Postgraduate Program in Climate Science, Center for Exact and Earth Sciences, Federal University of Rio Grande do Norte, Natal, Rio Grande do Norte, Brazil.
Fundação Cearense de Meteorologia e Recursos Hídricos, Fortaleza, Ceará, Brazil.
PLoS One. 2024 Jul 25;19(7):e0307641. doi: 10.1371/journal.pone.0307641. eCollection 2024.
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.
在多个国家,尤其是在风能方面,对可再生能源的投资正在增加,这是对因燃烧化石燃料发电而导致的全球气候变化的一种回应。因此,评估区域气候模型以模拟具有此类能源发电潜力的地区的风速和风力密度变得尤为重要,这对于风电场的实施至关重要。因此,本研究旨在计算 1986 年至 2005 年巴西东北部地区的区域气候模型的风力密度。首先,将 ECMWF-ERA5 再分析数据与来自 Xavier 的观测数据进行了验证。结果令人满意,在塞阿拉州和北里奥格兰德州(SON 季节除外)地区显示出较强的相关性,而在与观测数据记录的风速强度方面存在一些差异,尤其是在 JJA 季节。然后,对区域气候模型 RegCM4.7、RCA4 和 Remo2009 与 ECMWF-ERA5 再分析数据进行了验证,所有模型都成功地再现了风速模式,尤其是 12 月至 5 月期间。选择了巴西东北部的四个特定地区进行进一步研究。在这些地区,对 RCM 模拟进行了评估,以确定每个地区具有最佳统计指数和最低相关不确定性的 RCM。选定的 RCM 包括:RegCM4.7_HadGEM2(塞阿拉州北部沿海和北里奥格兰德州北部沿海)和 RCA4_Miroc(博博雷马和巴伊亚中部)。最后,从选定的 RCM 为每个地区计算了风力密度。北里奥格兰德州和塞阿拉州的北部地区表现出最高的风力密度。