500kV jumper lifting suppression gravity compensation unit and optimal configuration method and device thereof

Abstract

The invention provides a 500kV jumper lifting suppression gravity compensation unit and an optimal configuration method and device thereof. The optimal configuration method comprises the following steps: scanning a jumper wire and a tower by using scanning equipment to obtain three-dimensional point cloud data of the jumper wire and the tower; converting the three-dimensional point cloud data into a three-dimensional live-action model of the jumper and the tower, and importing the three-dimensional live-action model into finite element simulation software; in finite element simulation software, a gravity compensation unit is arranged on the jumper wire, environment parameters of the jumper wire are set, and the environment parameters comprise the wind speed and the wind direction; according to the number, the set position and the weight of the gravity compensation units on the jumper wire, the minimum air gap between the jumper wire and the tower under the environment parameters is calculated; analyzing and calculating a relational expression between the minimum air gap and the number, the setting position and the weight of the gravity compensation units; and according to the relational expression, the number, the set positions and the weight of the gravity compensation units on the jumper wire are determined with the purpose of maximizing the minimum air gap.

Description

Technical Field

[0001] The invention belongs to the field of electric power systems, and in particular relates to a 500kV jumper uplift suppression gravity compensation unit and an optimization configuration method and device thereof. Background Art

[0002] Wind deflection flashover of overhead transmission lines is one of the main reasons that affect the normal operation of the lines and the reliability of power supply. Under the action of wind load, the insulator strings and conductors of overhead transmission lines will be displaced, resulting in changes in the air gap between the conductors and the towers. When the electrical strength of the air gap is less than the line operating voltage or the operating overvoltage and lightning overvoltage, power frequency, operating impulse and lightning impulse breakdown may occur, resulting in dangers such as line tripping. In severe cases, it may even affect the normal operation of the local power grid, causing significant power and economic losses.

[0003] The mechanical characteristics of the jumper of the tension tower of the transmission line in the wind field are different from those of the suspension insulator. The jumper will swing upward under the action of wind load. If the degree of upward movement is too large, it may cause accidents such as discharge flashover. In order to suppress the upward movement of the jumper due to wind deflection and reduce the risk of jumper flashover, it is possible to consider installing spacers with gravity compensation function on the jumper. However, the weight, number and installation position of the gravity compensation spacers will have a great impact on the effect of suppressing the upward movement of the jumper. Therefore, the optimal configuration method of gravity compensation spacers for suppressing the upward movement of the jumper under the action of the 500kV overhead transmission line tension tower under the action of wind field (the weight, number and installation position of gravity compensation spacers) is a problem that needs to be solved. Summary of the invention

[0004] The present invention provides a 500kV jumper uplift suppression gravity compensation unit and an optimized configuration method and device thereof, which can keep the minimum air gap between the jumper and the pole tower in the 500kV overhead transmission line at a high level, ensuring that the jumper will not rise, thereby ensuring that wind deflection flashover will not occur in the overhead transmission line.

[0005] In one aspect, a method for optimizing configuration of a gravity compensation unit is provided, comprising: Scan the jumper and the pole tower using scanning equipment to obtain the three-dimensional point cloud data of the jumper and the pole tower; Converting the three-dimensional point cloud data into a three-dimensional real-scene model of the jumper and the tower, and importing the three-dimensional real-scene model into finite element simulation software; In the finite element simulation software, a gravity compensation unit is set on the jumper, and environmental parameters of the jumper are set, wherein the environmental parameters include wind speed and wind direction; According to the number, location and weight of gravity compensation units on the jumper, the minimum air gap between the jumper and the tower under environmental parameters is calculated; Analyze and calculate the relationship between the minimum air gap and the number, setting position and weight of gravity compensation units; According to the relationship, the number, location and weight of the gravity compensation units on the jumper are determined with the goal of maximizing the minimum air gap.

[0006] Optionally, in the finite element simulation software, a gravity compensation unit is provided on the jumper, and environmental parameters of the jumper are set, wherein the environmental parameters include wind speed and wind direction, including: Importing the number, setting position and weight of gravity compensation units into the finite element simulation software; Based on wind speed and direction, according to the formula The magnitude of the wind load is calculated and imported into the finite element simulation software as an environmental parameter, wherein is the wind speed, is the standard value of the base wind pressure, is the wind pressure height variation coefficient, is the body shape coefficient, is the wind load adjustment factor, is the outer diameter of the transmission wire, is the horizontal span of the tower, is the wind load increase factor when covered with ice, It is the angle between wind direction and jumper direction.

[0007] Optionally, according to the number, installation position and weight of the gravity compensation units on the jumper, the minimum air gap between the jumper and the tower under the environmental parameters is calculated, including: In the finite element simulation software, the three-dimensional real scene model is meshed, and the calculation step is set to perform simulation calculation on the three-dimensional real scene model; The gap circle method is used to find the point with the minimum air gap in the 3D real scene model, so as to obtain the minimum air gap between the jumper and the tower under the conditions of the current number, setting position and weight of the gravity compensation unit and the current environmental parameters; The number, setting position and weight of the gravity compensation units set in the finite element simulation software are adjusted, and the minimum air gap between the jumper and the tower is calculated again to obtain the relationship data between the minimum air gap and the number, setting position and weight of the gravity compensation spacer rods at a specific wind speed and wind direction as the first data set; The environmental parameters of the jumper in the finite element simulation software were adjusted to obtain the relationship data between the minimum air gap and the number, setting position, and weight of the gravity compensation units under different wind speeds and directions as the second data set.

