  Energy production using renewable sources exhibits inherent uncertainties due
to their intermittent nature. Nevertheless, the unified European energy market
promotes the increasing penetration of renewable energy sources (RES) by the
regional energy system operators. Consequently, RES forecasting can assist in
the integration of these volatile energy sources, since it leads to higher
reliability and reduced ancillary operational costs for power systems. This
paper presents a new dataset for solar and wind energy generation forecast in
Greece and introduces a feature engineering pipeline that enriches the
dimensional space of the dataset. In addition, we propose a novel method that
utilizes the innovative Prophet model, an end-to-end forecasting tool that
considers several kinds of nonlinear trends in decomposing the energy time
series before a tree-based ensemble provides short-term predictions. The
performance of the system is measured through representative evaluation
metrics, and by estimating the model's generalization under an industryprovided
scheme of absolute error thresholds. The proposed hybrid model competes with
baseline persistence models, tree-based regression ensembles, and the Prophet
model, managing to outperform them, presenting both lower error rates and more
favorable error distribution.
