Arrangement method and system for lightning arresters of plateau wind turbine blades

Abstract

The invention discloses a thunder and lightning arrester arrangement method and system for plateau wind turbine blades, and relates to the technical field of wind power generation, the method considers thunder and lightning arrester arrangement of wind turbines of different models and styles, so that the method can adapt to all wind turbines including three blades (such as multiple blades, spiral blades and other special-shaped blades); the lightning arresting simulation is carried out through the actually obtained lightning meteorological data, the next lightning arresting position is updated by continuously removing the lightning arresting position obtained through iteration in the previous step, the latest position of the lightning arresting point can be dynamically adjusted according to the number of lightning arresting times obtained through calculation of the current time of the blade, and judgment through prior experience is not needed. And finally, the minimum number of the lightning arresters is further pressed through global optimization, so that redundant arrangement of the lightning arresters is prevented, the arrangement cost can be reduced while comprehensive lightning arresters are ensured, and the dynamic balance influence of the lightning arresters on the blades is reduced.

Description

Technical Field

[0001] The present application relates to the technical field of wind power generation, and particularly relates to a method and system for arranging lightning arresters on blades of a high-altitude wind turbine. Background Art

[0002] Wind power generation refers to converting the kinetic energy of wind into electrical energy. Wind energy is a clean, pollution-free and renewable energy source. Wind power generation drives the rotation of the windmill blades by wind, and then increases the rotation speed through a speed increaser to promote the generator to generate electricity. Moreover, wind power generation does not require the use of fuel and does not produce radiation or air pollution, and is a renewable new energy source. Wind power generation mainly converts wind energy into mechanical work through a wind turbine (wind generator), the mechanical work drives the rotor to rotate, and finally alternating current is output.

[0003] In order to ensure the good operation efficiency of the wind turbine, it is usually necessary to build the wind turbine in a relatively flat area to avoid the influence of buildings, mountains, forests, etc. on the wind speed. Due to the long length of the sleeve and blades of the wind turbine, the blades of the wind turbine are at a high position and are prone to being struck by lightning during thunderstorm weather.

[0004] For lightning protection of wind turbines, lightning arresters are usually installed on the blades, and then through on-site judgment by staff during daily inspections and maintenance to obtain the hardware conditions of the blades. When the blades are struck by lightning with a small to medium amplitude, the cracks and bulges formed on the blades are not obvious and are difficult to be found during the inspection process. If small cracks and bulges are not dealt with in time, it is easy to cause further damage such as water accumulation and cracking under exposure to the sun, thus affecting the safe operation of the wind turbine unit; after the lightning strikes the lightning arrester, the current generated by the lightning is conducted to the grounding end through the wire connected to the lightning arrester, thus effectively protecting the blades from lightning damage.

[0005] At present, the installation of lightning arresters is still based on prior experience and industry norms. The installation principle of lightning arresters is only to install corresponding numbers of lightning arresters according to the different lengths of the blades. Since the technology of the lightning strike characteristics and probability of wind turbine blades is not yet clear, the lightning arresters installed based on experience cannot effectively reduce the lightning strike probability of the blades, resulting in poor protection pertinence and ineffective lightning protection effect of the lightning arresters. Summary of the Invention

[0006] The main purpose of the present application is to provide a method and system for arranging lightning arresters on blades of a high-altitude wind turbine to solve the problem that the installation of lightning arresters in the prior art is still based on prior experience and industry norms, resulting in poor protection pertinence and ineffective lightning protection effect of the lightning arresters.

[0007] To achieve the above purpose, the present application provides the following technical solutions: A method for arranging lightning arresters on the blades of a high-altitude wind turbine, where the high-altitude wind turbine blades are applied to a wind turbine in a preset area, and the wind turbine has a blade assembly driven by external wind energy. The method for arranging lightning arresters includes: Step S1: Obtain the point cloud data of the wind turbine through remote sensing scanning, and construct a digital model of the wind turbine based on the point cloud data. The digital model includes the blade assembly; Step S2: Obtain the digital surface model of the preset area, and input the digital model into the digital surface model to form a simulation environment; Step S3: Input the simulation environment into a preset simulation software, and add a number of real lightning meteorological data in the simulation environment through the preset simulation software; Step S4: Simulate multiple discharges through the preset simulation software based on all real lightning meteorological data, and calculate the lightning strike times of the blade assembly through a preset leader model; Step S5: Obtain the area in the blade assembly where the lightning strike times exceed a preset number threshold, and add a lightning arrester at the center of the area; Step S6: Exclude the area where the lightning arrester has been installed, and repeat Steps S4 to S5 until the installation quantity of the lightning arrester reaches a preset quantity threshold, or the blade assembly no longer receives lightning strikes; Step S7: Determine whether the iteration stop condition in Step S6 is that the installation quantity of the lightning arrester reaches a preset quantity threshold, or the blade assembly no longer receives lightning strikes. If the installation quantity of the lightning arrester reaches a preset quantity threshold, then execute Step S8; Step S8: Take the surface of the blade assembly as the iteration range, and globally optimize and iterate the installation positions and installation quantities of all lightning arresters until the blade assembly no longer receives lightning strikes and the installation quantity reaches the minimum value; Step S9: Obtain the post-iteration installation positions and post-iteration installation quantities of all lightning arresters, and send them to an external layout terminal.

[0008] As a further improvement of the present application, in Step S7, after determining whether the iteration stop condition in Step S6 is that the installation quantity of the lightning arrester reaches a preset quantity threshold, or the blade assembly no longer receives lightning strikes, it includes: Step S10: If the iteration stop condition is that the blade assembly no longer receives lightning strikes, then execute Step S20; Step S20: Based on the preset simulation software, obtain the spatial coordinates of all lightning arresters and the lightning strike surface orientations of all lightning arresters; Step S30: Integrate the spatial coordinates of the current lightning arrester and the orientation of the lightning-receiving surface of the current lightning arrester into the absolute installation position of the current lightning arrester; Step S40: Obtain the Euclidean distances of each lightning arrester based on at least two non-collinear edges of the blade assembly respectively; Step S50: Integrate all the Euclidean distances of the current lightning arrester and the orientation of the lightning-receiving surface of the current lightning arrester into the relative installation position of the current lightning arrester; Step S60: Package the absolute installation position and the relative installation position of the current lightning arrester into the installation data packet of the current lightning arrester; Step S70: Send the installation data packets of all lightning arresters to the external layout end.

[0009] As a further improvement of this application, in step S9, obtain the iterative installation positions and the iterative installation quantities of all lightning arresters, and send them to the external layout end. After that, it includes: Step S100: Take all the iterative installation positions as the execution entities, and repeat steps S20 to S50 to obtain the absolute installation position and the relative installation position of the current iteratively updated lightning arrester; Step S200: Package the absolute installation position and the relative installation position of the current iteratively updated lightning arrester into the iterative installation data packet of the current lightning arrester; Step S300: Send the iterative installation data packets of all lightning arresters to the external layout end.

