A method and device for generating system protection fault scenario

Abstract

The present invention discloses a method and device for generating a system protection fault scenario. The present invention calculates the index after the failure of a stabilizing control device, adopts a hierarchical analysis method to calculate the weight of each index, calculates the fault risk cost severity factor of each stabilizing control device based on the superior and inferior solution distance method of relative entropy, and adopts a Monte Carlo simulation method to realize the generation of system protection fault scenarios, which provides a basis for predicting, warning and evaluating the system protection action behavior, improving the reliability of system protection, and further guiding the design and operation of system protection.

Description

Technical Field

[0001] The invention relates to a method and a device for generating a system protection fault scenario, and belongs to the field of power systems and automation thereof. Background Art

[0002] With the rapid development of UHV cross-regional interconnected power grids and the access and use of a large number of power electronic equipment, the response characteristics of the power grid are becoming more and more complex. The safety and stability control system (referred to as the security control system) has become the standard configuration for the safe operation of the current UHV AC and DC power grids. Its reliable operation is crucial to ensure the safety and stability of the power grid. A reasonably configured security control system can greatly improve the transmission capacity of the power grid and improve the economic operation level of the power grid. The transmission capacity of the power system may differ several times when the security control system is put into operation than when it is not put into operation. The security control system is not only an important factor in ensuring the safety and stability of the power grid, but also the most reliable method to ensure that the power grid can still operate stably under special circumstances. The security control system has been widely used in regional power grids, and the technology has also made great progress, playing an indispensable role in ensuring the safe and stable operation of regional power grids.

[0003] In recent years, the State Grid Corporation of China has proposed the construction of a comprehensive defense system for the safety of large power grids, namely the requirement of "system protection", and has established system protection in various sub-centers such as Northwest, East China, Central China, Southwest China, and Northeast China, further expanding the architecture and ideas of traditional regional safety and stability control systems, making the security control system cover a wider range, and the control scope extends to global control over a wide range, covering more and more sites, and the coupling relationship between the functions of device strategies is becoming more and more complex. At the same time, due to the limited control resources, the cross-configuration between strategies is gradually increasing, and the impact range of device anomalies is also gradually expanding.

[0004] The existing reliability assurance measures of the device mainly rely on the pre-delivery test and on-site joint debugging of the device, and it is difficult to find all the abnormal links and safety hazards of the device. In the actual system operation, the alarm of the device is mainly discovered by the plant and station personnel and reported step by step, and the personnel analyze and arrange the operation and maintenance. There are many operation and maintenance units involved, the cycle is long and the efficiency is low, and the safety hazards are difficult to eliminate in time. With the expansion of the scale of the device, the increase in the complexity of the device strategy logic function, and the lack of detection means, the risk of power grid operation caused by the hidden dangers of the security control system has increased significantly. In order to carry out centralized and unified management of these devices, driven by the development of power grid dispatching automation and online analysis technology, the existing intelligent grid dispatching control system security control centralized monitoring and management application has realized real-time monitoring of the operating status of the security control device, and can collect various types of information of a single device in real time, such as pressure plate status, channel status, electrical quantity information, etc., which can provide basic information services for the online identification of abnormalities in the safe and stable system.

[0005] However, the existing centralized management system for security and control devices is still at the stage of monitoring the external characteristics of device operation. It mainly conducts online primary system analysis of system protection based on the strategy-level model and real-time status, taking into account the secondary impact. It is unable to monitor the abnormal conditions of the hardware and software inside the device, and then analyze the essential causes of the device abnormality. At the same time, it does not take into account the secondary system enough, lacks the ability to analyze the faults of the primary and secondary linkage, and is difficult to analyze the complex fault scenarios of system protection of the communication factors of the primary and secondary interaction. Under the coupling of UHV AC and DC and the access of a large number of power electronic equipment, the stable form of the system after the fault is more complex, the scope of influence is greatly expanded, and the chain risk is increasing. It is urgent to analyze the complex fault scenarios such as multiple faults and even chain faults, and the whole process of system protection that takes into account the primary and secondary interactions of multiple uncertain factors, analyze and predict the potential risks and hidden dangers of the system outbreak, and improve the reliability of system protection.

