Obstacle removing scheme generation method for removing branches beside overhead electrified line

Abstract

The invention provides a method for generating an obstacle clearing scheme for clearing branches beside an overhead electrified line, which comprises the following steps of: determining line tree contradiction points on a plurality of electrified lines and a plurality of vulnerability factors corresponding to the line tree contradiction points, and calculating the vulnerability T of each line tree contradiction point according to the vulnerability factors; and constructing an objective function and setting constraint conditions according to the vulnerability T of each line tree contradiction point, and determining the to-be-maintained line tree contradiction point based on the solution of the objective function to generate an obstacle clearing scheme. According to the method, the obstacle clearing scheme comprising the line tree contradictory points of the plurality of electrified lines can be formulated by taking the minimum load loss and obstacle clearing cost as targets, the utilization efficiency of obstacle clearing resources can be effectively improved, and the load loss of the electrified lines is reduced.

Description

Technical Field

[0001] This invention relates to the field of tree branch removal technology beside power lines, and specifically to a method for generating a tree branch removal scheme beside overhead power lines. Background Technology

[0002] The conflict between trees and overhead power lines refers to the tension between planting trees along power line corridors and ensuring the safe operation of power lines. During periods of vigorous tree growth, especially during extreme weather events such as strong winds and heavy rains, factors such as line galloping, tree swaying, and even bending and overturning can easily cause air breakdown between the trees and the power lines, leading to grounding faults and seriously threatening the safe and stable operation of the power distribution network.

[0003] However, tree-line conflicts involve the work of power companies and departments such as planning, forestry, and greening. Tree pruning requires communication with multiple departments. During periods when tree-line conflicts are concentrated, it is necessary to quickly and reasonably formulate the optimal obstacle removal plan, make efficient use of limited obstacle removal resources, and minimize the losses caused by tree-line conflicts.

[0004] In existing technology, a novel tree obstruction detection method based on lidar is disclosed (Li Junpeng, Huang Junbo, Jia Yongxiang). This method projects ground data from power line inspections onto a two-dimensional plane as point data, and utilizes the data detection function of multispectral lidar to verify the distance to tree obstructions. This detection method can effectively locate the detection position and improve detection efficiency. Existing documents propose a tree-line distance risk index, aiming to minimize the tree-line distance risk index for the entire power line under its jurisdiction, with the management cost of the transmission line corridor as a constraint. A two-stage genetic algorithm is used to solve the optimization model, thereby deriving an effective corridor handling scheme.

[0005] However, it does not effectively allocate manpower for clearing obstacles and reduce the impact of power line faults on users. Summary of the Invention

[0006] In view of this, the problem to be solved by the present invention is to provide a method for generating a clearing scheme for removing tree branches next to overhead power lines, which can efficiently utilize clearing manpower and minimize the impact of power line faults on power users.

[0007] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows: A method for generating a tree branch removal scheme for clearing tree branches beside overhead power lines includes identifying several tree-branch conflict points along the power lines, identifying several vulnerability factors corresponding to these conflict points, and calculating the vulnerability T of each tree-branch conflict point based on these vulnerability factors. Construct the objective function based on the vulnerability T of each line tree conflict point: , andu i conform to , Among them, u i =0 or 1, to indicate whether tree line conflict point i has not taken clearing measures or has taken clearing measures, respectively, T i This represents the fragility of the contradiction point i in the linear tree. This represents the load loss on the energized line caused by a unit power outage time at the point of conflict i in the line tree. This represents the time required to restore power after a power line fault is caused by the line tree's conflict point i. This represents the cost per unit time to clear a fault in a power line caused by a conflict point i in the line tree. Indicates the time required to clear the obstacle at line tree conflict point i. C i Indicates the contradiction points of the tree line. i The cost of conducting pre-emptive obstacle removal N max The upper limit for the number of conflict points in the obstacle clearing line tree; The solution based on the objective function is used to identify the conflict points in the line tree to be repaired, so as to generate a clearing plan.

[0008] Furthermore, the extreme values ​​of the objective function are calculated based on the weighted particle swarm optimization algorithm.

[0009] Furthermore, the vulnerability factors include two factors: the minimum distance D between tree lines and the service life Y of the power lines.

