A method and apparatus for assessing wind vibration of transmission line conductors in areas with unknown wind conditions.

Abstract

This invention relates to the field of transmission line operation and maintenance technology, specifically to a method and device for assessing wind-induced vibration of transmission line conductors in areas with unknown wind environments. In addressing the problem that existing methods for assessing wind-induced conductor damage in transmission lines often rely on extensive manual line patrols due to the lack of readily available wind environment characteristics and the absence of fundamental prerequisites for accurate assessment, the present invention obtains wind and elevation data for the analysis area and establishes a group of auxiliary assessment points. Considering topography, the probability density distribution of wind data at the auxiliary assessment points is determined based on the probability density distribution of wind data from meteorological observation points corresponding to those points. Furthermore, polynomial fitting is used to determine the probability density distribution of wind data for the area to be assessed, thereby enabling the assessment of the degree of wind-induced vibration of the conductors. This provides a data foundation for developing targeted operation and maintenance methods to address wind-induced conductor damage.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of line operation and maintenance, and particularly relates to a wind environment unknown area power transmission line conductor wind vibration evaluation method and device. BACKGROUND

[0002] When wind acts on the power transmission line conductor, wind vibration phenomena such as micro-vibration (low wind speed), galloping (moderate wind speed) and large amplitude vibration (high wind speed) under strong wind may occur. When wind vibration with high frequency, wide influence range or long duration occurs, it may cause conductor fatigue fracture, broken line.

[0003] At present, in response to conductor wind vibration, large-scale operation and maintenance inspection is mainly carried out, and the degree of influence of wind on the line is evaluated in combination with the climate characteristics of the area where the power transmission line is located, such as strengthening the operation and maintenance inspection frequency and the degree of detail in the traditional stable strong wind area. However, for some power transmission lines in certain areas, due to the lack of meteorological observation points and other reasons, it is impossible to obtain climate data, so it is impossible to evaluate the degree of influence of wind on the line. SUMMARY

[0004] Therefore, the present application provides a wind environment unknown area power transmission line conductor wind vibration evaluation method and device to solve the problem that the degree of influence of wind on the line cannot be evaluated for some power transmission line conductors in certain areas in the prior art.

[0005] In a first aspect, the present application provides a wind environment unknown area power transmission line conductor wind vibration evaluation method, which comprises: obtaining elevation data in an analysis area and wind data monitored by meteorological observation points, the analysis area being a region with a preset range outside a to-be-evaluated area, and the to-be-evaluated area being a wind environment unknown area; constructing a plurality of evaluation auxiliary points in the analysis area with the to-be-evaluated area as the center, and selecting a meteorological observation point corresponding to each evaluation auxiliary point based on the distance between each evaluation auxiliary point and the meteorological observation point; determining the joint probability density of the wind data of each evaluation auxiliary point based on the joint probability density and the weight of the wind data of each meteorological observation point, the weight being determined based on the elevation data between the meteorological observation point and the corresponding evaluation auxiliary point; performing polynomial fitting on the joint probability density of the wind data of each evaluation auxiliary point to obtain the joint probability density of the wind data of the to-be-evaluated area; and evaluating the wind vibration degree of the power transmission line conductor in the to-be-evaluated area based on the joint probability density of the wind data of the to-be-evaluated area.

[0006] In the present application, in the face of the existing power transmission line wind vibration induced conductor damage work, due to the inability to obtain the environmental characteristics of the environment, the pre-conditional basis for accurate evaluation of the degree of conductor wind vibration is missing, and only a large number of artificial line inspection can be carried out for line maintenance, the method obtains and analyzes the wind data and elevation data of the analysis area, establishes an evaluation auxiliary point group, determines the probability density distribution of the wind data of the evaluation auxiliary point based on the probability density distribution of the wind data of the corresponding meteorological observation point of the evaluation auxiliary point in the case of considering the topography, further determines the probability density distribution of the wind data of the to-be-evaluated area by polynomial fitting, and thus realizes the evaluation of the degree of conductor wind vibration. Based on this, a data basis is provided for formulating a targeted operation and maintenance method for responding to conductor wind vibration damage.

[0007] In an optional implementation, a plurality of evaluation auxiliary points are constructed in the analysis area with the to-be-evaluated area as the center, including: a plurality of concentric circles are constructed in the analysis area with the to-be-evaluated area as the center at a preset interval, and a plurality of wind direction angle interval lines are formed in the analysis area at a preset wind direction angle interval; the intersection points of the plurality of concentric circles and the plurality of wind direction angle interval lines are taken as the evaluation auxiliary points to obtain the evaluation auxiliary points corresponding to each wind direction angle.

[0008] In the present application, a plurality of evaluation auxiliary points are determined by dividing the concentric circles and the wind direction angles, thereby ensuring that evaluation auxiliary points are constructed in each direction of the to-be-evaluated area, and making the evaluation auxiliary points be approximately uniformly distributed, so that the wind environment characteristics of the to-be-evaluated area can be more accurately determined based on the wind environment characteristics of the evaluation auxiliary points.

[0009] In an optional implementation, the meteorological observation points corresponding to each evaluation auxiliary point are screened based on the distance between each evaluation auxiliary point and the meteorological observation point, including: the spatial distance between each evaluation auxiliary point corresponding to each wind direction angle and all meteorological observation points is calculated; the first meteorological observation points with a spatial distance less than a preset interval are screened; when the number of the first meteorological observation points is greater than a first threshold, a first preset number of the first meteorological observation points are obtained from the first meteorological observation points as the meteorological observation points corresponding to each evaluation auxiliary point; when the number of the first meteorological observation points is less than a second threshold, a second preset number of the second meteorological observation points with a spatial distance greater than the preset interval are screened, and a third preset number of the first meteorological observation points are combined to obtain the meteorological observation points corresponding to each evaluation auxiliary point.

[0010] In the present application, the meteorological observation points corresponding to each evaluation auxiliary point are screened based on the distance between the evaluation auxiliary point and the meteorological observation point and the preset interval, thereby making the corresponding meteorological observation points mostly fall within the range of a concentric circle, and ensuring the accuracy of the wind environment characteristics of the evaluation auxiliary point determined based on the wind environment characteristics of the meteorological observation point.

[0011] In an alternative embodiment, before determining the joint probability density of the wind data of each evaluation auxiliary point based on the joint probability density and the weight of the wind data of each meteorological observation point, the method further comprises: constructing a plurality of elevation sub-nodes based on the distance between each evaluation auxiliary node and the corresponding meteorological observation point; obtaining the terrain fluctuation degree between each evaluation auxiliary node and the corresponding meteorological observation point based on the elevation data of each evaluation auxiliary node, the corresponding meteorological observation point and the elevation sub-nodes; and calculating the weight of the meteorological observation point for the evaluation auxiliary node according to the distance and the terrain fluctuation degree between each evaluation auxiliary node and the corresponding meteorological observation point.

[0012] In the present application, the terrain fluctuation degree between the meteorological observation point and the evaluation auxiliary point is determined by constructing the elevation sub-nodes therebetween and the elevations of the plurality of elevation sub-nodes, thereby achieving an accurate description of the terrain fluctuation degree therebetween.

