Lightning arrester evaluation method, device and equipment and readable storage medium

Abstract

The invention discloses a lightning arrester evaluation method, apparatus and device, and a readable storage medium. The method comprises the steps of obtaining performance information and deployment information of a target lightning arrester; simulating the target lightning arrester based on the performance information and the deployment information to obtain a simulation model; performing lightning stroke test on the simulation model by adopting a Monte Carlo algorithm; and calculating the damage rate of the target lightning arrester in the simulation model after the lightning stroke test. It can be seen that the lightning protection performance of the target lightning arrester can be evaluated in combination with the Monte Carlo algorithm and the simulation process, the influence on normal power utilization in the performance evaluation process is avoided, and simulation errors are reduced. Meanwhile, in combination with the Monte Carlo algorithm, the random sampling characteristic of the lightning stroke test can be further improved, and the reliability of the evaluated damage rate is further improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of evaluation, in particular to a method, device and equipment for evaluating a surge arrester and a readable storage medium. BACKGROUND

[0002] In a power distribution network, the core function of a surge arrester (SA) is to protect power distribution equipment from lightning overvoltage damage. Therefore, the safety and reliability of the operation of the power distribution line are affected by the performance level of the surge arrester.

[0003] Evaluating the performance of a surge arrester helps to determine whether it can stably play a protective role in a lightning overvoltage impact scenario, effectively avoid damage to power distribution equipment and power supply interruption accidents caused by the failure of the surge arrester, and reduce the interference of faults on the safe and stable operation of the power system. SUMMARY

[0004] Therefore, the present application provides a method, device and equipment for evaluating the performance of a surge arrester and a readable storage medium.

[0005] In order to achieve the above-mentioned purpose, the present application provides the following scheme:

[0006] A method for evaluating a surge arrester, comprising:

[0007] obtaining performance information and deployment information of a target surge arrester;

[0008] simulating the target surge arrester based on the performance information and the deployment information to obtain a simulation model;

[0009] conducting a lightning test on the simulation model by using a Monte Carlo algorithm;

[0010] calculating a damage rate of the target surge arrester after the lightning test.

[0011] Optionally, the obtaining of the performance information and the deployment information of the target surge arrester comprises:

[0012] obtaining energy tolerance performance parameters, electrical performance parameters and deployment topology structure information of the target surge arrester.

[0013] Optionally, the conducting of the lightning test on the simulation model by using the Monte Carlo algorithm comprises:

[0014] randomly generating a plurality of lightning events in the simulation model by using the Monte Carlo algorithm, and simulating each lightning event respectively.

[0015] Optionally, the Monte Carlo algorithm is adopted to randomly generate a plurality of lightning strike events in the simulation model, and each lightning strike event is simulated, including:

[0016] The Monte Carlo algorithm is adopted to randomly generate a plurality of lightning strike positions in the simulation model.

[0017] For each lightning strike position, a plurality of corresponding lightning current amplitudes are generated to simulate a multi-pulse lightning strike event.

[0018] Optionally, the damage rate of the target lightning arrester after lightning strike test in the simulation model is calculated, including:

[0019] The energy absorption value of the target lightning arrester after each lightning strike event is calculated.

[0020] Based on the energy absorption values, the damage rate of the target lightning arrester after lightning strike test is calculated.

[0021] Optionally, the damage rate of the target lightning arrester after lightning strike test is calculated based on the energy absorption values, including:

[0022] The energy tolerance threshold of the target lightning arrester is determined;

[0023] Based on the energy tolerance threshold and the energy absorption values, the damage rate is calculated.

[0024] Optionally, the damage rate is calculated based on the energy tolerance threshold and the energy absorption values, including:

[0025] The lightning strike event occurrence probability of the target lightning arrester damaged due to lightning energy exceeding its energy tolerance threshold is calculated;

[0026] The lightning strike occurrence probability of each lightning strike position is calculated;

[0027] Based on the lightning strike occurrence probability of each lightning strike position and the lightning strike event occurrence probability, the damage rate is calculated.

