A heat dissipation optimization simulation method and system for an ultrahigh voltage line composite insulator

Abstract

A heat dissipation optimization simulation method and system of an ultrahigh-voltage line composite insulator. A parameterized template library of the composite insulator is constructed, a three-dimensional geometric model is generated based on the template library, and multi-path adaptive mesh division is adopted; a full-coupling model of electric heat flow is established, the loss heat source and leakage current joule heat are calculated through electric field intensity, and the thermal boundary and surface convective heat transfer coefficient are configured in combination with environmental working conditions; a nonlinear electric field enhancement term of space charge is introduced to correct the heat source, and the surface heat transfer coefficient of the shed is corrected in sections, and then the full-coupling model is solved; the solving result and the benchmark working condition parameters constitute a training sample to train a proxy model, new working condition parameters are input, heat dissipation performance indexes are output, and whether it is qualified is judged; for unqualified parameters, geometric optimization variables and multi-objective Pareto front are defined, and the optimal optimization variable combination is output by solving. The heat dissipation performance simulation of the ultrahigh-voltage line composite insulator is optimized.

Description

Technical Field

[0001] This invention belongs to the field of power equipment simulation and condition assessment technology, specifically relating to a simulation method and system for optimizing heat dissipation of composite insulators for ultra-high voltage lines. Background Technology

[0002] Under the long-term high electric field, heavy load, and complex environmental stress of ultra-high voltage lines, abnormal problems in composite insulators may lead to brittle fracture of fiberglass reinforced plastic (FRP) core rods, resulting in serious accidents such as conductor grounding and grid disconnection. Predicting heat dissipation performance and assessing thermal state are crucial for ensuring the safe and reliable operation of ultra-high voltage lines. In particular, under long-term high load and complex environments, how to control and assess heat generation through simulation is key to preventing accidents.

[0003] Existing simulation methods mainly include qualitative analysis based on empirical formulas and simplified models, or thermal simulation based on general-purpose finite element software. For example, patent application CN117077360A uses an electro-thermal-mechanical multiphysics coupling method to simulate and calculate the electro-thermal multiphysics field of composite insulators, enabling comparison of the electro-thermal distribution of insulators under multiphysics field conditions. Patent application CN117828902A establishes a temperature simulation model of composite insulators by establishing a functional relationship between temperature, electric field, and operating time, and optimizes the heat dissipation performance of composite insulators by adjusting the size of the equalizing ring.

[0004] However, the existing technology has the following shortcomings in the thermal simulation of composite insulators for the above-mentioned ultra-high voltage lines: (1) Under the complex scenario of internal and external integration, it is impossible to accurately simulate the complex multi-physics field coupling thermal process inside the composite insulator. This leads to a significant deviation between the predicted heat dissipation performance and the actual operating conditions. (2) General simulation tools have problems such as cumbersome modeling, long calculation cycle and poor professionalism, and lack dedicated and efficient simulation for the heating mechanism and complex structure of composite insulators for ultra-high voltage lines. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a simulation method for optimizing heat dissipation of composite insulators in ultra-high voltage lines. By using parametric modeling and fully coupled electrothermal-fluid simulation, combined with space charge correction and partitioned heat transfer correction, the accuracy of heat dissipation prediction is improved. A surrogate model is used to quickly evaluate the heat dissipation performance under new operating conditions, and geometric optimization and multi-objective Pareto front are used to optimize the heat dissipation performance of the insulator.

[0006] The first aspect of this application discloses a simulation method for optimizing heat dissipation of composite insulators for ultra-high voltage lines, employing the following technical solution: A parametric template library for composite insulators is constructed for ultra-high voltage line scenarios. The library includes geometric parameters, interface and connection parameters, material property parameters, field distribution parameters, and environmental parameters of composite insulators. A three-dimensional geometric model is generated based on the parametric template library, and a multi-path adaptive mesh generation strategy is used to process the three-dimensional geometric model. Based on the processed three-dimensional geometric model, a fully coupled electrothermal-fluid model is established. In the fully coupled model, the nonlinear dielectric loss heat source and leakage current Joule heat inside the insulator are calculated according to the electric field strength and substituted into the thermal field model. Thermal boundary conditions are configured in combination with environmental conditions, and the convective heat transfer coefficient on the surface of the insulator is calculated through the flow field to update the thermal boundary conditions. For the fully coupled model, a space charge nonlinear electric field enhancement term is introduced to correct the heat loss source, and the convective heat transfer coefficient of the umbrella skirt surface is corrected by partitioning. The corrected heat source distribution and boundary conditions are combined and solved by the fully coupled model. The solution results are combined with the corresponding benchmark parameters as benchmark training samples, and the surrogate model is trained. The trained surrogate model is invoked, new insulator operating parameters are input, and heat dissipation performance indicators are output. The heat dissipation performance indicators are compared with the corresponding safety range to determine whether the heat dissipation performance is qualified. For unqualified insulator operating parameters, multiple optimization variables are defined from the geometric parameters, and multiple optimization objectives are defined to form a Pareto front. The optimal combination of optimization variables at the Pareto front is solved and output.

