Power distribution network information physical system risk assessment method and system under information attack

Abstract

The invention discloses a power distribution network information physical system risk assessment method and system under information attack. The method comprises the following steps: collecting operation risk data of a power distribution network information physical system; establishing a power distribution network information physical system risk assessment framework, and analyzing a dependency relationship between an information system and a power system; information physical dependence is considered, the attack probability is calculated, and the degree of harm caused by attacks is analyzed; and according to the attack probability and the hazard degree, constructing a power distribution network power supply recovery model, and performing power distribution network information physical system risk assessment. According to the method, the coupling relationship between an information system and a physical system is combined, and risks of different levels can be comprehensively identified and evaluated, including the internal risk of a single system and the cross-system coupling risk. The recovery capability of the system after the information attack is evaluated, the recovery strategy is optimized, and the rapid recovery capability of the system is improved. Through calculation of the node risk coupling degree, the most fragile part in the system is determined, and operation and maintenance personnel are helped to solve the problem of high-risk nodes preferentially.

Description

Technical Field

[0001] The present invention relates to the technical field of power system engineering, and in particular to a method and system for risk assessment of a cyber-physical system of a distribution network under information attacks. Background Art

[0002] CPDS improves the reliability and efficiency of distribution network operation with the help of advanced sensor measurement systems and flexible communication infrastructure, but it also brings potential information security threats. Due to the close integration of information systems and power systems in CPDS, attackers may conduct cross-space risk transmission for risks caused by information systems, and overlap with traditional power system risks, thereby affecting the stable operation of distribution networks. Therefore, it is necessary to conduct risk assessment of distribution networks under information attacks to provide a basis for the planning, construction and risk mitigation of distribution networks.

[0003] At present, many scholars have studied the risks of CPDS. The risks of distribution terminals and distribution substations are calculated by calculating the probability and harm of information attacks on circuit breakers and section switches. The prior art proposes an evaluation model to quantify the impact of information failures on active distribution networks, and evaluates the impact of network traffic, component failure rate, and topology on the system. The prior art proposes a risk assessment method for active distribution networks considering FA systems, using the BAG model to calculate the success probability of attacks, and analyzing the physical response of FA systems to information attacks in combination with the output fluctuations of distributed power sources. The impact of information system anomalies on distribution networks under distributed FA mode, and on this basis, a reliability assessment model considering information attacks and information equipment is established. The consequences of different types of information disturbances on information systems are uniformly characterized as the status of information network topology, information integrity, and availability, and a distribution network evaluation framework that simultaneously considers multiple types of information disturbances is constructed. Although the above studies all indicate that the interaction between the distribution network information system and the power system is considered, in fact, only the impact of the abnormal state of the information system on the power system is considered, while the impact of the power system on the operating state of the information system is ignored. Summary of the invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] Therefore, the technical problem solved by the present invention is: how to quantify the risk of the information-physical system of the distribution network under information attacks, grasp the risk status of the system, and effectively improve the risk management level of the system.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: a method for risk assessment of a distribution network cyber-physical system under information attack, comprising:

[0007] Collecting data on the operation risks of the cyber-physical system of the distribution network;

[0008] Establish a risk assessment framework for the cyber-physical system of distribution networks and analyze the dependencies between the cyber system and the power system;

[0009] Consider information-physical dependencies and calculate attack probabilities to analyze the extent of damage caused by attacks;

[0010] According to the attack probability and the degree of damage, a distribution network power supply restoration model is constructed to conduct a risk assessment of the distribution network's cyber-physical system.

[0011] As a preferred solution of the risk assessment method of the information-physical system of the distribution network under information attack described in the present invention, wherein: the establishment of the risk assessment framework of the information-physical system of the distribution network includes: the construction of the risk index is based on the analysis object and the analysis method, specifically, the expected harm of the event to the system is expressed by the product of the event probability and its harm; the general calculation formula of CPDS risk assessment is expressed as:

[0012]

[0013] Among them, R sys represents system risk; E represents the set of events; P e represents the probability of event e; C e It represents the harm caused by accident e. To carry out a specific risk assessment of CPDS, it is necessary to conduct a quantitative analysis starting from the calculation of attack probability and the quantification of attack harm.

[0014] As a preferred scheme of the risk assessment method of the information-physical system of the distribution network under the information attack described in the present invention, wherein: the dependency relationship between the information system and the power system includes, according to the device type and the mapping relationship, abstracting the system to obtain the power topology and the information topology, and determining the mutual dependency relationship between the information element and the power element; in CPDS, the dependency between the information system and the power system includes monitoring dependency and energy dependency; monitoring dependency includes that the monitoring and scheduling of the power element are realized by the information element having a dependency relationship with it; energy dependency includes that the energy required for the operation of the information element is provided by the power element having an energy dependency relationship with it.