[0013] In an alternative embodiment, the weight is calculated using the following formula:

[0014]

[0015] In the formula, G z represents the weight of the zth meteorological observation point for the evaluation auxiliary point, r z represents the distance between the zth meteorological observation point and the corresponding evaluation auxiliary point, r maz represents the maximum value of the distance between the evaluation auxiliary point and the corresponding meteorological observation point, H z represents the terrain fluctuation degree between the zth meteorological observation point and the corresponding evaluation auxiliary point, H max represents the maximum value of the terrain fluctuation degree between the evaluation auxiliary point and the corresponding meteorological observation point, and pn represents the number of meteorological observation points corresponding to each evaluation auxiliary point.

[0016] In the present application, the weight of the meteorological observation point is determined by comprehensively considering the terrain fluctuation degree and the distance, thereby making the determined weight more objective.

[0017] In an alternative embodiment, determining the joint probability density of the wind data of each evaluation auxiliary point based on the joint probability density and the weight of the wind data of each meteorological observation point comprises: based on the wind data of each meteorological observation point, calculating the wind speed probability density distribution using the kernel density distribution method; dividing the wind speed interval based on the wind data of each meteorological observation point, and screening the wind direction data in each wind speed interval; based on the wind direction data, calculating the wind direction probability density distribution using the kernel density analysis method; constructing the wind speed and wind direction joint probability density distribution based on the wind speed and wind direction joint probability density distribution of the corresponding meteorological observation point of each evaluation auxiliary point; and determining the wind speed and wind direction joint probability density distribution of each evaluation auxiliary point based on the wind speed and wind direction joint probability density distribution and the weight of the corresponding meteorological observation point of each evaluation auxiliary point.

[0018] In an optional implementation, the wind vibration degree of the power transmission line conductor in the to-be-evaluated region is evaluated based on the joint probability density of the wind data of the to-be-evaluated region, including: determining the occurrence probability of different wind speed and wind direction based on the joint probability density of the wind data of the to-be-evaluated region; calculating the wind vibration degree quantification coefficient of different power transmission circuit conductors based on the occurrence probability of different wind speed and wind direction and the parameters of the power transmission circuit conductors; and evaluating the wind vibration degree of the power transmission line conductor in the to-be-evaluated region according to the wind vibration degree quantification coefficient of the different power transmission circuit conductors.

[0019] In the present application, when the wind vibration degree of the power transmission line conductor is evaluated, the wind vibration degree quantification coefficient of different power transmission circuit conductors is calculated based on the occurrence probability of different wind speed and wind direction and the parameters of the power transmission circuit conductors, thereby realizing the quantification analysis of the wind vibration degree and providing a data basis for formulating the operation and maintenance method for the power grid wind vibration induced disaster.

[0020] In a second aspect, the present application provides a wind environment unknown region power transmission line conductor wind vibration evaluation device, the device comprising: a data acquisition module for acquiring elevation data in an analysis region and wind data monitored by a meteorological observation point, the analysis region being a region in a preset range outside a to-be-evaluated region, and the to-be-evaluated region being a wind environment unknown region; an observation point screening module for constructing a plurality of evaluation auxiliary points in the analysis region with the to-be-evaluated region as the center, and screening the meteorological observation point corresponding to each evaluation auxiliary point based on the distance between each evaluation auxiliary point and the meteorological observation point; a first wind feature analysis module for determining the joint probability density of the wind data of each evaluation auxiliary point based on the joint probability density and weight of the wind data of each meteorological observation point, the weight being determined based on the elevation data between the meteorological observation point and the corresponding evaluation auxiliary point; a second wind feature analysis module for polynomial fitting of the joint probability density of the wind data of each evaluation auxiliary point to obtain the joint probability density of the wind data of the to-be-evaluated region; and an evaluation module for evaluating the wind vibration degree of the power transmission line conductor in the to-be-evaluated region based on the joint probability density of the wind data of the to-be-evaluated region.

[0021] In a third aspect, the present application provides a computer device, comprising: a memory and a processor, which are communicatively connected with each other, and the memory stores computer instructions, and the processor executes the computer instructions to perform the wind environment unknown region power transmission line conductor wind vibration evaluation method of the first aspect or any of the corresponding embodiments thereof.

[0022] In a fourth aspect, the present application provides a computer readable storage medium, which stores computer instructions, and the computer instructions are used to make the computer execute the wind environment unknown region power transmission line conductor wind vibration evaluation method of the first aspect or any of the corresponding embodiments thereof.

[0023] In a fifth aspect, the present application provides a computer program product comprising computer instructions for causing a computer to execute the wind environment unknown area transmission line conductor wind vibration evaluation method of the first aspect or any of the corresponding embodiments thereof. BRIEF DESCRIPTION OF DRAWINGS

[0024] In order to more clearly illustrate the specific embodiments of the present application or the technical solutions in the prior art, the drawings required to be used in the specific embodiments or prior art description will be briefly introduced as follows. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor on the basis of these drawings.

[0025] Figure 1 FIG. 1 is a flowchart of a wind environment unknown area transmission line conductor wind vibration evaluation method according to an embodiment of the present application;

[0026] Figure 2 FIG. 2 is a schematic diagram of the positions of the analysis area and the meteorological observation point according to an embodiment of the present application;

[0027] Figure 3 FIG. 3 is a schematic diagram of the determination method of the evaluation auxiliary point according to an embodiment of the present application;

[0028] Figure 4 FIG. 4 is a schematic diagram of the terrain fluctuation degree of a certain terrain according to an embodiment of the present application;

[0029] Figure 5 FIG. 5 is a schematic diagram of the polynomial fitting result according to an embodiment of the present application;

[0030] Figure 6 FIG. 6 is a schematic diagram of the wind speed and wind direction joint probability density distribution under any wind direction angle according to an embodiment of the present application;

[0031] Figure 7 FIG. 7 is a schematic diagram of the wind speed and wind direction joint probability density distribution under any terrain according to an embodiment of the present application;

[0032] Figure 8 FIG. 8 is a structural block diagram of a wind environment unknown area transmission line conductor wind vibration evaluation device according to an embodiment of the present application;

[0033] Figure 9 FIG. 9 is a hardware structure schematic diagram of a computer device according to an embodiment of the present application. DETAILED DESCRIPTION

[0034] As described in the related art, wind environment feature analysis is performed by wind data of an established meteorological observation point, which can provide data basis for conductor wind vibration fatigue damage. However, many power transmission lines are located in complex topography regions, and do not have conditions for laying meteorological observation points. Therefore, accurate wind environment features cannot be obtained, and the conductor wind vibration degree cannot be quantitatively evaluated.

[0035] Therefore, the wind environment unknown region power transmission line conductor wind vibration evaluation method provided in the embodiments combines the meteorological observation point data outside the unknown region, analyzes and extracts the wind environment features in the region. Meanwhile, the influence of topography and terrain and other factors is considered to accurately obtain the wind environment features in the unknown region, and further quantitatively evaluate the wind vibration degree for different conductor wind vibration phenomena.

[0036] To make the objectives, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some, but not all of the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of protection of the present application.

[0037] According to the embodiments of the present application, a wind environment unknown region power transmission line conductor wind vibration evaluation method embodiment is provided. It should be noted that the steps shown in the flowchart of the drawings can be executed in a computer system such as a group of computer executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0038] In the embodiments, a wind environment unknown region power transmission line conductor wind vibration evaluation method is provided, which can be used in electronic devices such as computers, mobile phones, tablet computers, etc. Figure 1 The flowchart of the wind environment unknown region power transmission line conductor wind vibration evaluation method according to the embodiments of the present application is shown in FIG. Figure 1 The flowchart includes the following steps:

[0039] In step S101, the elevation data in the analysis region and the wind data monitored by the meteorological observation point are obtained. The analysis region is a region in a predetermined range outside the to-be-evaluated region, and the to-be-evaluated region is a wind environment unknown region.