[0010] As a further improvement of this application, in step S4, based on all the real lightning meteorological data, simulate several discharges through the preset simulation software, and calculate the lightning-receiving times of the blade assembly through a preset leader model, including: Step S41: Define the blade assembly as the lightning-receiving area, and define several random lightning-receiving points in the lightning-receiving area; Step S42: Calculate the charge density of the current random lightning-receiving point based on a real lightning meteorological data through the downward leader charge equation; Step S43: Define the upward leader length equation based on the current random lightning-receiving point; Step S44: Substitute the charge density into the upward leader length equation to calculate the upward leader length of the current random lightning-receiving point; Step S45: Calculate the lightning-receiving times of the current random lightning-receiving point based on the upward leader length; Step S46: Calculate the arithmetic mean of all the lightning-receiving times of all the real lightning meteorological data to obtain the average lightning-receiving times of the current random lightning-receiving point.

[0011] As a further improvement of the present application, step S5, obtaining the area in the blade assembly where the lightning strike count exceeds the preset count threshold and adding a lightning arrester at the center of the area, includes: Step S51, selecting at least one random lightning strike point from all random lightning strike points and defining it as the center of the initial cluster; Step S52, respectively obtaining the Euclidean distance between each random lightning strike point and the centers of all initial clusters, and assigning each random lightning strike point to the initial cluster with the closest Euclidean distance; Step S53, after the assignment, recalculating the center of the current initial cluster based on all random lightning strike points in the current initial cluster; Step S54, repeatedly executing step S52 to step S53 to iterate the centers of all initial clusters; Step S55, when the distance between the centers of all initial clusters in the most recent iteration and the centers of all initial clusters in the previous iteration is less than or equal to the preset distance threshold, the iteration ends; Step S56, obtaining the centers of all initial clusters after the iteration ends and defining them as the centers of all areas; Step S57, adding a lightning arrester at the center of each area respectively.

[0012] As a further improvement of the present application, step S8, taking the surface of the blade assembly as the iteration range, iterating the installation positions and installation quantities of all lightning arresters through global optimization until the blade assembly no longer receives lightning strikes and the installation quantity reaches the minimum value, includes: Step S81, taking the surface of the blade assembly as the iteration range, redundantly adding several random solutions on the surface of the blade assembly, and each lightning arrester corresponds to at least one random solution; Step S82, defining the optimization result of all random solutions as that the blade assembly no longer receives lightning strikes and the installation quantity reaches the minimum value; Step S83, initializing the positions of each random solution, and respectively updating the current position and current speed of each random solution once based on a single discharge simulation; Step S84, obtaining the lightning strike situation of the blade assembly once based on each update; Step S85, if the blade assembly no longer receives lightning strikes, reducing one random solution; Step S86, repeatedly executing step S83 to step S85 until the number of all random solutions reaches the minimum value, and the iteration ends; Step S87, obtaining the positions and quantities of all random solutions after all iterations, which are the installation positions and installation quantities of all lightning arresters.

[0013] As a further improvement of the present application, in step S9, obtain the iterated installation positions and iterated installation quantities of all lightning arresters, and send them to the external layout end. After that, it includes: Step S1000, send the digital model, the iterated installation positions and iterated installation quantities of all lightning arresters to the external visual monitoring end.

[0014] To achieve the above object, the present application also provides the following technical solutions: A lightning arrester layout system for a high-altitude wind turbine blade, the lightning arrester layout system is applied to the lightning arrester layout method as described above, and the lightning arrester layout system includes: A wind turbine digital model construction module, configured to obtain the point cloud data of the wind turbine through remote sensing scanning, and construct the digital model of the wind turbine based on the point cloud data, where the digital model includes the blade assembly; A simulation environment generation module, configured to obtain the digital surface model of the preset area, and input the digital model into the digital surface model to form a simulation environment; A lightning meteorological data adding module, configured to input the simulation environment into a preset simulation software, and add a number of real lightning meteorological data to the simulation environment through the preset simulation software; A blade assembly lightning strike simulation module, configured to simulate a number of discharges through the preset simulation software based on all real lightning meteorological data, and calculate the lightning strike times of the blade assembly through a preset leader model; A lightning arrester adding module, configured to obtain the area in the blade assembly where the lightning strike times exceed a preset number threshold, and add a lightning arrester at the center of the area; A lightning arrester iteration module, configured to exclude the area where the lightning arrester has been installed, and repeat the execution of the blade assembly lightning strike simulation module to the lightning arrester adding module until the installation quantity of the lightning arrester reaches a preset quantity threshold, or the blade assembly no longer receives lightning strikes; An iteration result condition judgment module, configured to judge whether the iteration stop condition of the lightning arrester iteration module is that the installation quantity of the lightning arrester reaches a preset quantity threshold, or the blade assembly no longer receives lightning strikes; A lightning arrester optimization module, configured to, if the installation quantity of the lightning arrester reaches a preset quantity threshold, take the surface of the blade assembly as the iteration range, and globally optimize and iterate the installation positions and installation quantities of all lightning arresters until the blade assembly no longer receives lightning strikes and the installation quantity reaches the minimum value; A lightning arrester layout module, configured to obtain the iterated installation positions and iterated installation quantities of all lightning arresters, and send them to the external layout end.

[0015] To achieve the above object, the present application also provides the following technical solutions: An electronic device includes a processor and a memory coupled to the processor. The memory stores program instructions executable by the processor. When the processor executes the program instructions stored in the memory, the lightning arrester arrangement method for the blades of a high-altitude wind turbine as described above is implemented.

[0016] To achieve the above object, the present application also provides the following technical solutions: A storage medium stores program instructions that can implement the lightning arrester arrangement method for the blades of a high-altitude wind turbine as described above when executed by a processor.

[0017] The present application obtains the point cloud data of the wind turbine through remote sensing scanning, constructs a digital model of the wind turbine based on the point cloud data. The digital model includes a blade assembly; obtains the digital surface model of a preset area, and inputs the digital model into the digital surface model to form a simulation environment; inputs the simulation environment into a preset simulation software, and adds a number of real lightning meteorological data in the simulation environment through the preset simulation software; simulates multiple discharges in the simulation environment based on all real lightning meteorological data through the preset simulation software, and calculates the lightning strike times of the blade assembly through a preset leader model; obtains the area where the lightning strike times in the blade assembly exceed a preset number threshold and adds a lightning arrester at the center of the area; excludes the area where the lightning arrester has been installed, and repeats the above two steps until the installation quantity of the lightning arrester reaches a preset quantity threshold, or the blade assembly no longer receives lightning strikes; determines whether the iteration stop condition of the above steps is that the installation quantity of the lightning arrester reaches the preset quantity threshold or the blade assembly no longer receives lightning strikes. If it is that the installation quantity of the lightning arrester reaches the preset quantity threshold, then with the surface of the blade assembly as the iteration range, globally optimize and iterate the installation positions and installation quantities of all lightning arresters until the blade assembly no longer receives lightning strikes and the installation quantity reaches the minimum value; obtains the iterated installation positions and iterated installation quantities of all lightning arresters and sends them to an external layout terminal. The present application considers the lightning arrester arrangements of wind turbines of different models and styles, enabling the present application to adapt to all wind turbines including three-blade wind turbines (such as multi-blade wind turbines, spiral blade wind turbines, other special-shaped blade wind turbines, etc.), and conducts lightning strike simulations through realistically obtained lightning meteorological data. By continuously removing the lightning strike positions obtained in the previous iteration to update the next lightning strike position, it can dynamically adjust the latest position of the lightning strike point according to the lightning strike times calculated for the blade in the current iteration, without the need to judge through prior experience, and finally further squeezes the minimum quantity of the lightning arrester through global optimization, not only preventing redundant arrangements of the lightning arrester, but also being able to reduce the layout cost while ensuring comprehensive lightning strikes and reducing the impact of the lightning arrester on the dynamic balance of the blade. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a display diagram of different models of wind turbines for an embodiment of the lightning arrester arrangement method for the blades of a high-altitude wind turbine in this application; Figure 2 It is a schematic diagram of the step flow for an embodiment of the lightning arrester arrangement method for the blades of a high-altitude wind turbine in this application; Figure 3 It is a schematic diagram of the functional modules for an embodiment of the lightning arrester arrangement system for the blades of a high-altitude wind turbine in this application; Figure 4 It is a schematic structural diagram of an embodiment of an electronic device in this application; Figure 5 It is a schematic structural diagram of an embodiment of a storage medium in this application. Specific embodiments

