Power transmission line wind-resistant component parameter optimization method and device, storage medium and equipment

Abstract

The invention discloses a power transmission line wind-resistant component parameter optimization method and device, a storage medium and equipment. The method relates to the technical field of power transmission line strong wind resistance component parameter optimization, and comprises the following steps: obtaining operation parameters of a target wind power plant in real time; performing feature extraction on the operation parameters to obtain key wind field parameters; according to the key wind field parameters and a preset wind deflection angle prediction model, multiple times of prediction are carried out on different operation conditions of the wind power plant to obtain influence rules and correction coefficients of different influence factors influencing the wind deflection angle of the insulator string of the wind power plant; and based on the influence rule and the correction coefficient, optimizing the structural parameters of the target wind-resistant component by taking the key wind field parameters as boundary constraint conditions to obtain a parameter optimization result of the power transmission line wind-resistant component meeting the multi-target requirement. According to the method provided by the invention, collaborative optimization and accurate design of the wind-resistant component in pneumatic, structural and electrical performance are realized, so that the economy and reliability of the circuit are improved while the safety is guaranteed.

Description

Technical Field

[0001] This invention relates to the field of parameter optimization technology for wind-resistant components of transmission lines, and particularly to a method, apparatus, storage medium, and equipment for optimizing the parameters of wind-resistant components of transmission lines. Background Technology

[0002] The safety assessment of wind-induced deflection gaps in transmission lines and the optimization of typical components to withstand strong winds primarily involve evaluating the safety performance of transmission lines under strong wind conditions and improving the strong wind resistance of typical components through optimized design to ensure the stable operation and safety of transmission lines. Under strong wind conditions, the live conductors of transmission lines may experience insufficient clearance with line towers, guy wires, other phase conductors, nearby trees, buildings, etc., leading to atmospheric breakdown voltage and causing line tripping faults. Therefore, it is necessary to strengthen research on wind-induced deflection faults, reduce the possibility of wind-induced flashover, and ensure the stable transmission of power. Areas prone to wind-induced flashover faults typically experience strong winds formed by severe convective weather. These strong winds are characterized by rapid onset, rapid dissipation, and intermittent nature, generally lasting for tens of minutes, and are highly likely to be accompanied by heavy rain or hail. In such harsh environments, transmission line conductors can shift and deflect towards the tower due to strong winds, reducing the air discharge gap between the line and other conductors and easily leading to wind-induced deflection faults. For angle towers with an angle of less than 20 degrees, jumper strings should be installed to reduce the occurrence of tripping faults. If necessary, post-type windproof insulators can be used to prevent large swinging of the jumper strings. Windproof guy wires are mainly constructed by adding insulators and guy wires to fix the suspension insulators or conductors relatively, preventing them from discharging to the tower under strong winds. In windless conditions, the guy wires remain vertically taut due to the force of the counterweight; under maximum wind deflection conditions, the maximum travel of the guy wires is limited by the sliding end. For 220kV transmission lines, the length of tempered glass insulator strings or porcelain insulator strings has been significantly increased during the renovation process, thereby shortening the net space between the tower and the tower window in strong wind conditions. After replacing porcelain insulator strings with composite insulator suspension strings, it is essential to verify the air gap and wind deflection angle. Traditional transmission line wind-resistant design suffers from limitations such as inaccurate input, imprecise models, isolated designs, and one-sided verification. Summary of the Invention

[0003] In view of this, the present invention provides a method, apparatus, storage medium and equipment for optimizing the parameters of wind-resistant components of transmission lines, the main purpose of which is to solve the problem of inaccurate determination of component parameters in the current traditional wind-resistant design of transmission lines.

[0004] To address the above problems, this application provides a method for optimizing the parameters of wind-resistant components of transmission lines, including: Real-time acquisition of the operating parameters of the target wind farm, including meteorological parameters and wind farm operating status parameters; Feature extraction is performed on the operating parameters to obtain key wind field parameters, which include average wind speed, target wind direction, turbulence intensity, turbulence integral scale, and wind speed power spectrum. Based on the key wind field parameters and the preset wind deflection angle prediction model, multiple predictions are made for different operating conditions of the wind farm to obtain the influence law of different influencing factors affecting the wind deflection angle of the insulator string of the wind farm and the correction coefficients corresponding to different influencing factors. Based on the aforementioned influence patterns and correction coefficients, the structural parameters of the target wind-resistant components are optimized using the key wind field parameters as boundary constraints, resulting in parameter optimization results for transmission line wind-resistant components that meet multiple objective requirements.

[0005] Optionally, the step of extracting features from the operating parameters to obtain key wind field parameters specifically includes: The average wind speed is obtained by averaging the wind speed at different times based on the operating parameters. The first average wind vector and the second average wind vector are obtained by averaging the wind direction at different times. The wind direction is calculated based on the first average wind vector and the second average wind vector to obtain the target wind direction. The fluctuating wind speed for different wind directions is calculated by processing the current wind speed and average wind speed at different times. The root mean square calculation was performed on the fluctuating wind speed at different wind directions and times to obtain the standard deviation of the fluctuating wind speed for different wind directions. The turbulence intensity for different wind directions is obtained by performing a division operation based on the standard deviation of the fluctuating wind speed and the average wind speed. The turbulence integral scale is obtained by performing calculations based on the turbulence intensity and a preset autocorrelation function. Wind speed power is sampled based on a predetermined sampling window to obtain multiple wind speed power sample points; The power spectral density of each sampling window is calculated using a window function based on the aforementioned wind speed and power sample points. The wind speed power spectrum is obtained by calculating the power spectral density shown using the Welch method.

