Method and system for evaluating lightning stroke position probabilistic distribution through main line and branch line arrangement

Abstract

The invention discloses a method and system for evaluating lightning stroke position probabilistic distribution based on main line and branch line arrangement, and relates to the technical field of power system protection and control, and the method comprises the steps: collecting power distribution network data, and carrying out the preprocessing; traversing each point in the large graph by using DFS, and judging the number of connectionless sub-graphs; drawing a surrounding line for each non-connected sub-graph; probabilistic distribution evaluation of lightning stroke positions is carried out in a surrounding line range; designing and training a dynamic current waveform model, and simulating a current generated by a lightning event to a power distribution network system; according to the method, the probabilistic distribution of the lightning stroke positions is accurately evaluated, and the potential influence of lightning events on the power distribution network system is comprehensively considered, so that the lightning protection capability of the power distribution network is remarkably improved, the occurrence rate of lightning stroke accidents is reduced, and the stability and safety of power supply are ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of power system protection and control, and in particular to a method and system for evaluating the probabilistic distribution of lightning strike positions by arranging trunk lines and branch lines. Background Art

[0002] Lightning is a natural phenomenon that brings natural beauty to humans, but also poses a major threat to the distribution network system. The high voltage and strong current generated during lightning discharge may cause serious damage to distribution network facilities and even cause catastrophic accidents. Therefore, it is particularly important to accurately evaluate and predict the lightning strike location.

[0003] Lightning is also a major threat in the distribution network system. The distribution network system includes various trunk lines and branch lines. The trunk line is the main transmission line, and the branch line is the secondary line connecting the trunk line and specific users. These lines usually pass through various complex terrains and environments, and there may be various objects such as buildings and trees around them. These objects have a significant impact on the landing point of lightning. Especially in the distribution network, the shielding and attraction effects of buildings and trees at different heights and locations on lightning strikes make the prediction of lightning strike points more complicated. Therefore, it is particularly important to design a probabilistic distribution evaluation method for lightning strike locations that can combine the layout of trunk lines and branch lines in the distribution network system and the influence of nearby objects. Summary of the invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] Therefore, the technical problem solved by the present invention is to solve the technical problem of accurately evaluating the probabilistic distribution of lightning strike locations in the distribution network under lightning strike conditions and comprehensively evaluating the potential impact of lightning events on the distribution network system.

[0006] In order to solve the above technical problems, the present invention provides the following technical solution: a method for evaluating the probability distribution of lightning strike positions by arranging trunk lines and branch lines, which comprises the following steps:

[0007] Collect distribution network data and perform preprocessing; use DFS to traverse each point in the large graph to determine the number of unconnected subgraphs; draw encirclement lines for each unconnected subgraph; evaluate the probabilistic distribution of lightning strike locations within the encirclement lines; design and train a dynamic current waveform model to simulate the current generated by lightning events on the distribution network system.

[0008] As a preferred solution of the method for evaluating the probabilistic distribution of lightning strike locations based on the layout of trunk and branch lines described in the present invention, the distribution network data includes the geographical coordinates of the distribution network, high-resolution terrain data, line materials, historical meteorological data and regional historical lightning event records.

[0009] The preprocessing is to integrate the distribution network data into a data set and construct a large map through the tower positions in the geographical coordinates of the distribution network.

[0010] As a preferred solution of the method for evaluating the probabilistic distribution of lightning strike locations based on the layout of trunk and branch lines described in the present invention, the method of determining the number of unconnected subgraphs includes selecting an unvisited node from the large graph as a starting node, starting from the starting node, using DFS to traverse all nodes connected to the initial node, marking the connected nodes as visited, and recording the connection relationship between each node and the connected nodes during the traversal process.

[0011] Repeat the traversal process, find an unvisited node as the new starting node, and perform the next depth-first traversal until all nodes are visited and the traversal is completed.

[0012] As a preferred solution of the method for evaluating the probabilistic distribution of lightning strike locations based on the layout of trunk lines and branch lines described in the present invention, wherein: drawing the encirclement line for each unconnected subgraph includes drawing the encirclement line of each subgraph respectively according to the position of the tower in the subgraph, wherein the distance from each endpoint on the encirclement line to all trunk lines and branch lines is ≤ the set encirclement line distance.

