A method and device for evaluating the resilience of a backbone network architecture of a power system, and an electronic device

Abstract

The application provides a kind of power system backbone network frame resilience evaluation method, device and electronic equipment, belong to power system resilience evaluation technical field, including: obtaining the parameter of the backbone network frame of power system;The parameter of backbone network frame is input into pre-constructed deliberate physical attack loss load calculation model and secondary fault loss load calculation model, and the failure scenario set is obtained;Failure scenario set includes deliberate physical attack scenario set and secondary fault scenario set;Each secondary fault scenario in secondary fault scenario set corresponds to one deliberate physical attack scenario in deliberate physical attack scenario set;The parameter of backbone network frame and the failure scenario set are input into backbone network frame resilience evaluation model, and the backbone network frame resilience evaluation result is obtained.The application can quantify the high risk caused by deliberate physical attack and secondary fault of power system, and then improve the effectiveness of decision-making, ensure the safe recovery of power system and reduce the possible secondary power loss.

Description

Technical Field

[0001] This application relates to the field of power system resilience assessment technology, and more specifically, to a method, apparatus, and electronic equipment for assessing the resilience of a power system backbone grid. Background Technology

[0002] In recent years, external security threats such as extreme weather, geological disasters, and cyberattacks have increased, posing new and severe challenges to the safe and stable operation of power systems. Extreme events can easily trigger large-scale power outages, and during power restoration, the power grid structure is still incomplete. Therefore, clarifying the power system resilience evaluation method during the recovery phase is of great significance for effectively improving the power system's ability to withstand disturbances.

[0003] In power system restoration, grid reconfiguration is a crucial transitional stage, with the backbone grid representing the target or the desired state of this reconfiguration phase. While numerous technologies exist for the design, optimization, and evaluation of the backbone grid, actual restoration conditions are complex. A backbone grid determined solely based on maximizing restoration efficiency may suffer severe damage due to external disturbances. Furthermore, under deliberate physical or cyberattacks, the previously restored backbone grid could potentially collapse again. Therefore, research into enhancing the resilience of the backbone grid and improving its resistance to external disturbances is of great significance.

[0004] Existing methods for assessing the impact of deliberate external attacks on power systems tend to focus on the impact of information power system failures on physical power systems. They do not adequately consider the impact of deliberate physical attacks during power system recovery and cannot effectively assess the resilience of the backbone grid under extreme external disturbances.

[0005] Meanwhile, existing technologies do not consider the deliberate nature of external disturbances, only attacks based on the inherent characteristics of the physical power system itself. Furthermore, deliberate physical attacks or disturbances do not cause only one loss. Because the operating conditions of the power system in the restored state differ significantly from normal conditions, secondary power system protection devices and automatic operating devices may malfunction due to interference, causing secondary overload tripping and further failure losses. Without a scientifically sound assessment method, it is impossible to reasonably quantify the deliberate nature and secondary impacts of external physical attacks, making it impossible to make defensive decisions against deliberate physical attacks, thus significantly delaying power system recovery. Summary of the Invention

[0006] The purpose of this application is to provide a method, apparatus, and electronic device for assessing the resilience of a power system backbone network, in order to solve the problems of existing technologies that cannot quantify the losses caused by intentional physical attacks and secondary faults during power system restoration, cannot reduce the risk of intentional physical attacks, and cannot effectively assess the resilience of the backbone network. This application can accurately quantify the losses caused by intentional physical attacks and secondary faults in the power system, improve the effectiveness of restoration decisions, ensure the safe restoration of the power system, and reduce possible secondary power outage losses.

[0007] Firstly, a method for assessing the resilience of a power system backbone grid is provided, which may include:

[0008] Obtain the parameters of the backbone network of the power system;

[0009] The parameters of the backbone network are input into the pre-constructed calculation models for the load loss of intentional physical attacks and the load loss of secondary faults to obtain a set of fault scenarios.

[0010] The calculation model for the load loss due to a deliberate physical attack includes: an objective function for the load loss due to a deliberate physical attack and constraints for a deliberate physical attack; the calculation model for the load loss due to a secondary fault includes: an objective function for the load loss due to a secondary fault and constraints for a secondary fault.

[0011] The set of fault scenarios includes a set of intentional physical attack scenarios and a set of secondary fault scenarios; the set of intentional physical attack scenarios includes multiple different intentional physical attack scenarios and a load loss amount corresponding to each intentional physical attack scenario; the set of secondary fault scenarios includes multiple different secondary fault scenarios and a load loss amount corresponding to each secondary fault scenario.

[0012] Each of the secondary failure scenarios in the set of secondary failure scenarios corresponds to a deliberate physical attack scenario in the set of deliberate physical attack scenarios.

[0013] The parameters of the backbone space frame and the set of failure scenarios are input into a pre-built backbone space frame toughness assessment model to obtain the backbone space frame toughness assessment results.

[0014] In an optional implementation, the parameters of the backbone network are input into a pre-built calculation model for the load loss due to a deliberate physical attack and a calculation model for the load loss due to a secondary fault, to obtain a set of fault scenarios, including:

[0015] The parameters of the backbone network are input into a pre-constructed calculation model for the load loss of a deliberate physical attack to obtain a set of deliberate physical attack scenarios.

[0016] The parameters of the backbone network and the set of deliberate physical attack scenarios are input into a pre-built secondary fault load calculation model to obtain the set of secondary fault scenarios.

[0017] Based on the set of intentional physical attack scenarios and the set of secondary failure scenarios, a failure scenario set is obtained.

[0018] In an optional implementation, the parameters of the backbone network are input into a pre-built deliberate physical attack load loss calculation model to obtain a set of deliberate physical attack scenarios, including:

[0019] The parameters of the power system backbone network are input into a pre-constructed calculation model for the load loss of a deliberate physical attack, resulting in a set of deliberate physical attack scenarios that includes a deliberate physical attack scenario and the corresponding load loss of the deliberate physical attack scenario.

[0020] The set of deliberate physical attack scenarios and the parameters of the power system backbone network are input into the deliberate physical attack load loss calculation model to obtain the updated set of deliberate physical attack scenarios; wherein, the updated set of deliberate physical attack scenarios includes two different deliberate physical attack scenarios and the deliberate physical attack scenario load loss corresponding to each deliberate physical attack scenario.

