大能源思维与大数据思维的融合(一)大数据与电力大数据
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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。
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 multisource 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.
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 multisource 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.
引文
[1]TOLLE K M,TANSLEY D S W,HEY A J G.The fourth paradigm:data-intensive scientific discovery[J].Proceedings of the IEEE,2011,99(8):1334-1337.
[2]Nature.Big data[EB/OL].[2008-09-03].http://www.nature.com/news/specials/bigdata/index.html.
[3]BRYANT R E,KATZ R H,LAZOWSKA E D.Big-data computing:creating revolutionary breakthroughs in commerce,science,and society[R].2008.
[4]Science.Special online collection:dealing with data[EB/OL].[2011-02-11].http://www.sciencemag.org/site/special/data.
[5]MANYIKA J,CHUI M,BROWN B,et al.Big data:the next frontier for innovation,competition,and productivity[R].2011.
[6]United States Department of Energy Office of Electric Transmission and Distribution.The smart grid:an introduction[EB/OL].[2015-11-03].http://www.oe.energy.gov/DocumentsandMedia/DOE_SG_Book_Single_Pages(1).pdf.
[7]MELL P,GRANCE T.The NTST definition of cloud computing[R].2011.
[8]姚建国,赖业宁.智能电网的本质动因和技术需求[J].电力系统自动化,2010,34(2):1-5.YAO Jianguo,LAI Yening.The essential cause and technology requirements of smart grid construction[J].Automation of Electric Power Systems,2010,34(2):1-5.
[9]张东霞,姚良忠,马文媛.中外智能电网发展战略[J].中国电机工程学报,2013,33(31):1-14.ZHANG Dongxia,YAO Liangzhong,MA Wenyuan.Development strategies of smart grid in China and abroad[J].Proceedings of the CSEE,2013,33(31):1-14.
[10]余贻鑫,刘艳丽.智能电网的挑战性问题[J].电力系统自动化,2015,39(2):1-5.DOI:10.7500/AEPS20141204007.YU Yixin,LIU Yanli.Challenging issues of smart grid[J].Automation of Electric Power Systems,2015,39(2):1-5.DOI:10.7500/AEPS20141204007.
[11]宋亚奇,周国亮,朱永利.智能电网大数据技术现状与挑战[J].电网技术,2013,37(4):927-935.SONG Yaqi,ZHOU Guoliang,ZHU Yongli.Present status challenges of big data processing in smart grid[J].Power System Technology,2013,37(4):927-935.
[12]王德文,宋亚奇,朱永利.基于云计算的智能电网信息平台[J].电力系统自动化,2010,34(22):7-12.WANG Dewen,SONG Yaqi,ZHU Yongli.Information platform of smart grid based on cloud computing[J].Automation of Electric Power Systems,2010,34(22):7-12.
[13]WANG P J.Dynamic data center operation with demandresponsive electricity price in smart grid[J].IEEE Trans on Smart Grid,2012,3(4):1743-1754.
[14]刘振亚.中国电力与能源[M].北京:中国电力出版社,2012.
[15]XUE Y S,XIAO S J.Generalized congestion of power systems:insights from the massive blackouts in India[J].Journal of Modern Power Systems and Clean Energy,2013,1(2):91-100.
[16]KATAL A,WAZID M,GOUDAR R H.Big data:issues,challenges,tools and good practices[C]//2013 Sixth International Conference on Contemporary Computing(IC3),August 8-10,2013,Noida,India:404-409.
[17]孟小峰,慈祥.大数据管理:概念、技术与挑战[J].计算机研究与发展,2013,50(1):146-169.MENG Xiaofeng,CI Xiang.Big data management:concepts,techniques and challenges[J].Journal of Computer Research and Development,2013,50(1):146-169.
[18]李国杰.大数据研究的科学价值[J].中国计算机学会通讯,2012,8(9):8-15.LI Guojie.The scientific value of big data[J].Research Communications of the CCF,2012,8(9):8-15.
