Method and apparatus for determining seismic resilience of substation, computer device, and storage medium

Abstract

The present application relates to a method for determining seismic resilience of a substation, comprising: acquiring a target seismic intensity and preset parameters of a substation; on the basis of the target seismic intensity and the preset parameters, establishing a directed network graph model and a device damage probability matrix of the substation; on the basis of the directed network graph model and the device damage probability matrix, determining a total repair duration of the substation based on the target seismic intensity after an earthquake; establishing a vectorization analysis model of the substation on the basis of the preset parameters, and determining a residual function evaluation value of the substation on the basis of the vectorization analysis model; and on the basis of the product of the total repair duration and the residual function evaluation value, determining a seismic resilience value of the substation corresponding to the target seismic intensity.

Description

Method, device, computer equipment and storage medium for determining seismic toughness of substation

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims priority to Chinese patent application number 2023112777212, filed with the Patent Office of China on September 28, 2023, entitled “Method, device, computer equipment and storage medium for determining seismic resilience of substations,” the entire contents of which are incorporated herein by reference. Technical Field

[0003] The present application relates to the technical field of seismic resilience assessment in power systems, and in particular to a method, apparatus, computer equipment, and storage medium for determining seismic resilience of a substation. Background Art

[0004] A substation is a complex system composed of various types of electrical equipment, connected in series or parallel via busbars. As a key node controlling the flow of power, distributing electrical energy, and adjusting and transforming transmission voltage, substations play a vital role in the transmission and distribution network. During an earthquake, they must not only maintain essential functions but also quickly restore normal operations to maintain the fundamental social functions of modern cities. Therefore, they require high earthquake resistance and rapid response capabilities.

[0005] However, recent earthquake damage experience both domestically and internationally has demonstrated that substation systems are highly vulnerable to earthquakes and are difficult to repair and rebuild after damage, resulting in significant long-term negative impacts on social functions and economic development in affected areas. Therefore, it is necessary to comprehensively assess substations' ability to withstand earthquake risks and recover quickly after an earthquake. This typically involves assessing the seismic resilience of substation systems, identifying weaknesses through this resilience, and developing targeted, cost-effective design methods or technical improvements to enhance their seismic performance.

[0006] Currently, simulations based on the Simulink platform are used to determine the seismic resilience of substations. However, these simulations are slow and time-consuming, making it difficult to quickly calculate seismic resilience. Furthermore, system analysis methods based on fault tree and minimum cut set theory have high computational complexity and are difficult to analyze for large-scale, complex, directed network systems.

[0007] Summary of the Invention

[0008] According to various embodiments of the present application, a method, apparatus, computer equipment, and storage medium for determining the seismic resilience of a substation are provided, which can simplify the calculation of seismic resilience assessment and improve calculation efficiency.

[0009] In a first aspect, an embodiment of the present application provides a method for determining the seismic resilience of a substation, the method comprising:

[0010] Obtain target earthquake intensity and substation preset parameters;

[0011] Establishing a directed network graph model and an equipment damage probability matrix of the substation according to the target earthquake intensity and the preset parameters;

[0012] Determining, based on the directed network graph model and the equipment damage probability matrix, a total repair time of the substation after an earthquake based on a target earthquake intensity;

[0013] Establishing a vector analysis model of the substation according to preset parameters, and determining a residual function evaluation value of the substation according to the vector analysis model; and

[0014] Based on the product of the total repair time and the residual function evaluation value, the seismic toughness value of the substation corresponding to the target earthquake intensity is determined.

[0015] In a second aspect, an embodiment of the present application provides a device for determining the seismic toughness of a substation, the device comprising:

[0016] A parameter determination module is used to obtain the target earthquake intensity and the preset parameters of the substation;

[0017] an equipment status determination module, configured to establish a directed network graph model and an equipment damage probability matrix of the substation according to the target earthquake intensity and the preset parameters;

[0018] A time statistics module, configured to determine a total repair time of the substation after an earthquake based on a target earthquake intensity based on the directed network graph model and the equipment damage probability matrix;

[0019] a vector analysis module, configured to establish a vector analysis model of the substation according to preset parameters, and determine a residual function evaluation value of the substation according to the vector analysis model; and

[0020] The seismic resilience determination module is used to determine the seismic resilience value of the substation corresponding to the target earthquake intensity based on the product of the total repair time and the residual function evaluation value.

