Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 1 de 1
Filtrar
Mais filtros











Base de dados
Assunto principal
Intervalo de ano de publicação
1.
PLoS One ; 19(7): e0307641, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-39052597

RESUMO

Investments in renewable energy sources are increasing in several countries, especially in wind energy, as a response to global climate change caused by the burning of fossil fuels for electricity generation. Thus, it is important to evaluate the Regional Climate Models that simulate wind speed and wind power density in promising areas for this type of energy generation with the least uncertainty in recent past, which is essential for the implementation of wind farms. Therefore, this research aims to calculate the wind power density from Regional Climate Models in areas at Northeast of Brazil from 1986 to 2005. Initially, the ECMWF-ERA5 reanalysis data was validated against observed data obtained from Xavier. The results were satisfactory, showing a strong correlation in areas of Ceará and Rio Grande do Norte (except during the SON season), and some differences in relation to the wind intensity registered by observed data, particularly during the JJA season. Then, the Regional Climate Models RegCM4.7, RCA4 and Remo2009 were validated against the ECMWF-ERA5 reanalysis data, with all models successfully representing the wind speed pattern, especially from December to May. Four specific areas in Northeast of Brazil were selected for further study. In these areas, the RCMs simulations were evaluated to identify the RCM with the best statistical indices and consequently the lowest associated uncertainty for each area. The selected RCMs were: RegCM4.7_HadGEM2 (northern coastal of Ceará and northern coastal of Rio Grande do Norte) and RCA4_Miroc (Borborema and Central Bahia). Finally, the wind power density was calculated from the selected RCM for each area. The northern regions of Rio Grande do Norte and Ceará exhibited the highest wind power density.


Assuntos
Vento , Brasil , Modelos Climáticos , Energia Renovável , Mudança Climática , Estações do Ano
SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA