Multi-tower-shaped tower grounding resistance optimization method based on Monte Carlo algorithm

Abstract

The invention discloses a multi-tower-shaped tower grounding resistance optimization method based on a Monte Carlo algorithm, and relates to the technical field of power system grounding, and the method comprises the following steps: according to a long power transmission line back-strike trip-out rate requirement, a tower shape requirement, along-line topographic features and a plurality of tower-shaped tower grounding resistance construction requirements, carrying out grounding resistance optimization on a plurality of tower-shaped towers; establishing a multi-tower-shaped power transmission line tower grounding resistance optimization model; setting parameters of a Monte Carlo method, and randomly generating a plurality of groups of soil resistivity grades and grounding resistance values corresponding to the soil resistivity grades; solving the multi-tower-shaped power transmission line tower grounding resistance optimization model through a Monte Carlo method; the optimal value solved by the Monte Carlo method is converted into a corresponding soil resistivity grade and a corresponding grounding resistance value, and the soil resistivity grade and the corresponding grounding resistance value serve as the optimal design scheme of the grounding resistance of the multi-tower-shaped power transmission line tower; on one hand, construction cost increase caused by too small grounding resistance value can be avoided, and on the other hand, the overall lightning protection performance of the multi-tower-shaped power transmission line is ensured.

Description

Technical Field

[0001] The invention relates to the technical field of power system grounding, and in particular to a method for optimizing grounding resistance of a multi-tower pole tower based on a Monte Carlo algorithm. Background Art

[0002] According to the current power industry standards, for high-voltage and above transmission lines with lightning arresters installed, the power frequency grounding impedance limit of each level of towers is specified only by dividing the soil resistivity level. However, due to the differences in the terrain, tower type, tower parameters and voltage level of the transmission lines, the lightning protection levels of different transmission lines are significantly different. Relying solely on soil resistivity data to determine the power frequency grounding impedance limit of towers often results in the lightning protection performance of some transmission lines being too low, affecting the safety of power transmission, while the lightning protection performance of some lines is too strict, resulting in high power frequency grounding resistance costs for towers. Especially in some long-distance transmission lines, the difference in tower types will aggravate this phenomenon. Therefore, for different transmission lines, a reasonable method is used to design the soil resistivity division and the power frequency grounding impedance limit of towers, which can effectively improve the lightning protection and economy of transmission lines. Summary of the invention

[0003] In view of the above technical problems, the present invention proposes a multi-tower tower grounding resistance optimization method based on a Monte Carlo algorithm, comprising the following steps:

[0004] S1. According to the requirements of the back-tripping rate of long transmission lines, tower shape requirements, terrain characteristics along the line and the construction requirements of grounding resistance of various tower shapes, an optimization model of grounding resistance of multi-tower transmission line towers is established;

[0005] S2, setting the parameters of the Monte Carlo method, and randomly generating several groups of soil resistivity classifications and their corresponding ground resistance values;

[0006] S3, solving the grounding resistance optimization model of multi-tower transmission line towers by Monte Carlo method;

[0007] S4. Convert the optimal value obtained by the Monte Carlo method into the corresponding soil resistivity classification and its corresponding grounding resistance value as the optimal design scheme for the grounding resistance of multi-tower transmission line towers.

[0008] Furthermore, the optimization design model of multi-tower transmission line towers includes:

[0009] Construct objective function: To improve the economic efficiency of long transmission lines, the overall counter-tripping rate N of the line a It needs to be as close as possible to the transmission line counter-tripping rate control index N max ; To ensure the lightning protection of long transmission lines, it is required to reduce the local backlash tripping rate by more than N maxAccording to the above requirements, the two objectives are transformed into an objective function by weighted average, and the objective function is established as follows:

[0010]

[0011] In the formula, μ represents the weight coefficient, 0≤μ≤1;

[0012] As shown in the above objective function, the first goal is to improve the economy of long transmission lines, that is, N max -N a Approaching 0; To ensure the order of magnitude of the two objectives is consistent, the objective function is normalized, that is, (N max -N all ) / N max .

[0013] As the objective function above, the second objective is to ensure the lightning protection of long transmission lines, that is Approaching 0, where L k It represents the proportion of soil resistivity level k;

[0014] As shown in the objective function above, μ is an adjustable parameter, which is adjusted according to different engineering requirements. The larger μ is, the more important the economy of long transmission lines is, and the smaller μ is, the more important the lightning protection of long transmission lines is.