[0021] In a third aspect, an embodiment of the present application provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0022] Obtain target earthquake intensity and substation preset parameters;

[0023] Establishing a directed network graph model and an equipment damage probability matrix of the substation according to the target earthquake intensity and the preset parameters;

[0024] Determining, based on the directed network graph model and the equipment damage probability matrix, a total repair time of the substation after an earthquake based on a target earthquake intensity;

[0025] Establishing a vector analysis model of the substation according to preset parameters, and determining a residual function evaluation value of the substation according to the vector analysis model; and

[0026] Based on the product of the total repair time and the residual function evaluation value, the seismic toughness value of the substation corresponding to the target earthquake intensity is determined.

[0027] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the following steps are implemented:

[0028] Obtain target earthquake intensity and substation preset parameters;

[0029] Establishing a directed network graph model and an equipment damage probability matrix of the substation according to the target earthquake intensity and the preset parameters;

[0030] Determining, based on the directed network graph model and the equipment damage probability matrix, a total repair time of the substation after an earthquake based on a target earthquake intensity;

[0031] Establishing a vector analysis model of the substation according to preset parameters, and determining a residual function evaluation value of the substation according to the vector analysis model; and

[0032] Based on the product of the total repair time and the residual function evaluation value, the seismic toughness value of the substation corresponding to the target earthquake intensity is determined.

[0033] The above-mentioned method, device, computer equipment and storage medium for determining the seismic resilience of a substation use a directed network graph model and matrix operations to quickly determine the damage state of the equipment in a matrix modular manner, reduce the amount of data processing, and then determine the total repair time of the substation under the current target earthquake intensity. Then, by establishing a vectorized analysis model of the substation, the operation process of the substation is simulated in a logical operation manner to quickly determine the residual function evaluation value of the substation, and then determine the seismic resilience value of the substation corresponding to the target earthquake intensity by the product of the total repair time and the residual function evaluation value, effectively simplifying the calculation complexity of the residual function evaluation value and the total repair time of the substation, significantly improving the calculation speed, and thus helping to improve the seismic performance of the substation.

[0034] The details of one or more embodiments of the invention are set forth in the accompanying drawings and the description below. Other features, objects, and advantages of the invention will become apparent from the description, drawings, and claims. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] FIG1 is a diagram illustrating an application environment of a method for determining seismic toughness of a substation according to an embodiment of the present invention;

[0036] FIG2 is a schematic flow chart of a method for determining the seismic resilience of a substation according to an embodiment of the present invention;

[0037] FIG3 is a flow chart of steps for determining the seismic toughness of a substation in another embodiment of the present invention;

[0038] FIG4 is a general plan view of a 220 kV substation according to an embodiment of the present invention;

[0039] FIG5 is a side view of AA of the 220 kV device in FIG4 ;

[0040] FIG6 is a side view of the BB of the 110 kV device in FIG4 ;

[0041] FIG7 is a directed network diagram of a 220 kV substation according to an embodiment of the present invention;

[0042] FIG8 is a curve of the residual function and seismic toughness index of a 220 kV substation after an earthquake according to an embodiment of the present invention;

[0043] FIG9 is a structural block diagram of a device for determining the seismic toughness of a substation according to an embodiment of the present invention;

[0044] FIG10 is a diagram showing the internal structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0045] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0046] The method for determining the seismic toughness of a substation provided in an embodiment of the present application can be applied in an application environment as shown in FIG1 . The terminal 102 communicates with the server 104 via a network. The data storage system can store data that the server 104 needs to process. The data storage system can be integrated on the server 104, or it can be placed on the cloud or other network servers. For example, the acquired target earthquake intensity and the preset parameter data of the substation are stored in the data storage system, and the preset parameters of the substation can be input through the terminal. The terminal 102 can be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, Internet of Things devices and portable wearable devices. The Internet of Things devices can be smart speakers, smart TVs, smart air conditioners, smart car-mounted devices, etc. Portable wearable devices can be smart watches, smart bracelets, head-mounted devices, etc. The server 104 can be implemented as an independent server or a server cluster consisting of multiple servers.

[0047] Traditional technology typically uses the Simulink platform to establish a directed network model to simulate substation seismic resilience. However, performing calculations based on the Simulink platform requires the analysis of seismic resilience to rely on the Simulink platform, which has higher usage requirements and cannot be applied to all usage scenarios.

[0048] In a first aspect, as shown in FIG2 , this embodiment provides a method for determining the seismic resilience of a substation, the method comprising:

[0049] Step S202: Obtain target earthquake intensity and preset parameters of the substation.

