Brazilian wind energy generation potential using mixtures of Weibull distributions

Abstract

As concerns about the greenhouse effect and the resulting increase in carbon dioxide levels in the atmosphere continue to mount, there is an increasing need to curtail the use of fossil fuels for energy generation, especially given the ever-growing energy demands of the population. In this work, we applied the Weibull–Weibull distribution mixture to adjust the wind speed series of all 575 weather stations at six different heights for the 12 months of the year in the period from 01-01-2000 to 03-31-2022 measured in the hourly interval. We present the main results for the month with the lowest and the month with the highest incidence of wind speed in Brazil for the height of 120 m, which are the months of May and September, respectively. In estimating the Weibull–Weibull parameters, the Expectation–Maximization algorithm was used. Using the results obtained at each meteorological station and the Inverse Distance Weighting method, we predicted wind energy generation at points without information about wind speed. We observed that the Weibull–Weibull distribution mixture proved excellent for estimating wind energy density distribution over large areas We were able to provide a suitable fit for the different regions of Brazil. The findings indicate that the model employed has the potential to serve as a strong contender for adoption in other nations, enabling the integration of alternative energy sources in a complementary fashion. This measure could prove instrumental in mitigating the use of environmentally hazardous energy sources.