A lightning risk assessment method considering mutual shielding between wind turbines

Abstract

This invention proposes a lightning strike risk assessment method considering mutual shielding between wind turbine units, comprising the following steps: acquiring topographic elevation data, basic parameters, and geographical location information of the target wind farm, and calculating the dynamic strike distance parameters of the wind turbine units; determining the target lightning strike area based on lightning warning information, and constructing a three-dimensional strike distance spherical model corresponding to each wind turbine based on the basic parameters and dynamic strike distance parameters of the wind turbine units in the target lightning strike area; calculating the equivalent lightning interception area after mutual shielding between wind turbine units using a grid sweeping method, combined with the three-dimensional strike distance spherical model; calculating the estimated number of lightning strikes for each wind turbine and classifying the risk level based on the lightning prediction frequency and the equivalent lightning interception area, and generating a protection decision; this method can accurately quantify the mutual shielding effect between multiple wind turbines due to spatial location and dynamic operating status, improving the accuracy and reliability of the overall lightning strike risk assessment of the wind farm.

Description

Technical Field

[0001] This invention relates to the field of lightning protection technology for wind farms, and in particular to a method for assessing lightning strike risk that takes into account the mutual shielding between wind turbine units. Background Technology

[0002] With the rapid growth of global wind power installed capacity, lightning protection of wind turbines, as tall structures, has become a key technology for ensuring the safe operation of wind farms. In existing technologies, lightning protection mainly relies on the synergistic effect of lightning early warning systems and wind turbine lightning protection devices: lightning monitoring networks detect cloud-to-ground lightning activity in real time and generate a lightning probability distribution map for the next 0-6 hours in conjunction with numerical weather prediction models, providing short-term early warning information for wind farms; at the same time, wind turbines are usually equipped with external and internal lightning protection systems to intercept direct lightning strikes and suppress lightning wave intrusion.

[0003] Most existing methods are based on models of a single isolated wind turbine for lightning strike risk calculation, without fully considering the mutual shielding effect caused by factors such as blade rotation and spatial position when multiple wind turbines exist simultaneously in a wind farm. In actual wind farms, high-mounted turbines may provide a certain degree of lightning shielding for downwind turbines, while rotating blades dynamically change the local electric field distribution, affecting lightning attraction. Ignoring these complex spatial coupling effects leads to a large deviation between the assessment results and the actual situation, reducing the accuracy of lightning protection risk assessment for wind farms. Summary of the Invention

[0004] In view of this, the present invention proposes a lightning strike risk assessment method that considers the mutual shielding between wind turbine units. This method can accurately quantify the mutual shielding effect between multiple wind turbine units due to their spatial location and dynamic operating status, thereby improving the accuracy and reliability of the overall lightning strike risk assessment of the wind farm.

[0005] The technical solution of the present invention is implemented as follows: In a first aspect, the present invention provides a method for assessing lightning strike risk considering mutual shielding between wind turbine units, comprising the following steps: S1: Obtain the topographic elevation data of the target wind farm, the basic parameters of the wind turbine, and the geographical location information, and calculate the dynamic striking distance parameters of the wind turbine. S2, Based on lightning warning information, determine the target lightning strike area, and construct a three-dimensional strike distance spherical model for each wind turbine according to the basic parameters of the wind turbine in the target lightning strike area and the dynamic strike distance parameters of the wind turbine. S3, combined with a three-dimensional strike distance spherical model, calculates the equivalent lightning interception area after mutual shielding between wind turbine units using the grid sweeping method; S4 calculates the estimated number of lightning strikes for each wind turbine and classifies the risk level based on the predicted frequency of lightning strikes and the equivalent lightning interception area, and generates protection decisions.

[0006] Based on the above technical solutions, preferably, step S1 includes the following sub-steps: S11, acquire the digital elevation model data of the target wind farm, and convert the digital elevation model data into a grid matrix with a predetermined resolution; S12, acquire the basic parameters and real-time status parameters of each wind turbine in the target wind farm. The basic parameters include hub height, blade length, ground distance, and geographic coordinates of the hub center. The real-time status parameters include wind turbine operating status, blade angle, and rotational speed. S13, a three-dimensional terrain surface is generated based on the terrain elevation data in the grid matrix, and the geographical location information and hub height of each wind turbine are mapped to the corresponding position on the three-dimensional terrain surface to construct a three-dimensional wind farm model; S14. Based on the real-time status parameters of the wind turbine, calculate the basic strike distance value for the current operating state, and correct the basic strike distance value based on the waveform parameters and polarity of the lightning current to obtain the dynamic strike distance parameters for the corresponding wind turbine operating state.

[0007] Based on the above technical solutions, preferably, step S14 includes the following sub-steps: S141, When the wind turbine is in a stationary state, the foundation strike distance value of the wind turbine in a stationary state is calculated based on the hub height of the wind turbine and the amplitude of the lightning current. S142, When the fan is in a rotating state, the basic blow distance value in the rotating state of the fan is calculated based on the blade angle, rotation speed and fan model parameters. S143, Based on the lightning current waveform parameters and polarity, a correction coefficient is determined. The basic strike distance value is multiplied by the correction coefficient to obtain the dynamic strike distance parameters under the corresponding wind turbine operating state. The lightning current waveform parameters include wavefront time, half-wave time, lightning current amplitude, and waveform type.

