Complementarity modeling of monthly streamflow and wind speed regimes based on a copula-entropy approach: A Brazilian case study

Abstract

Wind power energy has been showing significant growth in installed capacity around the world. This opportunity presents big challenges to operate power systems with high wind power penetration levels, considering the variability and intermittent behavior of this type of power source. To reduce uncertainties associated with this kind of power systems, researchers have explored the integration of wind power energy with other renewable energy sources, like solar and hydropower. For instance, the integration of wind and hydro systems can deal with the spatial and temporal complementarity of hydrological and wind regimes to produce energy. Therefore, it is necessary to consider the stochastic behavior and the dependence structures between these variables to define better operational policies. This study explores the spatial correlation of hydrological and wind regimes in different regions of Brazil and defines an entropy-copula-based model for the joint simulation of monthly streamflow and wind speed time series to evaluate the potential integration of hydro and wind energy sources. The proposed model showed a good adherence to the periodic behavior for both variables, and the results indicate that simulated scenarios preserved statistical features of historical data.