[0007] Furthermore, the multi-path adaptive meshing strategy includes: a multi-physics coupled adaptive meshing method; A coupled model of electric field, temperature field, and mechanical stress field is established; the electric field distribution is calculated to generate the electric field intensity; the heat source is calculated based on the electric field intensity and the dielectric loss of the insulator material, and the temperature field is solved by substituting it into the heat conduction equation; the mechanical stress field is obtained by solving the stress distribution based on the temperature field and electric field. The electric field, temperature field, and mechanical stress field are weighted and coupled to solve for the convergent electric field strength, temperature, and stress. A joint error estimation function is constructed based on the electric field strength gradient, temperature gradient, and stress gradient. The mesh is refined in the region where the joint error exceeds the corresponding error threshold.

[0008] Furthermore, the thermal boundary conditions include: Convection heat transfer; convective heat flux density It is equal to the product of the convective heat transfer coefficient and the operating temperature difference; the operating temperature difference is the difference between the insulator surface temperature and the ambient temperature. The heat flux density at the interface between the insulator surface and the air is obtained by simulating the airflow over the composite insulator surface, and the convective heat transfer coefficient at the interface is calculated based on the heat flux density. ;Will As boundary conditions, they are used to update the thermal field model. .

[0009] Furthermore, the heat source loss is modified, including: The steady-state electric field intensity in the formula for calculating heat loss sources Updated to steady-state electric field strength Localized enhanced electric field strength caused by space charge sum; In the solution of the fully coupled field, the locally enhanced electric field strength is dynamically updated. .

[0010] Furthermore, the convective heat transfer coefficient of the umbrella skirt surface is corrected by region, including: The convective heat transfer coefficient of each section of the insulator is the product of the reference convective heat transfer coefficient of the insulator surface under the current environmental conditions and the convective correction coefficient. The convection correction factor is a multiple of the reference convection heat transfer coefficient, defined according to the umbrella skirt structure partition.

[0011] Furthermore, the training samples include: The solution output of the fully coupled model includes the temperature field, core rod hot spot temperature, local temperature gradient, and convective heat transfer coefficient at different locations on the surface of the composite insulator. The reference operating condition parameters include the insulator geometric parameters, voltage level, operating phase voltage, and environmental conditions corresponding to the solution output.

[0012] Furthermore, the optimization objective includes: Minimize the maximum temperature of the mandrel, minimize the temperature rise of the mandrel, and minimize the overall weight of the insulator; The constraints that need to be met in solving the optimization objective include: the maximum temperature of the core rod does not exceed the material's safe temperature; the overall weight increase of the insulator does not exceed a set proportion; and the heat loss source does not exceed the material's allowable peak value.

[0013] The second aspect of this application discloses a heat dissipation optimization simulation system for composite insulators of ultra-high voltage lines, which implements the heat dissipation optimization simulation method as described in the first aspect of this application. The system includes: Parametric modeling and adaptive mesh module; used to construct a parametric template library for composite insulators for ultra-high voltage line scenarios, the library includes composite insulator geometric parameters, interface and connection parameters, material property parameters, field distribution parameters and environmental parameters; based on the parametric template library, a three-dimensional geometric model is generated, and a multi-path adaptive mesh generation strategy is used to process the three-dimensional geometric model; A multiphysics coupling module is used to establish a fully coupled electrothermal-fluid model based on the processed three-dimensional geometric model. In the fully coupled model, the nonlinear dielectric loss heat source and leakage current Joule heat inside the insulator are calculated according to the electric field strength and substituted into the thermal field model. Thermal boundary conditions are configured in combination with environmental conditions, and the thermal boundary conditions are updated by calculating the convective heat transfer coefficient on the surface of the insulator through the flow field. The fully coupled field benchmark simulation module is used to correct the loss heat source by introducing a space charge nonlinear electric field enhancement term into the fully coupled model, and to perform partitioned correction on the convective heat transfer coefficient of the umbrella skirt surface; combined with the corrected heat source distribution and boundary conditions, the fully coupled model is solved; the solution results are combined with the corresponding benchmark operating condition parameters as benchmark operating condition training samples, and the surrogate model is trained. The heat dissipation performance evaluation module is used to call the trained surrogate model, input new insulator operating parameters, and output heat dissipation performance indicators. It compares the heat dissipation performance indicators with the corresponding safety range to determine whether the heat dissipation performance is qualified. For unqualified insulator operating parameters, it defines multiple optimization variables from the geometric parameters and defines multiple optimization objectives to form a Pareto front. It solves and outputs the optimal combination of optimization variables at the Pareto front.

[0014] The beneficial effects of this invention are that, compared with the prior art, 1. By constructing a parameterized template library for composite insulators, a fully coupled multi-physics model, and multi-path adaptive mesh generation, and combining space charge enhancement correction and shed partitioned heat transfer correction, this method can accurately simulate the distribution of electrothermal flow and heat dissipation behavior of insulators under different voltage levels, operating conditions, and environmental conditions, and achieve precise prediction of core rod hot spot temperature and local temperature gradient.

[0015] 2. By using the simulation results of the fully coupled model to construct training samples and train the surrogate model, it is possible to quickly output heat dissipation performance indicators after inputting new operating condition parameters, and compare them with the safety range to determine whether they are qualified, thereby improving the efficiency of heat dissipation performance evaluation and avoiding the problem of long simulation time in traditional simulation.

[0016] 3. For unqualified or underperforming operating conditions, by combining geometric parameter optimization and multi-objective Pareto front solution, the maximum temperature of the mandrel, temperature rise and overall weight of the insulator can be optimized at the same time while meeting the material safety temperature and weight constraints. This achieves coordinated optimization design of insulator structure and heat dissipation performance, improving future operational reliability and safety. Attached Figure Description

[0017] Figure 1 A flowchart of the simulation optimization method provided for the embodiment. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of this invention. The embodiments described in this application are merely some embodiments of this invention, and not all embodiments. Based on the spirit of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the protection scope of this invention.

[0019] Composite insulators are widely used in such lines due to their excellent hydrophobicity, anti-pollution flashover ability, light weight, and maintenance-free operation. However, under long-term high electric fields, heavy loads, and complex environmental stresses, composite insulators may generate abnormal heat due to various reasons (such as material dielectric loss, partial discharge from interface defects, and contamination and moisture). For ultra-high voltage insulators, this heating problem is particularly prominent and dangerous. Continuous internal heat accumulation can directly lead to the "brittle fracture" of its fiberglass core (FRP), causing catastrophic accidents such as conductor grounding and power grid disconnection.

[0020] Therefore, predicting the heat dissipation performance of insulators during the design phase and assessing their thermal state during operation are of paramount importance for ensuring the intrinsic safety and reliable operation of ultra-high voltage lines. Currently, the industry mainly uses the following two types of technical means to deal with the insulator heating problem: (1) Qualitative analysis based on empirical formulas and simplified models; mainly relying on electric field distribution simulation (such as electrostatic field finite element analysis) and mechanical strength verification, with insufficient consideration of thermal performance. Usually, only a rough verification is performed based on the heat resistance level of the material (such as about 200℃ for silicone rubber), or steady-state thermal calculation based on simplified empirical formulas (such as Newton's law of cooling). (2) General thermal simulation based on general finite element software; composite insulators have complex geometric structures (multiple skirts, multiple curved surfaces), and each simulation requires tedious geometric modeling, mesh generation, and boundary condition setting from scratch. Although general software can achieve multi-physics coupling, it lacks pre-set specialized models for the unique heating and heat dissipation mechanisms of composite insulators. For example, it is difficult to conveniently define the volume dielectric loss heat source that is nonlinear with the electric field strength, and it is difficult to accurately simulate the distribution of surface contaminant layer and its influence on leakage current and heating. The simulation results are often only qualitative, which is difficult to meet the stringent requirements of ultra-high voltage insulators for quantitative and accurate assessment of thermal state.

[0021] (1) Insufficient accuracy of thermal design methods; existing technologies mainly rely on simplified empirical formulas or steady-state thermal calculations, which cannot accurately simulate the complex multi-physics coupled thermal processes (such as electric field-thermal field-flow field coupling) inside ultra-high voltage composite insulators, resulting in huge deviations between heat dissipation performance predictions and actual operating conditions, and failing to support refined design and safety assessment. (2) Problems of inefficient and unprofessional simulation tools; using general-purpose finite element software for thermal simulation has the defects of cumbersome modeling process, long calculation cycle, and weak professional targeting. There is a lack of dedicated and efficient simulation models for the unique heating mechanism (such as nonlinear dielectric loss and pollution effects) and complex structure (multiple sheds, interface thermal resistance) of composite insulators, making it difficult to achieve rapid design iteration and optimization.

[0022] As an embodiment of this application, a specific implementation method for heat dissipation optimization simulation method of composite insulators for ultra-high voltage lines is disclosed. The execution flow of the method embodiment is as follows: Figure 1 .

[0023] S1: As one implementation method of the example, parametric modeling and preprocessing; 1.1: Construct a parameterized template library for composite insulators; Design templates that meet the heat dissipation optimization requirements for ultra-high voltage composite insulators through heat dissipation optimization simulation, ensuring that composite insulators can adapt to high electric field and high temperature working environments, while taking into account the changes in different current loads and ambient temperature.

[0024] A template for developing core parameters of ultra-high voltage composite insulators has been developed to support insulator models of different specifications. The core parameters include, but are not limited to: Geometry and dimensions: The diameter of the skirt, the thickness of the sheath, the diameter of the core rod, etc., are basic geometric dimensions that directly affect the physical shape and volume of the model; these parameters are used to generate insulator models of different sizes and shapes.

[0025] Interface and connection parameters: the contact interface between the mandrel and the sheath, the thermal contact area and thermal resistance of the fitting contact region, etc. In thermal simulation, these parameters directly affect the heat conduction path and thermal resistance, and are key inputs for temperature field calculation; in electric field simulation, the geometric continuity of the contact area also affects the degree of electric field concentration.

[0026] Material properties: Physical properties of insulator materials, such as thermal conductivity, specific heat capacity, and dielectric constant. These parameters determine the heat transfer and electric field response characteristics in simulations.

[0027] Field distribution parameters: These are parameters related to the distribution of the electric field and heat sources, such as electric field strength and heat source distribution. It should be noted that in simulations, these parameters can be used as preset heat source distributions or electric field boundary conditions to control simulation settings.

[0028] Environmental parameters include ambient temperature, humidity, and wind speed; in thermal simulation, these parameters serve as boundary conditions that affect the heat dissipation efficiency of the composite insulator.

[0029] Specifically, CAD tools and custom scripts can be used to automatically generate a three-dimensional geometric model of the composite insulator after the user inputs key design parameters. Those skilled in the art can implement this based on their engineering experience; further details are omitted in this embodiment.

[0030] 1.2: To address the more extreme physical fields and transient processes faced by composite insulators under ultra-high voltage line conditions, a multi-path adaptive mesh partitioning method is proposed.

[0031] Path 1: Multiphysics coupling adaptive mesh generation method: Establish an electric field-temperature-mechanical stress coupling model to ensure accurate simulation of composite insulators in high electric field, high temperature and stress regions; (1) The electric field distribution is calculated using the Poisson equation. ; For electric potential, Let be the dielectric constant of the material. The charge density is used to generate the electric field strength based on the electric field distribution. First, determine the first electric field region (high electric field region, such as the edge of the umbrella skirt). The high electric field region here is the region where the electric field strength is greater than or equal to the first field strength threshold, which can be set based on engineering experience.

[0032] (2) The heat source is generated based on the electric field strength and the dielectric loss of the insulator material. When input into the heat conduction equation, it is expressed as: ; Thermal conductivity is temperature-dependent. For temperature.

[0033] (3) Based on elasticity mechanics, the stress distribution is calculated using the stress-strain relationship, expressed as follows: ; For stress tensor, It is the strain tensor. Here is the material stiffness matrix; , , , This represents the tensor index.

[0034] (4) The calculation results of electric field, temperature field and stress are coupled using the weighted residual method: ; In the formula, For multiphysics residuals, , , For the trial function, For the computational domain.

[0035] Furthermore, the error is calculated using a multiphysics joint error estimation function, and the mesh is adjusted accordingly. The joint error estimation function is expressed as: ; in, Let be the error estimation function. , , These are the electric field intensity gradient, temperature gradient, and stress gradient, respectively.

[0036] Based on the error estimation function, the mesh is dynamically refined in regions with large electric field, temperature, and stress gradients; for example, in regions with high electric field strength and significant temperature rise (such as the edge of the equalizing ring, the interface between the fitting and the sheath), the error... If the error exceeds its corresponding error threshold, the area will be meshed.

[0037] Path 2: Dynamic adaptive mesh generation under transient and alternating loads; automatically refines the mesh in critical regions during transient processes and appropriately coarsens the mesh during steady-state phases to save computational resources.

[0038] Time-domain simulation is used to capture the effects of transient loads, based on the rate of change of current. and voltage change rate Determine transient loads; when and An increase indicates a sudden change in current and voltage, such as operational overvoltage or lightning strikes; it also identifies regions of rapid change in electric field and temperature and automatically densifies the grid.

[0039] Path 3: For DC ultra-high voltage insulators, establish a correlation model between space charge density and electric field distortion, and adaptively increase the grid density in the charge accumulation region; For a DC electric field, the electric field distortion is more significant in the charge accumulation region. Based on the Poisson equation, the relationship between space charge density and electric field distortion is established.