[0040] Specifically, the region to be evaluated is a region without a meteorological observation point due to various reasons, i.e., the wind environment feature data of the region to be evaluated cannot be obtained, and thus the region to be evaluated can also be referred to as a wind environment unknown region. In order to obtain the wind environment features of the region to be evaluated, the embodiment sets an analysis region in a certain range outside the periphery of the region to be evaluated. The meteorological observation point is established in the analysis region, and the wind environment feature data can be obtained. In actual application, the region to be evaluated can be a mountainous area, a forest, etc., and the analysis region can be a province containing the region to be evaluated. In addition, in order to facilitate the inference of the wind environment features of the region to be evaluated, the analysis region can be determined with the region to be evaluated as the center and a certain distance as the radius, and at the same time, in order to make the evaluation of the region to be evaluated more accurate, the analysis region needs to be at least the size of a province.

[0041] For the determined analysis region, the historical meteorological data of the public meteorological observation points established in the region can be obtained, and the wind environment feature data including wind speed, wind direction, etc. can be screened therefrom. In addition, in order to facilitate analysis based on the wind environment feature data, the time span of the obtained historical meteorological data is not less than ten years, and the data resolution is at least 1-hour average wind speed and wind direction. The spacing between the meteorological observation points is not more than 100 km. In addition, the wind environment is also affected by the topography, and thus the elevation data in the analysis region needs to be further obtained. The elevation data can be determined by high-precision satellite cloud map data, with color pixels as the recognition, and equivalent calculation of the elevation information of each position.

[0042] In step S102, a plurality of evaluation auxiliary points are constructed in the analysis region with the region to be evaluated as the center, and the meteorological observation points corresponding to each evaluation auxiliary point are screened based on the distance between each evaluation auxiliary point and the meteorological observation point. Specifically, because the analysis region is much larger than the region to be evaluated, the region to be evaluated can be regarded as a point. Then, the region to be evaluated is taken as the center point, and some points outside the periphery of the region to be evaluated are taken as evaluation auxiliary points, so as to subsequently determine the wind environment features of the center point based on the wind environment features of the evaluation auxiliary points. The evaluation auxiliary points are not necessarily the positions of the established meteorological observation points, and thus the distances between each evaluation auxiliary point and the meteorological observation are calculated to screen the meteorological observation points corresponding to each evaluation auxiliary point, so as to determine the wind environment features of each evaluation auxiliary point through the wind environment features of the corresponding meteorological observation points.

[0043] Step S103, determine the joint probability density of wind data of each evaluation auxiliary point based on the joint probability density of wind data of each meteorological observation point and the weight, the weight is determined based on the elevation data between the meteorological observation point and the corresponding evaluation auxiliary point. Specifically, in the embodiment, the joint probability density distribution is constructed by the wind data of each meteorological observation point obtained, as the wind environment feature observed by each meteorological observation point, which can be the joint probability density distribution of wind speed and wind direction. As for each evaluation auxiliary point, a plurality of meteorological observation points can be generally screened, so that the wind environment features observed by the plurality of meteorological observation points can be weighted, so as to obtain the wind environment feature of the corresponding evaluation auxiliary point. Wherein, in the weighting process, the weight is determined by the elevation data between each meteorological observation point and the corresponding evaluation auxiliary point. Thus, the influence of the wind environment feature observed by each meteorological observation point on the evaluation auxiliary point is determined in consideration of the topography.

[0044] Step S104, polynomial fitting is performed on the joint probability density of wind data of each evaluation auxiliary point to obtain the joint probability density of wind data of the to-be-evaluated region. Specifically, when the joint probability density is the joint probability density of wind speed and wind direction, the joint probability density of a plurality of evaluation auxiliary points can be polynomial fitted based on any wind speed and wind direction to obtain the joint probability density of the to-be-evaluated region under the corresponding wind speed and wind direction; then the wind speed and wind direction are changed, and polynomial fitting is performed respectively, so as to obtain the joint probability distribution of the to-be-evaluated region under different wind speed and wind direction.

[0045] Step S105, evaluate the wind vibration degree of the conductor of the power transmission line in the to-be-evaluated region based on the joint probability density of wind data of the to-be-evaluated region. Specifically, in the related art, the wind environment feature of the to-be-evaluated region is unknown, so the power transmission line conductor cannot be evaluated, but after the joint probability density of wind data of the to-be-evaluated region is determined, the evaluation can be combined with the related art. For example, the evaluation of any power transmission line conductor in the to-be-evaluated region can be realized by combining the determined joint probability density and the related parameters of any power transmission line conductor, such as the conductor direction.

[0046] The wind environment unknown area transmission line conductor wind vibration evaluation method provided by the embodiment of the present application, in the face of the existing transmission line wind vibration induced conductor damage work, due to the inability to obtain the environmental characteristics of the environment, the missing of the pre-conditional basis of the accurate evaluation of the conductor wind vibration degree, only through a large number of artificial line inspection to carry out line maintenance, the method obtains the wind data and elevation data of the analysis area, and establishes an evaluation auxiliary point group, in the case of considering the topography, the probability density distribution of the wind data of the evaluation auxiliary point is determined based on the wind data of the meteorological observation point corresponding to the evaluation auxiliary point, and the probability density distribution of the wind data of the evaluation auxiliary point is further determined by polynomial fitting, and the evaluation of the conductor wind vibration degree is realized. Based on this, a data basis is provided for formulating a targeted operation and maintenance method for responding to conductor wind vibration damage.

[0047] In the embodiment, a wind environment unknown area transmission line conductor wind vibration evaluation method is provided, which comprises the following steps:

[0048] In step S201, the elevation data in the analysis area and the wind data monitored by the meteorological observation points are obtained, the analysis area is a region in a preset range outside the to-be-evaluated region, and the to-be-evaluated region is a wind environment unknown region. For details, please refer to Figure 1 The step S101 of the embodiment shown is not repeated here.

[0049] In step S202, a plurality of evaluation auxiliary points are constructed in the analysis area with the to-be-evaluated region as the center, and the meteorological observation points corresponding to each evaluation auxiliary point are screened based on the distance between each evaluation auxiliary point and the meteorological observation points.

[0050] Specifically, the above step S202 comprises:

[0051] In step S2021, a plurality of concentric circles are constructed in the analysis area with the to-be-evaluated region as the center and a preset interval, and a plurality of wind direction angle interval lines are formed in the analysis area with a preset wind direction angle interval.

[0052] In step S2022, the intersection points of the plurality of concentric circles and the plurality of wind direction angle interval lines are taken as the evaluation auxiliary points, and the evaluation auxiliary points corresponding to each wind direction angle are obtained.

[0053] Specifically, in order to more accurately determine each evaluation auxiliary point, first, the coordinate system is established in combination with the meteorological observation point coordinate range, taking the to-be-evaluated region as the center (i.e., the origin). Then, a plurality of concentric circles are established taking the to-be-evaluated region as the center. The diameters of the plurality of concentric circles are spaced by D, which can be determined according to actual conditions such as the number of meteorological observation points, for example, can be 30 km, 50 km, 100 km, etc. Then, still taking the to-be-evaluated region as the center, a plurality of wind direction angle intervals are formed taking 0 degrees as the direction and taking the preset wind direction angle as the interval, for example, taking the north direction as 0° and taking 20° as the interval, the wind direction angle is cut into 18 regions, and 18 wind direction angle interval lines are obtained. Finally, the intersection points of the concentric circles and the wind direction angle interval lines are obtained, and a plurality of evaluation auxiliary points located in the analysis region are obtained.

