Artículo de revista
Forecasting electric load demand through advanced statistical techniques
Registro en:
1742-6588
1742-6596
Corporación Universidad de la Costa
REDICUC - Repositorio CUC
Autor
silva d, jesus g
Senior Naveda, Alexa
García Guiliany, Jesús Enrique
Niebles Nuñez, William
Hernández Palma, Hugo
Institución
Resumen
Traditional forecasting models have been widely used for decision-making in production, finance and energy. Such is the case of the ARIMA models, developed in the 1970s by George Box and Gwilym Jenkins [1], which incorporate characteristics of the past models of the same series, according to their autocorrelation. This work compares advanced statistical methods for determining the demand for electricity in Colombia, including the SARIMA, econometric and Bayesian methods.