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.
翻译:使用可再生能源的能源生产由于其间歇性质而具有内在的不确定性。然而,统一的欧洲能源市场促使区域能源系统操作者越来越多地渗透可再生能源,因此,可再生能源预测有助于整合这些挥发性能源,因为这样能提高可靠性,降低电力系统的辅助运作成本。本文为希腊太阳能和风能发电预测提供了一套新的数据集,并引入了一种特别工程管道,丰富数据集的维度空间。此外,我们提议了一种新颖的方法,利用创新先知模型,即一种端到端预测工具,考虑到在基于树木的元素提供短期预测之前将能源时间序列分解的几种非线性趋势。系统的业绩是通过具有代表性的评价指标来衡量的,并通过根据行业提供的绝对错误阈值计划估计模型的普及性。拟议混合模型与基线持久性模型、基于树木的回归组合和先知模型竞争,并设法超越这些模型,同时提出较低的错误率和更有利的错误分布。