[0019] Next, the technical solutions in the embodiments of this application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of this application. Obviously, the described embodiments are only a part of the embodiments of this application, rather than all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the scope of protection of this application.

[0020] The terms "first", "second", and "third" in this application are only used for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, features defined with "first", "second", and "third" may explicitly or implicitly include at least one of such features. In the description of this application, the meaning of "a plurality" is at least two, such as two, three, etc., unless otherwise specifically and clearly defined. All directional indications (such as up, down, left, right, front, back...) in the embodiments of this application are only used to explain the relative positional relationship and movement conditions between components in a specific posture (as shown in the drawings). If the specific posture changes, then the directional indications will also change accordingly. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the listed steps or units, but optionally further includes steps or units not listed, or optionally further includes other steps or units inherent to these processes, methods, products, or devices.

[0021] References herein to "embodiments" mean that the particular features, structures, or characteristics described in connection with the embodiments can be included in at least one embodiment of the present application. The phrase appears in various places in the specification and does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art will explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments.

[0022] As Figure 1 shown, this embodiment provides an embodiment of a method for arranging lightning arresters on blades of a high-altitude wind turbine. In this embodiment, the high-altitude wind turbine blade is applied to a wind turbine in a preset area, and the wind turbine has a blade assembly driven by external wind energy. Refer to Figure 1 , Figure 1 There are various models of wind turbines. In addition to the three-blade and five-blade shapes, there are also other special-shaped structures such as other spiral shapes and centrosymmetric shapes. Several of them are enumerated in this embodiment for illustrative purposes.

[0023] Specifically, refer to Figure 2 , the method for arranging lightning arresters includes the following steps: Step S1, obtain the point cloud data of the wind turbine through remote sensing scanning, and construct a digital model of the wind turbine based on the point cloud data. The digital model includes a blade assembly.

[0024] Preferably, the construction of the digital model can be achieved through modeling software. For example: ‌Bentley ContextCapture: Supports the fusion modeling of large-scale point cloud and photo data, and automatically generates a high-precision three-dimensional grid model, especially suitable for reverse modeling of facilities such as wind turbines; this software also provides a point cloud editing tool (Bentley Pointools) and a reverse modeling function (Bentley Descartes), which can handle complex structural features.

[0025] ‌Agisoft Metashape: Generates a three-dimensional model with millimeter-level accuracy through dense point clouds, supports the fusion of laser scanning and UAV image data, and is suitable for the surface reconstruction of wind turbine blades; this software provides GPU acceleration processing to optimize the calculation efficiency of massive point cloud data.

[0026] ‌RealityCapture: Processes millions of point cloud data using high-speed algorithms to generate a three-dimensional model with true color texture, suitable for the overall structure reconstruction of wind turbine units.

[0027] Step S2, obtain the digital surface model of the preset area, and input the digital model into the digital surface model to form a simulation environment.

[0028] Preferably, the Digital Surface Model (DSM) is a three-dimensional model representing the heights of all objects on the Earth's surface, including natural and man-made structures. The DSM not only includes the elevation of the ground but also the heights of buildings, trees, and other structures. The DSM is created by obtaining data from the air using Light Detection and Ranging (LiDAR) technology or photogrammetry methods.

[0029] Preferably, the design intention of introducing the Digital Surface Model in this embodiment is that not all wind turbines are significantly higher than the surrounding terrain or buildings. Therefore, this embodiment takes into account the influence of the surrounding terrain and buildings on the lightning strike of wind turbines.

[0030] Step S3: Input the simulation environment into a preset simulation software, and add a number of real lightning meteorological data to the simulation environment through the preset simulation software.

[0031] Preferably, the preset simulation software can be set to FAST / OpenFAST. This software optimizes the layout of wind turbines through micro-siting to reduce the risk of lightning concentration. It is necessary to conduct a secondary analysis of the protection range of lightning arresters in combination with electromagnetic simulation tools. This software integrates geographical data and wind resource models and supports multi-objective optimization (power generation efficiency + safety protection).

[0032] Step S4: Based on all the real lightning meteorological data, simulate several discharges through the preset simulation software, and calculate the number of lightning strikes on the blade assembly through a preset leader model.

[0033] Preferably, the leader model of lightning is used to describe the staged dynamic process of the development of charges from the cloud to the ground (or from the ground upwards) during the lightning discharge process. Its core is to simulate the formation and extension of the lightning channel through physical mechanisms. In the leader initiation stage, charge accumulation inside the thundercloud forms a strong electric field. When the local electric field strength exceeds the air breakdown threshold, the initial development of the ionization channel is triggered, which is called leader initiation. This stage is usually triggered by uneven charge distribution inside the cloud or electric field distortion of ground protrusions. Then it enters the stepped leader development stage. The stepped leader extends downward in a segmented jumping manner, with each segment about 50 - 100 meters long, forming a conductive channel by continuously ionizing the air. Its path is affected by factors such as electric field strength, air density, and humidity, showing a random branching characteristic. Finally, it is the connection process and the return stroke. When the stepped leader approaches the ground (or the upward leader from the ground approaches the cloud), the electric field between the two is further enhanced, triggering the instantaneous penetration of the main discharge channel (i.e., the return stroke), releasing huge energy and forming a visible lightning flash.

[0034] It should be noted that at the top of protrusions such as high-rise buildings or wind turbine blades, a strong electric field may actively trigger an upward leader, that is, charges develop from the ground upwards.

[0035] Step S5: Obtain the area in the blade assembly where the number of lightning strikes exceeds the preset number threshold, and add a lightning arrester at the center of the area.

[0036] Step S6: Exclude the area where the lightning arrester has been installed, and repeat steps S4 to S5 until the installation quantity of the lightning arrester reaches the preset quantity threshold, or the blade assembly no longer receives lightning strikes.