[0054] In step S2023, the spatial distance between each evaluation auxiliary point and all meteorological observation points corresponding to each wind direction angle is calculated; the first meteorological observation points with a spatial distance less than a preset interval are screened; when the number of first meteorological observation points is greater than a first threshold value, a first preset number of first meteorological observation points are obtained from the first meteorological observation points as the meteorological observation points corresponding to each evaluation auxiliary point; when the number of first meteorological observation points is less than a second threshold value, a second preset number of second meteorological observation points are screened from the second meteorological observation points with a spatial distance greater than the preset interval, and a third preset number of first meteorological observation points are combined to obtain the meteorological observation points corresponding to each evaluation auxiliary point.

[0055] Specifically, in order to facilitate analysis, the embodiment screens the meteorological observation points corresponding to each evaluation auxiliary point on each wind direction angle in turn. For example, in the 0° wind direction angle, four evaluation auxiliary observation points are included, and the spatial distance between each evaluation auxiliary point and all meteorological observation points is calculated using the following formula in turn:

[0056]

[0057] In the formula, r z represents the spatial distance between the zth meteorological observation point and the corresponding evaluation auxiliary point, (x n,cj , y n,cj ) is the coordinate of the evaluation auxiliary point, (px z , py z ) is the latitude and longitude coordinate of the meteorological observation point, n represents the nth wind direction angle, for example, in the embodiment, the 0° wind direction angle is the first direction angle, then n = 1, and cj is the serial number of the evaluation auxiliary point, z represents the zth meteorological observation point, z = 1, 2,..., pn.

[0058] After the spatial distance between each evaluation auxiliary point and all meteorological observation points is calculated, each spatial distance is compared with the preset interval D, and the meteorological observation points with a spatial distance greater than the preset interval are screened as first observation points; if the number of the screened first meteorological observation points is greater than a first threshold (which can be set according to actual conditions, for example, can be 4 or other number), a first preset number (which can be set according to actual conditions, for example, can be 4 or other number) of first meteorological observation points with smaller spatial distances are obtained from the screened first meteorological observation points as the meteorological observation points corresponding to each evaluation auxiliary point. In the process of obtaining the first preset number of first meteorological observation points with smaller spatial distances, the spatial distances of the screened first meteorological observation points can be sorted from small to large, and then the first preset number of first meteorological observation points can be selected from the smallest spatial distance.

[0059] When the number of the screened first meteorological observation points is less than a second threshold (which can be set according to actual conditions, for example, can be 3 or other number), the screened first meteorological observation points are first taken as the meteorological observation points corresponding to each evaluation auxiliary point; then a plurality of second meteorological observation points with smaller spatial distances are screened from the remaining second meteorological observation points (with a spatial distance greater than the preset interval) as the meteorological observation points corresponding to each evaluation auxiliary point. Similar to the above method, in the process of screening the second meteorological observation points, the second meteorological observation points can also be sorted from small to large based on the spatial distance, and then the second preset number of second meteorological observation points can be selected from the smallest spatial distance. The second preset number of the screened second meteorological observation points can be determined based on a third preset number of the screened first meteorological observation points, for example, the sum of the second preset number and the third preset number satisfies a certain condition (such as 3).

[0060] According to the above method, four meteorological observation points corresponding to the evaluation auxiliary points on the 0° wind direction angle can be determined. Then the meteorological observation points corresponding to the evaluation auxiliary points on the next 20° wind direction angle are calculated; the meteorological observation points corresponding to the evaluation auxiliary points on the next 40° wind direction angle are calculated, and so on, so that the meteorological observation points corresponding to the evaluation auxiliary points on each direction angle are finally obtained.

[0061] In step S203, the joint probability density of the wind data of each evaluation auxiliary point is determined based on the joint probability density of the wind data of each meteorological observation point and the weight, and the weight is determined based on the elevation data between the meteorological observation point and the corresponding evaluation auxiliary point.

[0062] In an optional embodiment, the weight is determined as follows:

[0063] In step S231, a plurality of elevation sub-nodes are constructed based on the distance between each evaluation auxiliary point and the corresponding meteorological observation point.

[0064] Step S232, based on the elevation data of each evaluation auxiliary node, the corresponding meteorological observation point and the elevation sub-node, the terrain fluctuation degree between each evaluation auxiliary point and the corresponding meteorological observation point is obtained.

[0065] Specifically, in order to accurately describe the terrain fluctuation degree between the evaluation auxiliary point and the meteorological observation point, the embodiment sets a plurality of elevation sub-nodes between the evaluation auxiliary point and the corresponding meteorological observation point, the number of elevation sub-nodes is determined based on the distance between the evaluation auxiliary point and the meteorological observation point, and the resolution of the obtained elevation data is considered. Generally, the number of set elevation sub-nodes is not less than 5. After setting the elevation sub-nodes, the terrain fluctuation degree between the evaluation auxiliary point and the meteorological observation point is calculated by the following formula:

[0066]

[0067] h i,i+1 = h i - h i+1

[0068] In the formula, H represents the terrain fluctuation degree, h i represents the elevation data of the node, h n represents the number of elevation sub-nodes, for example, as shown in the figure, there are 5 elevation sub-nodes between a certain evaluation auxiliary point and the corresponding meteorological observation point, wherein h1 is the elevation data of the meteorological observation point, h2 to h6 are the elevation data of the 5 elevation sub-nodes, and h7 is the elevation data of the evaluation auxiliary point; the calculation formula of the corresponding terrain fluctuation degree is:

[0069] H = h 12 + h 23 + h 34 + h 45 + h 56 + h 67

[0070] Step S233, according to the distance and the terrain fluctuation degree between each evaluation auxiliary point and the corresponding meteorological observation point, the weight of the meteorological observation point to the evaluation auxiliary point is calculated. Specifically, the weight is calculated by the following formula:

[0071]

[0072] In the formula, G z represents the weight of the zth meteorological observation point to the evaluation auxiliary point, r z represents the distance between the zth meteorological observation point and the corresponding evaluation auxiliary point, r max represents the maximum value of the distance between the evaluation auxiliary point and the corresponding meteorological observation point, and H zH represents the degree of terrain fluctuation between the zth meteorological observation point and the corresponding evaluation auxiliary point max H represents the maximum value of the degree of terrain fluctuation between the evaluation auxiliary point and the corresponding meteorological observation point, and p n represents the number of meteorological observation points corresponding to each evaluation auxiliary point.

[0073] Specifically, the above step S203 includes:

[0074] In step S2031, based on the wind data of each meteorological observation point, the kernel density distribution method is used to calculate the wind speed probability density distribution. Specifically, in the calculation of the probability density distribution, based on the distribution of the sample points in the multi-dimensional space, each sample point is weighted and smoothed by the kernel function, so as to obtain the probability density estimation on the whole space. In this embodiment, in the calculation of the wind speed probability density distribution, the wind speed data in the historical wind data obtained is taken as the sample point, and the wind speed probability density distribution is expressed by the following formula:

[0075]

[0076] In the formula, f(w s ) represents the wind speed probability density distribution when the wind speed is w s , n represents the total number of wind speed samples, K is the kernel function, and the kernel function adopts the Gaussian kernel function, that is, x i is the wind speed sample size, and h is the sample segmentation interval.

