Temperature rise prediction method, device and equipment of transformer structural component and storage medium

Abstract

The invention discloses a temperature rise prediction method and device for a transformer structural member, equipment and a storage medium, relates to the technical field of transformer structural member management, and discloses a temperature rise prediction method for a transformer structural member, and the method comprises the steps: obtaining a preset temperature rise threshold value and a three-dimensional model of a power transformer; carrying out electromagnetic simulation calculation on the three-dimensional model of the power transformer to obtain the loss of the transformer structural component; solving a temperature field according to the loss of the transformer structural component to obtain an initial temperature rise result; and obtaining a temperature rise judgment result according to the initial temperature rise result and a preset temperature rise threshold value, and determining a target temperature rise result according to the temperature rise judgment result to complete temperature rise prediction of the transformer structural member. The three-dimensional model is combined with coupling calculation of electromagnetic simulation and temperature field solution, so that the electromagnetic characteristic and the heat conduction characteristic of the structural member can be more accurately captured, errors caused by simplified calculation are avoided, and accurate prediction of the temperature rise of the transformer structural member is realized.

Description

Technical Field

[0001] This application relates to the field of transformer structural component management technology, and in particular to methods, devices, equipment and storage media for predicting the temperature rise of transformer structural components. Background Technology

[0002] As a critical piece of equipment in the power system, the safety and stability of transformers directly affect the reliable operation of the entire power grid. During long-term operation, structural components such as the transformer core, windings, clamps, and tank continuously accumulate heat due to electromagnetic losses and eddy current effects, leading to temperature rise. If the temperature continues to rise, it can cause aging of insulation materials, a decrease in mechanical strength, and even equipment failure. This not only shortens the transformer's service life but also poses a serious threat to the safe operation of the power system. Therefore, it is necessary to accurately predict and control the temperature rise characteristics of transformer structural components.

[0003] Existing research and applications typically rely on empirical formulas, simplified models, or physical experiments for temperature rise analysis. While empirical formulas and simplified models can quickly assess temperature rise to a certain extent, they struggle to fully reflect the complex coupling characteristics of electromagnetic and temperature fields in transformers, often resulting in significant errors. Physical experiments, although providing more intuitive results, are costly, time-consuming, and cannot flexibly address the temperature distribution requirements of different operating conditions during the design phase. Therefore, traditional technical solutions generally suffer from insufficient computational accuracy. Summary of the Invention

[0004] The main objective of this application is to provide a method, apparatus, equipment, and storage medium for predicting the temperature rise of transformer structural components, aiming to solve the technical problem of insufficient calculation accuracy in predicting the temperature rise of transformer structural components.

[0005] To achieve the above objectives, this application proposes a method for predicting the temperature rise of transformer structural components, the method comprising:

[0006] Obtain the preset temperature rise threshold and the 3D model of the power transformer;

[0007] Electromagnetic simulation calculations were performed on the above-mentioned three-dimensional model of the power transformer to obtain the losses of the transformer structural components;

[0008] The temperature field is solved based on the losses of the above-mentioned transformer structural components to obtain the initial temperature rise result;

[0009] Based on the initial temperature rise result and the preset temperature rise threshold, the temperature rise determination result is obtained, and the target temperature rise result is determined based on the temperature rise determination result, so as to complete the temperature rise prediction of the transformer structural components.

[0010] In one embodiment, the step of performing electromagnetic simulation calculations on the three-dimensional model of the power transformer to obtain the losses of the transformer structural components includes:

[0011] In the above three-dimensional model of the power transformer, the condensed current structural components, the meshing structural components, the preset meshing rules, and the preset solution conditions are determined.

[0012] Surface impedance boundary conditions are set on the above-mentioned concentrated current structural components;

[0013] Current excitation conditions are set at the coil cross-section of the above-mentioned three-dimensional model of the power transformer;

[0014] The above-mentioned meshing structure is meshed according to the above-mentioned preset meshing rules to obtain the target electromagnetic meshing model;

[0015] Electromagnetic simulation calculations are performed on the target electromagnetic partitioning model based on the above-mentioned preset solution conditions, surface impedance boundary conditions, and current excitation conditions to obtain the transformer structural component losses.