[0028] A lightning arrester evaluation device, comprising:

[0029] An acquisition module is configured to acquire performance information and deployment information of a target lightning arrester;

[0030] A simulation module is configured to simulate the target lightning arrester based on the performance information and the deployment information to obtain a simulation model;

[0031] A test module is configured to perform lightning strike test on the simulation model by using a Monte Carlo algorithm;

[0032] A calculation module is configured to calculate a damage rate of the target lightning arrester after lightning strike test in the simulation model.

[0033] A lightning arrester evaluation device, comprising a memory and a processor;

[0034] The memory is configured to store a program.

[0035] The processor is configured to execute the program to implement each step of the lightning arrester evaluation method.

[0036] A readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements each step of the lightning arrester evaluation method.

[0037] As can be seen from the above technical solution, the lightning arrester evaluation method provided by the present application can obtain performance information and deployment information of a target lightning arrester; a simulation model is obtained by simulating the target lightning arrester based on the performance information and the deployment information; based on this, the performance information of the target lightning arrester can provide core electrical parameters of the target lightning arrester, representing its performance; the deployment information can represent the deployment position, installation node, and other spatial positioning information of the target lightning arrester in the corresponding network, so that the simulation model simulated based on the performance information and the deployment information fits the actual operating environment and operating mode of the target lightning arrester, eliminating evaluation errors caused by scene distortion; then, the present application can use the Monte Carlo algorithm to perform a lightning strike test on the simulation model; based on this, the Monte Carlo algorithm has a random sampling characteristic, so that the Monte Carlo algorithm can generate multiple sets of differentiated lightning strikes in the process of lightning strike testing, covering multiple lightning strike scenarios and avoiding the test limitations caused by a single lightning strike; then, the present application can calculate the damage rate of the target lightning arrester in the simulation model after lightning strike testing; based on this, the present application can evaluate the lightning protection performance of the corresponding target lightning arrester by calculating the damage rate of the simulation model after multiple lightning strikes, so as to evaluate whether the target lightning arrester can stably play a protection role in subsequent lightning overvoltage impact scenarios and reduce the interference of lightning strikes on the safe and stable operation of the power system. It can be seen that the present application can evaluate the lightning protection performance of the target lightning arrester in combination with the Monte Carlo algorithm and the simulation process, avoid affecting normal power consumption during performance evaluation, and reduce simulation errors. At the same time, the random sampling characteristic of the lightning strike test can be further improved in combination with the Monte Carlo algorithm, and the reliability of the damage rate evaluation can be further improved. BRIEF DESCRIPTION OF DRAWINGS

[0038] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed in the embodiments or prior art description will be briefly introduced below. Obviously, the drawings in the following description are only embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0039] Figure 1 A flow chart of a method for evaluating a surge arrester according to an embodiment of the present application is disclosed.

[0040] Figure 2 A structure block diagram of a device for evaluating a surge arrester according to an embodiment of the present application is disclosed.

[0041] Figure 3 A hardware structure block diagram of a device for evaluating a surge arrester according to an embodiment of the present application is disclosed. DETAILED DESCRIPTION

[0042] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of protection of the present application.

[0043] The method for evaluating a surge arrester according to an embodiment of the present application can be applied in various power distribution network management systems or surge arrester detection systems, and can also be applied in various computer terminals or intelligent terminals. The execution subject can be a processor of a computer terminal or an intelligent terminal or a server.

[0044] Next, the method for evaluating a surge arrester according to an embodiment of the present application will be described in detail. Figure 1 The method for evaluating a surge arrester according to an embodiment of the present application will be described in detail, including the following steps.

[0045] Step S1, obtaining performance information and deployment information of a target surge arrester.

[0046] Specifically, the target surge arrester can be a surge arrester in a power distribution network that needs to be evaluated in performance, or a surge arrester planned to be deployed at a node of the power distribution network.

