Smart park toughness evaluation method

Abstract

The invention relates to the technical field of toughness evaluation of an information physical system, and discloses a smart park toughness evaluation method, which comprises the following steps of: establishing a double-layer graph structure for describing the characteristics of physical ring construction and information dispersion deployment of a smart park, and constructing a node association block model considering information physical coupling on the basis of the double-layer graph structure; the dynamic influence of the cyber-physical collaborative attack on the system performance is analyzed, a block failure event model in and after an accident is established, two toughness evaluation indexes of an equipment out-of-control index and a load supply stopping index are provided, and the indexes are analyzed and expressed in combination with a probability theory method. The method is not affected by the number of generated fault scenes, the dependency relationship is considered in an information physical fusion environment, and the method has good applicability to the smart park.

Description

Technical Field

[0001] The present invention relates to the technical field of resilience assessment of cyber-physical systems, and in particular to a resilience assessment method for smart parks. Background Art

[0002] Smart parks are at the end of the power cyber-physical system, with the distribution network, gas distribution network, and energy hub that converge various types of power flow control equipment as the core. By safely distributing various heterogeneous energies to high-density end-users, they support typical energy supply carriers for residential life, commercial activities, and industrial production. The deep coupling of cyber-physical systems improves the energy conversion efficiency and the digital and intelligent level of the system, but also gradually expands the threats faced by smart parks from the pure physical level to the cyber-physical level. Information-side failures (such as base station downtime) will trigger the collapse of the physical side (such as a full network power outage triggered within seconds) through the coupling relationship, exacerbating its vulnerability to cyber-physical coordinated attack events. Therefore, in order to describe the changes in functions such as energy supply, energy supply benefits, and equipment status in the fault state of the system, resilience assessment has received extensive attention from scholars at home and abroad.

[0003] In the research of resilience assessment, traditional statistical methods face the challenge of data scarcity. Especially in cyber-physical coordinated attack events with high randomness and suddenness, the available sample data is extremely limited and difficult to meet the basic requirements of statistical analysis. Therefore, current resilience assessment mainly relies on simulation methods, enumeration methods, and analytical methods. Among them, the simulation method is based on the failure probability of communication units and line pipelines, and repeatedly samples through Monte Carlo simulation and Markov processes to generate the fault state space of the system, and combines the system operation model to evaluate resilience. Although this method can consider the cyber-physical coupling characteristics of smart parks and achieve a detailed assessment of the resilience of the entire fault cycle, in systems with a low fault probability, the required number of sampling times increases significantly, resulting in low assessment efficiency; the enumeration method attempts to exhaust all possible system fault states, but its comprehensiveness is limited by the search cut-off rule and is still affected by the scenario generation efficiency; the analytical method starts from the failure probability and uses the mathematical model of complex network theory to evaluate resilience, avoiding the restriction of fault scenarios and effectively improving the resilience assessment speed, but it is difficult to achieve a full-cycle assessment of extreme events and cannot accurately reflect the cyber-physical dependence relationship of smart parks.

[0004] To sum up, the energy network and communication network of smart parks highly depend on each other for operation. When comprehensively and quickly generating the fault state space in the face of cyber-physical coordinated attacks, traditional methods only simulate physical-side faults (such as line disconnection) or information-side faults (such as base station downtime), ignoring their interaction. Therefore, existing methods cannot accurately reflect the cyber-physical dependence relationship of smart parks and have large errors in resilience assessment. Summary of the Invention

[0005] To this end, the technical problem to be solved by the present invention is to overcome the problem in the prior art that the cyber-physical dependence relationship in the park is ignored, resulting in a large error in the resilience assessment.

[0006] To solve the above technical problem, the present invention provides a method for assessing the resilience of a smart park, including:

[0007] Construct a physical subnet of the energy system with energy sources and loads as nodes and line pipelines as connection edges, and divide it into multiple energy blocks;

[0008] Construct an information subnet of the communication system with intelligent switches as nodes and communication links as connection edges, and divide it into multiple communication blocks;

[0009] Construct a node association block model for the smart park, including: for each energy block, taking the maximum recoverable load of the block as the objective function; setting the operation constraints of the functional channels of the energy block and the grid state constraints of the energy system; setting the operation state constraints of the communication system terminals of the communication block; setting the cyber-physical dependence constraints of the smart park;

[0010] Based on the non-repetitive constraints and the cyclic solution strategy, solve the node association block model of the smart park to obtain all the power supply channel indexes corresponding to each energy block;

[0011] Based on the node association block model of the smart park, collect the failure occurrence times of all the intelligent switches, line pipelines and power supply channel indexes in the block when a cyber-physical collaborative attack is launched, and calculate the failure probability of each block in the accident with the attack duration as the failure duration;

[0012] Collect the normal recovery times of all the intelligent switches, line pipelines and power supply channel indexes in the block after the cyber-physical collaborative attack ends, and calculate the post-accident failure probability of the block with the system recovery duration as the post-accident failure duration;

[0013] Based on the failure probability during the accident and the post-accident failure probability of all energy blocks, calculate the equipment out-of-control index of the smart park;

[0014] Based on the failure probability during the accident and the post-accident failure probability of all communication blocks, calculate and obtain the load outage index of the smart park;

[0015] Based on the equipment out-of-control index and the load outage index of the smart park, realize the resilience assessment of the smart park.

[0016] Preferably, constructing the node association block model of the smart park includes:

[0017] For each energy block, taking the maximum recoverable load of the block as the objective function, expressed as:

[0018] Operating constraints of the energy supply channel, including:

[0019] Virtual power flow constraint, expressed as:

[0020]

[0021] Constraint on the direction of energy flow between nodes, expressed as:

[0022] Operating state constraints of the energy system network framework, including:

[0023] First constraint of the energy supply channel, expressed as:

[0024] Second constraint of the energy supply channel, expressed as:

[0025] Third constraint of the energy supply channel, expressed as:

[0026] Fourth constraint of the energy supply channel, expressed as:

[0027] Operating state constraints of the communication system terminal, expressed as:

[0028] Cyber-physical dependence constraint, expressed as:

[0029] Among them, represents the energy supply state of the s-th energy block p in the physical subnet B ; represents that it can be supplied with energy under the current operating scenario, represents that the energy supply is cut off under the current operating scenario; Ω(s) represents the node set of the s-th energy block in the physical subnet ; represents the node load of the b-th node in the s-th energy block in the physical subnet; represents the parent node-channel incidence matrix of the energy block, represents the child node-channel incidence matrix of the energy block, represents the energy node-energy source incidence matrix, represents the energy node-gas turbine incidence matrix; f l 、f n and f u are the energy flows corresponding to the energy supply channel l, the energy source n, and the energy conversion device u respectively; represents the operating state variable of node b in the energy system, Indicates that node b can obtain power supply Indicates that node b cannot obtain power supply; Π represents the set of nodes in the energy system Represents the operating state variable of pipeline l in the energy system Indicates that pipeline l can obtain power supply Indicates that pipeline l cannot obtain power supply; Φ represents the set of all pipelines in the energy system, Φ tr Represents the set of pipelines connecting gas turbines and energy hubs in the energy system Represents the maximum capacity of the pipeline; Ω NS Represents the set of energy blocks containing energy sources, Ω N Represents the set of energy blocks without energy sources Indicates whether the current power supply channel passes through an energy block AND IF Indicates passing through. If Indicates not passing through Indicates whether the power supply channel can reach an energy block from an energy block TO an energy block Indicates that it can reach Indicates that it cannot reach Represents the physical subnet B p The power supply state variable of the i-th node in Indicates that this node can obtain power supply Indicates that this node cannot obtain power supply; Ξ(i) represents the set of pipelines within the energy block Indicates The online state variable of Indicates that the i-th base station in the communication block is online Indicates that the i-th base station is offline Represents the controlled state variable of the communication node Indicates that the switch is controllable Indicates that the switch is out of control; Δ(i) represents the set of communication nodes within the communication block, Ψ represents the set of switches installed on the external pipelines of B p