[0021] Determine whether the number of intentional physical attack scenarios included in the updated set of intentional physical attack scenarios meets a preset threshold.

[0022] If satisfied, output the updated set of intentional physical attack scenarios;

[0023] If the conditions are not met, the updated set of deliberate physical attack scenarios will be used as the new set of deliberate physical attack scenarios, and the execution steps will be returned: input the set of deliberate physical attack scenarios and the parameters of the power system backbone network into the calculation model of deliberate physical attack load loss, until the number of deliberate physical attack scenarios in the obtained set of deliberate physical attack scenarios meets the preset threshold; output the set of deliberate physical attack scenarios.

[0024] In an optional implementation, the parameters of the backbone network and the set of deliberate physical attack scenarios are input into a pre-built secondary fault load loss calculation model to obtain the set of secondary fault scenarios, including:

[0025] Choose one intentional physical attack scenario from the set of intentional physical attack scenarios;

[0026] The selected intentional physical attack scenario and the parameters of the backbone network are input into a pre-built secondary fault load loss calculation model to obtain a secondary fault scenario and a secondary fault scenario load loss corresponding to the secondary fault scenario; wherein, the secondary fault scenario corresponds to the selected intentional physical attack scenario.

[0027] Traverse all intentional physical attack scenarios in the intentional physical attack scenario set to obtain the secondary failure scenario set.

[0028] In an optional implementation, the backbone grid toughness assessment model is as follows:

[0029]

[0030] Where R represents the backbone structure toughness assessment model; f K,w f represents the power system load loss under a deliberate physical attack corresponding to attack scenario w; Sec,w α represents the load loss caused by a subsequent fault following a deliberate physical attack; W represents the set of attack scenarios; i represents a power system node, and N represents the set of nodes in the backbone network; i P represents the importance coefficient of the load on node i; d,i This represents the load on node i; n represents the number of attack scenarios.

[0031] In an optional implementation, after inputting the parameters of the backbone grid and the set of failure scenarios into a pre-built backbone grid resilience assessment model to obtain the backbone grid resilience assessment results, the method further includes:

[0032] Based on the backbone space frame toughness assessment model, a backbone space frame toughness optimization model is constructed.

[0033] The backbone space structure is optimized using the aforementioned backbone space structure toughness optimization model to obtain the optimized backbone space structure.

[0034] In an optional implementation, based on the backbone grid toughness assessment model, a backbone grid toughness optimization model is constructed, including:

[0035] The backbone space structure toughness assessment model is used as the objective function of the backbone space structure toughness optimization model.

[0036] The power flow constraints under the fault scenario set and the connectivity constraints of the backbone grid are used as constraints for the backbone grid resilience optimization model.

[0037] Based on the objective function and constraints of the backbone space frame toughness optimization model, the backbone space frame toughness optimization model is obtained.

[0038] Secondly, a resilience assessment device for a power system backbone grid is provided, the device comprising:

[0039] The parameter acquisition unit is used to acquire parameters of the backbone network of the power system.

[0040] The dataset construction unit is used to input the parameters of the backbone network into the pre-built calculation models of intentional physical attack load loss and secondary fault load loss to obtain a set of fault scenarios.

[0041] The calculation model for the load loss due to a deliberate physical attack includes: an objective function for the load loss due to a deliberate physical attack and constraints for a deliberate physical attack; the calculation model for the load loss due to a secondary fault includes: an objective function for the load loss due to a secondary fault and constraints for a secondary fault.

[0042] The set of fault scenarios includes a set of intentional physical attack scenarios and a set of secondary fault scenarios; the set of intentional physical attack scenarios includes multiple different intentional physical attack scenarios and a load loss amount corresponding to each intentional physical attack scenario; the set of secondary fault scenarios includes multiple different secondary fault scenarios and a load loss amount corresponding to each secondary fault scenario.

[0043] Each of the secondary failure scenarios in the set of secondary failure scenarios corresponds to a deliberate physical attack scenario in the set of deliberate physical attack scenarios.

[0044] The evaluation unit is used to input the parameters of the backbone grid and the set of failure scenarios into a pre-built backbone grid toughness evaluation model to obtain the backbone grid toughness evaluation results.

[0045] Thirdly, an electronic device is provided, which includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus;

[0046] Memory, used to store computer programs;

[0047] When a processor executes a program stored in memory, it implements any of the steps described in the first aspect above.

[0048] Fourthly, a computer-readable storage medium is provided, wherein a computer program is stored therein, and when executed by a processor, the computer program implements the steps of any of the methods described in the first aspect above.

[0049] The resilience assessment method for the power system backbone grid in this application comprehensively considers the impact of deliberate physical attacks and their secondary faults on the backbone grid and restored loads during the power system recovery process. It accurately quantifies and assesses the resilience of the backbone grid under the influence of deliberate physical attacks and secondary faults, and comprehensively and effectively reflects the backbone grid's ability to resist extreme disturbances. This application incorporates the proposed backbone grid resilience assessment model into the optimization of the backbone grid, which can significantly improve the resilience of the backbone grid, reduce the power system load loss under extreme disturbances, and ensure the safe and rapid recovery of the power system. Attached Figure Description

[0050] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0051] Figure 1 A flowchart illustrating a method for assessing the resilience of a power system backbone grid, as provided in this application embodiment;

[0052] Figure 2 A diagram illustrating the resilience assessment and optimization strategy for a power system backbone grid, provided in this application embodiment;

[0053] Figure 3 A schematic diagram of a method for assessing the resilience of a power system backbone grid, provided in an embodiment of this application;

[0054] Figure 4 A schematic diagram of the structure of a power system backbone grid toughness assessment device provided in an embodiment of this application;

[0055] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application;

[0056] Figure 6 A schematic diagram of the IEEE-57 power system backbone network and fault scenario set distribution provided in this application embodiment;

[0057] Figure 7 This application provides a schematic diagram of the load loss frequency distribution under a random attack, as illustrated in an embodiment of the present application.

[0058] Figure 8 This application provides a schematic diagram comparing the impact of various attack scenarios on the backbone network before and after resilience optimization.