[0050] The target earthquake intensity refers to the intensity of the earthquake waves experienced by the substation location at a certain point in time.

[0051] Exemplarily, the preset parameters of the substation include: equipment type, number of equipment, connection mode between equipment, and seismic vulnerability curve of equipment. It can be understood that different equipment types and connection modes between multiple devices will cause different damage to the equipment under the same earthquake intensity. Therefore, before determining the seismic resilience of the substation, it is necessary to determine the basic parameters such as the equipment type, number of equipment, and connection mode between equipment of the substation. Among them, the equipment types include gantries, voltage transformers, current transformers, disconnectors, circuit breakers, transformers and support insulators, for example, the gantries, current transformers, disconnectors, circuit breakers and transformers shown in Figures 5 to 7, with PF, CT, DS, CB and TF representing the gantry, current transformer, disconnector, circuit breaker and transformer respectively.

[0052] Step S204: establishing a directed network graph model and an equipment damage probability matrix of the substation according to the target earthquake intensity and the preset parameters.

[0053] Among them, each node in the directed network graph model of the substation represents an electrical device in the substation, and each line represents the wire connecting each electrical device. Therefore, the directed network graph model of the substation can be established according to the number of devices and the connection mode between the devices and the power transmission path based on the connection mode.

[0054] The seismic vulnerability of equipment refers to the probability of failure of the equipment structure under a certain limit state under the action of an earthquake of a certain intensity. The seismic vulnerability of the equipment under different earthquake intensities can be obtained by using empirical methods or Monte Carlo simulation methods, and a seismic vulnerability curve can be plotted. Based on the seismic vulnerability of each device, a damage probability matrix of the equipment can be established.

[0055] Step S206: Based on the directed network graph model and the equipment damage probability matrix, determine the total repair time of the substation after the target earthquake intensity.

[0056] The total repair time for a substation is the sum of the post-earthquake repair times for multiple devices. The devices requiring repair are identified based on the device damage probability matrix. Using a directed network graph model, the post-earthquake repair time for each device can be simulated and calculated. The total repair time for each device is then calculated.

[0057] Step S208: establishing a vector analysis model of the substation according to preset parameters, and determining a residual function evaluation value of the substation according to the vector analysis model.

[0058] The vectorized analysis model simulates the connection patterns of substation equipment and, based on these patterns, simulates power flow to determine the operational integrity of each line, thereby determining the substation's residual function and, ultimately, its residual function evaluation value. Simulations using the vectorized analysis model only require determining the operational integrity of each line, eliminating the need for complex simulations based on the Simulink platform. This effectively simplifies computation and significantly improves speed.

[0059] It can be understood that the residual function of a substation refers to the number of transmission lines that remain functional after the substation is struck by an earthquake, and the residual function of the substation is quantified by the residual function evaluation value.

[0060] Step S210: Determine the seismic resilience value of the substation corresponding to the target earthquake intensity based on the product of the total repair time and the residual function evaluation value.

[0061] Seismic resilience is used to quantify a substation's ability to withstand earthquake risks and recover after an earthquake. This helps identify weaknesses within a substation and propose targeted, cost-effective design methods or technical improvements to improve the substation's seismic performance.

[0062] For example, the specific calculation formula of the seismic toughness value R is as follows: R = F × T r Where F represents the residual function evaluation value of the substation system, T r The total repair time for all substation equipment is 100%. The seismic resilience index R reflects the seismic resilience level of the substation system. A larger R indicates a lower seismic resilience level, which in turn results in greater economic losses.

[0063] The present application provides a method for determining the seismic resilience of a substation. By using a directed network graph model and matrix operations, the damage state of the equipment is quickly determined in a matrix modular manner, the amount of data processing is reduced, and the total repair time of the substation under the current target earthquake intensity is determined. Then, by establishing a vectorized analysis model of the substation, the operation process of the substation is simulated in a logical operation manner to quickly determine the residual function evaluation value of the substation. The seismic resilience value of the substation corresponding to the target earthquake intensity is then determined by the product of the total repair time and the residual function evaluation value. This effectively simplifies the computational complexity of the residual function evaluation value and the total repair time of the substation, significantly improves the computational speed, and is conducive to improving the seismic performance of the substation. The method for determining the seismic resilience of a substation does not need to rely on the Simulink platform and is easy to apply.