[0008] Optionally, analyzing and calculating the relationship between the minimum air gap and the number, setting position, and weight of the gravity compensation units includes: According to the first data set and the second data set, the minimum air gap between the transmission line and the tower and the number of gravity compensation units are obtained by fitting. , Set location ,weight Function mapping relationship between .

[0009] Optionally, according to the relationship, with the goal of maximizing the minimum air gap, determining the number, setting position and weight of the gravity compensation units on the jumper includes: To minimize the air gap Maximize the number of gravity compensation units as the optimization objective ,Location ,weight As optimization variables; Determine the quantity based on the mechanical strength of the jumper. and gravity The setting position is determined according to the jumper length. Constraints of Determine the size of the particle swarm and initialize the particle swarm, randomly assign the particles initial positions and initial velocities, and the initial position of the jth particle is expressed as , , and They represent the weight, quantity and setting position of the gravity compensation unit represented by the jth particle respectively. The initial velocity of the jth particle is expressed as , , and Respectively , and The direction of optimization; Update the particle's position and velocity, and calculate the position and velocity required for the next iteration; the update formula is as follows: , ; In the formula, is the velocity of the jth particle at the tth iteration, is the velocity of the jth particle at the t+1th iteration; is the optimal position of the particle itself, that is, the best solution that each particle has found; is the global optimal position, that is, the best solution found by all particles in the particle swarm; , It is a random number between [0,1], used to increase the randomness and diversity of the algorithm; is the position of the jth particle at the tth iteration, is the new position of particle j at the t+1th iteration; is the inertia weight, is the individual learning factor, is the group learning factor; Asymmetric hyperbolic sine function is used to update inertia weight; The nonlinear update strategy of cosine function is used to dynamically adjust the learning factor; Calculate the fitness value of each particle according to its position, and record the individual historical fitness optimal solution and the global historical fitness optimal solution of each particle after each iteration; The number of updates of the particle's position and velocity meets the maximum number of iterations When , the position of the particle corresponding to the global historical optimal fitness solution is output As a result.

[0010] Optionally, an asymmetric hyperbolic sine function is used to update the inertia weight, including: Using formula Update the inertia weight. is the updated inertia weight, is the minimum value of the inertia weight set, is the maximum value of the inertia weight set, is the number of iterations of the current particle, The maximum number of iterations for the set particles. and is the parameter for adjusting the shape of the function. Used to control the slope of the function, Used to control function offset.

[0011] Optionally, the learning factor is dynamically adjusted using a nonlinear update strategy of the cosine function, including: The individual learning factor and the group learning factor are adjusted according to the learning factor adjustment. The learning factor adjustment formula includes:

[0012] in, is the updated individual learning factor, is the updated group learning factor, is the minimum value of the individual learning factor set, is the maximum value of the individual learning factor set, is the minimum value of the group learning factor set, is the maximum value of the group learning factor, is the number of iterations of the current particle, The maximum number of iterations for the set particles.

[0013] Optionally, the fitness value of each particle is calculated according to the position of the particle, and the individual historical fitness optimal solution and the global historical fitness optimal solution of each particle after each iteration are recorded, including: Determine the minimum air gap between particles based on their position , For the The particle in The minimum air gap at the iteration, According to the minimum air gap of the particles , using the formula Determine the fitness value of the particle ,in, It is the minimum air gap at which the jumper will not rise; Statistically update the optimal solution of each particle's individual historical fitness value and the optimal solution of the global historical fitness value.

[0014] On the other hand, there is provided an optimized configuration device for a gravity compensation unit, comprising: A three-dimensional real scene model generation module uses a scanning device to scan the jumper and the pole tower to obtain three-dimensional point cloud data of the jumper and the pole tower; converts the three-dimensional point cloud data into a three-dimensional real scene model of the jumper and the pole tower, and imports the three-dimensional real scene model into a finite element simulation software; A simulation module, in a finite element simulation software, sets a gravity compensation unit on the jumper and sets environmental parameters of the jumper, wherein the environmental parameters include wind speed and wind direction; and calculates a minimum air gap between the jumper and the tower under the environmental parameters according to the number, setting position and weight of the gravity compensation units on the jumper; The analysis and processing module is used to analyze and calculate the relationship between the minimum air gap and the number, setting position and weight of the gravity compensation units; based on the relationship, the number, setting position and weight of the gravity compensation units on the jumper are determined with the goal of maximizing the minimum air gap.

[0015] In another aspect, a gravity compensation unit is provided, comprising: main body; Support legs, a plurality of support legs are arranged at intervals on the side of the main body, and the support legs are used to fix the jumper wires; The counterweight modules are evenly arranged on two opposite sides of the main body.