[0030] Preferably, it includes:

[0031] When the block is a communication block, collect the failure occurrence time of the intelligent switch in the communication block when the cyber-physical collaborative attack is launched, and calculate the failure duration of the communication block in the accident as the attack duration υ d The failure probability in the accident Is expressed as:

[0032] ​

[0033] Among them, represents the currently calculated communication block, and CEvent1 is communication event 1, indicating that the currently calculated communication block fails in the cyber-physical system attack; represents t e moment the set of scenarios where the intelligent switch is in a faulty state at time t; represents t e -1 moment the set of scenarios where the intelligent switch is in a normal state before the fault occurs;

[0034] When the block is an energy block, collect the fault occurrence time of the line pipeline and functional channel in the energy block when the cyber-physical collaborative attack is launched, and calculate the failure duration of the energy block in the accident as the attack duration υ d the failure probability in the accident is expressed as:

[0035]

[0036] Among them, represents the currently calculated energy block; PEvent1 is energy event 1, indicating a fault occurs in the internal line; PEvent2 is energy event 2, indicating all external power supply channels fail; represents t e moment the set of scenarios where the line pipeline is in a faulty state at time t; represents t e -1 moment the set of scenarios where the line pipeline is in a normal state before the fault occurs; SW(s, m i ) indicates the power supply channel index in; represents t e moment the set of scenarios where the power supply channel is in a faulty state at time t, represents t e -1 moment the set of scenarios where the power supply channel is in a normal state before the fault occurs.

[0037] Preferably, based on the fault occurrence probability of the communication base station under the cyber-physical collaborative attack, solve the failure probability of the communication block in the accident with the failure duration of the attack duration υ d in the accident is expressed as:

[0038]

[0039] Among them, represents the probability of failure of the currently calculated communication block at time t e , and the expression is σ s,t represents the probability of failure of communication base station s at time t.

[0040] Preferably, using the total probability formula and the conditional probability formula, based on the probability of failure of the line pipeline under the cyber-physical collaborative attack, solve the probability of failure of the energy block during the accident with the outage duration being the attack duration υ d of the accident including:

[0041]

[0042] wherein, represents the probability of failure of the currently calculated energy block at time t e , and the expression is σ l,t represents the probability of failure of line pipeline l at time t; SWE(s,i,j) is the set of energy supply channels, indicating the i-th channel after excluding the j-th energy supply channel.

[0043] Preferably, it includes:

[0044] When the block is a communication block, collect the normal recovery time of the intelligent switches in the communication block after the cyber-physical collaborative attack ends, and calculate the post-accident outage duration of the communication block as the system recovery duration υ r of the post-accident failure probability which is expressed as:

[0045]

[0046] wherein, represents the currently calculated communication block; CEvent2 is communication event 2, indicating the communication base station fault exclusion event; indicating the set of scenarios where the intelligent switches in r are in the fault state before the normal recovery time t indicating the set of scenarios where the intelligent switches in r are in the normal state at time t + 1;

[0047] When the block is an energy block, collect the normal recovery time of the line pipeline and the energy supply channels in the energy block after the cyber-physical collaborative attack ends, and calculate the post-accident outage duration of the energy block as the system recovery duration υ r of the post-accident failure probability which is expressed as:

[0048]

[0049] Among them, represents the currently calculated energy block; PEvent3 is the energy event 3, indicating troubleshooting of internal line pipelines; PEvent4 is the energy event 4, indicating troubleshooting of any external power supply channel; the set of scenarios in which the intelligent switch was in a faulty state before the normal recovery time t r ; represents the set of scenarios in which the intelligent switch is in a normal state at time t r +1; represents the set of scenarios in which the line pipeline was in a faulty state before the normal recovery time t r ; represents the set of scenarios in which the line pipeline is in a normal state at time t r +1; represents the set of scenarios in which the power supply channel was in a faulty state before the normal recovery time t r ; represents the set of scenarios in which the power supply channel is in a normal state at time t r +1; T r represents the end time of the attack.

[0050] Preferably, based on the failure probability of the communication base station under the cyber-physical collaborative attack, solve the post-accident failure duration of the communication block as the system recovery duration υ r of the post-accident failure probability is expressed as:

[0051]

[0052] Among them, when υ r +1 is less than the equipment repair time, when υ r +1 is not less than the equipment repair time, represents the r failure probability at time T

[0053] of the currently calculated communication block, and the expression is σ s,t represents the failure probability of the communication base station s at time t.

[0054] Preferably, using the total probability formula and the conditional probability formula, based on the failure probability of the line pipeline under the cyber-physical collaborative attack, calculate the post-accident failure duration of the energy block as the system recovery duration υ r The post-accident failure probability is expressed as:

[0055]

[0056] wherein, represents the failure probability of the currently calculated energy block at time T r , and the expression is σ l,t represents the failure probability of the line pipeline l at time t.

[0057] Preferably, based on the failure probability during the accident and the post-accident failure probability of all energy blocks, calculate the equipment out-of-control index of the smart park, which is expressed as:

[0058]

[0059] wherein, κ c represents the equipment out-of-control index of the smart park, T r represents the end time of the attack, T e represents the start time of the attack, T n represents the time when it returns to normal.

[0060] Preferably, based on the failure probability during the accident and the post-accident failure probability of all communication blocks, calculate and obtain the load outage index of the smart park, which is expressed as:

[0061]

[0062] wherein, κ p represents the load outage index of the smart park, T r represents the end time of the attack, T e represents the start time of the attack, T n represents the time when it returns to normal.

[0063] The above technical solutions of the present invention have the following beneficial effects compared with the prior art:

[0064] The resilience assessment method for the smart park described in the present invention constructs a physical subnet and an information subnet based on the characteristics of "physical ring construction and information decentralized deployment" in the smart park, and conducts block decomposition to construct a node-associated block model. By explicit modeling, the cyber-physical dependencies of communication base stations, intelligent switches, energy sources, loads, and connection lines are considered. Relying on the node-associated block model, the cyber-physical dependencies can be effectively mapped, and the impact of double failures of communication base stations and line pipelines under cyber-physical coordinated attacks on system performance can be effectively described, improving the accuracy of the resilience assessment of the smart park.

[0065] The present invention analyzes the dynamic impact of cyber-physical coordinated attacks on system performance, converts the cyber-physical coupling relationship into a computable probability problem, calculates the block failure probabilities of the energy block and the communication block during and after an accident, and proposes two resilience assessment indicators, namely the equipment out-of-control index and the load outage index, to evaluate the resilience of the communication block and the energy block in the smart park respectively, significantly improving the accuracy of the resilience assessment of the smart park. Moreover, based on the probabilities at different times, the resilience assessment for the entire time period can be achieved.

[0066] The present invention combines the method of probability theory, decomposes through the total probability formula and conditional probability, solves the failure probability during the accident and the failure probability after the accident, converts non-independent events into independent events for analytical calculation, and then analyzes the resilience assessment indicators, which well solves the problem of lack of attack historical data. Moreover, the resilience assessment efficiency is not affected by the scenario generation efficiency, and it has good adaptability in systems with different failure probabilities. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] In order to make the content of the present invention easier to be clearly understood, the following further details the present invention according to specific embodiments of the present invention in conjunction with the drawings, where:

[0068] Figure 1 is the step flow chart of the resilience assessment method for the smart park provided by the present invention;

[0069] Figure 2 is the schematic diagram of the block decomposition process of the smart park;

[0070] Figure 3 is the schematic diagram of the time sequence process of the smart park under cyber-physical coordinated attacks;

[0071] Figure 4 is the load schematic diagram of each energy node of the smart park energy system. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0072] The following further illustrates the present invention in conjunction with the drawings and specific embodiments, so that those skilled in the art can better understand the present invention and be able to implement it, but the embodiments cited do not limit the present invention.