[0006] In order to solve the shortcomings of the centralized management system of security control devices, it is necessary to study the method of generating system protection fault scenarios, but there is no such method at present. Summary of the invention

[0007] The present invention provides a method and device for generating a system protection fault scenario, which solves the problems disclosed in the background technology.

[0008] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0009] A method for generating a system protection fault scenario, comprising:

[0010] Calculate the preset system protection failure risk cost severity evaluation indicators;

[0011] The weight of each indicator is calculated using the analytic hierarchy process;

[0012] According to the index, the index weight, and the failure probability of each stabilization and control device of the system protection, the relative entropy superiority and inferiority solution distance method is used to calculate the failure risk cost severity factor of each stabilization and control device of the system protection;

[0013] According to the failure risk cost severity factor of each stabilizing and controlling device of the system protection, the Monte Carlo simulation method is sampled to generate the system protection failure scenario.

[0014] The indicators include the proportion of control strategies, control strategy substitutability and control quantity loss;

[0015] in,

[0016] Control strategy ratio: the ratio of strategies that cannot be executed in the strategy table to the total strategies after the stabilization control device fails;

[0017] Control strategy substitutability: The substitutability of the strategies affected by the failure of the stabilization control device in the entire system;

[0018] Control quantity loss degree: the proportion of failed control quantity in the relevant control measures to the total control quantity after the failure of the stabilization control device.

[0019] The calculation formula for the proportion of control strategies is:

[0020] pro i =n i / sum

[0021] Among them, pro i is the proportion of control strategies after the failure of stabilization device i, n i is the strategy that cannot be executed in the strategy table after the failure of the stabilization control device i, and sum is the total strategy of the strategy table of all stabilization control devices;

[0022] The control strategy substitutability calculation formula is:

[0023]

[0024] Among them, rep i is the control strategy substitutability after the failure of the stabilizing device i, H is the number of primary fault components, r k is the number of related strategies for the primary fault component k after the failure of the stabilization device i, q k is the total number of relevant strategies for a faulty component k;

[0025] The calculation formula of control loss is:

[0026]

[0027] Among them, i is the control loss degree after the failure of the stabilizing device i, pow i,start is the initial control power of the stabilizing device i, pow i,end It is the controllable power after the stabilization device i fails.

[0028] The weight of each indicator is calculated using the hierarchical analysis method, including:

[0029] According to the results of the questionnaire and expert scoring, the judgment matrix of each indicator is obtained;

[0030] According to the judgment matrix, the weight of each indicator is obtained.

[0031] According to the indicators, the weights of the indicators, and the failure probability of each stabilizing control device of the system protection, the relative entropy superiority and inferiority solution distance method is used to calculate the failure risk cost severity factor of each stabilizing control device of the system protection, including:

[0032] According to the indicators, the weights of the indicators, and the failure probability of each stabilization and control device of the system protection, a weighted standardized failure risk cost severity assessment matrix is ​​obtained;

[0033] According to the weighted standardized failure risk cost severity assessment matrix, the positive ideal solution and the negative ideal solution are calculated;

[0034] The relative entropy superior and inferior solution distance method is used to calculate the distance between the indicators of each stabilization control device of the system protection and the positive ideal solution and the negative ideal solution;

[0035] According to the distance, the failure risk cost severity factor of each stabilizing control device protecting the system is calculated.

[0036] Calculate the failure risk cost severity factor of each stabilization device in the system protection, the formula is:

[0037]

[0038] Among them, f i is the failure risk cost severity factor of the stabilizing device i, is the distance between the index of the stabilizing device i and the positive ideal solution, is the distance between the index of the stabilizing device i and the negative ideal solution;

[0039]

[0040] in, is the jth element in the positive ideal solution, is the jth element in the negative ideal solution, Q ij is the element in the i-th row and j-th column of the weighted standardized failure risk cost severity assessment matrix, where j = 1, 2, 3.

[0041] According to the failure risk cost severity factor of each stabilization and control device of the system protection, the Monte Carlo simulation method is sampled to generate system protection failure scenarios, including;

[0042] Sort the failure risk cost severity factors of each stabilization and control device of the system protection in descending order;

[0043] According to the fault risk cost severity factors sorted in descending order, a sampling Monte Carlo simulation method is used to generate system protection fault scenarios.

[0044] A system protection fault scenario generating device, comprising:

[0045] Index calculation module: calculates the preset index for evaluating the severity of system protection failure risk cost;

[0046] Weight calculation module: use hierarchical analysis method to calculate the weight of each indicator;

[0047] Severity factor calculation module: Based on the indicators, the weights of the indicators, and the failure probability of each stabilization and control device of the system protection, the relative entropy superiority and inferiority solution distance method is used to calculate the failure risk cost severity factor of each stabilization and control device of the system protection;

[0048] Scenario generation module: Based on the failure risk cost severity factor of each stabilizing and control device of the system protection, the Monte Carlo simulation method is sampled to generate the system protection failure scenario.

[0049] A computer-readable storage medium storing one or more programs, wherein the one or more programs include instructions, which, when executed by a computing device, cause the computing device to perform a system protection fault scenario generation method.

[0050] A computing device includes one or more processors, one or more memories, and one or more programs, wherein the one or more programs are stored in the one or more memories and are configured to be executed by the one or more processors, and the one or more programs include instructions for executing a system protection fault scenario generation method.

[0051] The beneficial effects achieved by the present invention are as follows: the present invention calculates the indicators after the failure of the stabilizing and controlling device, adopts the hierarchical analysis method to calculate the weight of each indicator, calculates the failure risk cost severity factor of each stabilizing and controlling device based on the superior and inferior solution distance method of relative entropy, and adopts the Monte Carlo simulation method to realize the generation of system protection failure scenarios, which provides a basis for predicting, warning and evaluating the system protection action behavior, improving the reliability of the system protection, and further guiding the design and operation of the system protection. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 A flow chart of a method for generating a system protection failure scenario;

[0053] Figure 2 This is a diagram of the system protection failure risk cost severity evaluation index system. DETAILED DESCRIPTION

[0054] The present invention will be further described below in conjunction with the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and cannot be used to limit the protection scope of the present invention.

[0055] like Figure 1 As shown, a method for generating a system protection fault scenario may include the following steps:

[0056] Step 1, calculating the preset system protection failure risk cost severity evaluation index;

[0057] Step 2, use the analytic hierarchy process to calculate the weight of each indicator;

[0058] Step 3, according to the index, the weight of the index, and the failure probability of each stabilization and control device of the system protection, the relative entropy superiority and inferiority solution distance method is used to calculate the failure risk cost severity factor of each stabilization and control device of the system protection;

[0059] Step 4: Based on the failure risk cost severity factor of each stabilizing and controlling device of the system protection, a Monte Carlo simulation method is used to generate a system protection failure scenario.

[0060] The above method first calculates the indicators after the failure of the stabilizing and controlling device, uses the hierarchical analysis method to calculate the weight of each indicator, and calculates the failure risk cost severity factor of each stabilizing and controlling device based on the superior and inferior solution distance method based on relative entropy. Finally, the Monte Carlo simulation method is used to realize the generation of system protection fault scenarios.

[0061] Before generating the system protection failure scenario, three indicators for evaluating the severity of the system protection failure risk cost can be defined according to the composition of the system protection structure, including the proportion of control strategies, the substitutability of control strategies, and the degree of control loss.