[0016] The technical solution provided by the embodiments of the present disclosure has the following beneficial effects: In an embodiment of the present disclosure, a method for optimizing the configuration of a gravity compensation unit is provided. The method establishes a three-dimensional real-scene model by acquiring three-dimensional point cloud data of a jumper and a pole tower. A simulation is performed in a finite element simulation software based on the three-dimensional real-scene model to obtain the relationship between the number, setting position, weight and minimum air gap of the gravity compensation units. And based on the relationship between the number, setting position, weight and minimum air gap of the gravity compensation units, the number, setting position and weight of the gravity compensation units on the jumper are optimized, thereby maximizing the minimum air gap between the jumper and the pole tower. A larger air gap can avoid wind deflection flashover phenomenon, thereby ensuring the safety of overhead transmission lines. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0018] Figure 1 A structural schematic diagram of a gravity compensation unit provided in an embodiment of the present disclosure; Figure 2 A structural schematic diagram of another gravity compensation unit provided in an embodiment of the present disclosure; Figure 3 A method flow chart of an optimization configuration method of a gravity compensation unit provided in an embodiment of the present disclosure; Figure 4 A structural block diagram of an optimized configuration device for a gravity compensation unit provided in an embodiment of the present disclosure Figure 5 A structural block diagram of an electronic device provided in an embodiment of the present disclosure.

[0019] The reference numerals are as follows: 1: Main body; 11: Circular groove; 12: Fixing hole for counterweight module; 13: Fixing hole for support leg; 2: Support leg; 21: Support leg body; 22: Wire fastening structure; 23: Wire damping structure; 24: Support leg fastener; 3: counterweight module; 31: counterweight block; 32: counterweight block damping structure; 33: counterweight block fixing part; 41: 3D real scene model generation module; 42: simulation module; 43: analysis and processing module 4; 51: processor; 52: memory. DETAILED DESCRIPTION

[0020] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0021] The present invention proposes a gravity compensation unit and an optimal configuration method thereof. Numerical calculation is carried out based on a three-dimensional real-scene model of a jumper and a pole tower. Through the weight, quantity and setting position of the gravity compensation unit, a functional mapping relationship between the minimum air gap and the number, setting position and weight of the gravity compensation unit is fitted according to the simulation calculation result. The weight, quantity and setting position of the gravity compensation unit are used as optimization variables, and an improved SC-PSO algorithm is used for optimization. The optimal configuration scheme of the best gravity compensation unit is obtained, so as to ensure that when the gravity compensation unit is set on the jumper and the pole tower, the minimum air gap between the jumper and the pole tower can be made larger, so as to avoid the occurrence of discharge flashover and the like, and ensure the safety performance of the jumper and the pole tower.

[0022] Figure 1 A structural schematic diagram of a gravity compensation unit provided in an embodiment of the present disclosure. Figure 1 It is the overall schematic diagram of the gravity compensation unit.

[0023] Figure 2 This is a schematic diagram of the structure of another gravity compensation unit provided by an embodiment of the present disclosure. Figure 2 , Figure 2 for Figure 1 Schematic diagram of the gravity compensation unit after being disassembled. The gravity compensation unit includes: Subject 1; Support legs 2, a plurality of support legs 2 are arranged at intervals on the side of the main body 1, and the support legs 1 are used to fix the jumper wires; The counterweight modules 3 are evenly arranged on two opposite sides of the main body 1 .

[0024] In an embodiment of the present disclosure, a gravity compensation unit is provided, which includes a main body, a plurality of supporting legs arranged on the sides of the main body, and counterweight modules evenly arranged on both sides of the main body. The plurality of supporting legs can ensure that the gravity compensation unit can be fixed to a plurality of jumpers, and the counterweight modules evenly arranged on both sides of the main body can ensure that the center of gravity of the main body will not be offset, and the weight of the counterweight modules on both sides of the main body can be adjusted according to actual needs to adjust the minimum air gap between the jumper and the pole tower.

[0025] In the disclosed embodiment, the main body 1 is a square solid aluminum alloy casting plate with a thickness of 30 to 50 mm, for example, a thickness of 40 mm.

[0026] A circular groove 11 with a depth of 2-3 mm is opened in the center of the main body 1 to install the counterweight module 3 , and the diameter of the circular groove 11 matches the diameter of the counterweight module 3 .

[0027] A counterweight module fixing hole 12 is formed in the main body 1 in an area adjacent to the circular groove 11 .

[0028] The four corners of the main body 1 are arc-shaped structures, and support leg fixing holes 13 are opened on the arc-shaped structures for installing four support legs 2.

[0029] In the embodiment of the present disclosure, the supporting leg 2 includes a supporting leg body 21 , a wire fastening structure 22 , a wire damping structure 23 and a supporting leg fastener 24 .

[0030] The wire fastening structure 22 is arranged on the supporting leg body 21, and a wire through hole is provided on the wire fastening structure 22. After the wire passes through the wire through hole on the wire fastening structure 22, the wire can be fixed in the wire fastening structure 22 by adjusting the tightness of the wire fastening structure 22. The diameter of the wire through hole can be 25-35 mm, so as to use wires of different diameters.