[0006] Optionally, the optimization of the structural parameters of the target wind-resistant component based on the influence law and the correction coefficient, using the key wind field parameters as boundary constraints, to obtain the parameter optimization results of the transmission line wind-resistant component that meet multiple objective requirements, specifically includes: Step 1: Initialize the structural parameters of the target wind-resistant components; Step 2: Based on the key wind field parameters as boundary constraints, and based on the influence law and the correction coefficient, perform flow field simulation on the target wind-resistant component to obtain the flow field distribution map and surface wind pressure distribution cloud map; Step 3: Perform structural mechanics simulation based on the surface wind pressure distribution cloud map and the material properties of the target wind-resistant component to obtain the stress distribution map and bending deformation cloud map of the target wind-resistant component; Step 4: Optimize the structural parameters of the target wind-resistant component based on the stress distribution diagram and bending deformation cloud diagram to obtain the initial structural parameters of the target wind-resistant component; Step 5: Perform electric field distribution simulation processing on the three-dimensional model of the insulator string of the target wind-resistant component with the initial structural parameters installed to obtain a spatial electric field intensity distribution cloud map; Step Six: When the spatial electric field intensity distribution cloud map meets the preset conditions, the initial structural parameters are determined as the target optimization parameters of the transmission line wind-resistant component that meets the multi-objective requirements; when the spatial electric field intensity distribution cloud map does not meet the preset conditions, steps Two to Five are repeated to update the structural parameters of the target wind-resistant component, and the current structural parameters of the target wind-resistant component in the current iteration are obtained until the spatial electric field intensity distribution cloud map in the current iteration meets the preset conditions, at which point the current structural parameters in the current iteration are determined as the target optimization parameters of the transmission line wind-resistant component.

[0007] Optionally, the step of using the key wind field parameters as boundary constraints, and performing flow field simulation on the target wind-resistant component based on the influence law and the correction coefficient to obtain a flow field distribution map and a surface wind pressure distribution cloud map specifically includes: The key wind field parameters are converted into input conditions for the flow field simulation algorithm. The input conditions include the inlet boundary, inlet turbulence characteristics, wind spectrum model, and computational domain range. Based on the aforementioned influence patterns and correction coefficients, a boundary layer mesh is used to capture surface flow and a meshing method that locally refines the mesh in key areas. Steady-state and transient calculations are then performed within the input conditions to obtain flow field distribution maps and surface wind pressure distribution cloud maps.

[0008] Optionally, the step of performing structural mechanics simulation based on the surface wind pressure distribution cloud map and the material properties of the target wind-resistant component to obtain the stress distribution map and bending deformation cloud map of the target wind-resistant component specifically includes: Load mapping is performed based on the surface wind pressure distribution cloud map to obtain the mapping relationship between wind pressure distribution and load; The material properties and the preset material property model are used for calculation to obtain a finite element mesh suitable for structural analysis. Based on the mapping relationship and real-time displacement, a stress distribution map is obtained through calculation. The bending deformation contour map is obtained by performing calculations based on the finite element mesh, the preset material yield strength, and the ultimate strength.

[0009] Optionally, the electric field distribution simulation processing of the three-dimensional model of the insulator string of the target wind-resistant component with the initial structural parameters installed to obtain a spatial electric field intensity distribution cloud map specifically includes: The preset Poisson equation is solved based on the three-dimensional model of the insulator string of the target wind-resistant component with the initial structural parameters installed, and the potential field distribution cloud map is obtained. The electric potential gradient is calculated based on the electric potential field distribution cloud map to obtain the electric field intensity distribution cloud map.

[0010] Optionally, the method further includes: Electric field distribution simulation processing was performed on the first three-dimensional model equipped with the target wind-resistant components but without bird-proof devices, and on the second three-dimensional model equipped with the designed number of the target wind-resistant components, to determine the optimal solution suitable for high altitude and micro-topography.

[0011] To address the aforementioned problems, this application provides a device for optimizing the parameters of wind-resistant components of transmission lines, comprising: The acquisition module is used to acquire the operating parameters of the target wind farm in real time, including meteorological parameters and wind farm operating status parameters; The feature extraction module is used to extract features from the operating parameters to obtain key wind field parameters, including average wind speed, target wind direction, turbulence intensity, turbulence integral scale, and wind speed power spectrum. The prediction module is used to make multiple predictions for different operating conditions of the wind farm based on the key wind field parameters and the preset wind deflection angle prediction model, so as to obtain the influence law of different influencing factors affecting the wind deflection angle of the insulator string of the wind farm and the correction coefficients corresponding to different influencing factors. The optimization module is used to optimize the structural parameters of the target wind-resistant component based on the influence law and the correction coefficient, using the key wind field parameters as boundary constraints, to obtain the parameter optimization results of the transmission line wind-resistant component that meet the multi-objective requirements.

[0012] To address the aforementioned problems, this application provides a storage medium storing a computer program that, when executed by a processor, implements the steps of the above-described method for optimizing the parameters of wind-resistant components of transmission lines.

[0013] To address the aforementioned problems, this application provides an electronic device, comprising at least a memory and a processor. The memory stores a computer program, and the processor, when executing the computer program in the memory, implements the steps of the aforementioned method for optimizing the parameters of wind-resistant components of transmission lines.

[0014] The beneficial effects of this application are as follows: This application provides a multi-physics, high-fidelity, and fully coupled digital design and optimization system, which realizes the coordinated optimization and precise design of wind-resistant components in terms of aerodynamics, structure, and electrical performance, thereby improving the economy and reliability of the line while ensuring safety.

[0015] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, and in order to make the above and other objects, features and advantages of the present invention more apparent and understandable, specific embodiments of the present invention are described below. Attached Figure Description

[0016] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings: Figure 1 A flowchart illustrating a method for optimizing the parameters of wind-resistant components of a transmission line according to an embodiment of this application is shown. Figure 2 A flowchart illustrating a method for optimizing the parameters of wind-resistant components of a transmission line according to another embodiment of this application is shown. Figure 3 A structural block diagram of a power transmission line wind-resistant component parameter optimization device according to another embodiment of this application is shown. Detailed Implementation

[0017] Various embodiments and features of this application are described herein with reference to the accompanying drawings.

[0018] It should be understood that various modifications can be made to the embodiments described herein. Therefore, the above description should not be considered as limiting, but merely as an example of embodiments. Other modifications within the scope and spirit of this application will be apparent to those skilled in the art.

[0019] The accompanying drawings, which are included in and form part of this specification, illustrate embodiments of the present application and, together with the general description of the present application given above and the detailed description of the embodiments given below, serve to explain the principles of the present application.

[0020] These and other features of this application will become apparent from the following description of preferred forms of embodiments given as non-limiting examples, with reference to the accompanying drawings.

[0021] It should also be understood that although this application has been described with reference to some specific examples, those skilled in the art can certainly implement many other equivalent forms of this application.