[0047] The performance information of the target surge arrester can be a core electrical parameter representing the performance of the target surge arrester.

[0048] The deployment information of the target surge arrester can include a physical deployment position of the target surge arrester, an electrical installation node, and topology information of a power distribution network where the target surge arrester is deployed.

[0049] Step S2, simulating the target surge arrester based on the performance information and the deployment information to obtain a simulation model.

[0050] Specifically, the simulation of the target surge arrester based on the performance information and the deployment information to obtain a simulation model can be implemented in various ways.

[0051] For example, a plurality of different types of lightning arrester models can be pre-constructed;

[0052] determining a target type of the target lightning arrester, and selecting a lightning arrester model matching the target type from the plurality of lightning arrester models;

[0053] performing parameter updating on the selected lightning arrester model based on the performance information, to obtain a target lightning arrester model;

[0054] constructing a digital topology simulation structure of the power distribution network based on topology information in the deployment information;

[0055] accessing the target lightning arrester model to a corresponding node of the digital topology simulation structure according to the physical deployment position and the electrical installation node in the deployment information, to form a simulation model.

[0056] For example, the performance parameters can be converted into digital model electrical characteristic parameters of the target lightning arrester, and a single model reflecting the real lightning strike response of the target lightning arrester can be constructed;

[0057] constructing a digital topology simulation structure of the power distribution network based on topology information in the deployment information;

[0058] accessing the single model to a corresponding node of the digital topology simulation structure according to the physical deployment position and the electrical installation node in the deployment information, to form a simulation model.

[0059] Step S3, using a Monte Carlo algorithm to perform lightning strike test on the simulation model.

[0060] Specifically, historical lightning strike information of the power distribution network corresponding to the target lightning arrester can be obtained;

[0061] Analyzing the historical lightning strike information can extract the actual probability characteristics of lightning strikes on the power distribution network;

[0062] Based on the actual probability characteristics of lightning strikes on the power distribution network, a large number of differentiated lightning strike events are randomly generated in the simulation model;

[0063] The complete process of each lightning strike event from occurrence to energy transmission to the target lightning arrester is simulated in the simulation model, and the response information of the lightning arrester under each scenario is recorded synchronously, so as to realize the systematic lightning strike test on the simulation model.

[0064] The actual probability characteristics of lightning strikes on the power distribution network can include lightning strike related information such as spatial distribution law of lightning strike position and probability density distribution of lightning current amplitude.

[0065] Step S4, calculating the damage rate of the target lightning arrester in the simulation model after lightning strike test.

[0066] Specifically, the response information of each lightning strike event can be summarized;

[0067] calculating an energy absorption value of each lightning stroke event based on the response information of each lightning stroke event;

[0068] statistically processing the energy absorption values, and evaluating a damage rate of the target lightning arrester in the simulation model after lightning stroke test in reference to the performance parameters.

[0069] It can be seen from the technical solution that the lightning arrester evaluation method provided by the application can obtain performance information and deployment information of the target lightning arrester; the target lightning arrester is simulated based on the performance information and the deployment information to obtain a simulation model; based on this, the performance information of the target lightning arrester can provide core electrical parameters of the target lightning arrester to represent the performance of the target lightning arrester; the deployment information can represent the deployment position, installation node and other spatial positioning information of the target lightning arrester in the corresponding network to make the simulation model simulated based on the performance information and the deployment information fit the actual operation environment and operation mode of the target lightning arrester, and exclude evaluation errors caused by scene distortion; then, the Monte Carlo algorithm can be used to perform lightning stroke test on the simulation model; based on this, the Monte Carlo algorithm has random sampling characteristics, so that the Monte Carlo algorithm can generate multiple groups of different lightning strokes in the process of lightning stroke test to cover multiple lightning stroke scenes and avoid the test limitations caused by a single lightning stroke; then, the application can calculate the damage rate of the target lightning arrester in the simulation model after lightning stroke test; based on this, the application can evaluate the lightning protection performance of the corresponding target lightning arrester by calculating the damage rate of the simulation model after multiple lightning strokes to evaluate whether the corresponding target lightning arrester can stably play a protection role in subsequent lightning overvoltage impact scenes and reduce the interference of lightning on the safe and stable operation of the power system. It can be seen that the application can evaluate the lightning protection performance of the target lightning arrester in combination with the Monte Carlo algorithm and the simulation process to avoid affecting normal power consumption in the performance evaluation process and reduce simulation errors. At the same time, the random sampling characteristics of the lightning stroke test can be further improved in combination with the Monte Carlo algorithm to further improve the reliability of the damage rate evaluation.

