Particle Swarm Optimization method for estimation of Weibull parameters: a case study for the Brazilian northeast region

Detalhes bibliográficos
Autor(a) principal: Carneiro, Tatiane Carolyne
Data de Publicação: 2015
Outros Autores: Melo, Sofia Pinheiro, Carvalho, Paulo Cesar Marques de, Braga, Arthur Plínio de Souza
Tipo de documento: Artigo
Idioma: por
Título da fonte: Repositório Institucional da Universidade Federal do Ceará (UFC)
Texto Completo: http://dx.doi.org/10.1016/j.renene.2015.08.060
http://www.repositorio.ufc.br/handle/riufc/64581
Resumo: In this paper the application of the Particle Swarm Optimization (PSO) method to estimate the Weibull parameters for wind resources in the Brazilian Northeast Region (BRNER) is reported. For the present research, wind speed data from three 80 m towers installed at different sites in the region were collected. The measuring periods for each tower site are: February 2012 to January 2013 for Maracanaú, August 2012 to July 2013 for Parnaíba, and May 2012 to March 2013 for Petrolina. Aiming to compare with the PSO performance, five numerical methods are applied to calculate the Weibull distribution parameters. Best performance for all analyzed sites is achieved by the PSO method, with a correlation higher than 99% and an error close to zero. PSO proves to be a valuable technique for characterization of the particular wind conditions found in the BRNER.
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spelling Particle Swarm Optimization method for estimation of Weibull parameters: a case study for the Brazilian northeast regionParticle Swarm Optimization method for estimation of Weibull parameters: a case study for the Brazilian northeast regionParticle swarm optimizationWeibull distributionWind resourceNumerical methodsIn this paper the application of the Particle Swarm Optimization (PSO) method to estimate the Weibull parameters for wind resources in the Brazilian Northeast Region (BRNER) is reported. For the present research, wind speed data from three 80 m towers installed at different sites in the region were collected. The measuring periods for each tower site are: February 2012 to January 2013 for Maracanaú, August 2012 to July 2013 for Parnaíba, and May 2012 to March 2013 for Petrolina. Aiming to compare with the PSO performance, five numerical methods are applied to calculate the Weibull distribution parameters. Best performance for all analyzed sites is achieved by the PSO method, with a correlation higher than 99% and an error close to zero. PSO proves to be a valuable technique for characterization of the particular wind conditions found in the BRNER.Elsevier Ltd. - https://reader.elsevier.com/2022-03-24T12:21:43Z2022-03-24T12:21:43Z2015info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfCARNEIRO, Tatiane Carolyne; MELO, Sofia Pinheiro; CARVALHO, Paulo Cesar Marques de; BRAGA, Arthur Plínio de Souza. Particle swarm optimization method for estimation of weibull parameters: a case study for the Brazilian northeast region. v. 86, p. 751-759, 2016. http://dx.doi.org/10.1016/j.renene.2015.08.060.0960-1481http://dx.doi.org/10.1016/j.renene.2015.08.060http://www.repositorio.ufc.br/handle/riufc/64581Carneiro, Tatiane CarolyneMelo, Sofia PinheiroCarvalho, Paulo Cesar Marques deBraga, Arthur Plínio de Souzainfo:eu-repo/semantics/openAccessporreponame:Repositório Institucional da Universidade Federal do Ceará (UFC)instname:Universidade Federal do Ceará (UFC)instacron:UFC2023-12-06T17:10:37Zoai:repositorio.ufc.br:riufc/64581Repositório InstitucionalPUBhttp://www.repositorio.ufc.br/ri-oai/requestbu@ufc.br || repositorio@ufc.bropendoar:2024-09-11T18:35:47.817517Repositório Institucional da Universidade Federal do Ceará (UFC) - Universidade Federal do Ceará (UFC)false
dc.title.none.fl_str_mv Particle Swarm Optimization method for estimation of Weibull parameters: a case study for the Brazilian northeast region
Particle Swarm Optimization method for estimation of Weibull parameters: a case study for the Brazilian northeast region
title Particle Swarm Optimization method for estimation of Weibull parameters: a case study for the Brazilian northeast region