[0073] Refer to Figure 1 As shown, the flowchart of the steps of the intelligent park resilience assessment method of the present invention specifically includes:

[0074] S101: Taking the energy source and load as nodes and the line pipelines as connection edges, construct the physical subnet of the energy system and divide it into multiple energy blocks;

[0075] S102: Taking the intelligent switches as nodes and the communication links as connection edges, construct the information subnet of the communication system and divide it into multiple communication blocks;

[0076] S103: Construct the intelligent park node association block model, including: for each energy block, taking the maximum recoverable load of the block as the objective function; setting the operation constraints of the functional channels of the energy block and the state constraints of the energy system grid; setting the operation state constraints of the communication system terminals of the communication block; setting the information-physical dependence constraints of the intelligent park;

[0077] S104: Based on the non-repetitive constraints and the cyclic solution strategy, solve the intelligent park node association block model to obtain all the power supply channel indexes corresponding to each energy block;

[0078] S105: Based on the intelligent park node association block model, collect the failure occurrence times of all the intelligent switches, line pipelines and power supply channel indexes in the block when the information-physical collaborative attack is launched, and calculate the failure probability of each block in the accident with the failure duration of the attack as the attack duration;

[0079] S106: Collect the normal recovery times of all the intelligent switches, line pipelines and power supply channel indexes in the block after the information-physical collaborative attack ends, and calculate the post-accident failure probability of the block with the post-accident failure duration as the system recovery duration;

[0080] S107: Based on the in-accident failure probability and the post-accident failure probability of all the energy blocks, calculate the equipment out-of-control index of the intelligent park, expressed as:

[0081]

[0082] Where κ c represents the equipment out-of-control index of the intelligent park, T r represents the attack end time, T e represents the attack start time, T n represents the normal recovery time;

[0083] S108: Based on the in-accident failure probability and the post-accident failure probability of all the communication blocks, calculate and obtain the load outage index of the intelligent park, expressed as:

[0084]

[0085] Among them, κ p represents the load cut-off index of the smart park, T r represents the end time of the attack, T e represents the start time of the attack, T n represents the time when it returns to normal;

[0086] S109: Based on the equipment out-of-control index and load cut-off index of the smart park, realize the resilience assessment of the smart park.

[0087] Specifically, in step S103, the construction of the smart park node association model includes:

[0088] S103-1: For each energy block, take the maximum recoverable load of the block as the objective function, expressed as:

[0089] S103-2: The operation constraints of the power supply channel include:

[0090] The virtual power flow constraint, expressed as:

[0091]

[0092] The constraint on the energy flow direction between nodes, expressed as:

[0093] S103-3: The state constraints of the energy system grid framework include:

[0094] The first constraint of the power supply channel, expressed as:

[0095] The second constraint of the power supply channel, expressed as:

[0096] The third constraint of the power supply channel, expressed as:

[0097] The fourth constraint of the power supply channel, expressed as:

[0098] S103-4: The operation state constraint of the communication system terminal, expressed as:

[0099] S103-5: The cyber-physical dependence constraint, expressed as:

[0100] Among them, represents the power supply state of the p s-th energy block in the physical sub-network B Indicates Can be energized under the current operating scenario, Indicates De-energized under the current operating scenario; Ω(s) represents the set of nodes in the s-th energy block in the physical subnetwork ; Represents the node load of the b-th node in the s-th energy block in the physical subnetwork; Represents the parent node-channel incidence matrix of the energy block, Represents the child node-channel incidence matrix of the energy block, Represents the energy node-energy source incidence matrix, Represents the energy node-gas turbine incidence matrix; f l 、f n And f u Are the energy flows corresponding to the energy supply channel l, the energy source n, and the energy conversion device u respectively; Represents the operating state variable of node b in the energy system, Indicates that node b can receive energy supply, Indicates that node b cannot receive energy supply; Π represents the set of nodes in the energy system; Represents the operating state variable of the pipeline l in the energy system, Indicates that the pipeline l can receive energy supply, Indicates that the pipeline l cannot receive energy supply; Φ represents the set of all pipelines in the energy system, Φ tr Represents the set of pipelines connecting gas turbines and energy hubs in the energy system; Represents the maximum capacity of the pipeline; Ω NS Represents the set of energy blocks containing energy sources, Ω N Represents the set of energy blocks that do not contain energy sources; Indicates whether the current energy supply channel passes through an energy block And If Indicates passing through, if Indicates not passing through; Indicates whether the energy supply channel can reach an energy block from an energy block To Indicates can reach, Indicates cannot reach; Represents the physical subnetwork B p The energy supply state variable of the i-th node in, Indicates that the node can receive energy supply, Indicates that the node cannot receive energy supply; Ξ(i) represents the set of pipelines within the energy block; Indicates The online state variable of, Indicates that the i-th base station in the communication block is online, indicating that the i-th base station is offline; represents the controlled state variable of the communication node, indicating that the switch is controllable, indicating that the switch is out of control; Δ(i) represents the set of communication nodes in the communication block, and Ψ represents the set of switches installed in the external line pipeline. p Set of switches installed in the external line pipeline.

[0101] The intelligent park resilience assessment method described in the present invention constructs a physical subnet and an information subnet based on the characteristics of "physical ring construction and information decentralized deployment" of the intelligent park, and performs block decomposition to construct a node-associated block model. By explicit modeling, the cyber-physical dependency relationships of communication base stations, intelligent switches, energy sources, loads, and connection lines are taken into account. Relying on the node-associated block model, the cyber-physical dependency relationships can be effectively mapped, and the impact of double failures of communication base stations and line pipelines under cyber-physical collaborative attacks on system performance can be effectively described, improving the accuracy of the intelligent park resilience assessment.

[0102] Specifically, in step S104, based on the non-repetitive constraint and the cyclic solution strategy, the intelligent park node-associated block model is solved to obtain all the supply channel indices corresponding to each energy block, including:

[0103] S104-1: Taking the maximum objective function value of the energy block as the optimization objective, the first supply channel index is obtained;

[0104] S104-2: To avoid obtaining the first supply channel index repeatedly in subsequent solutions, a non-repetitive constraint is added to force the new channel to be different from the first supply channel;

[0105] S104-3: Resolve the optimal solution of the intelligent park node-associated block model again to obtain another supply channel index until there is no feasible solution for the intelligent park node-associated block model, and all the supply channel indices are obtained.

[0106] Specifically, in step S105, when calculating the failure probability in the accident of the block, it includes the calculation of the communication block and the energy block, and the failure probability is solved based on the total probability formula and the conditional probability formula, specifically including:

[0107] S105-1: When the block is a communication block, collect the failure occurrence time of the intelligent switch in the communication block when the cyber-physical collaborative attack is launched, and calculate the failure duration of the communication block in the accident as the attack duration υ d Failure probability in the accident Expressed as:

[0108]

[0109] Among them, represents the currently calculated communication block. CEvent1 is communication event 1, indicating that the currently calculated communication block fails in the cyber-physical system attack; represents t e moment the set of scenarios where the intelligent switch is in a faulty state at time t; represents t e -1 moment the set of scenarios where the intelligent switch is in a normal state before the fault occurs;

[0110] S105-2: Using the total probability formula, based on the probability of failure of the communication base station under the cyber-physical collaborative attack, solve for the probability of failure of the communication block in the accident where the outage duration is the attack duration υ d in the accident is expressed as

[0111] Among them, represents the probability of failure of the currently calculated communication block at time t e The expression is σ s,t represents the probability of failure of communication base station s at time t;

[0112] S105-3: When the block is an energy block, collect the failure occurrence times of the line pipes and functional channels in the energy block when the cyber-physical collaborative attack is launched, and calculate the probability of failure of the energy block in the accident where the outage duration is the attack duration υ d in the accident is expressed as:

[0113]

[0114] Among them, represents the currently calculated energy block; PEvent1 is energy event 1, indicating a fault occurs in the internal line; PEvent2 is energy event 2, indicating all external energy supply channels fail; represents t e moment the set of scenarios where the line pipes are in a faulty state at time t; represents t e -1 moment the set of scenarios where the line pipes are in a normal state before the fault occurs; SW(s, m i ) indicates the energy supply channel index in; represents t e moment The set of scenarios where the in - energy supply channel is in a fault state denote t e -1 moment The set of scenarios where the in - energy supply channel is in a normal state before the fault occurrence moment;

[0115] S105 - 4: Using the total probability formula and the conditional probability formula, based on the fault occurrence probability of the line pipeline under the cyber - physical collaborative attack, solve the failure probability of the energy block in the accident where the outage duration is the attack duration υ d in the accident including:

[0116]

[0117] wherein, denote the fault occurrence probability of the current calculated energy block at time t e The expression is σ l,t denote the fault occurrence probability of the line pipeline l at time t; SWE(s, i, j) is the set of energy supply channels, denoting the i - th channel after excluding the j - th energy supply channel.