[0015] As a preferred solution of the risk assessment method of the information-physical system of the distribution network under information attack described in the present invention, the consideration of information-physical dependence and calculation of attack probability include using CVSS to quantify the initial probability of the security vulnerability being exploited when all attack conditions are met, and assigning a value to the initial probability of the attack condition; the relationship between the security vulnerability and the attack condition is expressed as follows:

[0016]

[0017] in, represents the initial probability of vulnerability f; represents the actual probability of vulnerability f, which means the probability of the vulnerability being successfully exploited under the premise of considering the pre-attack conditions; represents the initial probability of the safety condition g; represents the actual probability of the safety condition g; Represents the set of all pre-attack conditions of security vulnerability f; Represents the set of all preceding security vulnerabilities of attack condition g; CVSS (vul f ) represents the score of security vulnerability f in CVSS;

[0018] According to the BAG model, the probability that the kth RTU is successfully invaded by an attacker is expressed as:

[0019]

[0020] in, Indicates the probability that an attacker obtains user(4) privileges.

[0021] As a preferred solution of the risk assessment method of the information-physical system of the distribution network under information attack described in the present invention, the degree of harm caused by the attack includes that the probability of the attacker launching an attack on an attack event containing multiple targets is expressed as the cumulative multiplication of the probabilities of each target, and the formula is expressed as follows:

[0022]

[0023] in, represents the set of target RTUs in attack combination e; represents the probability of the kth RTU being successfully attacked;

[0024] D=[d 1 ,d 2 ,d 3 ,...,d i ]

[0025] Among them, d i Indicates that the control center receives the fault signal uploaded by the i-th RTU. i When the value is 1, it indicates a positive fault current, d i A value of -1 indicates a negative fault current; when d i A value of 0 indicates no fault current;

[0026] Assume that the fault occurs on line B x , then the probability that the control center receives the fault current path D can be expressed as:

[0027]

[0028] Where T represents the combination of all RTUs on the feeder; c i ,x represents B x The current state of the i-th RTU when the fault occurs; p(d i |c i,x ) indicates that when the current state detected by the RTU is c i ,x, the signal received by the control center is d i The conditional probability of

[0029] The control center determined that the fault occurred on line B. x The probability formula is expressed as:

[0030]

[0031] Where H represents the set of all lines on the feeder.

[0032] As a preferred solution of the risk assessment method of the information-physical system of the distribution network under information attack described in the present invention, wherein: the construction of the distribution network power supply recovery model includes that the goal of power supply recovery is to reduce the economic loss of the system when the system topology changes, and the formula is expressed as:

[0033]

[0034] Among them, P shed,j represents the active power reduction of load bus j; C sedf represents the outage cost calculated by the department customer hazard function; T j Indicates the power outage time of bus j; D j represents the load type on bus j; N represents the set of all buses;

[0035] The Dist-Flow equation is used to establish the power flow equation, and the node power balance equation is expressed as:

[0036]

[0037] Among them, P ij and Q ij Represents the active and reactive power flowing through line ij; Q Shed,j represents the reactive power reduction of load bus j; P L,j and P L,j Respectively represent the active and reactive loads of bus j; P DG ,j represents the active power of distributed energy on bus j; Q DG ,j represents the reactive power of distributed energy on bus j; P Sub,j and Q Sub,jare the active and reactive power outputs of the substation at bus j, respectively; the line flow direction is set to be positive, the node in the inflow direction of bus j is the parent node, and the node in the outflow direction of bus j is the child node, δ(j) and λ(j) represent the parent node set and child node set of bus j, respectively;

[0038] The voltage constraint between adjacent nodes is expressed as:

[0039]

[0040] Among them, c ij represents the state of line ij, c ij =1 means the circuit breaker is closed, c ij =0 means the circuit breaker is in the disconnected state; U j represents the voltage of bus j; U 0 Indicates rated voltage; r ij and x ij Respectively represent the resistance and reactance of line ij; M represents a sufficiently large constant; the bus voltage constraint can be expressed as:

[0041] U min,j ≤U j ≤U max,j

[0042] Among them, U min,j and U max,j represents the lower and upper limits of the voltage of bus j; the output power constraint of distributed energy can be expressed as:

[0043]

[0044] in, represents the upper limit of the active power of distributed energy on bus j and represents the upper limit of the reactive power of distributed energy on bus j;

[0045] Combining the characteristics of information and power components in the distribution network, the cyber-physical dependency constraints are constructed, and the formula is expressed as:

[0046]

[0047] in, Indicates the power supply valid flag of information element m; D m represents the set of power elements connected to the information element m; α represents a parameter that defines the degree of dependence of the information system on the power system, and its value range is [0,1]. The larger the value, the stronger the dependence of the information system on the power system; if α is close to 1, it means that the power shortage of the power system makes the information element fail;