[0015] Furthermore, the multi-tower transmission line tower optimization design model also includes:

[0016] Construct the first set of conditions: In order to ensure the feasibility of transmission line construction, it is necessary to set the upper limit of soil resistivity classification. k When there are 1 level, the upper limit of soil resistivity of level k is ρ k , the upper limit of the soil resistivity of the k-1th level is ρ k-1 , the soil resistivity classification must satisfy the requirement that the difference between the previous and next levels is greater than or equal to 500Ω·m; that is, ρ k -ρ k-1 ≥500, 2≤k≤n k ;

[0017] Construct the second constraint: Since the grounding resistance value is positively correlated with the soil resistivity during the construction process, it is necessary to set the upper limit of the grounding resistance value corresponding to the same level of soil resistivity. The upper limit of the grounding resistance of the kth level is marked as R k , the upper limit of the grounding resistance of the k-1th level is R k-1 , the difference between the grounding resistance values ​​of the two levels before and after is greater than or equal to 5Ω, and the grounding resistance of the kth level is marked as R k , the grounding resistance of the k-1th level is R, that is, R k -R k-1≥5, 2≤k≤n k ;

[0018] Construct the third constraint: To meet the feasibility of the transmission line grounding design implementation, when the soil resistivity grade ρ k ≥ρ down , 2≤k≤n k When R k ≥R down , 2≤k≤n k ; where ρ down is the lower limit of the k-th soil resistivity range, R down is the minimum value of the kth level grounding resistance;

[0019] Construct the fourth constraint: To ensure the overall lightning protection of long transmission lines, the overall counter-tripping rate of the transmission lines is required to be N a Less than the transmission line back-tripping rate control index N max , that is, N a ≤N max ;

[0020] Where N a The proportional function L(ρ x ), counter-tripping rate fitting function N i , weighted summation is obtained; the specific calculation formula is as follows:

[0021] N a =∑ k ∑ i (N i (L(ρ k )-L(ρ k-1 ))), 2≤k≤n k

[0022] Where i represents the i-th tower shape, N i It represents the counter-tripping rate corresponding to the i-th tower shape.

[0023] Furthermore, the parameters of the Monte Carlo method are set to randomly generate several groups of soil resistivity classification and ground resistance values ​​including:

[0024] Determine the maximum number of cycles S and the objective function weight coefficient μ of the Monte Carlo algorithm: According to the value range of soil resistivity and ground resistance, randomly generate S groups of soil resistivity classification and ground resistance values, and the data group is marked as [ρ k R k ]1.

[0025] Furthermore, the soil resistivity classification and ground resistance values ​​that meet the constraints are screened out, including:

[0026] In the above S arrays, according to the constraints one, two, three, and four, the data group that meets all the conditions is selected and marked as [ρ k R k ]2.

[0027] Furthermore, a set of soil resistivity classification and ground resistance values ​​with the minimum objective function is found, including:

[0028] In the above data set [ρ k R k ]2, the objective function is calculated, and a set of soil resistivity classification and grounding resistance values ​​with the smallest objective function value is selected as the optimal solution, that is, as the optimal design scheme for grounding resistance.

[0029] Furthermore, a fitting function N is established between the multi-tower back-tripping rate N and the grounding resistance R. i Before (R), it is necessary to determine the pole striking rate g at the corresponding position j of each tower based on the structural dimensions and insulation parameters of various typical towers along the transmission line, the lightning parameters and terrain parameters along the line. j , arc construction rate η at position j j , the parameter P of the probability distribution of the lightning current amplitude at position j c，j , the density of ground-to-ground flash at location j is N g，j , the conductor height H of the tower used at position i j , the distance b between the tower-shaped lightning conductors used at position j j , and establish the fitting function of the grounding resistance R and the back-strike lightning resistance level I, and calculate the back-strike tripping rate N through the back-strike lightning resistance level and the terrain parameters along the line.

[0030] Furthermore, a function N(R) between the above back-tripping rate N and the grounding resistance R is established, including:

[0031] According to different tower shapes and terrain parameters, the corresponding back-attack tripping rate is calculated. The specific calculation formula is as follows:

[0032]

[0033] Among them, N L，j It represents the number of lightning strikes on the line per 100 km per year at position j. The calculation formula is as follows:

[0034] N L，j =0.1×N g，j ×(4H j +b j )

[0035] Among them, I j Represents the lightning strike resistance level at position j. According to the data set of grounding resistance R and lightning strike resistance level I, the lightning strike resistance level I is established.j The quadratic function between the ground resistance R is as follows:

[0036] I j (R) = a2R 2 +a1R+a0.

[0037] Furthermore, the proportional function L(ρ) of soil resistivity is established as above. x ),include:

[0038] According to the soil resistivity ρ dataset along the multi-tower transmission line, the soil resistivity proportional function is established as follows:

[0039]

[0040] Where L(ρ x ) indicates that the soil resistivity data set is less than ρ x % of.

[0041] Compared with the prior art, the invention has the following beneficial effects: the method for optimizing the grounding resistance of a multi-tower transmission line tower based on the Monte Carlo algorithm can be used to reasonably design soil resistivity classification and grounding resistance values ​​for different tower shapes, ensuring that the total counter-attack trip rate is as close as possible to the counter-attack trip rate control index of the transmission line, and at the same time, the proportion of the local counter-attack trip rate being greater than the counter-attack trip rate control index is minimized. On the one hand, it can avoid the increase in construction costs caused by too small a grounding resistance value, and on the other hand, it can ensure the overall lightning protection performance of the multi-tower transmission line. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 It is a model framework diagram of the multi-tower pole tower grounding resistance optimization method based on the Monte Carlo algorithm of the present invention.

[0043] Figure 2 The present invention is a flowchart of an algorithm implementation of a method for optimizing grounding resistance of a multi-tower pole tower based on a Monte Carlo algorithm. DETAILED DESCRIPTION

[0044] The present invention will be further described below in conjunction with specific embodiments. The illustrative embodiments and descriptions of the present invention are used to explain the present invention but are not intended to limit the present invention.

