Characterization of Potential Wind Generation EolioelÃtrica For Purposes: A Case Study For Maracanaà (CE), ParnaÃba (PI) and Petrolina (PE)
Autor(a) principal: | |
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Data de Publicação: | 2014 |
Tipo de documento: | Dissertação |
Idioma: | por |
Título da fonte: | Biblioteca Digital de Teses e Dissertações da UFC |
Texto Completo: | http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=12256 |
Resumo: | In recent years wind energy is becoming increasingly competitive on the world stage, making their participation in the electricity generation matrix presents a strong growth expectation. This dissertation initially presents an analysis of the behavior of wind at three locations in Northeast Brazil (Maracanau-CE, Petrolina-PE e Parnaiba-PI). In a second step, statistical analyzes are researched to the most appropriate behavior patterns of the observed wind resource in the three localities. In conclusion, the impact of the statistical analyzes used in the production of electricity from wind turbines is identified. In this study,historicaldata of speed and direction of wind collectedare used, during periods of: February 2012 to January 2013, to Maracanau; August 2012 to July 2013, for Parnaiba; and May 2012 to March 2013, for Petrolina. The Weibull distribution is applied to approximate the histograms of wind speed using different horizons of applications (annual, semiannual) and four different numerical methods (Empirical, Momentum, Energy Pattern Factor and Equivalent Energy) for estimation of the form and scale parameters. In addition to evaluating the application of Weibull, other frequency distributions (Normal, Gamma and Log-Normal)are analyzed, in order to obtain the best possible fit. In a last step, with the aid of RETScreen program,annual production of electricity, delivered to the grid from wind turbines,is calculated. The optimum wind speed occurred in Parnaiba (10 and 11 m / s), followed by Petrolina (8 and 9 m / s). Among all different numerical methods that was evaluated, the Equivalent Energy method presented the best performance, unlike the Energy Pattern Factor method, that presented the worst. The Weibull distribution showed good potential for setting wind data in Maracanau and Parnaiba, both located along the coastline. However, based on the wind data recorded, in Petrolina, which is located further inland, the performance was inferior. Among all the different frequency distributions that were verified, only normal distribution had an fit as good as Weibull distribution. Based on the annual electricity production estimation, Parnaiba is the city that has the best potential for energy production. |
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info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisCharacterization of Potential Wind Generation EolioelÃtrica For Purposes: A Case Study For Maracanaà (CE), ParnaÃba (PI) and Petrolina (PE)CaracterizaÃÃo de potencial eÃlico para fins de geraÃÃo eolioelÃtrica: estudo de caso para Maracanaà (CE), ParnaÃba (PI) e Petrolina (PE)2014-07-28Paulo CÃsar Marques de Carvalho00000000117http://lattes.cnpq.br/0935409654079900Arthur PlÃnio de Souza Braga42395194387http://lattes.cnpq.br/1473823107869382 Demercil de Souza Oliveira JÃnior18710730818http://lattes.cnpq.br/8797685933461323 07303414452Tatiane Carolyne CarneiroUniversidade Federal do CearÃPrograma de PÃs-GraduaÃÃo em Engenharia ElÃtricaUFCBRDistribuiÃÃo de Weibull AnÃlise de sÃries temporaisWeibull distribution Wind speed Time series analysisENGENHARIA ELETRICAIn recent years wind energy is becoming increasingly competitive on the world stage, making their participation in the electricity generation matrix presents a strong growth expectation. This dissertation initially presents an analysis of the behavior of wind at three locations in Northeast Brazil (Maracanau-CE, Petrolina-PE e Parnaiba-PI). In a second step, statistical analyzes are researched to the most appropriate