Predictive recommendation model for the energy dispatch of the Paute Hydropower complex

Abstract

This work proposes to make the most of the water resource used for the generation of electricity in Ecuador. Three models based on artificial intelligence have been made for the Mazar, Molino and Sopladora hydroelectric plants that belong to the Paute-Integral hydroelectric complex. For the implementation of the predictive recommendation algorithms, the behavior of the Mazar, Molino and Sopladora plants was first modeled, after which optimization was carried out to maximize electricity generation according to the capacity of the hydroelectric plants and hydrology. Finally, with the results obtained, it is observed that the maximization of electricity generation is achieved for the Mazar and Molino plants. Regarding the Sopladora plant, whose energy dispatch depends directly on the electricity generation of the Molino plant, the evaluation point remains to measure the impact produced by the optimization of the Molino plant.