Multicore Parallelization of CHC for Optimal Aerogenerator Placement in Wind Farms
- Autores
- Bilbao, Martín; Leguizamón, Guillermo
- Año de publicación
- 2019
- Idioma
- español castellano
- Tipo de recurso
- documento de conferencia
- Estado
- versión publicada
- Descripción
- In this paper, we study a parallelization of CHC algorithm (Crossover elitism population, Half uniform crossover combination, Cataclysm mutation) to solve the problem of placement of wind turbines in a wind farm. We also analyze the solutions obtained when we use both, the sequential and parallel version for the CHC algorithm. In this case we study the behavior of parallel metaheuristics using an island model to distribute the algorithm in different cores and compare this proposal with the sequential version to analyse the number of evaluation to find the best configuration, output power extracted, plant coefficient, evaluations needed, memory consumption, and execution time for different number of core and different problem sizes.
XX Workshop Agentes y Sistemas Inteligentes.
Red de Universidades con Carreras en Informática - Materia
-
Ciencias Informáticas
Wind Energy
Weibull Distribution
Wind Power
Evolutionary Computation
Metaheuristics - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc-sa/4.0/
- Repositorio
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/90896
Ver los metadatos del registro completo
id |
SEDICI_631d436e120d66ed7c94d9c35a7c8871 |
---|---|
oai_identifier_str |
oai:sedici.unlp.edu.ar:10915/90896 |
network_acronym_str |
SEDICI |
repository_id_str |
1329 |
network_name_str |
SEDICI (UNLP) |
spelling |
Multicore Parallelization of CHC for Optimal Aerogenerator Placement in Wind FarmsBilbao, MartínLeguizamón, GuillermoCiencias InformáticasWind EnergyWeibull DistributionWind PowerEvolutionary ComputationMetaheuristicsIn this paper, we study a parallelization of CHC algorithm (Crossover elitism population, Half uniform crossover combination, Cataclysm mutation) to solve the problem of placement of wind turbines in a wind farm. We also analyze the solutions obtained when we use both, the sequential and parallel version for the CHC algorithm. In this case we study the behavior of parallel metaheuristics using an island model to distribute the algorithm in different cores and compare this proposal with the sequential version to analyse the number of evaluation to find the best configuration, output power extracted, plant coefficient, evaluations needed, memory consumption, and execution time for different number of core and different problem sizes.XX Workshop Agentes y Sistemas Inteligentes.Red de Universidades con Carreras en Informática2019-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf85-94http://sedici.unlp.edu.ar/handle/10915/90896spainfo:eu-repo/semantics/altIdentifier/isbn/978-987-688-377-1info:eu-repo/semantics/reference/hdl/10915/90359info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:19:03Zoai:sedici.unlp.edu.ar:10915/90896Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:19:03.327SEDICI (UNLP) - Universidad Nacional de La Platafalse |
dc.title.none.fl_str_mv |
Multicore Parallelization of CHC for Optimal Aerogenerator Placement in Wind Farms |
title |
Multicore Parallelization of CHC for Optimal Aerogenerator Placement in Wind Farms |
spellingShingle |
Multicore Parallelization of CHC for Optimal Aerogenerator Placement in Wind Farms Bilbao, Martín Ciencias Informáticas Wind Energy Weibull Distribution Wind Power Evolutionary Computation Metaheuristics |
title_short |
Multicore Parallelization of CHC for Optimal Aerogenerator Placement in Wind Farms |
title_full |
Multicore Parallelization of CHC for Optimal Aerogenerator Placement in Wind Farms |
title_fullStr |
Multicore Parallelization of CHC for Optimal Aerogenerator Placement in Wind Farms |
title_full_unstemmed |
Multicore Parallelization of CHC for Optimal Aerogenerator Placement in Wind Farms |
title_sort |
Multicore Parallelization of CHC for Optimal Aerogenerator Placement in Wind Farms |
dc.creator.none.fl_str_mv |
Bilbao, Martín Leguizamón, Guillermo |
author |
Bilbao, Martín |
author_facet |
Bilbao, Martín Leguizamón, Guillermo |
author_role |
author |
author2 |
Leguizamón, Guillermo |
author2_role |
author |
dc.subject.none.fl_str_mv |
Ciencias Informáticas Wind Energy Weibull Distribution Wind Power Evolutionary Computation Metaheuristics |
topic |
Ciencias Informáticas Wind Energy Weibull Distribution Wind Power Evolutionary Computation Metaheuristics |
dc.description.none.fl_txt_mv |
In this paper, we study a parallelization of CHC algorithm (Crossover elitism population, Half uniform crossover combination, Cataclysm mutation) to solve the problem of placement of wind turbines in a wind farm. We also analyze the solutions obtained when we use both, the sequential and parallel version for the CHC algorithm. In this case we study the behavior of parallel metaheuristics using an island model to distribute the algorithm in different cores and compare this proposal with the sequential version to analyse the number of evaluation to find the best configuration, output power extracted, plant coefficient, evaluations needed, memory consumption, and execution time for different number of core and different problem sizes. XX Workshop Agentes y Sistemas Inteligentes. Red de Universidades con Carreras en Informática |
description |
In this paper, we study a parallelization of CHC algorithm (Crossover elitism population, Half uniform crossover combination, Cataclysm mutation) to solve the problem of placement of wind turbines in a wind farm. We also analyze the solutions obtained when we use both, the sequential and parallel version for the CHC algorithm. In this case we study the behavior of parallel metaheuristics using an island model to distribute the algorithm in different cores and compare this proposal with the sequential version to analyse the number of evaluation to find the best configuration, output power extracted, plant coefficient, evaluations needed, memory consumption, and execution time for different number of core and different problem sizes. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-10 |
dc.type.none.fl_str_mv |
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 |
format |
conferenceObject |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
http://sedici.unlp.edu.ar/handle/10915/90896 |
url |
http://sedici.unlp.edu.ar/handle/10915/90896 |
dc.language.none.fl_str_mv |
spa |
language |
spa |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/isbn/978-987-688-377-1 info:eu-repo/semantics/reference/hdl/10915/90359 |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
dc.format.none.fl_str_mv |
application/pdf 85-94 |
dc.source.none.fl_str_mv |
reponame:SEDICI (UNLP) instname:Universidad Nacional de La Plata instacron:UNLP |
reponame_str |
SEDICI (UNLP) |
collection |
SEDICI (UNLP) |
instname_str |
Universidad Nacional de La Plata |
instacron_str |
UNLP |
institution |
UNLP |
repository.name.fl_str_mv |
SEDICI (UNLP) - Universidad Nacional de La Plata |
repository.mail.fl_str_mv |
alira@sedici.unlp.edu.ar |
_version_ |
1844616064293404672 |
score |
13.070432 |