[0045] The present invention provides a method for optimizing the grounding resistance of a multi-tower pole tower based on a Monte Carlo algorithm. The design principle of the present invention is that the design of the grounding resistance of a multi-tower transmission line pole tower should meet the control index of the transmission line back-tripping rate, and in combination with the requirements of the engineering implementation of the pole tower grounding design, an optimization model for the grounding resistance of a multi-tower transmission line pole tower is established, and the Monte Carlo algorithm is used to solve the optimal value of the objective function, thereby calculating the optimal design scheme of the grounding resistance.

[0046] Example: Figure 1-Figure 2 As shown, the present invention proposes a multi-tower tower grounding resistance optimization method based on Monte Carlo algorithm, which includes the following steps:

[0047] S1. According to the requirements of the back-tripping rate of long transmission lines, tower shape requirements, terrain characteristics along the line and the construction requirements of grounding resistance of various tower shapes, an optimization model of grounding resistance of multi-tower transmission line towers is established;

[0048] S2, setting the parameters of the Monte Carlo method, and randomly generating several groups of soil resistivity classifications and their corresponding ground resistance values;

[0049] S3, solving the grounding resistance optimization model of multi-tower transmission line towers by Monte Carlo method;

[0050] S4. Convert the optimal value obtained by the Monte Carlo method into the corresponding soil resistivity classification and its corresponding grounding resistance value as the optimal design scheme for the grounding resistance of multi-tower transmission line towers.

[0051] In establishing the fitting function N between the multi-tower back-tripping rate N and the grounding resistance R i Before (R), it is necessary to determine the pole striking rate gj at position j of each tower and the arcing rate η at position j based on the structural dimensions and insulation parameters of various typical towers along the transmission line, the lightning parameters and terrain parameters along the line. j , the parameter P of the probability distribution of the lightning current amplitude at position j c，j , the density of ground-to-ground flash at location j is N g，j , the conductor height H of the tower used at position j j , the distance b between the tower-shaped lightning conductors used at position j j , and establish the fitting function of the grounding resistance R and the back-strike lightning resistance level I, and calculate the back-strike tripping rate N through the back-strike lightning resistance level and the terrain parameters along the line.

[0052] Establish the function N(R) between the above back-tripping rate N and the grounding resistance R, including:

[0053] According to different tower shapes and terrain parameters, the corresponding back-attack tripping rate is calculated. The specific calculation formula is as follows:

[0054]

[0055] Among them, N L，j It represents the number of lightning strikes on the line per 100 km per year at position j. The calculation format is as follows:

[0056] N L，j =0.1×N g，j ×(4H j +bj )

[0057] Among them, I j Represents the lightning strike resistance level at position j. According to the data set of grounding resistance R and lightning strike resistance level I, the lightning strike resistance level I is established. j The quadratic function between the ground resistance R is as follows:

[0058] I j (R) = a2R 2 +a1R+a0

[0059] Establish the above soil resistivity proportional function L(ρ x ),include:

[0060] According to the soil resistivity ρ dataset along the multi-tower transmission line, the soil resistivity proportional function is established as follows:

[0061]

[0062] Where L(ρ x ) indicates that the soil resistivity data set is less than ρ x % of.

[0063] like Figure 1 As shown, the model framework of the method of the present invention is as follows:

[0064] (1) Providing a preliminary data set and performing data processing, including the following steps:

[0065] ① Collect the preliminary data set, including: the ground resistance lower limit data set ρ corresponding to the soil resistivity range expected by the user down , R down The control index N of the counter-tripping rate of the local multi-tower transmission line max , soil resistivity ρ dataset near each tower along the transmission line, pole striking rate g corresponding to each tower position along the line j , arc building rate η j , Calculate the parameter P of the probability distribution of lightning current amplitude c，j , ground-to-ground lightning density N g，j , the conductor height H of the tower j , the distance between lightning conductors of tower-shaped poles and towers b j And the tower model dataset corresponding to the location.

[0066] ② Establish a data set of the relationship between the grounding resistance R and the back-strike lightning resistance level I of various tower shapes: Based on the structural dimensions and insulation parameters of each tower shape of the transmission line in the prepared data, the lightning parameters and terrain parameters along the line, calculate the back-strike lightning resistance level I values ​​of various tower shapes of the transmission line under different grounding resistance R values, and establish a data set of the relationship between the grounding resistance R and the back-strike lightning resistance level I;

[0067] ③ Establish the fitting function of the back-strike lightning resistance level: According to the data set of grounding resistance R and back-strike lightning resistance level I, establish I j The quadratic function between the ground resistance R is as follows:

[0068] I j (R) = a2R 2 +a1R+a0.

[0069] Among them, I j It represents the strike-back lightning resistance level at position j, and a2, a1, and a0 are constant coefficients of the fitting function model.

[0070] ④ Establishing the proportional function of soil resistivity: Based on the soil resistivity ρ data set in the prepared data, the soil resistivity proportional function is established as follows:

[0071]

[0072] Where L(ρ x ) indicates that the soil resistivity data set is less than ρ x % of.