[0070] In some embodiments of the application, the process of step S1, obtaining the performance information and deployment information of the target lightning arrester, is described in detail as follows:

[0071] S10, obtaining the energy tolerance performance parameters, electrical performance parameters and deployment topology structure information of the target lightning arrester.

[0072] Specifically, the energy tolerance performance parameters can include the rated energy tolerance value, short-time energy tolerance value and energy recovery time of the target lightning arrester, which can be used to define the limit of the lightning stroke energy impact resistance of the target lightning arrester.

[0073] The electrical performance parameters can include rated voltage, residual voltage, operating voltage, and volt-ampere characteristic curve, and can be used to represent the electrical response behavior of the target lightning arrester after being struck by lightning.

[0074] The deployment topology information can include the line connection mode, installation node, and deployment location device distribution of the power distribution network where the target lightning arrester is deployed, and the installation node and physical deployment location of the target lightning arrester itself, to provide environmental basis for subsequent simulation scene construction.

[0075] As can be seen from the above technical solution, the embodiment provides an optional way of obtaining performance information and deployment information of a target lightning arrester. Through the above way, multi-dimensional information such as energy tolerance performance parameters, electrical performance parameters, and deployment topology information can be comprehensively used for simulation model construction, further improving the adaptability of the simulation model to the actual use scenario and improving the accuracy of the damage rate.

[0076] In some embodiments of the present application, the process of step S3, lightning test on the simulation model using the Monte Carlo algorithm, is described in detail as follows:

[0077] S30, a plurality of lightning events are randomly generated in the simulation model using the Monte Carlo algorithm, and each lightning event is simulated.

[0078] Specifically, the Monte Carlo algorithm can be used to randomly generate lightning events containing lightning point coordinates, lightning current amplitude, lightning current waveform, and lightning time based on the actual probability characteristics of lightning strikes on the power distribution network.

[0079] Each lightning event is simulated in the simulation model to obtain the response information of the target lightning arrester after each lightning event occurs.

[0080] As can be seen from the above technical solution, the embodiment provides an optional way of using the Monte Carlo algorithm to perform lightning test on the simulation model. Through the above way, lightning test can be performed by constructing a plurality of differentiated lightning events, further improving the reliability of the lightning test of the present application.

[0081] In some embodiments of the present application, the process of step S30, randomly generating a plurality of lightning events in the simulation model using the Monte Carlo algorithm, is described in detail as follows:

[0082] S300, a plurality of lightning positions are randomly generated in the simulation model using the Monte Carlo algorithm.

[0083] Specifically, in combination with the spatial distribution characteristics of lightning in actual operation of the power distribution network, the sampling range of the lightning position in the simulation model can be determined.

[0084] By the random sampling mechanism of the Monte Carlo algorithm, a plurality of lightning strike positions with statistical representativeness are randomly generated in the sampling range, and each generated lightning strike position corresponds to a specific node or line section of the power distribution network topology in the simulation model, providing a scenario basis for simulating the influence of lightning strikes at different positions on the target lightning arrester.

[0085] Among them, the spatial distribution characteristics can be used to characterize the probability of lightning-prone areas such as line sections and tower vicinities, which can be obtained based on historical lightning information.