[0008] Based on the above technical solutions, preferably, the construction of the three-dimensional blow distance spherical model corresponding to each wind turbine in step S2 includes: The center of the wind turbine hub of each wind turbine unit is taken as the center of the sphere; When the wind turbine is in a stationary state, a three-dimensional spherical model of the wind turbine's impact distance is constructed with the dynamic impact distance parameter of the wind turbine in a stationary state as the radius. When the wind turbine is in a rotating state, a three-dimensional spherical model of the wind turbine's impact distance is constructed with the sum of the blade length of the corresponding wind turbine and the dynamic impact distance parameter in the rotating state as the radius.

[0009] Based on the above technical solutions, preferably, step S3, which involves determining the target lightning strike area based on lightning early warning information and calculating the equivalent lightning interception area after mutual shielding between wind turbine units using a grid sweeping method, includes the following sub-steps: S31, divide the ground projection area corresponding to the target lightning strike area into a fine grid; S32, traverse all fine grids, for each grid's preset vertex, simulate lightning leaders to draw lightning rays vertically upwards from each vertex, calculate the intersection of the lightning rays with the strike distance spheres of all wind turbines, if an intersection exists, select the intersection with the highest elevation, and only if the intersection with the highest elevation is greater than the ground strike distance, then the vertex is assigned to the corresponding wind turbine; otherwise, it is determined to belong to the ground. S33, based on the attribution determination results of all fine mesh vertices, if no less than three vertices belong to the same wind turbine, then the current fine mesh is determined as the valid lightning protection mesh of the corresponding wind turbine. S34, count the number of effective lightning protection grids for each wind turbine, and multiply by the square of the side length of the fine grid to obtain the equivalent interception area of ​​each wind turbine; S35, For multiple discrete lightning current amplitudes within the preset lightning current amplitude range, repeat steps S31 to S34 to obtain the equivalent interception area sequence of each wind turbine under different lightning current amplitudes. S36. Based on the probability density distribution of lightning current amplitude, the equivalent interception area sequence is weighted and summed to obtain the comprehensive equivalent interception area of ​​each wind turbine.

[0010] Based on the above technical solutions, preferably, the step S31 of dividing the ground projection area corresponding to the target lightning strike area into a fine grid includes the following sub-steps: S311, divide the target lightning strike area into several pre-divided evaluation sub-regions; S312, For each evaluation sub-region, calculate the wind turbine distribution density and topographic relief. The wind turbine distribution density is the ratio of the number of wind turbines in the evaluation sub-region to the area of ​​the evaluation sub-region, and the topographic relief is the standard deviation of the elevation data grid points of all topographic elevation data in the evaluation sub-region. S313, normalize the wind turbine distribution density and terrain undulation respectively to obtain the normalized wind turbine distribution density and terrain undulation; S314, Calculate the grid size for each evaluation sub-region based on the normalized wind turbine distribution density and terrain undulation, using the following expression: ; In the formula, L min The minimum boundary value of the preset mesh size. L maxThe preset maximum size boundary value, D norm The normalized wind turbine distribution density, R norm This represents the normalized topographic relief. w 1 represents the weighting coefficient for the normalized wind turbine distribution density. w 2 represents the weighting coefficient for the normalized terrain relief. S315: Based on the grid size of each evaluation sub-region, perform grid division within the ground projection range of the target lightning strike area to generate the final fine grid.

[0011] Based on the above technical solutions, preferably, the step S4 of calculating the estimated number of lightning strikes for each wind turbine based on the lightning prediction frequency and the equivalent lightning interception area includes: calculating the estimated number of lightning strikes for each wind turbine by multiplying the lightning prediction frequency in the future time period by the comprehensive equivalent interception area of ​​the corresponding wind turbine and the duration of the future time period.

[0012] Based on the above technical solutions, preferably, the risk level classification and protection decision generation in step S4 includes: When the expected number of lightning strikes on a wind turbine is less than the first preset reference value for the number of lightning strikes, it is classified as a low-risk level. When the expected number of lightning strikes on a wind turbine is greater than or equal to the first preset reference value for the number of lightning strikes, but less than the second preset reference value for the number of lightning strikes, it is classified as a medium-risk level. When the expected number of lightning strikes on a wind turbine is greater than or equal to the second preset reference value for the number of lightning strikes, but less than the third preset reference value for the number of lightning strikes, it is classified as a high-risk level. When the expected number of lightning strikes on a wind turbine is greater than or equal to the third preset reference value for the number of lightning strikes, it is classified as an extremely high risk level. If all wind turbines are classified as low-risk or medium-risk, no preventative measures will be taken. If the number of wind turbines with a risk level of high risk or very high risk is less than half the total number of wind turbines on the corresponding collector line, then the corresponding risky wind turbine will be shut down. If the number of wind turbines with a risk level of high risk or very high risk is greater than half the total number of wind turbines on the corresponding collector line, then all wind turbines on the corresponding collector line shall be shut down. If the number of wind turbines with a risk level of high risk or extremely high risk in a wind farm exceeds half the total number of wind turbines, then all wind turbines in the entire wind farm will be shut down.