[0059] Figure 9 This is a schematic diagram illustrating the load distribution of a deliberate attack scenario under different attack resources, provided as an embodiment of this application. Detailed Implementation

[0060] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0061] For ease of understanding, the terms used in the embodiments of this application are explained below:

[0062] A power system refers to the entire system composed of power generation units in power plants, transmission and distribution lines, substations, and various electrical devices used by users. Transmission and distribution lines and substations of different voltage levels form the power grid; the power grid is divided into transmission networks and distribution networks according to their different roles within the power system.

[0063] The backbone network refers to the main structure of the power system for nationwide or inter-provincial power transmission, including AC 500kV and above (750kV, 1000kV) and DC ±800kV transmission lines.

[0064] A cross-section refers to the network topology and operating status of a power grid at a certain time point.

[0065] The IEEE-57 power system is a standard node test power system.

[0066] The power system backbone network resilience assessment method provided in this application can be applied to servers or terminals with strong computing capabilities. The server can be a physical server, a server cluster consisting of multiple physical servers, or a distributed power system. It can also be a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and artificial intelligence platforms. The terminal can be user equipment (UE) such as mobile phones, smartphones, laptops, digital radio receivers, personal digital assistants (PDAs), and tablet computers (PADs), handheld devices, in-vehicle devices, wearable devices, computing devices, or other processing devices connected to a wireless modem, mobile stations (MS), and mobile terminals. The terminal and server can be directly or indirectly connected via wired or wireless communication methods, which is not limited herein.

[0067] The preferred embodiments of this application are described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit this application. Furthermore, the embodiments and features in the embodiments of this application can be combined with each other without conflict.

[0068] Figure 1 This is a flowchart illustrating a method for assessing the resilience of a power system backbone grid, as provided in an embodiment of this application. Figure 1 As shown, the method may include:

[0069] Step S110: Obtain the parameters of the backbone network of the power system.

[0070] In this embodiment of the application, the parameters of the backbone grid of the power system include: the cross-section of the backbone grid, transmission lines, generating units, and the operating parameters of the power system.

[0071] Step S120: Input the parameters of the backbone network structure into the pre-constructed calculation models of intentional physical attack load loss and secondary fault load loss to obtain the fault scenario set.

[0072] In this embodiment of the application, the calculation model for the load depletion of a deliberate physical attack includes: an objective function for the load depletion of a deliberate physical attack and constraints on the deliberate physical attack; the calculation model for the load depletion of a deliberate physical attack is as follows:

[0073]

[0074]

[0075]

[0076]

[0077]

[0078]

[0079]

[0080] 0≤P g ≤P g,max (8);

[0081]

[0082]

[0083] ∑ ijc∈L (1-z ijc )≤K max(11);

[0084] Where i and j are power system node indices, c is a loop index, g is a generator set index, z is the attack line set, and Ξ is the attack scheme set; N, L, and G are the node set, line set, and generator set in the backbone network, respectively; Ω is the power system defense scenario set; N B For balanced nodes; L' is the set of criteria for determining whether there is a path connection between nodes; P i，Loss P represents the load shedding at node i; ijc P represents the active power flow in the ijc direction of the line; jic The active power flow in the direction of line jic; ijc and jic represent different directions of the same line; θ i Let θ be the phase angle at node i. j The phase angle at node j; z ijc The 01 variable (z) represents the operational status of the line after the attack. ijc =1 hour to put into operation, z ijc =0 (not in operation); P g For the active power output of unit g; G i Let α be the set of units on node i; i B is the importance coefficient of the load on node i; ijc The susceptance in the ijc direction of the line; The upper limit of power transmission for line ijc; k ijc The line transmission limit coefficient (k) under extreme conditions ijc ∈[1, 1.2]); P g，max P represents the upper limit of the active power output of unit g; d，i Let K be the load on node i. max The maximum number of attack lines; It is a large M parameter, whose value can take the form of π|B ijc | / 3. u represents a controllable variable in the power system.

[0085] Formula (1) is the objective function f of the deliberate physical attack load loss calculation model. K That is, to maximize the minimum load loss. Formulas (2) to (10) are based on the DC power flow model to constrain the power flow of the power grid: Formulas (2) to (4) are linearized expressions of the relationship between line power flow and line operation status; Formula (5) is the active power balance constraint of the node, introducing the slack variable P. i，Loss Calculate the forced load loss; Formula (6) is the phase angle difference constraint at both ends of the line; Formulas (7) to (9) respectively constrain the range of values ​​for line power flow, unit output and node load loss. Formula (10) is the phase angle constraint for the balancing node, and Formula (11) constrains the upper limit of the number of attacks on the line.

[0086] From formulas (1) to (11), it can be seen that the calculation model for the unloaded amount of a deliberate physical attack in this application is a maximum-min problem with game variables, and the integer decision variable z i j c It is simultaneously constrained by both max and min problems, so it cannot be solved directly or by using the solver's automatic dual solution function. Therefore, the mathematical expression of the dual model is derived from the original model.

[0087] Based on this, the calculation model for the unloaded amount of a deliberate physical attack in this application is transformed into:

[0088]

[0089]

[0090]

[0091]

[0092] γ i +η i ≤α i (16);

[0093]

[0094] Among them, B jic The susceptance in the JIC direction of the line; and These are the dual variables of the line power flow constraints in the ijc direction, respectively, in formulas (2) and (3). and These are the dual variables of the line power flow constraints in the jic direction, respectively, in formulas (2) and (3); and γ represents the dual variable corresponding to both sides of equation (4); i The dual variables of the nodal equilibrium equation in formula (5); For the dual variables corresponding to the phase angle difference constraint between phase angles i and j in formula (6); For the dual variables corresponding to the phase angle difference constraint between phase angles j and i in formula (6); κ represents the dual variables corresponding to the two ends of the power flow range constraint of the line in formula (7); g η is the dual variable of the unit output constraint in formula (8); i ξ is the dual variable of the unload constraint in formula (9); i δ is the dual variable of the phase angle constraint at the equilibrium node in formula (10). iThe parameter (δ) is used to determine whether node i is a balanced node. i =1, is a balance node, δ i =0, not); Formula (11) is a pure integer variable constraint, and the range of non-dual transformation.