[0077] In step S2032, the wind speed interval is divided based on the wind data of each meteorological observation point, and the wind direction data in each wind speed interval is screened.

[0078] In step S2033, based on the wind direction data, the kernel density analysis method is used to calculate the wind direction probability density distribution.

[0079] Among them, for the obtained wind data, at a certain moment, it not only contains wind speed data, but also contains wind direction data. Therefore, when calculating the probability density distribution of the wind direction, the corresponding relationship between the wind speed and the wind direction needs to be considered. Therefore, this embodiment first divides the wind speed interval, for example, 1m / s can be taken as the boundary, and 0-20m / s is divided, and the wind speed greater than 20m / s is analyzed statistically according to 20m / s. Then the wind direction data corresponding to each wind speed interval is screened, and the wind direction data is taken as the sample point, then the wind direction probability density distribution in any wind speed interval is expressed by the following formula:

[0080]

[0081] In the formula, f(w d ) represents the wind direction probability density distribution in the corresponding wind speed interval, w dWind direction probability density distribution of the time, n x represents the total number of wind direction samples in the corresponding wind speed interval, K is a kernel function, and l is a wind direction sample segmentation interval, which is 20° in the embodiment, the interval is 0-360°, d i is the wind direction sample size.

[0082] Step S2034, constructing a wind speed and wind direction joint probability density distribution based on the wind speed probability density distribution and the wind direction probability density distribution; specifically, the wind speed and wind direction joint probability density distribution is expressed by the following formula:

[0083]

[0084] Step S2035, determining the wind speed and wind direction joint probability density distribution of each evaluation auxiliary point based on the wind speed and wind direction joint probability density distribution and the weight of the observation point of the meteorological station corresponding to each evaluation auxiliary point. Specifically, after determining the wind speed and wind direction joint probability density distribution and the weight of the meteorological observation point, for any evaluation auxiliary point, its wind speed and wind direction joint probability density distribution is determined by the weighted sum of the wind speed and wind direction joint probability density of the corresponding multiple meteorological observation points using the following formula:

[0085]

[0086] Step S204, polynomial fitting is performed on the joint probability density of the wind data of each evaluation auxiliary point to obtain the joint probability density of the wind data of the to-be-evaluated region. Specifically, according to the determination method of the evaluation auxiliary point, the evaluation auxiliary point is determined by the intersection of multiple concentric circles and multiple wind direction angle interval lines, that is, multiple evaluation auxiliary points are included on each wind direction angle interval line. Therefore, when performing polynomial fitting, the wind speed and wind direction joint probability density of multiple evaluation auxiliary points on a certain wind direction angle is first fitted by polynomial; at the same time, according to the above content, it can be known that when determining the wind direction probability density distribution, it is determined based on each wind speed interval, therefore, the above polynomial fitting is the fitting of a certain wind speed interval on a certain wind direction angle, that is, the joint probability density of a specific wind speed and wind direction. Based on this, for multiple evaluation auxiliary points on the wind direction angle, different wind speed intervals need to be used for polynomial fitting; then the wind direction angle is changed, and the same method is used to determine the polynomial fitting of the evaluation auxiliary points in different wind speed intervals on the corresponding wind direction angle. Therefore, through the above process, the wind speed and wind direction joint probability density of the to-be-evaluated region in different wind direction angles and different wind speed intervals can be determined.

[0087] Step S205, evaluating the wind vibration degree of the conductor of the power transmission line in the to-be-evaluated region based on the joint probability density of the wind data of the to-be-evaluated region.

[0088] Specifically, the above step S205 includes:

[0089] Step S2051, determine the occurrence probability of different wind speed and wind direction based on the joint probability density of the wind data of the region to be evaluated; specifically, the joint probability distribution table of the region to be evaluated can be determined by the joint probability density distribution of the wind speed and wind direction of the region to be evaluated. For example, for a certain region to be evaluated, its joint probability distribution table is shown in Table 1 as follows:

[0090] Table 1

[0091]

[0092] According to the joint probability distribution table, the occurrence probability of different wind speed and wind direction can be obtained, for example, the occurrence probability of wind direction angle of 0° and wind speed interval of 1-2 m / s in the region to be evaluated is 0.9%.

[0093] Step S2052, calculate the wind vibration degree quantification coefficient of different transmission line conductors based on the occurrence probability of different wind speed and wind direction and the parameters of the transmission line conductors; specifically, the parameters of the transmission line conductors include the conductor diameter, the angle between the conductor direction and the wind direction, etc. The wind vibration degree quantification coefficient is calculated by the following formula:

[0094]

[0095]

[0096] In the formula, η ws,wd is the wind vibration degree quantification coefficient of wind speed ws and wind direction wd, and the sum of η s is the wind vibration degree quantification coefficient of the corresponding conductor under all wind speed and wind direction, S is the Storha number, which can be taken as 0.2, B is the conductor diameter (unit: m), θ is the angle between the wind direction and the line direction, and f(w d ) represents the occurrence probability of wind speed ws and wind direction wd.

[0097] Step S2053, evaluate the wind vibration degree of the transmission line conductors in the region to be evaluated according to the wind vibration degree quantification coefficient of different transmission line conductors. Specifically, after determining the wind vibration degree quantification coefficient, calculate the sum of the maximum wind vibration degree quantification coefficient to obtain the dimensionless conductor wind vibration degree quantification coefficient, that is, the dimensionless conductor wind vibration degree quantification coefficient is calculated by the following formula:

[0098]

[0099] In the formula, η0 is the dimensionless wind vibration degree quantification coefficient, and η max is the maximum value of the conductor wind vibration degree quantification coefficient of all conductors. Based on the size of the calculated dimensionless wind vibration degree quantification coefficient of the conductor at different positions, the targeted operation and maintenance method for power grid wind vibration induced disasters can be formulated.

[0100] As a specific application example of the embodiment of the present application, as shown in the figure, the wind vibration evaluation method for the conductor of the power transmission line in the unknown wind environment area can be implemented by the following flow: Figure 5

[0101] (1) Collect historical wind speed and wind direction data and topographic elevation data.

[0102] When evaluating the power transmission line conductor in the unknown wind environment area, first select a large area including the target unknown area, which can be the "analysis area". Generally, it is recommended to take the province as the analysis area.

[0103] In the analysis area, due to the large area, there are public meteorological observation points in the flat topographic area. Collect the historical meteorological data of the meteorological observation points in the analysis area, including wind speed and wind direction data. The time span of the historical data is not less than 10 years, the data resolution is at least 1 hour average wind speed and wind direction, and the distance between meteorological observation points is not more than 100 km.

[0104] Collect the elevation data of the analysis area, which can be obtained through high-precision satellite cloud map data, and identify the color pixels to calculate the elevation information of each position.

[0105] (2) Wind environment characteristic analysis.

