Power transmission line design parameter correction method suitable for micro-topographic region

Abstract

The invention provides a power transmission line design parameter correction method suitable for a micro-topographic region, and belongs to the technical field of power transmission line design, and the method comprises the steps: taking meteorological data, landform features, and the distance between a meteorological station and a micro-topography as input variables, fitting the relationship between the input variables and the output variables of the power transmission line design parameters in the micro-topographic region, and correcting the power transmission line design parameters in the micro-topographic region; obtaining a meteorological change rule at a to-be-built power transmission line in the micro-topographic region, and building an algorithm model; and predicting the power transmission line design parameter value of the whole research area. The method has the advantages that after geographic information of the to-be-built line along the way is obtained, the to-be-built line is classified through related definitions of the microtopography, correct design parameters of the power transmission line in the microtopography are associated with meteorological data of surrounding meteorological stations based on geographic features of different types of microtopography, and the meteorological formation rule of the power transmission line in the microtopography area is deduced; and the design parameters of the power transmission line in the micro-topographic area can be rapidly and reasonably valued.

Description

Technical Field

[0001] The invention belongs to the technical field of power transmission line design, and in particular relates to a power transmission line design parameter correction method suitable for micro-topography areas. Background Art

[0002] The value of the transmission line design parameters represents the ability of the transmission line to bear the load, which is related to the safe operation of the transmission line after it is built. This value often requires designers to comprehensively consider the meteorological conditions of the location where the line is to be built, clarify the quality requirements of the transmission line, and finally obtain it through calculation. With the vigorous development of electricity in my country, the construction path of the transmission line will inevitably pass through micro-topography areas such as mountainous areas and canyons. However, when calculating the value of the design parameters, designers usually use the extensive meteorological data of nearby meteorological stations. In fact, the actual meteorological conditions in the area where the transmission line is to be built will be greatly different from the extensive meteorological data of the meteorological station due to the influence of micro-topography, resulting in incorrect values ​​of the transmission line design parameters, which in turn indirectly causes safety accidents in the operation of the transmission line.

[0003] In order to correctly calculate the design parameters of the transmission line, the prior art generally re-establishes micro-meteorological observation points according to the location of the area where the transmission line is to be built, and installs electronic measuring equipment in the area where the line is to be built to collect more accurate meteorological data; for example, the Chinese patent with publication number "CN117741815B" discloses "a transmission line micro-meteorological monitoring device installation structure", which is equipped with a rainfall monitoring module, a wind speed and direction monitoring module and a camera. Although the device can accurately collect meteorological data, one device can only be used for data collection in one area. There are many micro-topography areas through which the transmission line to be built passes. It will cost a lot to set up a large number of micro-meteorological monitoring devices, which are difficult to apply to numerous micro-topography areas. For example, the Chinese patent with publication number "CN108090285B" discloses a "micro-meteorological observation point layout method for wind disaster monitoring of complex terrain transmission lines" to realize the selection of micro-meteorological observation sites for transmission lines in the region. Although the meteorological observation points established according to this method can accurately measure the micro-meteorological data of a large area, the observation points need to undergo a long monitoring period after being re-established before the measured micro-meteorological data can be applied to the calculation of transmission line design parameters, and the design and rapid construction of transmission lines are not utilized. Summary of the invention

[0004] The technical problem to be solved by the present invention is that a long monitoring period is required after the observation point is re-established. In view of the shortcomings of the prior art, a transmission line design parameter correction method suitable for micro-topography areas is provided for the design and rapid construction of transmission lines.

[0005] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0006] The method comprises the following steps: obtaining the terrain parameters of the area where the transmission line is to be built, generating a geomorphic feature data set, generating a micro-topography area according to the area where the transmission line is to be built, extracting a micro-topography data set according to the geomorphic feature data set, and clustering the micro-topography areas in the area where the transmission line is to be built; obtaining the directional relationship between the micro-topography and the meteorological station and the minimum directional distance, screening the best meteorological station near the micro-topography area, and obtaining the meteorological data of the screened meteorological station; collecting the actual meteorological parameters at the micro-topography, and obtaining the design wind speed and design ice thickness values ​​of the transmission line; taking the meteorological data, the geomorphic features, and the distance between the meteorological station and the micro-topography as input quantities, fitting the relationship between the input quantity and the output quantity of the transmission line design parameters in the micro-topography area, obtaining the meteorological change law at the transmission line to be built in the micro-topography area, and building an algorithm model; and predicting the transmission line design parameter values ​​of the entire study area according to the relationship between the input quantity and the output quantity fitted in the sample.