behavior patterns of the observed wind resource in the three localities. In conclusion, the impact of the statistical analyzes used in the production of electricity from wind turbines is identified. In this study,historicaldata of speed and direction of wind collectedare used, during periods of: February 2012 to January 2013, to Maracanau; August 2012 to July 2013, for Parnaiba; and May 2012 to March 2013, for Petrolina. The Weibull distribution is applied to approximate the histograms of wind speed using different horizons of applications (annual, semiannual) and four different numerical methods (Empirical, Momentum, Energy Pattern Factor and Equivalent Energy) for estimation of the form and scale parameters. In addition to evaluating the application of Weibull, other frequency distributions (Normal, Gamma and Log-Normal)are analyzed, in order to obtain the best possible fit. In a last step, with the aid of RETScreen program,annual production of electricity, delivered to the grid from wind turbines,is calculated. The optimum wind speed occurred in Parnaiba (10 and 11 m / s), followed by Petrolina (8 and 9 m / s). Among all different numerical methods that was evaluated, the Equivalent Energy method presented the best performance, unlike the Energy Pattern Factor method, that presented the worst. The Weibull distribution showed good potential for setting wind data in Maracanau and Parnaiba, both located along the coastline. However, based on the wind data recorded, in Petrolina, which is located further inland, the performance was inferior. Among all the different frequency distributions that were verified, only normal distribution had an fit as good as Weibull distribution. Based on the annual electricity production estimation, Parnaiba is the city that has the best potential for energy production.Nos Ãltimos anos a energia eÃlica tem se tornando cada vez mais competitiva no cenÃrio mundial, fazendo com que sua participaÃÃo na matriz elÃtrica apresente uma forte expectativa de crescimento. A presente dissertaÃÃo apresenta inicialmente uma anÃlise do comportamento do vento em trÃs localidades no Nordeste do Brasil (Maracanaà (CE), Petrolina (PE) e ParnaÃba (PI)); numa segunda etapa, sÃo pesquisadas anÃlises estatÃsticas mais adequadas aos padrÃes de comportamento do recurso eÃlico observado nas trÃs localidades e, concluindo, à identificado o impacto das anÃlises estatÃsticas utilizadas na produÃÃo de eletricidade de aerogeradores. Neste estudo sÃo utilizados dados histÃricos de velocidade e direÃÃo do vento coletados durante os perÃodos de: fevereiro de 2012 - janeiro de 2013 para MaracanaÃ, Agosto de 2012 - Julho de 2013 para ParnaÃba, maio de 2012 - marÃo 2013 para Petrolina. A distribuiÃÃo de frequÃncia de Weibull à aplicada para aproximar os histogramas de velocidade do vento, utilizando diferentes horizontes de aplicaÃÃes (anual, semestral) e quatro diferentes mÃtodos numÃricos (EmpÃrico, Momento, Fator PadrÃo de Energia e Energia Equivalente) para a estimaÃÃo dos parÃmetros de forma e escala. AlÃm de avaliar a aplicaÃÃo de Weibull, sÃo analisadas outras distribuiÃÃes de frequÃncia (Normal, Gama e Log-Normal) objetivando obter o melhor ajuste possÃvel. Numa Ãltima etapa, com o auxÃlio do programa RETScreen,à calculada a produÃÃo de eletricidade anual entregue à rede a partir de aerogeradores. Os melhores valores de velocidade do vento ocorreram em ParnaÃba (10 e 11 m/s), seguido de Petrolina (8 e 9 m/s). Dos diferentes mÃtodos numÃricos avaliados, o mÃtodo de energia equivalente apresentou o melhor desempenho e o mÃtodo fator de padrÃo de energia foi o mÃtodo com o pior desempenho. A distribuiÃÃo de Weibull demonstrou bom potencial para o ajuste de dados de vento em Maracanaà e ParnaÃba, ambas localizadas ao longo do litoral. No entanto, em Petrolina, que està situada mais para o interior, foi verificado um desempenho limitado a partir dos dados de vento registrados. Das diferentes distribuiÃÃes de frequÃncias testadas, apenas a distribuiÃÃo normal apresenta um ajuste aproximado ao que Weibull permite desenvolver. Com base nas estimaÃÃes da produÃÃo de eletricidade anual, ParnaÃba à a cidade que apresenta o melhor potencial para o aproveitamento eolioelÃtrico.Conselho Nacional de Desenvolvimento CientÃfico e TecnolÃgicohttp://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=12256application/pdfinfo:eu-repo/semantics/openAccessporreponame:Biblioteca Digital de Teses e Dissertações da UFCinstname:Universidade Federal do Cearáinstacron:UFC2019-01-21T11:25:26Zmail@mail.com - |