[0095] Formula (12) is the objective function after dual transformation; Formulas (13) to (16) are the line power flow variables P, respectively. ijc Unit output variable P g Node phase angle variable θ i and the unloaded variable P i,Loss The corresponding dual constraints. Formula (17) represents the range of each variable in the dual model.

[0096] Formula (12) is the objective function of the deliberate physical attack load loss calculation model after dualization in this application. Formula (12) is a mixed integer nonlinear form. To facilitate the solution, it can be converted into a linear form by adding additional auxiliary variables. Formulas (18) and (19) are converted into linear forms by adding 01 variables λ. ijc and ε ijc Transform the objective function into the linear form shown in equation (21):

[0097]

[0098]

[0099]

[0100] In this embodiment of the application, the parameters of the backbone network are input into the constructed deliberate physical attack load loss calculation model to obtain a set of deliberate physical attack scenarios, specifically including the following steps:

[0101] The parameters of the power system backbone network are input into a pre-built calculation model for the load loss of a deliberate physical attack, resulting in a set of deliberate physical attack scenarios that includes a deliberate physical attack scenario and the corresponding load loss of the deliberate physical attack scenario.

[0102] The set of deliberate physical attack scenarios and the parameters of the power system backbone network are input into the deliberate physical attack load loss calculation model to obtain the updated set of deliberate physical attack scenarios. The updated set of deliberate physical attack scenarios includes two different deliberate physical attack scenarios and the load loss of each deliberate physical attack scenario.

[0103] Determine whether the number of intentional physical attack scenarios included in the updated set of intentional physical attack scenarios meets a preset threshold.

[0104] If satisfied, output the updated set of intentional physical attack scenarios;

[0105] If the conditions are not met, the updated set of intentional physical attack scenarios will be used as the new set of intentional physical attack scenarios, and the execution steps will be returned: input the set of intentional physical attack scenarios and the parameters of the power system backbone network into the calculation model of intentional physical attack load loss, until the number of intentional physical attack scenarios in the obtained set of intentional physical attack scenarios meets the preset threshold.

[0106] Based on the above scheme, each intentional physical attack scenario is taken as an infeasible cut set and input into the intentional physical attack load loss calculation model. This causes the intentional physical attack load loss calculation model to generate intentional physical attack scenarios that are different from the input intentional physical attack scenarios, thereby obtaining a set of intentional physical attack scenarios containing multiple different intentional physical attack scenarios.

[0107] Specifically, the mathematical expression for an infeasible cut set is shown in formula (21):

[0108]

[0109] Where w is the attack scenario index and W is the set of attack scenarios; Parameters of the backbone network structure of the power system under scenario w after a deliberate physical attack ( At that time, in scenario w, line ijc is in the operational state. (Then it is in the state of being out of operation). K′ is the scheme difference parameter. Assuming K′=n, the newly generated attack scheme is required to have at least n attack lines that are different from the previous scheme.

[0110] Specifically, the set of intentional physical attack scenarios includes multiple different intentional physical attack scenarios and the corresponding intentional physical attack scenario loadout for each scenario.

[0111] In this embodiment of the application, it is assumed that during the period from the time the power system suffers a deliberate attack to the end of the first secondary fault, the continued propagation of the fault can be blocked by means of low-frequency load shedding. The impact of the first secondary fault after the deliberate physical attack is simulated and analyzed, and a calculation model for the load loss of the secondary fault, which includes the objective function of the load loss of the secondary fault and the constraints of the secondary fault, is constructed as follows:

[0112]

[0113]

[0114]

[0115]

[0116]

[0117]

[0118]

[0119]

[0120]

[0121] In the formula, f Sec,w Let w be the objective function for the impact of secondary faults, i.e., minimizing the impact of load loss; This represents the load loss at node i under fault scenario w. The active power on line ijc under scenario w; Let i be the phase angle of node i in scene w; Let J be the phase angle of node J in scene w; Let w be a 01 variable representing the operational status of the line. Line commissioning, (Withdrawal from operation); For the active power output of unit g under scenario w; L represents the residual load on node i after a deliberate physical attack on scenario w. K,w For the backbone network of the power system after a deliberate physical attack. sec,w For the secondary fault lines in the scenario w of a deliberate attack, these lines can be selected from those with heavy power flow or overload after the attack. Furthermore, the set L can be adjusted according to the scale of the power system and the degree of consideration for secondary faults. Sec,w Size.

[0122] Formulas (22) to (30) contain integer variables. However, since formula (30) has already determined the backbone network of the power system after the secondary fault, it is a linear programming model. Through formulas (22) to (30), the load loss due to the secondary fault corresponding to the intentional physical attack scenario w can be obtained f. Sec,w .

[0123] In this embodiment of the application, the parameters of the backbone network and the set of deliberate physical attack scenarios are input into the above-mentioned secondary fault load loss calculation model to obtain the set of secondary fault scenarios, which specifically includes:

[0124] Select one intentional physical attack scenario from the set of intentional physical attack scenarios; input the selected intentional physical attack scenario and the parameters of the backbone network into the secondary fault load loss calculation model to obtain a secondary fault scenario and the corresponding secondary fault scenario load loss; wherein, the secondary fault scenario corresponds to the selected intentional physical attack scenario; traverse all intentional physical attack scenarios in the set of intentional physical attack scenarios to obtain the secondary fault scenario set.

[0125] The set of secondary failure scenarios includes multiple different secondary failure scenarios and the load loss of each secondary failure scenario; each secondary failure scenario in the set of secondary failure scenarios corresponds to a deliberate physical attack scenario in the set of deliberate physical attack scenarios.

[0126] In this embodiment of the application, a fault scenario set is obtained based on the obtained set of intentional physical attack scenarios and the set of secondary fault scenarios.

[0127] Step S130: Input the parameters and fault scenario set of the backbone grid structure into the pre-built backbone grid structure toughness assessment model to obtain the backbone grid structure toughness assessment results.

[0128] In this embodiment, the backbone structure toughness assessment model R is as follows:

[0129]

[0130] Among them, f K,w f represents the power system load loss under a deliberate physical attack corresponding to attack scenario w; Sec,w This indicates the amount of load loss caused by a subsequent failure following a deliberate physical attack.