[0048] For distributed energy, when the corresponding spatial element is in a failed state, considering safety, the distributed energy will exit operation. The constraint formula is expressed as:

[0049]

[0050] in, Represents the active power output of the distributed energy corresponding to the information element m; Represents the reactive power output by the distributed energy corresponding to the information element m; Indicates the upper limit of the active power output of the distributed energy corresponding to the information element m; Indicates the reactive power upper limit of the distributed energy output corresponding to the information element m;

[0051] When the corresponding information element is in a failed state, the load power cannot be adjusted, which means that the load power cannot be reduced. The load power constraint formula is expressed as:

[0052]

[0053] in, Indicates the active power reduction of the load element corresponding to the information element m; Indicates the reactive power reduction of the load element corresponding to the information element m; Indicates the upper limit of active power reduction of the load element corresponding to the information element m; Indicates the upper limit of reactive power reduction of the load element corresponding to the information element m.

[0054] As a preferred solution of the method for risk assessment of the information-physical system of the distribution network under information attack described in the present invention, the risk assessment of the information-physical system of the distribution network includes: inputting CPDS parameters, calculating the probability of RTU being invaded, and setting the attack state m=1; the control center analyzes the signal uploaded by the RTU to determine whether to issue a switch control instruction; if so, perform fault isolation and load transfer; consider information dependence to restore the power supply of the distribution network, if not, evaluate the interruption cost; if the termination condition is met, calculate the system risk, if not, m=m+1 and continue to iterate;

[0055] Monte Carlo simulation is used to calculate the risk, and the formula is expressed as;

[0056]

[0057] Among them, N m is the number of sampling simulations; C m The hazards under attack scenario m; introduce auxiliary variables and linearize the constraints, the formula is expressed as:

[0058]

[0059] Here, ε represents a small positive value.

[0060] A risk assessment system for a distribution network cyber-physical system under information attack using any of the methods described in the present invention, characterized in that:

[0061] The data acquisition and preprocessing module collects real-time data from various information systems and physical systems in the distribution network; performs data cleaning and preprocessing to ensure data accuracy and consistency;

[0062] The control center module analyzes the signals uploaded by the data acquisition and preprocessing modules, controls fault isolation, load transfer, and restores power supply to the distribution network;

[0063] The risk assessment framework module establishes a risk assessment model for the information-physical coupling system of the distribution network; calculates the dependencies between the information system and the physical system, simulates attack scenarios, quantifies the damage after a successful attack, and evaluates the system's recovery capabilities;

[0064] The attack analysis and impact calculation module analyzes the impact of different types of information attacks on the system, receives data from the risk assessment framework module, calculates and gives the optimal strategy, and transmits it to the control center module for control.

[0065] A computer device comprises: a memory and a processor; the memory stores a computer program, wherein the processor implements the steps of any one of the methods of the present invention when executing the computer program.

[0066] A computer-readable storage medium stores a computer program, wherein the computer program, when executed by a processor, implements the steps of any one of the methods of the present invention.

[0067] Beneficial effects of the present invention: The present invention combines the coupling relationship between information systems and physical systems, and can comprehensively identify and evaluate risks at different levels, including risks within a single system and coupling risks across systems. Using Monte Carlo simulation and Bayesian network models, the potential impact of different types of information attacks on the distribution network can be accurately quantified, providing detailed risk analysis results. By analyzing the impact of different types of attacks on the system, targeted defense measures are proposed to improve the system's ability to protect against potential attacks, and preventive defense measures are adopted to improve system resilience. Evaluate the system's recovery capabilities after an information attack, optimize the recovery strategy, shorten the power outage time, and improve the system's rapid recovery capabilities. By calculating the node risk coupling degree, the most vulnerable parts of the system are identified, helping operation and maintenance personnel to prioritize solving problems at high-risk nodes. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. Among them:

[0069] Figure 1 An overall flow chart of a method for risk assessment of a cyber-physical system of a distribution network under information attack provided by the first embodiment of the present invention;

[0070] Figure 2 An operation logic diagram of a method for risk assessment of a cyber-physical system of a distribution network under information attack provided by a second embodiment of the present invention;

[0071] Figure 3 A diagram of simulation results under different circumstances of a method for risk assessment of a distribution network cyber-physical system under information attack provided in the second embodiment of the present invention. DETAILED DESCRIPTION

[0072] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0073] Example 1

[0074] Reference Figure 1 , which is an embodiment of the present invention, provides a method for risk assessment of a cyber-physical system of a distribution network under information attack, comprising:

[0075] S1: Collect operational risk data of the cyber-physical system of the distribution network.