[0064] In one embodiment, step S204 of "establishing the substation directed network graph model and equipment damage probability matrix according to the target earthquake intensity and the preset parameters" includes:

[0065] Step 1: Establish a directed network graph model of the substation based on the type, number, and connection mode of the substation equipment;

[0066] Step 2: Determine the failure probability of each device according to the seismic vulnerability curve of the substation equipment and the target earthquake intensity.

[0067] For example, seismic vulnerability refers to the probability of failure of a device structure exceeding a certain limit state under an earthquake of a certain intensity. Therefore, the failure probability of the device under the target earthquake intensity can be determined by the seismic vulnerability curve and the target earthquake intensity.

[0068] Step 3: Based on the failure probabilities of all the devices, establish an equipment damage probability matrix for the substation.

[0069] Exemplarily, the “establishing an equipment damage probability matrix of the substation based on the failure probabilities of all the equipment” includes:

[0070] Step 1: Determine a parameter representing the target ground motion intensity. In this embodiment, the parameter is set to be the peak ground acceleration (PGA).

[0071] Step 2: Determine a functional relationship between the failure probability of each device and a characteristic parameter of the target ground motion intensity, wherein the functional relationship obeys a lognormal cumulative distribution with a median μ and a logarithmic standard deviation β:

[0072] Step 3: Determine the equipment damage probability matrix V based on the functional relationship and the target earthquake intensity: V i，j =P i，j (PGA=a), where V i,j represents the jth element in the i-th row of the matrix, P i,j represents the failure probability of the jth device of the i-th type.

[0073] In one embodiment, step 206 of "determining the total repair time of the substation after an earthquake based on a target earthquake intensity based on the directed network graph model and the equipment damage probability matrix" includes:

[0074] Step 1: Based on the directed network graph model and the equipment damage probability matrix, determine the equipment status matrix of the substation.

[0075] Step 2: Based on the equipment status matrix, determine the total repair time of the substation after the earthquake.

[0076] The elements of the equipment status matrix record whether a device was damaged by the earthquake during the Monte Carlo simulation. Each Monte Carlo simulation generates a random number matrix R with the same dimensions as the device damage probability matrix V. The elements of R are random numbers uniformly distributed between 0 and 1. The working status of each device is determined by comparing the random number matrix with the device damage probability matrix, with 0 representing damaged and 1 representing intact, as shown in the following formula: C = R > V. Thus, the device status is determined based on the device status matrix, and the equipment requiring repair in the substation is determined. The repair time required for each damaged device is determined based on the device type and earthquake intensity. The total repair time for the substation is then determined based on the repair time of the equipment requiring repair.

[0077] For example, the repair time for each type of equipment can be obtained from historical statistics, by collecting multiple equipment samples of the same type and determining the time required to repair the equipment of this type under the same earthquake intensity in historical data.

[0078] Furthermore, in one embodiment, determining the equipment status matrix of the substation based on the directed network graph model and the equipment damage probability matrix includes:

[0079] Step 1: Based on the directed network graph model and the equipment damage probability matrix, the working status of the equipment is determined according to the Monte Carlo simulation method;

[0080] Step 2: Perform multiple simulations based on the Monte Carlo method to determine the working status of multiple devices;

[0081] Step 3: Based on the working status of multiple devices, establish the equipment status matrix of the substation.

[0082] Specifically, the Monte Carlo method is used to determine whether the equipment is damaged based on the equipment damage probability matrix, and then the power flow on each outgoing line is simulated based on the directed network graph model to determine the working status of each device.

[0083] In one embodiment, step S208 of "establishing a vector analysis model of the substation according to preset parameters, and determining a residual function evaluation value of the substation according to the vector analysis model" includes:

[0084] Step 1: establishing the vector analysis model according to the connection mode between the devices;

[0085] Step 2: Obtaining a device function matrix based on the vectorized analysis model;

[0086] Step 3: Determine the number of operable outgoing lines in the substation and the total number of outgoing lines in the substation before the earthquake based on the equipment function matrix;

[0087] Step 4: Obtain the residual function evaluation value of the substation according to the quotient of the number of operable outgoing lines in the substation after the earthquake and the total number of outgoing lines in the substation before the earthquake.

[0088] Assuming that each device in the substation is independent of each other, and only considering the two states of the device, working and failure, the device is vectorized, with 0 representing the failure state and 1 representing the working state. All devices in the substation are represented by two matrices, which include a device state matrix and a device function matrix. The device state matrix is ​​used to represent whether the device itself is damaged, and the device function matrix represents whether the device can normally transmit electrical energy to downstream devices. In this way, the device function matrix of the downstream device is determined by its own device state matrix and the function matrix of the upstream device, that is, whether the outgoing line can operate normally is determined by whether the most downstream device of the substation outgoing line can operate normally. Therefore, the remaining function of the system can be defined as the connectivity ratio of the most downstream device of the system, that is, the ratio of 1 to the total number of elements in the device function matrix of the most downstream device.