dc.title.en.fl_str_mv |
Characterization of Potential Wind Generation EolioelÃtrica For Purposes: A Case Study For Maracanaà (CE), ParnaÃba (PI) and Petrolina (PE) |
dc.title.alternative.pt.fl_str_mv |
CaracterizaÃÃo de potencial eÃlico para fins de geraÃÃo eolioelÃtrica: estudo de caso para Maracanaà (CE), ParnaÃba (PI) e Petrolina (PE) |
title |
Characterization of Potential Wind Generation EolioelÃtrica For Purposes: A Case Study For Maracanaà (CE), ParnaÃba (PI) and Petrolina (PE) |
spellingShingle |
Characterization of Potential Wind Generation EolioelÃtrica For Purposes: A Case Study For Maracanaà (CE), ParnaÃba (PI) and Petrolina (PE) Tatiane Carolyne Carneiro DistribuiÃÃo de Weibull AnÃlise de sÃries temporais Weibull distribution Wind speed Time series analysis ENGENHARIA ELETRICA |
title_short |
Characterization of Potential Wind Generation EolioelÃtrica For Purposes: A Case Study For Maracanaà (CE), ParnaÃba (PI) and Petrolina (PE) |
title_full |
Characterization of Potential Wind Generation EolioelÃtrica For Purposes: A Case Study For Maracanaà (CE), ParnaÃba (PI) and Petrolina (PE) |
title_fullStr |
Characterization of Potential Wind Generation EolioelÃtrica For Purposes: A Case Study For Maracanaà (CE), ParnaÃba (PI) and Petrolina (PE) |
title_full_unstemmed |
Characterization of Potential Wind Generation EolioelÃtrica For Purposes: A Case Study For Maracanaà (CE), ParnaÃba (PI) and Petrolina (PE) |
title_sort |
Characterization of Potential Wind Generation EolioelÃtrica For Purposes: A Case Study For Maracanaà (CE), ParnaÃba (PI) and Petrolina (PE) |
author |
Tatiane Carolyne Carneiro |
author_facet |
Tatiane Carolyne Carneiro |
author_role |
author |
dc.contributor.advisor1.fl_str_mv |
Paulo CÃsar Marques de Carvalho |
dc.contributor.advisor1ID.fl_str_mv |
00000000117 |
dc.contributor.advisor1Lattes.fl_str_mv |
http://lattes.cnpq.br/0935409654079900 |
dc.contributor.referee1.fl_str_mv |
Arthur PlÃnio de Souza Braga |
dc.contributor.referee1ID.fl_str_mv |
42395194387 |
dc.contributor.referee1Lattes.fl_str_mv |
http://lattes.cnpq.br/1473823107869382 |
dc.contributor.referee2.fl_str_mv |
Demercil de Souza Oliveira JÃnior |
dc.contributor.referee2ID.fl_str_mv |
18710730818 |
dc.contributor.referee2Lattes.fl_str_mv |
http://lattes.cnpq.br/8797685933461323 |
dc.contributor.authorID.fl_str_mv |
07303414452 |
dc.contributor.author.fl_str_mv |
Tatiane Carolyne Carneiro |
contributor_str_mv |
Paulo CÃsar Marques de Carvalho Arthur PlÃnio de Souza Braga Demercil de Souza Oliveira JÃnior |
dc.subject.por.fl_str_mv |
DistribuiÃÃo de Weibull AnÃlise de sÃries temporais |
topic |
DistribuiÃÃo de Weibull AnÃlise de sÃries temporais Weibull distribution Wind speed Time series analysis ENGENHARIA ELETRICA |
dc.subject.eng.fl_str_mv |
Weibull distribution Wind speed Time series analysis |
dc.subject.cnpq.fl_str_mv |
ENGENHARIA ELETRICA |
dc.description.sponsorship.fl_txt_mv |
Conselho Nacional de Desenvolvimento CientÃfico e TecnolÃgico |
dc.description.abstract.por.fl_txt_mv |