[0073] (2) Refining the objective function and constraints in the optimal design of the grounding resistance of multi-tower transmission line towers, including the following steps:

[0074] ① Construct objective function: In order to improve the economy of long transmission lines, the overall counter-tripping rate N of the line a It needs to be as close as possible to the transmission line counter-tripping rate control index N max ; To ensure the lightning protection of long transmission lines, the local back-tripping rate is required to exceed N max According to the above requirements, the two objectives are transformed into an objective function by weighted average, and the objective function is established as follows:

[0075]

[0076] In the formula, μ represents the weight coefficient, 0≤μ≤1.

[0077] As shown in the above objective function, the first goal is to improve the economy of long transmission lines, that is, N max -N a As close to 0 as possible. In order to ensure the order of magnitude of the two objectives is consistent, the objective function is normalized, that is, (N max -N all ) / N max .

[0078] As the objective function above, the second objective is to ensure the lightning protection of long transmission lines, that is As close to 0 as possible, where L k Represents the proportion of the kth level of soil resistivity.

[0079] As shown in the objective function above, μ is an adjustable parameter that can be adjusted according to different engineering requirements. The larger the μ, the more important the economy of the long transmission line is, and the smaller the μ, the more important the lightning protection of the long transmission line is.

[0080] ②Construct the first set of conditions: In order to ensure the feasibility of transmission line construction, it is necessary to set the upper limit of soil resistivity classification. k When there are 1 level, the upper limit of soil resistivity of level k is ρ k , the upper limit of the soil resistivity of the k-1th level is ρ k-1 , the soil resistivity classification must satisfy the requirement that the difference between the previous and next levels is greater than or equal to 500Ω·m; that is, ρ k -ρ k-1 ≥500, 2≤k≤n k .

[0081] ③ Construct the second constraint: Since the grounding resistance value is positively correlated with the soil resistivity during the construction process, it is necessary to set the upper limit of the grounding resistance value corresponding to the same level of soil resistivity. The upper limit of the grounding resistance of the kth level is marked as R k , the upper limit of the grounding resistance of the k-1th level is R k-1 , the difference between the grounding resistance values ​​of the two levels before and after is greater than or equal to 5Ω, and the grounding resistance of the kth level is marked as R k , the grounding resistance of the k-1th level is R, that is, R k -R k-1 ≥5, 2≤k≤n k .

[0082] ④Construct the third constraint: To meet the feasibility of the transmission line grounding design implementation, when the soil resistivity grade ρ k ≥ρ down , 2≤k≤n k When R k ≥R down , 2≤k≤n k . Where ρ down is the lower limit of the k-th soil resistivity range, R down is the minimum value of the kth level grounding resistance.

[0083] ⑤Construct the fourth constraint: To ensure the overall lightning protection of long transmission lines, the overall counter-tripping rate of transmission lines is required to be N a Less than the transmission line back-tripping rate control index N max , that is, N a ≤N max .

[0084] Where N a The proportional function L(ρ x ), counter-tripping rate fitting function N i , obtained by weighted summation. The specific calculation formula is as follows:

[0085] N a =∑ k ∑ i (N i (L(ρ k )-L(ρ k-1 ))), 2≤k≤n k

[0086] Where i represents the i-th tower shape, N i It represents the counter-tripping rate corresponding to the i-th tower shape.

[0087] (3) Using the Monte Carlo algorithm to solve the minimum value of the objective function

[0088] According to the Monte Carlo algorithm, the soil resistivity classification and grounding resistance values ​​that meet the four constraints are screened out, and the corresponding optimal solution of the global objective function is calculated. The optimal solution vector is converted into soil resistivity classification and grounding resistance value, which is the optimal design scheme for grounding resistance.

[0089] Determine the maximum number of cycles S and the objective function weight coefficient μ of the Monte Carlo algorithm:

[0090] According to the range of soil resistivity and ground resistance, S groups of soil resistivity classification and ground resistance values ​​are randomly generated, and the data group is marked as [ρ k R k ]1.

[0091] Filter out soil resistivity classification and ground resistance values ​​that meet the constraints, including:

[0092] In the above S arrays, according to the constraints one, two, three, and four, the data group that meets all the conditions is selected and marked as [ρ k R k ]2.

[0093] Find a set of soil resistivity classification and ground resistance values ​​that minimize the objective function, including:

[0094] In the above data set [ρ k R k ]2, the objective function is calculated, and a set of soil resistivity classification and grounding resistance values ​​with the smallest objective function value is selected as the optimal solution, that is, as the optimal design scheme for grounding resistance.

[0095] like Figure 2As shown, this embodiment uses MTATLAB software to model and simulate the optimization design method of the grounding resistance of the multi-tower transmission line tower of the present invention. The steps of the MTATLAB main program to implement the Monte Carlo algorithm are as follows:

[0096] ① Save the prepared data in the root directory of the MATLAB main program in the formats of soil resistivity dataset.xlsx, counter-strike lightning resistance dataset.xlsx, ground resistance lower limit dataset.xlsx, and terrain tower dataset.xlsx. Use the xlsread command to directly import the data into the MATLAB workspace.

