Method and device for calculating ground inclination of power transmission line based on information entropy weight

Abstract

The application discloses a power transmission line ground inclination calculation method and device based on information entropy weight, and comprises the following steps: S1, constructing a three-dimensional scene; S2, sampling equidistantly left and right along the direction of the vertical line of the overhead line of each base tower, and obtaining the original slope value of each sampling point; S3, constructing an original slope value matrix R based on the original slope value of all sampling points on the left side or the right side; S4, performing normalization processing on the original slope value matrix R, and obtaining a normalized matrix R ′ ; S5, constructing a probability matrix P; S6, calculating the entropy value of each base tower in the probability matrix P; S7, calculating the slope value weight of each sampling point according to the entropy value; S8, modifying the original slope value by using the slope value weight, and obtaining the ground inclination on the left side or the right side of the tower; S9, selecting the other side of the vertical line of the tower to the overhead line, and repeating the process described in steps S3-S8, so as to calculate the ground inclination of the tower on the other side of each base tower. The application can improve the accuracy of ground inclination calculation.

Description

Technical Field

[0001] This invention relates to the field of power system lightning protection technology, specifically to a method and apparatus for calculating the ground tilt angle of transmission lines based on information entropy weights. Background Technology

[0002] Transmission lines are a fundamental component of the power grid, and their safety, reliability, and stability are crucial for ensuring the stable operation of the power system. Because transmission lines are exposed to the natural environment for extended periods, and often traverse open fields, hills, or mountains, they are frequently subjected to lightning strikes during the rainy season, posing a severe challenge to their safety, reliability, and stability. Lightning strikes account for a high percentage of all power system failures, and the resulting faults are often the most severe, seriously threatening the safety, reliability, and stability of the power grid.

[0003] Current methods for evaluating the lightning protection performance of transmission lines need to comprehensively consider factors such as lightning activity along the line corridor, topographic features, line structure, insulation configuration, and lightning protection measures. Among these, the topographic features are quantified using ground inclination angle. However, traditional algorithms often simply convert the slope value, such as taking the maximum, minimum, or average of multiple sampling points, without comprehensively considering the complex terrain conditions of the tower area. Since the ground is always undulating, the positive contribution of terrain parameters to the lightning protection performance calculation results is not high. Summary of the Invention

[0004] The purpose of this invention is to provide a method and apparatus for calculating the ground tilt angle of transmission lines based on information entropy weights, so as to improve the accuracy of ground tilt angle calculation.

[0005] This invention is achieved through the following technical solution:

[0006] The method for calculating the ground tilt angle of transmission lines based on information entropy weights includes the following steps:

[0007] S1. Construct a 3D scene;

[0008] S2. In the three-dimensional scene, sample at equal intervals to the left and right along the vertical direction of the overhead line of each tower to obtain the original slope value of each sampling point.

[0009] S3. Construct an original slope value matrix R(n, m) based on the original slope values ​​of all sampling points on the left or right. The original slope value matrix R contains n*m elements, where n is the number of towers and m is the number of sampling points on the left or right.

[0010] S4. Normalize the original slope value matrix R to obtain the normalized matrix R′;

[0011] S5. Calculate the weight of each sample in the normalized matrix R′, and construct the probability matrix P based on the weight of each sample.

[0012] S6. Calculate the entropy value of each base tower in the probability matrix P based on the probability distribution function, and construct the entropy value matrix E from the entropy values ​​of all towers;

[0013] S7. Obtain the difference coefficients of each base tower based on the entropy value obtained in step S6, calculate the slope weight of each sampling point based on the difference coefficients, and construct the weight matrix W.

[0014] S8. Based on the slope value weight obtained in step S7, modify the original slope value to obtain the ground inclination angle on the left or right side of the tower.

[0015] S9. Select the other side of the vertical line between the tower and the direction of the transmission line, and repeat the process described in steps S3-S8 to calculate the ground tilt angle of the other side of each tower.