[0013] Secondly, the present invention also provides a lightning strike risk assessment system that considers mutual shielding between wind turbine units, implemented using a lightning strike risk assessment method that considers mutual shielding between wind turbine units, including: The data acquisition module is used to acquire topographic elevation data of the target wind farm, basic parameters of the wind turbine, and geographical location information, and to calculate the dynamic striking distance parameters of the wind turbine. The spherical modeling module is used to determine the target lightning strike area based on lightning warning information, and to construct a three-dimensional spherical model of the strike distance for each wind turbine based on the basic parameters of the wind turbine in the target lightning strike area and the dynamic strike distance parameters of the wind turbine. The grid calculation module is used to calculate the equivalent lightning interception area after mutual shielding between wind turbine units by combining a three-dimensional strike distance spherical model and using a grid sweeping method. The risk assessment module is used to calculate the estimated number of lightning strikes for each wind turbine and classify the risk level based on the predicted frequency of lightning strikes and the equivalent lightning interception area, and generate protection decisions.

[0014] Thirdly, the present invention also provides a computer-readable storage medium storing a lightning strike risk assessment method program that considers mutual shielding between wind turbine units, wherein the lightning strike risk assessment method program that considers mutual shielding between wind turbine units is executed to implement the lightning strike risk assessment method that considers mutual shielding between wind turbine units.

[0015] The lightning strike risk assessment method of the present invention, which considers mutual shielding between wind turbine units, has the following advantages over the prior art: (1) By dynamically correcting the wind turbine strike distance parameters and constructing a three-dimensional strike distance spherical model, combined with adaptive mesh generation and mesh sweeping algorithm, the equivalent interception area after shielding was quantified; finally, by integrating lightning early warning and probability statistics, a graded protection decision was generated, which accurately quantified the mutual shielding effect between multiple wind turbines due to spatial location and dynamic operating status, thus improving the accuracy and reliability of the overall lightning strike risk assessment of the wind farm. (2) By acquiring the operating status, blade angle and speed parameters, and establishing differentiated strike distance calculation models for the stationary and rotating states of the wind turbine, and introducing correction coefficients based on the lightning current waveform and polarity, dynamic strike distance parameters under the corresponding wind turbine operating state are obtained. The coupling effect between the actual operating conditions of the wind turbine and the physical characteristics of the lightning current is considered, making the strike distance calculation more accurate and improving the accuracy and reliability of subsequent lightning shielding effect analysis and risk level assessment. (3) By adaptively adjusting the mesh density, the mesh is automatically densified in areas with dense wind turbines or complex terrain to ensure analysis accuracy, while the mesh is appropriately widened in flat and open areas to improve calculation speed. This reduces the overall calculation burden while ensuring the accuracy of assessment in key areas, and improves the efficiency and reliability of risk assessment. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 A flowchart of the lightning strike risk assessment method of the present invention, which takes into account mutual shielding between wind turbine units; Figure 2 This is a schematic diagram illustrating the calculation of the equivalent cut-off area of ​​the wind turbine in the lightning strike risk assessment method considering mutual shielding between wind turbine units according to the present invention. Figure 3 The flowchart shows the calculation process of the equivalent interception area for the lightning strike risk assessment method considering mutual shielding between wind turbine units, as described in this invention. Detailed Implementation

[0018] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0019] like Figure 1-3 As shown, in a first aspect, the present invention provides a lightning strike risk assessment method considering mutual shielding between wind turbine units, comprising the following steps: S1: Obtain the topographic elevation data of the target wind farm, the basic parameters of the wind turbine, and the geographical location information, and calculate the dynamic striking distance parameters of the wind turbine.

[0020] This step prepares complete spatial environment data and core electrical parameters for risk assessment. Its input is raw multi-source data, and its output is a structured three-dimensional wind farm basic model and dynamic strike distance parameters of each wind turbine.

[0021] Step S1 includes the following sub-steps: S11, acquire the digital elevation model data of the target wind farm, and convert the digital elevation model data into a grid matrix with a predetermined resolution; It should be noted that the Digital Elevation Model (DEM) data of the target wind farm is obtained through a Geographic Information System (GIS) or from an authoritative data platform. The DEM data is usually in raster format, with each raster cell recording an altitude value. To facilitate subsequent calculations, the obtained DEM data is uniformly converted into a regular grid matrix. In this embodiment, a spatial resolution of 30 meters is used, that is, each grid point represents a 30-meter × 30-meter area on the ground, mapping the entire target wind farm area into a two-dimensional matrix. At the same time, the geographic coordinate range of this matrix is ​​recorded to match the coordinates with the wind turbine locations.

[0022] S12, acquire the basic parameters and real-time status parameters of each wind turbine in the target wind farm. The basic parameters include hub height, blade length, ground distance, and geographic coordinates of the hub center. The real-time status parameters include wind turbine operating status, blade angle, and rotational speed. It should be noted that by connecting to the wind farm's monitoring and data acquisition SCADA system, the operating data of each wind turbine can be read in real time or acquired periodically. All parameters are organized and stored according to the wind turbine number to form a wind turbine parameter list.