[0007] Furthermore, the method of obtaining the terrain parameters of the area where the power transmission line is to be built and generating a geomorphic feature data set includes:

[0008] The satellite digital elevation data is used to obtain the longitude, latitude and altitude of the mountain where the line to be built is located and the surrounding mountains. The satellite scans 3 points each time to obtain their longitude, latitude and altitude, and establish three-dimensional spatial coordinates, which are (x n1 ,y n1 , z n1 ), (x n2 ,y n2 , z n2 ), (x n3 ,y n3 , z n3 ), the line connecting the three points constitutes a triangular surface. The slope and aspect calculation based on the irregular triangulated network uses the latitude and longitude of the points and the altitude as well as the trigonometric function calculation formula of three-dimensional space to convert the geomorphic feature data of the height α, slope β and slope aspect γ of the triangular surface area. The calculation process is as follows:

[0009]

[0010] Further, a method of generating a micro-topography area according to the area of ​​the transmission line to be built, extracting a micro-topography data set according to the geomorphic feature data set, and clustering the micro-topography areas in the area of ​​the transmission line to be built includes:

[0011] Provide domain description for geomorphic feature datasets, local domain geomorphic features Neighborhood points and The linear relationship is:

[0012]

[0013] in

[0014] Where W ij express In the construction The proportion of the process:

[0015]

[0016] The geomorphic feature dataset is reduced in dimension, the dataset is divided by the objective function after dimension reduction, and then the classified geomorphic feature dataset is obtained by using the inverse dimension change method. Its structure before and after dimensionality reduction The proportions occupied are consistent, and the minimum objective function after the dimension reduction of landform features is:

[0017]

[0018] ψ represents the landform feature data after dimensionality reduction, which is composed of the low-dimensional data set ψ i There are a total of N data sets after dimensionality reduction, and W is a matrix composed of weight coefficients.

[0019] Furthermore, the method for clustering the micro-topography areas in the area where the power transmission line is to be built also includes:

[0020] After obtaining the geomorphic features of the study area, micro-topographic areas were screened out. The types of micro-topographic areas include alpine watersheds, terrain uplifts, passes, and canyon wind tunnels. Constraint equations were established based on different micro-topographic area types to classify and cluster the geomorphic features of height α, slope β, and slope aspect γ.

[0021] The line to be built is pre-established on the mountain, distinguishing between high mountain watershed and uplift micro-topography types:

[0022] The alpine watershed is determined based on:

[0023] The basis for determining terrain uplift is:

[0024] The line to be built is pre-established between the mountains, distinguishing the micro-topography types of the pass and canyon wind channel:

[0025] The criteria for determining a pass are:

[0026] The basis for determining the canyon wind channel is

[0027] Furthermore, the method of obtaining the directional relationship between the micro-topography and the meteorological station and the minimum directional distance, screening the best meteorological station near the micro-topography area, and obtaining the meteorological data of the screened meteorological station includes:

[0028] Taking the climate wind direction and the straight-line distance along the ground surface from the meteorological station to the line to be built as reference, the meteorological stations near the micro-topography area are screened, and the meteorological data of the meteorological stations are extracted based on the multi-objective optimization results that simultaneously consider the climate flow direction and adjacent distances:

[0029] Taking wind direction as the objective function, the space where the micro-topography is located is divided into 9 directional areas {N, S, E, W, NE, SE, SW, NW, O}. The distribution of single meteorological stations in the 9 directional areas is recorded through a matrix, and the directional relationship between micro-topography A and meteorological station B is expressed as:

[0030]

[0031] Where D dir1 The element numerator of the first column of the matrix is ​​the number of cells occupied by the meteorological station in each direction of the micro-topography space, S B is the number of triangular face elements occupied by the micro-topography. The size of the weather station is expressed by the number of cells. The direction is determined by counting cells. θ is the horizontal angle between the north direction of the coordinate longitudinal line of the circumcenter of A and the direction of the climatic wind in a clockwise direction. S(D dir1 , D dir2 ) value indicates the similarity between the selected location of the weather station and the climatic wind direction; according to S(D dir1 , D dir2 ) value, judge whether the selected location of the meteorological station is close to the climatic wind direction, and then determine whether the meteorological parameters collected by the selected meteorological station are relevant to the actual meteorological parameters of the micro-topography;

[0032] Taking the distance between the weather station and the micro-topography as the objective function, after determining the directional relationship between the location of the micro-topography and the weather station, the directional distance fd(θ) based on θ is introduced, and the reference directional distance is extended from 9 directions to any direction to solve the centroid directional distance:

[0033] f d (θ) = d max ×arccos(cosθ) / π,θ∈[0,2π];

[0034] Where d max Indicates the maximum distance between direction areas;

[0035] Calculate the minimum direction distance f d (θ), the meteorological station selected corresponding to the minimum directional distance, whose collected meteorological data is used to predict the actual meteorological data of micro-topography.