[0040] First, set the threshold for space charge density. The space charge density is greater than The cells or nodes are retained; then the charge density gradient of the retained cells or nodes is calculated. ,when Greater than its critical value If the condition is found to be a critical region for charge accumulation, then the dynamic mesh encryption method described in path 1 is applied to the critical region for charge accumulation.

[0041] S2: As one implementation method of the embodiment, based on the processed three-dimensional geometric model, an electro-thermal-fluid fully coupled model for ultra-high voltage composite insulators is established, boundary conditions are configured, and environmental factors are combined to simulate the temperature rise, hot spots and heat dissipation performance of the insulators under various operating conditions.

[0042] 2.1: Electric field model; The Poisson distribution is used to solve for the internal potential distribution of the composite insulator, followed by the calculation of the electric field intensity. The nonlinear dielectric loss heat source generated inside the insulator dielectric is calculated and expressed as follows: ; In the formula, Indicates heat loss. The electric field angular frequency, Represents the vacuum permittivity. This represents the temperature-dependent relative permittivity. This represents the temperature-dependent loss factor. denoted as electric field strength.

[0043] Calculate the Joule heating caused by leakage current ; For local leakage current, It is a resistor.

[0044] 2.2: Based on heat loss sources Joule fever Establish a thermal field model, represented as: ; In the formula, For material mass density, This indicates the temperature-dependent specific heat capacity. This indicates temperature-dependent thermal conductivity.

[0045] The thermal boundary condition is expressed as follows: Convection heat transfer: ; The heat flux density for convective heat transfer is expressed at the insulator location. The amount of heat removed per unit area per unit time through convection and heat exchange; It is the convective heat transfer coefficient, used to reflect the strength of convective heat transfer between air and the surface of the insulator; and These represent the surface temperature of the insulator and the ambient temperature away from the insulator surface, respectively.

[0046] Surface radiation: ; Surface radiative heat flux density represents the net heat radiated from the surface of the insulator to the outside. The emissivity of the insulator surface depends on the insulator surface material and roughness; It is the Stefan-Boltzmann constant; This indicates the surface temperature of the insulator (Kelvin temperature is used in calculations). Indicates the sky temperature.

[0047] Solar radiation: ; The solar heat flux density represents the solar radiation power received by the insulator surface. Solar irradiance; The angle of incidence of the sun is the angle between the sunlight and the normal to the surface of the insulator.

[0048] 2.3: Establish the flow field model; Simulate airflow over the surface of a composite insulator, considering the effects of wind speed and direction on the convective heat transfer coefficient: ; This represents the heat flux density at the interface between the insulator surface and the air. The formula describes how the convective heat transfer coefficient at this interface is extracted through conjugate heat transfer calculations. It is used as a boundary condition in the thermal field model, serving as the convective heat transfer coefficient in the thermal boundary condition. .

[0049] 2.4: Configure boundary conditions according to the operating conditions; preset operating conditions in the simulation platform, such as voltage, ambient temperature, wind speed, wind direction, solar radiation intensity and angle, etc.; calculate and apply boundary conditions, such as heat source, convective heat transfer coefficient, surface emissivity, solar radiation heat flux, etc. through the steps of 2.1-2.4.

[0050] The basic simulation description is as follows: by applying voltage, the electric field distribution is calculated, and the node losses and leakage current Joule heat (i.e., heat sources) are calculated; the heat sources are input into the thermal field model, coupled with the flow field model to calculate the temperature rise and convective heat dissipation, and the temperature dependence parameters of the insulator material are updated. This process is iterated until convergence.

[0051] S3: As one implementation method of the embodiment, a baseline working condition simulation is performed on the physical characteristics of ultra-high voltage composite insulators to train the surrogate model, thereby improving the simulation accuracy and the solution speed in the simulation process.

[0052] 3.1: In the baseline simulation, considering that the nonlinear accumulation of space charge in ultra-high voltage composite insulators will cause local electric field distortion, resulting in non-uniform distribution of heat sources inside the insulator, this embodiment models the nonlinearity of space charge.

[0053] Under DC or transient high-voltage operating conditions, nonlinear accumulation of space charge may occur in the internal dielectric (silicone rubber + FRP core rod) of the insulator. This accumulation leads to an enhancement of the local electric field, affecting the accuracy of dielectric loss heat source calculations and consequently impacting the insulator's safety assessment. For example, hot spots on the core rod or localized hot spots under the sheath below the sheds may be missed.

[0054] For composite insulators under DC or transient high voltage conditions, the nonlinear dielectric loss heat source is updated as follows: ; in, This is due to the localized enhancement of the electric field caused by space charge. In the fully coupled field solution, dynamic updates are performed. This allows the local heat source distribution to reflect nonlinear charge accumulation. It ensures that the temperature field simulation matches actual operating conditions, improving the reliability of safety predictions.