[0022] The above and other aspects, features and advantages of this application will become more apparent when taken in conjunction with the accompanying drawings and in view of the following detailed description.

[0023] Specific embodiments of this application are described thereafter with reference to the accompanying drawings; however, it should be understood that the claimed embodiments are merely examples of this application, which can be implemented in various ways. Well-known and / or repeated functions and structures are not described in detail to avoid unnecessary or redundant details that could obscure the application. Therefore, the specific structural and functional details claimed herein are not intended to be limiting, but merely serve as the basis and representative basis for the claims to teach those skilled in the art to use this application in a variety of substantially any suitable detailed structures.

[0024] This specification may use the phrases “in one embodiment,” “in another embodiment,” “in yet another embodiment,” or “in other embodiments,” all of which may refer to one or more of the same or different embodiments according to this application.

[0025] This application provides a method for optimizing the parameters of wind-resistant components of transmission lines, such as... Figure 1 As shown, it includes: Step S101: Obtain the operating parameters of the target wind farm in real time, including meteorological parameters and wind farm operating status parameters; In the specific implementation process of this step, the meteorological parameters include wind speed, wind direction, temperature, humidity, and rainfall; the wind farm operating status parameters include wind turbine operating status parameters, power generation system electrical parameters, and control system parameters; the wind turbine operating status parameters include basic operating parameters and mechanical system parameters, the basic operating parameters include active power output, reactive power output, power factor, and operating status indicators; the mechanical system parameters include impeller speed, generator speed, blade pitch angle, gearbox oil temperature, bearing temperature, and vibration monitoring data.

[0026] Step S102: Extract features from the operating parameters to obtain key wind field parameters, including average wind speed, target wind direction, turbulence intensity, turbulence integral scale, and wind speed power spectrum. In this step, the average wind speed is calculated based on the wind speed at different times in the operating parameters; the first and second average wind vectors are calculated based on the wind direction at different times; the target wind direction is calculated based on the first and second average wind vectors; the fluctuating wind speed for different wind directions is calculated based on the current wind speed and the average wind speed; the root mean square of the fluctuating wind speed at different times for different wind directions is calculated to obtain the standard deviation of the fluctuating wind speed for different wind directions; the turbulence intensity for different wind directions is obtained by dividing the standard deviation of the fluctuating wind speed by the average wind speed; the turbulence integral scale is obtained by calculating the turbulence intensity and a preset autocorrelation function; wind speed power is sampled based on a predetermined sampling window to obtain multiple wind speed power sample points; the power spectral density of each sampling window is calculated using a window function based on each wind speed power sample point; and the wind speed power spectrum is obtained by calculating the power spectral density using the Welch method.

[0027] Step S103: Based on the key wind field parameters and the preset wind deflection angle prediction model, make multiple predictions for different operating conditions of the wind farm to obtain the influence law of different influencing factors affecting the wind deflection angle of the insulator string of the wind farm and the correction coefficients corresponding to different influencing factors. In this step, the stable wind load is obtained by calculating the average wind speed using the mathematical formula for conductor wind load. Based on the wind speed power spectrum, a simulation tool is used to generate the fluctuating wind speed time history using the harmonic superposition method. The fluctuating wind load is then calculated using the mathematical formula for fluctuating wind speed based on the average wind speed and the fluctuating wind speed time history. Finally, the total wind load acting on the tower-line model is obtained by adding the stable wind load and the fluctuating wind load together. The insulator string wind deflection angle is then calculated using the force balance formula of the rigid straight rod method based on the calculated total wind load, conductor wind load, insulator string wind load, and gravity load. By setting numerous different operating conditions, such as varying wind speed, span, and wind attack angle, the simulation process of step S103 is repeated. This yields a large amount of data showing the correspondence between "input parameters" and "output wind deflection angle." By analyzing this data, we can output quantitative laws regarding the influence of various factors, such as fluctuating wind speed, span, insulator string length, and wind attack angle, on wind deflection, and finally propose correction coefficients for precise design.

[0028] Step S104: Based on the influence law and the correction coefficient, the structural parameters of the target wind-resistant component are optimized using the key wind field parameters as boundary constraints to obtain the parameter optimization results of the transmission line wind-resistant component that meet the multi-objective requirements.

[0029] In the specific implementation process of this step, Step 1: Initialize the structural parameters of the target wind-resistant component; Step 2: Based on the key wind field parameters as boundary constraints, and based on the influence law and the correction coefficient, perform flow field simulation on the target wind-resistant component to obtain the flow field distribution map and surface wind pressure distribution cloud map; Step 3: Perform structural mechanics simulation based on the surface wind pressure distribution cloud map and the material properties of the target wind-resistant component to obtain the stress distribution map and bending deformation cloud map of the target wind-resistant component; Step 4: Optimize the structural parameters of the target wind-resistant component based on the stress distribution map and bending deformation cloud map to obtain the initial structural parameters of the target wind-resistant component; Step 5: Install the target wind-resistant component with the initial structural parameters... The three-dimensional model of the insulator string of the wind-resistant component is subjected to electric field distribution simulation processing to obtain a spatial electric field intensity distribution cloud map; Step 6: When the spatial electric field intensity distribution cloud map meets the preset conditions, the initial structural parameters are determined as the target optimization parameters of the wind-resistant component of the transmission line that meet the multi-objective requirements; When the spatial electric field intensity distribution cloud map does not meet the preset conditions, Steps 2 to 5 are repeated to update the structural parameters of the target wind-resistant component and obtain the current structural parameters of the target wind-resistant component in the current iteration round, until the spatial electric field intensity distribution cloud map of the current iteration round meets the preset conditions, and the current structural parameters of the current iteration round are determined as the target optimization parameters of the wind-resistant component of the transmission line.

