Wind Power Potential of Southeast Brazil: Analytical Study for São Paulo and Rio de Janeiro

ABSTRACT Statistical models to wind speed allow understanding accurately the wind potential of a location, which is significant when deciding where to locate new wind farm installations and sometimes for the strategy of buildings and their structural design. The intention of this research is to fit three probability distribution functions (PDFs) named Weibull, generalized extreme value (GEV), and Gumbel (GUM) to average wind speed data from the metropolises of both São Paulo (SP) and Rio de Janeiro (RJ). Moreover, the objective encompassed calculating the anticipated average wind speeds for these metropolises, taking into account the return periods of 10, 20, 30, 40, 50, and 100 years. The assessment and appropriateness for chosen PDF were evaluated using statistical measures such as mean absolute percentage errors (MAPEs), Ljung–Box test, and Kolmogorov–Smirnov (KS) test. Regarding the evaluation of the accuracy of wind speed predictions in RJ, the Weibull distribution showed the best performance. In SP, the GUM and Weibull distributions showed the same performance. The results presented in this article can help in understanding the wind potential of southeastern Brazil and serve as a source of wind energy projects. This study is the first complete probabilistic analysis of extreme winds in SP and RJ, addressing a significant gap in wind potential assessment in Southeast Brazil. Using high‐resolution data spanning 61 years, the study analyzes extreme events. Unlike previous regional studies that focused on annual averages, this research aims to calculate monthly variability and return periods (10–100 years).