基于知识图谱与细胞自动机模型的配电网信息系统风险分析

doi:10.11930/j.issn.1004-9649.202206114

中国电力 ›› 2022, Vol. 55 ›› Issue (10): 23-31.DOI: 10.11930/j.issn.1004-9649.202206114

• 多元负荷用能感知及友好互动 • 上一篇下一篇

基于知识图谱与细胞自动机模型的配电网信息系统风险分析

梅冰笑, 周金辉, 孙翔

国网浙江省电力有限公司电力科学研究院，浙江杭州　310007

收稿日期:2022-06-27 修回日期:2022-08-25 出版日期:2022-10-28 发布日期:2022-10-20
作者简介:梅冰笑（1978—），男，硕士，高级工程师，从事电力系统设备管理与安全技术研究，E-mail：48733021@qq.com;周金辉（1983—），男，通信作者，博士，高级工程师（教授级），从事智能配电网技术研究与工程应用，E-mail：38892714@qq.com
基金资助:
国家自然科学基金资助项目（输变电设备表征缺陷的视频图像检测平台研制，62127803）。

Analysis of Distribution Network Information Risks Based on Knowledge Graph and Cellular Automata

MEI Bingxiao, ZHOU Jinhui, SUN Xiang

State Grid Zhejiang Electric Power Company Research Institute, Hangzhou 310007, China

Received:2022-06-27 Revised:2022-08-25 Online:2022-10-28 Published:2022-10-20
Supported by:
This work is supported by National Natural Science Foundation of China (Development of Video Image Detection Platform for Characterizing Defection of Power Transmission and Transformation Equipment, No.62127803).

摘要/Abstract

摘要： 为了刻画配电网中信息系统的风险传播过程，保障电力系统安全可靠运行，利用知识图谱与细胞自动机技术相结合的方法实现对配电网信息系统的风险分析。首先利用知识图谱方法对配电网采集的多源异构信息开展风险知识提取和融合，实现对信息系统风险的静态分析。其次，构建配电网风险分析的细胞自动机模型，设计细胞在正常状态与故障状态之间的转变机制，实现对配电网信息风险发展过程的动态分析。最后结合仿真实验，验证了所提方法能够实现对配电网信息风险跨空间传播过程的有效刻画。

关键词: 知识图谱, 配电网, 信息系统, 风险分析, 细胞自动机

Abstract: In order to describe the propagation process of the information system risks in distribution networks and ensure the safe and reliable operation of power systems, the knowledge graph and cellular automata technology are used to analyze the distribution network information system risks. Firstly, the knowledge graph method is used to extract and fuse the risk knowledge of the multi-source heterogeneous information collected from distribution networks, so as to realize static analysis of the information risks. Secondly, a cellular automata model is built for risk analysis of the distribution networks, and the transition mechanism between the normal state and the fault state of the cell is designed to realize dynamic analysis of the evolution process of the distribution network information risks. Finally, based on simulation experiments, it is verified that the proposed method can effectively describe the cross-spatial propagation process of the distribution network information risks.

Key words: knowledge graph, distribution network, information system, risk analysis, cellular automata

梅冰笑, 周金辉, 孙翔. 基于知识图谱与细胞自动机模型的配电网信息系统风险分析[J]. 中国电力, 2022, 55(10): 23-31.

MEI Bingxiao, ZHOU Jinhui, SUN Xiang. Analysis of Distribution Network Information Risks Based on Knowledge Graph and Cellular Automata[J]. Electric Power, 2022, 55(10): 23-31.