[0016] In one embodiment, the step of solving the temperature field based on the losses of the transformer structural components to obtain the initial temperature rise result includes:

[0017] Obtain the preset temperature field mesh generation rules;

[0018] The heat transfer parameters are set based on the losses of the above-mentioned transformer structural components.

[0019] Based on the above-mentioned preset temperature field meshing rules, the meshing structure in the above-mentioned three-dimensional model of the power transformer is meshed to obtain the target temperature meshing model;

[0020] Based on the above heat transfer parameters, the temperature field of the target temperature partitioning model is solved to obtain the initial temperature rise result.

[0021] In one embodiment, the steps of obtaining a temperature rise determination result based on the initial temperature rise result and the preset temperature rise threshold, and determining a target temperature rise result based on the temperature rise determination result, include:

[0022] When the initial temperature rise result is greater than the preset temperature rise threshold, the model of the component to be optimized is determined based on the initial temperature rise result, and the model of the component to be optimized is optimized to obtain the optimized model.

[0023] Simulation analysis was performed based on the above optimized model to obtain the temperature rise determination result;

[0024] When the temperature rise determination result is less than or equal to the preset temperature rise threshold, the temperature rise determination result is taken as the target temperature rise result.

[0025] In one embodiment, the steps of determining the component model to be optimized based on the initial temperature rise result when the initial temperature rise result is greater than the preset temperature rise threshold, and optimizing the component model to obtain the optimized model, include:

[0026] When the initial temperature rise result is greater than the preset temperature rise threshold, the model of the component to be optimized is determined based on the initial temperature rise result.

[0027] Based on the above-mentioned model of the component to be optimized, a target optimization scheme is determined, wherein the target optimization scheme includes target optimization materials and / or target optimization strategies;

[0028] Based on the above-mentioned target optimization scheme, the model of the component to be optimized is optimized to obtain the optimized model.

[0029] In one embodiment, after the steps of obtaining a temperature rise determination result based on the initial temperature rise result and the preset temperature rise threshold, and determining a target temperature rise result based on the temperature rise determination result to complete the temperature rise prediction of the transformer structural component, the method further includes:

[0030] Based on the above target temperature rise results, the target cloud map components, simulation parameters, and simulation results are determined.

[0031] Generate a target display cloud map based on the above target cloud map components;

[0032] A simulation report is generated based on the above simulation parameters and simulation results;

[0033] Based on the aforementioned objectives, a cloud map and simulation report are used to visualize the temperature rise prediction.

[0034] In one embodiment, the aforementioned three-dimensional model of the power transformer includes a target core model, a coil three-dimensional model, and a structural component three-dimensional model;

[0035] Before the steps described above for obtaining the preset temperature rise threshold and the three-dimensional model of the power transformer, the following steps are also included:

[0036] Obtain core structure parameters, coil structure parameters, and transformer design parameters;

[0037] Based on the above core structure parameters, an initial core model is established;

[0038] Based on the initial core model described above, the spatial structure of the window and oil passage is constructed to obtain the target core model, wherein the target core model is based on the material properties of silicon steel sheet.

[0039] A three-dimensional model of the coil is established based on the above coil structure parameters, wherein the above three-dimensional model of the coil represents the properties of copper material;

[0040] Based on the above transformer design parameters, data matching is performed in the preset design principle database to obtain structural component design parameters, and a three-dimensional model of the structural component is established based on the above structural component design parameters.

[0041] In addition, to achieve the above objectives, this application also proposes a temperature rise prediction device for transformer structural components. The temperature rise prediction device for transformer structural components includes: a data acquisition module for acquiring a preset temperature rise threshold and a three-dimensional model of a power transformer.

[0042] The simulation calculation module is used to perform electromagnetic simulation calculations on the above-mentioned three-dimensional model of the power transformer to obtain the losses of the transformer structural components.

[0043] The temperature calculation module is used to solve the temperature field based on the losses of the above-mentioned transformer structural components to obtain the initial temperature rise result.

[0044] The temperature rise prediction module is used to obtain the temperature rise determination result based on the initial temperature rise result and the preset temperature rise threshold, and to determine the target temperature rise result based on the temperature rise determination result, so as to complete the temperature rise prediction of the transformer structural components.