[0037] Preferably, the preset quantity threshold of the lightning arrester can be set according to the spacing between adjacent lightning arresters, and the minimum spacing is usually 1 meter.

[0038] Step S7: Determine whether the iteration stop condition in step S6 is that the installation quantity of the lightning arrester reaches the preset quantity threshold or the blade assembly no longer receives lightning strikes. If it is that the installation quantity of the lightning arrester reaches the preset quantity threshold, then execute step S8.

[0039] Step S8: Take the surface of the blade assembly as the iteration range, and globally optimize the installation positions and installation quantities of all lightning arresters through iteration until the blade assembly no longer receives lightning strikes and the installation quantity reaches the minimum value.

[0040] Step S9: Obtain the post-iteration installation positions and post-iteration installation quantities of all lightning arresters, and send them to the external layout end.

[0041] Furthermore, in step S7, determine whether the iteration stop condition in step S6 is that the installation quantity of the lightning arrester reaches the preset quantity threshold or the blade assembly no longer receives lightning strikes. After that, the following steps are further included: Step S10: If the iteration stop condition is that the blade assembly no longer receives lightning strikes, then execute step S20.

[0042] Step S20: Obtain the spatial coordinates of all lightning arresters and the lightning strike surface orientations of all lightning arresters based on the preset simulation software.

[0043] Step S30: Integrate the spatial coordinates of the current lightning arrester and the lightning strike surface orientation of the current lightning arrester into the absolute installation position of the current lightning arrester.

[0044] Step S40: Respectively obtain the Euclidean distances of each lightning arrester based on at least two non-collinear edges of the blade assembly.

[0045] Step S50: Integrate all the Euclidean distances of the current lightning arrester and the lightning strike surface orientation of the current lightning arrester into the relative installation position of the current lightning arrester.

[0046] Step S60: Package the absolute installation position and the relative installation position of the current lightning arrester into the installation data packet of the current lightning arrester.

[0047] Step S70: Send the installation data packets of all lightning arresters to the external layout end.

[0048] Preferably, in this embodiment, the absolute installation position and the relative installation position are considered to be mutually verified to ensure the installation accuracy of the lightning arrester.

[0049] Further, in step S9, obtain the post-iteration installation positions and the post-iteration installation quantities of all lightning arresters, and send them to the external layout end. After that, the following steps are further included: Step S100: Take all the post-iteration installation positions as the execution entities, and repeatedly execute step S20 to step S50 to obtain the absolute installation position and the relative installation position of the lightning arrester after the current iteration.

[0050] Step S200: Package the absolute installation position and the relative installation position of the lightning arrester after the current iteration into the post-iteration installation data packet of the current lightning arrester.

[0051] Step S300: Send the post-iteration installation data packets of all lightning arresters to the external layout end.

[0052] Preferably, steps S100 to S300 are used to obtain the installation positions under another determination condition.

[0053] Further, in step S4, based on all the real lightning meteorological data, simulate the discharges for several times through a preset simulation software, and calculate the lightning strike times of the blade assembly through a preset leader model. The specific steps are as follows: Step S41: Define the blade assembly as the lightning strike area, and define several random lightning strike points in the lightning strike area.

[0054] Step S42: Calculate the charge density of the current random lightning strike point based on one piece of real lightning meteorological data through the downward leader charge equation.

[0055] Preferably, the charge density of the current random lightning strike point can be calculated by the following formula: .

[0056] Wherein, is the charge density of the current random lightning strike point; is the distance between the current random lightning strike point and the leader channel of the lightning cloud in the simulation environment, usually taking a negative sign; is the peak current of the lightning cloud; is the height of the lightning cloud from the ground; is the height of the current random lightning strike point from the ground; ; ; ; ; .

[0057] Step S43: Define the upward leader length equation based on the current random strike point.

[0058] Preferably, the upward leader length equation is shown as follows: .

[0059] Where, is the upward leader length of the th corona of the current random strike point; is the leader growth increment for each corona; is the electric charge required for the leader to convert per unit length, ; is the charge density of the current random strike point; is the volume of the leader channel; is the environmental factor, ; is the electric field strength of the th corona; is the leader head potential of the th corona of the current random strike point.

[0060] Preferably, under lightning conditions, the electric field near the ground object is jointly affected by the charged thunderstorm cloud and the downward leader. The height of the thunderstorm cloud from the ground is usually 2 km to 10 km. An individual thunderstorm cloud usually has two to three charge centers, and a large amount of positive charge accumulates in the uppermost layer of the thunderstorm cloud, while its lower part is negatively charged. Sometimes, there is one or more weak positive charge regions at the bottom, and a certain magnitude of electric field is generated near the ground, and the absolute value of its amplitude is about 10 kV / m to 20 kV / m.

[0061] Step S44: Substitute the charge density into the upward leader length equation to calculate the upward leader length of the current random strike point.

[0062] Step S45: Calculate the strike times of the current random strike point based on the upward leader length.

[0063] Preferably, the latest value of the upward leader length is iterated through the above formula following the time series. Usually, when exceeds the preset length, it is determined as the start of a stable leader. The preset length is generally two meters, that is, the critical length of leader development is two meters.

[0064] Preferably, after it is determined as the start of a stable leader, the part exceeding the preset length is defined as the strike radius of the current random strike point, and then the strike area of this time is calculated according to the strike radius: .

[0065] Among them, is the hitting radius of the current random lightning strike point; is the polarity constant of the lightning cloud layer. When the lightning cloud layer is positively polarized , when the lightning cloud layer is negatively polarized .

[0066] It should be noted that, as can be seen from the above formula, the lightning receiving area is usually a horizontal circle.

[0067] Step S46: Perform arithmetic mean on all lightning strike times based on all real lightning meteorological data to obtain the average lightning strike times of the current random lightning strike point.

[0068] Preferably, in the current real lightning meteorological data, the lightning strike times of the current random lightning strike point are shown in the following formula: .

[0069] Among them, is the positive-polarity lightning strike times of the current random lightning strike point in the current real lightning meteorological data; is the average lightning strike times of all real lightning meteorological data; is the current peak probability distribution of the current when the lightning cloud layer is positively polarized; is the negative-polarity lightning strike times of the current random lightning strike point in the current real lightning meteorological data; is the current peak probability distribution of the current when the lightning cloud layer is negatively polarized.

[0070] Furthermore, step S5: Obtain the area in the blade assembly where the lightning strike times exceed the preset number threshold and add a lightning arrester at the center of the area, which specifically includes the following steps: Step S51: Select at least one random lightning strike point from all random lightning strike points and define it as the center of the initial cluster.

[0071] Step S52: Respectively obtain the Euclidean distance between each random lightning strike point and all initial cluster centers, and assign each random lightning strike point to the initial cluster with the closest Euclidean distance.

[0072] Step S53: After the assignment, recalculate the center of the current initial cluster based on all random lightning strike points in the current initial cluster.

[0073] Step S54: Repeat steps S52 to S53 to iterate the centers of all initial clusters.

[0074] Step S55: When the distance between the centers of all initial clusters in the most recent iteration and the centers of all initial clusters in the previous iteration is less than or equal to the preset distance threshold, the iteration ends.