[0030] This application, through precise wind deflection calculation and high-altitude correction coefficients, can more accurately predict and control the sway amplitude of insulator strings, fundamentally reducing discharge and tripping accidents caused by insufficient clearance. Electric field distribution simulation ensures that optimized wind-resistant components do not cause electric field distortion, avoiding the awkward situation of solving mechanical problems but causing electrical ones, and preventing partial discharge and insulation breakdown. Structural mechanics simulation based on real wind pressure distribution ensures that components have sufficient strength and stiffness during the design phase, preventing structural damage such as fracture or plastic deformation under strong winds. This significantly improves the safety level of transmission lines. Precise load input: Replacing traditional empirical estimates with measured wind field characteristics (turbulence intensity, integral scale, wind speed spectrum) makes the boundary conditions of the simulation input infinitely close to reality, greatly improving the confidence of the entire analysis chain. By reducing power outage accidents such as wind deflection flashover, huge economic losses from power outages and emergency repair costs are avoided. Precise design avoids "over-design," allowing for optimized material usage, lightweighting, and cost savings on raw materials while ensuring safety.

[0031] Another embodiment of this application provides a different method for optimizing the parameters of wind-resistant components of transmission lines, such as... Figure 2 As shown, it includes: Step S201: Obtain the operating parameters of the target wind farm in real time, including meteorological parameters and wind farm operating status parameters; In the specific implementation process of this step, the meteorological parameters include wind speed, wind direction, temperature, humidity, and rainfall; the wind farm operating status parameters include wind turbine operating status parameters, power generation system electrical parameters, and control system parameters; the wind turbine operating status parameters include basic operating parameters and mechanical system parameters, such as active power output, reactive power output, power factor, and operating status indicators; the mechanical system parameters include impeller speed, generator speed, pitch angle, gearbox oil temperature, bearing temperature, and vibration monitoring data. The target wind farm can be a high-altitude, high-wind area.

[0032] Step S202: Perform feature extraction on the operating parameters to obtain key wind field parameters, including average wind speed, target wind direction, turbulence intensity, turbulence integral scale, and wind speed power spectrum; In this step, the average wind speed is calculated by averaging the wind speed at different times in the operating parameters. Specifically, the raw wind speed data is preprocessed to remove physically unreasonable data points; missing values ​​are linearly interpolated to ensure data continuity; a low-pass filter is applied to remove high-frequency noise and retain meaningful low-frequency pulsations. Then, the average wind speed modulus is directly calculated to obtain the average wind speed. The average wind vector and the second average wind vector are obtained by averaging the wind direction at different times. The average wind vector is calculated first, and then the wind direction is determined, with north as 0° and increasing clockwise to 360°. The scalar average reflects the overall wind energy, and the vector average reflects the dominant wind direction. The target wind direction is calculated based on the first and second average wind vectors; the first average wind vector can be the average value in the east-west direction, and the second average wind vector can be the average value in the north-south direction. The fluctuating wind speed for different wind directions is calculated based on the current wind speed and the average wind speed at different times. The root mean square of the fluctuating wind speed at different times for different wind directions is calculated to obtain the standard deviation of the fluctuating wind speed for different wind directions. The standard deviation of the fluctuating wind speed and the average wind speed are then used to calculate the standard deviation of the fluctuating wind speed. Perform division operations to obtain the turbulence intensity in different wind directions; the turbulence intensity in the downwind direction. It can be represented by the following formula:

[0033] Crosswind turbulence intensity It can be represented by the following formula:

[0034] in, Represents the intensity of turbulence in the downwind direction; Represents the intensity of turbulence against the wind direction; Represents the standard deviation of downwind pulsating wind speed; This represents the standard deviation of the upwind fluctuating wind speed. The ratio of crosswind to downwind turbulence intensity is approximately... . The mathematical formula for calculation can be shown as follows:

[0035] The mathematical formula for calculation can be shown as follows:

[0036] in, The gust factor represents the time interval. It is used to convert between peak average wind speeds at different time intervals, typically the ratio of the short-time interval to the long-time interval average wind speed. The short-time interval is taken as 3 seconds, and the long-time interval as 10 minutes. Both turbulence intensity and the gust factor characterize the intensity of turbulent wind fluctuations; they are not entirely independent.

[0037] The turbulence integral scale is obtained by calculation based on the turbulence intensity and a preset autocorrelation function; the turbulence integral scale in the downwind direction is also calculated. The mathematical expression for can be represented by the following formula:

[0038] Crosswind turbulence integral scale The mathematical expression for can be represented by the following formula:

[0039] in, , The autocorrelation function represents the turbulence intensity, a crucial parameter characterizing wind speed fluctuations, primarily influenced by surface roughness and altitude. The turbulence integral scale represents the average size of turbulent vortices in the airflow and also reflects the intensity of turbulence effects; a larger integral scale indicates a more significant turbulence effect. The ratio of the downwind to crosswind turbulence integral scales, when averaged, is approximately equal to... Wind speed power is sampled based on a predetermined sampling window to obtain multiple wind speed power sample points; the power spectral density of each sampling window is calculated using a window function based on each of the wind speed power sample points; the wind speed power spectrum is obtained by calculating the power spectral density using the Welch method. The von Karman spectrum is a spectral model based on classical turbulence theory, used to describe the three-dimensional energy spectrum distribution characteristics of isotropic turbulence. It has a clear physical background in the low-frequency region and the inertial subregion, conforming to the fourth power law of wavenumber in the low-frequency large eddy range and the "-5 / 3" power law in the inertial subregion. In many experimental studies, the von Karman spectrum is considered the most reliable spectral model currently available for describing the energy spectrum distribution of fluctuating wind speed, and has been adopted by authoritative international engineering scientific data organizations as the standard form of fluctuating wind speed energy spectrum distribution. The mathematical expression of the von Karman spectrum is shown below:

[0040] in, ; The power spectral density function is used. The von Karman spectral model reflects the variation of turbulent energy with frequency. The model uses the turbulent integral scale as a parameter to characterize the influence of the vortex scale on the endflow energy distribution of the wind field. For fluctuating wind speeds obtained from non-stationary wind speed models, establishing a suitable von Karman spectral model involves accurately calculating the endflow integral scale of the wind field. Therefore, this application uses the turbulent integral scales of non-stationary wind speed models in both the along-wind and cross-wind directions, and substitutes the results into the von Karman spectral model. By comparing the spectral deviation between the measured wind speed spectrum and the von Karman wind speed spectrum, a more reasonable longitudinal turbulent integral scale can be determined. The mathematical formula for calculation is shown below:

[0041] in, Represents the measured wind speed spectrum; The result represents the calculation of the von Karman wind speed spectrum.