[0062] The proportion of control strategies: the proportion of strategies that cannot be executed in the strategy table to the total strategies after the stabilization control device fails. Select a stabilization control device i (1≤i≤M), M is the total number of stabilization control devices in the system protection, and i is an integer between 1 and M.

[0063] Traverse the strategy tables of all stabilization control devices, and count the number of stabilization control device i sites covered by the control measures in the strategy table, that is, the strategies that cannot be executed in the strategy table after the stabilization control device i fails. The proportion of the control strategies can be calculated using the following formula:

[0064] pro i =n i / sum

[0065] Among them, pro i is the proportion of control strategies after the failure of stabilization device i, n i is the strategy that cannot be executed in the strategy table after the stabilization control device i fails, and sum is the total strategy of all stabilization control device strategy tables; the proportion of control strategies is a positive indicator.

[0066] Control strategy substitutability: The substitutability of the strategies affected by the failure of the stabilizing control device in the entire system. Select the stabilizing control device i, and record the number of faulty components as H. Then the control strategy substitutability can be calculated using the following formula:

[0067]

[0068] Among them, rep i is the control strategy substitutability after the failure of the stabilization device i, r kis the number of related strategies for the primary fault component k after the failure of the stabilization device i, q k is the total number of relevant strategies for a faulty component k; the substitutability of control strategies is a negative indicator.

[0069] Control quantity loss degree: the proportion of failed control quantity in related control measures to the total control quantity after the failure of the stabilization control device. For the selected stabilization control device i, the control quantity loss degree can be calculated using the following formula:

[0070]

[0071] Among them, i is the control loss degree after the failure of the stabilizing device i, pow i,start is the initial control power of the stabilizing device i, pow i,end It is the controllable power after the failure of the stabilizing device i; the control quantity loss degree is a positive indicator.

[0072] Based on the consequences of system protection failures, on the basis of the above three indicators, we can construct Figure 2 The system protection failure risk cost severity evaluation index system shown in the figure can use three indicators to evaluate the system protection failure risk cost severity.

[0073] Therefore, when generating scenarios, the indicators for evaluating the severity of system protection failure risk costs are calculated according to the above formula, and the judgment matrix of each indicator is obtained based on the results of the questionnaire and expert scoring.

[0074] Specifically, according to the questionnaire and expert scoring results in Table 1, the scores in the questionnaire were calculated using the arithmetic mean method, and the pairwise judgment matrix B of each indicator was obtained by rounding off. i′j′ ) n×n (n=3), where b i′j′ is the importance of indicator i′ relative to indicator j′, and the indicator weight is calculated based on it.

[0075] Table 1 Questionnaire

[0076]

[0077]

[0078] The questionnaire adopts the 1-9 scale method to generate a judgment matrix model and lists evaluation indicators for the severity of system protection failure risk costs, so that experts can determine the relative relationship between evaluation indicators through scoring.

[0079] Then, according to the judgment matrix, the weight of each indicator is obtained. Specifically, the eigenvector corresponding to the judgment matrix is ​​processed, the weight vector of the relevant factors at each level is calculated, and the maximum eigenvalue λ is calculated.max Because the method of pairwise comparison is used, the judgments obtained are likely to be inconsistent. However, the AHP does not require that the judgment matrices constructed by different personnel be absolutely identical, as long as the judgments obtained are generally consistent. max Finally, the consistency index is used to perform consistency check on the judgment matrices at each level. If the check passes, the weight vector is calculated. If not, a new judgment matrix needs to be constructed.

[0080] The steps to obtain the indicator weights can be as follows:

[0081] First, multiply the elements of each row of the judgment matrix to get the product

[0082] Next, calculate M i′ The nth root of:

[0083] Pair Vector normalization:

[0084]

[0085] The obtained W=(W1,W2,…,W n ) T That is the required weight vector;

[0086] Then, calculate the maximum eigenvalue of the judgment matrix A consistency check is performed on the judgment matrix. If the check passes, the weight result is W = (W1, W2, W3).

