Risk Analysis Of Power Cyber Physical System For Distribution And Consumption

With the rapid development of information and communication technology and automation control technology,the power grid has gradually transformed from the original physical network to the Cyber Physical System(Cyber Physical System,CPS)where information and physical systems are highly coupled.However,the information system also brings certain security risks to the power CPS when supporting the stable operation of the physical system.Therefore,this paper studied the security risk analysis of power CPS in the case of intrusion attacks.Typical attack scenarios were combined for modeling,and a cross-layer risk quantitative assessment method for power CPS was proposed.This article first summarized the current research work of domestic and foreign scholars on power CPS coupling modeling technology,power CPS attack path discovery and power CPS security risk analysis,and pointed out the deficiencies of these three aspects.At the same time,the advantages of modeling with Petri nets and the usage scenarios of different types of Petri nets were analyzed,which provided a basis and direction for the subsequent establishment of power CPS models.Secondly,in order to analyze the risk of false data injection attack(FDIA)to the power CPS,an information system model based on the random time Petri net(SPN)false data injection attack was established,which considered an information system for IDS intrusion detection.Then,a risk evaluation index for the distribution network CPS was proposed,which combined the probability of successful transfer of the attack and the consequences of the influence factors on the power side.Based on the IEEE33 node power distribution test system,a simulation analysis of the distribution network CPS model was established.After that,the risks faced by the system under false data injection attacks were analyzed,and the effectiveness of the proposed quantitative evaluation method were verified.Finally,in order to effectively evaluate the risks caused by different attack paths,this paper proposed a method of cross-domain propagation analysis of power CPS risks based on reinforcement learning.This method used Fuzzy Petri Net(FPN)to establish an attack model,and improved Q-Learning through FPN.The indicator of attack gain was defined from the attacker’s point of view to obtain the best attack path.On this basis,a quantitative indicator of information-physical cross-domain spreading risk was proposed to analyze the impact of cyber attacks on the real-time operation of the power grid.The simulation based on IEEE 14 power distribution system verified the effectiveness of the proposed risk assessment method.