[19]XUE Y S,WU J A,XIE D L,et al.Multi-agents modelling of EV purchase willingness based on questionnaires[J].Journal of Modern Power Systems and Clean Energy,2015,3(2):149-159.
[20]王珊,王会举,覃雄派,等.架构大数据:挑战、现状与展望[J].计算机学报,2011,34(10):1741-1752.WANG Shan,WANG Huiju,QIN Xiongpai,et al.Architecting big data:challenges,studies and forecasts[J].Chinese Journal of Computers,2011,34(10):1741-1752.
[21]金培权,郝行军,岳丽华.面向新型存储的大数据存储架构与核心算法综述[J].计算机工程与科学,2013,35(10):12-24.JIN Peiquan,HAO Xingjun,YUE Lihua.A survey on storage architectures and core algorithms for big data management on new storage[J].Computer Engineering&Science,2013,35(10):12-24.
[22]WU X D,ZHU X Q,WU G Q,et al.Data mining with big data[J].IEEE Trans on Knowledge and Data Engineering,2014,26(1):97-107.
[23]李建中,刘显敏.大数据的一个重要方面:数据可用性[J].计算机研究与发展,2015,50(6):1147-1162.LI Jianzhong,LIU Xianmin.An important aspect of big data:data usability[J].Journal of Computer Research and Development,2015,50(6):1147-1162.
[24]冯登国,张敏,李昊.大数据安全与隐私保护[J].计算机学报,2014,37(1):246-258.FENG Dengguo,ZAHNG Min,LI Hao.Big data security and privacy protection[J].Chinese Journal of Computers,2014,37(1):246-258.
[25]CHEN M,MAO S,LIU Y.Big data:a survey[J].Mobile Networks and Applications,2014,19(2):171-209.
[26]董朝阳,赵俊华,文福拴,等.从智能电网到能源互联网:基本概念与研究框架[J].电力系统自动化,2014,38(15):1-11.DOI:10.7500/AEPS20140613007.DONG Zhaoyang,ZHAO Junhua,WEN Fushuan,et al.From smart grid to energy internet:basic concept and research framework[J].Automation of Electric Power Systems,2014,38(15):1-11.DOI:10.7500/AEPS20140613007.
[27]Versant,NoSQL and the smart grid big data challenge[EB/OL].[2012-08-13].http://www.greentech media.com/articles/read/versant-nosql-and-the-smart-grid-big-datachallenge.
[28]薛禹胜.时空协调的大停电防御框架:(二)广域信息、在线量化分析和自适应优化控制[J].电力系统自动化,2006,30(2):1-10.XUE Yusheng.Space-time cooperative framework for defending blackouts:PartⅡreliable information,quantitative analyses and adaptive controls[J].Automation of Electric Power Systems,2006,30(2):1-10.
[29]薛禹胜,费圣英,卜凡强.极端外部灾害中的停电防御系统构思:(二)任务与展望[J].电力系统自动化,2008,32(10):1-5.XUE Yusheng,FEI Shengying,BU Fanqiang.Upgrading the blackout defense scheme against extreme disasters:PartⅡtasks and prospects[J].Automation of Electric Power Systems,2008,32(10):1-5.
[30]赵俊华,文福拴,薛禹胜,等.电力信息物理融合系统的建模分析与控制研究框架[J].电力系统自动化,2011,35(16):1-8.ZHAO Junhua,WEN Fushuan,XUE Yusheng,et al.Modeling analysis and control research framework of cyber physical power systems[J].Automation of Electric Power Systems,2011,35(6):1-8.
[31]李强,周京阳,于尔铿,等.基于混合量测的电力系统状态估计混合算法[J].电力系统自动化,2005,29(19):31-35.LI Qiang,ZHOU Jingyang,YU Erkeng,et al.A hybrid algorithm of power system state estimation based on PMU measurement and SCADA measurement[J].Automation of Electric Power Systems,2005,29(19):31-35.
[32]薛禹胜,徐伟,DONG Zhaoyang,等.关于广域测量系统及广域控制保护系统的评述[J].电力系统自动化,2007,31(15):1-5.XUE Yusheng,XU Wei,DONG Zhaoyang,et al.A review of wide area measurement system and wide area control system[J].Automation of Electric Power Systems,2007,31(15):1-5.