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参考文献

[1] 赵俊华, 文福拴, 薛禹胜, 等. 电力CPS的架构及其实现技术与挑战[J]. 电力系统自动化, 2010, 34(16): 1–7
ZHAO Junhua, WEN Fushuan, XUE Yusheng, et al. Cyber physical power systems: architecture, implementation techniques and challenges[J]. Automation of Electric Power Systems, 2010, 34(16): 1–7
[2] 刘东, 盛万兴, 王云, 等. 电网信息物理系统的关键技术及其进展[J]. 中国电机工程学报, 2015, 35(14): 3522–3531
LIU Dong, SHENG Wanxing, WANG Yun, et al. Key technologies and trends of cyber physical system for power grid[J]. Proceedings of the CSEE, 2015, 35(14): 3522–3531
[3] 郭庆来, 辛蜀骏, 孙宏斌, 等. 电力系统信息物理融合建模与综合安全评估: 驱动力与研究构想[J]. 中国电机工程学报, 2016, 36(6): 1481–1489
GUO Qinglai, XIN Shujun, SUN Hongbin, et al. Power system cyber-physical modelling and security assessment: motivation and ideas[J]. Proceedings of the CSEE, 2016, 36(6): 1481–1489
[4] YU X H, XUE Y S. Smart grids: a cyber-physical systems perspective[J]. Proceedings of the IEEE, 2016, 104(5): 1058–1070.
[5] 刘念, 余星火, 张建华. 网络协同攻击: 乌克兰停电事件的推演与启示[J]. 电力系统自动化, 2016, 40(6): 144–147
LIU Nian, YU Xinghuo, ZHANG Jianhua. Coordinated cyber-attack: inference and thinking of incident on Ukrainian power grid[J]. Automation of Electric Power Systems, 2016, 40(6): 144–147
[6] 汤奕, 陈倩, 李梦雅, 等. 电力信息物理融合系统环境中的网络攻击研究综述[J]. 电力系统自动化, 2016, 40(17): 59–69
TANG Yi, CHEN Qian, LI Mengya, et al. Overview on cyber-attacks against cyber physical power system[J]. Automation of Electric Power Systems, 2016, 40(17): 59–69
[7] 丁明, 李晓静, 张晶晶. 面向SCADA的网络攻击对电力系统可靠性的影响[J]. 电力系统保护与控制, 2018, 46(11): 37–45
DING Ming, LI Xiaojing, ZHANG Jingjing. Effect of SCADA-oriented cyber attack on power system reliability[J]. Power System Protection and Control, 2018, 46(11): 37–45
[8] 倪明, 颜诘, 柏瑞, 等. 电力系统防恶意信息攻击的思考[J]. 电力系统自动化, 2016, 40(5): 148–151
NI Ming, YAN Jie, BO Rui, et al. Power system cyber attack and its defense[J]. Automation of Electric Power Systems, 2016, 40(5): 148–151
[9] 王琦, 李梦雅, 汤奕, 等. 电力信息物理系统网络攻击与防御研究综述(一):建模与评估[J]. 电力系统自动化, 2019, 43(9): 9–21
WANG Qi, LI Mengya, TANG Yi, et al. A review on research of cyber-attacks and defense in cyber physical power systems: part one: modelling and evaluation[J]. Automation of Electric Power Systems, 2019, 43(9): 9–21
[10] 叶夏明, 文福拴, 尚金成, 等. 电力系统中信息物理安全风险传播机制[J]. 电网技术, 2015, 39(11): 3072–3079
YE Xiaming, WEN Fushuan, SHANG Jincheng, et al. Propagation mechanism of cyber physical security risks in power systems[J]. Power System Technology, 2015, 39(11): 3072–3079
[11] 苏盛, 吴长江, 马钧, 等. 基于攻击方视角的电力CPS网络攻击模式分析[J]. 电网技术, 2014, 38(11): 3115–3120
SU Sheng, WU Changjiang, MA Jun, et al. Attacker's perspective based analysis on cyber attack mode to cyber-physical system[J]. Power System Technology, 2014, 38(11): 3115–3120
[12] 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
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
[13] 王守相, 梁栋, 葛磊蛟. 智能配电网态势感知和态势利导关键技术[J]. 电力系统自动化, 2016, 40(12): 2–8
WANG Shouxiang, LIANG Dong, GE Leijiao. Key technologies of situation awareness and orientation for smart distribution systems[J]. Automation of Electric Power Systems, 2016, 40(12): 2–8
[14] 杨胜春, 汤必强, 姚建国, 等. 基于态势感知的电网自动智能调度架构及关键技术[J]. 电网技术, 2014, 38(1): 33–39
YANG Shengchun, TANG Biqiang, YAO Jianguo, et al. Architecture and key technologies for situational awareness based automatic intelligent dispatching of power grid[J]. Power System Technology, 2014, 38(1): 33–39
[15] 马世英, 刘道伟, 汤涌, 等. 基于多响应信息源的电压稳定全态势量化评估与辅助决策系统[J]. 电网技术, 2013, 37(8): 2151–2156