[0045] In addition, to achieve the above objectives, this application also proposes a temperature rise prediction device for transformer structural components. The device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. The computer program is configured to implement the steps of the temperature rise prediction method for transformer structural components as described above.

[0046] In addition, to achieve the above objectives, this application also proposes a storage medium, which is a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the steps of the temperature rise prediction method for transformer structural components as described above.

[0047] In addition, to achieve the above objectives, this application also provides a computer program product, which includes a computer program that, when executed by a processor, implements the steps of the temperature rise prediction method for transformer structural components as described above.

[0048] One or more technical solutions proposed in this application have at least the following technical effects:

[0049] The three-dimensional model of the power transformer in this application embodiment can realistically reproduce the actual structure of the structural components. Electromagnetic simulation calculation based on the three-dimensional model can accurately obtain the losses of the structural components. Then, using these losses as a basis for temperature field solution, it can fully consider the coupling relationship between the electromagnetic field and the temperature field, as well as the three-dimensional nonlinear characteristics of the structural components, avoiding the deviations caused by empirical formulas or simplified models. Traditional transformer structural component temperature rise prediction relies on empirical formulas or simplified models, which are difficult to accurately reflect the coupling effect of complex electromagnetic fields and temperature fields. In particular, the three-dimensional nonlinear characteristics of transformer structural components are significant, and simplified calculations are prone to large errors, resulting in insufficient calculation accuracy. The technical means of this application solves the technical problem of insufficient calculation accuracy in transformer structural component temperature rise prediction. Compared with the prior art, by combining the three-dimensional model with the synergistic effect of electromagnetic simulation and temperature field solution, the nonlinear electromagnetic characteristics and thermal conduction characteristics of the structural components are effectively captured, significantly improving the accuracy of temperature rise prediction, reducing the errors caused by simplified calculations, and making the prediction results more consistent with the actual temperature rise of the transformer structural components. Attached Figure Description

[0050] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0051] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0052] Figure 1 A flowchart illustrating the method for predicting the temperature rise of transformer structural components provided in this application embodiment;

[0053] Figure 2 A schematic diagram of the target core model for the temperature rise prediction method of transformer structural components provided in the embodiments of this application;

[0054] Figure 3 A schematic diagram of a coil three-dimensional model of the temperature rise prediction method for transformer structural components provided in the embodiments of this application;

[0055] Figure 4 A schematic diagram of a three-dimensional model of a transformer structural component for the temperature rise prediction method provided in the embodiments of this application;

[0056] Figure 5 A target cloud map schematic diagram illustrating the temperature rise prediction method for transformer structural components provided in the embodiments of this application;

[0057] Figure 6Another flowchart illustrating an embodiment of the method for predicting the temperature rise of transformer structural components provided in this application;

[0058] Figure 7 A simplified flowchart illustrating the method for predicting the temperature rise of transformer structural components provided in this application embodiment;

[0059] Figure 8 A schematic diagram of the module structure of the temperature rise prediction device for transformer structural components provided in the embodiments of this application;

[0060] Figure 9 A schematic diagram of the equipment structure of the hardware operating environment involved in the temperature rise prediction method for transformer structural components provided in the embodiments of this application.

[0061] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0062] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0063] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0064] The main solution of this application embodiment is as follows: obtain a preset temperature rise threshold and a three-dimensional model of a power transformer; perform electromagnetic simulation calculations on the three-dimensional model of the power transformer to obtain the losses of the transformer structural components; solve the temperature field based on the losses of the transformer structural components to obtain the initial temperature rise result; obtain the temperature rise determination result based on the initial temperature rise result and the preset temperature rise threshold, and determine the target temperature rise result based on the temperature rise determination result to complete the temperature rise prediction of the transformer structural components.

[0065] In this embodiment, for ease of description, the following description will focus on a temperature rise prediction device for identifying transformer structural components.