[0086] S301, for each lightning strike position, a plurality of corresponding lightning current amplitudes are generated to simulate multi-pulse lightning strike events.

[0087] Specifically, based on the multi-pulse lightning characteristics, a plurality of differentiated lightning current amplitudes such as the first pulse amplitude and the subsequent decay pulse amplitude are generated for each lightning strike position, and the plurality of lightning current amplitudes under the same lightning strike position are sequentially applied to the simulation model according to the time sequence logic of multi-pulse lightning, so as to simulate multi-pulse lightning events close to the actual scene.

[0088] Among them, the multi-pulse lightning characteristics can include pulse amplitude decay law and pulse interval time range, which can be obtained based on historical lightning information.

[0089] The multi-pulse lightning characteristics can satisfy the IEEE standard statistical distribution, such as the lognormal distribution.

[0090] The lightning strike positions of different lightning strike events can be the same or different.

[0091] The total number of lightning strike events can be 10,000 times.

[0092] The mean of the lightning current amplitude can be 30kA, and the standard deviation can be 10kA.

[0093] As can be seen from the above technical solution, the embodiment provides a method of generating a plurality of lightning strike events in the simulation model by using the Monte Carlo algorithm, and simulating the optional way of each lightning strike event. Through the above method, the multi-pulse situation in the actual lightning process can be simulated, and the accuracy of the lightning test is improved.

[0094] In some embodiments of the present application, the process of step S4, calculating the damage rate of the target lightning arrester after lightning test in the simulation model, is described in detail, and the steps are as follows:

[0095] S40, calculating the energy absorption value of the target lightning arrester after each lightning strike event.

[0096] Specifically, each energy absorption value refers to the energy consumed by discharging the lightning current in the corresponding lightning process, which is related to the lightning current amplitude, waveform and distance.

[0097] The response data of each lightning stroke event can be substituted into the energy value calculation function to calculate the energy absorption value of the target lightning arrester after each lightning stroke event.

[0098]

[0099] In the formula, is the energy absorption value of the lightning stroke event i; is the performance coefficient of the target lightning arrester; is the lightning current composed of the lightning current amplitude of the lightning stroke event i; and a is the attenuation coefficient; is the distance between the lightning stroke point coordinates of the lightning stroke event i and the target lightning arrester.

[0100] S41, based on each energy absorption value, calculating the damage rate of the target lightning arrester after the lightning stroke test.

[0101] Specifically, each energy absorption value can be analyzed, and the damage rate of the target lightning arrester after the lightning stroke test can be calculated according to the analysis result.

[0102] From the above technical solution, it can be seen that the embodiment provides an optional way to calculate the damage rate of the target lightning arrester after the lightning stroke test in the simulation model. Through the above way, the damage rate can be calculated from the energy absorption after each lightning stroke event, not only considering the influence of single lightning stroke, but also comprehensively considering the cumulative effect after multiple lightning strokes, so as to more comprehensively reflect the lightning stroke resistance of the lightning arrester in actual operation; and the accuracy and practicability of the damage rate evaluation are further improved.

[0103] In some embodiments of the present application, the process of step S41, calculating the damage rate of the target lightning arrester after the lightning stroke test based on each energy absorption value, is described in detail, and the steps are as follows:

[0104] S410, determining the energy tolerance threshold of the target lightning arrester.

[0105] Specifically, the energy tolerance threshold of the target lightning arrester can be determined according to the performance information of the target lightning arrester;

[0106] The energy tolerance threshold can also be obtained through the nominal parameters such as the tolerance energy under the 8 / 20 μs waveform provided by the lightning arrester manufacturer or experimental test.

[0107] S411, based on the energy tolerance threshold and each energy absorption value, the damage rate is calculated.

[0108] Specifically, each energy absorption value can be analyzed to determine that the energy absorption distribution of the target lightning arrester conforms to the logarithmic normal distribution, and the logarithmic normal distribution is independent of the distance.