[0076] Furthermore, in the process of calculating the harm of information attacks, it is necessary to use indicators such as stability and economy to measure the impact of attack events on the power system under information-physical interaction. The study of the interaction between information systems and power systems is the basis for analyzing the harm of attacks.

[0077] Furthermore, the relationship between the information system and the power system is divided into four types: direct impact of information components on power components, direct impact of information networks on power components, indirect impact of information components on power components, and indirect impact of information networks on power components. The information-physical interaction relationship is simplified into direct effects and indirect effects.

[0078] Furthermore, by giving the CPDS risk assessment framework, the interdependence between the information system and the power system is considered to analyze the alternating transmission process of risks across the cyber-physical space. Regarding information attacks, an attack method that misleads the judgment of the FA system by tampering with the monitoring data of the RTU is analyzed, and the BAG model is used to quantify the success probability of information attacks.

[0079] Furthermore, for the attack hazards, a power supply restoration model is established considering the interdependence of information and physical systems, and the attack hazards are quantified from the scale and duration of power outages. The risk of distribution network under information attack is quantitatively evaluated through comprehensive measurement of attack probability and hazard. Simulations are carried out based on the improved IEEE 33-node system and the improved CPS 62-node system to verify the effectiveness of the proposed method.

[0080] It should be noted that the power grid CPS covers a variety of risk scenarios, and the risk types, risk indicators and adopted algorithms in different scenarios are different. In the risk assessment of specific scenarios, the proposed risk assessment framework can be simplified, equivalent and adjusted according to the characteristics of the scenario, so that the proposed risk assessment framework can be used in more risk scenarios. Based on the risk framework, the Monte Carlo sampling algorithm is used to quantify the expected load loss of the active distribution network caused by information attacks.

[0081] S2: Establish a risk assessment framework for the cyber-physical system of distribution networks and analyze the dependencies between the information system and the power system.

[0082] Furthermore, the establishment of a risk assessment framework for the information-physical system of the distribution network includes the construction of risk indicators based on the analysis object and analysis method, specifically, the expected harm of the event to the system is expressed by the product of the event probability and its harm; the general calculation formula of CPDS risk assessment is expressed as:

[0083]

[0084] Among them, R sys represents system risk; E represents the set of events; P e represents the probability of event e; C e It represents the harm caused by accident e. To carry out a specific risk assessment of CPDS, it is necessary to conduct a quantitative analysis starting from the calculation of attack probability and the quantification of attack harm.

[0085] Furthermore, the dependency relationship between the information system and the power system includes, based on the equipment type and mapping relationship, abstracting the system to obtain the power topology and information topology, and determining the mutual dependency relationship between the information elements and the power elements; in CPDS, the dependency between the information system and the power system includes monitoring dependency and energy dependency; monitoring dependency includes that the monitoring and scheduling of the power elements are realized by the information elements with which there is a dependency relationship; energy dependency includes that the energy required for the operation of the information elements is provided by the power elements with which there is an energy dependency relationship.

[0086] Furthermore, the impact of abnormal conditions caused by information attacks on the operating state of the power system is considered, that is, the impact of information attacks on the "closed-loop control" process of measurement acquisition, fault handling / power regulation, command execution and state change is analyzed.

[0087] Furthermore, the second method not only considers the impact of the information system on the power system, but also analyzes the impact of insufficient power system energy supply on the operating status of the information system.

[0088] It should be noted that the first method is a traditional CPDS risk assessment method, which only considers the dependence of the power system on the information system. In this mode, the risks in the information system can be transmitted to the power system, while the risks in the power system cannot affect the operating status of the information components. The second method is the risk assessment method considering information dependence proposed in this chapter, which not only considers the dependence of the power system on the information system, but also the dependence of the information system on the power system.

[0089] S3: Consider information-physical dependencies and calculate attack probabilities to analyze the extent of damage caused by attacks.

[0090] Furthermore, the consideration of information physical dependency and calculation of attack probability includes using CVSS to quantify the initial probability of a security vulnerability being exploited when all attack conditions are met, and assigning a value to the initial probability of the attack condition; the relationship between the security vulnerability and the attack condition is expressed as follows:

[0091]

[0092] in, represents the initial probability of vulnerability f; represents the actual probability of vulnerability f, which means the probability of the vulnerability being successfully exploited under the premise of considering the pre-attack conditions; represents the initial probability of the safety condition g; represents the actual probability of the safety condition g; Represents the set of all pre-attack conditions of security vulnerability f; Represents the set of all preceding security vulnerabilities of attack condition g; CVSS (vul f) represents the score of security vulnerability f in CVSS.

[0093] Furthermore, according to the BAG model, the probability that the kth RTU is successfully invaded by an attacker is expressed as:

[0094]

[0095] in, Indicates the probability that an attacker obtains user(4) privileges.