[0031] The wire damping structure 23 is made of wear-resistant rubber material, embedded in the inner side of the wire through hole opened on the wire fastening structure 22, and uses the plasticity of the rubber material to damp the vibration of the wire.

[0032] The support leg fasteners 24 include bolts, nuts, flat washers, and spring washers, and are used to fasten the wire support legs to the central fixing plate.

[0033] In the embodiment of the present disclosure, the counterweight module 3 includes a counterweight block 31 , a counterweight block damping structure 32 , and a counterweight block fixing member 33 .

[0034] There are two counterweight blocks 31, which are cylindrical structures and made of stainless steel, and are installed on both sides of the central fixing plate through counterweight block fixing members 33. The thickness of each counterweight block 31 is 10-30 mm, and the specific thickness is determined by the gravity requirement to be compensated.

[0035] The counterweight damping structure 32 is a circular structure with a thickness of 3-5 mm, and is embedded in the circular groove 11 of the main body 1 and the counterweight 31. The counterweight damping structure 32 is formed of a wear-resistant rubber material and is used for breeze vibration between the main body 1 and the counterweight.

[0036] The counterweight fixing member 33 includes bolts, nuts, flat washers, and spring washers, and is used to fix the counterweight 31 to the main body 1 .

[0037] Figure 3A method flow chart of an optimization configuration method of a gravity compensation unit provided in an embodiment of the present disclosure. Figure 3 The method steps include: S101. Scan the jumper and the pole tower using a scanning device to obtain three-dimensional point cloud data of the jumper and the pole tower.

[0038] Among them, laser radar equipment is used to scan the actual 500kV overhead transmission line tension tower to obtain three-dimensional real-scene point cloud data.

[0039] S102, converting the three-dimensional point cloud data into a three-dimensional real-scene model of the jumper and the tower, and importing the three-dimensional real-scene model into finite element simulation software.

[0040] S103, in finite element simulation software, setting a gravity compensation unit on the jumper, and setting environmental parameters of the jumper, wherein the environmental parameters include wind speed and wind direction.

[0041] In one example, step S103 includes: The first step is to import the number, setting position and weight of the gravity compensation unit into the finite element simulation software.

[0042] In the first step, parameters such as jumper length, jumper mass, and gravity acceleration are also set in the finite element simulation software.

[0043] Step 2: Based on wind speed and direction, according to the formula The magnitude of the wind load is calculated and imported into the finite element simulation software as an environmental parameter, wherein is the wind speed, is the standard value of the base wind pressure, is the wind pressure height variation coefficient, is the body shape coefficient, is the wind load adjustment factor, is the outer diameter of the transmission wire, is the horizontal span of the tower, is the wind load increase factor when covered with ice, It is the angle between wind direction and jumper direction.

[0044] In the disclosed embodiment, the wind load is calculated according to the actual wind speed and wind direction data by using the above formula, and the actual environment is simulated by introducing the specific value of the wind load into the finite element simulation element.

[0045] S104. Calculate the minimum air gap between the jumper and the pole tower under environmental parameters according to the number, installation position and weight of the gravity compensation units on the jumper.

[0046] In one example, step S104 includes: The first step is to divide the three-dimensional real scene model into meshes in the finite element simulation software, set the calculation step size, and perform simulation calculations on the three-dimensional real scene model.

[0047] The second step is to use the gap circle method to find the point with the minimum air gap in the three-dimensional real-scene model, so as to obtain the minimum air gap between the jumper and the tower under the conditions of the current number, setting position and weight of the gravity compensation units and the current environmental parameters.

[0048] The third step is to adjust the number, location and weight of the gravity compensation units set in the finite element simulation software, calculate the minimum air gap between the jumper and the tower again, and obtain the relationship data between the minimum air gap and the number, location and weight of the gravity compensation spacer rods at a specific wind speed and wind direction as the first data set.

[0049] The fourth step is to adjust the environmental parameters of the jumper in the finite element simulation software to obtain the relationship data between the minimum air gap and the number, setting position, and weight of the gravity compensation unit under different wind speed and wind direction conditions as the second data set.

[0050] In the embodiment of the present disclosure, in the simulation software, simulation is performed according to the three-dimensional real scene model obtained in the actual scene, the set environmental parameters, etc., and the point with the minimum air gap is found in the three-dimensional real scene model by the gap circle method to obtain the size of the minimum air gap. By continuously adjusting the number, setting position and weight of the gravity compensation unit, and continuously adjusting the wind speed and wind direction, the corresponding relationship between the number, setting position, weight, wind speed and wind direction of the gravity compensation unit is obtained, and the optimization conditions are constructed for the subsequent optimization step of the gravity compensation unit.

[0051] S105. Analyze and calculate the relationship between the minimum air gap and the number, setting position, and weight of the gravity compensation units.

[0052] In one example, step S105 includes: According to the first data set and the second data set, the minimum air gap between the transmission line and the tower and the number of gravity compensation units are obtained by fitting. , Set location ,weight Function mapping relationship between .

[0053] In the embodiment of the present disclosure, a function mapping relationship can be obtained by fitting the data in the first data set and the second data set. The function mapping relationship is the basic relationship for optimization in step S106.