[0036] Furthermore, the method of collecting the actual meteorological parameters at the micro-topography and obtaining the design wind speed and design ice thickness of the transmission line includes:

[0037] The actual meteorological parameters of the micro-topography are collected by micro-meteorological electronic measuring equipment, which includes an anemometer and an icing monitoring device. Designers solve and give the design wind speed v and design icing thickness D of the transmission line through wind speed collection and icing weight measurement. The calculation method is expressed as:

[0038]

[0039] Among them, a and b are the distribution scale parameter and distribution location parameter of the collected wind speed data, respectively, R is the return period used to calculate the design wind speed, d is the diameter of the ground wire of the transmission line, g is the weight of ice per unit length, and ρ is the density of ice in the area.

[0040] Furthermore, the meteorological data, as well as the geomorphic features, and the distance between the meteorological station and the micro-topography are used as input quantities, and the relationship between the input quantity and the output quantity micro-topography area transmission line design parameters is fitted to obtain the meteorological change law at the transmission line to be built in the micro-topography area. The method of building an algorithm model includes:

[0041] Given the corresponding meteorological parameter temperature T of a nearby meteorological station nm RH nm Humidity, v nm Wind speed and Wind direction, distance between micro-topography, geomorphic features and meteorological stations are used as inputs. The relationship between the above inputs and output micro-topography regional transmission line design parameters is fitted through the generalized regression neural network algorithm. The algorithm model built by the generalized regression neural network algorithm is described as:

[0042] First, the input data is processed and the neuron transfer function in the pattern layer is calculated:

[0043]

[0044] Where σ is the width coefficient of the Gaussian function, ηi is the sample data set, ε=(T,RH,v, α, β, γ) T , ε i is the learning sample corresponding to the i-th neuron;

[0045] The output result is a two-dimensional parameter including the design wind speed and the design ice thickness. In the summation layer, an arithmetic sum of the model layer output is calculated, and a weighted sum of the two model layer outputs is calculated:

[0046]

[0047] S H With S NJ They are the output sum and weighted sum of the nodes in the summing layer during the algorithm solution process;

[0048] In arithmetic summation, the connection weight of each neuron in the pattern layer and the summation layer is 1; in weighted summation, the connection weight between the i-th neuron in the pattern layer and the j-th summation neuron in the summation layer is the i-th output sample ξ i The jth element in ;

[0049] Divide the output of the summation layer by D, which is the ice thickness, and the result can be summed with the output ξ = (v, D) T The jth element of :

[0050]

[0051] ξ is the design wind speed and ice thickness solved and used for prediction, ξ i is the i-th data of the output.

[0052] Compared with the prior art, the present invention has the following beneficial effects:

[0053] (1) The present invention solves the existing problem of selecting the design parameters of power transmission lines in micro-topography areas. Since the meteorological conditions in the micro-topography area are quite different from those in the surrounding typical areas, the design parameters of power transmission lines calculated by designers based on extensive meteorological data often do not meet the actual engineering requirements. After obtaining the geographical information along the line to be built, the present invention classifies them according to the micro-topography related definitions. Based on the geographical characteristics of different types of micro-topography, the correct design parameters of the power transmission lines in the micro-topography are linked with the meteorological data of the surrounding meteorological stations, and the meteorological formation law of the power transmission lines in the micro-topography area is derived, so that the design parameters of the power transmission lines in the micro-topography area can be quickly and reasonably selected.

[0054] (2) When classifying micro-topography types, the present invention can quickly extract micro-topography related data from the geographic information extracted by satellites through algorithms and directly locate the location of the micro-topography, and then classify the micro-topography data, that is, there is no need to arrange observers to conduct manual terrain surveys on the areas through which the transmission lines to be built pass.

[0055] (3) When selecting meteorological parameters of surrounding meteorological stations, the present invention combines geographic information and direction ranging, and reasonably adopts the meteorological parameters of the most scientific meteorological station in the surrounding area to ensure that the adopted meteorological parameters are related to the actual design parameters of the micro-topography transmission line.

[0056] (4) After deducing the meteorological formation law of the transmission line in the micro-topography area within the research scope, the present invention brings the geomorphic feature data of any micro-topography area and the meteorological parameters of the meteorological stations selected in its surroundings into the law equation, thereby obtaining the transmission line design parameters that meet the actual engineering specifications, thereby reducing the occurrence of safety accidents after the transmission line is built. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] The present invention is further described in detail below in conjunction with the accompanying drawings.