[0096] Furthermore, the degree of harm caused by the attack includes that the probability of the attacker launching an attack on an attack event involving multiple targets is expressed as the cumulative multiplication of the probabilities of each target, and the formula is expressed as follows:

[0097]

[0098] in, represents the set of target RTUs in attack combination e; It represents the probability that the kth RTU is successfully attacked.

[0099] D=[d 1 ,d 2 ,d 3 ,...,d i ]

[0100] Among them, d i Indicates that the control center receives the fault signal uploaded by the i-th RTU. i When the value is 1, it indicates a positive fault current, d i A value of -1 indicates a negative fault current; when d i A value of 0 indicates no fault current.

[0101] Furthermore, suppose the fault occurs on line B. x , then the probability that the control center receives the fault current path D can be expressed as:

[0102]

[0103] Where T represents the combination of all RTUs on the feeder; c i ,x represents B x The current state of the i-th RTU when the fault occurs; p(d i |c i,x ) indicates that when the current state detected by the RTU is c i ,x, the signal received by the control center is d i The conditional probability of

[0104] Furthermore, the control center determined that the fault occurred on line B.x The probability formula is expressed as:

[0105]

[0106] Where H represents the set of all lines on the feeder.

[0107] It should be noted that the FA system is an important part of CPDS, which can achieve rapid self-healing of line faults through coordination between the control center, communication network and RTU to reduce the power outage time of distribution network users. The FA system locates the fault location by analyzing the grid status data monitored by the RTU, and sends corresponding control instructions to the RTU to achieve isolation of the fault area and recovery of the non-fault area. RTU plays an important role in the FA system. As the most vulnerable component in the FA system, it is very easy to become a potential target of attackers. Attackers can remotely execute unauthorized commands. By exploiting security vulnerabilities, attackers can tamper with the RTU's monitoring data to mislead the FA system's fault judgment to trigger the system's power supply recovery process, thereby causing unnecessary power outages for users.

[0108] S4: Based on the attack probability and degree of damage, a distribution network power supply restoration model is constructed to conduct a risk assessment of the distribution network cyber-physical system.

[0109] Furthermore, the construction of the distribution network power supply restoration model includes that the goal of power supply restoration is to reduce the economic loss of the system when the system topology changes, and the formula is expressed as:

[0110]

[0111] Among them, P shed,j represents the active power reduction of load bus j; C sedf represents the outage cost calculated by the department customer hazard function; T j Indicates the power outage time of bus j; D j represents the load type on bus j; N represents the set of all buses.

[0112] Furthermore, the Dist-Flow equation is used to establish the power flow equation, and the node power balance equation is expressed as:

[0113]

[0114] Among them, P ij and Q ij Represents the active and reactive power flowing through line ij; Q Shed,j represents the reactive power reduction of load bus j; P L,j and P L,j Respectively represent the active and reactive loads of bus j; PDG ,j represents the active power of distributed energy on bus j; Q DG ,j represents the reactive power of distributed energy on bus j; P Sub,j and Q Sub,j are the active and reactive power outputs of the substation at bus j, respectively. The line flow direction is set to the positive direction, the node in the inflow direction of bus j is the parent node, and the node in the outflow direction of bus j is the child node. δ(j) and λ(j) represent the parent node set and child node set of bus j, respectively.

[0115] Furthermore, the voltage constraint between adjacent nodes is expressed as:

[0116]

[0117] Among them, c ij represents the state of line ij, c ij =1 means the circuit breaker is closed, c ij =0 means the circuit breaker is in the disconnected state; U j represents the voltage of bus j; U 0 Indicates rated voltage; r ij and x ij They represent the resistance and reactance of line ij respectively; M represents a sufficiently large constant.

[0118] Furthermore, the bus voltage constraint can be expressed as:

[0119] U min,j ≤U j ≤U max,j

[0120] Furthermore, U min,j and U max,j represents the lower and upper limits of the voltage of bus j; the output power constraint of distributed energy can be expressed as:

[0121]

[0122] in, represents the upper limit of the active power of distributed energy on bus j and Represents the upper limit of the reactive power of distributed energy on bus j.

[0123] Furthermore, the information in the distribution network and the characteristics of the power components are combined to construct the cyber-physical dependency constraints, which are expressed as follows:

[0124]

[0125] in, Indicates the power supply valid flag of information element m; D mrepresents the set of power elements connected to the information element m; α represents a parameter that defines the degree of dependence of the information system on the power system, and its value range is [0,1]. The larger the value, the stronger the dependence of the information system on the power system; if α is close to 1, it means that the power shortage of the power system makes the information element invalid.