[0054] S106. According to the relationship, with the goal of maximizing the minimum air gap, determine the number, installation position and weight of the gravity compensation units on the jumper.

[0055] In one example, step S106 includes: Step 1: Minimum air gap Maximize the number of gravity compensation units as the optimization objective ,Location ,weight as optimization variables.

[0056] Step 2: Determine the quantity based on the mechanical strength of the jumper wires and gravity The setting position is determined according to the jumper length. constraints.

[0057] The mechanical strength of the jumper can be the mechanical strength of the jumper itself or the mechanical strength of the jumper clip. In step 2, the deadweight of the jumper needs to be further considered to establish the constraint condition. That is, the product of the number and weight of the gravity compensation units plus the deadweight of the jumper does not exceed the mechanical strength of the jumper clip.

[0058] Step 3: Determine the size of the particle swarm and initialize the particle swarm, randomly assign the particles initial positions and initial velocities, and the initial position of the jth particle is expressed as , , and They represent the weight, quantity and setting position of the gravity compensation unit represented by the jth particle respectively. The initial velocity of the jth particle is expressed as , , and Respectively , and Optimization direction.

[0059] Step 4: Update the position and velocity of the particle, and calculate the position and velocity required for the next iteration; the update formula is as follows: , ; In the formula, is the velocity of the jth particle at the tth iteration, is the velocity of the jth particle at the t+1th iteration; is the optimal position of the particle itself, that is, the best solution that each particle has found; is the global optimal position, that is, the best solution found by all particles in the particle swarm; , It is a random number between [0,1], used to increase the randomness and diversity of the algorithm; is the position of the jth particle at the tth iteration, is the new position of particle j at the t+1th iteration; is the inertia weight, is the individual learning factor, is the group learning factor.

[0060] In step 4, the total number of iterations is set to , the value range is 500~1000 times, for example 600 times.

[0061] Step 5: Use an asymmetric hyperbolic sine function to update the inertia weight.

[0062] In one example, step 5 includes: Using formula Update the inertia weight. is the updated inertia weight, is the minimum value of the inertia weight set, is the maximum value of the inertia weight set, is the number of iterations of the current particle, The maximum number of iterations for the set particles. and is the parameter for adjusting the shape of the function. Used to control the slope of the function, Used to control function offset.

[0063] in, 0.1~0.4, 0.8~1.2, 2~5, is 0.

[0064] For example, is 0.3, is 0.9, is 4, is 0.

[0065] In the disclosed embodiment, the inertia weight controls the influence of the current speed of the particle on the next speed. If the inertia weight is large, the particle will have a larger search range during the search process; otherwise, the particle search will be more detailed. The present invention uses an asymmetric hyperbolic sine function to update the inertia weight, which can make the inertia weight value larger in the initial stage of optimization, enhancing the global search capability; smaller in the later stage, enhancing the local search capability, and ultimately making the search more detailed and the optimization more accurate. is the minimum value of the inertia weight. To ensure that the particle has a strong local search ability in the search space, it is set to a small positive value; It is the maximum value of the inertia weight. To ensure that particles have greater inertia in the initial stage, set it to a larger positive value.

[0066] Step 6: Use the nonlinear update strategy of the cosine function to dynamically adjust the learning factor.

[0067] In one example, step 6 includes: The individual learning factor and the group learning factor are adjusted according to the learning factor adjustment. The learning factor adjustment formula includes:

[0068] in, is the updated individual learning factor, is the updated group learning factor, is the minimum value of the individual learning factor set, is the maximum value of the individual learning factor set, is the minimum value of the group learning factor set, is the maximum value of the group learning factor, is the number of iterations of the current particle, The maximum number of iterations for the set particles.

[0069] in, and 0.5~1, and It is 1.5~2.5.

[0070] For example, is 0.6, is 0.7, is 1.7, is 2.

[0071] In the disclosed embodiment, the learning factor determines the speed at which the particle moves to its own optimal position and the global optimal position. In order to make the learning factor gradually change during the iteration process, the present invention adopts a nonlinear update strategy based on the cosine function to dynamically adjust the learning factor, so that the learning factor can be larger in the initial stage of optimization to enhance the global search capability; smaller in the later stage to enhance the local search capability, thereby enhancing different search characteristics at different stages.

[0072] Step 7: Calculate the fitness value of each particle according to its position, and record the individual historical fitness optimal solution and the global historical fitness optimal solution of each particle after each iteration.

[0073] In one example, step 7 includes: The first step is to determine the minimum air gap of the particles based on their position. , For the The particle in Minimum air gap at iterations.

[0074] Step 2: Based on the minimum air gap of particles , using the formula Determine the fitness value of the particle ,in, This is the minimum air gap at which the jumper will not rise.

[0075] The third step is to statistically update the optimal solution of each particle's individual historical fitness and the optimal solution of the global historical fitness value.

[0076] In the disclosed embodiment, the setting of the fitness function can effectively reflect the distance between each particle and the optimal solution. The present invention sets the fitness function as the relative error of the minimum air gap. By counting the individual historical fitness optimal solution and the global historical fitness value optimal solution, after the iteration is completed, the optimal number, setting position and weight of the gravity compensation unit can be obtained.

