电力系统自动化2017，Vol.41Issue(4)：1-11,19,12.DOI:10.7500/AEPS20160813002
面向能源系统的数据科学:理论、技术与展望
Data Science for Energy Systems: Theory, Techniques and Prospect
摘要
Abstract
The comprehensive energy system,which can coordinate multiple types of energy and be characterized by a deep integration of "cyber-physical-social" 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.关键词
大能源系统/智能电网/“信息-物理-社会”系统/数据科学/大数据Key words
comprehensive energy system/smart grid/"cyber-physical-social" system/data science/big data引用本文复制引用
赵俊华,董朝阳,文福拴,薛禹胜..面向能源系统的数据科学:理论、技术与展望[J].电力系统自动化,2017,41(4):1-11,19,12.基金项目
国家重点基础研究发展计划(973计划)资助项目(2013CB228202) （973计划）
国家自然科学基金资助项目(51477151) （51477151）
高等学校博士学科点专项科研基金资助项目(20120101110112).本文研究获得南方电网公司科技项目(WYKJ00000027)资助,特此致谢！This work is supported by National Basic Research Program of China (973 Program) (No.2013CB228202),National Natural Science Foundation of China (No.51477151) and Specialized Research Fund for the Doctoral Program of Higher Education of China (No.20120101110112). （20120101110112）
