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Wind speed is currently a renewable energy source that plays a very important role in mitigating the impact of energy consumption in two aspects: reducing fossil fuels and contributing to the reliability of electricity systems. Different approaches have been used to provide wind energy forecasts, since for a given wind speed, wind generation might take different values, which implies a stochastic relationship between wind speed and wind production. In this work an analysis based on quantile regression is used, which allows to address this difficulty. For this, wind energy predictions are obtained using data from a wind farm in Brazil to validate the proposed model. The results are encouraging and show that the model is robust and efficient because its estimation via optimization does not require any hypothesis about the errors distribution.

REGRESSÃO QUANTÍLICA: UMA ANÁLISE PARA A GERAÇÃO DE ENERGIA EÓLICA E VELOCIDADE DO VENTO