[0077] Step 8: When the number of updates of the particle's position and velocity meets the maximum number of iterations When , the position of the particle corresponding to the global historical optimal fitness solution is output As a result.

[0078] In the embodiment of the present disclosure, the weight, setting position and number of the gravity compensation unit are optimized through the above steps to obtain the optimal configuration of the gravity compensation unit.

[0079] In an embodiment of the present disclosure, a method for optimizing the configuration of a gravity compensation unit is provided. The method establishes a three-dimensional real-scene model by acquiring three-dimensional point cloud data of a jumper and a pole tower. A simulation is performed in a finite element simulation software based on the three-dimensional real-scene model to obtain the relationship between the number, setting position, weight and minimum air gap of the gravity compensation units. And based on the relationship between the number, setting position, weight and minimum air gap of the gravity compensation units, the number, setting position and weight of the gravity compensation units on the jumper are optimized, thereby maximizing the minimum air gap between the jumper and the pole tower. A larger air gap can avoid wind deflection flashover phenomenon, thereby ensuring the safety of overhead transmission lines.

[0080] Figure 4 This is a structural block diagram of an optimized configuration device for a gravity compensation unit provided in an embodiment of the present disclosure. Figure 4 , the device comprises: The three-dimensional real scene model generation module 41 uses a scanning device to scan the jumper and the pole tower to obtain three-dimensional point cloud data of the jumper and the pole tower; converts the three-dimensional point cloud data into a three-dimensional real scene model of the jumper and the pole tower, and imports the three-dimensional real scene model into a finite element simulation software.

[0081] Simulation module 42, in the finite element simulation software, sets a gravity compensation unit on the jumper and sets environmental parameters of the jumper, wherein the environmental parameters include wind speed and wind direction; and calculates the minimum air gap between the jumper and the pole tower under the environmental parameters according to the number, setting position and weight of the gravity compensation units on the jumper.

[0082] The analysis and processing module 43 is used to analyze and calculate the relationship between the minimum air gap and the number, setting position and weight of the gravity compensation units; based on the relationship, the number, setting position and weight of the gravity compensation units on the jumper are determined with the goal of maximizing the minimum air gap.

[0083] Optionally, the simulation module 41 is used for: Importing the number, setting position and weight of gravity compensation units into the finite element simulation software; Based on wind speed and direction, according to the formula The magnitude of the wind load is calculated and imported into the finite element simulation software as an environmental parameter, wherein is the wind speed, is the standard value of the base wind pressure, is the wind pressure height variation coefficient, is the body shape coefficient, is the wind load adjustment factor, is the outer diameter of the transmission wire, is the horizontal span of the tower, is the wind load increase factor when covered with ice, It is the angle between wind direction and jumper direction.

[0084] Optionally, the simulation module 42 is used to: In the finite element simulation software, the three-dimensional real scene model is meshed, and the calculation step is set to perform simulation calculation on the three-dimensional real scene model; The gap circle method is used to find the point with the minimum air gap in the 3D real scene model, so as to obtain the minimum air gap between the jumper and the tower under the conditions of the current number, setting position and weight of the gravity compensation unit and the current environmental parameters; The number, setting position and weight of the gravity compensation units set in the finite element simulation software are adjusted, and the minimum air gap between the jumper and the tower is calculated again to obtain the relationship data between the minimum air gap and the number, setting position and weight of the gravity compensation spacer rods at a specific wind speed and wind direction as the first data set; The environmental parameters of the jumper in the finite element simulation software were adjusted to obtain the relationship data between the minimum air gap and the number, setting position, and weight of the gravity compensation units under different wind speeds and directions as the second data set.

[0085] Optionally, the analysis and calculation module 43 is used to: According to the first data set and the second data set, the minimum air gap between the transmission line and the tower and the number of gravity compensation units are obtained by fitting. , Set location ,weight Function mapping relationship between .

[0086] Optionally, the analysis and calculation module 43 is used to: To minimize the air gap Maximize the number of gravity compensation units as the optimization objective ,Location ,weight As optimization variables; Determine the quantity based on the mechanical strength of the jumper. and gravity The setting position is determined according to the jumper length. Constraints of Determine the size of the particle swarm and initialize the particle swarm, randomly assign the particles initial positions and initial velocities, and the initial position of the jth particle is expressed as , , and They represent the weight, quantity and setting position of the gravity compensation unit represented by the jth particle respectively. The initial velocity of the jth particle is expressed as , , and Respectively , and The direction of optimization; Update the particle's position and velocity, and calculate the position and velocity required for the next iteration; the update formula is as follows: , ; In the formula, is the velocity of the jth particle at the tth iteration, is the velocity of the jth particle at the t+1th iteration; is the optimal position of the particle itself, that is, the best solution that each particle has found; is the global optimal position, that is, the best solution found by all particles in the particle swarm; , It is a random number between [0,1], used to increase the randomness and diversity of the algorithm; is the position of the jth particle at the tth iteration, is the new position of particle j at the t+1th iteration; is the inertia weight, is the individual learning factor, is the group learning factor; Asymmetric hyperbolic sine function is used to update inertia weight; The nonlinear update strategy of cosine function is used to dynamically adjust the learning factor; Calculate the fitness value of each particle according to its position, and record the individual historical fitness optimal solution and the global historical fitness optimal solution of each particle after each iteration; The number of updates of the particle's position and velocity meets the maximum number of iterations When , the position of the particle corresponding to the global historical optimal fitness solution is output As a result.

