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复杂系统与复杂性科学  2025, Vol. 22 Issue (1): 43-49    DOI: 10.13306/j.1672-3813.2025.01.006
  复杂网络 本期目录 | 过刊浏览 | 高级检索 |
基于关键节点的电力信息物理系统鲁棒性评估
胡福年, 杨伟丹, 陈军
江苏师范大学电气工程及自动化学院,江苏 徐州 221116
Robustness Assessment of Cyber-Physical Power System Based on Critical Nodes
HU Funian, YANG Weidan, CHEN Jun
School of Electrical Engineering and Automation, Jiangsu Normal University, Xuzhou 221116, China
全文: PDF(3226 KB)  
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摘要 为保证电力信息物理系统(Cyber-Physical Power System,CPPS)安全稳定运行,对其拓扑结构及鲁棒性进行研究。基于复杂网络理论,提出一种全方位CPPS鲁棒性评估框架,建立拓扑结构和功能级联故障模型,并给出相应的系统性能量化指标,实现对系统鲁棒性精准、高效评估。结合Louvain算法与重力引力中心性提出了考虑网络底层拓扑结构的节点重要性辨识方法,根据节点重要性对系统实施灾前保护,并对比不同保护策略下系统的鲁棒性。最后,用IEEE118网络构建CPPS模型,模拟系统在不同情况下的状态响应,结果验证了所提方法的有效性。
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胡福年
杨伟丹
陈军
关键词 电力信息物理系统复杂网络理论关键节点鲁棒性    
Abstract:To ensure the secure and stable operation of Cyber-Physical Power System (CPPS), research on their topology and robustness is essential. Based on the theory of complex networks, a comprehensive CPPS robustness evaluation framework is proposed, which establishes topological structures and functional cascading failure models, along with corresponding performance quantification metrics. By combining the Louvain algorithm and gravity centrality, a method for identifying the importance of nodes considering the underlying network topology is proposed. Pre-disaster protection measures are implemented based on node importance, and the robustness of the system is compared under different protection strategies. Finally, the CPPS model constructed using the IEEE118 network is used to simulate the system's state response under different conditions, verifying the effectiveness of the proposed method.
Key wordscyber-physical power system    complex network theory    critical nodes    robustness
收稿日期: 2023-07-18      出版日期: 2025-04-27
ZTFLH:  TM73  
  O157  
基金资助:国家自然科学基金(62173165);江苏师范大学研究生科研创新计划项目(2022XKT0150)
通讯作者: 杨伟丹(1998-),女,河南新乡人,硕士研究生,主要研究方向为电力信息物理系统鲁棒性。   
作者简介: 胡福年(1967-),男,江苏徐州人,博士,教授,主要研究方向为电力系统分析与控制、智能电网。
引用本文:   
胡福年, 杨伟丹, 陈军. 基于关键节点的电力信息物理系统鲁棒性评估[J]. 复杂系统与复杂性科学, 2025, 22(1): 43-49.
HU Funian, YANG Weidan, CHEN Jun. Robustness Assessment of Cyber-Physical Power System Based on Critical Nodes[J]. Complex Systems and Complexity Science, 2025, 22(1): 43-49.
链接本文:  
https://fzkx.qdu.edu.cn/CN/10.13306/j.1672-3813.2025.01.006      或      https://fzkx.qdu.edu.cn/CN/Y2025/V22/I1/43
[1] 许珞, 郭庆来, 刘新展,等. 提升电力信息物理系统韧性的通信网鲁棒优化方法[J]. 电力系统自动化, 2021, 45(3):68-75.
XU L, GUO Q L, LIU X Z, et al. Robust optimization method of communication network to improve resilience of cyber-physical power system[J]. Automation of Electric Power Systems, 2021, 45(3):68-75.
[2] PAUL S, DING F, UTKARSH F, et al. On vulnerability and resilience of cyber-physical power systems: a review[J]. IEEE Systems Journal, 2022, 16(2):2367-2378.
[3] XU L, GUO Q L, SHENG Y J, et al. On the resilience of modern power systems: a comprehensive review from the cyber-physical perspective[J]. Renewable and Sustainable Energy Reviews, 2022, 152:1364-0321.
[4] 杨得福. 恶意攻击下电力信息物理系统安全控制[D]. 吉林: 东北电力大学,2022.
YANG D F. Reliable control of power cyber physical systems under malicious attack[D]. Jilin: Northeast Electric Power University, 2022.
[5] 王思源. 基于相依网络理论的电力信息物理系统鲁棒性分析与优化[D]. 南昌: 华东交通大学, 2021.
WANG S Y. Robustness analysis and optimization of electrical cyber physical system based on interdependent networks[D]. Nanchang: East China Jiaotong University, 2021.
[6] LIU Z X, WANG L F. Leveraging network topology optimization to strengthen power grid resilience against cyber-physical attacks[J]. IEEE Transactions on Smart Grid, 2021, 12(2):1949-3053.
