Fatores de forma e de escala da distribuição de probabilidade Weibull: um estudo de caso para dados de recursos eólicos da Região Nordeste do Brasil

• Autor(a) principal: Silva, Francisco Jeandson Rodrigues da
• Data de Publicação: 2020
• Outros Autores: Costa, Douglas Aurélio Carvalho, Soares, Fellipe Souto, Vieira, Obed Leite, Carvalho, Pollyana Rodrigues de, Carvalho, Paulo Cesar Marques de
• Tipo de documento: Artigo de conferência
• Idioma: por
• Título da fonte: Repositório Institucional da Universidade Federal do Ceará (UFC)
• Texto Completo: http://www.repositorio.ufc.br/handle/riufc/61037
• topic: Distribuição de Probabilidade de Weibull; Energia eólica; Fator de forma; Fator de escala

The purpose of this article is to use a series of wind velocity data (V) measured in the coast of Ceara state at a height of 100 m during 2016, in order to estimate the parameters of the Weibull probability distribution function, shape factor (k) and scale factor (c), using the following methods: graphical (MG), empirical of Justus (MEJ) and empirical of Lysen (MEL), standard factor of energy (MFPE), maximum likelihood (MMV) and modified maximum likelihood (MMVM). Results of each method are compared using evaluation indicators such as relative percentage errors, mean absolute percentage, mean percentage error, mean root error root and error root relative mean square. Afterwards, wind resource characteristics are evaluated: probability density of V, monthly capacity factor (FC), estimated monthly energy. The best method for Ceara coast is MMV, due to three indicators: RPE, RMSE and RRMSE, with values of -0.0012, 2.8e-03 and 5.83, respectively, with the values of and for this method, 2.6587 and 8.8664, respectively. Considering a wind class speed of 8.5 m/s, a 2 MW Harvester turbine has an estimated annual electricity generation of 10,865 GWh and a FC of 60.98%; an Enercon 2 MW turbine has an estimated annual electricity generation of 7,869 GWh and a FC of 44.92%.