[0118] Specifically, in step S106, when calculating the post - accident failure probability of the block, it includes the calculation of the communication block and the energy block, and solves the failure probability based on the total probability formula and the conditional probability formula, specifically including:

[0119] S106 - 1: When the block is a communication block, collect the normal recovery moment of the intelligent switch in the communication block after the cyber - physical collaborative attack ends, and calculate the post - accident failure probability of the communication block where the post - accident outage duration is the system recovery duration υ r in the accident It is expressed as:

[0120]

[0121] wherein, denote the current calculated communication block; CEvent2 is communication event 2, denoting the communication base station fault exclusion event; denote the set of scenarios where the intelligent switch in r is in a fault state before the normal recovery moment t denote the set of scenarios where the intelligent switch in r is in a normal state at time t + 1;

[0122] S106 - 2: Using the total probability formula, based on the failure probability of communication base stations under cyber - physical collaborative attacks, solve for the post - accident failure duration of the communication block as the system recovery duration υ r The post - accident failure probability Is expressed as:

[0123]

[0124] Where, when υ r + 1 is less than the equipment repair time, When υ r + 1 is not less than the equipment repair time, Represents the failure probability of the currently calculated communication block at time T r The expression is σ s,t Represents the failure probability of communication base station s at time t;

[0125] S106 - 3: When the block is an energy block, collect the normal recovery times of the line pipelines and energy supply channels in the energy block after the cyber - physical collaborative attack ends, and calculate the post - accident failure duration of the energy block as the system recovery duration υ r The post - accident failure probability Is expressed as:

[0126]

[0127] Where, Represents the currently calculated energy block; PEvent3 is energy event 3, indicating Internal line pipeline fault elimination; PEvent4 is energy event 4, indicating External any energy supply channel fault elimination; The set of scenarios where the intelligent switch in r Is in a faulty state before the normal recovery time t Indicates The set of scenarios where the intelligent switch in r Is in a normal state at time t + 1; Indicates The set of scenarios where the line pipeline in r Is in a faulty state before the normal recovery time t Indicates The set of scenarios where the line pipeline in r Is in a normal state at time t + 1; Indicates The set of scenarios where the energy supply channel in r Is in a faulty state before the normal recovery time t Indicates The set of scenarios where the energy supply channel in rThe set of scenarios in the normal state at the moment of +1; T r Indicates the end moment of the attack;

[0128] S106-4: Using the total probability formula and the conditional probability formula, based on the failure probability of the line pipeline under the cyber-physical collaborative attack, calculate the post-accident failure duration of the energy block as the system recovery duration υ r The post-accident failure probability It is expressed as:

[0129]

[0130] Among them, Indicates the failure probability of the currently calculated energy block at time T r The expression is σ l,t Indicates the failure probability of the line pipeline l at time t.

[0131] The present invention analyzes the dynamic impact of cyber-physical collaborative attacks on system performance, converts the cyber-physical coupling relationship into a computable probability problem, calculates the block failure probabilities of the energy block and the communication block during and after the accident, proposes two resilience evaluation indicators, namely the equipment out-of-control index and the load outage index, to evaluate the resilience of the communication block and the energy block in the smart park respectively, significantly improves the accuracy of the resilience evaluation of the smart park, and can realize the resilience evaluation of the whole period based on the probabilities at different times. The present invention combines the method of probability theory, decomposes through the total probability formula and the conditional probability, solves the failure probability during the accident and the failure probability after the accident, converts non-independent events into independent events for analytical calculation, and then analyzes the resilience evaluation indicators, which well solves the problem of lack of attack historical data; and the resilience evaluation efficiency is not affected by the scenario generation efficiency, and has good adaptability in systems with different failure probabilities.

[0132] Based on the above embodiments, in the embodiments of the present invention, based on the smart park resilience evaluation method provided by the present invention, considering the cyber-physical coupling of the smart park, realizes the comprehensive and efficient evaluation of the resilience of the smart park under cyber-physical collaborative attacks. The specific steps include:

[0133] S201: Analyze the cyber-physical dependence relationship;

[0134] Considering that in order to avoid the situation of large-scale load loss in the downstream due to a single-point failure of the upstream energy supply channel in the power and natural gas energy systems in the smart park, a weakly looped wiring method is usually adopted during the planning and construction, and the radiation operation is maintained by adjusting the primary and secondary integrated intelligent switches. In addition, combined with the fact that the intelligent switch needs to be within the communication network as a remote control terminal and the communication base stations are usually deployed in adjacent positions, a node set V = {v1, v2,..., v N} and edge set E = {e1, e2, …, e M} form a two - layer complex network structure G = (V, E) to describe the characteristics of "physical environment construction and information decentralized deployment" in the smart park. Among them, the physical sub - network G p and the information sub - network G c On the basis of satisfying , they are respectively denoted as:

[0135] ① The urban energy system on the physical side is an undirected graph with the element set G p . The energy sources and loads are the points V p , and the lines and pipelines are the edges E p ;

[0136] ② The wireless communication network on the information side is a sparse undirected graph with the element set G c . The intelligent switches are the points V c , and the communication links are the edges E c .

[0137] S202: Generation of the node - associated block model for the smart park;

[0138] Based on the established two - layer graph structure G, define the node blocks:

[0139] ① In the graph G p , the set of points V p that are directly connected by the edge E c without passing through the point V p is denoted as the energy block B p ;

[0140] ② In the graph G c , the set of points V c that are directly connected by the edge E c (i.e., the intelligent switches sharing the same base - station signal source) is denoted as the communication block B c .

[0141] Refer to Figure 2 as the schematic diagram of the block - based decomposition process of the smart park. In the smart park shown in Figure 2 , is the node - associated block of the distribution network; and are the node - associated blocks of the natural gas network; is the node - associated block containing a gas turbine, and the energy conversion direction is indicated by a green arrow; is the node - associated block containing an energy hub. The node EH1 in the block meets the urban multi - energy load demand and is the energy distribution end - point of the distribution network and the natural gas network; In the communication network, and are two node - associated blocks containing shared signal - source switches, and the rest Bc Contains only one intelligent switch.

[0142] During normal operation, the communication base station sends control instructions to the corresponding communication block B through the allocated channel according to the established communication protocol, c so as to ensure that the energy system can operate efficiently and economically according to the radial topology. Different from the communication network that does not rely on physical media for operation, in the energy system, each energy block B p 's energy supply is not only limited by the energy distribution process in the power line and fuel pipeline, but also highly dependent on the controlled state of the intelligent switch. This dependence on physical media, combined with the characteristics of physical loop construction, results in that the energy block B without energy source p may have multiple functional channels.

[0143] To describe the energy supply channels of the energy system, a smart campus node association block model that describes the information-physical dependence relationship is established. In this model, the energy system is represented by the mathematical model of the target functional channel, and the communication network is described by a set of constraints that represent the relationship between the intelligent switch and the communication base station and its impact on the energy system. Its objective function is expressed as:

[0144] where, Ω(·) is the set of nodes in B p ; is 's energy supply state, and its value of 1 means it can be supplied with energy in the current operating scenario, and its value of 0 means it is cut off from energy supply in the current operating scenario; is the physical node load. For the electrical load node, it is characterized by the power consumption. For the gas load node, it is characterized by the gas consumption. For the multi-energy load, it is characterized by the heat consumption and power consumption.