[0042] Step S203: Based on the key wind field parameters and the preset wind deflection angle prediction model, make multiple predictions for different operating conditions of the wind farm to obtain the influence law of different influencing factors affecting the wind deflection angle of the insulator string of the wind farm and the correction coefficients corresponding to different influencing factors. In this step, the stable wind load is obtained by calculating the average wind speed using the mathematical formula for conductor wind load. Based on the wind speed power spectrum, a simulation tool is used to generate the fluctuating wind speed time history using the harmonic superposition method. The fluctuating wind load is then calculated using the mathematical formula for fluctuating wind speed based on the average wind speed and the fluctuating wind speed time history. Finally, the total wind load acting on the tower-line model is obtained by adding the stable wind load and the fluctuating wind load together. The insulator string wind deflection angle is then calculated using the force balance formula of the rigid straight rod method based on the calculated total wind load, conductor wind load, insulator string wind load, and gravity load. By setting numerous different operating conditions, such as varying wind speed, span, and wind attack angle, the simulation process of step S203 is repeated. This yields a large amount of data showing the correspondence between "input parameters" and "output wind deflection angle." By analyzing this data, we can output quantitative laws regarding the influence of various factors, such as fluctuating wind speed, span, insulator string length, and wind attack angle, on wind deflection, and finally propose correction coefficients for precise design.

[0043] Step S204: Initialize the structural parameters of the target wind-resistant component; In this specific implementation process, the target wind-resistant component can be a bird shield for power transmission lines. The structural parameters include overall geometric shape parameters, cross-sectional profile parameters, skirt structure parameters, material and structural strength parameters, and installation and connection parameters. The overall geometric shape parameters include total diameter, total height, projected area, and volume. The cross-sectional profile parameters include radius of curvature, tilt angle or cone angle, and edge shape. The skirt structure parameters include the number of skirts, skirt spacing, skirt shape, and creepage distance. The material and structural strength parameters include material type, material thickness, reinforcing frame, hardness, and tear strength. The installation and connection parameters include mounting hole diameter, fixing method, protrusion length, and weight. The structural parameters of the target wind-resistant component are initialized.

[0044] Step S205: Based on the key wind field parameters as boundary constraints, and based on the influence law and the correction coefficient, perform flow field simulation on the target wind-resistant component to obtain the flow field distribution map and the surface wind pressure distribution cloud map; In this step, the key wind field parameters are converted into input conditions for the flow field simulation algorithm. These input conditions include the inlet boundary, inlet turbulence characteristics, wind spectrum model, and computational domain range. Specifically, the velocity inlet conditions (i.e., the inlet boundary) are set based on the average wind speed and direction. The inlet turbulence characteristics are defined using turbulence intensity and integral scale. The von Karman wind spectrum model is used to describe the energy distribution of fluctuating wind speeds. A sufficiently large computational domain range is ensured to avoid boundary effects. Based on the aforementioned influence laws and correction coefficients, a boundary layer mesh is used to capture surface flow and locally refine the mesh in key areas. Steady-state and transient calculations are performed within the input condition range to obtain the flow field distribution map and surface wind pressure distribution cloud map. A three-dimensional model of wind-resistant components (bird shields, insulators, etc.) is established. A boundary layer mesh is used to capture surface flow and locally refine the mesh in key areas. A suitable turbulence model for separated flow, such as SST k-ω, is selected. Steady-state or transient calculations are performed under the set wind field boundary conditions to obtain the flow field distribution map and surface wind pressure distribution cloud map. The flow field distribution map includes a velocity contour map, showing the velocity distribution across the entire flow basin; a streamline map, visually illustrating airflow paths and separation regions; a vorticity map, identifying vortex structure and intensity; and a pressure contour map, displaying the pressure distribution characteristics within the flow basin. Surface wind pressure distribution contour maps are used to reflect pressure coefficient distribution, identify high-pressure areas (maximum pressure region on the windward side), identify low-pressure areas (negative pressure regions on the leeward side and separation zone), and perform pressure gradient analysis to assess local load concentration.

[0045] Step S206: Perform structural mechanics simulation based on the surface wind pressure distribution cloud map and the material properties of the target wind-resistant component to obtain the stress distribution map and bending deformation cloud map of the target wind-resistant component; In this step, load mapping is performed based on the surface wind pressure distribution cloud map to obtain the mapping relationship between wind pressure distribution and load. Specifically, the surface wind pressure distribution cloud map obtained from CFD analysis is mapped to structural mesh nodes, converting the distributed pressure into equivalent nodal forces. Boundary constraints (fixed, hinged, etc.) are set according to the actual installation method of the component. The influence of the component's self-weight is considered and superimposed on the wind pressure load. Calculations are performed based on the material properties and a preset material property model to obtain a finite element mesh suitable for structural analysis. Linear elastic or nonlinear material constitutive equations are established based on elastic parameters such as elastic modulus, Poisson's ratio, and density. Key parameters such as material yield strength and ultimate strength are defined to generate a high-quality finite element mesh suitable for structural analysis. Calculations are performed based on the mapping relationship and real-time displacement to obtain a stress distribution map. Based on the mapping relationship and real-time displacement, a preset equilibrium equation is solved to obtain a stress distribution map. Calculations are performed based on the finite element mesh, preset material yield strength, and ultimate strength to obtain a bending deformation cloud map.

[0046] Step S207: Optimize the structural parameters of the target wind-resistant component based on the stress distribution diagram and bending deformation cloud diagram to obtain the initial structural parameters of the target wind-resistant component; In this step, finite element analysis is performed to obtain the stress distribution and bending deformation contour map of the bird shield. This ensures that under maximum wind pressure, the deformation of the bird shield is within allowable limits; for example, it must not touch the insulator skirt, and the stress is below the material's yield strength. This yields the initial structural parameters of the target wind-resistant component that meet the wind load and deformation stress requirements.

[0047] Step S208: Perform electric field distribution simulation processing on the three-dimensional model of the insulator string of the target wind-resistant component with the initial structural parameters installed to obtain a spatial electric field intensity distribution cloud map; In the specific implementation process of this step, the electric field distribution of the three-dimensional model of the insulator string of the target wind-resistant component with the initial structural parameters is simulated to obtain a spatial electric field intensity distribution cloud map near the insulator string.