spellingShingle Particle Swarm Optimization method for estimation of Weibull parameters: a case study for the Brazilian northeast region
Carneiro, Tatiane Carolyne
Particle swarm optimization
Weibull distribution
Wind resource
Numerical methods
title_short Particle Swarm Optimization method for estimation of Weibull parameters: a case study for the Brazilian northeast region
title_full Particle Swarm Optimization method for estimation of Weibull parameters: a case study for the Brazilian northeast region
title_fullStr Particle Swarm Optimization method for estimation of Weibull parameters: a case study for the Brazilian northeast region
title_full_unstemmed Particle Swarm Optimization method for estimation of Weibull parameters: a case study for the Brazilian northeast region
title_sort Particle Swarm Optimization method for estimation of Weibull parameters: a case study for the Brazilian northeast region
author Carneiro, Tatiane Carolyne
author_facet Carneiro, Tatiane Carolyne
Melo, Sofia Pinheiro
Carvalho, Paulo Cesar Marques de
Braga, Arthur Plínio de Souza
author_role author
author2 Melo, Sofia Pinheiro
Carvalho, Paulo Cesar Marques de
Braga, Arthur Plínio de Souza
author2_role author
author
author
dc.contributor.author.fl_str_mv Carneiro, Tatiane Carolyne
Melo, Sofia Pinheiro
Carvalho, Paulo Cesar Marques de
Braga, Arthur Plínio de Souza
dc.subject.por.fl_str_mv Particle swarm optimization
Weibull distribution
Wind resource
Numerical methods
topic Particle swarm optimization
Weibull distribution
Wind resource
Numerical methods
description In this paper the application of the Particle Swarm Optimization (PSO) method to estimate the Weibull parameters for wind resources in the Brazilian Northeast Region (BRNER) is reported. For the present research, wind speed data from three 80 m towers installed at different sites in the region were collected. The measuring periods for each tower site are: February 2012 to January 2013 for Maracanaú, August 2012 to July 2013 for Parnaíba, and May 2012 to March 2013 for Petrolina. Aiming to compare with the PSO performance, five numerical methods are applied to calculate the Weibull distribution parameters. Best performance for all analyzed sites is achieved by the PSO method, with a correlation higher than 99% and an error close to zero. PSO proves to be a valuable technique for characterization of the particular wind conditions found in the BRNER.
publishDate 2015
dc.date.none.fl_str_mv 2015
2022-03-24T12:21:43Z
2022-03-24T12:21:43Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv CARNEIRO, Tatiane Carolyne; MELO, Sofia Pinheiro; CARVALHO, Paulo Cesar Marques de; BRAGA, Arthur Plínio de Souza. Particle swarm optimization method for estimation of weibull parameters: a case study for the Brazilian northeast region. v. 86, p. 751-759, 2016. http://dx.doi.org/10.1016/j.renene.2015.08.060.
0960-1481
http://dx.doi.org/10.1016/j.renene.2015.08.060
http://www.repositorio.ufc.br/handle/riufc/64581
identifier_str_mv CARNEIRO, Tatiane Carolyne; MELO, Sofia Pinheiro; CARVALHO, Paulo Cesar Marques de; BRAGA, Arthur Plínio de Souza. Particle swarm optimization method for estimation of weibull parameters: a case study for the Brazilian northeast region. v. 86, p. 751-759, 2016. http://dx.doi.org/10.1016/j.renene.2015.08.060.
0960-1481
url http://dx.doi.org/10.1016/j.renene.2015.08.060
http://www.repositorio.ufc.br/handle/riufc/64581
dc.language.iso.fl_str_mv por
language por
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier Ltd. - https://reader.elsevier.com/
publisher.none.fl_str_mv Elsevier Ltd. - https://reader.elsevier.com/
dc.source.none.fl_str_mv reponame:Repositório Institucional da Universidade Federal do Ceará (UFC)
instname:Universidade Federal do Ceará (UFC)
instacron:UFC
instname_str Universidade Federal do Ceará (UFC)
instacron_str UFC
institution UFC
reponame_str Repositório Institucional da Universidade Federal do Ceará (UFC)
collection Repositório Institucional da Universidade Federal do Ceará (UFC)
repository.name.fl_str_mv Repositório Institucional da Universidade Federal do Ceará (UFC) - Universidade Federal do Ceará (UFC)
repository.mail.fl_str_mv bu@ufc.br || repositorio@ufc.br
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