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Analysis of cascading failures of power cyber-physical systems considering false data injection attacks

Analysis of cascading failures of power cyber-physical systems considering false data injection attacks

作     者:Jian Li Chaowei Sun Qingyu Su Jian Li;Chaowei Sun;Qingyu Su

作者机构:Northeast Electric Power UniversityJilin132000P.R.China 

出 版 物:《Global Energy Interconnection》 (全球能源互联网(英文版))

年 卷 期:2021年第4卷第2期

页      面:204-213页

核心收录:

学科分类:080802[工学-电力系统及其自动化] 0808[工学-电气工程] 08[工学] 

基  金:the National Natural Science Foundation of China(61873057) the Education Department of Jilin Province(JJKH20200118KJ) 

主  题:Power cyber-physical systems False date injection attack Cascading failure Vulnerability Power flow betweenness. 

摘      要:This study considers the performance impacts of false data injection attacks on the cascading failures of a power cyber-physical system,and identifies vulnerable ***,considering the monitoring and control functions of a cyber network and power flow characteristics of a power network,a power cyber-physical system model is ***,the influences of a false data attack on the decision-making and control processes of the cyber network communication processes are studied,and a cascading failure analysis process is proposed for the cyber-attack *** addition,a vulnerability evaluation index is defined from two perspectives,i.e.,the topology integrity and power network operation ***,the effectiveness of a power flow betweenness assessment for vulnerable nodes in the cyberphysical environment is verified based on comparing the node power flow betweenness and vulnerability assessment ***,an IEEE14-bus power network is selected for constructing a power cyber-physical *** show that both the uplink communication channel and downlink communication channel suffer from false data attacks,which affect the ability of the cyber network to suppress the propagation of cascading failures,and expand the scale of the cascading *** vulnerability evaluation index is calculated for each node,so as to verify the effectiveness of identifying vulnerable nodes based on the power flow betweenness.

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