[0106] 1) Carry out probability density distribution analysis of historical wind speed data. Use kernel density distribution method to calculate the probability density distribution of wind speed, the expression is as follows:

[0107]

[0108] 2) Carry out joint probability density analysis of historical wind speed and wind direction. First, divide the wind speed magnitude into several sections with 1 m / s as the boundary, and divide from 0-20 m / s. Wind speeds greater than 20 m / s are analyzed statistically according to 20 m / s. Screen the wind direction data in each wind speed section, and calculate the wind direction probability density distribution under the condition of a specific wind speed by kernel density analysis method. The calculation formula is as follows:

[0109]

[0110] 3) Calculate the joint probability density distribution function of wind speed and wind direction, as follows:

[0111]

[0112] For the wind speed and wind direction data obtained from any meteorological observation point, the joint probability density distribution function of wind speed and wind direction can be calculated by the above steps. For example, the joint probability distribution of wind speed and wind direction calculated for a meteorological observation point can be obtained in the following form:

[0113] ​Table 2

[0114]

[0115] (3) Construct auxiliary points for wind speed and wind direction assessment.

[0116] 1) Establish an evaluation coordinate system based on meteorological observation points and the analysis area. Specifically, such as... Figure 2 As shown, within the analysis area, there is at least one meteorological observation point within every 100 km. Based on the coordinate range of these meteorological observation points, a wind environment assessment coordinate system is established with the area to be evaluated as the origin.

[0117] 2) Based on the area to be evaluated, divide the auxiliary point set for different wind speed and direction characteristics.

[0118] Since the analysis area is large, the area to be evaluated can be considered as a single point, namely, the evaluation point P. Therefore, with the evaluation point P as the center, a set of auxiliary evaluation points is determined for different wind speeds and directions. Specifically, firstly, multiple concentric circles are formed with P as the center. Spatially, the diameters of these concentric circles are spaced outwards at intervals of D. D can be determined based on the size of the area to be evaluated and the meteorological observation points, typically 30km, 50km, or 100km. Then, with north as 0° and at intervals of 20°, the wind direction angle is divided into 18 regions, resulting in multiple wind direction angle interval lines. Finally, the intersections of the equally spaced concentric circles and the multiple wind direction angle interval lines are used as auxiliary evaluation points. Based on these auxiliary evaluation points, subsequent interpolation analysis of the wind speed and direction distribution characteristics of the area to be evaluated can be performed.

[0119] For any wind direction angle w dn (n = 1, 2, ..., 18, corresponding to wind angles of 0°, 20°, ..., 340° respectively), the schematic diagram of the determined assessment auxiliary points is as follows: Figure 3 As shown. For each wind direction angle w dn Corresponding assessment auxiliary point C n,cj This constitutes the set of auxiliary assessment points, where cj is the index of the auxiliary assessment point. The number of auxiliary assessment points varies depending on the wind direction angle. The auxiliary assessment points obtained based on the above method are shown in Table 3 below:

[0120] Table 3

[0121]

[0122] 3) Select meteorological observation points for wind speed and direction interpolation based on different assessment auxiliary points under different wind angles.

[0123] For assessment auxiliary point C n,cj The latitude and longitude coordinates (x, y, cj) of the evaluation auxiliary point are calculated using the wind direction angle n, the serial number cj, and the spacing D. n,cj, y n,cj ), and then the spatial distance between it and all weather observation points is calculated using the following formula:

[0124]

[0125] The calculated spatial distance and the size of the distance D are compared, and the weather observation points with a spatial distance less than D are screened out. When the number of screened weather observation points is greater than 4, the four weather observation points with the smallest spatial distance are selected. When the number of screened weather observation points is less than 3, the smallest point is selected from the weather observation points with a spatial distance greater than D until the number of weather observation points reaches 3. Thus, the weather observation points corresponding to the evaluation auxiliary point are obtained.

[0126] For each evaluation auxiliary point, the above method is used for calculation and screening, and finally the weather observation points corresponding to all evaluation auxiliary points are obtained, as shown in Table 4 below:

[0127] Table 4

[0128]

[0129] (4) Weight and wind speed and direction characteristics calculation of the weather observation points corresponding to the evaluation auxiliary points.

[0130] 1) The wind speed and direction characteristics of the evaluation auxiliary point are calculated from the wind speed and direction characteristics of the corresponding weather observation points screened in step (3). Before calculation, the calculation weight of each weather observation point needs to be determined. The size of the calculation weight is mainly determined by the spatial distance between the evaluation auxiliary point and the corresponding weather observation point and the terrain fluctuation degree. The terrain fluctuation degree is quantitatively calculated according to the following formula:

[0131]

[0132] h i,i+1 =h i -h i+1

[0133] In the formula, H is the terrain fluctuation degree, hn is the number of elevation sub-nodes between the weather observation point and the evaluation auxiliary point, h i is the corresponding elevation of the node, and the number of nodes is determined according to the distance between the weather observation point and the evaluation auxiliary point, and is generally not less than 5. For example, as shown in the figure, point 1 is a weather station, and point 7 is an evaluation auxiliary point. According to the distance between 1-7 and the GIS data resolution, it is divided into 6 equal segments, and five nodes are added. Therefore, the terrain fluctuation degree of the weather observation point can be calculated by the following formula: Figure 4

[0134] H=h 12 +h 23 +h 34 +h 45 +h​56 +h 67

[0135] According to the spatial distance and the terrain fluctuation degree, the weight coefficient of each meteorological observation point for the evaluation auxiliary point is calculated by the following formula:

[0136]

[0137] Based on the above weight, the wind speed and direction characteristics (wind speed and direction joint probability density) of each meteorological observation point are weighted and calculated, and finally the joint probability density of the evaluation auxiliary point corresponding to the wind speed and direction is obtained by the following formula:

[0138]

[0139] 2) Using the polynomial fitting method, the wind speed and direction joint probability density of the corresponding wind speed and direction of the to-be-evaluated region is calculated.

[0140] Using the above method, the wind speed and direction joint probability density f n,1 (w s ,w d ) of all evaluation auxiliary points under a certain wind direction angle is calculated n,cj (w s ,w d ), and through polynomial fitting, the corresponding wind speed and direction interpolation probability of the to-be-evaluated region is calculated; the polynomial fitting result is shown in Figure 5 , wherein the abscissa represents the evaluation auxiliary point (point), and the ordinate represents the probability (frequency) under a certain wind speed and direction.

[0141] By analyzing the joint probability density of all evaluation auxiliary points under a certain wind speed and direction, the overall regional climate characteristics of the wind environment characteristics can be reflected. (As shown in Figure 6 and Figure 7 , in the analysis region, the probability density of northeast wind can reach about 4% in most regions, but in the southwest region, due to the influence of climate characteristics and landform, the probability of northeast wind is about 2%).

[0142] 3) According to the above method, the repetitive process calculation under different wind direction angles and different wind speeds is carried out. Finally, the wind environment feature distribution table in the to-be-evaluated region is obtained, as shown in Table 1 above.

[0143] 4) Based on the obtained wind environment feature joint probability distribution table of the to-be-evaluated region, the conductor wind vibration degree quantitative calculation is carried out through the following formula for different wind vibration phenomena:

[0144]

[0145]

[0146] According to the above method, the wind vibration degree coefficients of all transmission line conductors in the to-be-evaluated region are calculated, and the dimensionless conductor wind vibration degree quantification coefficient is calculated according to the following formula:

[0147]

[0148] Therefore, according to the dimensionless coefficient of the line at different positions, a targeted operation and maintenance method for the wind vibration induced disaster of the power grid can be formulated.