[0055] 3.2: Considering the umbrella skirt structure of ultra-high voltage composite insulators, the heat dissipation coefficient of the outer surface varies greatly at different umbrella skirt positions. During the simulation of the baseline working condition, the convective heat transfer coefficient at different positions of the umbrella skirt is corrected accordingly.

[0056] Ultra-high voltage composite insulators typically employ a multi-layered shed design. The shape and spacing of the sheds can lead to uneven airflow, resulting in localized differences in convective heat dissipation. The top sheds have low wind resistance and good heat dissipation, while the bottom sheds or those below the high-voltage end have obstructed airflow and poor heat dissipation, meaning that the convective heat transfer coefficient is uneven at different locations on the sheds.

[0057] Based on CFD (Computational Fluid Dynamics) predictions or empirical models, the local convective heat transfer coefficient on the umbrella skirt surface is corrected during baseline simulation. : ; In the formula, This is the baseline convective heat transfer coefficient of the insulator surface under current environmental conditions; This represents the convection correction factor for different locations on the umbrella skirt, indicating the multiple of that location relative to the average heat dissipation capacity, and is affected by wind direction, obstruction, and the geometry of the umbrella skirt. Since umbrella skirts typically have distinct geometric features, this embodiment defines the convection correction factor in a zoned manner for engineering practice, directly assigning an empirical coefficient to each region. For example, the top surface / windward side... ,side Bottom / Leaf The root occlusion area can be assigned a value. .

[0058] It should be noted that the fouling level (such as ESDD / NSDD) affects the local reference convective heat transfer coefficient of the umbrella skirt surface by changing surface wetting, roughness, and the thermal boundary layer characteristics of the fouling layer. or equivalent convection correction factor This should be taken into account in CFD calibration or empirical models. Alternatively, a scaling factor can be used for correction.

[0059] Simultaneously solve the electro-thermal-fluid coupling model, and the solution output includes the temperature field. Chipstick hotspot Local temperature gradient (Axial) and The non-uniform distribution of radial and convective heat transfer (i.e., the convective heat transfer coefficient at different locations on the surface of the composite insulator) is combined with the baseline operating parameters to generate high-precision training samples.

[0060] It should be noted that when using baseline operating condition parameters to obtain high-fidelity simulation samples, in order to ensure that the surrogate model has sufficient generalization ability in subsequent rapid prediction and optimization iterations, it is necessary to design a model that covers a variety of possible operating conditions. These operating conditions should include combinations of different voltage levels, wind speeds, wind directions, solar radiation intensity, ambient temperatures, and pollution levels, so as to fully reflect the extreme and normal conditions that composite insulators may encounter in actual operation.

[0061] 3.3: Train the surrogate model based on the high-precision training samples generated in 3.2.

[0062] The baseline operating parameters include the insulator's geometric parameters (sleeve diameter, spacing, tilt angle, sheath thickness, core rod diameter, etc.), voltage level, operating phase voltage, and environmental conditions (wind speed, wind direction, solar radiation intensity, humidity, pollution level).

[0063] Furthermore, a loss function is constructed using a neural network or Gaussian model and high-precision training samples to train the surrogate model. The loss function is expressed as: ; In the formula, This is the total loss value. This represents the total number of high-precision training samples. For sample index; This indicates that the surrogate model predicts the temperature field. For the sample The realistic temperature field in high-fidelity simulation; To predict the temperature field gradient for the surrogate model, For high-fidelity simulation of the real temperature field gradient; This is the regularization coefficient.

[0064] S4: As one implementation method of the embodiment, the trained proxy model is called to simulate the new insulator operating parameters, output the insulator heat dissipation performance index and perform quantitative evaluation.

[0065] The surrogate model outputs performance metrics including: mandrel hotspot temperature. Maximum axial temperature gradient Maximum radial temperature gradient Temperature distribution on the surface of the umbrella skirt ; A safety threshold is set based on the design performance of the composite insulator; for example, the maximum allowable operating temperature of the mandrel. The maximum allowable temperature rise is 70~75℃. wait.

[0066] The automatic evaluation logic can be set so that the insulator's heat dissipation performance is qualified only if all performance indicators are less than their corresponding safety thresholds; otherwise, it is determined that optimization is required.

[0067] Furthermore, for the insulator parameter combinations that need optimization, their operating parameters are optimized. In this embodiment, the selected optimization variables include: shed spacing, sheath thickness, equalizing ring size, shed angle, etc. Define constraints, including: maximum mandrel temperature Not exceeding the upper limit of the safe temperature range Maximum temperature rise (the increase in the highest temperature of the mandrel relative to the ambient temperature) Weight increase not exceeding 5%, heat loss Not exceeding the material's allowable peak value , Determined based on the allowable range of the material under long-term operating conditions.

