Comparison of methods and distribution models for the modeling of wind speed data in the municipality of Petrolina, Northeast Brazil
| Autor(a) principal: | |
|---|---|
| Data de Publicação: | 2020 |
| Outros Autores: | , , |
| Tipo de documento: | Artigo |
| Idioma: | por |
| Título da fonte: | Research, Society and Development |
| Texto Completo: | https://rsdjournal.org/index.php/rsd/article/view/4221 |
Resumo: | The identification of the probability distribution model that provides the best fit to the wind speed databases is necessary for defining investment and developing projects about the wind potential of different locations. For this, the estimation of the parameters of the models is essential in this process. The aim of this study is to investigate among the distribution models and methods for estimating their respective parameters with better modeling in the literature which of them provides better fit to the wind speed data of Petrolina-PE. Through the case study, of quali-quanti nature, the adjustment of the Moment Method, the Estimation of Maximum Likelihood and the Particle Swarm Optimization (PSO) algorithm with Weibull were evaluated in this work, as well as the PSO with the Lognormal-Weibull and Weibull-Weibull distributions to the historical series of information. The results, investigated with the RMSE, R^2 and X^2 error measures and by verifying the percentage of correctness between the theoretical and sample quantiles, demonstrated a better modeling of the Lognormal-Weibull distribution model with the PSO algorithm to the historical speed series of the wind. Thus, from the determination of the best distribution model that fits the data in the region, it may be possible to generate estimated wind speed series for areas where these historical series do not exist. |
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Comparison of methods and distribution models for the modeling of wind speed data in the municipality of Petrolina, Northeast BrazilComparación de métodos y modelos de distribución para el modelado de datos de velocidad eólica en el municipio de Petrolina, noreste de BrasilComparação de métodos e modelos de distribuição para a modelagem de dados de velocidade do vento no município de Petrolina, Nordeste brasileiroWeibullLognormalMMEMVPSOAdjustmentWeibullLognormalMMEMVPSOAjusteWeibullLognormalMMEMVPSOAjusteThe identification of the probability distribution model that provides the best fit to the wind speed databases is necessary for defining investment and developing projects about the wind potential of different locations. For this, the estimation of the parameters of the models is essential in this process. The aim of this study is to investigate among the distribution models and methods for estimating their respective parameters with better modeling in the literature which of them provides better fit to the wind speed data of Petrolina-PE. Through the case study, of quali-quanti nature, the adjustment of the Moment Method, the Estimation of Maximum Likelihood and the Particle Swarm Optimization (PSO) algorithm with Weibull were evaluated in this work, as well as the PSO with the Lognormal-Weibull and Weibull-Weibull distributions to the historical series of information. The results, investigated with the RMSE, R^2 and X^2 error measures and by verifying the percentage of correctness between the theoretical and sample quantiles, demonstrated a better modeling of the Lognormal-Weibull distribution model with the PSO algorithm to the historical speed series of the wind. Thus, from the determination of the best distribution model that fits the data in the region, it may be possible to generate estimated wind speed series for areas where these historical series do not exist.La identificación del modelo de distribución de probabilidad que proporciona el mejor ajuste a las bases de datos de velocidad del viento es necesario para definir la inversión y desarrollar proyectos sobre el potencial eólico de diferentes ubicaciones. Para esto, la estimación de los parámetros de los modelos es esencial en este proceso. El objetivo de este estudio es investigar entre los modelos y métodos de distribución para estimar sus respectivos parámetros con un mejor modelado en la literatura que de ellos proporciona un mejor ajuste a los datos de velocidad del viento de Petrolina-PE. A través del estudio de caso, de naturaleza quali-quanti, el ajuste del Método momento, la Estimación de Máxima Probabilidad y el algoritmo de Optimización de Enjambre de Partículas (PSO) con Weibull fueron evaluados