[0023] S13, a three-dimensional terrain surface is generated based on the terrain elevation data in the grid matrix, and the geographical location information and hub height of each wind turbine are mapped to the corresponding position on the three-dimensional terrain surface to construct a three-dimensional wind farm model; It should be noted that, based on the grid matrix and using a 3D graphics library, the planar coordinates and height of each grid point are rendered to generate a continuous 3D terrain surface. The latitude and longitude coordinates of each wind turbine are converted into the same planar coordinate system as the DEM data through map projection. Based on the interpolation of the location in the DEM grid matrix, the ground elevation at the wind turbine foundation is obtained. The height in the 3D spatial coordinates of the wind turbine is the superposition of the ground elevation at the wind turbine foundation and the hub height. The calculated 3D coordinate points of the wind turbine are drawn on the generated 3D terrain surface with specific identifiers, thus completing the construction of a 3D wind farm foundation model that includes the terrain and the spatial location of the wind turbines.

[0024] S14. Based on the real-time status parameters of the wind turbine, calculate the basic strike distance value for the current operating state, and correct the basic strike distance value based on the waveform parameters and polarity of the lightning current to obtain the dynamic strike distance parameters for the corresponding wind turbine operating state.

[0025] Step S14 includes the following sub-steps: S141, When the wind turbine is in a stationary state, the foundation strike distance value of the wind turbine in a stationary state is calculated based on the hub height of the wind turbine and the lightning current amplitude. The expression is: ; In the formula, This is a coefficient for the wheel hub height.H h For wheel hub height, b This is a coefficient for the lightning current amplitude used in the current assessment. I p This is the lightning current amplitude used in the current assessment.

[0026] S142, When the fan is in a rotating state, the basic striking distance value under the rotating state is calculated based on the blade angle, rotational speed, and fan model parameters. The expression is: ; In the formula, c, α, β, φ are the wind turbine model parameters used to characterize the influence of the rotating blades on the electric field distortion, and are determined through joint simulation of computational fluid dynamics and electromagnetic fields. θ ω is the blade angle, and ω is the fan speed; S143, Based on the lightning current waveform parameters and polarity, a correction coefficient is determined. The basic strike distance value is multiplied by the correction coefficient to obtain the dynamic strike distance parameters under the corresponding wind turbine operating state. The lightning current waveform parameters include wavefront time, half-wave time, lightning current amplitude, and waveform type.

[0027] It should be noted that a strike distance correction database for different lightning current characteristics is established beforehand through high-precision electromagnetic transient simulation. For example, simulation results show that for the same 100kA lightning current, the strike distance under a 10 / 350μs positive polarity waveform may be 15% larger than that under an 8 / 20μs negative polarity waveform. Therefore, the corresponding correction coefficients can be set to 1.15 and 0.85 respectively. Finally, the dynamic strike distance parameter is calculated, and the expression is: D d =d b *k w ; In the formula, D d This corresponds to the dynamic strike distance parameters under the current operating conditions of the wind turbine. d b This is the base stroke distance value corresponding to the wind turbine's operating state. k w This is a correction factor.

[0028] In this step, dynamic parameters such as operating status, blade angle, and rotation speed are obtained by real-time access to the wind turbine's SCADA system. Different strike distance calculation models are established for the wind turbine's static and rotating states. At the same time, correction coefficients based on lightning current waveform and polarity are introduced to obtain dynamic strike distance parameters for the corresponding wind turbine operating states. This method considers the coupling effect between the actual operating conditions of the wind turbine and the physical characteristics of lightning current, making the strike distance calculation more accurate and improving the accuracy and reliability of subsequent lightning strike shielding effect analysis and risk level assessment.

[0029] S2. Based on lightning warning information, determine the target lightning strike area. Based on the basic parameters of the wind turbines in the target lightning strike area and the dynamic strike distance parameters of the wind turbines, construct a three-dimensional strike distance spherical model corresponding to each wind turbine.

[0030] Step S2 includes: The center of the wind turbine hub of each wind turbine unit is taken as the center of the sphere; When the wind turbine is in a stationary state, a three-dimensional spherical model of the wind turbine's impact distance is constructed with the dynamic impact distance parameter of the wind turbine in a stationary state as the radius. When the wind turbine is in a rotating state, a three-dimensional spherical model of the wind turbine's impact distance is constructed with the sum of the blade length of the corresponding wind turbine and the dynamic impact distance parameter in the rotating state as the radius.

[0031] It should be noted that determining the target lightning strike area based on lightning warning information includes receiving short-term forecast information from a lightning monitoring network or early warning system, which contains a probability distribution map of possible lightning strikes within a certain future period; extracting all grids whose lightning strike risk exceeds a preset lightning strike probability threshold, merging these grids, and defining the geographical area covered by them as the target lightning strike area; using the center point of each wind turbine hub as the center of a sphere, with the sphere radius dynamically determined according to the real-time operating status of the wind turbine, when the wind turbine is stationary, the dynamic strike distance parameter in the stationary state is used as the radius to construct a three-dimensional strike distance spherical model of the corresponding wind turbine; when the wind turbine is rotating, the sum of the blade length of the corresponding wind turbine and the dynamic strike distance parameter in the rotating state is used as the radius to construct a three-dimensional strike distance spherical model of the corresponding wind turbine, satisfying the following on the three-dimensional strike distance sphere of the wind turbine: ( X - X i ) 2 +( Y - Y i ) 2 +( Z - Z i ) 2 =( R i ) 2 ; In the formula, ( X , Y , Z Let be the Cartesian coordinates of any point on the sphere. X i , Y i , Z i ) is the first iThe coordinates of the center of the spherical surface at the impact distance of the typhoon turbine generator. R i For the first i The radius of the spherical radius of the typhoon generator's strike distance.