[0075] Step S56: Obtain the centers of all initial clusters after the iteration ends and define them as the centers of all regions.

[0076] Step S57: Add a lightning arrester at the center of each region respectively.

[0077] Generally understood, the process idea from Step S51 to Step S57 is as follows: ① Initialize the cluster centers: Randomly select K data points as the initial cluster centers (centroids). The selection method can be simple random selection or using an optimization strategy (such as K-Means++).

[0078] ② Assign data points to clusters: Calculate the distance from each data point to all cluster centers (usually using Euclidean distance), and assign each point to the cluster corresponding to the nearest cluster center.

[0079] ③ Update the positions of the cluster centers: Recalculate the centroid of each cluster, and the new centroid is the mean value of all data points in the cluster (i.e., the average of the coordinates of each dimension).

[0080] ④ Iterative optimization: Repeat steps ② to ③ until one of the following conditions is met and stop: The centroids no longer change significantly (the distance between the old and new centroids is less than the set threshold); The preset maximum number of iterations is reached.

[0081] It should be noted that in order to eliminate the error of artificial subjective experience, the value of K can be determined by the elbow method or the silhouette coefficient.

[0082] Furthermore, in Step S8, with the surface of the blade assembly as the iteration range, globally optimize and iterate the installation positions and installation quantities of all lightning arresters until the blade assembly no longer receives lightning strikes and the installation quantity reaches the minimum value. The specific steps are as follows: Step S81: With the surface of the blade assembly as the iteration range, redundantly add several random solutions on the surface of the blade assembly, and each lightning arrester corresponds to at least one random solution.

[0083] Step S82: Define the optimization result of all random solutions as that the blade assembly no longer receives lightning strikes and the installation quantity reaches the minimum value.

[0084] Step S83: Initialize the positions of each random solution, and update the current position and current speed of each random solution once respectively based on a single discharge simulation.

[0085] Step S84: Obtain the lightning strike situation of the blade assembly once based on each update.

[0086] Step S85, if the blade assembly no longer receives lightning strikes, reduce one random solution.

[0087] Step S86, repeatedly execute Step S83 to Step S85 until the number of all random solutions reaches the minimum value, and the iteration ends.

[0088] Preferably, the determination of the minimum value can be set as follows: under the condition that the blade assembly no longer receives lightning strikes, reduce the number of current random solutions by one. If lightning strikes start again, it is determined that the number of random solutions before reduction is the minimum value.

[0089] Step S87, obtain the positions and quantities of all random solutions after iteration, which are the installation positions and installation quantities of all lightning arresters.

[0090] Further, in Step S9, obtain the installation positions and installation quantities of all lightning arresters after iteration and send them to the external layout end. After that, the following steps are further included: Step S1000, send the digital model, the installation positions and installation quantities of all lightning arresters after iteration to the external visual monitoring end.

[0091] In this embodiment, the point cloud data of the wind turbine is obtained through remote sensing scanning, and a digital model of the wind turbine is constructed based on the point cloud data. The digital model includes a blade assembly; a digital surface model of a preset area is obtained, and the digital model is input into the digital surface model to form a simulation environment; the simulation environment is input into a preset simulation software, and a number of real lightning meteorological data are added in the simulation environment through the preset simulation software; a number of discharges are simulated based on all the real lightning meteorological data through the preset simulation software, and the lightning strike times of the blade assembly are calculated through a preset leader model; the area in the blade assembly where the lightning strike times exceed a preset number threshold is obtained, and a lightning arrester is added at the center of the area; the area where the lightning arrester has been installed is excluded, and the above two steps are repeated until the installation quantity of the lightning arrester reaches a preset quantity threshold, or the blade assembly no longer receives lightning strikes; it is judged whether the iteration stop condition of the above steps is that the installation quantity of the lightning arrester reaches the preset quantity threshold or the blade assembly no longer receives lightning strikes. If it is that the installation quantity of the lightning arrester reaches the preset quantity threshold, the surface of the blade assembly is used as the iteration range, and the installation positions and installation quantities of all the lightning arresters are iterated through global optimization until the blade assembly no longer receives lightning strikes and the installation quantity reaches the minimum value; the iterated installation positions and iterated installation quantities of all the lightning arresters are obtained and sent to an external layout end. This embodiment considers the lightning arrester layout of wind turbines of different models and styles, enabling this embodiment to adapt to all wind turbines including three blades (such as multi-blades, spiral blades, other special-shaped blades, etc.), and performing lightning strike simulation through the actually obtained lightning meteorological data. By continuously removing the lightning strike positions obtained in the previous iteration to update the next lightning strike position, the latest position of the lightning strike point can be dynamically adjusted according to the lightning strike times calculated for the current blade, without the need to judge through prior experience. Finally, through global optimization, the minimum quantity of the lightning arrester is further reduced, not only preventing redundant layout of the lightning arrester, but also being able to reduce the layout cost while ensuring comprehensive lightning strikes and reducing the impact of the lightning arrester on the dynamic balance of the blade.

[0092] As Figure 3 shown, this embodiment provides an embodiment of a lightning arrester layout system for a high-altitude wind turbine blade. In this embodiment, the lightning arrester layout system is applied to the lightning arrester layout method in the above-mentioned embodiment.

[0093] Specifically, the lightning arrester layout system includes a wind turbine digital model construction module 1, a simulation environment generation module 2, a lightning meteorological data addition module 3, a blade assembly lightning strike simulation module 4, a lightning arrester addition module 5, a lightning arrester iteration module 6, an iteration result condition judgment module 7, a lightning arrester optimization module 8, and a lightning arrester layout module 9 that are electrically connected in sequence.

[0094] Among them, the wind turbine digital model construction module 1 is used to obtain the point cloud data of the wind turbine through remote sensing scanning, and construct the digital model of the wind turbine based on the point cloud data. The digital model includes blade components; the simulation environment generation module 2 is used to obtain the digital surface model of the preset area and input the digital model into the digital surface model to form a simulation environment; the lightning meteorological data adding module 3 is used to input the simulation environment into the preset simulation software, and add a number of real lightning meteorological data to the simulation environment through the preset simulation software; the blade component lightning strike simulation module 4 is used to simulate a number of discharges based on all real lightning meteorological data through the preset simulation software, and calculate the lightning strike times of the blade components through the preset leader model; the lightning arrester adding module 5 is used to obtain the area where the lightning strike times of the blade components exceed the preset number threshold and add a lightning arrester at the center of the area; the lightning arrester iteration module 6 is used to exclude the area where the lightning arrester has been installed, and repeat the execution of the blade component lightning strike simulation module to the lightning arrester adding module until the installation quantity of the lightning arrester reaches the preset quantity threshold, or the blade components no longer receive lightning strikes; the iteration result condition judgment module 7 is used to judge whether the iteration stop condition of the lightning arrester iteration module is that the installation quantity of the lightning arrester reaches the preset quantity threshold or the blade components no longer receive lightning strikes; the lightning arrester optimization module 8 is used to, if the installation quantity of the lightning arrester reaches the preset quantity threshold, take the surface of the blade components as the iteration range, and globally optimize and iterate the installation positions and installation quantities of all lightning arresters until the blade components no longer receive lightning strikes and the installation quantity reaches the minimum value; the lightning arrester layout module 9 is used to obtain the iteration installation positions and iteration installation quantities of all lightning arresters and send them to the external layout end.

