Prediction intervals for electricity demand and price using functional data

This paper provides two procedures to obtain prediction intervals for electricity demand and price based on functional data. The proposed procedures are related to one day ahead pointwise forecast. In particular, the first method uses a nonparametric autoregressive model and the second one uses a partial linear semi-parametric model, in which exogenous scalar covariates are incorporated in a linear way. In both cases, the proposed procedures for the construction of the prediction intervals use residual-based bootstrap algorithms, which allows also to obtain estimates of the prediction density. Applications to the Spanish Electricity Market, in year 2012, are reported. This work extends and complements the results of Aneiros et al. (2016), focused on pointwise forecasts of next-day electricity demand and price daily curves.