[0145] B p The operation constraints of the energy supply channel analysis model include:

[0146] ① Virtual power flow constraint, which represents the power balance of electricity, gas, and heat energy in the energy system, and is expressed as:

[0147]

[0148] ② Pre-constraint on the energy flow direction between nodes in the energy system. In the block containing gas turbines, the energy can only flow unidirectionally;

[0149]

[0150] ③ Energy system grid state constraint:

[0151] The energy supply channel starts from B containing an energy sourcep , expressed as:

[0152] Target A power supply channel will not pass through the same B repeatedly p , expressed as:

[0153] B connected by the power supply channel p Can restore power supply, expressed as:

[0154] When restoring power supply, B p The node load and line pipeline inside can also restore power supply, expressed as:

[0155] ④ Communication network terminal operation state constraint, indicating that the controlled state of the intelligent switch is related to the online state of the base station, expressed as:

[0156]

[0157] ⑤ Cyber-physical dependence constraint, indicating that the operation state of the line outside B p is related to the controlled state of the intelligent switch, expressed as:

[0158]

[0159] Among them, Ω NS and Ω N are respectively the set of B blocks containing and not containing energy sources; Π is the set of nodes of the energy system; Φ is the set of line pipelines of the energy system; Φ p is the set of line pipelines connecting gas turbines and energy hubs; Ξ is the set of line pipelines inside B tr ; Ψ is the set of switches installed on the external line pipelines of B p ; Δ is the set of communication nodes inside B p ; f c and f l are respectively the energy flows of the line pipeline and the energy source, f s is the energy flow of the energy conversion device; u is the maximum capacity of the line pipeline; is the maximum capacity of the line pipeline; and are the parent node-channel and child node-channel association matrices of the energy system, is the energy node-energy source association matrix, is the energy node-gas turbine association matrix; is whether the required power supply channel passes through and is an integer variable, if so, the corresponding element is 1, otherwise it is 0; For the energy supply state; and are respectively the operating state variables of the energy system nodes and line pipelines, and when the energy is supplied, their values are 1, otherwise 0; is the online state variable of , when its value is 1, it means that base station i is online, and when its value is 0, it means that base station i is offline; is the controlled state variable of the communication node, when its value is 1, it means that the switch is controllable, and when its value is 0, it means out of control.

[0160] By solving the above model, an energy supply channel index of the target energy block can be obtained. In order to traverse other energy supply channels, it is necessary to combine the existing solution methods, add non-repetitive constraints to the model, and solve it iteratively to obtain all the energy supply channel indexes.

[0161] S203: Modeling of block failure events under cyber-physical collaborative attacks;

[0162] The time sequence process of the smart park under cyber-physical collaborative attacks can be divided into the continuous attack stage during the accident and the operation recovery stage after the accident; Referring to Figure 3 as shown, it is a schematic diagram of the time sequence process of the smart park under cyber-physical collaborative attacks. Among them, T e and T r are respectively the start and end times of the attack, T n is the time when the system returns to normal, υ d and υ r are respectively the block failure time period during the continuous stage of cyber-physical collaborative attacks during the accident and the block failure time period during the system recovery stage after the accident, t e = T r - υ d is the occurrence time of the block failure event during the accident, t r = T r + υ r is the end time of the block failure event after the accident.

[0163] S203-1: Probability model of block failure events during the accident;

[0164] With the initiation of cyber-physical collaborative attacks, communication base stations and line pipelines may malfunction at any time during the accident period, resulting in block failure events during the accident. During this stage, the park management agency can only issue action instructions to the intelligent switches in the service area through the surviving base stations, and adjust the system power flow and energy distribution in a timely manner through topological reconstruction to reduce the scale of power outage.

[0165] In a communication system, the block failure event in an accident is mainly composed of the situation where the intelligent switch gets out of control due to the offline of the communication base station. Taking Figure 2 the shown smart park as an example, when a failure occurs, the intelligent switches C6 and C8 sharing the information source get out of control due to the cyber-physical collaborative attack and thus remain in the off state all the time. Therefore, the event that the target block fails in the accident is the event of failure occurring in the cyber-physical collaborative attack (denoted as CEvent1).

[0166] In the energy system, the main block failure event in an accident is the load outage of nodes caused by the interruption of the energy supply channel, which is not only affected by the interruption of the line pipeline but also related to the out-of-control of the intelligent switch. Considering that the line pipeline is divided into two types: with intelligent switch and without intelligent switch, the failure event of the target block in the accident can also be divided into two categories. Taking Figure 2 the shown smart park as an example, when a failure occurs in the internal line of the block , in order to avoid the spread of the failure, the adjacent intelligent switches C2 and C3 need to be in the off state, and the energy nodes E2 and E3 are in the outage state all the time due to the interruption of all the energy supply channels; when there is no failure in the internal line, but a failure occurs in the external line or the base station , E2 and E3 can only obtain energy supply from this only remaining energy supply channel. Further, when also fails, all the nodes inside will be in the outage state all the time due to no energy supply channel. Therefore, the block failure event in the energy system accident can be represented by two mutually exclusive events, namely a failure occurs in the internal line (denoted as PEvent1) and all the external energy supply channels fail (denoted as PEvent2). After any one of the events PEvent1 and PEvent2 occurs, it will cause to fail in the accident.

[0167] Based on the above analysis, it is known that assuming the moment when the communication base station and the line pipeline fail in the accident is t e , then the probabilities that the block and the block fail in the accident with the failure event duration of υ d are respectively:

[0168]

[0169] where SW(s,m i ) is The power supply channel index, where m s is the number of power supply channels; and are respectively the scenario sets of the intelligent switch, line pipeline and power supply channel of block s at time t e in a fault state; and are respectively the scenario sets of the intelligent switch, line pipeline and power supply channel of block s in a normal state before the fault occurs.

[0170] Based on the above two probability calculation formulas, the probability model of the communication and energy blocks operating normally at t e -1 but failing at time t e in the accident can be determined.

[0171] S203-2: Probability model of block failure events after an accident;

[0172] After an accident, the park management agency implements a maintenance plan to repair the faulty communication base stations and line pipelines. Combining with system topology reconstruction, existing block failure events are eliminated to restore the system to a normal operating state.

[0173] In the communication system, block failure events after an accident mainly consist of events when the communication base stations are repaired and thus the controlled state of the intelligent switches is restored. Taking the smart park shown in Figure 2 as an example, when the fault of is eliminated, the urban energy management agency restores and maintains the remote control state of the intelligent switch C3 and can execute switch commands. Therefore, the event of the target block failing after the accident is the event of the communication base station fault being eliminated (denoted as CEvent2).

[0174] In the energy system, block failure events after an accident mainly depend on when the power supply channels are repaired. Referring to the definition method of failure events in the accident, the failure events of the target block after the accident can also be divided into two categories. Taking the smart park shown in Figure 2 as an example, when the fault of the line in block is eliminated, the power supply channel will adjust the topology according to the requirements of the energy system's radiation operation and continuously supply power to E2 and E3 again; when any power supply channel of is repaired, the continuous power supply to E2 and E3 can be restored. Therefore, the block failure events after the accident in the energy system can be represented by two mutually exclusive events, namely the internal line pipeline fault being eliminated (denoted as PEvent3) and Any external power supply channel fault is eliminated (denoted as PEvent4). Before either PEvent3 or PEvent4 occurs The power supply will remain cut off.