[0131] In one embodiment of this application, after inputting the parameters of the backbone grid, the set of deliberate physical attack scenarios, and the set of secondary failure scenarios into a pre-constructed backbone grid resilience assessment model to obtain the backbone grid resilience assessment results, the following can also be performed:

[0132] Based on the backbone space structure toughness assessment model, a backbone space structure toughness optimization model is constructed; the backbone space structure is then optimized using the backbone space structure toughness optimization model to obtain the optimized backbone space structure.

[0133] Specifically, based on the backbone grid resilience assessment model, a backbone grid resilience optimization model is constructed, including: using the backbone grid resilience assessment model as the objective function of the backbone grid resilience optimization model; and using the power flow constraints under the fault scenario set and the connectivity constraints of the backbone grid as constraints of the backbone grid resilience optimization model.

[0134] Based on the objective function and constraints of the backbone space frame toughness optimization model, the backbone space frame toughness optimization model is obtained as follows:

[0135] max R

[0136]

[0137] Among them, L s For the set of all lines in the power system, z R,ijc This refers to the 01 variables representing the operational status of line ijc in the backbone network after resilience enhancement, distinct from the line operational variable z during a deliberate physical attack. ijc (z R,ijc =1 hour to put into operation, z R,ijc =0 means no line is put into operation), K0 is the number of lines put into operation in the initial backbone network, K R The resilience enhancement resource refers to the number of newly commissioned lines used to improve the resilience of the backbone grid during the recovery process. h(x,u) and g(x,u) represent the inequality and equality constraints of the model, respectively, including power flow constraints under fault scenario sets and backbone grid connectivity constraints. The backbone grid resilience optimization model, combined with the fault scenario set, constructs a ring network through newly commissioned lines to enhance the connection between power system sources and loads. Even after external disturbances damage some critical lines of the grid, it can still provide new feasible power supply paths, thereby reducing forced load shedding and enhancing the security of power system recovery.

[0138] In one embodiment of this application, such as Figure 2 As shown, the resilience assessment of the backbone grid includes two backbone grid sections: one after a deliberate physical attack, and the other after a secondary failure caused by the deliberate physical attack. The two backbone grid sections exhibit different stages and degrees of load loss. A set of deliberate physical attack scenarios is constructed based on the deliberate physical attack scenario and its corresponding load loss; a set of secondary failure scenarios is constructed based on the secondary failure scenarios and their corresponding load loss; the attack scenarios include the backbone grid sections. Based on the deliberate physical attack scenario set and the secondary failure scenario set, a failure scenario set is obtained.

[0139] Using a backbone grid resilience assessment model, the resilience of the backbone grid is assessed based on a set of fault scenarios. Based on the resilience assessment results, the backbone grid resilience optimization model is used to optimize the transmission network structure, thereby obtaining a backbone grid resilience-optimized transmission network with significantly reduced load loss.

[0140] Assume the attacker selects n attack scenarios, and the load loss of the power system under a deliberate physical attack corresponding to attack scenario w and the load loss caused by subsequent faults after the attack are respectively f. K,w and f Sec,w Then the total load shedding L under scenario w.w It can be represented as shown in formula (33).

[0141]

[0142]

[0143] Assuming that each attack scenario occurs with equal probability, calculate the expected load loss under the scenario set and divide it by the total load L that the power system has currently restored. All Then, take its opposite number and add it to 1 to obtain the toughness index R of the backbone grid as shown in equation (34). The smaller the R value, the lower the backbone grid's ability to resist extreme external disturbances; conversely, the larger the R value, the stronger the ability to resist extreme external disturbances. It can be seen from this that the set of scenarios of deliberate physical attack and secondary failure is the core of the backbone grid toughness assessment method.

[0144] like Figure 3 As shown in one embodiment of this application, the overall process of backbone grid resilience assessment may include: First, reading the backbone grid cross-section and power system parameters; generating intentional physical attack and secondary fault scenarios based on the backbone grid cross-section and power system parameters, and constructing a fault scenario set; determining whether the fault scenario set has been constructed; if not, adding infeasible cuts and regenerating intentional physical attack and secondary fault scenarios until the number in the fault scenario set reaches a preset threshold; finally, assessing the resilience of the backbone grid based on the fault scenario set; optimizing the backbone grid using a backbone grid optimization model that considers proactive resilience improvement, and comparing the backbone grid resilience before and after optimization and the load loss under different attack scenarios to verify the effectiveness of the backbone grid resilience assessment method.

[0145] Corresponding to the above method, embodiments of this application also provide a device for assessing the resilience of a power system backbone grid, such as... Figure 4 As shown, the resilience assessment device for the power system backbone grid includes:

[0146] The parameter acquisition unit 410 is used to acquire parameters of the backbone network of the power system;

[0147] Data set construction unit 420 is used to input the parameters of the backbone network into the pre-built calculation models of intentional physical attack load loss and secondary fault load loss to obtain a set of fault scenarios;

[0148] The calculation model for load loss due to intentional physical attack includes: the objective function for load loss due to intentional physical attack and the constraints for intentional physical attack; the calculation model for load loss due to secondary fault includes: the objective function for load loss due to secondary fault and the constraints for secondary fault.

[0149] The fault scenario set includes a deliberate physical attack scenario set and a secondary fault scenario set; the deliberate physical attack scenario set includes multiple different deliberate physical attack scenarios and the deliberate physical attack scenario load loss corresponding to each deliberate physical attack scenario; the secondary fault scenario set includes multiple different secondary fault scenarios and the secondary fault scenario load loss corresponding to each secondary fault scenario.

[0150] Each secondary failure scenario in the set of secondary failure scenarios corresponds to a deliberate physical attack scenario in the set of deliberate physical attack scenarios.

[0151] The evaluation unit 430 is used to input the parameters and fault scenario set of the backbone grid structure into the pre-built backbone grid structure toughness evaluation model to obtain the backbone grid structure toughness evaluation results.

[0152] The functions of each functional unit of the power system backbone grid resilience assessment device provided in the above embodiments of this application can be realized through the above methods and steps. Therefore, the specific working process and beneficial effects of each unit in the power system backbone grid resilience assessment device provided in the embodiments of this application will not be repeated here.