[7] BULDYREV S V, PARSHANI R, PAUL G, et al. Catastrophic cascade of failures in interdependent networks[J]. Nature, 2010, 464(7291):1025-1028.
[8] 薛禹胜, 李满礼, 罗剑波,等. 基于关联特性矩阵的电网信息物理系统耦合建模方法[J]. 电力系统自动化, 2018, 42(2):11-19.
XUE Y S, LI M L, LUO J B, et al. Modeling method for coupling relations in cyber physical power systems based on correlation characteristic matrix[J]. Automation of Electric Power Systems, 2018, 42(2):11-19.
[9] 伍志韬, 杜伟, 刘蕾蕾,等. 恶意攻击下的电力耦合网络风险传播模型研究[J]. 电网技术, 2020, 44(6):2045-2052.
WU Z T, DU W, LIU L L, et al. Risk propagation model of power coupled networks under malicious attack[J]. Power Grid Technology, 2020,44(6):2045-2052.
[10] 何瑞文, 龙隆, 张宝仁,等. 电力信息物理系统中信息系统物理化的建模及分析方法[J]. 中国电机工程学报, 2024, 44(1):72-85.
HE R W, LONG L, ZHANG B R, et al, Cyber system physicalizing modeling and analysis method in cyber-physical power systems[J]. Proceeding of the CSEE: 2024, 44(1):72-85.
[11] CHEN L J, HU F N, WANG S L. Cyber-physical system fusion modeling and robustness evaluation[J]. Electric Power Systems Research, 2022, 213:108654.
[12] 张晶晶, 陈博进, 吴佳瑜,等. 交直流电力信息物理系统连锁故障演化模型及风险评估[J]. 电力自动化设备, 2022, 42(5):160-166.
ZHANG J J, CHEN B J, WU J Y, et al. Cascading failure evolution model and risk assessment of AC/DC CPPS[J]. Electric Power Automation Equipment, 2022, 42(5):160-166.
[13] 陈洋, 蔡晔, 汤丽,等. 减小电网信息物理系统停电风险的信息网局部演化模型[J]. 电气工程学报, 2022, 17(3):162-169.
CHEN Y, CAI Y, TANG L, et al. Information network local evolution model for reducing outage risk of power grid cyber-physical system[J]. Chinese Journal of Electrical Engineering, 2022, 17(3):162-169.
[14] ZHOU D Y, HU F N, WANG S L, Power network robustness analysis based on electrical engineering and complex network theory[J]. Physica A: Statistical Mechanics and Its Applications, 2021, 564:125540.
[15] 李炅菊, 黄宏光, 舒勤. 相依网络理论下电力通信网节点重要度评价[J]. 电力系统保护与控制, 2019, 47(11):143-150.
LI J J, HUANG H G, SHU Q. Evaluation method for node importance in power telecommunication network based on interdependent network theory[J]. Power System Protection and Control, 2019, 47(11):143-150.
[16] 谭阳红, 罗研彬, 谭鑫,等. 电力信息物理融合系统结构脆弱性分析[J]. 湖南大学学报(自然科学版), 2018, 45(8):91-98.
TAN H Y, LUO Y B, TAN X, et al. Analysis on structural vulnerabilities of cyber physical power systems[J]. Journal of Hunan University (Natural Sciences), 2018, 45(8): 91-98.
[17] 王淑良, 陈辰, 张建华,等. 基于复杂网络的关联公共交通系统韧性分析[J]. 复杂系统与复杂性科学, 2022, 19(4):47-54.
WANG S L, CHEN C, ZHANG J H, et al. Resilience analysis of public interdependent transport system based on complex network[J]. Complex Systems and Complexity Science, 2022, 19(4):47-54.
[18] 龚钢军, 张哲宁, 张心语,等. 分布式信息能源系统的耦合模型、网络架构与节点重要度评估[J]. 中国电机工程学报, 2020, 40(17):5412-5426.
GONG G J, ZHANG Z N, ZHANG X Y, et al. Coupling model, network architecture and node importance evaluation of distributed information energy system[J]. Proceeding of the CSEE, 2020, 40(17):5412-5426.
[19] YU A Q, WANG N. Node-importance ranking in scale-free networks: a network metric response model and its solution algorithm[J]. Journal of Supercomputing, 2022, 78(15):17450-17469.
[20] ZHANG J C, FEI J C, SONG X P, et al. An improved louvain algorithm for community detection[J]. Mathematical Problems in Engineering, 2021, 2021:1485592.
[21] YAO B B, ZHU J F, MA P J, et al. A constrained louvain algorithm with a novel modularity[J]. Applied Sciences-basel, 2023, 13(6):2076-3417.
[22] MA L L, MA, C, ZHANG H F, et al. Identifying influential spreaders in complex networks based on gravity formula[J]. Physica A, 2016, 451:205-212.
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