en este trabajo, así como el PSO con las distribuciones Lognormal-Weibull y Weibull-Weibull a la serie histórica de información. Los resultados, investigados con las medidas de error RMSE, R^2 y X^2 y al verificar el porcentaje de corrección entre los cuantiles teóricos y de muestra, demostraron un mejor modelado del modelo de distribución Lognormal-Weibull con el algoritmo PSO a la serie de velocidad histórica del viento. Por lo tanto, a partir de la determinación del mejor modelo de distribución que se ajuste a los datos de la región, puede ser posible generar series estimadas de velocidad del viento para áreas donde estas series históricas no existen.A identificação do modelo de distribuição de probabilidade que forneça o melhor ajuste às bases de dados de velocidade do vento é necessária para definição de investimento e desenvolvimento de projetos acerca do potencial eólico de diversas localidades. Para isso, a estimativa dos parâmetros dos modelos é essencial nesse processo. O objetivo deste estudo é investigar dentre os modelos de distribuição e métodos para estimativa de seus respectivos parâmetros com melhor modelagem na literatura qual deles fornece melhor ajuste aos dados de velocidade do vento de Petrolina-PE. Através do estudo de caso, de natureza quali-quanti, foram avaliados neste trabalho o ajuste do Método dos Momentos, da Estimação de Máxima Verossimilhança e do algoritmo Particle Swarm Optimization (PSO) com a Weibull, bem como o PSO com as distribuições Lognormal-Weibull e Weibull-Weibull à série histórica de informações. Os resultados, investigados com as medidas de erro RMSE, R^2 e X^2 e pela verificação da porcentagem de acerto entre os quantis teóricos e amostrais, demonstraram melhor modelagem do modelo de distribuição Lognormal-Weibull com o algoritmo PSO à série histórica de velocidade do vento. Dessa maneira, através da determinação do melhor modelo de distribuição que se ajuste aos dados na região, pode ser possível gerar séries de velocidade do vento estimadas para áreas onde não existem essas séries históricas.Research, Society and Development2020-05-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://rsdjournal.org/index.php/rsd/article/view/422110.33448/rsd-v9i7.4221Research, Society and Development; Vol. 9 No. 7; e308974221Research, Society and Development; Vol. 9 Núm. 7; e308974221Research, Society and Development; v. 9 n. 7; e3089742212525-3409reponame:Research, Society and Developmentinstname:Universidade Federal de Itajubá (UNIFEI)instacron:UNIFEIporhttps://rsdjournal.org/index.php/rsd/article/view/4221/3466Copyright (c) 2020 Kerolly Kedma Felix do Nascimento, Fábio Sandro dos Santos, Jader da Silva Jale, Tiago Alessandro Espínola Ferreirainfo:eu-repo/semantics/openAccessNascimento, Kerolly Kedma Felix doSantos, Fábio Sandro dosJale, Jader da SilvaFerreira, Tiago Alessandro Espínola2020-08-20T18:05:03Zoai:ojs.pkp.sfu.ca:article/4221Revistahttps://rsdjournal.org/index.php/rsd/indexPUBhttps://rsdjournal.org/index.php/rsd/oairsd.articles@gmail.com2525-34092525-3409opendoar:2024-01-17T09:28:08.681425Research, Society and Development - Universidade Federal de Itajubá (UNIFEI)false |
| dc.title.none.fl_str_mv |
Comparison of methods and distribution models for the modeling of wind speed data in the municipality of Petrolina, Northeast Brazil Comparación de métodos y modelos de distribución para el modelado de datos de velocidad eólica en el municipio de Petrolina, noreste de Brasil Comparação de métodos e modelos de distribuição para a modelagem de dados de velocidade do vento no município de Petrolina, Nordeste brasileiro |
| title |
Comparison of methods and distribution models for the modeling of wind speed data in the municipality of Petrolina, Northeast Brazil |
| spellingShingle |
Comparison of methods and distribution models for the modeling of wind speed data in the municipality of Petrolina, Northeast Brazil Nascimento, Kerolly Kedma Felix do Weibull Lognormal MM EMV PSO Adjustment Weibull Lognormal MM EMV PSO Ajuste Weibull Lognormal MM EMV PSO Ajuste |
| title_short |
Comparison of methods and distribution models for the modeling of wind speed data in the municipality of Petrolina, Northeast Brazil |
| title_full |
Comparison of methods and distribution models for the modeling of wind speed data in the municipality of Petrolina, Northeast Brazil |
| title_fullStr |
Comparison of methods and distribution models for the modeling of wind speed data in the municipality of Petrolina, Northeast Brazil |
| title_full_unstemmed |