[0087] The consistency check process can be as follows:

[0088] 1) Calculate the consistency index that reflects the gap between the judgment matrix and complete consistency The smaller the CI value, the smaller the deviation;

[0089] 2) Calculate the consistency index value based on CI It is generally believed that when CR<0.1, the consistency of the index meets the requirements, where RI is the average random consistency index, and its corresponding coefficient values ​​at different orders are shown in Table 2.

[0090] Table 2 Average random consistency index table

[0091]

[0092] After obtaining the index weights, the relative entropy superior and inferior solution distance method is used to calculate the fault risk cost severity factor of each stabilization and control device of the system protection. The specific process can be:

[0093] S1) A weighted standardized failure risk cost severity assessment matrix is ​​obtained based on the indicators, the weights of the indicators, and the failure probabilities of the various stabilization and control devices of the system protection.

[0094] Note that the system protection structure has M stabilizing devices, and the failure probability of stabilizing device i is fau i (i=1,…,M), use V ij (i=1,…,M;j=1,2,3) represents the weighted value of index j of stabilization control device i (i.e., the product of index value and corresponding weight), then:

[0095] The matrix composed of the weighted values ​​of all indicators of M stabilization control devices is:

[0096]

[0097] Upward V ij To standardize:

[0098]

[0099] Construct a weighted standardized failure risk cost severity assessment matrix (Q ij ) M×3 , where Q ij =W j U ij , W j It is the j-th element in W, j=1,2,3, corresponding to 3 indicators respectively.

[0100] S2) Calculate the positive ideal solution and the negative ideal solution according to the weighted standardized failure risk cost severity assessment matrix.

[0101] The positive ideal solution is

[0102] The negative ideal solution is

[0103] in,

[0104]

[0105] S3) The relative entropy superior-inferior solution distance method is used to calculate the distance between the indicators of each stabilization control device of the system protection and the positive ideal solution and the negative ideal solution.

[0106]

[0107] in, is the distance between the index of the stabilizing device i and the positive ideal solution, is the distance between the index of the stabilizing device i and the negative ideal solution, is the jth element in the positive ideal solution, is the jth element in the negative ideal solution, Q ij is the element in the i-th row and j-th column of the weighted normalized failure risk cost severity assessment matrix.

[0108] S4) Calculate the failure risk cost severity factor of each stabilization and control device of the system protection according to the distance.

[0109]

[0110] Among them, f i is the failure risk cost severity factor of stabilizing device i.

[0111] The obtained fault risk cost severity factor f is sorted by bubble sorting method. i (i=1,…,M) are sorted in descending order, that is, the sorting result of the fault risk cost severity factor from large to small is obtained, which is recorded as g i (i=1,…,M).

[0112] According to the fault risk cost severity factors sorted in descending order, the sampling Monte Carlo simulation method is used to generate system protection fault scenarios. The process can be:

[0113] 1) Calculate the probability of stabilization device i being selected

[0114] 2) Calculate the cumulative probability of stabilization device i

[0115] 3) Randomly generate a random number rand uniformly distributed in [0,1]. If rand≤q1, the stabilization device k=1 is selected; if q k-1 <rand≤q k (2≤k≤M), then the stabilizing device k is selected;

[0116] 4) If N (N≤M) stabilization devices need to be selected, repeat 3) N times;

[0117] 5) Finally, N stabilization device failures are selected to generate system protection failure scenarios.

[0118] The above method provides a basis for predicting, warning and evaluating the system protection action behavior, improving the reliability of system protection, and guiding the design and operation of system protection.