[0048] Step S209: When the spatial electric field intensity distribution cloud map meets the preset conditions, the initial structural parameters are determined as the target optimization parameters of the transmission line wind-resistant components that meet the multi-objective requirements; In the specific implementation process of this step, when the spatial electric field intensity distribution cloud map meets the preset conditions, the initial structural parameters are determined as the target optimization parameters of the transmission line wind-resistant components that meet the multi-objective requirements; when the spatial electric field intensity distribution cloud map meets the electrical design requirements, the initial structural parameters are determined as the target optimization parameters of the transmission line wind-resistant components that meet the multi-objective requirements; at this time, the optimal balance is achieved among the multiple objectives of wind resistance performance, rigidity and electrical safety.

[0049] Step S210: When the spatial electric field intensity distribution cloud map does not meet the preset conditions, repeat steps S205 to S208 to update the structural parameters of the target wind-resistant component and obtain the current structural parameters of the target wind-resistant component in the current iteration round until the spatial electric field intensity distribution cloud map in the current iteration round meets the preset conditions. Then, determine the current structural parameters of the current iteration round as the target optimization parameters of the transmission line wind-resistant component.

[0050] In this step, when the spatial electric field intensity distribution cloud map does not meet the preset conditions, steps S205 to S208 are repeated to update the structural parameters of the target wind-resistant component, obtaining the current structural parameters of the target wind-resistant component in the current iteration. This process continues until the spatial electric field intensity distribution cloud map in the current iteration meets the preset conditions, at which point the current structural parameters of the current iteration are determined as the target optimized parameters of the transmission line wind-resistant component. This can be achieved by changing the parameters in the parameterized model, for example, changing the tilt angle θ from 30 degrees to 35 degrees, and then repeating steps S205 to S208. The results of each iteration are evaluated, and the wind load, deformation, and electric field distribution are analyzed. When the optimal balance is achieved among the multiple objectives, i.e., when the spatial electric field intensity distribution cloud map in the current iteration meets the preset conditions, the current structural parameters of the current iteration are determined as the target optimized parameters of the transmission line wind-resistant component.

[0051] This application provides a multi-physics, high-fidelity, fully coupled digital design and optimization system, which enables the coordinated optimization and precise design of wind-resistant components in terms of aerodynamics, structure, and electrical performance, thereby improving the economy and reliability of the line while ensuring safety.

[0052] Another embodiment of this application provides a device for optimizing the parameters of wind-resistant components of transmission lines, such as... Figure 3 As shown, it includes: The acquisition module 1 is used to acquire the operating parameters of the target wind farm in real time, including meteorological parameters and wind farm operating status parameters; Feature extraction module 2 is used to extract features from the operating parameters to obtain key wind field parameters, including average wind speed, target wind direction, turbulence intensity, turbulence integral scale, and wind speed power spectrum. Prediction module 3 is used to make multiple predictions for different operating conditions of the wind farm based on the key wind field parameters and the preset wind deflection angle prediction model, so as to obtain the influence law of different influencing factors affecting the wind deflection angle of the insulator string of the wind farm and the correction coefficients corresponding to different influencing factors. The optimization module 4 is used to optimize the structural parameters of the target wind-resistant component based on the influence law and the correction coefficient, using the key wind field parameters as boundary constraints, so as to obtain the parameter optimization results of the transmission line wind-resistant component that meet the multi-objective requirements.

[0053] In the specific implementation process, the feature extraction module 2 is specifically used for: calculating the mean wind speed based on the wind speed at different times in the operating parameters to obtain the average wind speed; calculating the mean wind direction at different times to obtain the first average wind vector and the second average wind vector; calculating the wind direction based on the first average wind vector and the second average wind vector to obtain the target wind direction; calculating the fluctuating wind speed for different wind directions based on the current wind speed and the average wind speed at different times; calculating the root mean square of the fluctuating wind speed for different wind directions at different times to obtain the standard deviation of the fluctuating wind speed for different wind directions; performing a division operation based on the standard deviation of the fluctuating wind speed and the average wind speed to obtain the turbulence intensity for different wind directions; calculating the turbulence integral scale based on the turbulence intensity and a preset autocorrelation function; sampling the wind speed power based on a predetermined sampling window to obtain multiple wind speed power sample points; calculating the power spectral density of each sampling window based on each wind speed power sample point using a window function; and calculating the wind speed power spectrum based on the power spectral density using the Welch method.

[0054] In the specific implementation process, the optimization module 4 is specifically used for: Step 1, initializing the structural parameters of the target wind-resistant component; Step 2, based on the key wind field parameters as boundary constraints, performing flow field simulation on the target wind-resistant component based on the influence law and the correction coefficient, obtaining the flow field distribution map and surface wind pressure distribution cloud map; Step 3, performing structural mechanics simulation based on the surface wind pressure distribution cloud map and the material properties of the target wind-resistant component, obtaining the stress distribution map and bending deformation cloud map of the target wind-resistant component; Step 4, optimizing the structural parameters of the target wind-resistant component based on the stress distribution map and bending deformation cloud map, obtaining the initial structural parameters of the target wind-resistant component; Step 5, installing the initial structural parameters... The electric field distribution of the three-dimensional model of the insulator string of the target wind-resistant component is simulated to obtain a spatial electric field intensity distribution cloud map. Step six: When the spatial electric field intensity distribution cloud map meets the preset conditions, the initial structural parameters are determined as the target optimization parameters of the transmission line wind-resistant component that meet the multi-objective requirements. When the spatial electric field intensity distribution cloud map does not meet the preset conditions, steps two to five are repeated to update the structural parameters of the target wind-resistant component and obtain the current structural parameters of the target wind-resistant component in the current iteration round. This process continues until the spatial electric field intensity distribution cloud map in the current iteration round meets the preset conditions, at which point the current structural parameters in the current iteration round are determined as the target optimization parameters of the transmission line wind-resistant component.

[0055] In the specific implementation process, the optimization module 4 is also used to convert the key wind field parameters into input conditions for the flow field simulation algorithm. The input conditions include the inlet boundary, inlet turbulence characteristics, wind spectrum model and computational domain range. Based on the influence law and the correction coefficient, the steady-state and transient calculations are performed within the input condition range by using boundary layer mesh to capture surface flow and locally refine the mesh division of key areas to obtain the flow field distribution map and surface wind pressure distribution cloud map.