[0089] For example, the specific calculation formula of the residual function evaluation index F of the substation system is as follows: Among them, N out Refers to the total number of outgoing lines in the system, n out Refers to the number of output lines that can work normally after the earthquake.

[0090] In one embodiment, step S210 of “determining the seismic resilience value of the substation based on the product of the total repair time and the residual function evaluation value” includes:

[0091] Step 1: Based on the same target earthquake intensity, repeatedly obtain multiple seismic resilience indicators of the substation;

[0092] Step 2: Based on the multiple seismic toughness indices, determine an expected value of the seismic toughness index, where the expected value is the seismic toughness value.

[0093] In order to avoid errors in single calculations, the seismic toughness index of the substation under the same target earthquake intensity is repeatedly calculated to obtain multiple seismic toughness indexes. Then, based on the multiple seismic toughness indexes, the expected value of the seismic toughness index is calculated. The expected value is used as the seismic toughness value, which can effectively avoid calculation errors and improve calculation accuracy.

[0094] In one embodiment, after step 210 of "determining the seismic resilience value of the substation corresponding to the target earthquake intensity based on the product of the total repair time and the residual function evaluation value" further includes:

[0095] Step 212: Analyze the time steps according to the multiple seismic waves to obtain multiple target earthquake intensities;

[0096] It is understandable that the intensity of seismic waves applied to the substation in a certain period of time is different. Therefore, it is necessary to determine the analysis time step and calculate the seismic resilience of the substation at each analysis time step node in order to fully determine the extent of earthquake damage to the substation.

[0097] Step 214: Based on the multiple target earthquake intensities, determine the seismic toughness values ​​of the substation corresponding to the target earthquake intensities respectively.

[0098] Step 216: Draw a seismic resilience curve of the substation based on the multiple seismic resilience values.

[0099] It can be understood that by changing the analysis time step, multiple seismic toughness values ​​are calculated, and the seismic toughness curve of the substation is retrieved based on the multiple seismic toughness values. Based on the seismic toughness curve, the seismic toughness value of any point on the curve can be easily and quickly obtained, that is, the seismic toughness assessment of the substation in a certain earthquake intensity or earthquake range can be quickly determined. In this way, there is no need to repeatedly perform simulation calculations for a certain earthquake intensity each time, and the evaluation is more flexible and saves time and effort.

[0100] The following is a detailed description of the rapid assessment of seismic resilience for the specific embodiments shown in Figures 3 to 7. Figure 3 is a flow chart of the method for determining the seismic resilience of a substation in this embodiment, Figure 4 is a general plan view of a 220kV substation, Figure 5 is a side view of AA of the 220kV equipment in Figure 4, that is, a side view of the high-voltage side equipment, and Figure 6 is a side view of BB of the 110kV equipment in Figure 4, that is, a side view of the low-voltage side equipment.

[0101] Determine the earthquake intensity: Based on the structural fortification intensity and the importance of the power system in the area, the target earthquake intensity range is determined to be 0.1g to 0.8g, and the analysis time step is 0.05g.

[0102] As shown in Figure 4, the substation is primarily divided into five levels: six incoming line bays, two 220kV busbar bays, three main transformer bays, two 110kV busbar bays, and 12 outgoing line bays. Electric energy enters the substation system through the incoming line bays, is transmitted to the substation's main transformer bays via the 220kV busbar bays, and is then delivered to power users via the outgoing line bays via the 110kV busbar bays. The substation has six types of equipment: PF, DS, CT, CB, TF, and PI, representing gantry, disconnector, current transformer, circuit breaker, transformer, and post insulator, respectively. By clarifying the earthquake intensity, substation equipment type, number of devices, and the connection mode between each device, the preset parameters of step S202 are set.

[0103] Calculate the seismic vulnerability of each device: Calculate the seismic vulnerability curve of each device based on the target earthquake intensity range, analysis time step, and preset parameters.