[0119] Based on the same technical solution, the present invention also discloses a software device of the above method, namely a system protection fault scenario generation device, comprising:

[0120] Index calculation module: calculates the preset index for evaluating the severity of system protection failure risk cost;

[0121] Weight calculation module: use hierarchical analysis method to calculate the weight of each indicator;

[0122] Severity factor calculation module: Based on the indicators, the weights of the indicators, and the failure probability of each stabilization and control device of the system protection, the relative entropy superiority and inferiority solution distance method is used to calculate the failure risk cost severity factor of each stabilization and control device of the system protection;

[0123] Scenario generation module: Based on the failure risk cost severity factor of each stabilizing and control device of the system protection, the Monte Carlo simulation method is sampled to generate the system protection failure scenario.

[0124] The data processing flow in the module is consistent with that in the above method and will not be repeated here.

[0125] Based on the same technical solution, the present invention also discloses a computer-readable storage medium storing one or more programs, wherein the one or more programs include instructions, and when the instructions are executed by a computing device, the computing device executes a system protection fault scenario generation method.

[0126] Based on the same technical solution, the present invention also discloses a computing device, comprising one or more processors, one or more memories and one or more programs, wherein the one or more programs are stored in the one or more memories and are configured to be executed by the one or more processors, and the one or more programs include instructions for executing a system protection fault scenario generation method.

[0127] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may 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.

[0128] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as 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 a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1A device that provides the functions specified in a block or multiple blocks.

[0129] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0130] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0131] The above are merely embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention are included in the scope of the claims of the present invention to be approved.

Claims

1. A method for generating a system protection fault scenario, characterized in that: include: Calculate the indicators for evaluating the severity of the risk cost of the preset system protection failure; the indicators include the proportion of control strategies, control strategy substitutability and control quantity loss; the proportion of control strategies: the proportion of strategies that cannot be executed in the strategy table to the total strategies after the failure of the stabilization device; control strategy substitutability: the substitutability of the strategies affected by the failure of the stabilization device in the entire system; control quantity loss: the proportion of failed control quantities in the relevant control measures to the total control quantities after the failure of the stabilization device; The weight of each indicator is calculated using the analytic hierarchy process; According to the index, the index weight, and the failure probability of each stabilization and control device of the system protection, the relative entropy superiority and inferiority solution distance method is used to calculate the failure risk cost severity factor of each stabilization and control device of the system protection; The fault risk cost severity factors of each stabilization and control device of the system protection are sorted in descending order, and the system protection fault scenario is generated by sampling the Monte Carlo simulation method according to the fault risk cost severity factors sorted in descending order; The process of generating system protection failure scenarios includes: 1) Calculate the probability of stabilization device i being selected Among them, g i is the failure risk cost severity factor of the stabilizing device i in descending order; 2) According to the probability p of the stabilization device i being selected i , calculate the cumulative probability of stabilization device i 3) Randomly generate a random number rand uniformly distributed in [0,1]. If rand≤q1, the stabilization device k=1 is selected; if q k-1 <rand≤q k , 2≤k≤M, then the stabilizing control device k is selected, and M is the total number of stabilizing control devices in the system protection; 4) If N stabilization devices need to be selected, repeat 3) N times; where N≤M; 5) Finally, N stabilization device failures are selected to generate system protection failure scenarios.

2. A method for generating a system protection fault scenario according to claim 1, characterized in that: The calculation formula for the proportion of control strategies is: pro i =n i / sum Among them, pro i is the proportion of control strategies after the failure of stabilization device i, n i is the strategy that cannot be executed in the strategy table after the failure of the stabilization control device i, and sum is the total strategy of the strategy table of all stabilization control devices; The control strategy substitutability calculation formula is: Among them, rep i is the control strategy substitutability after the failure of the stabilizing device i, H is the number of primary fault components, r k is the number of related strategies for the primary fault component k after the failure of the stabilization device i, q k is the total number of relevant strategies for a faulty component k; The calculation formula of control loss is: Among them, i is the control loss degree after the failure of the stabilizing device i, pow i,start is the initial control power of the stabilizing device i, pow i,end It is the controllable power after the stabilization device i fails.