[0058] Figure 1 : Schematic diagram of geographic information data collection based on satellite DEM of the present invention;

[0059] Figure 2 : Flow chart of the steps of extracting and classifying micro-topography features of the present invention;

[0060] Figure 3 : A schematic diagram of the locations of meteorological stations around the location where the power transmission line of the present invention is to be built;

[0061] Figure 4 : Correlation analysis diagram between meteorological data of the weather station of the present invention and design parameters of the transmission line. DETAILED DESCRIPTION

[0062] In order to better understand the present invention, the content of the present invention is further clearly described below in conjunction with the embodiments and the accompanying drawings, but the protection content of the present invention is not limited to the following embodiments. In the following description, a large number of specific details are provided to provide a more thorough understanding of the present invention. However, it is obvious to those skilled in the art that the present invention can be implemented without one or more of these details.

[0063] Example 1: See Figure 1-4 , a transmission line design parameter correction method applicable to micro-topography areas in this embodiment includes:

[0064] Step 1: Use satellite DEM to obtain the terrain parameters of the area where the transmission line is to be built, and cluster the micro-topography areas in the study area using the LLEAM algorithm.

[0065] LLEAM algorithm: This algorithm combines the LLE (Locally Linear Embedding) algorithm and the PAM (Partitioning Around Medoid) algorithm. Since elevation data is high-dimensional data, it is first reduced in dimension by nonlinearity, and then clustered by the center point method. The definition of the center point is omitted in the implementation case, that is, the data of the typical area of ​​geomorphic features.

[0066] Call satellite DEM (digital elevation data) to obtain the longitude, latitude and altitude of the mountain where the line to be built is located and the surrounding mountains. The data set is in units of triangular face elements. The extraction process is as follows: Figure 1 The subsequent slope and aspect calculation based on the irregular triangulated network converts the latitude and longitude and altitude of the point into the geomorphic feature data of the height α, slope β and slope aspect γ of the triangular surface area. These geomorphic features are obtained through satellite positioning scanning, using the latitude and longitude and altitude of the point, based on the trigonometric function calculation formula of three-dimensional space. The calculation process is as follows:

[0067]

[0068] The satellite scans three points each time, obtains their latitude, longitude and altitude, and establishes three-dimensional spatial coordinates, which are (x n1 ,y n1 , z n1 ), (x n2 ,y n2 , z n2 ), (x n3 ,y n3 , z n3 ), the lines connecting the three points form a triangle.

[0069] Based on the definition of micro-topography in engineering guidelines, the LLEAM algorithm is used to extract the micro-topography dataset from the geomorphic feature dataset, and the micro-topography regions in the study area are clustered. The specific clustering analysis process can be described as follows:

[0070] Provide domain description for geomorphic feature datasets and local domain geomorphic features Neighborhood points and The linear relationship is described as:

[0071]

[0072] in

[0073] Where W ij express In the construction The proportion of the process:

[0074]

[0075] This refers to the typical geomorphic feature data of high mountain watersheds, terrain uplift, passes and canyon wind channels in micro-topography. Here it refers to k groups of similar geomorphic feature data. Here, m, l, s are just simple variables used to mark k groups of domain geomorphic feature data;

[0076] In order to quickly identify the classified geomorphic feature dataset, the geomorphic feature dataset is reduced in dimension, the dataset is divided by the objective function after dimension reduction, and then the classified geomorphic feature dataset is obtained by the dimensional inverse change method. The implementation process is as follows: Figure 2 shown. Its structure before and after dimensionality reduction The proportions occupied are consistent, and the minimum objective function after dimensionality reduction of landform features can be obtained:

[0077]

[0078] ψ represents the landform feature data after dimensionality reduction, which is a matrix composed of low-dimensional data sets ψi. There are a total of N data sets after dimensionality reduction, and W is a matrix composed of weight coefficients.

[0079] Step 2: Use the SOS (Spatial Orientation Similarity) method to screen the meteorological stations near the micro-topography area, and extract the meteorological data of the meteorological stations based on the multi-objective optimization results that simultaneously consider the climate flow direction and adjacent distance;

[0080] The selection of meteorological stations should take into account the climate, wind direction, and the straight-line distance from the meteorological station to the line to be built. The selection process is as follows: Figure 3 The selected meteorological station cannot be located in a special terrain. At the same time, the straight line along the surface to the line to be built does not cross more than one mountain. The specific screening process can be described as:

[0081] The so-called SOS method can be described as follows: taking wind direction as the objective function, the space where the micro-topography is located is divided into 9 directional areas {N, S, E, W, NE, SE, SW, NW, O}, the distribution of a single meteorological station in the 9 directional areas is recorded through a matrix, and the directional relationship between the micro-topography A and the meteorological station B is expressed as:

[0082]

[0083] Where D dir1 The element numerator of the first column of the matrix is ​​the number of cells occupied by the meteorological station in each direction of the micro-topography space, S B is the number of triangular face elements occupied by the micro-topography. The size of the weather station is expressed by the number of cells, and the direction is determined by counting cells. θ is the horizontal angle from the north direction of the coordinate longitudinal line of the circumcenter of A to the direction of the climatic wind in a clockwise direction. S(D dir1 , D dir2 ) value indicates the similarity between the selected location of the weather station and the climatic wind direction. dir1 , D dir2 ) value to determine whether the selected location of the meteorological station is close to the climate wind direction. The meteorological parameters collected by the selected meteorological station should be correlated with the actual meteorological parameters of the micro-topography.

[0084] Taking the distance between the weather station and the micro-topography as the objective function, after determining the directional relationship between the location of the micro-topography and the weather station, the directional distance f based on θ is introduced. d (θ), expand the reference direction distance from 9 directions to any direction, and solve the distance in the direction of the centroid:

[0085] f d (θ) = d max ×arccos(cosθ) / π,θ∈[0,2π]

[0086] Where d max Indicates the maximum distance between direction zones.

[0087] Calculate the minimum direction distance f d (θ), the meteorological station corresponding to the minimum directional distance, whose collected meteorological data of temperature, humidity, wind speed and wind direction can be more effectively applied to the prediction of actual meteorological data of micro-topography.

[0088] Step 3: Collect the actual meteorological parameters of the micro-topography through micro-meteorological electronic measuring equipment to solve the design wind speed and design ice thickness of the transmission line;

[0089] The design wind speed and design ice thickness of the transmission lines shall be calculated strictly in accordance with the transmission line design specifications.

[0090] In step 3, the micro-meteorological electronic measurement equipment includes an anemometer and an icing monitoring device. Designers can more accurately solve and give the design wind speed v and design icing thickness D of the transmission line through wind speed collection and icing weight measurement.

[0091]

[0092] Where a and b are the distribution scale parameter and distribution location parameter of the collected wind speed data, respectively, R is the return period used to calculate the design wind speed, d is the diameter of the ground wire of the transmission line, g is the weight of ice per unit length, and ρ is the density of ice in the area.

[0093] Step 4: Based on the actual meteorological parameters of the sampling area and the meteorological data of the nearby meteorological stations, the correlation between the meteorological data and the terrain trend and the location of the transmission line to be built is considered to obtain the meteorological change law of the transmission line to be built in the micro-topography area. The correlation analysis process is as follows: Figure 4 As shown;

[0094] Given the corresponding meteorological parameter temperature T of a nearby meteorological station nm RH nm Humidity, v nm Wind speed and Wind direction, geomorphic features, and the distance between the meteorological station and the micro-topography are used to fit the relationship between the above input and output micro-topography regional transmission line design parameters through the generalized regression neural network algorithm. The BMT-GRNN neural network algorithm can be described as:

[0095] First, the input data is processed and the neuron transfer function in the pattern layer is calculated:

[0096]

[0097] The formula belongs to the model layer, σ is the width coefficient of the Gaussian function, ηi is the sample data set, which is obtained by collecting the geomorphic characteristic parameters of the micro-topography and the actual meteorological parameters through micro-meteorological electronic measurement equipment and satellite positioning scanning; ε i is the learning sample corresponding to the i-th neuron.

[0098] Since the output results are two-dimensional parameters including the design wind speed and the design ice thickness, a model layer output arithmetic sum is calculated in the summation layer, and two model layer output weighted sums are also calculated:

[0099]

[0100] S H With S NJ They are the output sum and weighted sum of the nodes in the summing layer during the algorithm solution process;

[0101] In arithmetic summation, the connection weight of each neuron in the pattern layer and the summation layer is 1; in weighted summation, the connection weight between the i-th neuron in the pattern layer and the j-th summation neuron in the summation layer is the i-th output sample ξ i The jth element in .

[0102] Divide the output of the summation layer, and the result can be summed with the output ξ = (v, D) T The jth element of :

[0103]

[0104] ξ refers to the design wind speed and ice thickness that are solved and used for prediction. This article only uses the design wind speed and ice thickness as the transmission line design parameter objects, which are also the output results. i It refers to the i-th type of output data. Only two types are used in this paper, namely the design wind speed and ice thickness.