MA Shiying, LIU Daowei, TANG Yong, et al. Multi-response information sources based whole situation quantitative assessment of voltage stability and decision support system[J]. Power System Technology, 2013, 37(8): 2151–2156
[16] 唐文虎, 牛哲文, 赵柏宁, 等. 数据驱动的人工智能技术在电力设备状态分析中的研究与应用[J]. 高电压技术, 2020, 46(9): 2985–2999
TANG Wenhu, NIU Zhewen, ZHAO Boning, et al. Research and application of data-driven artificial intelligence technology for condition analysis of power equipment[J]. High Voltage Engineering, 2020, 46(9): 2985–2999
[17] 王鑫, 傅强, 王林, 等. 知识图谱可视化查询技术综述[J]. 计算机工程, 2020, 46(6): 1–11
WANG Xin, FU Qiang, WANG Lin, et al. Survey on visualization query technology of knowledge graph[J]. Computer Engineering, 2020, 46(6): 1–11
[18] 乔骥, 王新迎, 闵睿, 等. 面向电网调度故障处理的知识图谱框架与关键技术初探[J]. 中国电机工程学报, 2020, 40(18): 5837–5849
QIAO Ji, WANG Xinying, MIN Rui, et al. Framework and key technologies of knowledge-graph-based fault handling system in power grid[J]. Proceedings of the CSEE, 2020, 40(18): 5837–5849
[19] 李新鹏, 徐建航, 郭子明, 等. 调度自动化系统知识图谱的构建与应用[J]. 中国电力, 2019, 52(2): 70–77,157
LI Xinpeng, XU Jianhang, GUO Ziming, et al. Construction and application of knowledge graph of power dispatching automation system[J]. Electric Power, 2019, 52(2): 70–77,157
[20] 吴小刚, 许士锦, 陈兴望, 等. 基于知识图谱的电网智能调度辅助决策系统设计[J]. 信息技术, 2021, 45(12): 60–65
WU Xiaogang, XU Shijin, CHEN Xingwang, et al. Design of power grid intelligent dispatching assistant decision system based on knowledge graph[J]. Information Technology, 2021, 45(12): 60–65
[21] 施正钗, 郑俊翔, 周泰斌, 等. 基于语义分析的设备监控告警信息知识图谱构建研究[J]. 浙江电力, 2020, 39(8): 83–87
SHI Zhengchai, ZHENG Junxiang, ZHOU Taibin, et al. Study on knowledge graph construction of equipment monitoring and alarming information based on semantic analysis[J]. Zhejiang Electric Power, 2020, 39(8): 83–87
[22] 付鑫, 郭阳, 聂玲, 等. 基于知识图谱技术的电网运营监测分析系统设计[J]. 供用电, 2021, 38(7): 45–50
FU Xin, GUO Yang, NIE Ling, et al. Design of power grid operation monitoring and analysis system based on knowledge graph technology[J]. Distribution & Utilization, 2021, 38(7): 45–50
[23] 于乃功, 阮晓钢. 细胞自动机及其在复杂系统研究中的应用[J]. 计算机工程与应用, 2004, 40(12): 25–28,54
YU Naigong, RUAN Xiaogang. Cellular automata and its applications in complex system study[J]. Computer Engineering and Applications, 2004, 40(12): 25–28,54
[24] 方锡康, 周纯杰. 基于细胞自动机的电力CPS安全风险预测方法[J]. 信息技术, 2020, 44(10): 7–11,18
FANG Xikang, ZHOU Chunjie. Prediction method of power cyber-physical system security risk based on cellular automata[J]. Information Technology, 2020, 44(10): 7–11,18
[25] 李钊, 徐国爱, 班晓芳, 等. 基于元胞自动机的复杂信息系统安全风险传播研究[J]. 物理学报, 2013, 62(20): 200203
LI Zhao, XU Guoai, BAN Xiaofang, et al. Complex information system security risk propagation research based on cellular automata[J]. Acta Physica Sinica, 2013, 62(20): 200203
[26] 于群, 曹娜, 郭剑波. 基于元胞自动机的电力系统自组织临界特性仿真模型[J]. 电力系统自动化, 2011, 35(21): 1–5
YU Qun, CAO Na, GUO Jianbo. Power system self-organized criticality simulation model based on cellular automata[J]. Automation of Electric Power Systems, 2011, 35(21): 1–5

基于知识图谱与细胞自动机模型的配电网信息系统风险分析

Analysis of Distribution Network Information Risks Based on Knowledge Graph and Cellular Automata

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基于知识图谱与细胞自动机模型的配电网信息系统风险分析

Analysis of Distribution Network Information Risks Based on Knowledge Graph and Cellular Automata

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