[2]Nature.Big data[EB/OL].[2008-09-03].http://www.nature.com/news/specials/bigdata/index.html.
[3]BRYANT R E,KATZ R H,LAZOWSKA E D.Big-data computing:creating revolutionary breakthroughs in commerce,science,and society[R].2008.
[4]Science.Special online collection:dealing with data[EB/OL].[2011-02-11].http://www.sciencemag.org/site/special/data.
[5]MANYIKA J,CHUI M,BROWN B,et al.Big data:the next frontier for innovation,competition,and productivity[R].2011.
[6]United States Department of Energy Office of Electric Transmission and Distribution.The smart grid:an introduction[EB/OL].[2015-11-03].http://www.oe.energy.gov/DocumentsandMedia/DOE_SG_Book_Single_Pages(1).pdf.
[7]MELL P,GRANCE T.The NTST definition of cloud computing[R].2011.
[8]姚建国,赖业宁.智能电网的本质动因和技术需求[J].电力系统自动化,2010,34(2):1-5.YAO Jianguo,LAI Yening.The essential cause and technology requirements of smart grid construction[J].Automation of Electric Power Systems,2010,34(2):1-5.
[9]张东霞,姚良忠,马文媛.中外智能电网发展战略[J].中国电机工程学报,2013,33(31):1-14.ZHANG Dongxia,YAO Liangzhong,MA Wenyuan.Development strategies of smart grid in China and abroad[J].Proceedings of the CSEE,2013,33(31):1-14.
[10]余贻鑫,刘艳丽.智能电网的挑战性问题[J].电力系统自动化,2015,39(2):1-5.DOI:10.7500/AEPS20141204007.YU Yixin,LIU Yanli.Challenging issues of smart grid[J].Automation of Electric Power Systems,2015,39(2):1-5.DOI:10.7500/AEPS20141204007.
[11]宋亚奇,周国亮,朱永利.智能电网大数据技术现状与挑战[J].电网技术,2013,37(4):927-935.SONG Yaqi,ZHOU Guoliang,ZHU Yongli.Present status challenges of big data processing in smart grid[J].Power System Technology,2013,37(4):927-935.
[12]王德文,宋亚奇,朱永利.基于云计算的智能电网信息平台[J].电力系统自动化,2010,34(22):7-12.WANG Dewen,SONG Yaqi,ZHU Yongli.Information platform of smart grid based on cloud computing[J].Automation of Electric Power Systems,2010,34(22):7-12.
[13]WANG P J.Dynamic data center operation with demandresponsive electricity price in smart grid[J].IEEE Trans on Smart Grid,2012,3(4):1743-1754.
[14]刘振亚.中国电力与能源[M].北京:中国电力出版社,2012.
[15]XUE Y S,XIAO S J.Generalized congestion of power systems:insights from the massive blackouts in India[J].Journal of Modern Power Systems and Clean Energy,2013,1(2):91-100.
[16]KATAL A,WAZID M,GOUDAR R H.Big data:issues,challenges,tools and good practices[C]//2013 Sixth International Conference on Contemporary Computing(IC3),August 8-10,2013,Noida,India:404-409.
[17]孟小峰,慈祥.大数据管理:概念、技术与挑战[J].计算机研究与发展,2013,50(1):146-169.MENG Xiaofeng,CI Xiang.Big data management:concepts,techniques and challenges[J].Journal of Computer Research and Development,2013,50(1):146-169.
[18]李国杰.大数据研究的科学价值[J].中国计算机学会通讯,2012,8(9):8-15.LI Guojie.The scientific value of big data[J].Research Communications of the CCF,2012,8(9):8-15.
[19]XUE Y S,WU J A,XIE D L,et al.Multi-agents modelling of EV purchase willingness based on questionnaires[J].Journal of Modern Power Systems and Clean Energy,2015,3(2):149-159.