[0013] If the enveloping lines of two separated towers have an intersection, the overlapping parts of the enveloping lines will be removed and merged into a new enveloping line.

[0014] Each endpoint of the merged enclosing line is stored in a clockwise direction to form a new closed figure.

[0015] As a preferred embodiment of the method for evaluating the probabilistic distribution of lightning strike locations based on the layout of trunk and branch lines described in the present invention, the method of determining the lightning strike point through the EGM physical model includes classifying each generated lightning event by calculating the attraction radius through the EGM model to determine whether the strike location of the lightning event is on a building or a bush on the line.

[0016] The attraction radius is expressed as,

[0017] R=1.86I 0.78 H 0.255

[0018] R a =0.84H1 0.6 I 0.74

[0019] Among them, R represents the attraction radius of the building, R a represents the attraction radius of the bush, H represents the height of the building, I represents the current intensity, and H1 represents the height of the bush.

[0020] If the distance between lightning and a building is within the building's attraction radius and is closer to the building than to the bushes, the lightning strike point is at the midpoint of the building.

[0021] If the distance between lightning and the bushes is within the attraction radius of the bushes and the distance to the bushes is closer than the distance to the building, the lightning strike point is at the midpoint of the bushes.

[0022] If the distance between lightning and a building is greater than the attraction radius of the building and the distance between lightning and a bush is greater than the attraction radius of the bush, the lightning strike point is at a vertical point on the ground.

[0023] If the lightning strikes a building or a bush, it is a direct lightning strike.

[0024] As a preferred solution of the method for evaluating the probabilistic distribution of lightning strike locations based on the layout of trunk and branch lines described in the present invention, the current generated by the simulated lightning event on the distribution network system includes drawing the current waveform of the direct lightning strike through a dynamic current waveform model, and the specific method is the Cigre method or the Heidler method.

[0025] The Cigre method is expressed as,

[0026] i(t)=At+Bt n ,t≤t n

[0027]

[0028] Among them, i(t) represents the rising current value at time t, i1(t) represents the decaying current value at time t, A, B, n represent the parameters of the current rising stage, which determine the initial rising characteristics of the current waveform, t n It indicates the time when the current reaches the peak value, I1 and I2 indicate the current peak parameters in the decay stage, and t1 and t2 indicate the time constants in the decay stage.

[0029] The Heidler method is expressed as,

[0030]

[0031] Wherein, i2(t) represents the rising current value at time t, τ1 and τ2 represent time constants, η represents the normalization factor, and N represents the shape parameter.

[0032] Another object of the present invention is to provide a system for evaluating the probabilistic distribution of lightning strike locations based on the layout of trunk lines and branch lines, which can solve the problems in the prior art of being unable to accurately simulate the impact of lightning events on the distribution network and lacking effective lightning strike risk assessment by integrating a dynamic current waveform model and an EGM physical model.

[0033] To solve the above technical problems, the present invention provides the following technical solutions: a system for evaluating the probabilistic distribution of lightning strike locations for arranging trunk and branch lines, comprising a data acquisition module, a sub-graph enclosing line drawing module, a probabilistic distribution evaluation module and a dynamic current waveform model module.

[0034] The data acquisition module is responsible for collecting the geographic coordinates, high-resolution terrain data, line materials, historical meteorological data and regional historical lightning event records of the distribution network, integrating the collected data into a data set, and constructing a large map through the tower locations.

[0035] The sub-graph enclosing line drawing module draws enclosing lines according to the positions of the pole towers in the sub-graph, processes the overlapping areas of the enclosing lines, merges them into new enclosing lines, and forms a closed graph.

[0036] The probabilistic distribution evaluation module is used to determine the statistical distribution of lightning parameters, and generate random samples using the Monte Carlo method to construct an EGM physical model for determining the lightning strike point.

[0037] The dynamic current waveform model module uses the Cigre method or the Heidler method to simulate the current waveform of a direct lightning strike.

[0038] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of the method for evaluating the probability distribution of lightning strike positions by arranging trunk lines and branch lines as described above are implemented.

[0039] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the method for evaluating the probability distribution of lightning strike positions by arranging trunk lines and branch lines as described above.