[0032] It should be noted that by delineating the target lightning strike area based on lightning early warning information and dynamically combining it with the wind turbine operating status to construct a three-dimensional strike distance spherical model, a spatial quantitative assessment of lightning risk can be achieved. This characterizes the spatial geometric features of the lightning-attracting range of wind turbines under different conditions, providing data support for subsequent quantification of the mutual shielding effect between wind turbines.

[0033] S3, combined with a three-dimensional strike distance spherical model, calculates the equivalent lightning interception area after mutual shielding between wind turbine units using a grid sweeping method.

[0034] Step S3 includes the following sub-steps: S31, divide the ground projection area corresponding to the target lightning strike area into a fine grid; It should be noted that this sub-step divides the computational grid according to the wind turbine layout and terrain changes in the region, thereby improving the overall computational efficiency while ensuring the accuracy of key areas.

[0035] Step S31 includes the following sub-steps: S311, divide the target lightning strike area into several pre-divided evaluation sub-regions; S312, For each evaluation sub-region, calculate the wind turbine distribution density and topographic relief. The wind turbine distribution density is the ratio of the number of wind turbines in the evaluation sub-region to the area of ​​the evaluation sub-region, and the topographic relief is the standard deviation of the elevation data grid points of all topographic elevation data in the evaluation sub-region. S313, normalize the wind turbine distribution density and terrain undulation respectively to obtain the normalized wind turbine distribution density and terrain undulation; S314, Calculate the grid size for each evaluation sub-region based on the normalized wind turbine distribution density and terrain undulation, using the following expression: ; In the formula, L min The minimum boundary value of the preset mesh size. L max The preset maximum size boundary value, D norm The normalized wind turbine distribution density, R norm This represents the normalized topographic relief. w 1 represents the weighting coefficient for the normalized wind turbine distribution density. w 2 represents the weighting coefficient for the normalized topographic relief.

[0036] It should be noted that this formula ensures that smaller, finer grids are used in areas with dense wind turbines or complex terrain, while larger grids are used in open, flat areas, thus achieving adaptive allocation of computing resources.

[0037] S315: Based on the grid size of each evaluation sub-region, perform grid division within the ground projection range of the target lightning strike area to generate the final fine grid.

[0038] It should be noted that by establishing an adaptive grid partitioning algorithm based on wind turbine distribution density and terrain undulation, dynamic optimization of computing resources is achieved. In key risk areas with dense wind turbines or complex terrain, a finer grid is automatically adopted to ensure assessment accuracy, while a sparser grid is adopted in open and flat areas to improve computing efficiency. Thus, without sacrificing the accuracy of the analysis of key areas, the overall computational complexity is reduced and the accuracy of the final risk assessment results is improved.

[0039] S32, traverse all fine grids, for each grid's preset vertex, simulate lightning leaders to draw lightning rays vertically upwards from each vertex, calculate the intersection of the lightning rays with the strike distance spheres of all wind turbines, if an intersection exists, select the intersection with the highest elevation, and only if the intersection with the highest elevation is greater than the ground strike distance, then the vertex is assigned to the corresponding wind turbine; otherwise, it is determined to belong to the ground. It should be noted that, by traversing all four vertices of the fine mesh, a lightning-induced ray extending vertically upwards from each vertex is simulated, and the intersection points of this ray with the strike distance spheres of all wind turbines are calculated. For each wind turbine... i The ray parameter equations are substituted into the three-dimensional impact distance spherical model for solution; S33, based on the attribution determination results of all fine mesh vertices, if no less than three vertices belong to the same wind turbine, then the current fine mesh is determined as the valid lightning protection mesh of the corresponding wind turbine. It should be noted that if three or four of the four vertices of a grid belong to the same wind turbine, then the entire grid area is considered to be easily attracted by that wind turbine, and the grid is determined to be an effective lightning-receiving grid for the wind turbine. If the vertices are scattered, then the grid is considered to have uncertainty during the downward lightning process or is not completely dominated by a single wind turbine, and is not included in the effective area of ​​any wind turbine.

[0040] S34, count the number of effective lightning protection grids for each wind turbine, multiply by the square of the side length of the fine grid, and obtain the equivalent interception area of ​​each wind turbine, expressed as: ; In the formula, N k For the first k Number of effective lightning protection grids per fan Lgrid This is a fine-grained grid for calculating the side lengths of the sub-region containing this grid.

[0041] S35, For multiple discrete lightning current amplitudes within the preset lightning current amplitude range, repeat steps S31 to S34 to obtain the equivalent interception area sequence of each wind turbine under different lightning current amplitudes. S36. Based on the probability density distribution of lightning current amplitude, the equivalent interception area sequence is weighted and summed to obtain the comprehensive equivalent interception area of ​​each wind turbine, expressed as: ; In the formula, Δ I m The amplitude is segmented at intervals. A d ( k , I m ) is the first k The equivalent interception area of ​​each wind turbine, and the statistical probability density distribution of lightning current amplitude in the region.