[20]王珊,王会举,覃雄派,等.架构大数据:挑战、现状与展望[J].计算机学报,2011,34(10):1741-1752.WANG Shan,WANG Huiju,QIN Xiongpai,et al.Architecting big data:challenges,studies and forecasts[J].Chinese Journal of Computers,2011,34(10):1741-1752.
[21]金培权,郝行军,岳丽华.面向新型存储的大数据存储架构与核心算法综述[J].计算机工程与科学,2013,35(10):12-24.JIN Peiquan,HAO Xingjun,YUE Lihua.A survey on storage architectures and core algorithms for big data management on new storage[J].Computer Engineering&Science,2013,35(10):12-24.
[22]WU X D,ZHU X Q,WU G Q,et al.Data mining with big data[J].IEEE Trans on Knowledge and Data Engineering,2014,26(1):97-107.
[23]李建中,刘显敏.大数据的一个重要方面:数据可用性[J].计算机研究与发展,2015,50(6):1147-1162.LI Jianzhong,LIU Xianmin.An important aspect of big data:data usability[J].Journal of Computer Research and Development,2015,50(6):1147-1162.
[24]冯登国,张敏,李昊.大数据安全与隐私保护[J].计算机学报,2014,37(1):246-258.FENG Dengguo,ZAHNG Min,LI Hao.Big data security and privacy protection[J].Chinese Journal of Computers,2014,37(1):246-258.
[25]CHEN M,MAO S,LIU Y.Big data:a survey[J].Mobile Networks and Applications,2014,19(2):171-209.
[26]董朝阳,赵俊华,文福拴,等.从智能电网到能源互联网:基本概念与研究框架[J].电力系统自动化,2014,38(15):1-11.DOI:10.7500/AEPS20140613007.DONG Zhaoyang,ZHAO Junhua,WEN Fushuan,et al.From smart grid to energy internet:basic concept and research framework[J].Automation of Electric Power Systems,2014,38(15):1-11.DOI:10.7500/AEPS20140613007.
[27]Versant,NoSQL and the smart grid big data challenge[EB/OL].[2012-08-13].http://www.greentech media.com/articles/read/versant-nosql-and-the-smart-grid-big-datachallenge.
[28]薛禹胜.时空协调的大停电防御框架:(二)广域信息、在线量化分析和自适应优化控制[J].电力系统自动化,2006,30(2):1-10.XUE Yusheng.Space-time cooperative framework for defending blackouts:PartⅡreliable information,quantitative analyses and adaptive controls[J].Automation of Electric Power Systems,2006,30(2):1-10.
[29]薛禹胜,费圣英,卜凡强.极端外部灾害中的停电防御系统构思:(二)任务与展望[J].电力系统自动化,2008,32(10):1-5.XUE Yusheng,FEI Shengying,BU Fanqiang.Upgrading the blackout defense scheme against extreme disasters:PartⅡtasks and prospects[J].Automation of Electric Power Systems,2008,32(10):1-5.
[30]赵俊华,文福拴,薛禹胜,等.电力信息物理融合系统的建模分析与控制研究框架[J].电力系统自动化,2011,35(16):1-8.ZHAO Junhua,WEN Fushuan,XUE Yusheng,et al.Modeling analysis and control research framework of cyber physical power systems[J].Automation of Electric Power Systems,2011,35(6):1-8.
[31]李强,周京阳,于尔铿,等.基于混合量测的电力系统状态估计混合算法[J].电力系统自动化,2005,29(19):31-35.LI Qiang,ZHOU Jingyang,YU Erkeng,et al.A hybrid algorithm of power system state estimation based on PMU measurement and SCADA measurement[J].Automation of Electric Power Systems,2005,29(19):31-35.
[32]薛禹胜,徐伟,DONG Zhaoyang,等.关于广域测量系统及广域控制保护系统的评述[J].电力系统自动化,2007,31(15):1-5.XUE Yusheng,XU Wei,DONG Zhaoyang,et al.A review of wide area measurement system and wide area control system[J].Automation of Electric Power Systems,2007,31(15):1-5.