[0175] Based on the above analysis, when a cyber-physical load fault occurs, the node failure times within the associated block of the same node are the same. Assume that the line pipeline of a communication base station is r fault-free at time t r and returns to normal at time t + 1. Then the probabilities that block has a post-accident failure event duration of υ r are respectively:

[0176]

[0177]

[0178] Among them, and are respectively the scenario sets where the intelligent switch, line pipeline, and power supply channel of block s are in a normal state at time t r + 1; and are respectively the scenario sets where the intelligent switch, line pipeline, and power supply channel of block s are in a faulty state before the recovery normal time.

[0179] Based on the above two probability formulas for the post-accident failure event duration of υ r , it is possible to determine the probability model that the blocks in the communication system and the energy system are in a failure event at time T r + υ r after the accident, but are operating normally at time T r + υ r + 1.

[0180] S204: Establish a resilience evaluation index system;

[0181] Since the system performance curve can well describe the dynamic performance of the smart park during the full cycle of extreme events, the missing area of the system performance in the time period [T e , T n can be used to characterize the resilience level of the smart park under cyber-physical collaborative attacks. The calculation formula is:

[0182]

[0183] Among them, Q(t) represents the system performance at time t.

[0184] Different from traditional energy systems, the operation regulation measures of smart campuses highly rely on remote control operations of wireless communication networks. After receiving instructions, smart switches can perform disconnection or closing operations to achieve fault isolation or load adjustment of the power grid. The entire remote control process is not only highly automated but also ensures the accuracy of operations and the response speed of equipment, significantly enhancing the flexibility of urban energy systems. Therefore, considering the impact of cyber-physical collaborative attacks on system performance, such as the offline state of communication base stations and the interruption of line pipelines, starting from the intelligence and reliability of smart campuses, a system performance function is quantified based on the number of controllable devices in the communication network and the supply load level of the energy system. Two resilience evaluation indicators, namely the equipment out-of-control index and the load outage index, are established. Combining with the node-associated block model, the resilience indicators are expressed as:

[0185]

[0186] Among them, is the controlled state at time t ; is the energy supply state at time t .

[0187] Given the significant differences among the capability levels of cyber-physical collaborative attackers, the protection levels of urban energy system construction, and the preventive measures taken, campus energy management agencies often adopt risk assessment methods such as expert security analysis and high-precision simulation of cyber-physical collaborative attack scenarios to measure the probability of cyber-physical compound failures occurring in communication base stations and line pipelines under cyber-physical collaborative attacks through probability. Therefore, the resilience evaluation indicators can be further decomposed by the occurrence probability of block failure events into:

[0188]

[0189] Among them, and are respectively the probabilities that the outage durations are υ d and υ r in the in-accident stage and the post-accident stage; and are respectively the probabilities that the out-of-control durations are υ d and υ r in the in-accident stage and the post-accident stage.

[0190] Specifically, in this embodiment, the resilience evaluation indicators are analyzed. The analytical expressions for in-accident block failure events include:

[0191] ① In the in-accident block failure event of the communication network, based on the total probability formula, the in-accident failure duration is the attack duration υ dThe failure probability in the accident is converted to;

[0192] If in the accident, the target component is in a normal state at time t e then it is also in a normal state at time t e -1. Therefore, there exists Further transformation gives:

[0193]

[0194] Among them, can be expressed as σ s,t is the failure probability of communication base station s at time t;

[0195] ② In the accident of the energy system, in the block failure event, the failure duration in the accident is the attack duration υ d The failure probability in the accident can also be converted based on the total probability formula to;

[0196]

[0197] Since regarding the scenario set of the internal line pipeline and regarding the scenario set of the external energy supply channel are independent of each other, so it can be further transformed into:

[0198]

[0199] Since there exists, so it can be further transformed into:

[0200]

[0201] If in the accident, the target component is in a failed state at time t e -1, then it is also in a failed state at time t e Therefore, there exists The transformation gives:

[0202]

[0203] Among them, can be expressed as: σ l,t is the failure probability of line pipeline l at time t.

[0204] In addition, since there are multiplexed intelligent switches and line pipelines in the external energy supply channels, so regarding The events are still non - independent events, and their occurrence probabilities are difficult to calculate. In this embodiment, further through the total probability formula and the conditional probability formula perform the following transformation, expressed as:

[0205]

[0206] Among them, represents the event that the first energy - supply channel of e is in a normal state at time t e while all other energy - supply channels are in a faulty state at time t

[0207] To simplify the representation of this event, this embodiment proposes to screen the energy - supply channel set SWE(s,i,j), representing the i - th channel after excluding the j - th energy - supply channel, that is:

[0208]

[0209] Therefore, it can be further equivalently obtained that:

[0210]

[0211] Through analysis, it can be seen that by applying the total probability formula and the conditional probability formula, the original event can be decomposed into events independent of. Therefore, for the scenario set of multiple energy - supply channels in the formula repeatedly perform w = m s - 1 decompositions, which can be removed one by one, and finally decomposed into independent events with only one energy - supply path, expressed as:

[0212] In summary, through the above steps, the occurrence probabilities and of the block failure event in the accident s,t and σ l,t can be analytically expressed by the failure occurrence probabilities of the communication base station and the line pipeline under the cyber - physical collaborative attack.

[0213] Specifically, this embodiment analyzes the resilience evaluation index. For the analytical expression of the block failure event after the accident, it includes:

[0214] ① If the target component is in a normal state at time t r + 1 after the accident, then it is also in a normal state at time t r ; Therefore, there exists Combined with the total probability formula, the post-accident block failure event of the communication network can be transformed into:

[0215]

[0216] Since the cyber-physical collaborative attack has ended, the probability of the independent event has two cases: when υ r +1 is less than the equipment repair time, its probability is equal to the probability of no block failure time in the accident, that is When υ r +1 is greater than or equal to the equipment repair time, the fault in the target block is eliminated, so

[0217] ② In the post-accident block failure event of the energy system, it can also be based on the scenario set of the internal line pipeline and the scenario set of the external energy supply channel being independent of each other, and transformed into by the total probability formula:

[0218]

[0219] If, after the accident, the target component is in a faulty state at time t r +1, then it is also in a faulty state at time t r . Therefore, there exists which can be further transformed and obtained:

[0220]

[0221] In this formula, the probability of the independent event regarding is also determined by the relationship between υ r +1 and the equipment repair time. The non-independent event regarding can be decomposed and transformed into:

[0222]

[0223] To sum up, the occurrence probabilities and of the post-accident block failure event can be analytically expressed by the fault occurrence probabilities σ s,t and σ l,t .

[0224] Furthermore, substituting and into the calculation expressions of the equipment out-of-control index and the load outage index, the analytical expression of the proposed resilience evaluation index can be obtained.

[0225] The resilience assessment method of the intelligent park proposed by the present invention relies on the node-associated block model to effectively map the dependencies between the cyber and physical systems, can effectively describe the impact of dual failures of communication base stations and line pipelines on system performance under cyber-physical collaborative attacks, and based on probability theory knowledge, this method well solves the problem of lack of attack historical data, and the assessment efficiency is not affected by the scenario generation efficiency, and it has good adaptability in systems with high and low failure probabilities.

[0226] Based on the above embodiments, in the embodiments of the present invention, based on Figure 2 the intelligent park shown in the figure, the intelligent park consists of a communication network with 8 nodes, a power distribution network with 7 nodes, a natural gas network with 5 nodes, and 1 energy hub. Based on the proposed node-associated block concept, the smart city energy system can be decomposed into 6 communication blocks B c and 7 energy blocks B p . Referring to Figure 4 shown in the figure, it is a load schematic diagram of each energy node of the intelligent park energy system. For the convenience of representation, natural gas and heat energy are both converted into electric energy for presentation.

[0227] Set the accident cycle of malicious supply to 6 hours (i.e., [T e , T r = 6), and the post-accident cycle to 6 hours (i.e., [T r , T n = 6). The failure probabilities and repair times of communication base stations and line pipelines during malicious attacks are shown in Tables 1 and 2.