[0066] Due to insufficient calculation accuracy in the temperature rise prediction of transformer structural components in existing technologies, this application provides a solution. By employing a three-dimensional model of the power transformer to realistically recreate the actual structure of the components, electromagnetic simulation calculations based on the three-dimensional model can accurately obtain the component losses. This loss is then used as the basis for temperature field calculation, fully considering the coupling relationship between the electromagnetic and temperature fields and the three-dimensional nonlinear characteristics of the components, avoiding deviations caused by empirical formulas or simplified models. Traditional transformer structural component temperature rise prediction relies on empirical formulas or simplified models, which are difficult to accurately reflect the coupling effect of complex electromagnetic and temperature fields. In particular, the three-dimensional nonlinear characteristics of transformer structural components are significant, and simplified calculations easily lead to large errors, resulting in insufficient calculation accuracy. The technical means of this application solves the technical problem of insufficient calculation accuracy in the temperature rise prediction of transformer structural components. Compared with existing technologies, by combining the three-dimensional model with the synergistic effect of electromagnetic simulation and temperature field calculation, the nonlinear electromagnetic and thermal conduction characteristics of the components are effectively captured, significantly improving the accuracy of temperature rise prediction, reducing errors caused by simplified calculations, and making the prediction results more consistent with the actual temperature rise of the transformer structural components.

[0067] It should be noted that the executing entity in this embodiment can be a computing service device with data processing, network communication, and program execution functions, such as a tablet computer, personal computer, or mobile phone, or an electronic device capable of performing the above functions, such as a temperature rise prediction device for transformer structural components. The following description uses a temperature rise prediction device for transformer structural components as an example to illustrate this embodiment and the subsequent embodiments.

[0068] Based on this, embodiments of this application provide a method for predicting the temperature rise of transformer structural components, referring to... Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the temperature rise prediction method for transformer structural components according to this application.

[0069] In this embodiment, the method for predicting the temperature rise of transformer structural components includes steps S10 to S40:

[0070] Step S10: Obtain the preset temperature rise threshold and the three-dimensional model of the power transformer.

[0071] It should be noted that the preset temperature rise threshold is the maximum allowable temperature rise value set in advance based on the transformer design agreement, industry standards, or actual operating requirements before conducting temperature rise prediction of transformer structural components.

[0072] Furthermore, the 3D model of the power transformer is constructed using 3D modeling tools, providing a complete digital representation of the shape, size, and relative positional relationships of each structural component. The model includes key structural components such as the core, coils, tank, web, limb plates, and tie plates, and assigns corresponding material properties to each component. For example, the core model is assigned silicon steel sheet properties, and the coil model is assigned copper material properties, realistically simulating the physical structure of the transformer and providing a foundation for subsequent simulation calculations.

[0073] In one feasible implementation, the three-dimensional model of the power transformer includes a target core model, a coil three-dimensional model, and a structural component three-dimensional model. Before step S10, steps S01 to S05 may also be included.

[0074] Step S01: Obtain the core structure parameters, coil structure parameters, and transformer design parameters.

[0075] It should be noted that the core structure parameters are key data used to construct the transformer core model, covering core lamination width, side lamination width, yoke lamination width, yoke window internal grade difference, stack thickness, oil channels, oil channel offset, yoke window external grade difference, core column grade difference, and side column grade difference. These parameters directly determine the core's geometry, size hierarchy, and internal oil channel distribution.

[0076] Furthermore, the coil structure parameters are the core data for constructing a transformer coil model, mainly including the coil's inner diameter, outer diameter, reactance height, and distance to the lower yoke of the core. These parameters determine the coil's radial dimensions, axial height, and relative position to the core, directly affecting the coil's electromagnetic characteristics and heat dissipation effect. They are crucial for ensuring that the coil model can simulate the actual coil's operating state.

[0077] In addition, transformer design parameters are data describing the overall design specifications and key characteristics of the transformer. These include rated capacity, voltage level, core type, tank shape, tank length, width, and height, web length, thickness, height, vertical position, web spacing, leg length, width, distance from the center of the transformer body, tie plate length, width, thickness, slot position, slot width, lung lobe magnetic shield large circle radius, small circle radius, distance from the centerline of the transformer body, vertical position, tank magnetic shield length, width, thickness, position, and quantity. These parameters cover the overall performance indicators of the transformer and the shape and position information of the main structural components, serving as the key basis for subsequent matching of structural component design parameters and construction of structural component models.

[0078] Step S02: Establish an initial core model based on the core structure parameters.

