基于大数据的电力信息网络智能风险预警策略研究及应用
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  • 英文篇名:Research and Application of Intelligent Risk Early Warning Strategy for Electric Power Information Network Based on Big Data
  • 作者:陈龙 ; 郝悍勇 ; 巢玉坚 ; 李鹏 ; 罗玲 ; 马远东 ; 胡阳
  • 英文作者:CHEN Long;HAO Hanyong;CHAO Yujian;LI Peng;LUO Ling;MA YuANDong;HU Yang;NARI Group Corporation/State Grid Electric Power Research Institute;State Grid Corporation of China;Ningbo Power Supply Company,State Grid Zhejiang Electric Power Co.,Ltd.;
  • 关键词:电力信息化 ; 网络安全 ; 大数据 ; 风险预警 ; 智能运维
  • 英文关键词:electric power information network;;network security;;big data;;risk early warning;;intelligent operation and maintenance
  • 中文刊名:DXXH
  • 英文刊名:Electric Power Information and Communication Technology
  • 机构:南瑞集团有限公司(国网电力科学研究院有限公司);国家电网有限公司;国网浙江省电力有限公司宁波供电公司;
  • 出版日期:2019-01-15
  • 出版单位:电力信息与通信技术
  • 年:2019
  • 期:v.17;No.185
  • 语种:中文;
  • 页:DXXH201901004
  • 页数:7
  • CN:01
  • ISSN:10-1164/TK
  • 分类号:22-28
摘要
基于全面提升电网信息安全防护能力和推进自主运维的需求,文章提出了基于大数据的电力信息网络智能风险预警策略。基于大数据技术,设计了包括状态预警、阈值预警、快变预警、趋势预警、评价预警、分级预警、排名预警和关联预警的信息网络风险预警方法体系,并构建了包括网络基础架构评价模型、信息系统实时可靠性评价模型和信息网络历史评价模型3个子模型的信息网络风险预警模型。原型系统已在试点单位示范应用,实现了电力信息网络运行态势全面感知、运行风险实时预警和预警事件及时处置。
        Based on the need to comprehensively enhance the information security protection capability of power grid and promote independent operation and maintenance,an intelligent risk early warning strategy of power information network based on big data is proposed.Based on big data technology,an information network risk early warning method system including state early warning,threshold early warning,fast change early warning,trend early warning,evaluation early warning,hierarchical early warning,ranking early warning and correlation early warning is designed.An information network risk early warning model including three sub-models of network infrastructure evaluation model,real-time reliability evaluation model of information system and history evaluation model of information network is constructed.The prototype system has been demonstrated and applied in pilot units.It realizes the overall perception of power information network operation situation,real-time operational risk early warning and timely disposal of early warning events.
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