Multivariate Forecasting of Electricity Production using Neural Network and Box-Jenkins Methodologies

The aim of this paper is to prove the validity of an alternative prediction technique to another classical one, which is Box-Jenkins methodology, in order to produce multivariate prediction. In particular, one-step ahead forecasts will be obtained for two time series: thermic and hydraulic power production. These forecasts are based on the past values of those series.