[0079] It should be noted that the initial core model is a cuboid model of each level of the core, built piece by piece using geometric modeling tools based on the core structure parameters.

[0080] Understandably, a geometric modeling tool is used to import the core structure parameters. The basic widths of key parts of the core are determined based on the widths of the core pillars, side pillars, and yokes. The overall thickness of the core is determined based on the stack thickness. Parameters such as the dimensional variations within the yoke window, core pillar variations, side pillar variations, and yoke window variations are used to clarify the dimensional changes at each level of the core. Following these parameters, a piece-by-piece modeling approach is adopted. First, cuboid units for each level of the core pillars, side pillars, and yoke are constructed. Then, these cuboid units are combined according to the actual stacking order and structural relationships of the core to form a complete cuboid model containing only the basic geometry, thus obtaining the initial core model.

[0081] Step S03: Construct the spatial structure of the window and oil passage based on the initial core model to obtain the target core model, wherein the target core model is a silicon steel sheet material.

[0082] It should be noted that the window is a space structure reserved in the core model to accommodate the coil.

[0083] Additionally, oil channels are channel structures set within the core model for the flow of transformer oil. As the transformer oil flows within these channels, it carries away the heat generated during the core's operation, thus achieving heat dissipation. The number, size, and distribution of these oil channels directly affect the core's heat dissipation efficiency, thereby influencing the transformer's temperature rise performance and operational reliability.

[0084] Understandably, the target core model is the final core model formed by constructing window and oil channel spatial structures and assigning silicon steel sheet material properties based on the initial core model. This model fully reflects the actual geometry, internal channels, and material properties of the core, and can accurately simulate the magnetic circuit characteristics and heat dissipation of the core during transformer operation.

[0085] It should be understood that the material properties of silicon steel sheets refer to the physical characteristics of silicon steel sheets, mainly including magnetic permeability, resistivity, thermal conductivity, density, and specific heat capacity. Silicon steel sheets have good magnetic permeability and low iron loss. By assigning silicon steel sheet material properties to the iron core model, the model can accurately reflect the electromagnetic and thermal conductivity characteristics of the actual iron core, ensuring the authenticity of subsequent simulation calculation results.

[0086] Reference Figure 2 , Figure 2 This is a schematic diagram of the target core model provided in Embodiment 1 of the method for predicting the temperature rise of transformer structural components in this application.

[0087] like Figure 2As shown, the model is the target core model, with a grid-like coordinate system as the background. The coordinates are represented by the letters X and Y, indicating the model's position in three-dimensional space. X and Y represent two coordinate axes on a two-dimensional plane, indicating the model's specific location and orientation. The model's shape consists of multiple rectangular windows, representing the core's windows and oil passages. The overall rectangular shape of the model aims to optimize magnetic flux and reduce losses. The lines along the model's edges and window edges are clear and detailed, demonstrating the model's precision and design accuracy. Furthermore, the target core model is made of silicon steel sheets. Overall, this model represents a typical transformer core design used for evaluating its performance in electromagnetic simulations.

[0088] Step S04: Establish a three-dimensional model of the coil based on the coil structure parameters, wherein the three-dimensional model of the coil is based on the properties of copper material.

[0089] It should be noted that the coil 3D model is a digital model constructed using geometric modeling tools based on the coil's structural parameters, which can fully represent the geometric shape, size, and spatial position of the transformer coil.

[0090] It should be understood that copper material properties refer to the physical characteristics of copper, mainly including electrical conductivity, thermal conductivity, density, specific heat capacity, and resistivity. Copper has excellent electrical and thermal conductivity and is widely used in transformer coils. Assigning copper material properties to the three-dimensional model of the coil enables the model to accurately reflect the electrical and thermal conductivity characteristics of the actual coil, ensuring accurate calculation of copper losses and heat dissipation in subsequent electromagnetic simulation calculations.