[0153] This application also provides an electronic device, such as... Figure 5 As shown, it includes a processor 510, a communication interface 520, a memory 530, and a communication bus 540, wherein the processor 510, the communication interface 520, and the memory 530 communicate with each other through the communication bus 540.

[0154] Memory 530 is used to store computer programs;

[0155] When the processor 510 executes the program stored in the memory 530, it performs the following steps:

[0156] Obtain the parameters of the backbone network of the power system;

[0157] The parameters of the backbone network are input into the pre-built calculation models for the load loss of intentional physical attacks and the load loss of secondary faults to obtain a set of fault scenarios.

[0158] The calculation model for load loss due to intentional physical attack includes: the objective function for load loss due to intentional physical attack and the constraints for intentional physical attack; the calculation model for load loss due to secondary fault includes: the objective function for load loss due to secondary fault and the constraints for secondary fault.

[0159] The fault scenario set includes a deliberate physical attack scenario set and a secondary fault scenario set; the deliberate physical attack scenario set includes multiple different deliberate physical attack scenarios and the deliberate physical attack scenario load loss corresponding to each deliberate physical attack scenario; the secondary fault scenario set includes multiple different secondary fault scenarios and the secondary fault scenario load loss corresponding to each secondary fault scenario.

[0160] Each secondary failure scenario in the set of secondary failure scenarios corresponds to a deliberate physical attack scenario in the set of deliberate physical attack scenarios.

[0161] The parameters and fault scenario set of the backbone space frame are input into the pre-built backbone space frame toughness assessment model to obtain the backbone space frame toughness assessment results.

[0162] The communication bus mentioned above can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This communication bus can be divided into address bus, data bus, control bus, etc. For ease of illustration, only one thick line is used to represent it in the diagram, but this does not mean that there is only one bus or one type of bus.

[0163] The communication interface is used for communication between the aforementioned electronic devices and other devices.

[0164] The memory may include random access memory (RAM) or non-volatile memory (NVM), such as at least one disk storage device. Optionally, the memory may also be at least one storage device located remotely from the aforementioned processor.

[0165] The processors mentioned above can be general-purpose processors, including central processing units (CPUs), network processors (NPs), etc.; they can also be digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0166] The implementation methods and beneficial effects of the various components of the electronic device in the above embodiments for solving the problem can be found in [reference needed]. Figure 1 The steps in the illustrated embodiments are used to implement the electronic device. Therefore, the specific working process and beneficial effects of the electronic device provided in this application will not be repeated here.

[0167] In another embodiment provided in this application, a computer-readable storage medium is also provided, which stores instructions that, when executed on a computer, cause the computer to perform the resilience assessment method for the power system backbone grid described in any of the above embodiments.

[0168] In another embodiment provided in this application, a computer program product containing instructions is also provided, which, when run on a computer, causes the computer to execute the resilience assessment method for the power system backbone grid described in any of the above embodiments.

[0169] The technical effects of this application will be explained below with reference to experiments.

[0170] The effectiveness of the backbone network resilience assessment method proposed in this application is verified using the IEEE-57 Node power system. The relevant parameter settings are as follows: the power system power reference value is 100 MVA, K... max =K R =2, the number of infeasible cutset scenarios is 10. The test uses the GAMS platform for modeling and solving, and the engineering MILP solver is set to GUROBI (with 4 threads). The computing platform is a PC configured with an Intel(R) i5-8250U CPU and 8.00GB of installed memory.

[0171] (1) Verification of the impact of intentional physical attacks and secondary failure scenarios on the backbone network.

[0172] To verify whether the intentional physical attack load decompression calculation model of this application can achieve the maximum attack effect, the intentional attack model proposed in this application and the Monte Carlo simulation method were used to test the following: Figure 6 The attack targets the IEEE-57 power system backbone network. The IEEE-57 power system backbone network can be obtained using the initial target backbone network generation method and can be considered a typical backbone network cross-section during power system recovery. The IEEE-57 power system backbone network includes all power system units and important loads, containing 27 generator nodes and 26 lines; among the 26 lines, there are backbone network lines and non-backbone network lines. Figure 6 The IEEE-57 power system shown also includes toughened and optimized lines; it also includes lines in deliberate attack scenarios (i.e., lines in deliberate physical attack scenarios) and lines in secondary fault scenarios. Figure 6In the IEEE-57 power system, the numbers 1 to 55 are the numbers of each node (i.e. each bus) in the IEEE-57 power system.

[0173] Using the calculation models for load loss due to intentional physical attacks and load loss due to secondary faults, we obtained the combinations of lines subject to intentional physical attacks and lines subject to secondary faults as shown in Table 1, and the load loss due to intentional physical attacks and load loss due to secondary faults under the corresponding scenarios as shown in Table 2.

[0174] Before the attack, the total load in the power system was 1123MW. Tables 1 and 2 show that the attack had the greatest impact on the affected line sets 1-17-1 and 8-9-1, causing a load loss of 403.7MW, equivalent to 35.95% of the total restored load. Observing the source-load distribution of the power system, it was found that the two generating units located at nodes 1 and 8 have capacities of 575.88MW and 550MW respectively, making them the two largest generating units in the power system. Lines 1-17-1 and 8-9-1 are also transmission lines with high outgoing power capacity from these two generating units; therefore, an attack on them would significantly affect the power supply to the restored load.

[0175] Table 1. Scenarios of Intentional Physical Attacks and Subsequent Failures

[0176] attack scenarios Deliberate physical attack route Secondary fault circuit 1 1-17-1、8-9-1 7-8-1 2 8-9-1、12-17-1 7-8-1 3 1-17-1、9-13-1 7-8-1 4 1-17-1、3-4-1 7-8-1 5 1-17-1、13-49-1 8-9-1 6 1-17-1、4-6-1 8-9-1 7 9-13-1、12-17-1 8-9-1 8 3-4-1、12-17-1 8-9-1 9 1-17-1、6-7-1 8-9-1 10 1-17-1、2-3-1 8-9-1

[0177] Table 2 Load Loss Quantity under Various Attack Scenarios

[0178]

[0179]

[0180] Furthermore, it was found that the scenario with the greatest impact from a deliberate physical attack was not necessarily the scenario with the largest total load loss. For example, after attacking lines 1-17-1 and 4-6-1, line 8-9-1 was subsequently disconnected due to overload, resulting in a total load loss of 488.5MW, equivalent to 43.5% of the total restored load. Simultaneously, it was found that secondary fault lines, i.e., lines with severe overload, were consistently concentrated on lines 7-8-1 and 8-9-1. A possible reason is that after disconnecting some line connections between the units located at nodes 1 and 8, in order to minimize the load loss, the power generated by the larger units at node 8 had to be routed to distant loads, resulting in lines 7-8-1 or 8-9-1 carrying a larger load.