[0105] Step 5: According to the meteorological variation law of the transmission line to be built in the micro-topography area, reasonable values ​​of design parameters for the transmission line in the micro-topography area are selected.

[0106] The generalized regression neural network algorithm is used to fit the relationship between the input and output of the micro-topography regional transmission line design parameters in the sample, and then the values ​​of the transmission line design parameters in the entire study area are predicted.

[0107] First, define the study area, observe the transmission line path scanned by satellite, and call the coordinate data and elevation data of the surrounding terrain. After data processing and classification, the terrain elevation type micro-topography is selected as the research object, and multiple samples of this type are collected for subsequent data analysis. Then, taking one of the samples as an example, the cumulative maximum height of the terrain can reach 200m, the slope is 0.5, the slope is 265°, and the transmission tower is built on the top of the mountain. Collect the coordinate data of nearby meteorological stations and their meteorological data to select the best meteorological station. The grid direction matrix between the meteorological station and the line to be built has a similarity of 0.929 with the wind direction matrix of the meteorological station. Moreover, the direct distance between the meteorological station and the line to be built along the surface is the minimum of 2.7km. The temperature of the meteorological station is 25℃, the humidity is 65%, the wind speed is 25m / s, and the wind direction from the top view is 30°. The meteorological conditions at the line to be built are collected using micro-meteorological electronic measuring equipment, and the design wind speed of the transmission line is calculated to be 27m / s and the design ice thickness is 15mm. Based on a large number of samples, we can form:

[0108]

[0109] Each micro-topography type forms its own unique regression prediction equation based on the samples. After that, in the study area, any transmission line to be built in the micro-topography can directly obtain its design wind speed and design ice thickness that meet the engineering requirements based on the landform characteristics, the meteorological conditions of the nearby meteorological station and the distance from the meteorological station to the line to be built.

[0110] Beneficial effects:

[0111] (1) The present invention solves the existing problem of selecting the design parameters of power transmission lines in micro-topography areas. Since the meteorological conditions in the micro-topography area are quite different from those in the surrounding typical areas, the design parameters of power transmission lines calculated by designers based on extensive meteorological data often do not meet the actual engineering requirements. After obtaining the geographical information along the line to be built, the present invention classifies them according to the micro-topography related definitions. Based on the geographical characteristics of different types of micro-topography, the correct design parameters of the power transmission lines in the micro-topography are linked with the meteorological data of the surrounding meteorological stations, and the meteorological formation law of the power transmission lines in the micro-topography area is derived, so that the design parameters of the power transmission lines in the micro-topography area can be quickly and reasonably selected.

[0112] (2) When classifying micro-topography types, the present invention can quickly extract micro-topography related data from the geographic information extracted by satellites through algorithms and directly locate the location of the micro-topography, and then classify the micro-topography data, that is, there is no need to arrange observers to conduct manual terrain surveys on the areas through which the transmission lines to be built pass.

[0113] (3) When selecting meteorological parameters of surrounding meteorological stations, the present invention combines geographic information and direction ranging, and reasonably adopts the meteorological parameters of the most scientific meteorological station in the surrounding area to ensure that the adopted meteorological parameters are related to the actual design parameters of the micro-topography transmission line.

[0114] (4) After deducing the meteorological formation law of the transmission line in the micro-topography area within the research scope, the present invention brings the geomorphic feature data of any micro-topography area and the meteorological parameters of the meteorological stations selected in its surroundings into the law equation, thereby obtaining the transmission line design parameters that meet the actual engineering specifications, thereby reducing the occurrence of safety accidents after the transmission line is built.

[0115] Embodiment 2: Embodiment 2 is a further improvement made on the basis of Embodiment 1. This embodiment is a method for correcting design parameters of a power transmission line applicable to a micro-topography area, which includes:

[0116] After obtaining the geomorphic features of the study area, the micro-topography areas should be screened out. Micro-topography mainly includes four types: alpine watershed, terrain uplift, pass, and canyon wind channel. The meteorological change law of each type is different. Based on the definition of these four types, constraint equations are established to classify and cluster the geomorphic features of height α, slope β and slope direction γ. Like the symbols above, only the height and slope of n groups of triangular faces were obtained before. In order to obtain the height and slope of the area, it is divided into two categories for discussion according to the definition of micro-topography. For the mountain, the subtraction is to find the relative height of the mountain, which refers to the average slope of the mountain. For the mountains, it is compared with the mountain, and there is an additional subscript, which represents the two adjacent mountains, and the other meanings have not changed. As for the numbers in the formula, they are the definition data unique to different types of micro-topography.