[0042] This step dynamically optimizes the grid layout based on wind turbine density and terrain complexity, significantly improving overall computational efficiency while ensuring the analytical accuracy of core risk areas. Subsequently, by simulating lightning leader development and geometric intersection, the lightning strike attribution of each grid is accurately determined, realistically reproducing the spatial competition and shielding mechanisms in a multi-wind turbine environment. Finally, by comprehensively considering the exposure area under different lightning current intensities and weighting it according to probability, a risk assessment result that better conforms to the natural statistical characteristics of lightning is obtained, thus providing a reliable and detailed quantitative basis for differentiated lightning protection and operation scheduling of wind farms.

[0043] S4 calculates the estimated number of lightning strikes for each wind turbine and classifies the risk level based on the predicted frequency of lightning strikes and the equivalent lightning interception area, and generates protection decisions.

[0044] Step S4 includes: The estimated number of lightning strikes for each wind turbine is calculated by multiplying the predicted frequency of lightning strikes in the future time period by the comprehensive equivalent interception area of ​​the corresponding wind turbine and the duration of the future time period. The expression is as follows: ; In the formula, N g The predicted frequency of lightning activity in the future period is obtained from the lightning warning system; A d,综合 ( k (for fans) k The comprehensive equivalent interception area, Δ T The duration of the future time period to be assessed; The risk level classification and protection decision generation in step S4 include: When the expected number of lightning strikes on a wind turbine is less than the first preset reference value for the number of lightning strikes, it is classified as a low-risk level. When the expected number of lightning strikes on a wind turbine is greater than or equal to the first preset reference value for the number of lightning strikes, but less than the second preset reference value for the number of lightning strikes, it is classified as a medium-risk level. When the expected number of lightning strikes on a wind turbine is greater than or equal to the second preset reference value for the number of lightning strikes, but less than the third preset reference value for the number of lightning strikes, it is classified as a high-risk level. When the expected number of lightning strikes on a wind turbine is greater than or equal to the third preset reference value for the number of lightning strikes, it is classified as an extremely high risk level. If all wind turbines are classified as low-risk or medium-risk, no preventative measures will be taken. If the number of wind turbines with a risk level of high risk or very high risk is less than half the total number of wind turbines on the corresponding collector line, then the corresponding risky wind turbine will be shut down. If the number of wind turbines with a risk level of high risk or very high risk is greater than half the total number of wind turbines on the corresponding collector line, then all wind turbines on the corresponding collector line shall be shut down. If the number of wind turbines with a risk level of high risk or extremely high risk in a wind farm exceeds half the total number of wind turbines, then all wind turbines in the entire wind farm will be shut down.

[0045] It should be noted that if all wind turbines in the entire wind farm are classified as low-risk or medium-risk, the overall risk is considered controllable, and the wind farm will continue to operate normally. If one or more wind turbines reach a high-risk or extremely high-risk level, but the number of wind turbines at the same high-risk level on their respective collector lines does not exceed half of the total number of wind turbines on that line, the decision-making system will send an instruction to the wind farm control system to shut down only these specific high-risk wind turbines. If the number of wind turbines at a high-risk or extremely high-risk level on a certain collector line reaches or exceeds half of the total number of wind turbines on that line, the decision will be made to shut down all wind turbines on the entire collector line. This is because high-risk wind turbines are too concentrated, the local risk is already very high, and from the perspective of grid dispatch and on-site electrical operation, shutting down the entire line is safer and more convenient. If the number of wind turbines at a high-risk or extremely high-risk level in the wind farm exceeds half of the total number of wind turbines, then all wind turbines in the entire wind farm will be shut down.

[0046] It should be noted that by calculating the estimated number of lightning strikes for each wind turbine based on the predicted frequency of lightning strikes, the comprehensive equivalent interception area of ​​the wind turbine, and the duration of the future period, and classifying the risk level according to different expected lightning strike frequency ranges, targeted protection decisions can be made, thus achieving a scientific assessment and precise control of wind turbine lightning strike risks, ensuring the safety and efficiency of wind farm operation.

[0047] Secondly, the present invention also provides a lightning strike risk assessment system that considers mutual shielding between wind turbine units, implemented using a lightning strike risk assessment method that considers mutual shielding between wind turbine units, including: The data acquisition module is used to acquire topographic elevation data of the target wind farm, basic parameters of the wind turbine, and geographical location information, and to calculate the dynamic striking distance parameters of the wind turbine. The spherical modeling module is used to determine the target lightning strike area based on lightning warning information, and to construct a three-dimensional spherical model of the strike distance for each wind turbine based on the basic parameters of the wind turbine in the target lightning strike area and the dynamic strike distance parameters of the wind turbine. The grid calculation module is used to calculate the equivalent lightning interception area after mutual shielding between wind turbine units by combining a three-dimensional strike distance spherical model and using a grid sweeping method. The risk assessment module is used to calculate the estimated number of lightning strikes for each wind turbine and classify the risk level based on the predicted frequency of lightning strikes and the equivalent lightning interception area, and generate protection decisions.

[0048] It should be noted that this system corresponds to the above-mentioned lightning strike risk assessment method that considers mutual shielding between wind turbine units. All implementation methods in the above-mentioned method embodiments are applicable to the embodiments of this system and can achieve the same technical effect.