[0228] Table 1 Base station failure probability and repair time

[0229]

[0230] Table 2 Line pipeline failure probability and repair time

[0231]

[0232] To verify the effectiveness of the intelligent park resilience assessment method provided by the present invention, in this embodiment, first, the node-associated block model is solved to obtain the energy supply channels of each energy block B p , as shown in Table 3;

[0233] Table 3 Energy supply channels of node-associated blocks in the energy system

[0234]

[0235]

[0236] Then, after calculating based on the analysis method of the present invention, each block B c and Bp The probability of failure in an accident is shown in Table 4. It can be seen from the analysis that the failure probability of each block in the accident increases with the increase of time period υ d . In this embodiment, taking and as examples respectively, analyze their failure probabilities at υ d = 4 (that is, and ). The calculation process of its failure probability can be expressed in the following form:

[0237]

[0238] Among them, the event probability related to within the block can be directly obtained according to probability calculation, while the events related to the energy supply channel need to be further solved, and finally

[0239] Table 4 Probability of block failure events in an accident

[0240]

[0241]

[0242] Next, after calculating based on the proposed analytical method in the same way, the failure probabilities of each block B c and B p in the system after the accident are shown in Table 5. It can be seen from the analysis that the failure probabilities of each block after the accident are strongly correlated with the repair time period. In this embodiment, continue to take and as examples, analyze their failure probabilities at υ r = 2 (that is, and ). The failure probability can be expressed as:

[0243]

[0244]

[0245] Among them, the event probability related to within the block can be directly obtained according to probability calculation, while the events related to the energy supply channel need to be further solved, and finally

[0246] Table 5 Probability of block failure events after the accident

[0247]

[0248] Finally, by synthesizing the failure event probabilities of each block during and after the accident shown in Table 4 and Table 5, through the equipment out-of-control index κ cand the load outage index κ p Perform analytical expression to achieve the analytical evaluation of the resilience of the smart city energy system, expressed as:

[0249]

[0250] Based on the above embodiments, in the embodiments of the present invention, in order to analyze the impact of cyber-physical collaborative attacks and cyber-physical dependencies on the evaluation results, the resilience evaluation method provided by the present invention is set as Scenario 1 in this embodiment, and 2 additional scenarios are set for comparison. Among them:

[0251] Scenario 2: Only consider the impact of physical attacks on pipelines;

[0252] Scenario 3: Do not consider the impact of communication status on intelligent switches. Regardless of whether the base station is online or not, the intelligent switches can operate correctly.

[0253] Through simulation calculations, the results of each scenario are compared as shown in Table 6. In Scenarios 2 and 3, due to ignoring the impact of communication failures and switch controlled states respectively, the obtained resilience indicators are both on the low side. This shows that when studying the resilience of smart campuses, potential attacks on the communication network must be fully considered, and the "information fusion" feature must be comprehensively considered to avoid overly optimistic evaluation results of system resilience.

[0254] Table 6 Comparison of resilience evaluation indicators for each scenario

[0255]

[0256] The present invention provides a resilience evaluation method for a smart campus considering cyber-physical coupling. This method establishes a two-layer graph structure that describes the characteristics of "physical ring construction and information decentralized deployment" of the smart campus. On this basis, a node association block model considering cyber-physical coupling is constructed to analyze the dynamic impact of cyber-physical collaborative attacks on system performance. An accident and post-accident block failure event model is established, and two resilience evaluation indicators, namely the equipment out-of-control index and the load outage index, are proposed, and the analytical expression of the indicators is combined with the probability theory method. This method is not affected by the number of generated fault scenarios, considers its dependencies in the cyber-physical fusion environment, and has good applicability to smart campuses.

[0257] The resilience assessment method of the intelligent park described in the present invention constructs a physical subnet and an information subnet based on the characteristics of the intelligent park of "physical ring construction and decentralized information deployment", and conducts block decomposition to construct a node-associated block model. By explicit modeling, the cyber-physical dependency relationships of communication base stations, intelligent switches, energy sources, loads, and connection lines are taken into account. Relying on the node-associated block model, the cyber-physical dependency relationships can be effectively mapped, and the impact of double failures of communication base stations and line pipelines under cyber-physical collaborative attacks on system performance can be effectively described, improving the accuracy of the resilience assessment of the intelligent park. The present invention analyzes the dynamic impact of cyber-physical collaborative attacks on system performance, transforms the cyber-physical coupling relationship into a computable probability problem, calculates the block failure probabilities of the energy block and the communication block during and after an accident, and proposes two resilience assessment indicators, namely the equipment out-of-control index and the load outage index, to evaluate the resilience of the communication block and the energy block in the intelligent park respectively, significantly improving the accuracy of the resilience assessment of the intelligent park, and enabling the resilience assessment of the entire time period based on the probabilities at different times. The present invention combines the method of probability theory, decomposes through the total probability formula and conditional probability, solves the failure probability during the accident and the failure probability after the accident, transforms non-independent events into independent events for analytical calculation, and then analyzes the resilience assessment indicators, well solving the problem of lack of attack historical data; moreover, the resilience assessment efficiency is not affected by the scenario generation efficiency, and it has good adaptability in systems with different failure probabilities.

[0258] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0259] The present application is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, and the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0260] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to operate in a particular manner, such that the instructions stored in the computer-readable memory produce a manufacture including an instruction device that implements the functions specified in one or more of the processes Figure 1 one or more of the processes and / or blocks Figure 1 specified in the blocks or blocks.

[0261] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, whereby the instructions executed on the computer or other programmable apparatus provide steps for implementing the functions specified in one or more of the processes Figure 1 one or more of the processes and / or blocks Figure 1 specified in the blocks or blocks.

[0262] Obviously, the above embodiments are only examples for clear illustration and are not limitations on the implementation. For those of ordinary skill in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the implementation manners here. And the obvious changes or modifications derived therefrom are still within the protection scope of the present invention.

Claims

1. A method for evaluating the resilience of an intelligent park, characterized in that, Including: Taking the energy source and the load as nodes and the line pipelines as connection edges, constructing a physical subnet of the energy system, which is divided into multiple energy blocks; Taking the intelligent switches as nodes and the communication links as connection edges, constructing an information subnet of the communication system, which is divided into multiple communication blocks; Constructing a smart campus node association block model, including: for each energy block, taking the maximum recoverable load of the block as the objective function; setting the operation constraints of the functional channels of the energy block and the state constraints of the energy system grid; setting the operation state constraints of the communication system terminals of the communication block; setting the cyber-physical dependence constraints of the smart campus; Based on the non-repetitive constraints and the cyclic solution strategy, solving the smart campus node association block model to obtain all the supply channel indexes corresponding to each energy block; Based on the smart campus node association block model, collecting the failure occurrence times of all the intelligent switches, line pipelines and supply channel indexes in the block when a cyber-physical coordinated attack is launched, and calculating the failure probability of each block in the accident with the attack duration as the failure duration; Collecting the normal recovery times of all the intelligent switches, line pipelines and supply channel indexes in the block after the cyber-physical coordinated attack ends, and calculating the post-accident failure probability of the block with the system recovery duration as the post-accident failure duration; Calculating the equipment out-of-control index of the smart campus based on the failure probabilities during the accident and the post-accident failure probabilities of all energy blocks; Calculating and obtaining the load outage index of the smart campus based on the failure probabilities during the accident and the post-accident failure probabilities of all communication blocks; Realizing the resilience assessment of the smart campus based on the equipment out-of-control index and the load outage index of the smart campus.