[0040] Beneficial effects of the invention: The invention significantly improves the lightning protection capability of the distribution network, reduces the incidence of lightning accidents, and ensures the stability and safety of power supply by accurately evaluating the probabilistic distribution of lightning strike locations and comprehensively considering the potential impact of lightning events on the distribution network system. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0042] Figure 1 An overall flow chart of a method for evaluating the probabilistic distribution of lightning strike locations based on the layout of trunk lines and branch lines provided in the first embodiment of the present invention.

[0043] Figure 2 A schematic diagram of subgraph identification of a method for evaluating the probabilistic distribution of lightning strike locations based on the layout of trunk lines and branch lines provided in the first embodiment of the present invention.

[0044] Figure 3 A schematic diagram of the enclosing drawing of a method for evaluating the probabilistic distribution of lightning strike locations based on the layout of trunk lines and branch lines provided in the first embodiment of the present invention.

[0045] Figure 4 A short-time current diagram of a method for evaluating the probabilistic distribution of lightning strike locations based on the layout of trunk lines and branch lines provided in a first embodiment of the present invention.

[0046] Figure 5 An EGM model diagram of the method for evaluating the probabilistic distribution of lightning strike locations based on the layout of trunk lines and branch lines provided in the first embodiment of the present invention.

[0047] Figure 6 A graph showing the probability distribution of lightning strike locations according to the method for evaluating the probability distribution of lightning strike locations based on the layout of trunk lines and branch lines provided in the first embodiment of the present invention.

[0048] Figure 7 A system framework diagram for evaluating the probabilistic distribution of lightning strike locations based on the layout of trunk and branch lines provided in the second embodiment of the present invention. DETAILED DESCRIPTION

[0049] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0050] Example 1, reference Figure 1 to Figure 6 , which is an embodiment of the present invention, provides a method for evaluating the probability distribution of lightning strike locations based on the layout of trunk lines and branch lines, characterized in that:

[0051] S1: Collect distribution network data and perform preprocessing.

[0052] Distribution network data includes distribution network geographic coordinates, high-resolution terrain data, line material, historical meteorological data and regional historical lightning event records.

[0053] The preprocessing is to integrate the distribution network data into a data set and construct a large map through the tower positions in the geographical coordinates of the distribution network.

[0054] S2: Use DFS to traverse each point in the large graph and determine the number of unconnected subgraphs.

[0055] S2.1 Select an unvisited node from the graph as the starting node.

[0056] S2.2 starts from the starting node and uses DFS to traverse all nodes connected to the node and mark these nodes as visited. During the traversal process, the connection relationship between each node and its adjacent nodes is recorded.

[0057] S2.3 Repeat steps 1 and 2, continue to look for unvisited nodes as new starting nodes, and perform the next depth-first traversal. Each traversal represents the discovery of a new unconnected subgraph. The traversal ends when all nodes have been visited.

[0058] S2.4 outputs the node numbers contained in each subgraph. For example, nodes 1, 2, and 3 belong to the first subgraph, nodes 4 and 5 belong to the second subgraph, and so on.

[0059] The pattern formed by S2.5 is as follows Figure 2 As shown in Figure 1. This figure shows how to identify unconnected subgraphs through DFS. Each node is connected to its adjacent nodes to form multiple subgraphs.

[0060] S3: Draw encircling lines for each unconnected subgraph;

[0061] For each unconnected subgraph, draw the encirclement of its towers. The encirclement represents the set of all points with equal distance to the tower coordinates. Assuming that the encirclements of two separated towers have an intersection, remove the overlapping parts of the encirclements and merge them into a new encirclement.

[0062] S3.1 Draw the encirclement lines of each separated tower (each sub-graph) according to the position of the tower in the sub-graph.

[0063] S3.2 Ensure that the distance from each endpoint on the encircling line to all trunk lines and branch lines is ≤ the set encircling line distance (threshold).

[0064] S3.3 If the envelopes of two separate towers intersect, the overlapping areas of the envelopes shall be removed and merged into a new envelope.

[0065] S3.4 stores each endpoint (turning point) of the merged enclosing line in a clockwise direction to form a new closed figure.

[0066] The pattern formed by S3.5 is as follows Figure 3 This figure shows how the enclosing lines of two separated towers are merged into a new enclosing line. By removing the overlapping parts, a new closed figure is drawn.