In recent years wind energy is becoming increasingly competitive on the world stage, making their participation in the electricity generation matrix presents a strong growth expectation. This dissertation initially presents an analysis of the behavior of wind at three locations in Northeast Brazil (Maracanau-CE, Petrolina-PE e Parnaiba-PI). In a second step, statistical analyzes are researched to the most appropriate behavior patterns of the observed wind resource in the three localities. In conclusion, the impact of the statistical analyzes used in the production of electricity from wind turbines is identified. In this study,historicaldata of speed and direction of wind collectedare used, during periods of: February 2012 to January 2013, to Maracanau; August 2012 to July 2013, for Parnaiba; and May 2012 to March 2013, for Petrolina. The Weibull distribution is applied to approximate the histograms of wind speed using different horizons of applications (annual, semiannual) and four different numerical methods (Empirical, Momentum, Energy Pattern Factor and Equivalent Energy) for estimation of the form and scale parameters. In addition to evaluating the application of Weibull, other frequency distributions (Normal, Gamma and Log-Normal)are analyzed, in order to obtain the best possible fit. In a last step, with the aid of RETScreen program,annual production of electricity, delivered to the grid from wind turbines,is calculated. The optimum wind speed occurred in Parnaiba (10 and 11 m / s), followed by Petrolina (8 and 9 m / s). Among all different numerical methods that was evaluated, the Equivalent Energy method presented the best performance, unlike the Energy Pattern Factor method, that presented the worst. The Weibull distribution showed good potential for setting wind data in Maracanau and Parnaiba, both located along the coastline. However, based on the wind data recorded, in Petrolina, which is located further inland, the performance was inferior. Among all the different frequency distributions that were verified, only normal distribution had an fit as good as Weibull distribution. Based on the annual electricity production estimation, Parnaiba is the city that has the best potential for energy production. Nos Ãltimos anos a energia eÃlica tem se tornando cada vez mais competitiva no cenÃrio mundial, fazendo com que sua participaÃÃo na matriz elÃtrica apresente uma forte expectativa de crescimento. A presente dissertaÃÃo apresenta inicialmente uma anÃlise do comportamento do vento em trÃs localidades no Nordeste do Brasil (Maracanaà (CE), Petrolina (PE) e ParnaÃba (PI)); numa segunda etapa, sÃo pesquisadas anÃlises estatÃsticas mais adequadas aos padrÃes de comportamento do recurso eÃlico observado nas trÃs localidades e, concluindo, à identificado o impacto das anÃlises estatÃsticas utilizadas na produÃÃo de eletricidade de aerogeradores. Neste estudo sÃo utilizados dados histÃricos de velocidade e direÃÃo do vento coletados durante os perÃodos de: fevereiro de 2012 - janeiro de 2013 para MaracanaÃ, Agosto de 2012 - Julho de 2013 para ParnaÃba, maio de 2012 - marÃo 2013 para Petrolina. A distribuiÃÃo de frequÃncia de Weibull à aplicada para aproximar os histogramas de velocidade do vento, utilizando diferentes horizontes de aplicaÃÃes (anual, semestral) e quatro diferentes mÃtodos numÃricos (EmpÃrico, Momento, Fator PadrÃo de Energia e Energia Equivalente) para a estimaÃÃo dos parÃmetros de forma e escala. AlÃm de avaliar a aplicaÃÃo de Weibull, sÃo analisadas outras distribuiÃÃes de frequÃncia (Normal, Gama e Log-Normal) objetivando obter o melhor ajuste possÃvel. Numa Ãltima etapa, com o auxÃlio do programa RETScreen,à calculada a produÃÃo de eletricidade anual entregue à rede a partir de aerogeradores. Os melhores valores de velocidade do vento ocorreram em ParnaÃba (10 e 11 m/s), seguido de Petrolina (8 e 9 m/s). Dos diferentes mÃtodos numÃricos avaliados, o mÃtodo de energia equivalente apresentou o melhor desempenho e o mÃtodo fator de padrÃo de energia foi o mÃtodo com o pior desempenho. A distribuiÃÃo de Weibull demonstrou bom potencial para o ajuste de dados de vento em Maracanaà e ParnaÃba, ambas localizadas ao longo do litoral. No entanto, em Petrolina, que està situada mais para o interior, foi verificado um desempenho limitado a partir dos dados de vento registrados. Das diferentes distribuiÃÃes de frequÃncias testadas, apenas a distribuiÃÃo normal apresenta um ajuste aproximado ao que Weibull permite desenvolver. Com base nas estimaÃÃes da produÃÃo de eletricidade anual, ParnaÃba à a cidade que apresenta o melhor potencial para o aproveitamento eolioelÃtrico. |