[0117] Regarding the definition of micro-topography types, there are two specific situations:

[0118] The line to be built is pre-established on the mountain, and two types of micro-topography can be distinguished: alpine watershed and terrain uplift.

[0119] The alpine watershed is determined based on:

[0120] The basis for determining terrain uplift is:

[0121] The route to be built is pre-established between the mountains, and two types of micro-topography can be distinguished: passes and canyon wind channels.

[0122] The criteria for determining a pass are:

[0123] The basis for determining the canyon wind channel is

[0124] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Other modifications or equivalent substitutions made to the technical solution of the present invention by ordinary technicians in the field should be included in the scope of the claims of the present invention as long as they do not depart from the spirit and scope of the technical solution of the present invention.

Claims

1. A method for correcting design parameters of power transmission lines suitable for micro-topography areas, characterized in that: include: Acquire terrain parameters of the area where the transmission line is to be built, generate a geomorphic feature data set, generate a micro-topography area according to the area where the transmission line is to be built, extract a micro-topography data set according to the geomorphic feature data set, and cluster the micro-topography areas in the area where the transmission line is to be built; Obtain the directional relationship between the micro-topography and the meteorological station and the minimum directional distance, select the best meteorological station near the micro-topography area, and obtain the meteorological data of the selected meteorological station; Collect actual meteorological parameters at the micro-topography to obtain the design wind speed and design ice thickness values ​​of the transmission lines; The meteorological data, as well as the geomorphic features and the distance between the meteorological station and the micro-topography are used as input quantities, the relationship between the input quantity and the output quantity of the micro-topography area transmission line design parameters is fitted, the meteorological change law at the transmission line to be built in the micro-topography area is obtained, and an algorithm model is built; According to the relationship between the input quantity and the output quantity fitted in the sample, the values ​​of the transmission line design parameters in the entire study area are predicted.

2. The method for correcting design parameters of a power transmission line suitable for a micro-topography area according to claim 1, characterized in that: The method for obtaining the terrain parameters of the area where the power transmission line is to be built and generating a geomorphic feature data set comprises: The satellite digital elevation data is used to obtain the longitude, latitude and altitude of the mountain where the line to be built is located and the surrounding mountains. The satellite scans 3 points each time to obtain their longitude, latitude and altitude, and establish three-dimensional spatial coordinates, which are (x n1 ,y n1 , z n1 ), (x n2 ,y n2 , z n2 ), (x n3 ,y n3 , z n3 ), the line connecting the three points constitutes a triangular surface. The slope and aspect calculation based on the irregular triangulated network uses the latitude and longitude of the points and the altitude as well as the trigonometric function calculation formula of three-dimensional space to convert the geomorphic feature data of the height α, slope β and slope aspect γ of the triangular surface area. The calculation process is as follows:

3. The method for correcting design parameters of a power transmission line applicable to a micro-topography area according to claim 2, characterized in that: A method for generating a micro-topography region according to a transmission line area to be built, extracting a micro-topography data set according to the geomorphic feature data set, and clustering the micro-topography regions in the transmission line area to be built comprises: Provide domain description for geomorphic feature datasets, local domain geomorphic features Neighborhood points and The linear relationship is: in Where W ij express In the construction The proportion of the process: The geomorphic feature dataset is reduced in dimension, the dataset is divided by the objective function after dimension reduction, and then the classified geomorphic feature dataset is obtained by using the inverse dimension change method. Its structure before and after dimensionality reduction The proportions occupied are consistent, and the minimum objective function after the dimension reduction of landform features is: ψ represents the landform feature data after dimensionality reduction, which is composed of the low-dimensional data set ψ i There are a total of N data sets after dimensionality reduction, and W is a matrix composed of weight coefficients.