[0067] S4: Probabilistic distribution assessment of lightning strike locations within the encirclement;

[0068] The probabilistic distribution assessment of the lightning strike location includes determining the statistical distribution of lightning parameters, using the determined statistical distribution to generate random samples using the Monte Carlo method, constructing an EGM physical model, and determining the lightning strike point through the EGM physical model.

[0069] To further describe the Monte Carlo method, we first need to determine the statistical distribution of these key lightning parameters, such as the probability distribution of current amplitude, front time, half-peak time, maximum front steepness, and the position of the descending conductor. The schematic diagram is shown in Figure 4 shown.

[0070] 1. Random sample generation: Using a certain statistical distribution, a large number of random samples are generated using the Monte Carlo method. These samples simulate the possibility of different lightning events.

[0071] 2. Physical model: Construct the EGM physical model, including the lightning strike point, etc. The physical model must be able to accurately simulate the impact of lightning strikes on the line system.

[0072] 3. Simulation calculation: The generated random samples are input into the physical model to perform a large number of simulation calculations, such as overvoltage calculations. Through these simulations, the specific impact of each lightning strike event on the system can be understood.

[0073] 4. Data statistics and analysis: Collect simulation results and conduct statistical analysis on the results. By analyzing the impact of different lightning events on the system, the lightning tolerance level and protection performance of the system can be evaluated.

[0074] 5. Risk assessment: Based on the results of statistical analysis, the failure probability and damage risk of the system under different lightning strike intensities are evaluated. This can help determine the effectiveness of existing protection measures and the necessary improvement directions.

[0075] 6. Optimization of protection measures: Based on the results of risk assessment, study the effects of different protection measures and optimize the design to improve the lightning protection performance of the system.

[0076] Through the above steps, the random lightning parameters generated by the Monte Carlo method combined with the physical model and simulation analysis can more comprehensively and accurately evaluate the lightning protection performance of the distributed line system. This method takes into account the randomness and diversity of lightning parameters, making the evaluation results more reliable.

[0077] Determining the lightning strike point through the EGM physical model includes classifying each generated lightning event by calculating the attraction radius through the EGM model to determine whether the strike position of the lightning event is on the building or trees of the line;

[0078] The attraction radius refers to the maximum horizontal distance between the step leader and the building that can produce a lightning strike. The following steps are followed to calculate the attraction radius: first, place the lightning channel directly above the building, allow it to continuously develop downward, and obtain the maximum height that can successfully trigger the upward leader; then move the lightning channel away from the building, and use the same method to record the maximum height that can successfully trigger the upward leader at this location. When the distance increases to a certain extent, it is no longer sufficient for the tip of the building to initiate an effective upward leader. At this time, the horizontal distance between the lightning channel and the building is defined as the attraction radius:

[0079] The attraction radius is expressed as,

[0080] R=1.86I 0.78 H 0.255

[0081] R a =0.84H1 0.6 I 0.74

[0082] Among them, R represents the attraction radius of the building, R a represents the attraction radius of the bush, H represents the height of the building, I represents the current intensity, and H1 represents the height of the bush;

[0083] If the distance between the lightning and the building is within the attraction radius of the building and the distance to the building is closer than the distance to the bushes, the lightning strike point is at the midpoint of the building;

[0084] If the distance between the lightning and the bush is within the attraction radius of the bush and the distance to the bush is closer than the distance to the building, the lightning strike point is at the midpoint of the bush;

[0085] If the distance between the lightning and the building is greater than the attraction radius of the building and the distance between the lightning and the bushes is greater than the attraction radius of the bushes, the lightning strike point is at a vertical point on the ground;

[0086] If the lightning strikes a building or a bush, it is a direct lightning strike.

[0087] like Figure 5 As shown in the figure, within the attraction radius, lightning strikes are more likely to fall on the midpoint of a building or a bush. This is because buildings and bushes have a significant attraction and guidance effect on lightning within their attraction radius. When lightning activity occurs, these nearby objects will preferentially attract lightning strikes due to their higher conductivity and prominent position, forming hot spots for lightning strikes. In this way, the specific location of lightning strikes can be predicted more accurately, providing more reliable lightning protection measures.