[0126] Furthermore, for distributed energy, when the corresponding spatial element is in a failed state, considering safety, the distributed energy will exit operation, and the constraint formula is expressed as:

[0127]

[0128] in, Represents the active power output of the distributed energy corresponding to the information element m; Represents the reactive power output by the distributed energy corresponding to the information element m; Indicates the upper limit of the active power output of the distributed energy corresponding to the information element m; Indicates the reactive power upper limit of the distributed energy output corresponding to information element m.

[0129] Furthermore, when the corresponding information element is in a failed state, the load power cannot be adjusted, which is specifically reflected in the inability to reduce the load power; the load power constraint formula is expressed as:

[0130]

[0131] in, Indicates the active power reduction of the load element corresponding to the information element m; Indicates the reactive power reduction of the load element corresponding to the information element m; Indicates the upper limit of active power reduction of the load element corresponding to the information element m; Indicates the upper limit of reactive power reduction of the load element corresponding to the information element m.

[0132] Furthermore, if Figure 2 As shown, the risk assessment of the information-physical system of the distribution network includes: inputting CPDS parameters, calculating the probability of RTU being invaded, and setting the attack state m=1; the control center analyzes the signal uploaded by the RTU to determine whether to issue a switch control instruction; if so, perform fault isolation and load transfer; consider information dependence to restore the power supply of the distribution network, if not, evaluate the interruption cost; if the termination condition is met, calculate the system risk, if not, m=m+1 and continue to iterate.

[0133] Furthermore, Monte Carlo simulation is used to calculate the risk, and the formula is expressed as:

[0134]

[0135] Among them, N m is the number of sampling simulations; C m The hazards under attack scenario m; introduce auxiliary variables and linearize the constraints, the formula is expressed as:

[0136]

[0137] Here, ε represents a small positive value.

[0138] It should be noted that the risk obtained by the proposed risk assessment method is higher than that of the traditional assessment method, which shows that the dependence of the information system on the power system increases the CPDS risk, and the simulation of the system under different degrees of dependence shows that the system risk increases with the increase of the degree of dependence. When the attacker's level is low, the attack has little impact on the system risk, but the system risk will increase rapidly with the increase of the attacker's level, so the information security of the distribution network should receive more attention. The configuration of distributed energy can effectively alleviate the system risk under information attack, and its effect increases with the increase of distributed energy penetration in the feeder area.

[0139] On the other hand, this embodiment also provides a risk assessment system for a distribution network cyber-physical system under information attack, which includes:

[0140] The data acquisition and preprocessing module collects real-time data from various information systems and physical systems in the distribution network; performs data cleaning and preprocessing to ensure the accuracy and consistency of the data.

[0141] The control center module analyzes the signals uploaded by the data acquisition and preprocessing module, controls fault isolation and load transfer, and restores power supply to the distribution network.

[0142] The risk assessment framework module establishes a risk assessment model for the information-physical coupling system of the distribution network; calculates the dependencies between the information system and the physical system, simulates attack scenarios, quantifies the damage after a successful attack, and evaluates the system's recovery capabilities.

[0143] The attack analysis and impact calculation module analyzes the impact of different types of information attacks on the system, receives data from the risk assessment framework module, calculates and gives the optimal strategy, and transmits it to the control center module for control.

[0144] If the above functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0145] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0146] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0147] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0148] Example 2

[0149] Reference Figure 3 , which is an embodiment of the present invention, provides a risk assessment method for the information-physical system of a distribution network under information attacks. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0150] In order to verify the effectiveness of the proposed method, we compared the proposed evaluation method with the traditional method. In addition, in order to verify the rationality of the adopted Monte Carlo simulation method, we calculated the proposed method and the traditional method using analytical algorithms and Monte Carlo simulation methods, respectively, and analyzed them in the following four methods / factors:

[0151] Approach / Factor 1: Using analytical algorithms to calculate systemic risk without considering information dependence (traditional approach).

[0152] Method / Factor 2: Use an analytical algorithm to calculate systemic risk that takes information dependence into account.

[0153] Method / Factor 3: Monte Carlo simulation is used to calculate the systematic risk without considering information dependence.

[0154] Method / Factor 4: Monte Carlo simulation is used to calculate the systematic risk taking into account information dependence.

[0155] For the above four scenarios, the calculated risk results are shown in Table 1.

[0156] Table 1 Risk calculation results for different scenarios.

[0157]

[0158] The differences in risk results between methods / factors 1 and 3, and 2 and 4 are all within 1.2%, which shows that both the traditional assessment method and the assessment method proposed in this chapter can calculate the system risk within an acceptable error range by Monte Carlo simulation. In addition, the risk of method / factor 4 is about 13% higher than that of method / factor 3, which shows that information dependence has a greater impact on the risk of CPDS. Therefore, the impact of the power system on the operating status of the information system should be given enough attention, especially when the coupling relationship between the information system and the power system in the future distribution network is gradually strengthened.