[0109] Thus, a probability density function representing the distribution characteristics of the energy absorption values can be constructed according to the energy absorption values.

[0110] The probability density function can be as follows:

[0111]

[0112] In the formula, is the energy absorption value; is the probability density value; is the standard deviation; is the average value of the energy absorption values.

[0113] The probability density function can be used to analyze the possibility of lightning strike events that cause the target lightning arrester to fail due to exceeding the energy tolerance threshold of the target lightning arrester, and the possibility is taken as the damage rate.

[0114] As can be seen from the above technical solution, the embodiment provides an optional way of calculating the damage rate of the target lightning arrester after lightning strike test based on the energy absorption values. Through the above method, the distribution characteristics of energy absorption and the energy tolerance threshold of the lightning arrester can be further considered, and the damage of the lightning arrester after multiple lightning strikes can be more scientifically evaluated. This method not only considers the energy impact of a single lightning strike, but also analyzes the statistical law of lightning arrester energy absorption under multiple lightning strikes through the probability density function, so as to more accurately predict the performance degradation and failure risk of the lightning arrester in long-term operation.

[0115] In some embodiments of the present application, the process of calculating the damage rate based on the energy tolerance threshold and the energy absorption values in step S411 is described in detail as follows:

[0116] S4110, calculate the probability of lightning strike events that cause the target lightning arrester to be damaged due to lightning energy exceeding its energy tolerance threshold.

[0117] Specifically, the probability of lightning strike events that cause the target lightning arrester to be damaged due to lightning energy exceeding its energy tolerance threshold can be calculated according to the above probability density function.

[0118] S4111, calculate the probability of lightning occurrence at each lightning position.

[0119] Specifically, the probability of lightning occurrence at each lightning position can be calculated as the probability of lightning occurrence according to historical lightning information.

[0120] S4112, calculate the damage rate based on the probability of lightning occurrence at each lightning position and the probability of lightning strike events.

[0121] Specifically, a product of a lightning occurrence probability of each lightning strike position and a lightning event occurrence probability can be calculated, and a sum of each product can be taken as the damage rate.

[0122] The damage rate calculation function can be used to calculate the damage rate based on the lightning occurrence probability of each lightning strike position and the lightning event occurrence probability.

[0123] The damage rate calculation function can be as follows:

[0124]

[0125] In the formula, is the damage rate; is the lightning occurrence probability of lightning event i; is the lightning event occurrence probability due to lightning energy exceeding the energy tolerance threshold; λ is a decay constant; E th is the energy tolerance threshold.

[0126] As can be seen from the above technical solution, the embodiment provides an optional way of calculating the damage rate based on the energy tolerance threshold and the energy absorption value of each lightning strike position. Through the above way, the damage of the lightning arrester under multiple lightning strikes can be more comprehensively evaluated by integrating the lightning occurrence probability of each lightning strike position and the lightning event occurrence probability. Not only the energy tolerance characteristics of the lightning arrester itself are considered, but also the spatial distribution and frequency characteristics of the actual lightning scene are combined, so that the damage rate evaluation result is closer to the actual operation.

[0127] Next, the lightning arrester evaluation device provided in the present application will be described in detail. Figure 2 The lightning arrester evaluation device provided in the present application can be compared with the lightning arrester evaluation method provided above.

[0128] Referring to Figure 2 It can be found that the lightning arrester evaluation device can include:

[0129] The acquisition module 10 is configured to acquire performance information and deployment information of a target lightning arrester.

[0130] The simulation module 20 is configured to simulate the target lightning arrester based on the performance information and the deployment information to obtain a simulation model.

[0131] The test module 30 is configured to perform lightning test on the simulation model by using a Monte Carlo algorithm.

[0132] The calculation module 40 is configured to calculate a damage rate of the target lightning arrester after lightning test in the simulation model.

[0133] Further, the acquisition module 10 can include:

[0134] a parameter acquisition unit, configured to acquire an energy withstand performance parameter, an electrical performance parameter, and deployment topology information of the target lightning arrester.