[0056] In the specific implementation process, the optimization module 4 is also used to: perform load mapping based on the surface wind pressure distribution cloud map to obtain the mapping relationship between wind pressure distribution and load; perform calculation processing based on the material properties and the preset material property model to obtain a finite element mesh suitable for structural analysis; perform calculation processing based on the mapping relationship and real-time displacement to obtain a stress distribution map; and perform calculation processing based on the finite element mesh, the preset material yield strength and ultimate strength to obtain a bending deformation cloud map.

[0057] In the specific implementation process, the optimization module 4 is also used to solve the preset Poisson equation based on the three-dimensional model of the insulator string of the target wind-resistant component with the initial structural parameters installed, and obtain the electric potential field distribution cloud map; and to perform electric potential gradient calculation processing based on the electric potential field distribution cloud map to obtain the electric field intensity distribution cloud map.

[0058] In the specific implementation process, the optimization module 4 is also used to perform electric field distribution simulation processing on the first three-dimensional model equipped with the target wind-resistant components but not equipped with bird-proof devices and the second three-dimensional model equipped with the designed number of target wind-resistant components, so as to determine the optimal solution suitable for high altitude and micro-topography.

[0059] This application provides a multi-physics, high-fidelity, fully coupled digital design and optimization system, which enables the coordinated optimization and precise design of wind-resistant components in terms of aerodynamics, structure, and electrical performance, thereby improving the economy and reliability of the line while ensuring safety.

[0060] Another embodiment of this application provides a storage medium storing a computer program, which, when executed by a processor, implements the following method steps: Step 1: Obtain the operating parameters of the target wind farm in real time, including meteorological parameters and wind farm operating status parameters; Step 2: Extract features from the operating parameters to obtain key wind field parameters, including average wind speed, target wind direction, turbulence intensity, turbulence integral scale, and wind speed power spectrum. Step 3: Based on the key wind field parameters and the preset wind deflection angle prediction model, make multiple predictions for different operating conditions of the wind farm to obtain the influence law of different influencing factors affecting the wind deflection angle of the insulator string of the wind farm and the correction coefficients corresponding to different influencing factors. Step 4: Based on the influence law and the correction coefficient, optimize the structural parameters of the target wind-resistant component using the key wind field parameters as boundary constraints to obtain the parameter optimization results of the transmission line wind-resistant component that meet the multi-objective requirements.

[0061] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0062] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0063] The specific implementation process of the above method steps can be found in the embodiment of the above method for optimizing the parameters of wind-resistant components of any transmission line, and will not be repeated here.

[0064] This application provides a multi-physics, high-fidelity, fully coupled digital design and optimization system, which enables the coordinated optimization and precise design of wind-resistant components in terms of aerodynamics, structure, and electrical performance, thereby improving the economy and reliability of the line while ensuring safety.

[0065] Another embodiment of this application provides an electronic device, which can be a server. The electronic device includes a processor, a memory, a network interface, and a database connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile and / or volatile storage media and internal memory. The non-volatile storage media stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface is used to communicate with external clients via a network connection. When the program is executed by the processor, it implements the functions or steps of a method for optimizing the parameters of wind-resistant components of a power transmission line on the server side.

[0066] In one embodiment, an electronic device is provided, which can be a client. The electronic device includes a processor, memory, a network interface, a display screen, and an input device connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The network interface is used to communicate with an external server via a network connection. When the program of the electronic device is executed by the processor, it implements the functions or steps of a method for optimizing the parameters of wind-resistant components of a power transmission line on the client side.

[0067] Another embodiment of this application provides an electronic device, including at least a memory and a processor. The memory stores a computer program, and the processor, when executing the computer program in the memory, performs the following method steps: Step 1: Obtain the operating parameters of the target wind farm in real time, including meteorological parameters and wind farm operating status parameters; Step 2: Extract features from the operating parameters to obtain key wind field parameters, including average wind speed, target wind direction, turbulence intensity, turbulence integral scale, and wind speed power spectrum. Step 3: Based on the key wind field parameters and the preset wind deflection angle prediction model, make multiple predictions for different operating conditions of the wind farm to obtain the influence law of different influencing factors affecting the wind deflection angle of the insulator string of the wind farm and the correction coefficients corresponding to different influencing factors. Step 4: Based on the influence law and the correction coefficient, optimize the structural parameters of the target wind-resistant component using the key wind field parameters as boundary constraints to obtain the parameter optimization results of the transmission line wind-resistant component that meet the multi-objective requirements.

[0068] The specific implementation process of the above method steps can be found in the embodiment of the above method for optimizing the parameters of wind-resistant components of any transmission line, and will not be repeated here.

[0069] The above embodiments are merely exemplary embodiments of this application and are not intended to limit this application. The scope of protection of this application is defined by the claims. Those skilled in the art can make various modifications or equivalent substitutions to this application within its substance and scope of protection, and such modifications or equivalent substitutions should also be considered to fall within the scope of protection of this application.

Claims

1. A method for optimizing the parameters of wind-resistant components of transmission lines, characterized in that, include: Real-time acquisition of the operating parameters of the target wind farm, including meteorological parameters and wind farm operating status parameters; Feature extraction is performed on the operating parameters to obtain key wind field parameters, which include average wind speed, target wind direction, turbulence intensity, turbulence integral scale, and wind speed power spectrum. Based on the key wind field parameters and the preset wind deflection angle prediction model, multiple predictions are made for different operating conditions of the wind farm to obtain the influence law of different influencing factors affecting the wind deflection angle of the insulator string of the wind farm and the correction coefficients corresponding to different influencing factors. Based on the aforementioned influence patterns and correction coefficients, the structural parameters of the target wind-resistant components are optimized using the key wind field parameters as boundary constraints, resulting in parameter optimization results for transmission line wind-resistant components that meet multiple objective requirements.