[0159] The simulation results in different cases are as follows Figure 3 As shown in the figure, as the capacity of distributed energy increases, the system risk index continues to decrease. This is mainly because all loads in this example are powered by a superior power supply. When the information attack causes a bus failure near the feeder outlet, the distribution network will disconnect from the superior power supply, thereby forming an island area. The island area is completely powered by distributed energy, and the user load is greater than the distributed energy capacity in the initial state. Therefore, when the distributed energy capacity increases, the consequences of the attack in the above situation can be effectively reduced, thereby reducing the system risk.

[0160] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for risk assessment of a cyber-physical system of a distribution network under information attack, characterized in that: include: Collecting data on the operation risks of the cyber-physical system of the distribution network; Establish a risk assessment framework for the cyber-physical system of distribution networks and analyze the dependencies between the cyber system and the power system; Consider information-physical dependencies and calculate attack probabilities to analyze the extent of damage caused by attacks; According to the attack probability and the degree of damage, a distribution network power supply restoration model is constructed to conduct a risk assessment of the distribution network's cyber-physical system.

2. The method for risk assessment of a cyber-physical system of a distribution network under information attack according to claim 1, characterized in that: The establishment of the risk assessment framework of the information-physical system of the distribution network includes the construction of risk indicators based on the analysis object and analysis method, specifically, the expected harm of the event to the system is expressed by the product of the event probability and its harm; the general calculation formula of CPDS risk assessment is expressed as: Among them, R sys represents system risk; E represents the set of events; P e represents the probability of event e; C e It represents the harm caused by accident e. To carry out a specific risk assessment of CPDS, it is necessary to conduct a quantitative analysis starting from the calculation of attack probability and the quantification of attack harm.

3. The method for risk assessment of a cyber-physical system of a distribution network under information attack according to claim 2, characterized in that: The dependency relationship between the information system and the power system includes abstracting the system to obtain power topology and information topology based on device types and mapping relationships, and determining the mutual dependency relationship between information components and power components; In CPDS, the dependency between information system and power system includes monitoring dependency and energy dependency; Monitoring dependency includes that the monitoring and scheduling of power components are realized by information components that have a dependency relationship with them; Energy dependence includes that the energy required for the operation of the information element is provided by the power element with which the information element establishes an energy dependence relationship.

4. The method for risk assessment of a cyber-physical system of a distribution network under information attack according to claim 3, characterized in that: The consideration of information physical dependency and calculation of attack probability includes using CVSS to quantify the initial probability of a security vulnerability being exploited when all attack conditions are met, and assigning a value to the initial probability of the attack condition; the relationship between the security vulnerability and the attack condition is expressed as follows: in, represents the initial probability of vulnerability f; represents the actual probability of vulnerability f, which means the probability of the vulnerability being successfully exploited under the premise of considering the pre-attack conditions; represents the initial probability of the safety condition g; represents the actual probability of the safety condition g; Represents the set of all pre-attack conditions of security vulnerability f; Represents the set of all preceding security vulnerabilities of attack condition g; CVSS (vul f ) represents the score of security vulnerability f in CVSS; According to the BAG model, the probability that the kth RTU is successfully invaded by an attacker is expressed as: in, Indicates the probability that an attacker obtains user(4) privileges.

5. The method for risk assessment of a cyber-physical system of a distribution network under information attack according to claim 4, characterized in that: The degree of harm caused by the attack includes that the probability of the attacker launching an attack on an attack event involving multiple targets is expressed as the cumulative multiplication of the probabilities of each target, and the formula is expressed as follows: in, represents the set of target RTUs in attack combination e; represents the probability of the kth RTU being successfully attacked; <h2 style=";text-align:left;direction:ltr">D=[d1,d2,d3,...,d<h2 style=";text-align:left;direction:ltr"> i <h2 style=";text-align:left;direction:ltr"> ] Among them, d i Indicates that the control center receives the fault signal uploaded by the i-th RTU. i When the value is 1, it indicates a positive fault current, d i A value of -1 indicates a negative fault current; when d i A value of 0 indicates no fault current; Assume that the fault occurs on line B x , then the probability that the control center receives the fault current path D can be expressed as: Where T represents the combination of all RTUs on the feeder; c i ,x represents B x The current state of the i-th RTU when the fault occurs; p(d i |c i,x ) indicates that when the current state detected by the RTU is c i ,x, the signal received by the control center is d i The conditional probability of The control center determined that the fault occurred on line B. x The probability formula is expressed as: Where H represents the set of all lines on the feeder.