3. A method for generating a system protection fault scenario according to claim 1, characterized in that: The weight of each indicator is calculated using the hierarchical analysis method, including: According to the results of the questionnaire and expert scoring, the judgment matrix of each indicator is obtained; According to the judgment matrix, the weight of each indicator is obtained.

4. A method for generating a system protection fault scenario according to claim 1, characterized in that: According to the indicators, the weights of the indicators, and the failure probability of each stabilizing control device of the system protection, the relative entropy superiority and inferiority solution distance method is used to calculate the failure risk cost severity factor of each stabilizing control device of the system protection, including: According to the indicators, the weights of the indicators, and the failure probability of each stabilization and control device of the system protection, a weighted standardized failure risk cost severity assessment matrix is ​​obtained; According to the weighted standardized failure risk cost severity assessment matrix, the positive ideal solution and the negative ideal solution are calculated; The relative entropy superior and inferior solution distance method is used to calculate the distance between the indicators of each stabilization control device of the system protection and the positive ideal solution and the negative ideal solution; According to the distance, the failure risk cost severity factor of each stabilizing control device protecting the system is calculated.

5. A method for generating a system protection fault scenario according to claim 4, characterized in that: Calculate the failure risk cost severity factor of each stabilization device in the system protection, the formula is: Among them, f i is the failure risk cost severity factor of the stabilizing device i, is the distance between the index of the stabilizing device i and the positive ideal solution, is the distance between the index of the stabilizing device i and the negative ideal solution; in, is the jth element in the positive ideal solution, is the jth element in the negative ideal solution, Q ij is the element in the i-th row and j-th column of the weighted standardized failure risk cost severity assessment matrix, where j = 1, 2, 3.

6. A system protection fault scenario generating device, characterized in that: include: Index calculation module: calculates the preset index for evaluating the severity of the risk cost of system protection failure; the indexes include the proportion of control strategies, control strategy substitutability and control quantity loss degree; the proportion of control strategies: the proportion of strategies that cannot be executed in the strategy table to the total strategies after the failure of the stabilization control device; control strategy substitutability: the substitutability of the strategies affected by the failure of the stabilization control device in the entire system; control quantity loss degree: the proportion of failed control quantities in the relevant control measures to the total control quantities after the failure of the stabilization control device; Weight calculation module: use hierarchical analysis method to calculate the weight of each indicator; Severity factor calculation module: Based on the indicators, the weights of the indicators, and the failure probability of each stabilization and control device of the system protection, the relative entropy superiority and inferiority solution distance method is used to calculate the failure risk cost severity factor of each stabilization and control device of the system protection; Scenario generation module: sort the fault risk cost severity factors of each stabilization and control device of the system protection in descending order, and generate the system protection fault scenario by sampling Monte Carlo simulation method according to the fault risk cost severity factors sorted in descending order; The process of generating system protection failure scenarios includes: 1) Calculate the probability of stabilization device i being selected Among them, g i is the failure risk cost severity factor of the stabilizing device i in descending order; 2) According to the probability p of the stabilization device i being selected i , calculate the cumulative probability of stabilization device i 3) Randomly generate a random number rand uniformly distributed in [0,1]. If rand≤q1, the stabilization device k=1 is selected; if q k-1 <rand≤q k , 2≤k≤M, then the stabilizing control device k is selected, and M is the total number of stabilizing control devices in the system protection; 4) If N stabilization devices need to be selected, repeat 3) N times; where N≤M; 5) Finally, N stabilization device failures are selected to generate system protection failure scenarios.

7. A computer-readable storage medium storing one or more programs, characterized in that: The one or more programs include instructions which, when executed by a computing device, cause the computing device to perform any one of the methods according to claims 1 to 5 .

8. A computing device, characterized in that include: One or more processors, one or more memories, and one or more programs, wherein the one or more programs are stored in the one or more memories and are configured to be executed by the one or more processors, and the one or more programs include instructions for executing any of the methods according to claims 1 to 5.

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