文章摘要
薛禹胜,赖业宁.大能源思维与大数据思维的融合:(一)大数据与电力大数据[J].电力系统自动化,2016,40(1):1-8. DOI: 10.7500/AEPS20151208005.
XUE Yusheng,LAI Yening.Integration of Macro Energy Thinking and Big Data Thinking: Part One Big Data and Power Big Data[J].Automation of Electric Power Systems,2016,40(1):1-8. DOI: 10.7500/AEPS20151208005.
大能源思维与大数据思维的融合:(一)大数据与电力大数据
Integration of Macro Energy Thinking and Big Data Thinking: Part One Big Data and Power Big Data
DOI:10.7500/AEPS20151208005
关键词: 信息能源系统  能源互联  因果型数据  统计型数据  博弈型数据  非结构型数据  知识提取
KeyWords: cyber energy system  energy interconnection  causal data  statistic data  gambling data  unstructured data  knowledge extraction
上网日期:2015-12-28
基金项目:国家自然科学基金重点资助项目(61533010);中英合作研究项目(513111025-2013);中泰合作研究项目(5151101161);国家电网公司科技项目
作者单位E-mail
薛禹胜 南瑞集团公司(国网电力科学研究院), 江苏省南京市 211106  
赖业宁 南瑞集团公司(国网电力科学研究院), 江苏省南京市 211106 laiyening@sgepri.sgcc.com.cn 
摘要:
      大能源思维将电力视为能源生产与消费全流程中的枢纽环节,藉此推动上游一次能源的清洁替代与下游终端能源的电能替代,支撑能源的可持续发展。大数据思维将各种数据资源从简单的处理对象转变为生产的基础要素。这两种思维的融合,使电力大数据成为大能源系统广泛互联、开放互动及高度智能的支撑,包括:广域多时间尺度的能源数据及相关领域数据的采集、传输和存储,以及从这些大量多源异构数据中快速提炼出深层知识并发挥其应用价值。作为两篇论文中的开篇,在演绎大数据基本概念、结构类型及本质特征的基础上,归纳电力大数据的特点。针对综合能源,通过基于数学模型的因果型数据、无因果关系的统计型数据以及参与者博弈型数据的融合,构建信息能源系统的知识挖掘平台。其续篇将讨论信息能源系统,并通过若干案例,反映大数据思维对提高大能源经济性与可靠性的贡献。
Abstract:
      The macro energy thinking which regards electricity as a hub between energy production and consumption, can promote “clean energy substitution” of the upstream primary energy and “electricity substitution” of the downstream end-use energy, in order to support the sustainable development of energy. Meanwhile the big data thinking regards various data resources as fundamental elements of production rather than simple process objects. The integration of these thinking will make the big data on power become the foundation of an extensively interconnected, openly interactive and highly intelligent macro energy system. Key elements of this integration include the acquirement, transmission and storage of wide-area power data with different timescales, the data from related domains, as well as the fast and in-depth knowledge extraction from the multi-source heterogeneous data and its applications. As the first part of a series of paper, this paper summarizes unique features of big data based on the deduction of the basic concept, data structures and essential characteristics of big data. For the comprehensive energy network, a knowledge extraction platform is constructed by integrating the causal data (based on mathematical models), the statistic data (with non-causal relationship) and the gambling data (of human participants). More case studies will be proposed in the subsequent paper, which will show the contributions of big data thinking to enhance the economy and reliability of macro energy systems. This work is supported by National Natural Science Foundation of China (No. 61533010), NSFC-EPSRC Collaborative Project (No. 513111025-2013), China-Thailand Cooperation Fund Project (No. 5151101161), and State Grid Corporation of China.
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