6. The method for risk assessment of a cyber-physical system of a distribution network under information attack according to claim 5, characterized in that: The construction of the distribution network power supply restoration model includes that the goal of power supply restoration is to reduce the economic loss of the system when the system topology changes. The formula is expressed as: Among them, P shed,j represents the active power reduction of load bus j; C sedf represents the outage cost calculated by the department customer hazard function; T j Indicates the power outage time of bus j; D j represents the load type on bus j; N represents the set of all buses; The Dist-Flow equation is used to establish the power flow equation, and the node power balance equation is expressed as: Among them, P ij and Q ij Represents the active and reactive power flowing through line ij; Q Shed,j represents the reactive power reduction of load bus j; P L,j and P L,j Respectively represent the active and reactive loads of bus j; P DG ,j represents the active power of distributed energy on bus j; Q DG ,j represents the reactive power of distributed energy on bus j; P Sub,j and Q Sub,j are the active and reactive power outputs of the substation at bus j, respectively; the line flow direction is set to be positive, the node in the inflow direction of bus j is the parent node, and the node in the outflow direction of bus j is the child node, δ(j) and λ(j) represent the parent node set and child node set of bus j, respectively; The voltage constraint between adjacent nodes is expressed as: Among them, c ij Indicates the state of line ij, c ij =1 means the circuit breaker is in the closed state, c ij =0 means the circuit breaker is in the disconnected state; U j represents the voltage of bus j; U0 represents the rated voltage; r ij and x ij Respectively represent the resistance and reactance of line ij; M represents a sufficiently large constant; the bus voltage constraint can be expressed as: IN min,j ≤U j ≤U max,j Among them, U min,j and U max,j represents the lower and upper limits of the voltage of bus j; the output power constraint of distributed energy can be expressed as: in, represents the upper limit of the active power of distributed energy on bus j and represents the upper limit of the reactive power of distributed energy on bus j; Combining the characteristics of information and power components in the distribution network, the cyber-physical dependency constraints are constructed, and the formula is expressed as: in, Indicates the power supply valid flag of information element m; D m represents the set of power elements connected to the information element m; α represents a parameter that defines the degree of dependence of the information system on the power system, and its value range is [0,1]. The larger the value, the stronger the dependence of the information system on the power system; if α is close to 1, it means that the power shortage of the power system makes the information element fail; For distributed energy, when the corresponding spatial element is in a failed state, considering safety, the distributed energy will exit operation. The constraint formula is expressed as: in, Represents the active power output of the distributed energy corresponding to the information element m; Represents the reactive power output of the distributed energy corresponding to the information element m; Indicates the upper limit of active power output of distributed energy corresponding to information element m; Indicates the reactive power upper limit of the distributed energy output corresponding to the information element m; When the corresponding information element is in a failed state, the load power cannot be adjusted, which means that the load power cannot be reduced. The load power constraint formula is expressed as: in, Indicates the active power reduction of the load element corresponding to the information element m; Indicates the reactive power reduction of the load element corresponding to the information element m; Indicates the upper limit of active power reduction of the load element corresponding to the information element m; Indicates the upper limit of reactive power reduction of the load element corresponding to the information element m.

7. The method for risk assessment of a cyber-physical system of a distribution network under information attack according to claim 6, characterized in that: The risk assessment of the information-physical system of the distribution network includes: inputting CPDS parameters, calculating the probability of RTU being invaded, and setting the attack state m=1; the control center analyzes the signal uploaded by the RTU to determine whether to issue a switch control instruction; if so, perform fault isolation and load transfer; consider information dependence to restore the power supply of the distribution network, if not, evaluate the interruption cost; if the termination condition is met, calculate the system risk, if not, m=m+1 and continue to iterate; Monte Carlo simulation is used to calculate the risk, and the formula is expressed as; Among them, N m is the number of sampling simulations; C m The hazards under attack scenario m; introduce auxiliary variables and linearize the constraints, the formula is expressed as: Here, ε represents a small positive value.

8. A distribution network cyber-physical system risk assessment system under information attack using the method according to any one of claims 1 to 7, characterized in that: The data acquisition and preprocessing module collects real-time data from various information systems and physical systems in the distribution network; performs data cleaning and preprocessing to ensure data accuracy and consistency; The control center module analyzes the signals uploaded by the data acquisition and preprocessing modules, and controls fault isolation and load transfer; Restoring power supply to the distribution network; The risk assessment framework module establishes a risk assessment model for the information-physical coupling system of the distribution network; calculates the dependencies between the information system and the physical system, simulates attack scenarios, quantifies the damage after a successful attack, and evaluates the system's recovery capabilities; The attack analysis and impact calculation module analyzes the impact of different types of information attacks on the system, receives data from the risk assessment framework module, calculates and gives the optimal strategy, and transmits it to the control center module for control.

9. A computer device comprising: Memory and processor; The memory stores a computer program, characterized in that when the processor executes the computer program, the steps of the method for risk assessment of the information-physical system of the distribution network under information attack are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for risk assessment of the information-physical system of a distribution network under information attacks are implemented.

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