Applying Copulas Functions for Wind and Hydro Complementarity Evaluation: a Brazilian Case

Abstract

Wind energy has been expanding in many countries typically hydro electricity producers in the last decades and some investments take advantage from the complementarity among hydro and wind productions as a strategy to increase profits and minimize risks. In this paper, our focus is applying copulas functions to evaluate a complementarity between wind and hydro production in different regions in Brazil. The goal is evaluate which regions are most suitable for development of wind energy considering the existing hydro electricity production. Copulas functions can capture the dependence structure among random variables offering a great flexibility in building multivariate stochastic models while statistic correlation does not capture nonlinear effects sufficiently. For this reason, we apply nine different copulas functions in our study finding those that best capture the complementarity.