| 能源互联网大数据分析技术综述 |
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| 引用本文： | 曹军威,袁仲达,明阳阳,张华赢.能源互联网大数据分析技术综述[J].南方电网技术,2015,9(11):1-12. |
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| 作者姓名： | 曹军威 袁仲达 明阳阳 张华赢 |
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| 作者单位： | 清华大学信息技术研究院，北京100084,清华大学信息技术研究院，北京100084,清华大学信息技术研究院，北京100084,深圳供电局有限公司，深圳518020 |
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| 基金项目： | 国家自然科学基金项目(61472200，61233016)；国家重点基础研究发展计划项目(973计划) (2013CB228206) |
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| 摘 要： | 大数据技术具有数据容量大、数据类型繁多、商业价值高、处理速度快的特点。能源互联网是信息通信与能源电力结合发展的高级阶段，以逐步实现信息通信基础设施与能源电力基础设施的一体化为特征。在能源互联网中不仅信息的种类和数量巨大，而且对信息的实时性要求也越来越高，因此大数据分析技术在能源互联网中具有广泛的应用前景。在大数据处理平台和大数据分析算法研究现状两方面综述了大数据分析技术，列举了大数据分析在能源互联网的典型应用场景和研究课题。
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| 关 键 词： | 能源互联网 大数据分析 数据挖掘 深度学习 负荷云库 态势感知 |
Survey of Big Data Analysis Technology for Energy Internet |
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| CAO Junwei,YUAN Zhongd,MING Yangyang and ZHANG Huaying.Survey of Big Data Analysis Technology for Energy Internet[J].Southern Power System Technology,2015,9(11):1-12. |
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| Authors: | CAO Junwei YUAN Zhongd MING Yangyang and ZHANG Huaying |
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| Affiliation: | Research Institute of Information Technology, Tsinghua University, Beijing 100084, China,Research Institute of Information Technology, Tsinghua University, Beijing 100084, China,Research Institute of Information Technology, Tsinghua University, Beijing 100084, China and Shenzhen Power Supply Co.Ltd., Shenzhen, Guangdong 518020, China |
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| Abstract: | The features of big data technology are big volume, numerous data types, high business value and fast handling speed. Energy Internet is the advanced stage of the combined development of information communication and energy electric technologies, and its main feature is the gradual integration of the two technologies infrastructures. For energy intermet, there are not only numerous information quantities and information categories, but also higer real time requirements of information. So it is obvious that big data analysis technology has a broad application prospect in Energy Internet.This article makes an overview on big data analysis technology in the big data processing platform and the current research situation of related algorithms, and lists the typical application scenes and research projects in Energy Internet. |
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| Keywords: | energy internet big data analysis data mining deep learning power load cloud situation awareness |
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