[0097] ② Establish the fitting function of the lightning strike resistance level of different tower shapes and the soil resistivity proportional function: According to the data set of grounding resistance R and lightning strike resistance level I of different tower shapes in the prepared data, use the polyfit (R, I, 2) command in MATLAB to determine the constant coefficient part a2, a1, a0 of the fitting function model. According to the soil resistivity ρ data set, calculate the soil resistivity proportional function.

[0098] ③ Initialization settings: Set the maximum number of algorithm cycles S, the initial value of the objective function value f0=1, the initial value of the grounding resistance R0=0, the initial value of the soil resistivity classification ρ0=0, and the number of calculation steps s=1.

[0099] ④ Determine whether the current iteration step satisfies s≤S max If it is satisfied, proceed to step ⑥, if not, proceed to step ⑤.

[0100] ⑤Output R0, ρ0, and end.

[0101] ⑥ Randomly generate a set of grounding resistance R and soil resistivity classification ρ: Use the randi command in MATLAB, take the data in the grounding resistance lower limit data set as the upper and lower bounds, and randomly select a set of grounding resistance values ​​and soil resistivity classification that meet constraint condition four.

[0102] ⑦ Calculate the other three constraints: First, use the counter-strike lightning resistance level fitting function I i (R), calculate the grounding resistance back-tripping rate N generated in ⑥ k , using the soil resistivity proportional function L(ρ x ), calculate the proportion L of each grade of soil resistivity generated in ⑥ k , calculate the total back-tripping rate N of the transmission line a =∑N k ×L k ; Second, calculate the difference R between the two grounding resistance values ​​before and after all current classifications k -R k-1; Third, calculate the difference ρ between the two items before and after the soil resistivity classification under all current classifications k -ρ k-1 .

[0103] ⑧ Determine whether all three constraints are met, that is, determine whether N a ≤N max , ρ k -ρ k-1 ≥500, R k -R k-1 ≥5. If all three constraints are satisfied, proceed to step 9; otherwise, the number of calculation steps increases by s=s+1, and returns to step 4.

[0104] ⑨Calculate the objective function f:

[0105] ⑩ Determine whether the objective function f reaches the minimum value. If f<f0, derive the soil resistivity classification, the corresponding soil resistivity ratio and the grounding resistance value, that is, R0=R, ρ0=ρ, L0=L, and record the objective function value f0=f, increase the number of calculation steps by s=s+1, and return to step ④; if f≥f0, increase the number of calculation steps by s=s+1, and return to step ④.

[0106] The following is a specific application of the present invention in designing grounding resistance when two types of towers, 2A2-ZB1 and 2A2-J1 towers, are used on a 220kV transmission line.

[0107] (1) Data preparation and data processing

[0108] ① Collect preliminary data

[0109] Collected local control requirements for the counter-tripping rate of 220kV multi-tower transmission lines N max It is 0.1575 times / (100km / year).

[0110] The soil resistivity ρ data set along the 220kV transmission line is collected, as shown in Table 1:

[0111] 112 236 691 9071 9608 1727 1319 1727 2544 816 196 226 659 1632 393 1978 117 502 1413 550 345 239 1036 1256 973 239 137 1601 1979 1600 267 118 5024 1382 1005 659 151 14695 1759 2400 4710 147 722 1821 503 3140 135 151 2512 11587 179 210 597 1539 628 157 973 7850 722 11587 198 141 1539 1570 471 471 345 1036 1051 1727 160 314 628 2669 1634 114 1193 408 1790 282 440 785 2669 1382 298 1005 2387 1696 377 220 785 832 1570 160 502 9043 1884 157 816 565 1853 9043 220 659 9043 2104 251 1601 502 1476 1916 135 377 5589 3768 160 377 785 1633 131 138 1350 2889 1602 210 502 942 1884 105 166 597 14130 9608 117 785 2606 3454 104 226 942 1821 816

[0112] Table 1 - Soil resistivity ρ along the transmission line

[0113] The pole striking rate g data set along the 220kV transmission line is collected, as shown in Table 2:

[0114]

[0115]

[0116] Table 2-220kV transmission line pole striking rate g

[0117] Collect the density of ground lightning along the 220kV transmission line N g The data set is shown in Table 3:

[0118] 1.4 2.8 3.7 2.8 3.7 2.8 2.8 3.7 2.8 2.8 1.4 2.8 3.7 2.8 3.7 2.8 2.8 3.7 2.8 3.7 1.4 2.8 3.7 2.8 1.4 2.8 2.8 3.7 2.8 3.7 1.4 2.8 3.7 2.8 1.4 2.8 2.8 3.7 2.8 3.7 1.4 2.8 3.7 2.8 1.4 2.8 2.8 3.7 2.8 3.7 1.4 2.8 3.7 2.8 1.4 2.8 2.8 3.7 2.8 3.7 1.4 2.8 3.7 2.8 1.4 2.8 2.8 3.7 2.8 3.7 1.4 2.8 3.7 2.8 1.4 2.8 2.8 3.7 2.8 1.4 2.8 3.7 2.8 1.4 2.8 2.8 2.8 2.8 2.8 2.8 3.7 2.8 2.8 2.8 2.8 2.8 2.8 2.8 2.8 3.7 3.7 2.8 2.8 3.7 1.4 2.8 2.8 2.8 3.7 3.7 2.8 2.8 3.7 1.4 2.8 2.8 2.8 3.7 3.7 2.8 2.8 3.7 1.4 2.8 2.8 2.8 2.8 3.7 2.8 2.8 3.7 1.4 2.8 2.8 2.8 2.8 3.7 2.8 2.8 3.7 2.8 2.8

