Recent trends of the most used metaheuristic techniques for distribution network reconfiguration
Distribution network reconfiguration (DNR) continues to be a good option to reduce technical losses in a distribution power grid. However, this non-linear combinatorial problem is not easy to assess by exact methods when solving for large distribution networks, which requires large computational tim...
- Autores:
-
Quintero Duran, Michell Josep
Candelo Becerra, John Edwin
Sousa Santos, Vladimir
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2017
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/2233
- Acceso en línea:
- https://hdl.handle.net/11323/2233
https://repositorio.cuc.edu.co/
- Palabra clave:
- Combinatorial problems
Distribution networks
Metaheuristics
Optimization
Reconfiguration
- Rights
- openAccess
- License
- Atribución – No comercial – Compartir igual
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| dc.title.spa.fl_str_mv |
Recent trends of the most used metaheuristic techniques for distribution network reconfiguration |
| title |
Recent trends of the most used metaheuristic techniques for distribution network reconfiguration |
| spellingShingle |
Recent trends of the most used metaheuristic techniques for distribution network reconfiguration Combinatorial problems Distribution networks Metaheuristics Optimization Reconfiguration |
| title_short |
Recent trends of the most used metaheuristic techniques for distribution network reconfiguration |
| title_full |
Recent trends of the most used metaheuristic techniques for distribution network reconfiguration |
| title_fullStr |
Recent trends of the most used metaheuristic techniques for distribution network reconfiguration |
| title_full_unstemmed |
Recent trends of the most used metaheuristic techniques for distribution network reconfiguration |
| title_sort |
Recent trends of the most used metaheuristic techniques for distribution network reconfiguration |
| dc.creator.fl_str_mv |
Quintero Duran, Michell Josep Candelo Becerra, John Edwin Sousa Santos, Vladimir |
| dc.contributor.author.spa.fl_str_mv |
Quintero Duran, Michell Josep Candelo Becerra, John Edwin Sousa Santos, Vladimir |
| dc.subject.spa.fl_str_mv |
Combinatorial problems Distribution networks Metaheuristics Optimization Reconfiguration |
| topic |
Combinatorial problems Distribution networks Metaheuristics Optimization Reconfiguration |
| description |
Distribution network reconfiguration (DNR) continues to be a good option to reduce technical losses in a distribution power grid. However, this non-linear combinatorial problem is not easy to assess by exact methods when solving for large distribution networks, which requires large computational times. For solving this type of problem, some researchers prefer to use metaheuristic techniques due to convergence speed, near-optimal solutions, and simple programming. Some literature reviews specialize in topics concerning the optimization of power network reconfiguration and try to cover most techniques. Nevertheless, this does not allow detailing properly the use of each technique, which is important to identify the trend. The contributions of this paper are three-fold. First, it presents the objective functions and constraints used in DNR with the most used metaheuristics. Second, it reviews the most important techniques such as particle swarm optimization (PSO), genetic algorithm (GA), simulated annealing (SA), ant colony optimization (ACO), immune algorithms (IA), and tabu search (TS). Finally, this paper presents the trend of each technique from 2011 to 2016. This paper will be useful for researchers interested in knowing the advances of recent approaches in these metaheuristics applied to DNR in order to continue developing new best algorithms and improving solutions for the topic |
| publishDate |
2017 |
| dc.date.issued.none.fl_str_mv |
2017-11-11 |
| dc.date.accessioned.none.fl_str_mv |
2019-01-25T13:32:01Z |
| dc.date.available.none.fl_str_mv |
2019-01-25T13:32:01Z |
| dc.type.spa.fl_str_mv |
Artículo de revista |
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http://purl.org/coar/resource_type/c_2df8fbb1 |
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http://purl.org/coar/resource_type/c_6501 |
| dc.type.content.spa.fl_str_mv |
Text |
| dc.type.driver.spa.fl_str_mv |
info:eu-repo/semantics/article |
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http://purl.org/redcol/resource_type/ART |
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info:eu-repo/semantics/acceptedVersion |
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http://purl.org/coar/resource_type/c_6501 |
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acceptedVersion |
| dc.identifier.issn.spa.fl_str_mv |
17919320 |
| dc.identifier.uri.spa.fl_str_mv |
https://hdl.handle.net/11323/2233 |
| dc.identifier.instname.spa.fl_str_mv |
Corporación Universidad de la Costa |
| dc.identifier.reponame.spa.fl_str_mv |
REDICUC - Repositorio CUC |
| dc.identifier.repourl.spa.fl_str_mv |
https://repositorio.cuc.edu.co/ |
| identifier_str_mv |
17919320 Corporación Universidad de la Costa REDICUC - Repositorio CUC |
| url |
https://hdl.handle.net/11323/2233 https://repositorio.cuc.edu.co/ |
| dc.language.iso.none.fl_str_mv |
eng |
| language |
eng |
| dc.relation.references.spa.fl_str_mv |
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Quintero Duran, Michell JosepCandelo Becerra, John EdwinSousa Santos, Vladimir2019-01-25T13:32:01Z2019-01-25T13:32:01Z2017-11-1117919320https://hdl.handle.net/11323/2233Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/Distribution network reconfiguration (DNR) continues to be a good option to reduce technical losses in a distribution power grid. However, this non-linear combinatorial problem is not easy to assess by exact methods when solving for large distribution networks, which requires large computational times. For solving this type of problem, some researchers prefer to use metaheuristic techniques due to convergence speed, near-optimal solutions, and simple programming. Some literature reviews specialize in topics concerning the optimization of power network reconfiguration and try to cover most techniques. Nevertheless, this does not allow detailing properly the use of each technique, which is important to identify the trend. The contributions of this paper are three-fold. First, it presents the objective functions and constraints used in DNR with the most used metaheuristics. Second, it reviews the most important techniques such as particle swarm optimization (PSO), genetic algorithm (GA), simulated annealing (SA), ant colony optimization (ACO), immune algorithms (IA), and tabu search (TS). Finally, this paper presents the trend of each technique from 2011 to 2016. This paper will be useful for researchers interested in knowing the advances of recent approaches in these metaheuristics applied to DNR in order to continue developing new best algorithms and improving solutions for the topicQuintero Duran, Michell Josep-97c79d40-a005-47ef-84cd-90d38ce9ce95-0Candelo Becerra, John Edwin-3016826a-740c-46a8-87b7-f9c358612fcb-0Sousa Santos, Vladimir-0000-0001-8808-1914-600engJOURNAL OF Engineering Science and Technology ReviewAtribución – No comercial – Compartir igualinfo:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Combinatorial problemsDistribution networksMetaheuristicsOptimizationReconfigurationRecent trends of the most used metaheuristic techniques for distribution network reconfigurationArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/acceptedVersion[1] Y. M. Atwa, E. F. 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