Time Series Analysis for Predicting Hydroelectric Power Production: The Ecuador Case

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 a...

Full description

Saved in:
Bibliographic Details
Published inSustainability Vol. 11; no. 23; p. 6539
Main Authors Barzola-Monteses, Julio, Mite-León, Mónica, Espinoza-Andaluz, Mayken, Gómez-Romero, Juan, Fajardo, Waldo
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.12.2019
Subjects
Alternative energy
Autoregressive models
Drought
Electric power generation
Electrical faults
Electricity
Electricity distribution
Energy industry
Energy policy
Fossil fuels
Hydroelectric power
Hydrologic data
Methods
Power sources
Precipitation
Prediction models
Rain
Random variables
Renewable resources
River basins
Statistical analysis
Sustainability
Time series
Ecuador
Online AccessGet full text

Cover

More Information
Summary: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.
ISSN:2071-1050
2071-1050
DOI:10.3390/su11236539