[0010] Furthermore, the vulnerability T of the line tree contradiction point i is calculated. i The formula is: i =a 1× D i + a 2× Y i , a 1+ a 2 = 1 in, a 1. a 2. Weighting coefficients; D i Y represents the minimum distance between tree lines at the point of conflict i in the line tree; i Let i be the line tree contradiction point corresponding to the number of years the energized line has been in operation.

[0011] Further, the weighting coefficients are calculated. a 1. a2. This includes constructing a comparison matrix C, calculating the eigenvectors w1 and w2 corresponding to the vulnerability factors in the comparison matrix C, calculating the largest eigenvalue based on the eigenvectors w1 and w2, and performing a consistency check based on the largest eigenvalue and the eigenvectors w1 and w2. If the check passes, the eigenvectors w1 and w2 are normalized to generate weight coefficients. a 1. a 2; If it fails, the comparison matrix C needs to be reconstructed and recalculated.

[0012] Furthermore, constructing the comparison matrix C includes setting the comparison scale: elements k With elements j When elements are equally important, their relative importance is 1. k Compared to elements j When it is slightly important, the relative importance level is 3, and the element k Compared to elements j When clearly important, the relative importance is 5, element k Compared to elements j When it is much more important, the relative importance is 7, and the importance is 2. n -1 and 2 n When the value is between +1 and 2, the relative importance is 2. n ( n= 1,2,3,4); Construct a comparison matrix of three factors based on the comparison scale. ,in, To indicate the importance of factor D relative to factor Y, the values ​​of other elements in the comparison matrix C are determined using the same method.

[0013] The advantages and positive effects of this invention are: By calculating the vulnerability T of line-tree conflict points based on the vulnerability factors corresponding to them, the vulnerability T of multiple line-tree conflict points is substituted into the objective function. The objective function includes the load loss of the power line caused by the line-tree conflict point per unit power outage time, the power restoration time after the power line fault is caused, the unit time cost of clearing the fault after the power line fault is caused, the required clearing time, and the cost required for pre-clearing. When the output value of the objective function is minimized, the corresponding combination of line-tree conflict points to be cleared has the highest utilization rate of clearing resources and the lowest impact on users. This can efficiently utilize clearing human resources and minimize the impact of power line faults on electricity users. Detailed Implementation

[0014] The technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0015] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the specification of this invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed terms.

[0016] This invention provides a method for generating a tree branch removal scheme next to overhead power lines. The method includes identifying several tree-line conflict points along the power lines, identifying several vulnerability factors corresponding to these conflict points, and calculating the vulnerability level T of each conflict point based on these vulnerability factors. One embodiment of this application uses a 10kV power line.

[0017] By periodically inspecting the deployed power lines, and based on the minimum distance between the power lines and the trees on both sides (minimum distance D between trees and lines), coordinate points where the minimum distance is below a threshold are artificially designated as line-tree conflict points. One embodiment of this application involves using a drone to inspect the power lines, collecting image data or radar point cloud data of the power lines, and determining the minimum distance D between trees and lines based on the image data or radar point cloud data, thereby identifying line-tree conflict points.

[0018] Vulnerability factors include two aspects: the minimum distance between tree lines (D) and the service life (Y) of the power lines. The minimum distance between tree lines (D) can be collected manually or using drones.

[0019] Calculate the vulnerability T of conflict point i in the line tree. i The formula is: i =a 1× D i + a 2× Y i , a 1+ a 2=1, in, a 1. a 2 represents the weighting coefficient; D i Y represents the minimum distance between tree lines at the point of conflict i in the line tree; i Let i be the line tree contradiction point corresponding to the number of years the energized line has been in operation.

[0020] The weight coefficients of the two vulnerability factors are determined using the principles of the analytic hierarchy process (AHP). a 1. a2. Specifically: The Analytic Hierarchy Process (AHP) includes a scheme layer, a criterion layer, and a target layer. The scheme layer includes several overhead power lines; the criterion layer includes a comparison matrix C constructed based on two vulnerability factors: minimum distance between trees and lines and the service life of the lines; the target layer is the vulnerability of the tree-line conflict points.

[0021] Constructing the comparison matrix C involves setting the comparison scale: the comparison matrix is ​​constructed using the comparison scales 1-9 shown in the table below. C： Construct a comparison matrix of three factors based on the comparison scale. ,in, This indicates the relative importance of vulnerability factor D to vulnerability factor Y. The same method is used to determine the values ​​of other elements in the comparison matrix C.