[0091] Understandably, coil structural parameters, such as inner and outer diameters, reactance height, and distance to the lower yoke of the core, are imported into a geometric modeling tool. The radial cross-sectional dimensions of the coil are determined based on its inner and outer diameters, its axial length is determined based on the reactance height, and its position in space is determined by its distance to the lower yoke of the core, ensuring that the coil model accurately matches the subsequent target core model. A cylindrical toroidal coil geometric model that meets these parameter requirements is constructed using the modeling tool. After the geometric model is completed, copper material properties are assigned to the coil model in the modeling tool, setting corresponding parameters such as conductivity, thermal conductivity, and resistivity, so that the coil model possesses the physical characteristics of an actual copper coil. The resulting model is the three-dimensional model of the coil.

[0092] Figure 3 A schematic diagram of a three-dimensional coil model in the temperature rise prediction method for transformer structural components provided in the embodiments of this application.

[0093] like Figure 3As shown, the model is a 3D coil model. The background is a grid-like coordinate system, composed of horizontal and vertical lines forming a 2D plane to indicate the model's position on that plane. The model's shape consists of multiple stacked cylindrical layers. This layered structure demonstrates the complexity and precision of the coil; each layer is tightly arranged to form a complete cylindrical structure, used to evaluate the coil's performance in transformers or other electromagnetic devices. Furthermore, the 3D coil model represents the material properties of copper.

[0094] Step S05: Based on the transformer design parameters, perform data matching in the preset design principle database to obtain the structural component design parameters, and establish a three-dimensional model of the structural component based on the structural component design parameters.

[0095] It should be noted that the preset design principle database is a pre-established data set that stores the design rules and parameter matching relationships of various structural components of the transformer. This database contains design principles such as the standard shape, size range, and position requirements of structural components such as webs, limbs, tie plates, lung-shaped magnetic shielding, tank magnetic shielding, and tanks corresponding to different rated capacities, voltage levels, and core types. It can automatically match the structural component design parameters that conform to the design specifications based on the input transformer design parameters.

[0096] Furthermore, structural component design parameters are detailed data used to construct the three-dimensional models of each structural component of the transformer, and they vary for different structural components. For example, web structure design parameters include web length, thickness, height, vertical position, and web spacing; leg plate structure design parameters include leg length, width, and distance from the center of the transformer body; tie plate structure design parameters include tie plate length, width, thickness, slot position, and slot width; lung lobe magnetic shielding structure design parameters include large circle radius, small circle radius, distance from the centerline of the transformer body, and vertical position; tank magnetic shielding structure design parameters include length, width, thickness, position, and quantity; and tank structure design parameters include tank shape, length, width, and height.

[0097] Furthermore, the 3D model of the structural components is a digital model constructed based on the design parameters of the structural components, reflecting the shape, size, and position of other key structural components of the transformer besides the core and coils. It mainly includes models of structural components such as the tank, web, limb plates, tie plates, lung-shaped magnetic shielding, and tank magnetic shielding. These models, together with the target core model and the 3D model of the coils, form a complete 3D model of the power transformer, which is an important component in simulating the overall structure and operating state of the transformer.

[0098] Understandably, transformer design parameters, such as rated capacity, voltage level, and core type, are input into a pre-defined design principle database. Based on these input parameters, the database automatically matches the corresponding design parameters for each structural component according to pre-stored design rules and parameter matching relationships. For example, if the input is the rated capacity and core type of a 110kV three-phase three-limb transformer, the database will match the corresponding parameters for that type of transformer, including web length, thickness, and height; leg length and distance from the transformer body center; tie plate slot position and width; lung lobe magnetic shield radius; tank magnetic shield quantity; and tank length, width, and height. After obtaining the structural component design parameters, a geometric modeling tool is used to construct corresponding 3D models for each component. For instance, a 3D model of the tank is constructed based on its shape and dimensions; a 3D model of the web is constructed based on its length, thickness, height, and position; similarly, 3D models of the leg plates, tie plates, lung lobe magnetic shield, and tank magnetic shield are constructed, ultimately forming a complete set of 3D models for the structural components.

[0099] Reference Figure 4 , Figure 4 This is a schematic diagram of a three-dimensional model of a transformer structural component provided in Embodiment 1 of the temperature rise prediction method for this application.