[0016] The three-dimensional scene construction technology used in step S1 of this invention is an existing technology. By using three-dimensional parametric modeling technology, three-dimensional power grid transmission lines can be quickly constructed. At the same time, three-dimensional digital elevation data can be superimposed to display the shape of the line body in the three-dimensional virtual space, as well as the terrain undulations of the transmission line corridor and its surroundings. That is, the three-dimensional scene can realistically display the power elements such as the towers of the transmission line, as well as three-dimensional terrain information, and has the function of panoramic display of the geographical space where the transmission line is located.

[0017] The terrain parameter calculation method of this invention obtains the topographic slope sampling point matrix R(n,m) of each tower of the power transmission line in the vertical direction of the power transmission line in a three-dimensional real scene. For each sampling point, a slope weight based on information entropy is calculated, and finally the left and right terrain parameter slope values ​​of each tower are calculated, thereby obtaining the left and right ground tilt angle values ​​of each tower. Compared with the existing method of taking the maximum or minimum value of the slope value or the average of multiple sampling points, this method improves the accuracy of ground tilt angle calculation.

[0018] Furthermore, in step S1, the three-dimensional scene parametrically models the overhead power transmission lines of the power grid and overlays terrain data to create a panoramic simulation display.

[0019] Furthermore, in step S4, the normalization range is (0, 1).

[0020] Furthermore, in step S4, the normalization process is as follows:

[0021] The difference between the original slope value of each sampling point in each tower and the smallest original slope value among all sampling points of the corresponding tower is denoted as h1. The difference between the largest original slope value among all sampling points of the corresponding tower and the smallest original slope value among all sampling points of the corresponding tower is denoted as h2. The ratio of h1 to h2 is the normalized value. The normalized values ​​of each sample constitute the normalization matrix R′.

[0022] Furthermore, in step S5, the calculation process for the proportion of each sample is as follows:

[0023] The ratio of the normalized value of a sampling point in the same base tower to the sum of the normalized values ​​of all sampling points in the same base tower.

[0024] Furthermore, in step S5, the weight of each sample is greater than 0.

[0025] Furthermore, in step S7, the difference coefficient is positively correlated with the weight.

[0026] Furthermore, in step S7, the weight calculation process is as follows:

[0027] The ratio of the difference coefficient of each base tower to the sum of the difference coefficients of all towers.

[0028] Further, in step S8, the ground tilt angle of the tower is obtained based on the condition that the ground tilt angle of the i-th tower is equal to the terrain slope parameter value calculated based on entropy weight of the i-th tower.

[0029] A device for calculating the ground tilt angle of a power transmission line, comprising:

[0030] The 3D scene building module is used to build and store 3D scenes;

[0031] The data acquisition module is used to collect the original slope values ​​at each sampling point;

[0032] The normalization module is used to obtain the original slope values ​​from the data acquisition module and perform normalization processing to obtain the normalization matrix R′.

[0033] The proportion calculation module is used to obtain the data in the normalized matrix R′, calculate the proportion of each sample in the normalized matrix R′, and construct the probability matrix P;

[0034] The entropy calculation module is used to obtain data from the probability matrix P and calculate the entropy value of each base tower in the probability matrix P, and construct the entropy matrix E from the entropy values ​​of all towers.

[0035] The weight calculation module is used to obtain the entropy values ​​in the entropy matrix E, calculate the slope weight of each sampling point, and construct the weight matrix W.

[0036] The ground tilt angle calculation module is used to obtain the weight matrix W and the original slope value matrix R, modify the original slope value with the slope value weights, and obtain the ground tilt angle of the tower.

[0037] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0038] 1. This invention takes into account the influence of the terrain near the tower on the value of the ground inclination angle, avoids the effect of reducing the slope of the terrain by taking the maximum, minimum or average value, and fully considers the terrain near the tower. It is a comprehensive value of the ground inclination angle, which improves the accuracy of the ground inclination angle calculation.

[0039] 2. This invention improves the calculation accuracy of the lightning strike risk coefficient, providing a more precise service for the calculation and early warning of the lightning strike risk coefficient. Attached Figure Description

[0040] The accompanying drawings, which are included to provide a further understanding of embodiments of the invention and form part of this application, do not constitute a limitation thereof. In the drawings:

[0041] Figure 1 This is a flowchart of the present invention. Detailed Implementation

[0042] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the embodiments and accompanying drawings. The illustrative embodiments and descriptions of the present invention are only used to explain the present invention and are not intended to limit the present invention.