2. The resilient evaluation method for an intelligent park according to claim 1, wherein, Constructing a smart campus node association block model, including: For each energy block, the maximum recoverable load of the block is used as the objective function, expressed as: The operation constraints of the supply channels, including: The virtual power flow constraint, expressed as: The constraint on the energy flow direction between nodes is expressed as: The state constraints of the energy system grid, including: First constraint of the energy supply channel, expressed as: The second constraint of the energy supply channel, expressed as: The third constraint of the energy supply channel, expressed as: The fourth constraint of the energy supply channel, expressed as: The operating state constraints of the communication system terminal are expressed as: Cyber-physical dependency constraints, expressed as: Among them, represents the physical subnet B p the s-th energy block in the power supply status, represents can be powered in the current operating scenario, represents is cut off from power supply in the current operating scenario; Ω(s) represents the s-th energy block in the physical subnet the set of nodes, represents the node load of the b-th node in the s-th energy block of the physical subnet; represents the parent node-channel incidence matrix of the energy block, represents the child node-channel incidence matrix of the energy block, represents the energy node-energy source incidence matrix, represents the energy node-gas turbine incidence matrix; f l 、f n and f u are the energy flows corresponding to the power supply channel l, the energy source n, and the energy conversion device u respectively; represents the operating state variable of node b in the energy system, represents that node b can receive power supply, represents that node b cannot receive power supply; Π represents the set of nodes in the energy system; represents the operating state variable of the pipeline l in the energy system, represents that the pipeline l can receive power supply, represents that the pipeline l cannot receive power supply; Φ represents the set of all pipelines in the energy system, Φ tr represents the set of pipelines connecting gas turbines and energy hubs in the energy system; represents the maximum capacity of the pipeline; Ω NS represents the set of energy blocks containing energy sources, Ω N represents the set of energy blocks without energy sources; represents whether the current power supply channel passes through the energy block and if represents passing through, if represents not passing through; represents whether the power supply channel can reach the energy block from the energy block to the energy block represents being able to reach, represents not being able to reach; represents the physical subnet B p the power supply status variable of the i-th node in Indicates that the node can obtain power supply. Indicates that the node cannot obtain power supply; Ξ(i) represents the set of line pipelines in the energy block. Indicates The on-line state variable of Indicates that the i-th base station in the communication block is on-line. Indicates that the i-th base station is off-line. Indicates the controlled state variable of the communication node. Indicates that the switch is controllable. Indicates that the switch is out of control; Δ(i) represents the set of communication nodes in the communication block, and Ψ represents the set of switches installed on the external line pipelines of B. p Set of switches installed on the external line pipelines.

3. The resilience assessment method for an intelligent park according to claim 2, wherein Including: When the block is a communication block, collect the failure occurrence moment of the intelligent switch in the communication block when the physical collaborative attack on information is launched, and calculate that the failure duration of the communication block in the accident is the attack duration υ d The failure probability in the accident It is expressed as: Among them, represents the currently calculated communication block, and CEvent1 is communication event 1, indicating that the currently calculated communication block fails in the cyber-physical system attack; represents t e moment the set of scenarios where the intelligent switch is in a faulty state at time t; represents t e time t - 1 the set of scenarios where the intelligent switch is in a normal state before the fault occurs; When the block is an energy block, collect the failure occurrence moments of the pipelines and functional channels in the energy block at the time when the physical collaborative attack on the collected information is launched, and calculate the failure duration of the energy block in the accident as the attack duration υ d The failure probability in the accident It is expressed as: Among them, represents the currently calculated energy block; PEvent1 is energy event 1, indicating that there is a fault in the internal circuit; PEvent2 is energy event 2, indicating that all external energy supply channels have failed; represents the set of scenarios where the line pipeline is in a fault state at time t e moment ; represents the set of scenarios where the line pipeline was in a normal state before the fault occurred at time t -1; SW(s, m e ) represents the index of the energy supply channel in ; represents the set of scenarios where the energy supply channel is in a fault state at time t i ; represents the set of scenarios where the energy supply channel was in a normal state before the fault occurred at time t -1. represents the set of scenarios where the energy supply channel is in a fault state at time t e moment ; represents the set of scenarios where the energy supply channel was in a normal state before the fault occurred at time t -1. e ; represents the set of scenarios where the energy supply channel was in a normal state before the fault occurred at time t .

4. The intelligent park resilience assessment method according to claim 3, wherein Using the total probability formula, based on the failure probability of communication base stations under cyber-physical collaborative attacks, solve for the failure probability of the communication block in an accident where the outage duration is the attack duration υ d in an accident which is expressed as: Among them, represents the probability of a fault occurring in the currently calculated communication block at time t e The expression is σ s,t represents the probability of a fault occurring in communication base station s at time t.

5. The resilient evaluation method for an intelligent park according to claim 3, wherein Using the total probability formula and the conditional probability formula, based on the failure probability of the line pipeline under the cyber-physical collaborative attack, solve the failure probability of the energy block in the accident where the outage duration is the attack duration υ d in the accident including: Among them, represents the probability of failure of the currently calculated energy block at time t e The expression is σ l,t represents the probability of failure of the line pipeline l at time t; SWE(s,i,j) is the set of energy supply channels, indicating the i-th channel after excluding the j-th energy supply channel.

6. The resilient evaluation method for an intelligent park according to claim 3, wherein Including: When the block is a communication block, at the moment when the intelligent switch in the communication block returns to normal after the physical collaborative attack on information collection, calculate the post-accident failure duration of the communication block as the system recovery duration υ r The post-accident failure probability It is expressed as: Among them, represents the currently calculated communication block; CEvent2 is communication event 2, representing the communication base station troubleshooting event; represents the set of scenarios where the intelligent switch in r was in a faulty state before the normal recovery time t represents the set of scenarios where the intelligent switch in r is in a normal state at time t + 1; When the block is an energy block, at the moment when the line pipelines and energy supply channels in the energy block return to normal after the physical collaborative attack on the acquisition information, calculate the post-accident failure duration of the energy block as the system recovery duration υ r The post-accident failure probability It is expressed as: Among them, represents the currently calculated energy block; PEvent3 is Energy Event 3, indicating the troubleshooting of internal line pipelines; PEvent4 is Energy Event 4, indicating the troubleshooting of any external energy supply channel; the set of scenarios in which the intelligent switch was in a faulty state before the recovery normal time t r ; represents the set of scenarios in which the intelligent switch is in a normal state at time t r + 1; represents the set of scenarios in which the line pipeline was in a faulty state before the recovery normal time t r ; represents the set of scenarios in which the line pipeline is in a normal state at time t r + 1; represents the set of scenarios in which the energy supply channel was in a faulty state before the recovery normal time t r ; represents the set of scenarios in which the energy supply channel is in a normal state at time t r + 1; T r represents the end time of the attack.

7. The resilient evaluation method for an intelligent park according to claim 6, wherein Using the total probability formula, based on the failure probability of communication base stations under cyber-physical collaborative attacks, the post-accident failure duration of the communication block is solved as the system recovery duration υ r The post-accident failure probability is expressed as: Among them, when υ r +1 is less than the equipment maintenance time, when υ r +1 is not less than the equipment maintenance time, represents the probability of a fault occurring in the currently calculated communication block at time T r , and the expression is σ s,t represents the probability of a fault occurring in communication base station s at time t.

8. The intelligent park resilience assessment method according to claim 6, wherein Using the total probability formula and the conditional probability formula, based on the failure probability of the line pipeline under the cyber-physical collaborative attack, calculate the post-accident failure duration of the energy block as the system recovery duration υ r The post-accident failure probability is expressed as: Among them, represents the probability of failure occurrence of the currently calculated energy block at time T r , and the expression is σ l,t represents the probability of failure occurrence of the line pipeline l at time t.

9. The resilience assessment method for an intelligent park according to claim 6, wherein, Calculating the equipment out-of-control index of the smart campus based on the failure probabilities during the accident and the post-accident failure probabilities of all energy blocks, expressed as: Among them, κ c represents the equipment out-of-control index of the smart park, T r represents the end time of the attack, T e represents the start time of the attack, T n represents the time when it returns to normal.

10. The intelligent park resilience assessment method according to claim 6, wherein Calculating and obtaining the load outage index of the smart campus based on the failure probabilities during the accident and the post-accident failure probabilities of all communication blocks, expressed as: Among them, κ p represents the load cut-off index of the smart park, T r represents the end time of the attack, T e represents the start time of the attack, T n represents the time when it returns to normal.

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