[0135] Further, the test module 30 can include:

[0136] a lightning stroke event simulation unit, configured to randomly generate a plurality of lightning stroke events in the simulation model by using a Monte Carlo algorithm, and simulate each lightning stroke event respectively.

[0137] Further, the lightning stroke event simulation unit can include:

[0138] a first lightning stroke event simulation sub-unit, configured to randomly generate a plurality of lightning stroke positions in the simulation model by using a Monte Carlo algorithm;

[0139] a second lightning stroke event simulation sub-unit, configured to generate a plurality of corresponding lightning current amplitudes for each lightning stroke position, and simulate a multi-pulse lightning stroke event.

[0140] Further, the calculation module 40 can include:

[0141] an energy absorption value calculation unit, configured to calculate an energy absorption value of the target lightning arrester after each lightning stroke event;

[0142] a damage rate calculation unit, configured to calculate a damage rate of the target lightning arrester after the lightning stroke test based on the respective energy absorption values.

[0143] Further, the damage rate calculation unit can include:

[0144] an energy withstand threshold value determination sub-unit, configured to determine an energy withstand threshold value of the target lightning arrester;

[0145] an energy withstand threshold value utilization sub-unit, configured to calculate the damage rate based on the energy withstand threshold value and the respective energy absorption values.

[0146] Further, the energy withstand threshold value utilization sub-unit can include:

[0147] a first energy withstand threshold value utilization component, configured to calculate a lightning stroke event occurrence probability of the target lightning arrester being damaged due to lightning stroke energy exceeding the energy withstand threshold value thereof;

[0148] a second energy withstand threshold value utilization component, configured to calculate a lightning stroke occurrence probability of each lightning stroke position;

[0149] a third energy withstand threshold value utilization component, configured to calculate the damage rate based on the lightning stroke occurrence probability of each lightning stroke position and the lightning stroke event occurrence probability.

[0150] The lightning arrester evaluation device provided in the embodiments of the present application can be applied to lightning arrester evaluation equipment such as a PC terminal, a cloud platform, a server, a server cluster and the like. Optionally, Figure 3 A hardware structure block diagram of the lightning arrester evaluation device is shown, referring to Figure 3 The hardware structure of the lightning arrester evaluation device can include at least one processor 1, at least one communication interface 2, at least one memory 3 and at least one communication bus 4.

[0151] In the embodiments of the present application, the number of the processor 1, the communication interface 2, the memory 3 and the communication bus 4 is at least one, and the processor 1, the communication interface 2 and the memory 3 complete the communication with each other through the communication bus 4.

[0152] The processor 1 can be a central processing unit CPU, or a specific integrated circuit ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement the embodiments of the present application, etc.

[0153] The memory 3 can include a high-speed RAM memory, and can also include a non-volatile memory such as at least one disk memory.

[0154] The memory stores a program, and the processor can call the program stored in the memory, and the program is used for:

[0155] obtaining performance information and deployment information of a target lightning arrester;

[0156] performing simulation on the target lightning arrester based on the performance information and the deployment information to obtain a simulation model;

[0157] performing lightning strike test on the simulation model by using a Monte Carlo algorithm;

[0158] calculating a damage rate of the target lightning arrester after lightning strike test in the simulation model.

[0159] Optionally, the detailed functions and extended functions of the program can refer to the description above.

[0160] The embodiments of the present application also provide a readable storage medium which can store a program suitable for processor execution, and the program is used for:

[0161] obtaining performance information and deployment information of a target lightning arrester;

[0162] performing simulation on the target lightning arrester based on the performance information and the deployment information to obtain a simulation model;

[0163] The Monte Carlo algorithm is used to test the simulation model under lightning strike.

[0164] The damage rate of the target lightning arrester in the simulation model after lightning strike test is calculated.

[0165] Optionally, the refinement function and the extension function of the program can refer to the above description.