[0088] The present invention uses DFS to identify unconnected subgraphs and combines the encircling line merging method to solve the problems of high data requirements, high model complexity, insufficient comprehensive consideration and poor real-time performance in the prior art, and provides a more accurate, simple and real-time lightning risk assessment solution. This will help improve the lightning protection level of the distribution network system and ensure the safe operation of the system.

[0089] The resulting probability distribution is evaluated as Figure 6 shown.

[0090] S5: Design and train a dynamic current waveform model to simulate the current generated by lightning events on the distribution network system;

[0091] The dynamic current waveform model draws the current waveform for direct lightning strikes, and the specific method is the Cigre method or the Heidler method;

[0092] The Cigre method is expressed as,

[0093] i(t)=At+Bt n ,t≤t n

[0094]

[0095] Among them, i(t) represents the rising current value at time t, i1(t) represents the decaying current value at time t, A, B, n represent the parameters of the current rising stage, which determine the initial rising characteristics of the current waveform, t n It indicates the time when the current reaches the peak value, I1 and I2 indicate the current peak parameters in the decay stage, and t1 and t2 indicate the time constants in the decay stage;

[0096] The Heidler method is expressed as,

[0097]

[0098] Among them, i2(t) represents the rising current value at time t, I2 represents the current peak parameter, τ1 and τ2 represent time constants, η represents the normalization factor, and N represents the shape parameter.

[0099] The basis for selecting Cigre method or Heidler method is as follows: Cigre method: It is often used in situations where it is necessary to simplify the current waveform representation to reduce the calculation time. This method is suitable for preliminary lightning protection performance evaluation.

[0100] Heidler method: Applicable to situations where a more accurate description of the current waveform is required, especially when detailed simulation of lightning waveform characteristics is required.

[0101] Example 2, reference Figure 7, which is an embodiment of the present invention, provides a system for evaluating the probabilistic distribution of lightning strike locations based on the layout of trunk lines and branch lines, characterized in that it includes a data acquisition module, a sub-graph enclosing line drawing module, a probabilistic distribution evaluation module and a dynamic current waveform model module.

[0102] The data acquisition module is responsible for collecting the geographic coordinates of the distribution network, high-resolution terrain data, line materials, historical meteorological data, and historical lightning event records of the region, integrating the collected data into a data set, and constructing a large map through the tower locations.

[0103] The sub-graph enclosing line drawing module draws enclosing lines according to the positions of the pole towers in the sub-graph, processes the overlapping areas of the enclosing lines, merges them into new enclosing lines, and forms a closed graph.

[0104] The probabilistic distribution evaluation module is used to determine the statistical distribution of lightning parameters, generate random samples using the Monte Carlo method, and construct the EGM physical model to determine the lightning strike point.

[0105] The dynamic current waveform model module uses the Cigre method or the Heidler method to simulate the current waveform of a direct lightning strike.

[0106] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program code.

[0107] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0108] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0109] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0110] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for evaluating the probabilistic distribution of lightning strike locations for main and branch line layouts, characterized in that: include: Collect distribution network data and perform preprocessing; Use DFS to traverse each point in the large graph and determine the number of unconnected subgraphs; Draw bounding lines for each unconnected subgraph; Probabilistic distribution assessment of lightning strike locations within the enclosure; Design and train a dynamic current waveform model to simulate the current generated by lightning events on the distribution network system.

2. The method for evaluating the probability distribution of lightning strike locations by arranging trunk and branch lines according to claim 1, characterized in that: The distribution network data includes the geographical coordinates of the distribution network, high-resolution terrain data, line material, historical meteorological data and regional historical lightning event records; The preprocessing is to integrate the distribution network data into a data set and construct a large map through the tower positions in the geographical coordinates of the distribution network.

3. The method for evaluating the probability distribution of lightning strike positions by arranging trunk and branch lines according to claim 2, characterized in that: The determining the number of unconnected subgraphs includes selecting an unvisited node from the large graph as a starting node, starting from the starting node, using DFS to traverse all nodes connected to the initial node, marking the connected nodes as visited, and during the traversal, recording the connection relationship between each node and the connected nodes; Repeat the traversal process, find an unvisited node as the new starting node, and perform the next depth-first traversal until all nodes are visited and the traversal is completed.