[0181] The Monte Carlo method was used to randomly attack 3000 times, and the frequency distribution of power system load loss was compared. The results are as follows: Figure 7As shown, no samples exceeding 403.7 MW were found for load loss under different Monte Carlo attack frequencies, proving the accuracy of the intentional physical attack load loss calculation model in this application. Furthermore, according to... Figure 7 It can be observed that the load loss in most attacks is concentrated below 150MW, while the load loss in each deliberate attack scenario in Table 2 exceeds 280MW, with a relatively low frequency, indirectly reflecting the deliberate nature of the attacks. Finally, based on the resilience assessment method proposed in this application based on the impact of deliberate physical attacks and secondary faults, the initial IEEE-57 node power system backbone network resilience is calculated to be 0.638. At this low resilience level, the restored load of the power system is highly susceptible to re-outage due to deliberate physical attacks; therefore, resilience optimization of the initial backbone network is necessary.

[0182] (2) Toughness assessment and effectiveness verification of the backbone space frame

[0183] To address the issue of low toughness in the current backbone space structure, the backbone space structure optimization model proposed in this application, which considers proactive toughness enhancement, is used to optimize the toughness of the current backbone space structure, thereby verifying the effectiveness of the proposed toughness assessment method.

[0184] The newly commissioned lines after optimization are as follows: Figure 6 The two newly commissioned lines 1-15-1 and 1-16-1 are used in this application. Based on the resilience assessment method proposed in this application, which considers the impact of intentional physical attacks and secondary faults, the optimized IEEE-57 node power system backbone network resilience is calculated to be 0.937. The two newly commissioned lines effectively enhance the connection between the generating units at node 1 and the power system backbone network. It is also noted that the generating units at node 1 have a large capacity; strengthening their electrical connection with other nodes effectively increases the power support for the load nodes of the power system. Furthermore, the commissioning of line 1-15-1 constructs a ring network structure connecting all generating units in the power system, effectively improving the backbone network resilience.

[0185] Observation Figure 8The comparison chart showing the impact of deliberate physical attacks and secondary fault scenarios before and after optimization clearly reveals that the load loss of the optimized backbone grid under deliberate attack lines 1 and 2 is mostly less than 100MW; while the load loss of the unoptimized backbone grid under the same scenarios is mostly higher than 200MW. The overall load loss of the optimized backbone grid is significantly reduced compared to the unoptimized backbone grid. Furthermore, it was found that the backbone grid resilience optimization targeting the impact of deliberate physical attacks not only has a significant risk mitigation effect on deliberate physical attack scenarios but also has a significant optimization effect on other common attack scenarios. The load loss samples in the resilient optimized backbone grid are all in the lower range (below 200MW), while samples in the 200-400MW load loss range only exist in the unoptimized backbone grid. This significantly improves the power system's resilience to external disturbances during recovery.

[0186] In the above analysis, all scenarios are in K. max =2 was established. For different attack resource conditions, deliberate attack simulations were conducted. The top 20 most influential attack scenarios were selected using an infeasible cutset method. To avoid high similarity between different attack schemes under multiple attack resources, K' was set to 0.5 times K. max And rounded up, we get the following: Figure 9 The diagram shows the load distribution of intentional physical attack scenarios under different attack resources.

[0187] Figure 9 It gives different K max Under the given values, observe the load loss corresponding to the intentional physical attack failure scenarios numbered 1 to 20. Figure 9 It was found that as the number of attack resources increased, the differences in attack effects between different scenarios and under different attack resources gradually decreased, especially in K. max With a threshold of ≥6, the effects of different attack scenarios are not significantly different, indicating that the impact of line attack modes exhibits a saturation phenomenon. This suggests that there exists a relatively fixed set of vulnerable lines in the power system that significantly impact it. On the other hand, it also indicates that under a given load distribution and within the range of deliberate external physical attacks, the resilience or disturbance resistance of the backbone network has a certain limit at certain stages.

[0188] In summary, the backbone grid resilience assessment index based on the impact of deliberate physical attacks and secondary faults can effectively reflect the power system's ability to withstand extreme disturbances. The backbone grid optimization model constructed using this resilience index, which considers proactive resilience enhancement, can significantly optimize the backbone grid resilience and improve the safety of power system recovery.

[0189] Those skilled in the art will understand that the embodiments in this application can be provided as methods, power systems, or computer program products. Therefore, the embodiments in this application can take the form of entirely hardware embodiments, entirely software embodiments, or embodiments combining software and hardware aspects. Furthermore, the embodiments in this application can take the form of computer program products 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.

[0190] This application describes embodiments of methods, apparatus (power systems), and computer program products according to embodiments of this application with reference to flowchart illustrations and / or block diagrams. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0191] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0192] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0193] Although preferred embodiments have been described in this application, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of the embodiments of this application.

[0194] Obviously, those skilled in the art can make various modifications and variations to the embodiments of this application without departing from the spirit and scope of the embodiments of this application. Therefore, if these modifications and variations to the embodiments of this application fall within the scope of the claims in this application and their equivalents, then this application also intends to include these modifications and variations.

Claims

1. A method for assessing the resilience of a power system backbone grid, characterized in that, The method includes: Obtain the parameters of the backbone network of the power system; The parameters of the backbone network are input into the pre-constructed calculation models for the load loss of intentional physical attacks and the load loss of secondary faults to obtain a set of fault scenarios. The calculation model for the load loss due to a deliberate physical attack includes: an objective function for the load loss due to a deliberate physical attack and constraints for a deliberate physical attack; the calculation model for the load loss due to a secondary fault includes: an objective function for the load loss due to a secondary fault and constraints for a secondary fault. The set of fault scenarios includes a set of intentional physical attack scenarios and a set of secondary fault scenarios; the set of intentional physical attack scenarios includes multiple different intentional physical attack scenarios and a load loss amount corresponding to each intentional physical attack scenario; the set of secondary fault scenarios includes multiple different secondary fault scenarios and a load loss amount corresponding to each secondary fault scenario. Each of the secondary failure scenarios in the set of secondary failure scenarios corresponds to a deliberate physical attack scenario in the set of deliberate physical attack scenarios. The parameters of the backbone space frame and the set of failure scenarios are input into a pre-built backbone space frame toughness assessment model to obtain the backbone space frame toughness assessment results.