[0119] Table 3-220kV ground lightning density along the transmission line N g

[0120] The tower shape dataset along the 220kV transmission line is collected, marking 2A2-ZB1 tower as type 1 and 2A2-J1 as type 2 tower. The tower shape dataset is shown in Table 4:

[0121]

[0122]

[0123] Table 4-220kV transmission line tower data set

[0124] ② Establish a data set of the relationship between ground resistance R and back-strike lightning resistance level I

[0125] Based on the ATP program, the transient analysis of the wave process of the lightning-struck 220kV line is carried out, and the relationship data set between the grounding resistance R and the back-strike lightning resistance level I of the tower 2A2-ZB1 and tower 2A2-J1 is calculated, as shown in Table 5:

[0126]

[0127] Table 5-ATP calculated grounding resistance and lightning strike resistance level

[0128] The grounding resistance value range that can be implemented within different soil resistivity ranges is input according to the default values ​​in Table 1.

[0129] ③Establish fitting function of strike-back lightning resistance level

[0130] Using the polyfit(R, I, 2) function in MATLAB software, the constant coefficients of the quadratic function model can be obtained as follows: Type 1: a2 = 0.0270, a1 = -4.0111, a0 = 191.3623; Type 2: a2 = 0.0251, a1 = -3.7809, a0 = 179.2816. Therefore, the horizontal fitting function of the counter-strike lightning resistance is:

[0131] I1(R)=0.0270R 2 -4.0111R+191.3623

[0132] I2(R)=0.0251R 2 -3.7809R+179.2816

[0133] ④Establish soil resistivity proportional function

[0134] According to the soil resistivity ρ along the 220kV transmission line and the proportional function of soil resistivity When ρ x When increasing by 100, L(ρ x ) values ​​are shown in Table 6:

[0135]

[0136]

[0137] Table 6 - Soil resistivity scaling function

[0138] ⑤ Establish a ground resistance lower limit data set

[0139] Since soil resistivity is positively correlated with the grounding resistance of the grounding body, a lower limit data set of grounding resistance is proposed under different soil resistivity ranges:

[0140] When ρ∈[100Ω·m, 1000Ω·m], R≥10Ω;

[0141] When ρ∈[1000Ω·m, 2000Q·m], R≥15Ω;

[0142] When ρ∈[2000Ω·m, 5000Ω·m], R≥25Ω;

[0143] When ρ∈[5000Ω·m, 7500Ω·m], R≥40Ω;

[0144] When ρ∈[750Ω·m, 10000Ω·m], R≥60Ω;

[0145] When ρ>10000Ω·m], R≥80Ω.

[0146] The maximum soil resistivity along the project is 14695Ω·m, and the lower limit data set of grounding resistance is established as shown in Table 7:

[0147]

[0148] Table 7 - Lower limit of soil resistivity range and lower limit of ground resistance

[0149] (2) Constructing the objective function and constraint conditions in the optimization design of the grounding resistance of multi-tower transmission line towers includes the following steps:

[0150] ① Construct objective function: In order to improve the economy of long transmission lines, the overall counter-tripping rate N of the line a It needs to be as close as possible to the transmission line counter-tripping rate control index N max ; To ensure the lightning protection of long transmission lines, the local back-tripping rate is required to exceed N max According to the above requirements, the two objectives are transformed into an objective function by weighted average, and the objective function is established as follows:

[0151]

[0152] In the formula, μ represents the weight coefficient, 0≤μ≤1.

[0153] As shown in the above objective function, the first goal is to improve the economy of long transmission lines, that is, N max -N a As close to 0 as possible. In order to ensure the order of magnitude of the two objectives is consistent, the objective function is normalized, that is, (N max -N all ) / N max .

[0154] As the objective function above, the second objective is to ensure the lightning protection of long transmission lines, that is As close to 0 as possible, where L k Indicates the proportion of the kth level of soil resistivity.

[0155] As shown in the objective function above, μ is an adjustable parameter that can be adjusted according to different engineering requirements. The larger the μ, the more important the economy of the long transmission line is, and the smaller the μ, the more important the lightning protection of the long transmission line is.

[0156] ②Construct the first bundle of conditions: In order to ensure the feasibility of long transmission line construction, it is necessary to set the upper limit of soil resistivity classification. k When there are 1 level, the upper limit of soil resistivity of level k is ρ k , the upper limit of the soil resistivity of the k-1th level is ρ k-1 , the soil resistivity classification must satisfy the difference between the previous and next levels is greater than or equal to 500Ω·m, that is, ρ k -ρ k-1 ≥500, 2≤k≤n k .