4. The method for evaluating the probability distribution of lightning strike positions by arranging trunk and branch lines according to claim 3, characterized in that: Drawing the encirclement line for each unconnected subgraph includes drawing the encirclement line of each subgraph according to the position of the pole tower in the subgraph, wherein the distance from each endpoint on the encirclement line to all trunk lines and branch lines is less than or equal to the set encirclement line distance; If the enveloping lines of two separated towers have an intersection, the overlapping parts of the enveloping lines are removed and merged into a new enveloping line; Each endpoint of the merged enclosing line is stored in a clockwise direction to form a new closed figure.

5. The method for evaluating the probability distribution of lightning strike positions by arranging trunk and branch lines according to claim 4, characterized in that: The probabilistic distribution evaluation of the lightning strike location includes determining the statistical distribution of lightning parameters, using the determined statistical distribution, using the Monte Carlo method to generate random samples, constructing an EGM physical model, and determining the lightning strike point through the EGM physical model.

6. The method for evaluating the probability distribution of lightning strike positions by arranging trunk and branch lines according to claim 5, characterized in that: Determining the lightning strike point by using the EGM physical model includes calculating the attraction radius by using the EGM model, classifying each generated lightning event, and determining whether the strike position of the lightning event is on a building or a bush on the line; The attraction radius is expressed as, R=1.86I 0.78 H 0.255 R a =0.84H1 0.6 I 0.74 Among them, R represents the attraction radius of the building, R a represents the attraction radius of the bush, H represents the height of the building, I represents the current intensity, and H1 represents the height of the bush; If the distance between the lightning and the building is within the attraction radius of the building and the distance to the building is closer than the distance to the bushes, the lightning strike point is at the midpoint of the building; If the distance between the lightning and the bush is within the attraction radius of the bush and the distance to the bush is closer than the distance to the building, the lightning strike point is at the midpoint of the bush; If the distance between the lightning and the building is greater than the attraction radius of the building and the distance between the lightning and the bushes is greater than the attraction radius of the bushes, the lightning strike point is at a vertical point on the ground; If the lightning strikes a building or a bush, it is a direct lightning strike.

7. The method for evaluating the probability distribution of lightning strike positions by arranging trunk and branch lines according to claim 6, characterized in that: The simulation of the current generated by the lightning event on the distribution network system includes drawing the current waveform of the direct lightning strike through a dynamic current waveform model, and the specific method is the Cigre method or the Heidler method; The Cigre method is expressed as, i(t)=At+Bt n ,t≤t n Among them, i(t) represents the rising current value at time t, i1(t) represents the decaying current value at time t, A, B, n represent the parameters of the current rising stage, which determine the initial rising characteristics of the current waveform, t n It indicates the time when the current reaches the peak value, I1 and I2 indicate the current peak parameters in the decay stage, and t1 and t2 indicate the time constants in the decay stage; The Heidler method is expressed as, Wherein, i2(t) represents the rising current value at time t, τ1 and τ2 represent time constants, η represents the normalization factor, and N represents the shape parameter.

8. A system for evaluating the probability distribution of lightning strike locations using the method for arranging trunk and branch lines as claimed in any one of claims 1 to 7, characterized in that: It includes a data acquisition module, a sub-graph enclosing line drawing module, a probability distribution evaluation module and a dynamic current waveform model module; The data acquisition module is responsible for collecting geographic coordinates, high-resolution terrain data, line materials, historical meteorological data and regional historical lightning event records of the distribution network, integrating the collected data into a data set, and constructing a large map through the tower locations; The sub-graph encirclement line drawing module draws encirclement lines according to the positions of the pole towers in the sub-graphs, processes the overlapping areas of the encirclement lines, merges them into new encirclement lines, and forms a closed graph; The probabilistic distribution evaluation module is used to determine the statistical distribution of lightning parameters, and generate random samples using the Monte Carlo method to construct an EGM physical model for determining the lightning strike point; The dynamic current waveform model module uses the Cigre method or the Heidler method to simulate the current waveform of a direct lightning strike.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method for estimating the probabilistic distribution of lightning strike positions by arranging trunk lines and branch lines according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for estimating the probabilistic distribution of lightning strike positions by arranging trunk lines and branch lines as claimed in any one of claims 1 to 7 are implemented.

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