[0104] Establish the equipment damage probability matrix V: Establish a directed network graph model and equipment damage probability matrix for the 220kV substation system, as shown in Figures 5 to 7. Figure 7 is a directed network graph of a 220kV substation, including the incoming line bay, bus bay, main transformer bay, bus bay, and outgoing line bay. Each bus bay consists of 10 support insulators PI corresponding to the voltage level. The median and logarithmic standard deviation parameters of the vulnerability curves of various types of equipment are shown in Table 1. Based on the vulnerability curves of various types of equipment, the failure probability of the equipment is determined to form the equipment damage probability matrix of the substation. The equipment corresponding to each element in the equipment damage probability matrix is ​​shown in Table 2:

[0105] Table 1

[0106] Table 2

[0107] Generate a 0-1 random number matrix R and compare R > V to obtain the device state matrix C. The device state matrix C is calculated in each Monte Carlo simulation as follows: C = R > V. Specifically, in each Monte Carlo simulation, a random number matrix R with the same dimensions as the device damage probability matrix V is generated. The elements of random number matrix R are random numbers uniformly distributed between 0 and 1. By comparing the random number matrix with the device damage probability matrix, the operating status of each device is determined. Based on the operating status of each device, the device state matrix C is established.

[0108] Determine the functional matrix and residual function index F at each level: Based on the connection mode of each device in the substation, establish a vector analysis model of the system to obtain the functional matrix of the current level of the equipment. Then calculate the residual function evaluation index F of the substation system, as follows: R = F × T r .

[0109] Nout refers to the total number of outgoing lines in the system before the earthquake, and nout refers to the number of outgoing lines that can operate normally after the earthquake.

[0110] The seismic toughness index R of each Monte Carlo simulation is calculated as follows:

[0111] The total recovery time is calculated and the resilience index R is calculated. Specifically, based on the device function matrix of the current level, the repair time of each device is determined. The repair time of each device at the current level is calculated to obtain the total recovery time (i.e., the total repair time of each level), and the resilience index R is calculated.

[0112] Obtain an expectation of the toughness index R. Specifically, repeat the above steps to obtain multiple seismic toughness indexes R, and obtain an expected value of R based on the multiple seismic toughness indexes R. The expected value is the seismic toughness value of the equipment.

[0113] Traverse the target earthquake intensity range: Determine the analysis time step, traverse the target earthquake intensity range, and then determine the target earthquake intensity. Repeat the above steps to obtain the equipment function matrix at each level, and then determine the repair time and residual function index F of each device, and calculate the seismic toughness value of each device.

[0114] Multiple seismic resilience values ​​at different earthquake intensities: Multiple seismic resilience values ​​at different earthquake intensities are obtained through traversal and calculation. Based on these values, a seismic resilience curve for the 220kV substation system is plotted, as shown in Figure 8. Figure 8 shows the post-earthquake residual function and seismic resilience index curve for the 220kV substation. It can be understood that based on this seismic resilience curve, the seismic resilience of the substation under any earthquake intensity can be determined, enabling seismic resilience analysis.

[0115] It should be understood that, although the various steps in the flowcharts involved in the various embodiments described above are displayed in sequence according to the instructions of the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flowcharts involved in the various embodiments described above can include multiple steps or multiple stages, and these steps or stages are not necessarily executed and completed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0116] Secondly, based on the same inventive concept, embodiments of the present application further provide a device for determining substation seismic resilience, for implementing the aforementioned method for determining substation seismic resilience. The solution provided by this device is similar to the solution described in the aforementioned method. Therefore, the specific limitations of one or more embodiments of the device for determining substation seismic resilience provided below can be found in the aforementioned method for determining substation seismic resilience, and will not be further elaborated here.

[0117] As shown in FIG9 , this embodiment provides a device for determining the seismic toughness of a substation, the device comprising:

[0118] Parameter determination module 100, for obtaining target earthquake intensity and preset parameters of the substation;

[0119] The equipment status determination module 200 establishes a directed network graph model and an equipment damage probability matrix of the substation according to the target earthquake intensity and the preset parameters;

[0120] A time statistics module 300 is configured to determine the total repair time of the substation after an earthquake of a target earthquake intensity based on the directed network graph model and the equipment damage probability matrix;

[0121] A vector analysis module 400 is configured to establish a vector analysis model of the substation according to preset parameters, and determine a residual function evaluation value of the substation according to the vector analysis model;

[0122] The seismic resilience determination module 500 is used to determine the seismic resilience value of the substation corresponding to the target earthquake intensity based on the product of the total repair time and the residual function evaluation value.

[0123] In one embodiment, the seismic resilience determination module 500 is further configured to draw a seismic resilience curve of the substation based on the plurality of seismic resilience values.