[0022] Calculate the eigenvectors w1 and w2 corresponding to the vulnerability factors in the comparison matrix C. Calculate the largest eigenvalue based on the eigenvectors w1 and w2. Perform a consistency check based on the largest eigenvalue and the eigenvectors w1 and w2. If the check passes, normalize the eigenvectors w1 and w2 to generate weight coefficients. a 1. a 2; If it fails, the comparison matrix C needs to be reconstructed and recalculated.

[0023] Specifically, the geometric mean of the elements in each row of the comparison matrix C is calculated to generate eigenvectors w1 and w2 corresponding to the vulnerability factors in that row, and the maximum eigenvalue is calculated based on the eigenvectors w1 and w2. The calculation formula is: , Where n represents the number of eigenvectors, C represents the comparison matrix, and (Cw) i This represents a comparison between the matrix C and the eigenvector w. i The i-th element of the product, w i Let represent the feature vector of the i-th vulnerability factor.

[0024] Consistency testing includes calculating the consistency index (CI): , Here, n represents the order of the comparison matrix C. Looking up the average consistency index, we find that when n=2, RI=0.58.

[0025] Based on the consistency index CI and the average consistency index RI, the consistency ratio CR is calculated. , If CR < 0.1, the consistency test passes, and the normalized eigenvectors w1 and w2 are used to generate the eigencoefficients. a 1. a 2, anda 1+ a 2=1. If the consistency check fails, readjust the comparison matrix C and repeat the above calculation process for the comparison matrix C.

[0026] Construct the objective function based on the vulnerability T of each line tree conflict point: , andu i conform to , Among them, u i =0 or 1, to indicate whether tree line conflict point i has not taken clearing measures or has taken clearing measures, respectively, T i This represents the fragility of the contradiction point i in the linear tree. This represents the load loss on the energized line caused by a unit power outage time at the point of conflict i in the line tree. This represents the time required to restore power after a power line fault is caused by the line tree's conflict point i. This represents the cost per unit time to clear a fault in a power line caused by a conflict point i in the line tree. Indicates the time required to clear the obstacle at line tree conflict point i. C i Indicates the contradiction points of the tree line. i The cost of conducting pre-emptive obstacle removal N max The upper limit for the number of conflict points in the obstacle removal line tree is set. The conflict points in the line tree to be repaired are determined based on the solution of the objective function to generate an obstacle removal plan. One embodiment of this application is: setting an upper limit based on the number of obstacle removal personnel. N max .

[0027] In the objective function, and The product of and represents the load loss generated when the line tree's contradiction point i fails; the greater the load loss, the greater the impact on users; T i Multiplying this by the load loss indicates the first impact value that the line tree contradiction point i may have on the load loss; and The product represents the clearing cost incurred when a line tree inconsistency point i fails, T. i Multiplying by the total cost indicates the second impact value that the line tree conflict point i may have on the clearance cost; u i With C i The product represents the third impact value of the cost required for pre-emptive obstacle removal measures that may be generated at the conflict point i in the tree line. The sum of the first impact value, the second impact value, and the third impact value represents the total influencing factors of the conflict point i in the tree line.

[0028] The greater the total influencing factors of line-tree conflict points, the greater the probability of failure, the higher the clearance cost, or the greater the load loss. Timely clearance is necessary to avoid serious impact on users. Conversely, the smaller the total influencing factors of line-tree conflict points, the lower the probability of failure, the lower the clearance cost, or the smaller the load loss. Clearance can be abandoned. By calculating the minimum value of the objective function, the combination of line-tree conflict points to be cleared (the combination of line-tree conflict points that will have a serious impact) is determined. Limited clearance resources (clearance personnel) are allocated based on the combination of line-tree conflict points to be repaired. The vulnerability T of the line-tree conflict points is added to the objective function. i This is equivalent to increasing the weight of line tree conflict points, so that the objective function can prioritize the selection of line tree conflict points with high weight, high load loss, and high subsequent clearing costs, thereby ensuring power supply while reducing the probability of large-scale power supply accidents and high subsequent clearing losses.

[0029] Specifically: load loss includes power loss; subsequent clearing costs include tree trimming, power line repair, and maintenance of electrical equipment associated with the power line.