2. The method as described in claim 1, characterized in that, The parameters of the backbone network are input into a pre-constructed calculation model for the load loss due to intentional physical attack and a calculation model for the load loss due to secondary faults to obtain a set of fault scenarios, including: The parameters of the backbone network are input into a pre-constructed calculation model for the load loss of a deliberate physical attack to obtain a set of deliberate physical attack scenarios. The parameters of the backbone network and the set of deliberate physical attack scenarios are input into a pre-built secondary fault load calculation model to obtain the set of secondary fault scenarios. Based on the set of intentional physical attack scenarios and the set of secondary failure scenarios, a failure scenario set is obtained.

3. The method as described in claim 2, characterized in that, The parameters of the backbone network are input into a pre-constructed model for calculating the load loss of a deliberate physical attack, resulting in a set of deliberate physical attack scenarios, including: The parameters of the power system backbone network are input into a pre-constructed calculation model for the load loss of a deliberate physical attack, resulting in a set of deliberate physical attack scenarios that includes a deliberate physical attack scenario and the corresponding load loss of the deliberate physical attack scenario. The set of deliberate physical attack scenarios and the parameters of the power system backbone network are input into the deliberate physical attack load loss calculation model to obtain the updated set of deliberate physical attack scenarios; wherein, the updated set of deliberate physical attack scenarios includes two different deliberate physical attack scenarios and the deliberate physical attack scenario load loss corresponding to each deliberate physical attack scenario. Determine whether the number of intentional physical attack scenarios included in the updated set of intentional physical attack scenarios meets a preset threshold. If satisfied, output the updated set of intentional physical attack scenarios; If the conditions are not met, the updated set of deliberate physical attack scenarios will be used as the new set of deliberate physical attack scenarios, and the execution steps will be returned: input the set of deliberate physical attack scenarios and the parameters of the power system backbone network into the calculation model of deliberate physical attack load loss, until the number of deliberate physical attack scenarios included in the obtained set of deliberate physical attack scenarios meets the preset threshold; output the set of deliberate physical attack scenarios.

4. The method as described in claim 2, characterized in that, The parameters of the backbone network and the set of deliberate physical attack scenarios are input into a pre-constructed secondary fault load loss calculation model to obtain the set of secondary fault scenarios, including: Choose one intentional physical attack scenario from the set of intentional physical attack scenarios; The selected intentional physical attack scenario and the parameters of the backbone network are input into a pre-built secondary fault load loss calculation model to obtain a secondary fault scenario and a corresponding secondary fault scenario load loss; wherein, the secondary fault scenario corresponds to the selected intentional physical attack scenario. Traverse all intentional physical attack scenarios in the intentional physical attack scenario set to obtain the secondary failure scenario set.

5. The method as described in claim 1, characterized in that, The toughness assessment model for the backbone space frame is as follows: Where R represents the backbone structure toughness assessment model; f K,w f represents the power system load loss under a deliberate physical attack corresponding to attack scenario w; Sec,w α represents the load loss caused by a subsequent fault following a deliberate physical attack; W represents the set of attack scenarios; i represents a power system node, and N represents the set of nodes in the backbone network; i P represents the importance coefficient of the load on node i; d,i This represents the load on node i; n represents the number of attack scenarios.

6. The method as described in claim 1, characterized in that, After inputting the parameters of the backbone space frame and the set of failure scenarios into a pre-constructed backbone space frame resilience assessment model to obtain the backbone space frame resilience assessment results, the method further includes: Based on the backbone space frame toughness assessment model, a backbone space frame toughness optimization model is constructed. The backbone space structure is optimized using the aforementioned backbone space structure toughness optimization model to obtain the optimized backbone space structure.

7. The method as described in claim 6, characterized in that, Based on the aforementioned backbone space frame toughness assessment model, a backbone space frame toughness optimization model is constructed, including: The backbone space structure toughness assessment model is used as the objective function of the backbone space structure toughness optimization model. The power flow constraints under the fault scenario set and the connectivity constraints of the backbone grid are used as constraints for the backbone grid resilience optimization model. Based on the objective function and constraints of the backbone space frame toughness optimization model, the backbone space frame toughness optimization model is obtained.

8. A device for assessing the resilience of a power system backbone grid, characterized in that, The device includes: The parameter acquisition unit is used to acquire parameters of the backbone network of the power system. The dataset construction unit is used to input the parameters of the backbone network into the pre-built calculation models of intentional physical attack load loss and secondary fault load loss to obtain a set of fault scenarios. The calculation model for the load loss due to a deliberate physical attack includes: an objective function for the load loss due to a deliberate physical attack and constraints for a deliberate physical attack; the calculation model for the load loss due to a secondary fault includes: an objective function for the load loss due to a secondary fault and constraints for a secondary fault. The set of fault scenarios includes a set of intentional physical attack scenarios and a set of secondary fault scenarios; the set of intentional physical attack scenarios includes multiple different intentional physical attack scenarios and a load loss amount corresponding to each intentional physical attack scenario; the set of secondary fault scenarios includes multiple different secondary fault scenarios and a load loss amount corresponding to each secondary fault scenario. Each of the secondary failure scenarios in the set of secondary failure scenarios corresponds to a deliberate physical attack scenario in the set of deliberate physical attack scenarios. The evaluation unit is used to input the parameters of the backbone grid and the set of failure scenarios into a pre-built backbone grid toughness evaluation model to obtain the backbone grid toughness evaluation results.

9. An electronic device, characterized in that, The electronic device includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; Memory, used to store computer programs; A processor, when executing a program stored in memory, implements the method of any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method described in any one of claims 1-7.

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