[0095] Further, the lightning arrester layout system includes a lightning arrester installation data acquisition module, an absolute installation position acquisition module, a lightning arrester relative position acquisition module, a relative installation position acquisition module, a lightning arrester installation data packet packaging module, and an installation data packet sending module that are electrically connected in sequence; the lightning arrester installation data acquisition module is electrically connected to the iteration result condition judgment module 7.

[0096] Among them, the lightning arrester installation data acquisition module is used to, if the iteration stop condition is that the blade assembly no longer receives lightning strikes, obtain the spatial coordinates of all lightning arresters and the lightning receiving surface orientations of all lightning arresters based on a preset simulation software; the absolute installation position acquisition module is used to integrate the spatial coordinates of the current lightning arrester and the lightning receiving surface orientation of the current lightning arrester into the absolute installation position of the current lightning arrester; the relative position acquisition module of the lightning arrester is used to respectively obtain the Euclidean distances of each lightning arrester based on at least two non-collinear edges of the blade assembly; the relative installation position acquisition module is used to integrate all the Euclidean distances of the current lightning arrester and the lightning receiving surface orientation of the current lightning arrester into the relative installation position of the current lightning arrester; the lightning arrester installation data packet packaging module is used to package the absolute installation position and the relative installation position of the current lightning arrester into the installation data packet of the current lightning arrester; the installation data packet sending module is used to send the installation data packets of all lightning arresters to an external layout end.

[0097] Further, the lightning arrester layout system includes an iteration-post lightning arrester installation position acquisition module, an iteration-post installation data packet packaging module, and an iteration-post installation data packet sending module that are electrically connected in sequence; the iteration-post lightning arrester installation position acquisition module is electrically connected to the lightning arrester layout module 9.

[0098] Among them, the iteration-post lightning arrester installation position acquisition module is used to use all the iteration-post installation positions as the execution entities, and repeatedly execute the absolute installation position acquisition module to the lightning arrester installation data packet packaging module to obtain the absolute installation position and the relative installation position of the current iteration-post lightning arrester; the iteration-post installation data packet packaging module is used to package the absolute installation position and the relative installation position of the current iteration-post lightning arrester into the iteration-post installation data packet of the current lightning arrester; the iteration-post installation data packet sending module is used to send the iteration-post installation data packets of all lightning arresters to an external layout end.

[0099] Further, the blade assembly lightning strike simulation module 4 specifically includes a first blade assembly lightning strike simulation unit, a second blade assembly lightning strike simulation unit, a third blade assembly lightning strike simulation unit, a fourth blade assembly lightning strike simulation unit, a fifth blade assembly lightning strike simulation unit, and a sixth blade assembly lightning strike simulation unit that are electrically connected in sequence; the first blade assembly lightning strike simulation unit is electrically connected to the lightning meteorological data adding module 3, and the sixth blade assembly lightning strike simulation unit is electrically connected to the lightning arrester adding module 5.

[0100] Among them, the first blade assembly lightning strike simulation unit is used to define the blade assembly as a lightning strike area and define a number of random lightning strike points in the lightning strike area; the second blade assembly lightning strike simulation unit is used to calculate the charge density of the current random lightning strike point through the downward leader charge equation based on a real lightning meteorological data; the third blade assembly lightning strike simulation unit is used to define the upward leader length equation based on the current random lightning strike point; the fourth blade assembly lightning strike simulation unit is used to substitute the charge density into the upward leader length equation to calculate the upward leader length of the current random lightning strike point; the fifth blade assembly lightning strike simulation unit is used to calculate the number of lightning strikes of the current random lightning strike point based on the upward leader length; the sixth blade assembly lightning strike simulation unit is used to perform an arithmetic average based on the number of lightning strikes of all real lightning meteorological data to obtain the average number of lightning strikes of the current random lightning strike point.

[0101] Further, the lightning arrester adding module 5 specifically includes a first lightning arrester adding unit, a second lightning arrester adding unit, a third lightning arrester adding unit, a fourth lightning arrester adding unit, a fifth lightning arrester adding unit, a sixth lightning arrester adding unit, and a seventh lightning arrester adding unit that are electrically connected in sequence; the first lightning arrester adding unit is electrically connected to the sixth blade assembly lightning strike simulation unit, and the seventh lightning arrester adding unit is electrically connected to the lightning arrester iteration module 6.

[0102] Among them, the first lightning arrester adding unit is used to select at least one random lightning strike point among all random lightning strike points and define it as the center of the initial cluster; the second lightning arrester adding unit is used to respectively obtain the Euclidean distance between each random lightning strike point and all initial cluster centers, and assign each random lightning strike point to the initial cluster with the closest Euclidean distance; the third lightning arrester adding unit is used to recalculate the center of the current initial cluster based on all random lightning strike points in the current initial cluster after the assignment; the fourth lightning arrester adding unit is used to repeatedly execute the second lightning arrester adding unit to the third lightning arrester adding unit to iterate the centers of all initial clusters; the fifth lightning arrester adding unit is used to end the iteration when the distance between the centers of all initial clusters in the most recent iteration and the centers of all initial clusters in the previous iteration is less than or equal to the preset distance threshold; the sixth lightning arrester adding unit is used to obtain the centers of all initial clusters after the iteration ends and define them as the centers of all regions; the seventh lightning arrester adding unit is used to add a lightning arrester at the center of each region respectively.

[0103] Further, the lightning arrester optimization module 8 specifically includes a first lightning arrester optimization unit, a second lightning arrester optimization unit, a third lightning arrester optimization unit, a fourth lightning arrester optimization unit, a fifth lightning arrester optimization unit, a sixth lightning arrester optimization unit, and a seventh lightning arrester optimization unit that are electrically connected in sequence; the first lightning arrester optimization unit is electrically connected to the iteration result condition judgment module 7, and the seventh lightning arrester optimization unit is electrically connected to the lightning arrester layout module 9.

[0104] Among them, the first lightning arrester optimization unit is used to take the surface of the blade assembly as the iteration range, redundantly add a number of random solutions on the surface of the blade assembly, and each lightning arrester corresponds to at least one random solution; the second lightning arrester optimization unit is used to define the optimization result of all random solutions as that the blade assembly no longer receives lightning strikes and the installation quantity reaches the minimum value; the third lightning arrester optimization unit is used to initialize the position of each random solution and update the current position and current speed of each random solution once based on a single discharge simulation; the fourth lightning arrester optimization unit is used to obtain the lightning strike situation of the blade assembly once based on each update; the fifth lightning arrester optimization unit is used to reduce one random solution if the blade assembly no longer receives lightning strikes; the sixth lightning arrester optimization unit is used to repeatedly execute the third lightning arrester optimization unit to the fifth lightning arrester optimization unit until the number of all random solutions reaches the minimum value and the iteration ends; the seventh lightning arrester optimization unit is used to obtain the positions and quantities of all random solutions after iteration, which are the installation positions and installation quantities of all lightning arresters.