[0149] Compared with the wind speed and wind direction interpolation method in the related art, which can only calculate the wind speed and wind direction in an instant or within a certain time, and cannot obtain the wind environment characteristics of the unknown region, the evaluation method can realize the wind environment evaluation of the meteorological unknown region. In the evaluation, a calculation method considering the regional flow field characteristics is adopted. Under each wind direction angle, a plurality of evaluation auxiliary points are established, and through the joint probability density calculation of the wind speed and wind direction of the evaluation auxiliary points, the evolution trend of the joint probability density of the wind speed and wind direction in the region can be determined, and the joint probability distribution evaluation of the wind speed and wind direction of the to-be-evaluated region is realized by combining the polynomial fitting. In the joint probability density calculation of the wind speed and wind direction of the evaluation auxiliary points, the influence of topography and distance is considered together. Meanwhile, different wind speed intervals are calculated. According to the wind environment characteristics of the unknown region (to-be-evaluated region) obtained by calculation and evaluation, the wind vibration degree quantification coefficient is calculated. The quantification evaluation of the wind vibration damage is realized.

[0150] In the embodiment, a wind environment unknown region transmission line conductor wind vibration evaluation device is also provided, which is used to realize the above-mentioned embodiments and preferred embodiments, and will not be described again. As used below, the term "module" can be a combination of software and / or hardware that realizes a predetermined function. Although the device described in the following embodiments is preferably realized in software, the realization of hardware, or a combination of software and hardware, is also possible and conceived.

[0151] The embodiment provides a wind environment unknown region transmission line conductor wind vibration evaluation device, as shown in Figure 8 , comprising:

[0152] The data acquisition module 81 is used to acquire the elevation data in the analysis region and the wind data monitored by the meteorological observation points, the analysis region is a region in a preset range outside the to-be-evaluated region, and the to-be-evaluated region is a wind environment unknown region;

[0153] The observation point screening module 82 is used to construct a plurality of evaluation auxiliary points in the analysis region with the to-be-evaluated region as the center, and screen the meteorological observation points corresponding to each evaluation auxiliary point based on the distance between each evaluation auxiliary point and the meteorological observation points;

[0154] The first wind feature analysis module 83 is used to determine the joint probability density of wind data at each assessment auxiliary point based on the joint probability density and weight of wind data at each meteorological observation point. The weight is determined based on the elevation data between the meteorological observation point and the corresponding assessment auxiliary point.

[0155] The second wind feature analysis module 84 is used to perform multinomial fitting on the joint probability density of wind data at each evaluation auxiliary point to obtain the joint probability density of wind data in the area to be evaluated.

[0156] Evaluation module 85 is used to evaluate the wind vibration level of transmission line conductors in the area to be evaluated based on the joint probability density of wind data of the area to be evaluated.

[0157] Further functional descriptions of the above modules are the same as those in the corresponding embodiments described above, and will not be repeated here.

[0158] This invention also provides a computer device having the above-described features. Figure 8 The device shown is for assessing wind vibration of transmission line conductors in areas with unknown wind environments.

[0159] Please see Figure 9 , Figure 9 This is a schematic diagram of the structure of a computer device provided in an optional embodiment of the present invention, such as... Figure 9 As shown, the computer device includes one or more processors 10, memory 20, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The components communicate with each other via different buses and can be mounted on a common motherboard or otherwise installed as needed. The processors can process instructions executed within the computer device, including instructions stored in or on memory to display graphical information of a GUI on external input / output devices (such as display devices coupled to the interfaces). In some alternative implementations, multiple processors and / or multiple buses can be used with multiple memories and multiple memory modules, if desired. Similarly, multiple computer devices can be connected, each providing some of the necessary operations (e.g., as a server array, a group of blade servers, or a multiprocessor system). Figure 9 Take a processor 10 as an example.

[0160] Processor 10 may be a central processing unit, a network processor, or a combination thereof. Processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The programmable logic device may be a complex programmable logic device (CAMP), a field-programmable gate array (FPGA), a general-purpose array logic (GDA), or any combination thereof.

[0161] The memory 20 stores instructions executable by the at least one processor 10 to cause the at least one processor 10 to perform the method illustrated in the above embodiments.

[0162] The memory 20 can include a program storage area and a data storage area. The program storage area can store an operating system and application programs required by at least one function. The data storage area can store data created by the use of the computer device according to the presentation of the applet landing page, and the like. In addition, the memory 20 can include a high-speed random access memory, and can also include a non-transitory memory, such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state memory device. In some optional embodiments, the memory 20 can optionally include a memory disposed remotely with respect to the processor 10, and these remote memories can be connected to the computer device through a network. Examples of the network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof.

[0163] The memory 20 can include a volatile memory, such as a random access memory; the memory can also include a non-volatile memory, such as a flash memory, a hard disk, or a solid-state disk; and the memory 20 can also include a combination of the above-mentioned kinds of memories.

[0164] The computer device further includes a communication interface 30 for the computer device to communicate with other devices or a communication network.

[0165] The embodiments of the present application also provide a computer readable storage medium. The above method according to the embodiments of the present application can be implemented in hardware, firmware, or recorded in a storage medium, or stored in a remote storage medium or a non-transitory machine readable storage medium and downloaded to a local storage medium through network downloading of computer code, so that the method described herein can be processed by such software on a storage medium using a general purpose computer, a special purpose processor, or programmable or special purpose hardware. The storage medium can be a magnetic disk, an optical disk, a read-only memory, a random access memory, a flash memory, a hard disk, or a solid-state disk, and the like; further, the storage medium can also include a combination of the above-mentioned kinds of memories. It can be understood that the computer, the processor, the microprocessor controller, or the programmable hardware includes a storage component that can store or receive software or computer code, when the software or computer code is accessed and executed by the computer, the processor, or the hardware, the method illustrated in the above embodiments is implemented.

[0166] Part of the present application can be applied as a computer program product, for example, computer program instructions, when executed by a computer, through the operation of the computer, can invoke or provide the method and / or technical solutions according to the present application. Those skilled in the art should understand that the form of computer program instructions in computer readable medium includes but is not limited to source files, executable files, installation package files and the like, and accordingly, the way of computer program instructions executed by computer includes but is not limited to: the computer directly executes the instructions, or the computer compiles the instructions and then executes the corresponding compiled program, or the computer reads and executes the instructions, or the computer reads and installs the instructions and then executes the corresponding installed program. Here, the computer readable medium can be any available computer readable storage medium or communication medium accessible to the computer.

[0167] Although the embodiments of the present application are described in conjunction with the drawings, various modifications and changes can be made by those skilled in the art without departing from the spirit and scope of the present application, and such modifications and changes fall within the scope defined by the appended claims.