[0030] One embodiment of this application involves calculating the objective function based on a weighted particle swarm optimization algorithm. The core improvement of this algorithm lies in its linearly decreasing inertia weight setting. In the initial search phase, each line-tree conflict point is assigned a large inertia weight, enabling it to explore a wide range of line-tree conflict points and find the optimal combination of line-tree conflict points where obstacle-clearing measures can be taken. As the number of iterations increases, the inertia weight of line-tree conflict points within non-optimal combinations is gradually reduced, allowing for more precise local searches within better combinations in later stages. This better balances global and local search capabilities, increasing the probability of convergence to the global optimum.

[0031] The embodiments of the present invention have been described in detail above, but the content described is only a preferred embodiment of the present invention and should not be considered as limiting the scope of the present invention. All equivalent changes and improvements made within the scope of this patent should still fall within the scope of this patent.

Claims

1. A method for generating a clearing scheme for removing tree branches beside overhead power lines, characterized in that, This includes obtaining several line tree conflict points on several power lines, several vulnerability factors corresponding to the line tree conflict points, and calculating the vulnerability T of each line tree conflict point based on the vulnerability factors: Construct the objective function based on the vulnerability T of each line tree conflict point: ， and u i conform to , in, u i =0 or 1, to represent tree line contradiction points respectively. i No clearing measures were taken or no clearing measures were taken, T i This represents the fragility of the contradiction point i in the linear tree. This represents the load loss on the energized line caused by a unit power outage time at the point of conflict i in the line tree. This represents the time required to restore power after a power line fault is caused by the line tree's conflict point i. This represents the cost per unit time to clear a fault in a power line caused by a conflict point i in the line tree. Indicates the time required to clear the obstacle at line tree conflict point i. C i Indicates the contradiction points of the tree line. i The cost of conducting pre-emptive obstacle removal C i Indicates the contradiction points of the tree line. i The cost of conducting pre-emptive obstacle removal N max The upper limit for the number of conflict points in the obstacle clearing line tree; The conflict points of the line tree to be repaired are determined based on the extreme values ​​of the objective function in order to generate a clearing plan.

2. The method for generating a clearing scheme for removing tree branches beside overhead power lines according to claim 1, characterized in that, The extreme values ​​of the objective function are calculated using a particle swarm optimization algorithm with decreasing weights.

3. The method for generating a clearing scheme for removing tree branches beside overhead power lines according to claim 1, characterized in that, The vulnerability factors include the minimum distance D between tree lines and the number of years the power lines have been in operation Y.

4. A method for generating a clearing scheme for removing tree branches beside overhead power lines according to claim 3, characterized in that, Calculate tree line conflict points i Vulnerability T i The formula is: i =a 1× D i + a 2× Y i ， a 1+ a 2=1， in, a 1. a 2 represents the weighting coefficient; D i Points of contradiction in tree lines i The minimum distance between tree lines; Y i Points of contradiction in tree lines i The corresponding service life of the power lines.

5. A method for generating a clearing scheme for removing tree branches beside overhead power lines according to claim 3, characterized in that, Calculate the weighting coefficients a 1. a 2. This includes constructing a comparison matrix C, calculating the eigenvectors w1 and w2 corresponding to the vulnerability factors in the comparison matrix C, calculating the maximum eigenvalue based on the eigenvectors w1 and w2, performing a consistency check based on the maximum eigenvalue and the eigenvectors w1 and w2, and if the check passes, normalizing the eigenvectors w1 and w2 to generate weight coefficients. a 1. a 2; If it fails, the comparison matrix C needs to be reconstructed and recalculated.

6. A method for generating a clearing scheme for removing tree branches beside overhead power lines according to claim 5, characterized in that, Constructing the comparison matrix C includes setting the comparison scale: elements k With elements j When elements are equally important, their relative importance is 1. k Compared to elements j When it is slightly important, the relative importance level is 3, and the element k Compared to elements j When clearly important, the relative importance is 5, element k Compared to elements j When it is much more important, the relative importance is 7, and the importance is 2. n -1 and 2 n When the value is between +1 and 2, the relative importance is 2. n ( n= 1,2,3,4); Construct a comparison matrix of three factors based on the comparison scale. ,in, To indicate the importance of factor D relative to factor Y, the values ​​of other elements in the comparison matrix C are determined using the same method.

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