[0049] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0050] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working process of the system and modules described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0051] In the embodiments provided by this invention, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0052] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0053] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0054] If the aforementioned functions are implemented as 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 this invention, essentially, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0055] Furthermore, it should be noted that in the system and method of the present invention, it is obvious that the components or steps can be decomposed and / or recombined. These decompositions and / or recombinations should be considered equivalent solutions of the present invention. Moreover, the steps performing the above series of processes can naturally be executed in the order described, but are not necessarily required to be executed in chronological order; some steps can be executed in parallel or independently of each other. Those skilled in the art will understand that all or any step or component of the method and apparatus of the present invention can be implemented in any computing device (including processors, storage media, etc.) or network of computing devices, in hardware, firmware, software, or a combination thereof. This is something that those skilled in the art can achieve by using their basic programming skills after reading the description of the present invention.

[0056] Therefore, the object of the present invention can also be achieved by running a program or a set of programs on any computing system. The computing system can be a known general-purpose system. Therefore, the object of the present invention can also be achieved simply by providing a program product containing program code implementing the method or apparatus. That is, such a program product also constitutes the present invention, and the storage medium storing such a program product also constitutes the present invention. Obviously, the storage medium can be any known storage medium or any storage medium developed in the future. It should also be noted that in the apparatus and method of the present invention, it is obvious that the components or steps can be decomposed and / or recombined. These decompositions and / or recombinations should be considered equivalent to the present invention. Furthermore, the steps performing the above series of processes can naturally be performed in the order described, but are not necessarily required to be performed in chronological order. Some steps can be performed in parallel or independently of each other.

[0057] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for assessing lightning strike risk considering mutual shielding between wind turbine units, characterized in that, Includes the following steps: S1: Obtain the topographic elevation data of the target wind farm, the basic parameters of the wind turbine, and the geographical location information, and calculate the dynamic striking distance parameters of the wind turbine. S2, Based on lightning warning information, determine the target lightning strike area, and construct a three-dimensional strike distance spherical model for each wind turbine according to the basic parameters of the wind turbine in the target lightning strike area and the dynamic strike distance parameters of the wind turbine. S3, combined with a three-dimensional strike distance spherical model, calculates the equivalent lightning interception area after mutual shielding between wind turbine units using the grid sweeping method; S4 calculates the estimated number of lightning strikes for each wind turbine and classifies the risk level based on the predicted frequency of lightning strikes and the equivalent lightning interception area, and generates protection decisions.

2. The lightning strike risk assessment method considering mutual shielding between wind turbine units as described in claim 1, characterized in that, Step S1 includes the following sub-steps: S11, acquire the digital elevation model data of the target wind farm, and convert the digital elevation model data into a grid matrix with a predetermined resolution; S12, acquire the basic parameters and real-time status parameters of each wind turbine in the target wind farm. The basic parameters include hub height, blade length, ground distance, and geographic coordinates of the hub center. The real-time status parameters include wind turbine operating status, blade angle, and rotational speed. S13, a three-dimensional terrain surface is generated based on the terrain elevation data in the grid matrix, and the geographical location information and hub height of each wind turbine are mapped to the corresponding position on the three-dimensional terrain surface to construct a three-dimensional wind farm model; S14. Based on the real-time status parameters of the wind turbine, calculate the basic strike distance value for the current operating state, and correct the basic strike distance value based on the waveform parameters and polarity of the lightning current to obtain the dynamic strike distance parameters for the corresponding wind turbine operating state.

3. The lightning strike risk assessment method considering mutual shielding between wind turbine units as described in claim 2, characterized in that, Step S14 includes the following sub-steps: S141, When the wind turbine is in a stationary state, the foundation strike distance value of the wind turbine in a stationary state is calculated based on the hub height of the wind turbine and the amplitude of the lightning current. S142, When the fan is in a rotating state, the basic blow distance value in the rotating state of the fan is calculated based on the blade angle, rotation speed and fan model parameters. S143, Based on the lightning current waveform parameters and polarity, a correction coefficient is determined. The basic strike distance value is multiplied by the correction coefficient to obtain the dynamic strike distance parameters under the corresponding wind turbine operating state. The lightning current waveform parameters include wavefront time, half-wave time, lightning current amplitude, and waveform type.

4. The lightning strike risk assessment method considering mutual shielding between wind turbine units as described in claim 3, characterized in that, Step S2, which involves constructing a three-dimensional blow distance spherical model for each wind turbine, includes: The center of the wind turbine hub of each wind turbine unit is taken as the center of the sphere; When the wind turbine is in a stationary state, a three-dimensional spherical model of the wind turbine's impact distance is constructed with the dynamic impact distance parameter of the wind turbine in a stationary state as the radius. When the wind turbine is in a rotating state, a three-dimensional spherical model of the wind turbine's impact distance is constructed with the sum of the blade length of the corresponding wind turbine and the dynamic impact distance parameter in the rotating state as the radius.