[0105] Further, the lightning arrester layout system includes a safety monitoring module electrically connected to the lightning arrester layout module 9, and this module is used to send the above digital model, the installation positions after iteration of all lightning arresters, and the installation quantities after iteration to an external visual monitoring terminal.

[0106] It should be noted that this embodiment is a device embodiment based on the above method embodiment. For additional content such as the preference, expansion, limitation, and example illustration of this embodiment, refer to the above method embodiment, and this embodiment will not be elaborated further.

[0107] In this embodiment, point cloud data of a wind turbine is obtained through remote sensing scanning, and a digital model of the wind turbine is constructed based on the point cloud data. The digital model includes a blade assembly. A digital surface model of a preset area is obtained, and the digital model is input into the digital surface model to form a simulation environment. The simulation environment is input into a preset simulation software, and a number of real lightning meteorological data are added to the simulation environment through the preset simulation software. The preset simulation software simulates a number of discharges based on all the real lightning meteorological data, and calculates the lightning strike times of the blade assembly through a preset leader model. The area in the blade assembly where the lightning strike times exceed a preset number threshold is obtained, and a lightning arrester is added at the center of the area. The area where the lightning arrester has been installed is excluded, and the above two steps are repeatedly executed until the installation quantity of the lightning arrester reaches a preset quantity threshold, or the blade assembly no longer receives lightning strikes. It is judged whether the iteration stop condition of the above steps is that the installation quantity of the lightning arrester reaches the preset quantity threshold or the blade assembly no longer receives lightning strikes. If it is that the installation quantity of the lightning arrester reaches the preset quantity threshold, then with the surface of the blade assembly as the iteration range, the installation positions and installation quantities of all the lightning arresters are iterated through global optimization until the blade assembly no longer receives lightning strikes and the installation quantity reaches the minimum value. The iteration-installed positions and iteration-installed quantities of all the lightning arresters are obtained and sent to an external layout terminal. This embodiment considers the lightning arrester layout of wind turbines of different models and styles, enabling this embodiment to adapt to all wind turbines including three-blade ones (such as multi-blade, spiral blade, other special-shaped blades, etc.). The lightning strike simulation is carried out through the real lightning meteorological data obtained. The next lightning strike position is updated by continuously removing the lightning strike positions obtained in the previous iteration. The latest position of the lightning strike point can be dynamically adjusted according to the lightning strike times calculated for the current time of the blade, without the need to judge through prior experience. Finally, through global optimization, the minimum quantity of the lightning arrester is further reduced, which not only prevents redundant layout of the lightning arrester, but also can reduce the layout cost when ensuring comprehensive lightning strike and reduce the influence of the lightning arrester on the dynamic balance of the blade.

[0108] Figure 3 It is a schematic structural diagram of an electronic device according to an embodiment of the present application. As Figure 3 shown, the electronic device 10 includes a processor 101 and a memory 102 coupled to the processor 101.

[0109] The memory 102 stores program instructions for implementing a method for arranging lightning arresters on blades of a high-altitude wind turbine according to any one of the above embodiments.

[0110] The processor 101 is configured to execute the program instructions stored in the memory 102 to arrange lightning arresters on blades of a high-altitude wind turbine.

[0111] Among them, the processor 101 can also be referred to as a CPU (Central Processing Unit). The processor 101 may be an integrated circuit chip with signal processing capabilities. The processor 101 can also be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc.

[0112] Furthermore, Figure 4 is a schematic structural diagram of a storage medium according to an embodiment of the present application. Refer to Figure 4 , the storage medium 11 of the embodiment of the present application stores program instructions 111 that can implement all of the above methods. Among them, the program instructions 111 can be stored in the above storage medium in the form of a software product, including several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to execute all or part of the steps of the methods described in various embodiments of the present application. The foregoing storage medium includes: various media that can store program codes such as USB flash drives, mobile hard disks, read-only memories (ROMs, Read-Only Memories), random access memories (RAMs, Random Access Memories), magnetic disks, or optical discs, or terminal devices such as computers, servers, mobile phones, and tablets.

[0113] In several embodiments provided by the present application, it should be understood that the disclosed systems, systems, and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative. For example, the division of units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces. The indirect couplings or communication connections of systems or units can be in electrical, mechanical, or other forms.

[0114] In addition, each functional unit in various embodiments of the present application may be integrated into one processing unit, may exist separately as individual physical units, or two or more units may be integrated into one unit. The above-mentioned integrated units may be implemented in the form of hardware or in the form of software functional units. The above is only the implementation manner of the present application, and does not limit the patent scope of the present application. Any equivalent structural or equivalent process transformation made by using the content of the specification and drawings of the present application, or directly or indirectly applied in other related technical fields, shall be equally included in the patent protection scope of the present application.

Claims

1. A method for arranging a lightning arrester on a blade of a high-altitude wind turbine, the blade of the high-altitude wind turbine being applied to a wind turbine in a preset area, the wind turbine having a blade assembly driven by external wind energy, characterized in that, The lightning arrester layout method includes: Step S1, obtaining the point cloud data of the wind turbine through remote sensing scanning, and constructing a digital model of the wind turbine based on the point cloud data, where the digital model includes the blade assembly; Step S2, obtaining the digital surface model of the preset area, and inputting the digital model into the digital surface model to form a simulation environment; Step S3, inputting the simulation environment into a preset simulation software, and adding a number of real lightning meteorological data in the simulation environment through the preset simulation software; Step S4, simulating a number of discharges through the preset simulation software based on all real lightning meteorological data, and calculating the lightning strike times of the blade assembly through a preset leader model; Step S5, obtaining the area where the lightning strike times in the blade assembly exceed the preset number threshold, and adding a lightning arrester at the center of the area; Step S6, excluding the area where the lightning arrester has been installed, and repeating steps S4 to S5 until the installation quantity of the lightning arrester reaches the preset quantity threshold, or the blade assembly no longer receives lightning strikes; Step S7, determining whether the iteration stop condition in step S6 is that the installation quantity of the lightning arrester reaches the preset quantity threshold, or the blade assembly no longer receives lightning strikes. If it is that the installation quantity of the lightning arrester reaches the preset quantity threshold, then execute step S8; Step S8, taking the surface of the blade assembly as the iteration range, and globally optimizing and iterating the installation positions and installation quantities of all lightning arresters until the blade assembly no longer receives lightning strikes and the installation quantity reaches the minimum value; Step S9, obtaining the iterated installation positions and iterated installation quantities of all lightning arresters, and sending them to an external layout terminal.

