中文摘要：

以多能源互补协调、“信息-物理-社会”系统深度融合为特征的大能源系统正在出现。因此，急需对面向能源系统的数据科学及大数据挖掘理论与技术开展深入研究。在此背景下，初步探讨了数据科学及其在大能源系统中的应用。首先介绍了数据科学的基本理论，并着重讨论了统计学习理论及数据质量理论的重要性。接着，介绍了深度学习、转移学习和多源数据融合等大数据挖掘技术的新进展。最后，对数据挖掘技术在能源系统中的应用现状做了简单回顾，并展望了未来能源系统数据挖掘研究中值得关注的若干问题。

英文摘要：

The comprehensive energy system, which can coordinate multiple types of energy and be characterized by a deep integration of ＂cyber-physical-socia[＂ systems, is emerging. There is therefore an urgent need to conduct in-depth study on data science and big data mining for energy systems. This paper presents an initial discussion on data science and its applications in comprehensive energy systems. The fundamentals of data science, in particular the importance of the statistical learning theory and data quality, are discussed first. The new progresses in big data mining, such as deep learning, transfer learning and cross domain data fusion, are introduced then. Finally, a brief review is given on the applications of data mining techniques in energy systems; some research problems in energy system data mining, which require further attentions in future, are also discussed.