[0068] Furthermore, the optimization objectives of the optimization variables are defined as follows: the primary objective is to minimize the maximum temperature of the mandrel, and the secondary objectives are to minimize the temperature rise and the overall weight.

[0069] Multiple optimization objectives form a Pareto front, which is then solved using genetic algorithms, particle swarm optimization, or multi-objective evolutionary algorithms to generate frontier solutions.

[0070] As an embodiment of this application, a heat dissipation optimization simulation system for composite insulators of ultra-high voltage lines is disclosed. Employing the specific implementation method described above for heat dissipation optimization simulation, the system includes: Parametric modeling and adaptive mesh module; used to construct a parametric template library for composite insulators for ultra-high voltage line scenarios, the library includes composite insulator geometric parameters, interface and connection parameters, material property parameters, field distribution parameters and environmental parameters; based on the parametric template library, a three-dimensional geometric model is generated, and a multi-path adaptive mesh generation strategy is used to process the three-dimensional geometric model; A multiphysics coupling module is used to establish a fully coupled electrothermal-fluid model based on the processed three-dimensional geometric model. In the fully coupled model, the nonlinear dielectric loss heat source and leakage current Joule heat inside the insulator are calculated according to the electric field strength and substituted into the thermal field model. Thermal boundary conditions are configured in combination with environmental conditions, and the thermal boundary conditions are updated by calculating the convective heat transfer coefficient on the surface of the insulator through the flow field. The fully coupled field benchmark simulation module is used to correct the loss heat source by introducing a space charge nonlinear electric field enhancement term into the fully coupled model, and to perform partitioned correction on the convective heat transfer coefficient of the umbrella skirt surface; combined with the corrected heat source distribution and boundary conditions, the fully coupled model is solved; the solution results are combined with the corresponding benchmark operating condition parameters as benchmark operating condition training samples, and the surrogate model is trained. The heat dissipation performance evaluation module is used to call the trained surrogate model, input new insulator operating parameters, and output heat dissipation performance indicators. It compares the heat dissipation performance indicators with the corresponding safety range to determine whether the heat dissipation performance is qualified. For unqualified insulator operating parameters, it defines multiple optimization variables from the geometric parameters and defines multiple optimization objectives to form a Pareto front. It solves and outputs the optimal combination of optimization variables at the Pareto front.

[0071] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the protection scope of the claims of the present invention.

Claims

1. A heat dissipation optimization simulation method for an ultra-high voltage line composite insulator, characterized in that, include: A parametric template library for composite insulators is constructed for ultra-high voltage line scenarios. The library includes geometric parameters, interface and connection parameters, material property parameters, field distribution parameters, and environmental parameters of composite insulators. A three-dimensional geometric model is generated based on the parametric template library, and a multi-path adaptive mesh generation strategy is used to process the three-dimensional geometric model. Based on the processed three-dimensional geometric model, a fully coupled electrothermal-fluid model is established. In the fully coupled model, the nonlinear dielectric loss heat source and leakage current Joule heat inside the insulator are calculated according to the electric field strength and substituted into the thermal field model. Thermal boundary conditions are configured in combination with environmental conditions, and the convective heat transfer coefficient on the surface of the insulator is calculated through the flow field to update the thermal boundary conditions. For the fully coupled model, a space charge nonlinear electric field enhancement term is introduced to correct the heat loss source, and the convective heat transfer coefficient of the umbrella skirt surface is corrected by partitioning. Combining the corrected heat source distribution and boundary conditions, the model is solved again through the fully coupled model. The solution results are combined with the corresponding benchmark parameters as benchmark training samples, and the surrogate model is trained. The trained surrogate model is invoked, new insulator operating parameters are input, and heat dissipation performance indicators are output. The heat dissipation performance indicators are compared with the corresponding safety range to determine whether the heat dissipation performance is qualified. For unqualified insulator operating parameters, multiple optimization variables are defined from the geometric parameters, and multiple optimization objectives are defined to form a Pareto front. The optimal combination of optimization variables at the Pareto front is solved and output.

2. The heat dissipation optimization simulation method for composite insulators of ultra-high voltage lines according to claim 1, characterized in that, The multi-path adaptive mesh partitioning strategy includes: Multiphysics coupling adaptive mesh generation method; A coupled model of electric field, temperature field, and mechanical stress field is established; the electric field distribution is calculated to generate the electric field intensity; the heat source is calculated based on the electric field intensity and the dielectric loss of the insulator material, and the temperature field is solved by substituting it into the heat conduction equation; the mechanical stress field is obtained by solving the stress distribution based on the temperature field and electric field. The electric field, temperature field, and mechanical stress field are weighted and coupled to solve for the convergent electric field strength, temperature, and stress. A joint error estimation function is constructed based on the electric field strength gradient, temperature gradient, and stress gradient. The mesh is refined in the region where the joint error exceeds the corresponding error threshold.