[0166] Finally, it should be noted that in this document, the terms such as first and second are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between such entities or operations. Moreover, the terms "comprising", "including" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or apparatus including a series of elements includes not only those elements, but also other elements not explicitly listed, or inherent to such a process, method, article or apparatus. Without more limitations, the element defined by the statement "comprising a" does not exclude the presence of additional identical elements in the process, method, article or apparatus including the element.

[0167] The various embodiments in the specification are described in a progressive manner, and each embodiment focuses on the difference from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0168] The above description of the disclosed embodiments enables a person skilled in the art to implement or use the present application. Various modifications to the embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. The various embodiments of the present application can be combined with each other. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method of surge arrester evaluation, characterized by, The method comprises the following steps: obtaining performance information and deployment information of a target lightning arrester; performing simulation on the target lightning arrester based on the performance information and the deployment information to obtain a simulation model; performing lightning strike test on the simulation model by using a Monte Carlo algorithm; calculating a damage rate of the target lightning arrester after the lightning strike test.

2. The surge arrester evaluation method according to claim 1, characterized by, The step of obtaining the performance information and the deployment information of the target lightning arrester comprises the following steps: obtaining energy tolerance performance parameters, electrical performance parameters and deployment topological structure information of the target lightning arrester.

3. The surge arrester evaluation method according to claim 1, characterized by, The step of performing lightning strike test on the simulation model by using the Monte Carlo algorithm comprises the following steps: randomly generating a plurality of lightning strike events in the simulation model by using the Monte Carlo algorithm, and simulating each lightning strike event respectively.

4. The surge arrester evaluation method according to claim 3, characterized by, The step of randomly generating a plurality of lightning strike events in the simulation model by using the Monte Carlo algorithm and simulating each lightning strike event respectively comprises the following steps: randomly generating a plurality of lightning strike positions in the simulation model by using the Monte Carlo algorithm; generating a plurality of corresponding lightning current amplitudes for each lightning strike position to simulate a multi-pulse lightning strike event.

5. The surge arrester evaluation method according to claim 3, characterized by, The step of calculating the damage rate of the target lightning arrester after the lightning strike test comprises the following steps: calculating an energy absorption value of the target lightning arrester after each lightning strike event; calculating the damage rate of the target lightning arrester after the lightning strike test based on the energy absorption values.

6. The surge arrester evaluation method according to claim 5, characterized by, The step of calculating the damage rate of the target lightning arrester after the lightning strike test based on the energy absorption values comprises the following steps: determining an energy tolerance threshold of the target lightning arrester; calculating the damage rate based on the energy tolerance threshold and the energy absorption values.

7. The surge arrester evaluation method according to claim 6, characterized by, The step of calculating the damage rate based on the energy tolerance threshold and the energy absorption values comprises the following steps: calculating a lightning strike event occurrence probability of the target lightning arrester damaged due to lightning energy exceeding the energy tolerance threshold; calculating a lightning occurrence probability of each lightning strike position; calculating the damage rate based on the lightning occurrence probability of each lightning strike position and the lightning strike event occurrence probability.

8. A surge arrester evaluation device, characterized by, The method comprises the following steps: an obtaining module, configured to obtain performance information and deployment information of a target lightning arrester; a simulation module, configured to perform simulation on the target lightning arrester based on the performance information and the deployment information to obtain a simulation model; a test module, configured to perform lightning strike test on the simulation model by using a Monte Carlo algorithm; a calculation module, configured to calculate a damage rate of the target lightning arrester after the lightning strike test.

9. A surge arrester evaluation device, characterized by The method comprises a memory and a processor. The memory is configured to store a program. The processor is configured to execute the program to implement each step of the lightning arrester evaluation method according to any one of claims 1-7.

10. A readable storage medium, having stored thereon a computer program, characterized in that, The computer program is executed by the processor to implement each step of the lightning arrester evaluation method according to any one of claims 1-7.

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