Claims

1. A method for evaluating wind-induced vibration of a conductor of a power transmission line in an area with unknown wind environment, characterized in that, The method comprises: obtaining elevation data in an analysis region and wind data monitored by meteorological observation points, the analysis region being a region with a preset range outside a periphery of a to-be-evaluated region, and the to-be-evaluated region being a region with unknown wind environment; centering on the to-be-evaluated region, constructing a plurality of evaluation auxiliary points in the analysis region, and screening meteorological observation points corresponding to each evaluation auxiliary point based on a distance between each evaluation auxiliary point and the meteorological observation points; determining a joint probability density of wind data of each evaluation auxiliary point based on a joint probability density of wind data of each meteorological observation point and a weight determined based on elevation data between the meteorological observation points and the corresponding evaluation auxiliary points; performing polynomial fitting on the joint probability density of wind data of each evaluation auxiliary point to obtain a joint probability density of wind data of the to-be-evaluated region; evaluating a wind vibration degree of a conductor of a power transmission line in the to-be-evaluated region based on the joint probability density of wind data of the to-be-evaluated region; centering on the to-be-evaluated region, constructing a plurality of evaluation auxiliary points in the analysis region comprises: constructing a plurality of concentric circles in the analysis region at a preset interval and forming a plurality of wind direction angle interval lines in the analysis region at a preset wind direction angle interval, centering on the to-be-evaluated region; taking an intersection of the plurality of concentric circles and the plurality of wind direction angle interval lines as an evaluation auxiliary point to obtain evaluation auxiliary points corresponding to each wind direction angle; before determining the joint probability density of wind data of each evaluation auxiliary point based on the joint probability density of wind data of each meteorological observation point and the weight, the method further comprises: constructing a plurality of elevation sub-nodes based on a distance between each evaluation auxiliary point and the corresponding meteorological observation points; obtaining a terrain fluctuation degree between each evaluation auxiliary point and the corresponding meteorological observation points based on elevation data of each evaluation auxiliary node, the corresponding meteorological observation points and the elevation sub-nodes; calculating a weight of the meteorological observation points for the evaluation auxiliary points according to the distance and the terrain fluctuation degree between each evaluation auxiliary point and the corresponding meteorological observation points; the weight is calculated by using the following formula: wherein, represents the weight of the zth meteorological observation point for the evaluation auxiliary point, represents the distance between the zth meteorological observation point and the corresponding evaluation auxiliary point, represents the maximum value of the distance between the evaluation auxiliary point and the corresponding meteorological observation point, represents the degree of topographic fluctuation between the zth meteorological observation point and the corresponding evaluation auxiliary point, represents the maximum value of the degree of topographic fluctuation between the evaluation auxiliary point and the corresponding meteorological observation point, and pn represents the number of meteorological observation points corresponding to each evaluation auxiliary point, represents the wind speed.

2. The method of claim 1, wherein, screening the meteorological observation points corresponding to each evaluation auxiliary point based on the distance between each evaluation auxiliary point and the meteorological observation points comprises: calculating a spatial distance between each evaluation auxiliary point and all the meteorological observation points corresponding to each wind direction angle; screening a first meteorological observation point with a spatial distance less than a preset interval; when a number of the first meteorological observation points is greater than a first threshold value, obtaining a first preset number of the first meteorological observation points from the first meteorological observation points as the meteorological observation points corresponding to each evaluation auxiliary point; when the number of the first meteorological observation points is less than a second threshold value, screening a second preset number of second meteorological observation points from second meteorological observation points with a spatial distance greater than the preset interval, combining a third preset number of the first meteorological observation points to obtain the meteorological observation points corresponding to each evaluation auxiliary point.

3. The method of claim 1, wherein, determining the joint probability density of wind data of each evaluation auxiliary point based on the joint probability density of wind data of each meteorological observation point and the weight comprises: based on wind data of each meteorological observation point, calculating a wind speed probability density distribution by using a kernel density distribution method; dividing wind speed intervals based on the wind data of each meteorological observation point, and screening wind direction data in each wind speed interval; Based on the wind direction data, a kernel density analysis method is used to calculate a wind direction probability density distribution; Based on the wind speed probability density distribution and the wind direction probability density distribution, a wind speed and wind direction joint probability density distribution is constructed; Based on the wind speed and wind direction joint probability density distribution of each evaluation auxiliary point corresponding to the meteorological station observation point and the weight, the wind speed and wind direction joint probability density distribution of each evaluation auxiliary point is determined.

4. The method of claim 1, wherein, Based on the joint probability density of the wind data of the to-be-evaluated region, the wind vibration degree of the conductor of the transmission line in the to-be-evaluated region is evaluated, including: Based on the joint probability density of the wind data of the to-be-evaluated region, the occurrence probability of different wind speeds and wind directions is determined; Based on the occurrence probability of different wind speeds and wind directions and the parameters of the conductor of the transmission line, the wind vibration degree quantization coefficient of different transmission circuit conductors is calculated; According to the wind vibration degree quantization coefficient of different transmission circuit conductors, the wind vibration degree of the conductor of the transmission line in the to-be-evaluated region is evaluated.

5. A wind environment unknown area power transmission line conductor wind vibration evaluation device characterized by, The device comprises: A data acquisition module is configured to acquire elevation data and wind data monitored by meteorological observation points in an analysis region, the analysis region being a region in a preset range outside a to-be-evaluated region, and the to-be-evaluated region being a region with unknown wind environment; An observation point screening module is configured to construct a plurality of evaluation auxiliary points in the analysis region with the to-be-evaluated region as the center, and screen meteorological observation points corresponding to each evaluation auxiliary point based on the distance between each evaluation auxiliary point and the meteorological observation points; A first wind feature analysis module is configured to determine the joint probability density of the wind data of each evaluation auxiliary point based on the joint probability density of the wind data of each meteorological observation point and a weight, the weight being determined based on the elevation data between the meteorological observation points and the corresponding evaluation auxiliary points; A second wind feature analysis module is configured to perform polynomial fitting on the joint probability density of the wind data of each evaluation auxiliary point to obtain the joint probability density of the wind data of the to-be-evaluated region; An evaluation module is configured to evaluate the wind vibration degree of the conductor of the transmission line in the to-be-evaluated region based on the joint probability density of the wind data of the to-be-evaluated region; The plurality of evaluation auxiliary points are constructed in the analysis region with the to-be-evaluated region as the center, including: A plurality of concentric circles are constructed in the analysis region with a preset interval with the to-be-evaluated region as the center, and a plurality of wind direction angle interval lines are formed in the analysis region with a preset wind direction angle interval; The intersection points of the plurality of concentric circles and the plurality of wind direction angle interval lines are taken as the evaluation auxiliary points to obtain the evaluation auxiliary points corresponding to each wind direction angle; Before determining the joint probability density of the wind data of each evaluation auxiliary point based on the joint probability density of the wind data of each meteorological observation point and the weight, the method further comprises: A plurality of elevation sub-nodes are constructed based on the distance between each evaluation auxiliary point and the corresponding meteorological observation points; The terrain fluctuation degree between each evaluation auxiliary node and the corresponding meteorological observation point is obtained based on the elevation data of each evaluation auxiliary node, the corresponding meteorological observation point, and the elevation sub-nodes; The weight of the meteorological observation point with respect to the evaluation auxiliary point is calculated according to the distance and the terrain fluctuation degree between each evaluation auxiliary point and the corresponding meteorological observation point; The weight is calculated using the following formula: wherein, represents the weight of the zth meteorological observation point for the evaluation auxiliary point, represents the distance between the zth meteorological observation point and the corresponding evaluation auxiliary point, represents the maximum value of the distance between the evaluation auxiliary point and the corresponding meteorological observation point, represents the degree of topographic fluctuation between the zth meteorological observation point and the corresponding evaluation auxiliary point, represents the maximum value of the degree of topographic fluctuation between the evaluation auxiliary point and the corresponding meteorological observation point, and pn represents the number of meteorological observation points corresponding to each evaluation auxiliary point, represents the wind speed.

6. A computer device, comprising: including: A memory and a processor, which are connected in communication with each other, the memory storing computer instructions, and the processor executing the computer instructions to perform the wind environment unknown area transmission line conductor wind vibration evaluation method of any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer instructions for causing a computer to perform the wind environment unknown area transmission line conductor wind vibration evaluation method of any one of claims 1 to 4.

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