Avaliação dos impactos das mudanças climáticas na geração de energia eólica nos estados do Rio Grande do Norte e Ceará - Cunto, Guilherme Alcantara Barbosa (Universidade Federal de São Carlos, 2025)
Wind energy has emerged as one of the main sustainable alternatives for electricity generation in Brazil. Among the states with the greatest potential, Rio Grande do Norte and Ceará stand out due to their favorable climatic and geographic conditions, which ensure strong and consistent wind regimes. However, the availability of this resource is highly dependent on climatic variability, making it essential that long-term energy planning incorporates reliable projections of future wind behavior. This study analyzed climate scenarios proposed by the Intergovernmental Panel on Climate Change (IPCC) and their potential impacts on the wind energy sector, using outputs from Global Climate Models (GCMs) regionalized through the Eta model (BESM, CanESM2, HadGEM2-ES, and MIROC5), subsequently refined through machine learning techniques. Historical observational series were integrated into these projections, resulting in a hybrid modeling framework capable of providing high-accuracy forecasts for the next three decades. The results indicate a general trend of slight decreases in mean wind speeds, ranging from 2% to 7% by the mid-21st century. Ceará shows a more stable and homogeneous pattern, with modest reductions and low spatial variability, while Rio Grande do Norte exhibits more heterogeneous declines, particularly in inland areas. Despite these projected reductions, both states remain highly favorable for wind power expansion and for strengthening the green hydrogen production chain, consolidating the Northeast region as a strategic axis in Brazil’s energy transition.
Assessment of climate change impacts on wind energy generation in the states of Rio Grande do Norte and Ceará
Keywords: Energia Eólica; Planejamento Energético; Mudanças Climáticas; Modelos Climáticos Globais; Wind Energy; Energy Planning; Climate Change; Global Climate Models; ENGENHARIAS; 7. Energia limpa e acessível