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基于相依网络理论的配电信息物理系统脆弱性

Research on vulnerability analysis of cyber-physical distribution system based on interdependent network theory
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摘要 配电信息物理系统(CPDS)利用配电网与信息系统的互通与深度耦合,实现超越传统配电网系统的运行效果和性能水平的同时,也给配电系统运行的可靠性和安全性带来了潜在的负面影响。因此,考虑信息物理交互研究配电信息耦合网络的脆弱性具有重要的意义。借鉴相依网络理论的思想与方法,考虑孤岛电网运行,分析不同攻击策略下信息网络拓扑和耦合模式对CPDS的影响,探索具有强鲁棒性的CPDS网络架构。仿真结果表明:高介数节点攻击对CPDS网络模型具有最强的破坏性,并且具有小世界特性信息网络的CPDS具有最强的鲁棒性;不同的网络耦合模式面对不同的攻击方式具有不同的脆弱性,相对于随机耦合模式,同配性耦合模式面对随机攻击具有更强的鲁棒性,但对于蓄意攻击方式,同配性耦合具有更差的鲁棒性。 The cyber physical distribution system(CPDS)is designed to realize the interoperability and deep integration of physical and cyber systems,so that it can obtain better operating effects beyond the traditional distribution system.At the same time,it also brings potential negative impact on the reliability and security of distribution systems’operation.Therefore,it is of great significance to study the vulnerability of the CPDS considering cyber-physical interactions.Considering the islanded operation of power grids,this paper analyzes the influence of network topology and coupling mode under different attack strategies on CPDS,and explores the strong robustness of the CPDS network topology based on the theory of interdependent networks.The simulation results show that:high-betweenness node attack is the most destructive to CPDS network model,and the CPDS with small-world characteristic cyber network has the strongest robustness.Different network coupling modes have different vulnerabilities to different attack modes.Compared with random coupling mode,assortative coupling mode has stronger robustness to random attack,but assortative coupling mode has worse robustness to target attack mode.
作者 肖祥慧 张振山 谭海曙 XIAO Xianghui;ZHANG Zhenshan;TAN Haishu(School of Mechatronic Engineering and Automation,Foshan University,Foshan 528500,China)
出处 《电力科学与技术学报》 CAS 北大核心 2022年第4期125-133,共9页 Journal of Electric Power Science And Technology
基金 国家自然科学基金(52177132) 国家重点研发计划(2018YFB1308200 2018YFB1308203)。
关键词 配电网 信息物理系统 脆弱性 相依网络 distribution network cyber-physical system vulnerability interdependent network
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