2. The method as described in claim 1, characterized in that, The step of extracting features from the operating parameters to obtain key wind field parameters specifically includes: The average wind speed is obtained by averaging the wind speed at different times based on the operating parameters. The first average wind vector and the second average wind vector are obtained by averaging the wind direction at different times. The wind direction is calculated based on the first average wind vector and the second average wind vector to obtain the target wind direction. The fluctuating wind speed for different wind directions is calculated by processing the current wind speed and average wind speed at different times. The root mean square calculation was performed on the fluctuating wind speeds at different wind directions and times to obtain the standard deviation of the fluctuating wind speeds for different wind directions. The turbulence intensity for different wind directions is obtained by performing a division operation based on the standard deviation of the fluctuating wind speed and the average wind speed. The turbulence integral scale is obtained by performing calculations based on the turbulence intensity and a preset autocorrelation function. Wind speed power is sampled based on a predetermined sampling window to obtain multiple wind speed power sample points; The power spectral density of each sampling window is calculated using a window function based on the aforementioned wind speed and power sample points. The wind speed power spectrum is obtained by calculating the power spectral density shown using the Welch method.

3. The method as described in claim 1, characterized in that, Based on the aforementioned influence patterns and correction coefficients, the structural parameters of the target wind-resistant components are optimized using the key wind field parameters as boundary constraints to obtain parameter optimization results for transmission line wind-resistant components that meet multi-objective requirements. Specifically, this includes: Step 1: Initialize the structural parameters of the target wind-resistant component; Step 2: Based on the key wind field parameters as boundary constraints, and based on the influence law and the correction coefficient, perform flow field simulation on the target wind-resistant component to obtain the flow field distribution map and surface wind pressure distribution cloud map; Step 3: Perform structural mechanics simulation based on the surface wind pressure distribution cloud map and the material properties of the target wind-resistant component to obtain the stress distribution map and bending deformation cloud map of the target wind-resistant component; Step 4: Optimize the structural parameters of the target wind-resistant component based on the stress distribution diagram and bending deformation cloud diagram to obtain the initial structural parameters of the target wind-resistant component; Step 5: Perform electric field distribution simulation processing on the three-dimensional model of the insulator string of the target wind-resistant component with the initial structural parameters installed to obtain a spatial electric field intensity distribution cloud map; Step Six: When the spatial electric field intensity distribution cloud map meets the preset conditions, the initial structural parameters are determined as the target optimization parameters of the transmission line wind-resistant component that meets the multi-objective requirements; when the spatial electric field intensity distribution cloud map does not meet the preset conditions, steps Two to Five are repeated to update the structural parameters of the target wind-resistant component, and the current structural parameters of the target wind-resistant component in the current iteration are obtained until the spatial electric field intensity distribution cloud map in the current iteration meets the preset conditions, at which point the current structural parameters in the current iteration are determined as the target optimization parameters of the transmission line wind-resistant component.

4. The method as described in claim 3, characterized in that, The process involves using the key wind field parameters as boundary constraints, and performing flow field simulation on the target wind-resistant component based on the influence law and the correction coefficient to obtain a flow field distribution map and a surface wind pressure distribution cloud map. Specifically, this includes: The key wind field parameters are converted into input conditions for the flow field simulation algorithm. The input conditions include the inlet boundary, inlet turbulence characteristics, wind spectrum model, and computational domain range. Based on the aforementioned influence patterns and correction coefficients, a boundary layer mesh is used to capture surface flow and a meshing method that locally refines the mesh in key areas. Steady-state and transient calculations are then performed within the input conditions to obtain flow field distribution maps and surface wind pressure distribution cloud maps.

5. The method as described in claim 3, characterized in that, The step of performing structural mechanics simulation based on the surface wind pressure distribution cloud map and the material properties of the target wind-resistant component to obtain the stress distribution map and bending deformation cloud map of the target wind-resistant component specifically includes: Load mapping is performed based on the surface wind pressure distribution cloud map to obtain the mapping relationship between wind pressure distribution and load; The material properties and the preset material property model are used for calculation to obtain a finite element mesh suitable for structural analysis. Based on the mapping relationship and real-time displacement, a stress distribution map is obtained through calculation. The bending deformation contour map is obtained by performing calculations based on the finite element mesh, the preset material yield strength, and the ultimate strength.

6. The method as described in claim 3, characterized in that, The electric field distribution simulation of the three-dimensional model of the insulator string of the target wind-resistant component with the initial structural parameters is performed to obtain a spatial electric field intensity distribution cloud map, specifically including: The preset Poisson equation is solved based on the three-dimensional model of the insulator string of the target wind-resistant component with the initial structural parameters installed, and the potential field distribution cloud map is obtained. The electric potential gradient is calculated based on the electric potential field distribution cloud map to obtain the electric field intensity distribution cloud map.

7. The method as described in claim 1, characterized in that, The method further includes: Electric field distribution simulation processing was performed on the first three-dimensional model equipped with the target wind-resistant components but without bird-proof devices, and on the second three-dimensional model equipped with the designed number of the target wind-resistant components, to determine the optimal solution suitable for high altitude and micro-topography.

8. A device for optimizing the parameters of wind-resistant components of transmission lines, characterized in that, include: The acquisition module is used to acquire the operating parameters of the target wind farm in real time, including meteorological parameters and wind farm operating status parameters; The feature extraction module is used to extract features from the operating parameters to obtain key wind field parameters, including average wind speed, target wind direction, turbulence intensity, turbulence integral scale, and wind speed power spectrum. The prediction module is used to make multiple predictions for different operating conditions of the wind farm based on the key wind field parameters and the preset wind deflection angle prediction model, so as to obtain the influence law of different influencing factors affecting the wind deflection angle of the insulator string of the wind farm and the correction coefficients corresponding to different influencing factors. The optimization module is used to optimize the structural parameters of the target wind-resistant component based on the influence law and the correction coefficient, using the key wind field parameters as boundary constraints, to obtain the parameter optimization results of the transmission line wind-resistant component that meet the multi-objective requirements.

9. A storage medium, characterized in that, The storage medium stores a computer program, which, when executed by a processor, implements the steps of the method for optimizing the parameters of wind-resistant components of transmission lines according to any one of claims 1-7.

10. An electronic device, characterized in that, It includes at least a memory and a processor, wherein the memory stores a computer program, and the processor, when executing the computer program in the memory, implements the steps of the method for optimizing the parameters of wind-resistant components of transmission lines according to any one of claims 1-7.

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