4. The method for correcting design parameters of a power transmission line applicable to a micro-topography area according to claim 2, characterized in that: The method for clustering micro-topography areas in the area where the transmission line is to be built also includes: After obtaining the geomorphic features of the study area, micro-topographic areas were screened out. The types of micro-topographic areas include alpine watersheds, terrain uplifts, passes, and canyon wind tunnels. Constraint equations were established based on different micro-topographic area types to classify and cluster the geomorphic features of height α, slope β, and slope aspect γ. The line to be built is pre-established on the mountain, distinguishing between high mountain watershed and uplift micro-topography types: The alpine watershed is determined based on: The basis for determining terrain uplift is: The line to be built is pre-established between the mountains, distinguishing the micro-topography types of the pass and canyon wind channel: The criteria for determining a pass are: The canyon wind channel is determined based on 5. The method for correcting design parameters of a power transmission line applicable to a micro-topography area according to claim 1, characterized in that: The method of obtaining the directional relationship between the micro-topography and the meteorological station and the minimum directional distance, screening the best meteorological station near the micro-topography area, and obtaining the meteorological data of the screened meteorological station includes: Taking the climate wind direction and the straight-line distance along the ground surface from the meteorological station to the line to be built as reference, the meteorological stations near the micro-topography area are screened, and the meteorological data of the meteorological stations are extracted based on the multi-objective optimization results that simultaneously consider the climate flow direction and adjacent distances: Taking wind direction as the objective function, the space where the micro-topography is located is divided into 9 directional areas {N, S, E, W, NE, SE, SW, NW, O}. The distribution of single meteorological stations in the 9 directional areas is recorded through a matrix, and the directional relationship between micro-topography A and meteorological station B is expressed as: Where D dir1 The element numerator of the first column of the matrix is ​​the number of cells occupied by the meteorological station in each direction of the micro-topography space, S B is the number of triangular face elements occupied by the micro-topography. The size of the weather station is expressed by the number of cells. The direction is determined by counting cells. θ is the horizontal angle between the north direction of the coordinate longitudinal line of the circumcenter of A and the direction of the climatic wind in a clockwise direction. S(D dir1 , D dir2 ) value indicates the similarity between the selected location of the weather station and the climatic wind direction; according to S(D dir1 , D dir2 ) value, judge whether the selected location of the meteorological station is close to the climatic wind direction, and then determine whether the meteorological parameters collected by the selected meteorological station are relevant to the actual meteorological parameters of the micro-topography; Taking the distance between the weather station and the micro-topography as the objective function, after determining the directional relationship between the location of the micro-topography and the weather station, the directional distance fd(θ) based on θ is introduced, and the reference directional distance is extended from 9 directions to any direction to solve the centroid directional distance: f d (θ)=d max ×arccos(cosθ) / π,θ∈[0,2π]; Where d max Indicates the maximum distance between direction areas; The minimum directional distance fd(θ) is calculated, and the meteorological station corresponding to the minimum directional distance is selected, and the meteorological data collected by the meteorological station is used to predict the actual meteorological data of the micro-topography.

6. The method for correcting design parameters of a power transmission line applicable to a micro-topography area according to claim 1, characterized in that: The methods for collecting actual meteorological parameters at the micro-topography and obtaining the design wind speed and design ice thickness values ​​of the transmission line include: The actual meteorological parameters of the micro-topography are collected by micro-meteorological electronic measuring equipment, which includes an anemometer and an icing monitoring device. Designers solve and give the design wind speed v and design icing thickness D of the transmission line through wind speed collection and icing weight measurement. The calculation method is expressed as: Among them, a and b are the distribution scale parameter and distribution location parameter of the collected wind speed data, respectively, R is the return period used to calculate the design wind speed, d is the diameter of the ground wire of the transmission line, g is the weight of ice per unit length, and ρ is the density of ice in the area.

7. The method for correcting design parameters of a power transmission line applicable to a micro-topography area according to claim 1, characterized in that: The meteorological data, geomorphic features, and the distance between the meteorological station and the micro-topography are used as input quantities, and the relationship between the input quantity and the output quantity micro-topography area transmission line design parameters is fitted to obtain the meteorological change law at the transmission line to be built in the micro-topography area. The method for building an algorithm model includes: Given the corresponding meteorological parameter temperature T of a nearby meteorological station nm RH nm Humidity, v nm Wind speed and Wind direction, distance between micro-topography, geomorphic features and meteorological stations are used as inputs. The relationship between the above inputs and output micro-topography regional transmission line design parameters is fitted through the generalized regression neural network algorithm. The algorithm model built by the generalized regression neural network algorithm is described as: First, the input data is processed and the neuron transfer function in the pattern layer is calculated: Where σ is the width coefficient of the Gaussian function, ηi is the sample data set, ε i is the learning sample corresponding to the i-th neuron; The output result is a two-dimensional parameter including the design wind speed and the design ice thickness. In the summation layer, an arithmetic sum of the model layer output is calculated, and a weighted sum of the two model layer outputs is calculated: S H With S NJ They are the output sum and weighted sum of the nodes in the summing layer during the algorithm solution process; In arithmetic summation, the connection weight of each neuron in the pattern layer and the summation layer is 1; in weighted summation, the connection weight between the i-th neuron in the pattern layer and the j-th summation neuron in the summation layer is the i-th output sample ξ i The jth element in ; Divide the output of the summation layer by D, which is the ice thickness, and the result can be summed with the output ξ = (v, D) T The jth element of : ξ is the design wind speed and ice thickness solved and used for prediction, ξ i is the i-th data of the output.

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