3. The heat dissipation optimization simulation method for composite insulators of ultra-high voltage lines according to claim 1, characterized in that, The thermal boundary conditions include: Convection heat transfer; convective heat flux density It is equal to the product of the convective heat transfer coefficient and the operating temperature difference; the operating temperature difference is the difference between the insulator surface temperature and the ambient temperature. The heat flux density at the interface between the insulator surface and the air is obtained by simulating the airflow over the composite insulator surface, and the convective heat transfer coefficient at the interface is calculated based on the heat flux density. ;Will As boundary conditions, they are used to update the thermal field model. .

4. The heat dissipation optimization simulation method for composite insulators of ultra-high voltage lines according to claim 1, characterized in that, Correcting the heat loss source includes: The steady-state electric field intensity in the formula for calculating heat loss sources Updated to steady-state electric field strength Localized enhanced electric field strength caused by space charge sum; In the solution of the fully coupled field, the locally enhanced electric field strength is dynamically updated. .

5. The heat dissipation optimization simulation method for composite insulators of ultra-high voltage lines according to claim 1, characterized in that, The convective heat transfer coefficient of the umbrella skirt surface is corrected by region, including: The convective heat transfer coefficient of each section of the insulator is the product of the reference convective heat transfer coefficient of the insulator surface under the current environmental conditions and the convective correction coefficient. The convection correction factor is a multiple of the reference convection heat transfer coefficient, defined according to the umbrella skirt structure partition.

6. The heat dissipation optimization simulation method for composite insulators of ultra-high voltage lines according to claim 1, characterized in that, The training samples include: The solution output of the fully coupled model includes the temperature field, core rod hot spot temperature, local temperature gradient, and convective heat transfer coefficient at different locations on the surface of the composite insulator. The reference operating condition parameters include the insulator geometric parameters, voltage level, operating phase voltage, and environmental conditions corresponding to the solution output.

7. The heat dissipation optimization simulation method for composite insulators of ultra-high voltage lines according to claim 1, characterized in that, The optimization objectives include: Minimize the maximum temperature of the mandrel, minimize the temperature rise of the mandrel, and minimize the overall weight of the insulator; The constraints that need to be met in solving the optimization objective include: the maximum temperature of the core rod does not exceed the material's safe temperature; the overall weight increase of the insulator does not exceed a set proportion; and the heat loss source does not exceed the material's allowable peak value.

8. A heat dissipation optimization simulation system for composite insulators of ultra-high voltage lines, comprising executing the heat dissipation optimization simulation method as described in any one of claims 1-7, characterized in that, The system includes: Parametric modeling and adaptive mesh module; used to construct a parametric template library for composite insulators for ultra-high voltage line scenarios, the library includes composite insulator geometric parameters, interface and connection parameters, material property parameters, field distribution parameters and environmental parameters; based on the parametric template library, a three-dimensional geometric model is generated, and a multi-path adaptive mesh generation strategy is used to process the three-dimensional geometric model; A multiphysics coupling module is used to establish a fully coupled electrothermal-fluid model based on the processed three-dimensional geometric model. In the fully coupled model, the nonlinear dielectric loss heat source and leakage current Joule heat inside the insulator are calculated according to the electric field strength and substituted into the thermal field model. Thermal boundary conditions are configured in combination with environmental conditions, and the thermal boundary conditions are updated by calculating the convective heat transfer coefficient on the surface of the insulator through the flow field. The fully coupled field benchmark simulation module is used to correct the loss heat source by introducing a space charge nonlinear electric field enhancement term into the fully coupled model, and to perform partitioned correction on the convective heat transfer coefficient of the umbrella skirt surface; combined with the corrected heat source distribution and boundary conditions, the fully coupled model is solved; the solution results are combined with the corresponding benchmark operating condition parameters as benchmark operating condition training samples, and the surrogate model is trained. The heat dissipation performance evaluation module is used to call the trained surrogate model, input new insulator operating parameters, and output heat dissipation performance indicators. It compares the heat dissipation performance indicators with the corresponding safety range to determine whether the heat dissipation performance is qualified. For unqualified insulator operating parameters, it defines multiple optimization variables from the geometric parameters and defines multiple optimization objectives to form a Pareto front. It solves and outputs the optimal combination of optimization variables at the Pareto front.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the computer program is loaded into the processor, it implements the heat dissipation optimization simulation method according to any one of claims 1-7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the heat dissipation optimization simulation method according to any one of claims 1-7.

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