[0087] Optionally, the analysis and calculation module 43 is used to: Using formula Update the inertia weight. is the updated inertia weight, is the minimum value of the inertia weight set, is the maximum value of the inertia weight set, is the number of iterations of the current particle, The maximum number of iterations for the set particles. and is the parameter for adjusting the shape of the function. Used to control the slope of the function, Used to control function offset.

[0088] Optionally, the analysis and calculation module 43 is used to: The individual learning factor and the group learning factor are adjusted according to the learning factor adjustment. The learning factor adjustment formula includes:

[0089] in, is the updated individual learning factor, is the updated group learning factor, is the minimum value of the individual learning factor set, is the maximum value of the individual learning factor set, is the minimum value of the group learning factor set, is the maximum value of the group learning factor, is the number of iterations of the current particle, The maximum number of iterations for the set particles.

[0090] Optionally, the analysis and calculation module 43 is used to: Determine the minimum air gap between particles based on their position , For the The particle in The minimum air gap at the iteration; According to the minimum air gap of the particles , using the formula Determine the fitness value of the particle ,in, It is the minimum air gap at which the jumper will not rise; Statistically update the optimal solution of each particle's individual historical fitness value and the optimal solution of the global historical fitness value.

[0091] Figure 5 This is a structural block diagram of an electronic device provided by an embodiment of the present disclosure. Figure 5 , the electronic device may include an optimized configuration device of the gravity compensation unit. Generally, the electronic device includes: a processor 51 and a memory 52.

[0092] The processor 51 may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 51 may be implemented in at least one hardware form of DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array). The processor 51 may also include a main processor and a coprocessor. The main processor is a processor for processing data in the awake state, also known as a CPU (Central Processing Unit); the coprocessor is a low-power processor for processing data in the standby state.

[0093] The memory 52 may include one or more computer-readable storage media, which may be non-transitory. The memory 52 may also include a high-speed random access memory, and a non-volatile memory, such as one or more disk storage devices, flash memory storage devices. In some embodiments, the non-transitory computer-readable storage medium in the memory 52 is used to store at least one instruction, which is used to be executed by the processor 51 to implement the method for optimizing the configuration of the gravity compensation unit performed by the electronic device provided in the method embodiment of the present application.

[0094] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for optimizing the configuration of a gravity compensation unit, characterized in that: include: Scan the jumper and the pole tower using scanning equipment to obtain the three-dimensional point cloud data of the jumper and the pole tower; Converting the three-dimensional point cloud data into a three-dimensional real-scene model of the jumper and the tower, and importing the three-dimensional real-scene model into finite element simulation software; In the finite element simulation software, a gravity compensation unit is set on the jumper, and environmental parameters of the jumper are set, wherein the environmental parameters include wind speed and wind direction; According to the number, location and weight of gravity compensation units on the jumper, the minimum air gap between the jumper and the tower under environmental parameters is calculated; Analyze and calculate the relationship between the minimum air gap and the number, setting position and weight of gravity compensation units; According to the relationship, the number, location and weight of the gravity compensation units on the jumper are determined with the goal of maximizing the minimum air gap.

2. The method for optimizing the configuration of the gravity compensation unit according to claim 1, characterized in that: In the finite element simulation software, a gravity compensation unit is set on the jumper, and the environmental parameters of the jumper are set. The environmental parameters include wind speed and wind direction, including: Importing the number, setting position and weight of gravity compensation units into the finite element simulation software; Based on wind speed and direction, according to the formula The magnitude of the wind load is calculated and imported into the finite element simulation software as an environmental parameter, wherein is the wind speed, is the standard value of the base wind pressure, is the wind pressure height variation coefficient, is the body shape coefficient, is the wind load adjustment factor, is the outer diameter of the transmission wire, is the horizontal span of the tower, is the wind load increase factor when covered with ice, It is the angle between wind direction and jumper direction.

3. The method for optimizing the configuration of the gravity compensation unit according to claim 2, characterized in that: Based on the number, location and weight of the gravity compensation units on the jumper, the minimum air gap between the jumper and the tower under environmental parameters is calculated, including: In the finite element simulation software, the three-dimensional real scene model is meshed, and the calculation step is set to perform simulation calculation on the three-dimensional real scene model; The gap circle method is used to find the point with the minimum air gap in the 3D real scene model, so as to obtain the minimum air gap between the jumper and the tower under the conditions of the current number, setting position and weight of the gravity compensation unit and the current environmental parameters; The number, setting position and weight of the gravity compensation units set in the finite element simulation software are adjusted, and the minimum air gap between the jumper and the tower is calculated again to obtain the relationship data between the minimum air gap and the number, setting position and weight of the gravity compensation spacer rods at a specific wind speed and wind direction as the first data set; The environmental parameters of the jumper in the finite element simulation software were adjusted to obtain the relationship data between the minimum air gap and the number, setting position, and weight of the gravity compensation units under different wind speeds and directions as the second data set.

