Time Series Analysis for Predicting Hydroelectric Power Production: The Ecuador Case Barzola Monteses, Julio Mite León, Mónica Espinoza Andaluz, Mayken Gómez Romero, Juan Fajardo Contreras, Waldo Hydroelectric power plants Production prediction Functional time series analysis ARIMA ARIMAX Electrical generation in Ecuador mainly comes from hydroelectric and thermo-fossil sources, with the former amounting to almost half of the national production. Even though hydroelectric power sources are highly stable, there is a threat of droughts and floods affecting Ecuadorian water reservoirs and producing electrical faults, as highlighted by the 2009 Ecuador electricity crisis. Therefore, predicting the behavior of the hydroelectric system is crucial to develop appropriate planning strategies and a good starting point for energy policy decisions. In this paper, we developed a time series predictive model of hydroelectric power production in Ecuador. To this aim, we used production and precipitation data from 2000 to 2015 and compared the Box-Jenkins (ARIMA) and the Box-Tiao (ARIMAX) regression methods. The results showed that the best model is the ARIMAX (1,1,1) (1,0,0)12, which considers an exogenous variable precipitation in the Napo River basin and can accurately predict monthly production values up to a year in advance. This model can provide valuable insights to Ecuadorian energy managers and policymakers. 2020-02-11T09:52:54Z 2020-02-11T09:52:54Z 2019-11-20 info:eu-repo/semantics/article Barzola-Monteses, J., Mite-León, M., Espinoza-Andaluz, M., Gómez-Romero, J., & Fajardo, W. (2019). Time Series Analysis for Predicting Hydroelectric Power Production: The Ecuador Case. Sustainability, 11(23), 6539. http://hdl.handle.net/10481/59566 10.3390/su11236539 eng http://creativecommons.org/licenses/by/3.0/es/ info:eu-repo/semantics/openAccess Atribución 3.0 España MDPI