[0043] Example 1:

[0044] like Figure 1 As shown, the method for calculating the ground tilt angle of transmission lines based on information entropy weights includes the following steps:

[0045] S1. Construct a 3D scene; The 3D scene parametrically models the overhead power transmission lines and overlays terrain and other data for panoramic simulation display; It can realistically display power elements such as towers of the transmission lines, as well as 3D terrain and other information, and has the function of panoramic display of the geographical space where the transmission lines are located.

[0046] S2. In the three-dimensional scene, sample at equal intervals to the left and right along the vertical direction of the overhead line of each tower to obtain the original slope value of each sampling point.

[0047] That is, the same number of sampling points are set on the left and right sides of each tower. For example, m sampling points are set on the left side of each tower and m sampling points are set on the corresponding right side.

[0048] S3. Construct an original slope value matrix R(n, m) based on the original slope values ​​of all sampling points on the left or right. The original slope value matrix R contains n*m elements (samples), where n is the number of towers and m is the number of sampling points on the left or right.

[0049] The original slope value matrix R(n, m) contains n rows and m columns. Assuming an overhead transmission line has N towers, when calculating the ground inclination angle, samples are taken at equal intervals to the left and right along the vertical direction of the overhead line from each tower. Assuming there are M sampling points on each side, the terrain slope is sampled to obtain the original slope value matrix R. This R matrix is ​​a matrix (n = N, m = M). A sample in the original slope value matrix R(n, m) is represented as x. ij , 1≤i≤N, 1≤j≤M, x ij This represents the original slope value of the j-th sampling point in the i-th tower.

[0050] S4. Normalize the original slope value matrix R to obtain the normalized matrix R′;

[0051] The normalization process is as follows:

[0052] The difference between the original slope value of each sampling point in each tower and the smallest original slope value among all sampling points of the corresponding tower is denoted as h1. The difference between the largest original slope value among all sampling points of the corresponding tower and the smallest original slope value among all sampling points of the corresponding tower is denoted as h2. The ratio of h1 to h2 is the normalized value. The normalized values ​​of each sample constitute the normalization matrix R′. The normalization calculation formula is shown in equation (1):

[0053]

[0054] Where x ij ∈R(n,m), and satisfy i∈(1,n), j∈(1,m), max{x i1 ,x i2 ,…,x ij} and min{x i1 ,x i2 ,…,x ij} are the computation sets {x i1 ,x i2 ,…,x ij The maximum and minimum values ​​in} can be calculated using formula (1), which yields the normalized matrix R′(n, m). To avoid zero-value calculations, the normalization range should be between (0, 1).

[0055] S5. Calculate the weight of each sample in the normalized matrix R′, and construct the probability matrix P(n,m) based on the weight of each sample.

[0056] The calculation process for the proportion of each sample is as follows:

[0057] The ratio of the normalized value of a sampling point in the same base tower to the sum of the normalized values ​​of all sampling points in the same base tower;

[0058] The formula for calculating the proportion (probability) of the j-th sampling point in the i-th tower is shown in equation (2):

[0059]

[0060] Where r ij ∈R′(n,m), which is the normalized matrix of the original values ​​of the terrain parameter slope; where p ij The probability value of occurrence corresponding to the slope value of each sampling point.

[0061] S6. Calculate the entropy value of each base tower in the probability matrix P based on the probability distribution function formula (3), and construct the entropy value matrix E with the entropy values ​​of all towers.

[0062]

[0063] Where p ij The probability of occurrence of the slope value at each sampling point should satisfy p to avoid zero-value calculations. ij >0.

[0064] S7. Obtain the difference coefficients of each base tower based on the entropy value obtained in step S6, calculate the slope weight of each sampling point based on the difference coefficients, and construct the weight matrix W.

[0065] The weight calculation process is as follows:

[0066] The ratio of the difference coefficient of each base tower to the sum of the difference coefficients of all towers;

[0067] The formula for calculating the weight is shown in formula (4):

[0068]

[0069] Where w ij ∈W, where its value is the slope value weight of the j-th sampling point, E j ∈E, where is the entropy value of the j-th sampling point, j∈(1,m); where (1-E j ) represents the difference coefficient of the j-th indicator. The higher the difference coefficient, the greater the weight.