5. The lightning strike risk assessment method considering mutual shielding between wind turbine units as described in claim 4, characterized in that, Step S3, which involves determining the target lightning strike area based on lightning early warning information and calculating the equivalent lightning interception area after mutual shielding between wind turbine units using a grid sweeping method, includes the following sub-steps: S31, divide the ground projection area corresponding to the target lightning strike area into a fine grid; S32, traverse all fine grids, for each grid's preset vertex, simulate lightning leaders to draw lightning rays vertically upwards from each vertex, calculate the intersection of the lightning rays with the strike distance spheres of all wind turbines, if an intersection exists, select the intersection with the highest elevation, and only if the intersection with the highest elevation is greater than the ground strike distance, then the vertex is assigned to the corresponding wind turbine; otherwise, it is determined to belong to the ground. S33, based on the attribution determination results of all fine mesh vertices, if no less than three vertices belong to the same wind turbine, then the current fine mesh is determined as the valid lightning protection mesh of the corresponding wind turbine. S34, count the number of effective lightning protection grids for each wind turbine, and multiply by the square of the side length of the fine grid to obtain the equivalent interception area of ​​each wind turbine; S35, For multiple discrete lightning current amplitudes within the preset lightning current amplitude range, repeat steps S31 to S34 to obtain the equivalent interception area sequence of each wind turbine under different lightning current amplitudes. S36. Based on the probability density distribution of lightning current amplitude, the equivalent interception area sequence is weighted and summed to obtain the comprehensive equivalent interception area of ​​each wind turbine.

6. The lightning strike risk assessment method considering mutual shielding between wind turbine units as described in claim 5, characterized in that, Step S31, which involves dividing the ground projection area corresponding to the target lightning strike area into a fine grid, includes the following sub-steps: S311, divide the target lightning strike area into several pre-divided evaluation sub-regions; S312, For each evaluation sub-region, calculate the wind turbine distribution density and topographic relief. The wind turbine distribution density is the ratio of the number of wind turbines in the evaluation sub-region to the area of ​​the evaluation sub-region, and the topographic relief is the standard deviation of the elevation data grid points of all topographic elevation data in the evaluation sub-region. S313, normalize the wind turbine distribution density and terrain undulation respectively to obtain the normalized wind turbine distribution density and terrain undulation; S314, Calculate the grid size for each evaluation sub-region based on the normalized wind turbine distribution density and terrain undulation, using the following expression: ； In the formula, L min The minimum boundary value of the preset mesh size. L max The preset maximum size boundary value, D norm The normalized wind turbine distribution density, R norm This represents the normalized topographic relief. w 1 represents the weighting coefficient for the normalized wind turbine distribution density. w 2 represents the weighting coefficient for the normalized terrain relief. S315: Based on the grid size of each evaluation sub-region, perform grid division within the ground projection range of the target lightning strike area to generate the final fine grid.

7. The lightning strike risk assessment method considering mutual shielding between wind turbine units as described in claim 5, characterized in that, The step S4, which calculates the estimated number of lightning strikes for each wind turbine based on the lightning prediction frequency and the equivalent lightning interception area, includes: calculating the estimated number of lightning strikes for each wind turbine by multiplying the lightning prediction frequency in the future time period by the comprehensive equivalent interception area of ​​the corresponding wind turbine and the duration of the future time period.

8. The lightning strike risk assessment method considering mutual shielding between wind turbine units as described in claim 7, characterized in that, The risk level classification and protection decision generation in step S4 include: When the expected number of lightning strikes on a wind turbine is less than the first preset reference value for the number of lightning strikes, it is classified as a low-risk level. When the expected number of lightning strikes on a wind turbine is greater than or equal to the first preset reference value for the number of lightning strikes, but less than the second preset reference value for the number of lightning strikes, it is classified as a medium-risk level. When the expected number of lightning strikes on a wind turbine is greater than or equal to the second preset reference value for the number of lightning strikes, but less than the third preset reference value for the number of lightning strikes, it is classified as a high-risk level. When the expected number of lightning strikes on a wind turbine is greater than or equal to the third preset reference value for the number of lightning strikes, it is classified as an extremely high risk level. If all wind turbines are classified as low-risk or medium-risk, no preventative measures will be taken. If the number of wind turbines with a risk level of high risk or very high risk is less than half the total number of wind turbines on the corresponding collector line, then the corresponding risky wind turbine will be shut down. If the number of wind turbines with a risk level of high risk or very high risk is greater than half the total number of wind turbines on the corresponding collector line, then all wind turbines on the corresponding collector line shall be shut down. If the number of wind turbines with a risk level of high risk or extremely high risk in a wind farm exceeds half the total number of wind turbines, then all wind turbines in the entire wind farm will be shut down.

9. A lightning strike risk assessment system considering mutual shielding between wind turbine units, implemented using the lightning strike risk assessment method considering mutual shielding between wind turbine units as described in any one of claims 1-8, characterized in that, include: The data acquisition module is used to acquire topographic elevation data of the target wind farm, basic parameters of the wind turbine, and geographical location information, and to calculate the dynamic striking distance parameters of the wind turbine. The spherical modeling module is used to determine the target lightning strike area based on lightning warning information, and to construct a three-dimensional spherical model of the strike distance for each wind turbine based on the basic parameters of the wind turbine in the target lightning strike area and the dynamic strike distance parameters of the wind turbine. The grid calculation module is used to calculate the equivalent lightning interception area after mutual shielding between wind turbine units by combining a three-dimensional strike distance spherical model and using a grid sweeping method. The risk assessment module is used to calculate the estimated number of lightning strikes for each wind turbine and classify the risk level based on the predicted frequency of lightning strikes and the equivalent lightning interception area, and generate protection decisions.

10. A computer-readable storage medium, characterized in that, The storage medium stores a lightning strike risk assessment method program that considers mutual shielding between wind turbine units. When the lightning strike risk assessment method program that considers mutual shielding between wind turbine units is executed, it implements the lightning strike risk assessment method that considers mutual shielding between wind turbine units as described in any one of claims 1-8.

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