2. The lightning arrester layout method according to claim 1, characterized in that Step S7, determining whether the iteration stop condition in step S6 is that the installation quantity of the lightning arrester reaches the preset quantity threshold, or the blade assembly no longer receives lightning strikes. After that, it includes: Step S10, if the iteration stop condition is that the blade assembly no longer receives lightning strikes, then execute step S20; Step S20, obtaining the spatial coordinates of all lightning arresters and the lightning strike surface orientations of all lightning arresters based on the preset simulation software; Step S30, integrating the spatial coordinates of the current lightning arrester and the lightning strike surface orientation of the current lightning arrester into the absolute installation position of the current lightning arrester; Step S40, respectively obtaining the Euclidean distances of each lightning arrester based on at least two non - collinear edges of the blade assembly; Step S50, integrating all the Euclidean distances of the current lightning arrester and the lightning strike surface orientation of the current lightning arrester into the relative installation position of the current lightning arrester; Step S60, packaging the absolute installation position and the relative installation position of the current lightning arrester into the installation data packet of the current lightning arrester; Step S70, sending the installation data packets of all lightning arresters to an external layout terminal.

3. The method for arranging a lightning arrester according to claim 2, wherein Step S9, obtaining the iterated installation positions and iterated installation quantities of all lightning arresters, and sending them to an external layout terminal. After that, it includes: Step S100: Taking all the installation positions after iteration as the execution entity, repeat Steps S20 to S50 to obtain the absolute installation position and relative installation position of the lightning arrester after the current iteration. Step S200: Package the absolute installation position and relative installation position of the lightning arrester after the current iteration into the installation data packet after iteration of the current lightning arrester. Step S300: Send the installation data packets after iteration of all lightning arresters to the external layout end.

4. The method for arranging a lightning arrester according to claim 1, wherein Step S4: Based on all the real lightning meteorological data, simulate several discharges through the preset simulation software, and calculate the lightning strike times of the blade assembly through the preset leader model, including: Step S41: Define the blade assembly as the lightning strike area, and define several random lightning strike points in the lightning strike area. Step S42: Calculate the charge density of the current random lightning strike point based on a real lightning meteorological data through the downward leader charge equation. Step S43: Define the upward leader length equation based on the current random lightning strike point. Step S44: Substitute the charge density into the upward leader length equation to calculate the upward leader length of the current random lightning strike point. Step S45: Calculate the lightning strike times of the current random lightning strike point based on the upward leader length. Step S46: Calculate the average lightning strike times of the current random lightning strike point by taking the arithmetic mean of all the lightning strike times of all the real lightning meteorological data.

5. The method for arranging a lightning arrester according to claim 1, wherein Step S5: Obtain the area in the blade assembly where the lightning strike times exceed the preset number threshold, and add a lightning arrester at the center of the area, including: Step S51: Select at least one random lightning strike point from all the random lightning strike points and define it as the center of the initial cluster. Step S52: Respectively obtain the Euclidean distance between each random lightning strike point and all the centers of the initial clusters, and assign each random lightning strike point to the initial cluster with the closest Euclidean distance. Step S53: After the assignment, recalculate the center of the current initial cluster based on all the random lightning strike points in the current initial cluster. Step S54: Repeat Steps S52 to S53 to iterate the centers of all the initial clusters. Step S55: When the distance between the centers of all the initial clusters in the most recent iteration and the centers of all the initial clusters in the previous iteration is less than or equal to the preset distance threshold, the iteration ends. Step S56: Obtain the centers of all the initial clusters after the iteration ends and define them as the centers of all the areas. Step S57: Add a lightning arrester at the center of each area respectively.

6. The method for arranging a lightning arrester according to claim 1, wherein Step S8: Taking the surface of the blade assembly as the iteration range, globally optimize and iterate the installation positions and installation quantities of all the lightning arresters until the blade assembly no longer receives lightning strikes and the installation quantity reaches the minimum value, including: Step S81: Taking the surface of the blade assembly as the iteration range, redundantly add several random solutions on the surface of the blade assembly, and each lightning arrester corresponds to at least one random solution. Step S82: Define the optimization result of all the random solutions as that the blade assembly no longer receives lightning strikes and the installation quantity reaches the minimum value. Step S83: Initialize the positions of each random solution, and update the current position and current velocity of each random solution once based on a single discharge simulation. Step S84: Obtain the lightning strike situation of the blade assembly once based on each update. Step S85: If the blade assembly is no longer struck by lightning, reduce one random solution. Step S86: Repeat Steps S83 to S85 until the number of all random solutions reaches the minimum value, and the iteration ends. Step S87: Obtain the positions and quantities of all random solutions after iteration, which are the installation positions and installation quantities of all lightning arresters.

7. The method for arranging a lightning arrester according to claim 1, wherein Step S9: Obtain the installation positions and installation quantities of all lightning arresters after iteration and send them to the external layout terminal. After that, it includes: Step S1000: Send the digital model, the installation positions and installation quantities of all lightning arresters after iteration to the external visual monitoring terminal.

8. A lightning arrester arrangement system for a blade of a high-altitude wind turbine, the lightning arrester arrangement system being applied to the lightning arrester arrangement method according to any one of claims 1 to 7, characterized in that, The lightning arrester layout system includes: A wind turbine digital model construction module, which is used to obtain the point cloud data of the wind turbine through remote sensing scanning, and construct the digital model of the wind turbine based on the point cloud data. The digital model includes the blade assembly. A simulation environment generation module, which is used to obtain the digital surface model of the preset area and input the digital model into the digital surface model to form a simulation environment. A lightning meteorological data adding module, which is used to input the simulation environment into a preset simulation software, and add a number of real lightning meteorological data to the simulation environment through the preset simulation software. A blade assembly lightning strike simulation module, which is used to simulate a number of discharges based on all real lightning meteorological data through the preset simulation software, and calculate the number of lightning strikes of the blade assembly through a preset leader model. A lightning arrester adding module, which is used to obtain the area where the number of lightning strikes in the blade assembly exceeds a preset number threshold and add a lightning arrester at the center of the area. A lightning arrester iteration module, which is used to exclude the area where the lightning arrester has been installed, and repeat the execution of the blade assembly lightning strike simulation module to the lightning arrester adding module until the installation quantity of the lightning arrester reaches a preset quantity threshold, or the blade assembly is no longer struck by lightning. An iteration result condition judgment module, which is used to judge whether the iteration stop condition of the lightning arrester iteration module is that the installation quantity of the lightning arrester reaches a preset quantity threshold, or the blade assembly is no longer struck by lightning. A lightning arrester optimization module, which is used to, if the installation quantity of the lightning arrester reaches a preset quantity threshold, take the surface of the blade assembly as the iteration range, and globally optimize and iterate the installation positions and installation quantities of all lightning arresters until the blade assembly is no longer struck by lightning and the installation quantity reaches the minimum value. A lightning arrester layout module, which is used to obtain the installation positions and installation quantities of all lightning arresters after iteration and send them to the external layout terminal.

9. An electronic device, characterized in that, It includes a processor and a memory coupled to the processor, and the memory stores program instructions executable by the processor; when the processor executes the program instructions stored in the memory, it implements the method for arranging a lightning arrester on a high-altitude wind turbine blade according to any one of claims 1 to 7.

10. A storage medium, characterized in that, The storage medium stores program instructions, and when the program instructions are executed by a processor, they can implement the method for arranging a lightning arrester on a high-altitude wind turbine blade according to any one of claims 1 to 7.

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