[0070] S8. Based on the slope value weight obtained in step S7, modify the original slope value. The specific calculation is shown in formula (5) to obtain the ground inclination angle on the left or right side of the tower.

[0071]

[0072] Take V t h eta(i) =V slope(i) V t h eta(i) V is the ground tilt angle of the i-th tower. slope(i) v is the terrain slope parameter value calculated based on entropy weight for the i-th tower. slope(i,j) It is the original terrain slope value of the j-th sampling point of the i-th tower, and satisfies condition v. slope(i,j) ∈R(n,m), w ij It is the entropy weight of the terrain slope value at the j-th sampling point.

[0073] S9. Select the other side of the vertical line between the tower and the direction of the transmission line, and repeat the process described in steps S3-S8 to calculate the ground tilt angle of the other side of each tower.

[0074] This embodiment considers the influence of the terrain near the tower on the value of the ground inclination angle, avoiding the effect of reducing the slope of the terrain by taking the maximum, minimum or average values. It takes into full account the terrain near the tower and is a comprehensive value of the ground inclination angle, which improves the accuracy of the ground inclination angle calculation.

[0075] The following is a specific application example of this embodiment (a certain line contains 20 towers, numbered 1-20#):

[0076] 1) Data preprocessing: acquire terrain DEM data, generate slope data, and acquire sampling point data.

[0077] 2) As shown in Appendix Table 1, terrain slope values ​​were sampled at equal intervals on the right side of the tower. This data is the original slope value matrix R(n,m):

[0078] Table 1. Raw terrain sampling data (right side)

[0079]

[0080]

[0081] 3) After sampling, in order to eliminate dimensional differences, the data is processed to be dimensionless and normalized. To avoid zero-value calculations, the quantization value should be set to (0, 1], resulting in the normalization matrix R′(n, m), as shown in Table 2 below:

[0082] Table 2 Normalized matrix R′(n, m)

[0083]

[0084] 4) After normalization, matrix P(n,m) can be calculated, as shown in Table 3 below:

[0085] Table 3 shows the matrix P(n,m).

[0086] 0m 20m 40m 60m 80m 100m 120m 140m 160m 180m 200m 220m 240m 0.13038 0.09227 0.02257 0.00021 0.00360 0.01904 0.03757 0.04922 0.04395 0.02444 0.02127 0.02137 0.03308 0.07248 0.05802 0.05777 0.00021 0.01499 0.08707 0.03043 0.02504 0.03783 0.04458 0.05317 0.04836 0.06208 0.04264 0.04983 0.04336 0.02759 0.01702 0.00194 0.00043 0.00006 0.00066 0.00798 0.03223 0.06250 0.07868 0.08634 0.06242 0.07513 0.05233 0.00407 0.00017 0.00743 0.07647 0.07718 0.08152 0.08004 0.07795 0.07868 0.12996 0.09085 0.00139 0.06095 0.05240 0.08707 0.01272 0.00006 0.01051 0.00430 0.02463 0.01389 0.00016 0.00026 0.01461 0.05708 0.07732 0.09688 0.05722 0.05190 0.05625 0.06397 0.07935 0.08274 0.07945 0.07823 0.00026 0.05160 0.06852 0.06942 0.07889 0.06440 0.07397 0.06631 0.08063 0.07805 0.05625 0.04703 0.04528 0.01389 0.07173 0.02458 0.05343 0.07173 0.05508 0.07451 0.08258 0.08063 0.06290 0.04577 0.04122 0.03954 0.09165 0.06968 0.04965 0.00021 0.02059 0.05857 0.08903 0.08311 0.07835 0.08277 0.08207 0.07768 0.07370 0.08812 0.04202 0.00486 0.01476 0.01200 0.00413 0.00019 0.00610 0.01197 0.04732 0.07587 0.07945 0.07532 0.06970 0.02299 0.03451 0.04592 0.07107 0.06209 0.07569 0.06330 0.07819 0.08460 0.06015 0.04365 0.03819 0.12664 0.10557 0.08232 0.05538 0.02959 0.05808 0.08036 0.05865 0.03928 0.00274 0.00017 0.03501 0.07208 0.00026 0.00036 0.00563 0.01429 0.05869 0.05751 0.04261 0.05785 0.07012 0.07791 0.08286 0.06886 0.04243 0.04313 0.01104 0.01145 0.01145 0.01345 0.03211 0.06211 0.07173 0.08063 0.08078 0.07893 0.07590 0.07822 0.10212 0.08247 0.08305 0.08125 0.09098 0.06138 0.05672 0.03693 0.01912 0.00017 0.02518 0.03619 0.07868 0.01098 0.05952 0.10978 0.08262 0.03846 0.02735 0.03666 0.04686 0.04366 0.05039 0.02779 0.01572 0.00016 0.06970 0.02681 0.06970 0.10334 0.10663 0.08677 0.08796 0.07754 0.06048 0.06041 0.06114 0.06423 0.06864 0.04113 0.07769 0.10866 0.10334 0.10222 0.06906 0.05884 0.02867 0.01567 0.02495 0.02134 0.00751 0.00016 0.00026 0.03942 0.03196 0.04264 0.04124 0.07412 0.08589 0.08311 0.07609 0.07124 0.05966 0.05838 0.05652 0.01949 0.04286 0.06948 0.10334 0.07550 0.03682 0.03498 0.03022 0.03107 0.03359 0.02874 0.04566 0.00016