Comparison of methods and distribution models for the modeling of wind speed data in the municipality of Petrolina, Northeast Brazil |
| title_sort |
Comparison of methods and distribution models for the modeling of wind speed data in the municipality of Petrolina, Northeast Brazil |
| author |
Nascimento, Kerolly Kedma Felix do |
| author_facet |
Nascimento, Kerolly Kedma Felix do Santos, Fábio Sandro dos Jale, Jader da Silva Ferreira, Tiago Alessandro Espínola |
| author_role |
author |
| author2 |
Santos, Fábio Sandro dos Jale, Jader da Silva Ferreira, Tiago Alessandro Espínola |
| author2_role |
author author author |
| dc.contributor.author.fl_str_mv |
Nascimento, Kerolly Kedma Felix do Santos, Fábio Sandro dos Jale, Jader da Silva Ferreira, Tiago Alessandro Espínola |
| dc.subject.por.fl_str_mv |
Weibull Lognormal MM EMV PSO Adjustment Weibull Lognormal MM EMV PSO Ajuste Weibull Lognormal MM EMV PSO Ajuste |
| topic |
Weibull Lognormal MM EMV PSO Adjustment Weibull Lognormal MM EMV PSO Ajuste Weibull Lognormal MM EMV PSO Ajuste |
| description |
The identification of the probability distribution model that provides the best fit to the wind speed databases is necessary for defining investment and developing projects about the wind potential of different locations. For this, the estimation of the parameters of the models is essential in this process. The aim of this study is to investigate among the distribution models and methods for estimating their respective parameters with better modeling in the literature which of them provides better fit to the wind speed data of Petrolina-PE. Through the case study, of quali-quanti nature, the adjustment of the Moment Method, the Estimation of Maximum Likelihood and the Particle Swarm Optimization (PSO) algorithm with Weibull were evaluated in this work, as well as the PSO with the Lognormal-Weibull and Weibull-Weibull distributions to the historical series of information. The results, investigated with the RMSE, R^2 and X^2 error measures and by verifying the percentage of correctness between the theoretical and sample quantiles, demonstrated a better modeling of the Lognormal-Weibull distribution model with the PSO algorithm to the historical speed series of the wind. Thus, from the determination of the best distribution model that fits the data in the region, it may be possible to generate estimated wind speed series for areas where these historical series do not exist. |
| publishDate |
2020 |
| dc.date.none.fl_str_mv |
2020-05-12 |
| dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
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article |
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publishedVersion |
| dc.identifier.uri.fl_str_mv |
https://rsdjournal.org/index.php/rsd/article/view/4221 10.33448/rsd-v9i7.4221 |
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https://rsdjournal.org/index.php/rsd/article/view/4221 |
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10.33448/rsd-v9i7.4221 |
| dc.language.iso.fl_str_mv |
por |
| language |
por |
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https://rsdjournal.org/index.php/rsd/article/view/4221/3466 |
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info:eu-repo/semantics/openAccess |
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openAccess |
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application/pdf |
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Research, Society and Development |
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Research, Society and Development |
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Research, Society and Development; Vol. 9 No. 7; e308974221 Research, Society and Development; Vol. 9 Núm. 7; e308974221 Research, Society and Development; v. 9 n. 7; e308974221 2525-3409 reponame:Research, Society and Development instname:Universidade Federal de Itajubá (UNIFEI) instacron:UNIFEI |
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Universidade Federal de Itajubá (UNIFEI) |
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UNIFEI |
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UNIFEI |
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Research, Society and Development |
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Research, Society and Development |
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Research, Society and Development - Universidade Federal de Itajubá (UNIFEI) |
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rsd.articles@gmail.com |
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1797052649718153216 |