[0157] ③ Construct the second constraint: Since the grounding resistance value is positively correlated with the soil resistivity during the construction process, it is necessary to set the upper limit of the grounding resistance value corresponding to the same level of soil resistivity. The upper limit of the grounding resistance of the kth level is marked as R k , the upper limit of the grounding resistance of the k-1th level is Rk-1 , the difference between the grounding resistance values ​​of the two levels before and after is greater than or equal to 5Ω, and the grounding resistance of the kth level is marked as R k , the grounding resistance of the k-1th level is R, that is, R k -R k-1 ≥5, 2≤k≤n k .

[0158] ④Construct the third constraint: To meet the feasibility of the transmission line grounding design implementation, when the soil resistivity grade ρ k ≥ρ down , 2≤k≤n k When R k ≥R down , 2≤k≤n k . Where ρ down is the lower limit of the k-th soil resistivity range, R down is the minimum value of the kth level grounding resistance.

[0159] ⑤ Construct the fourth constraint: To ensure the overall lightning protection of long transmission lines, the overall back-tripping rate of the transmission lines is required to be N a Less than the transmission line back-tripping rate control index N max , that is, N a ≤N max .

[0160] Where N a The proportional function L(ρ x ), counter-tripping rate fitting function N i , obtained by weighted summation. The specific calculation formula is as follows:

[0161] N a =∑ k ∑ i (N i (L(ρ k )-L(ρ k-1 ))), 2≤k≤n k

[0162] Where i represents the i-th tower shape, N i It represents the counter-tripping rate corresponding to the i-th tower shape.

[0163] (3) Using the Monte Carlo method to solve the minimum value of the objective function

[0164] ①Parameter selection

[0165] In this specific example, the maximum number of iterations of the algorithm is 4×10 9 From the perspective of computational efficiency and reliability, we take S = 10 6In addition, the weight coefficient μ of the objective function measures the proportion of the two sub-objectives. In this example, it is more necessary to improve the economic efficiency of the transmission line, so the weight coefficient μ is 0.9.

[0166] ②Monte Carlo simulation

[0167] The soil resistivity classification and grounding resistance optimization model are solved by using the Monte Carlo method of MTATLAB simulation, and the grounding resistance optimization scheme is output, as shown in Table 8:

[0168]

[0169]

[0170] Table 8 - Soil resistivity classification and grounding resistance design values

[0171] As can be seen from Table 8, according to the optimal design value of the grounding resistance in this example, the total back-tripping rate of the multi-tower transmission line can reach 0.1574 times / 100km·year, which is only 0.0001 less than the back-tripping rate control index in the requirement, improving the economy of the transmission line. In addition, the proportion of all grades exceeding the back-tripping rate control index is 11.9%, which is a small proportion, ensuring the lightning protection of the transmission line, and the calculation results meet the preset construction requirements.

[0172] The above contents are only preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, various changes and modifications may be made according to the present invention. Any modifications, equivalent substitutions and improvements made within the design principles of the present invention should be covered within the protection scope of the present invention.

Claims

1. A multi-tower grounding resistance optimization method based on Monte Carlo algorithm, characterized in that: The following steps are involved: S1. According to the requirements of the back-tripping rate of long transmission lines, tower shape requirements, terrain characteristics along the line and the construction requirements of grounding resistance of various tower shapes, an optimization model of grounding resistance of multi-tower transmission line towers is established; S2, setting the parameters of the Monte Carlo method, and randomly generating several groups of soil resistivity classifications and their corresponding ground resistance values; S3, solving the grounding resistance optimization model of multi-tower transmission line towers by Monte Carlo method; S4. Convert the optimal value obtained by the Monte Carlo method into the corresponding soil resistivity classification and its corresponding grounding resistance value as the optimal design scheme for the grounding resistance of multi-tower transmission line towers.

2. The method for optimizing the grounding resistance of a multi-tower pole tower based on the Monte Carlo algorithm according to claim 1, characterized in that: The optimization design model of multi-tower transmission line towers includes: Construct objective function: To improve the economic efficiency of long transmission lines, the overall counter-tripping rate N of the line a Need to approach the transmission line back-tripping rate control index N max ; To ensure the lightning protection of long transmission lines, it is required to reduce the local backlash tripping rate by more than N max According to the above requirements, the two objectives are transformed into an objective function by weighted average, and the objective function is established as follows: In the formula, μ represents the weight coefficient, 0≤μ≤1; As shown in the above objective function, the first goal is to improve the economy of long transmission lines, that is, N max -N a Approaching 0; To ensure the order of magnitude of the two objectives is consistent, the objective function is normalized, that is, (N max -N all ) / N max . As the objective function above, the second objective is to ensure the lightning protection of long transmission lines, that is Approaching 0, where L k It represents the proportion of soil resistivity level k; As shown in the objective function above, μ is an adjustable parameter, which is adjusted according to different engineering requirements. The larger μ is, the more important the economy of long transmission lines is, and the smaller μ is, the more important the lightning protection of long transmission lines is.