[0087] 5) The E matrix can be calculated from the matrix P(n,m). This matrix is ​​a row vector, as shown in Table 4 below:

[0088] Table 4E Matrix

[0089] 0m 20m 40m 60m 80m 100m 120m 140m 160m 180m 200m 220m 240m 0.02562 0.045061 0.061847 0.078297 0.065116 0.040579 0.039152 0.0353 0.036008 0.03805 0.034051 0.047042 0.00046

[0090] 6) Calculate the weight matrix based on the E matrix, as shown in Table 5 below:

[0091] Table 5 W Weight Matrix

[0092] 0m 20m 40m 60m 80m 100m 120m 140m 160m 180m 200m 220m 240m 0.07824 0.07668 0.07533 0.07401 0.0750 0.07704 0.07715 0.07746 0.07740 0.07724 0.07756 0.07652 0.08026

[0093] 7) Calculate the terrain slope value for each tower based on the weights in the weight matrix W, and convert it into a ground tilt angle value, as shown in Table 6 below:

[0094] Table 6. Ground tilt values ​​based on information entropy weights

[0095]

[0096]

[0097] Example 2:

[0098] A device for calculating the ground tilt angle of a power transmission line, comprising:

[0099] The 3D scene building module is used to build and store 3D scenes;

[0100] The data acquisition module is used to collect the original slope values ​​at each sampling point;

[0101] The normalization module is used to obtain the original slope values ​​from the data acquisition module and perform normalization processing to obtain the normalization matrix R′.

[0102] The proportion calculation module is used to obtain the data in the normalized matrix R′, calculate the proportion of each sample in the normalized matrix R′, and construct the probability matrix P;

[0103] The entropy calculation module is used to obtain data from the probability matrix P and calculate the entropy value of each base tower in the probability matrix P, and construct the entropy matrix E from the entropy values ​​of all towers.

[0104] The weight calculation module is used to obtain the entropy values ​​in the entropy matrix E, calculate the slope weight of each sampling point, and construct the weight matrix W.

[0105] The ground tilt angle calculation module is used to obtain the weight matrix W and the original slope value matrix R, modify the original slope value with the slope value weights, and obtain the ground tilt angle of the tower.

