Particle Swarm Optimization method for estimation of Weibull parameters: a case study for the Brazilian northeast region
Autor(a) principal: | |
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Data de Publicação: | 2015 |
Outros Autores: | , , |
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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Repositório Institucional da Universidade Federal do Ceará (UFC) |
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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 |
_version_ |
1813028869653921792 |