GA and PSO applied towind energy optimization
- Autores
- Alba, Enrique; Bilbao, Martín
- Año de publicación
- 2009
- Idioma
- inglés
- Tipo de recurso
- documento de conferencia
- Estado
- versión publicada
- Descripción
- In this article we analyze two kinds of metaheuristic algorithms applied to wind farm optimization. The basic idea is to utilize CHC (a sort of GA) and GPSO (a sort of PSO) algorithms to obtain an acceptable configuration of wind turbines in the wind farm that maximizes the total output energy and minimize the number of wind turbines used. The energy produced depends of the farm geometry, wind conditions and the terrain where it is settled. In this work we will analyze three study farm scenarios with different wind speeds and we will apply both algorithms to analyze the performance of the algorithms and the behavior of the computed wind farm designs.
Presentado en el X Workshop Agentes y Sistemas Inteligentes
Red de Universidades con Carreras en Informática (RedUNCI) - Materia
-
Ciencias Informáticas
CHC
geometric particle swarm optimization
Energía Eólica
Optimization
Heuristic methods - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
- Repositorio
.jpg)
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/20883
Ver los metadatos del registro completo
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GA and PSO applied towind energy optimizationAlba, EnriqueBilbao, MartínCiencias InformáticasCHCgeometric particle swarm optimizationEnergía EólicaOptimizationHeuristic methodsIn this article we analyze two kinds of metaheuristic algorithms applied to wind farm optimization. The basic idea is to utilize CHC (a sort of GA) and GPSO (a sort of PSO) algorithms to obtain an acceptable configuration of wind turbines in the wind farm that maximizes the total output energy and minimize the number of wind turbines used. The energy produced depends of the farm geometry, wind conditions and the terrain where it is settled. In this work we will analyze three study farm scenarios with different wind speeds and we will apply both algorithms to analyze the performance of the algorithms and the behavior of the computed wind farm designs.Presentado en el X Workshop Agentes y Sistemas InteligentesRed de Universidades con Carreras en Informática (RedUNCI)2009-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf50-59http://sedici.unlp.edu.ar/handle/10915/20883enginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/2.5/ar/Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T10:54:25Zoai:sedici.unlp.edu.ar:10915/20883Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 10:54:25.848SEDICI (UNLP) - Universidad Nacional de La Platafalse |
| dc.title.none.fl_str_mv |
GA and PSO applied towind energy optimization |
| title |
GA and PSO applied towind energy optimization |
| spellingShingle |
GA and PSO applied towind energy optimization Alba, Enrique Ciencias Informáticas CHC geometric particle swarm optimization Energía Eólica Optimization Heuristic methods |
| title_short |
GA and PSO applied towind energy optimization |
| title_full |
GA and PSO applied towind energy optimization |
| title_fullStr |
GA and PSO applied towind energy optimization |
| title_full_unstemmed |
GA and PSO applied towind energy optimization |
| title_sort |
GA and PSO applied towind energy optimization |
| dc.creator.none.fl_str_mv |
Alba, Enrique Bilbao, Martín |
| author |
Alba, Enrique |
| author_facet |
Alba, Enrique Bilbao, Martín |
| author_role |
author |
| author2 |
Bilbao, Martín |
| author2_role |
author |
| dc.subject.none.fl_str_mv |
Ciencias Informáticas CHC geometric particle swarm optimization Energía Eólica Optimization Heuristic methods |
| topic |
Ciencias Informáticas CHC geometric particle swarm optimization Energía Eólica Optimization Heuristic methods |
| dc.description.none.fl_txt_mv |
In this article we analyze two kinds of metaheuristic algorithms applied to wind farm optimization. The basic idea is to utilize CHC (a sort of GA) and GPSO (a sort of PSO) algorithms to obtain an acceptable configuration of wind turbines in the wind farm that maximizes the total output energy and minimize the number of wind turbines used. The energy produced depends of the farm geometry, wind conditions and the terrain where it is settled. In this work we will analyze three study farm scenarios with different wind speeds and we will apply both algorithms to analyze the performance of the algorithms and the behavior of the computed wind farm designs. Presentado en el X Workshop Agentes y Sistemas Inteligentes Red de Universidades con Carreras en Informática (RedUNCI) |
| description |
In this article we analyze two kinds of metaheuristic algorithms applied to wind farm optimization. The basic idea is to utilize CHC (a sort of GA) and GPSO (a sort of PSO) algorithms to obtain an acceptable configuration of wind turbines in the wind farm that maximizes the total output energy and minimize the number of wind turbines used. The energy produced depends of the farm geometry, wind conditions and the terrain where it is settled. In this work we will analyze three study farm scenarios with different wind speeds and we will apply both algorithms to analyze the performance of the algorithms and the behavior of the computed wind farm designs. |
| publishDate |
2009 |
| dc.date.none.fl_str_mv |
2009-10 |
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info:eu-repo/semantics/conferenceObject info:eu-repo/semantics/publishedVersion Objeto de conferencia http://purl.org/coar/resource_type/c_5794 info:ar-repo/semantics/documentoDeConferencia |
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http://sedici.unlp.edu.ar/handle/10915/20883 |
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http://sedici.unlp.edu.ar/handle/10915/20883 |
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eng |
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eng |
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info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-sa/2.5/ar/ Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5) |
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openAccess |
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