[0106] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for calculating the ground tilt angle of transmission lines based on information entropy weights, characterized in that, Includes the following steps: S1. Construct a 3D scene; S2. In the three-dimensional scene, sample at equal intervals to the left and right along the vertical direction of the overhead line of each tower to obtain the original slope value of each sampling point. S3. Construct the original slope value matrix R based on the original slope values ​​of all sampling points on the left or right; S4. Normalize the original slope value matrix R to obtain the normalized matrix. ; S5. Calculate the normalized matrix. The proportion of each sample in the sample is determined, and a probability matrix P is constructed based on the proportion of each sample. S6. Calculate the entropy value of each base tower in the probability matrix P based on the probability distribution function, and construct the entropy value matrix E from the entropy values ​​of all towers; S7. Obtain the difference coefficient of each base tower based on the entropy value obtained in step S6, calculate the slope value weight of each sampling point based on the difference coefficient, and construct the weight matrix W. S8. Based on the slope value weight obtained in step S7, modify the original slope value to obtain the ground inclination angle on the left or right side of the tower. S9. Select the other side of the vertical line between the tower and the direction of the transmission line, and repeat the process described in steps S3-S8 to calculate the ground tilt angle of the tower on the other side of each tower. The formula for calculating the entropy value in step S6 is as follows: ； In the formula This represents the proportion of slope values ​​at each sampling point. ; The formula for calculating the weight in step S7 is as follows: ； In the formula W is the slope value weight of the j-th sampling point; , where is the entropy value of the j-th sampling point; j (1, m); (1- ) is the difference coefficient of the j-th indicator.

2. The method for calculating the ground tilt angle of transmission lines based on information entropy weights according to claim 1, characterized in that, In step S1, the 3D scene parametrically models the overhead power transmission lines and overlays terrain data for panoramic simulation display.

3. The method for calculating the ground tilt angle of transmission lines based on information entropy weights according to claim 1, characterized in that, In step S4, the normalization range is (0, 1).

4. The method for calculating the ground tilt angle of transmission lines based on information entropy weights according to claim 1, characterized in that, In step S4, the normalization process is as follows: The difference between the original slope value of each sampling point in each tower and the minimum original slope value among all sampling points of the corresponding tower is denoted as h1. The difference between the maximum original slope value among all sampling points of the corresponding tower and the minimum original slope value among all sampling points of the corresponding tower is denoted as h2. The ratio of h1 to h2 is the normalized value. The normalized values ​​of each sample constitute a normalization matrix. .

5. The method for calculating the ground tilt angle of transmission lines based on information entropy weights according to claim 1, characterized in that, In step S5, the calculation process for the proportion of each sample is as follows: The ratio of the normalized value of a sampling point in the same base tower to the sum of the normalized values ​​of all sampling points in the same base tower.

6. The method for calculating the ground tilt angle of transmission lines based on information entropy weights according to claim 1, characterized in that, In step S5, the weight of each sample is greater than 0.

7. The method for calculating the ground tilt angle of transmission lines based on information entropy weights according to claim 1, characterized in that, In step S7, the difference coefficient is positively correlated with the weight.

8. The method for calculating the ground tilt angle of transmission lines based on information entropy weights according to claim 1, characterized in that, In step S7, the weight calculation process is as follows: The ratio of the difference coefficient of each base tower to the sum of the difference coefficients of all towers.

9. The method for calculating the ground tilt angle of transmission lines based on information entropy weights according to claim 1, characterized in that, In step S8, the ground tilt angle of the i-th tower is obtained based on the condition that the ground tilt angle of the i-th tower is equal to the terrain slope parameter value calculated based on entropy weight.

10. A ground tilt angle calculation device for transmission lines, used to implement the ground tilt angle calculation method for transmission lines based on information entropy weight as described in any one of claims 1-9, characterized in that, include: The 3D scene building module is used to build and store 3D scenes; The data acquisition module is used to collect the original slope values ​​at each sampling point; The normalization module is used to obtain the raw slope values ​​from the data acquisition module and perform normalization processing to obtain a normalization matrix. ; The proportion calculation module is used to obtain the normalized matrix. The data in the dataset is used to calculate the normalized matrix. The proportion of each sample in the sample is determined, and a probability matrix P is constructed. The entropy calculation module is used to obtain data from the probability matrix P and calculate the entropy value of each base tower in the probability matrix P, and construct the entropy matrix E from the entropy values ​​of all towers. The weight calculation module is used to obtain the entropy values ​​in the entropy matrix E, calculate the slope weight of each sampling point, and construct the weight matrix W. The ground tilt angle calculation module is used to obtain the weight matrix W and the original slope value matrix R, modify the original slope value with the slope value weights, and obtain the ground tilt angle of the tower.

Images