 |
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openAccess |
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application/pdf |
| dc.publisher.spa.fl_str_mv |
Hikari |
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Ruse, Bulgaria |
| institution |
Universidad de Antioquia |
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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. 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.COL00104779application/pdfengHikariRuse, Bulgariahttp://creativecommons.org/licenses/by/2.5/co/https://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Optimal allocation of distributed generation for improving chargeability and voltage profile under different operative scenariosArtículo de investigaciónhttp://purl.org/coar/resource_type/c_2df8fbb1https://purl.org/redcol/resource_type/ARThttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionSistemas de energía eléctricaElectric power distributionDistribución de energía eléctricaElectric power distributionCargabilidad (electricidad)Sistemas eléctricos de potenciaSistemas de distribuciónContemp. Eng. Sci.251151250311Contemporary Engineering SciencesPublicationCC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8927https://bibliotecadigital.udea.edu.co/bitstreams/31e99f47-1ec1-4dcd-af8e-0a5b85c760a2/download1646d1f6b96dbbbc38035efc9239ac9cMD52falseAnonymousREADLICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://bibliotecadigital.udea.edu.co/bitstreams/ccb19197-719f-4e20-aa1b-4ff886222d21/download8a4605be74aa9ea9d79846c1fba20a33MD53falseAnonymousREADORIGINALLopezJesus_2018_DistributedChargeabilityOperative.pdfLopezJesus_2018_DistributedChargeabilityOperative.pdfArtículo de investigaciónapplication/pdf677127https://bibliotecadigital.udea.edu.co/bitstreams/cfcdb154-b772-451c-b24f-995b33991632/download7bb19320bbd141b7a6a46751909c8042MD51trueAnonymousREADTEXTLopezJesus_2018_DistributedChargeabilityOperative.pdf.txtLopezJesus_2018_DistributedChargeabilityOperative.pdf.txtExtracted texttext/plain20487https://bibliotecadigital.udea.edu.co/bitstreams/8c7b91df-0a31-4f58-9e71-f0d597b0970e/download8df24022bf519a5f17d1ad0904a84f40MD54falseAnonymousREADTHUMBNAILLopezJesus_2018_DistributedChargeabilityOperative.pdf.jpgLopezJesus_2018_DistributedChargeabilityOperative.pdf.jpgGenerated Thumbnailimage/jpeg12925https://bibliotecadigital.udea.edu.co/bitstreams/32193718-8c31-4885-9680-0f44c2b58178/downloadf3d98124d7b8fa1154ae208f76861aeaMD55falseAnonymousREAD10495/22565oai:bibliotecadigital.udea.edu.co:10495/225652025-03-27 01:27:49.447http://creativecommons.org/licenses/by/2.5/co/open.accesshttps://bibliotecadigital.udea.edu.coRepositorio Institucional de la Universidad de Antioquiaaplicacionbibliotecadigitalbiblioteca@udea.edu.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 |