3. The method for optimizing the grounding resistance of a multi-tower pole tower based on the Monte Carlo algorithm as claimed in claim 2, characterized in that: The multi-tower transmission line tower optimization design model also includes: Construct the first set of conditions: To ensure the feasibility of transmission line construction, the upper limit of soil resistivity classification is set. k When there are 1 level, the upper limit of soil resistivity of level k is ρ k , the upper limit of the soil resistivity of the k-1th level is ρ k-1 , the soil resistivity classification satisfies that the difference between the previous and next levels is greater than or equal to 500Ω·m; that is, ρ k -ρ k-1 ≥500, 2≤k≤n k ; Construct the second constraint: Since the grounding resistance value is positively correlated with the soil resistivity during the construction process, the upper limit of the grounding resistance value corresponding to the same level of soil resistivity is set, and the upper limit of the grounding resistance of the kth level is marked as R k , the upper limit of the grounding resistance of the k-1th level is R k-1 , the difference between the grounding resistance values ​​of the two levels before and after is greater than or equal to 5Ω, and the grounding resistance of the kth level is marked as R k , the grounding resistance of the k-1th level is R, that is, R k -R k-1 ≥5, 2≤k≤n k ; Construct the third constraint: To meet the feasibility of the transmission line grounding design implementation, when the soil resistivity grade ρ k ≥ρ down , 2≤k≤n k When R k ≥R down , 2≤k≤n k ; where ρ down is the lower limit of the k-th soil resistivity range, R down is the minimum value of the kth level grounding resistance; Construct the fourth constraint: To ensure the overall lightning protection of long transmission lines, the overall counter-tripping rate of the transmission lines is required to be N a Less than the transmission line back-tripping rate control index N max , that is, N a ≤N max ; Where N a The proportional function L(ρ x ), counter-tripping rate fitting function N i , weighted summation is obtained; the specific calculation formula is as follows: N a =∑ k ∑ i (N i (L(p k )-L(ρ k-1 ))),2≤k≤n k Where i represents the i-th tower shape, N i It represents the counter-tripping rate corresponding to the i-th tower shape.

4. The method for optimizing the grounding resistance of a multi-tower pole tower based on the Monte Carlo algorithm as claimed in claim 3, characterized in that: Set the parameters of the Monte Carlo method to randomly generate several groups of soil resistivity classification and ground resistance values ​​including: Determine the maximum number of cycles S and the objective function weight coefficient μ of the Monte Carlo algorithm: According to the value range of soil resistivity and ground resistance, randomly generate S groups of soil resistivity classification and ground resistance values, and the data group is marked as [ρ k R k ]1.

5. The method for optimizing the grounding resistance of a multi-tower pole tower based on the Monte Carlo algorithm according to claim 4, characterized in that: Filter out soil resistivity classification and ground resistance values ​​that meet the constraints, including: In the above S arrays, according to the constraints one, two, three, and four, the data group that meets all the conditions is selected and marked as [ρ k R k ]2.

6. The method for optimizing the grounding resistance of a multi-tower pole tower based on the Monte Carlo algorithm as claimed in claim 5, characterized in that: Find a set of soil resistivity classification and ground resistance values ​​that minimize the objective function, including: In the above data set [ρ k R k ]2, the objective function is calculated, and a set of soil resistivity classification and grounding resistance values ​​with the smallest objective function value is selected as the optimal solution, that is, as the optimal design scheme for grounding resistance.

7. The method for optimizing the grounding resistance of a multi-tower pole tower based on the Monte Carlo algorithm as claimed in claim 6, characterized in that: In establishing the fitting function N between the multi-tower back-tripping rate N and the grounding resistance R i (R) Based on the structural dimensions and insulation parameters of various typical towers along the transmission line, the lightning parameters and terrain parameters along the line were statistically analyzed to determine the pole striking rate g at the corresponding position j of each tower. j , arc construction rate η at position j j , the parameter P of the probability distribution of the lightning current amplitude at position j c，j , the density of ground-to-ground flash at location j is N g，j , the conductor height H of the tower used at position j j , the distance b between the tower-shaped lightning conductors used at position j j , and establish the fitting function of the grounding resistance R and the back-strike lightning resistance level I, and calculate the back-strike tripping rate N through the back-strike lightning resistance level and the terrain parameters along the line.

8. The method for optimizing the grounding resistance of a multi-tower pole tower based on the Monte Carlo algorithm according to claim 7, characterized in that: Establish the function N(R) between the above back-tripping rate N and the grounding resistance R, including: According to different tower shapes and terrain parameters, the corresponding back-attack tripping rate is calculated. The specific calculation formula is as follows: Among them, N L，j It represents the number of lightning strikes on the line per 100 km per year at position j. The calculation formula is as follows: N L，j =0.1×N g，j ×(4H j +b j ) Among them, I j Represents the lightning strike resistance level at position j. According to the data set of grounding resistance R and lightning strike resistance level I, the lightning strike resistance level I is established. j The quadratic function between the ground resistance R is as follows: I j (R)=a2R 2 +a1R+a0。 9. The method for optimizing the grounding resistance of multiple towers based on the Monte Carlo algorithm according to claim 8, characterized in that: Establish the above soil resistivity proportional function L(ρ x ),include: According to the soil resistivity ρ dataset along the multi-tower transmission line, the soil resistivity proportional function is established as follows: In the formula, L(ρ x ) indicates that the soil resistivity data set is less than ρ x % of.

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