description |
In recent years wind energy is becoming increasingly competitive on the world stage, making their participation in the electricity generation matrix presents a strong growth expectation. This dissertation initially presents an analysis of the behavior of wind at three locations in Northeast Brazil (Maracanau-CE, Petrolina-PE e Parnaiba-PI). In a second step, statistical analyzes are researched to the most appropriate behavior patterns of the observed wind resource in the three localities. In conclusion, the impact of the statistical analyzes used in the production of electricity from wind turbines is identified. In this study,historicaldata of speed and direction of wind collectedare used, during periods of: February 2012 to January 2013, to Maracanau; August 2012 to July 2013, for Parnaiba; and May 2012 to March 2013, for Petrolina. The Weibull distribution is applied to approximate the histograms of wind speed using different horizons of applications (annual, semiannual) and four different numerical methods (Empirical, Momentum, Energy Pattern Factor and Equivalent Energy) for estimation of the form and scale parameters. In addition to evaluating the application of Weibull, other frequency distributions (Normal, Gamma and Log-Normal)are analyzed, in order to obtain the best possible fit. In a last step, with the aid of RETScreen program,annual production of electricity, delivered to the grid from wind turbines,is calculated. The optimum wind speed occurred in Parnaiba (10 and 11 m / s), followed by Petrolina (8 and 9 m / s). Among all different numerical methods that was evaluated, the Equivalent Energy method presented the best performance, unlike the Energy Pattern Factor method, that presented the worst. The Weibull distribution showed good potential for setting wind data in Maracanau and Parnaiba, both located along the coastline. However, based on the wind data recorded, in Petrolina, which is located further inland, the performance was inferior. Among all the different frequency distributions that were verified, only normal distribution had an fit as good as Weibull distribution. Based on the annual electricity production estimation, Parnaiba is the city that has the best potential for energy production. |
publishDate |
2014 |
dc.date.issued.fl_str_mv |
2014-07-28 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
status_str |
publishedVersion |
format |
masterThesis |
dc.identifier.uri.fl_str_mv |
http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=12256 |
url |
http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=12256 |
dc.language.iso.fl_str_mv |
por |
language |
por |
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info:eu-repo/semantics/openAccess |
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openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Federal do Cearà |
dc.publisher.program.fl_str_mv |
Programa de PÃs-GraduaÃÃo em Engenharia ElÃtrica |
dc.publisher.initials.fl_str_mv |
UFC |
dc.publisher.country.fl_str_mv |
BR |
publisher.none.fl_str_mv |
Universidade Federal do Cearà |
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reponame:Biblioteca Digital de Teses e Dissertações da UFC instname:Universidade Federal do Ceará instacron:UFC |
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Biblioteca Digital de Teses e Dissertações da UFC |
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Biblioteca Digital de Teses e Dissertações da UFC |
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Universidade Federal do Ceará |
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UFC |
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UFC |
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mail@mail.com |
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