4. The method for optimizing the configuration of the gravity compensation unit according to claim 3, characterized in that: Analyze and calculate the relationship between the minimum air gap and the number, setting position, and weight of the gravity compensation units, including: According to the first data set and the second data set, the minimum air gap between the transmission line and the tower and the number of gravity compensation units are obtained by fitting. , Set location ,weight Function mapping relationship between .

5. The method for optimizing the configuration of the gravity compensation unit according to claim 4, characterized in that: According to the relationship, the number, location and weight of the gravity compensation units on the jumper are determined with the goal of maximizing the minimum air gap, including: To minimize the air gap Maximize the number of gravity compensation units as the optimization objective ,Location ,weight As optimization variables; Determine the quantity based on the mechanical strength of the jumper. and gravity The setting position is determined according to the jumper length. Constraints of Determine the size of the particle swarm and initialize the particle swarm, randomly assign the particles initial positions and initial velocities, and the initial position of the jth particle is expressed as , , and They represent the weight, quantity and setting position of the gravity compensation unit represented by the jth particle respectively. The initial velocity of the jth particle is expressed as , , and Respectively , and The direction of optimization; Update the particle's position and velocity, and calculate the position and velocity required for the next iteration; the update formula is as follows: , ; In the formula, is the velocity of the jth particle at the tth iteration, is the velocity of the jth particle at the t+1th iteration; is the optimal position of the particle itself, that is, the best solution that each particle has found; is the global optimal position, that is, the best solution found by all particles in the particle swarm; , It is a random number between [0,1], used to increase the randomness and diversity of the algorithm; is the position of the jth particle at the tth iteration, is the new position of particle j at the t+1th iteration; is the inertia weight, is the individual learning factor, is the group learning factor; Asymmetric hyperbolic sine function is used to update inertia weight; The nonlinear update strategy of cosine function is used to dynamically adjust the learning factor; Calculate the fitness value of each particle according to its position, and record the individual historical fitness optimal solution and the global historical fitness optimal solution of each particle after each iteration; The number of updates of the particle's position and velocity meets the maximum number of iterations When , the position of the particle corresponding to the global historical optimal fitness solution is output As a result.

6. The method for optimizing the configuration of the gravity compensation unit according to claim 5, characterized in that: An asymmetric hyperbolic sine function is used to update the inertia weight, including: Using formula Update the inertia weight. is the updated inertia weight, is the minimum value of the inertia weight set, is the maximum value of the inertia weight set, is the number of iterations of the current particle, The maximum number of iterations for the set particles. and is the parameter for adjusting the shape of the function. Used to control the slope of the function, Used to control function offset.

7. The method for optimizing the configuration of a gravity compensation unit according to claim 5, characterized in that: The nonlinear update strategy of the cosine function is used to dynamically adjust the learning factor, including: The individual learning factor and the group learning factor are adjusted according to the learning factor adjustment. The learning factor adjustment formula includes: in, is the updated individual learning factor, is the updated group learning factor, is the minimum value of the individual learning factor set, is the maximum value of the individual learning factor set, is the minimum value of the group learning factor set, is the maximum value of the group learning factor, is the number of iterations of the current particle, The maximum number of iterations for the set particles.

8. The method for optimizing the configuration of a gravity compensation unit according to claim 5, characterized in that: The fitness value of each particle is calculated according to the position of the particle, and the individual historical fitness optimal solution and the global historical fitness optimal solution of each particle after each iteration are recorded, including: Determine the minimum air gap between particles based on their position , For the The particle in The minimum air gap at iterations; According to the minimum air gap of the particles , using the formula Determine the fitness value of the particle ,in, It is the minimum air gap at which the jumper will not rise; Statistically update the optimal solution of each particle's individual historical fitness value and the optimal solution of the global historical fitness value.

9. An optimized configuration device for a gravity compensation unit, characterized in that: include: The 3D real scene model generation module uses scanning equipment to scan the jumper and the tower to obtain the 3D point cloud data of the jumper and the tower; Converting the three-dimensional point cloud data into a three-dimensional real-scene model of the jumper and the tower, and importing the three-dimensional real-scene model into finite element simulation software; A simulation module, in a finite element simulation software, sets a gravity compensation unit on the jumper and sets environmental parameters of the jumper, wherein the environmental parameters include wind speed and wind direction; and calculates a minimum air gap between the jumper and the tower under the environmental parameters according to the number, setting position and weight of the gravity compensation units on the jumper; The analysis and processing module is used to analyze and calculate the relationship between the minimum air gap and the number, setting position and weight of the gravity compensation units; based on the relationship, the number, setting position and weight of the gravity compensation units on the jumper are determined with the goal of maximizing the minimum air gap.

10. A gravity compensation unit, characterized in that: include: main body; Support legs, a plurality of support legs are arranged at intervals on the side of the main body, and the support legs are used to fix the jumper wires; The counterweight modules are evenly arranged on two opposite sides of the main body.

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