[0124] In one embodiment, the equipment status determination module 200 is used to determine the equipment status matrix of the substation based on the directed network graph model and the equipment damage probability matrix, and is also used to perform multiple simulations according to the Monte Carlo method to determine the working status of multiple devices, and establish the equipment status matrix of the substation based on the working status of multiple devices.

[0125] In one embodiment, the equipment status determination module 200 establishes the directed network graph model based on the substation equipment type, the number of equipment, and the connection mode, and determines the failure probability of each of the equipment based on the seismic vulnerability curve of the substation equipment and the target earthquake intensity, and establishes the equipment damage probability matrix based on the failure probabilities of all the equipment.

[0126] In one embodiment, the time statistics module 300 is used to determine the total repair time of the substation after the earthquake based on the equipment status matrix.

[0127] In one embodiment, the vector analysis module 400 is used to establish the vector analysis model according to the connection mode between the devices, and obtain the device function matrix based on the vector analysis model; according to the device function matrix, determine the number of operable outgoing lines in the substation and the total number of outgoing lines in the substation before the earthquake; and obtain the residual function evaluation value of the substation based on the quotient of the number of operable outgoing lines in the substation after the earthquake and the total number of outgoing lines in the substation before the earthquake.

[0128] In one embodiment, the seismic resilience determination module 500 is used to repeatedly obtain multiple seismic resilience indicators of the substation based on the same target earthquake intensity; based on the multiple seismic resilience indicators, determine the expected value of the seismic resilience indicator, and the expected value is the seismic resilience value.

[0129] Each module in the aforementioned device for determining substation seismic resilience may be implemented in whole or in part via software, hardware, or a combination thereof. Each module may be embedded in or independent of a processor within a computer device in hardware form, or may be stored in a computer device memory in software form, allowing the processor to call and execute the corresponding operations of each module.

[0130] In a third aspect, this embodiment provides a computer device including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, it implements the steps in the above-mentioned method for determining the seismic resilience of a substation.

[0131] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as shown in FIG10 . The computer device includes a processor, memory, a communication interface, a display screen, and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal via wired or wireless communication. The wireless communication may be achieved via Wi-Fi, a mobile cellular network, NFC (near field communication), or other technologies. When executed by the processor, the computer program implements a method for determining the seismic resilience of a substation. The display screen of the computer device may be a liquid crystal display or an electronic ink display screen. The input device of the computer device may be a touch layer covering the display screen, or may be buttons, a trackball, or a touchpad provided on the computer device housing, or may be an external keyboard, touchpad, or mouse.

[0132] Those skilled in the art will understand that the structure shown in FIG10 is merely a block diagram of a portion of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.

[0133] In a fourth aspect, this embodiment provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-mentioned method for determining the seismic resilience of a substation.

[0134] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, database or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory may include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processor involved in the various embodiments provided herein may be, but are not limited to, a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic unit, a data processing logic unit based on quantum computing, and the like.

[0135] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0136] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A method for determining the seismic toughness of a substation, the method comprising: Obtain target earthquake intensity and preset parameters of substation; According to the target earthquake intensity and the preset parameters, a directed network graph model and an equipment damage probability matrix of the substation are established; Determine the total repair time of the substation after an earthquake based on the target earthquake intensity based on the directed network graph model and the equipment damage probability matrix; Establishing a vector analysis model of the substation according to preset parameters, and determining a residual function evaluation value of the substation according to the vector analysis model; and, Based on the product of the total repair time and the residual function evaluation value, the seismic toughness value of the substation corresponding to the target earthquake intensity is determined.

2. According to the method of claim 1, the determining, based on the directed network graph model and the equipment damage probability matrix, the total repair time of the substation after an earthquake based on the target earthquake intensity comprises: Determining an equipment state matrix of the substation based on the directed network graph model and the equipment damage probability matrix; and, Based on the equipment status matrix, a total repair time of the substation after the earthquake is determined.

3. The method according to claim 2, wherein determining the equipment state matrix of the substation based on the directed network graph model and the equipment damage probability matrix comprises: Based on the directed network graph model and the equipment damage probability matrix, the working state of the equipment is determined according to Monte Carlo simulation; Determine the working status of multiple devices by multiple simulations based on the Monte Carlo method; and, Based on the working status of multiple devices, the device status matrix of the substation is established.

4. The method according to claim 1, after determining the seismic resilience value of the substation corresponding to the target earthquake intensity based on the product of the total repair time and the residual function evaluation value, further comprises: Analyze time steps based on multiple seismic waves to obtain multiple target earthquake intensities; Based on a plurality of the target earthquake intensities, respectively determining a plurality of seismic resilience values ​​of the substation corresponding to the target earthquake intensities; and, According to the plurality of seismic toughness values, a seismic toughness curve of the substation is drawn.

5. The method according to claim 1, establishing the directed network graph model of the substation and the equipment damage probability matrix according to the target earthquake intensity and the preset parameters comprises: The preset parameters include: equipment type, number of equipment, connection mode between equipment and seismic vulnerability curve of equipment; Establishing the directed network graph model according to the substation equipment type, equipment number and connection mode; determining the failure probability of each of the devices according to the seismic fragility curve of the devices and the target earthquake intensity; and, Based on the failure probabilities of all the devices, the device damage probability matrix is ​​established.

6. The method according to claim 1, wherein establishing a vector analysis model of the substation according to preset parameters and determining a residual function evaluation value of the substation according to the vector analysis model comprises: The preset parameters include device type, number of devices, and connection mode between devices; Establishing the vectorized analysis model according to the connection mode between the devices; Obtaining a device function matrix based on the vectorized analysis model; Determine, according to the equipment function matrix, the number of outgoing lines that can be operated in the substation after the earthquake and the total number of outgoing lines in the substation before the earthquake; and, The residual function evaluation value of the substation is obtained according to the quotient of the number of operable outgoing lines in the substation after the earthquake and the total number of outgoing lines in the substation before the earthquake.

7. According to the method of claim 1, determining the seismic resilience value of the substation based on the product of the total repair time and the residual function evaluation value further comprises: Based on the same target earthquake intensity, repeatedly obtaining multiple seismic resilience indicators of the substation; and, Based on the plurality of seismic toughness indicators, an expected value of the seismic toughness indicator is determined, wherein the expected value is the seismic toughness indicator. value.

8. A device for determining the seismic toughness of a substation, the device comprising: A parameter determination module, used to obtain the target earthquake intensity and the preset parameters of the substation; An equipment status determination module, used to establish a directed network graph model and an equipment damage probability matrix of the substation according to the target earthquake intensity and the preset parameters; A time statistics module, used to determine the total repair time of the substation after an earthquake based on a target earthquake intensity based on the directed network graph model and the equipment damage probability matrix; A vector analysis module, used to establish a vector analysis model of the substation according to preset parameters, and determine a residual function evaluation value of the substation according to the vector analysis model; and, The seismic resilience determination module is used to determine the seismic resilience value of the substation corresponding to the target earthquake intensity based on the product of the total repair time and the remaining function evaluation value.

9. According to the device of claim 8, the seismic resilience determination module is also used to draw a seismic resilience curve of the substation based on a plurality of the seismic resilience values.

10. According to the device according to claim 8, the equipment status determination module is used to determine the equipment status matrix of the substation based on the directed network graph model and the equipment damage probability matrix, and is also used to determine the working status of multiple devices through multiple simulations according to the Monte Carlo method, and establish the equipment status matrix of the substation based on the working status of multiple devices.

11. According to the device according to claim 8, the equipment status determination module is used to establish the directed network graph model according to the substation equipment type, the number of equipment, and the connection mode, and determine the failure probability of each of the equipment according to the earthquake vulnerability curve of the substation equipment and the target earthquake intensity, and establish the equipment damage probability matrix based on the failure probability of all the equipment.

12. The device according to claim 8, wherein the time statistics module is used to determine the total repair time of the substation after the earthquake based on the equipment status matrix.

13. According to the device of claim 8, the vector analysis module is used to establish the vector analysis model according to the connection mode between the devices, and obtain the device function matrix based on the vector analysis model; determine the number of operable outgoing lines in the substation and the total number of outgoing lines in the substation before the earthquake according to the device function matrix; and obtain the residual function evaluation value of the substation according to the quotient of the number of operable outgoing lines in the substation after the earthquake and the total number of outgoing lines in the substation before the earthquake.

14. According to the device of claim 8, the seismic resilience determination module is used to repeatedly obtain multiple seismic resilience indicators of the substation based on the same target earthquake intensity; and, based on the multiple seismic resilience indicators, determine the expected value of the seismic resilience indicator, and the expected value is the seismic resilience value.

15. A computer device comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the method according to any one of claims 1 to 7 when executing the computer program.

16. A computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the method according to any one of claims 1 to 7.

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