[0100] like Figure 4 As shown, the 3D model is primarily composed of green and brown colors. The green areas represent the main material of the structural components, while the brown areas represent another material or component. The model background is a grid, and the coordinate system in the diagram consists of three arrows labeled X, Y, and Z, representing the three coordinate axes in 3D space and indicating the model's position and orientation. The model is shaped like a cuboid structure, containing multiple vertical and horizontal structures used to enhance the stability of the core. The bottom and top of the model feature horizontal green structures representing the transformer's clamps, while the brown plate-like structure in the middle represents the transformer's tie plates.

[0101] Step S20: Perform electromagnetic simulation calculations on the three-dimensional model of the power transformer to obtain the losses of the transformer structural components.

[0102] It should be understood that electromagnetic simulation calculation is the process of using electromagnetic simulation software to simulate the electromagnetic environment of a power transformer during operation, based on a pre-constructed three-dimensional model of the transformer, and to analyze the electromagnetic field distribution and related electromagnetic characteristics. During the testing process, parameters such as boundary conditions, current excitation, mesh generation method, and solution conditions need to be set to simulate the electromagnetic state of the transformer during actual operation, thereby obtaining the relevant physical quantities of the structural components under electromagnetic influence.

[0103] Furthermore, transformer structural component losses refer to the energy losses generated by electromagnetic phenomena such as electromagnetic induction and eddy current effects in various structural components during transformer operation. These losses mainly include core losses, coil losses, and losses caused by eddy currents in structural components such as the tank, web, limb plates, and tie plates. The magnitude of these losses is closely related to the material properties, shape, size, and electromagnetic environment of the structural components, and is an important basis for subsequent temperature field calculations.

[0104] Understandably, the pre-built 3D model of the power transformer is imported into the electromagnetic simulation software, and then a series of parameters are set. First, boundary conditions are set. For structural components with obvious skin effect, such as tank walls and tie plates, surface impedance boundary conditions are assigned to accurately simulate the physical phenomenon of current concentration on the surface of these structural components. Current excitation is set. Current excitation is set at the coil cross-section. The excitation magnitude is the product of the rated current and the number of coil turns. The type is set to stranded, and the current phases of the three-phase coils are 120 degrees apart to simulate the three-phase current state when the transformer is actually running.

[0105] Next, the mesh generation is set. Based on the complexity of the shape of each structural component and the accuracy requirements of electromagnetic analysis, an appropriate mesh type is selected, such as a tetrahedral mesh or a hexahedral mesh, and the mesh size is determined. For areas with complex shapes and drastic electromagnetic changes, such as the edges, corners, and areas near the coils of structural components, a smaller mesh size is used for densification. For areas with regular shapes and gentle electromagnetic changes, the mesh size is appropriately increased to improve computational efficiency while ensuring accuracy. Finally, the solution conditions are set, including parameters such as the maximum number of iterations, error percentage, and frequency. After the parameter settings are completed, the electromagnetic simulation software is started to solve the problem. After the simulation is completed, the loss data of each structural component will be output, thus obtaining the loss of the transformer structural components.

[0106] In one feasible implementation, step S20 may include steps S21 to S25:

[0107] Step S21: In the three-dimensional model of the power transformer, determine the concentrated current structure, the mesh generation structure, the preset mesh generation rules, and the preset solution conditions.

[0108] It should be noted that concentrated current structural components refer to those components in which the current mainly flows on the surface during transformer operation due to the alternating electromagnetic field. These components exhibit a significant skin effect; the current is not uniformly distributed across the entire cross-section but rather concentrated within a certain depth range on the surface. Common concentrated current structural components include tank walls and tie plates. Their current distribution characteristics directly affect the accuracy of boundary condition settings and loss calculations in electromagnetic simulations.

[0109] Additionally, meshed structural components refer to critical structural components that require mesh generation before electromagnetic simulation. These components significantly impact the accuracy of the simulation results and typically include fuel tanks, webs, limb plates, and tension plates. Meshing these components involves discretizing their geometric models into multiple small mesh elements so that the electromagnetic simulation software can perform numerical calculations based on these elements. The quality and density of the mesh directly affect the accuracy and efficiency of the simulation calculations.

[0110] Additionally, the preset mesh generation rules are pre-defined standards and requirements used to guide the mesh generation of structural components. These rules determine the mesh type and size based on the complexity of the structural component's shape and the intensity of its electromagnetic variations. For example, for regions with complex shapes and intense electromagnetic variations, such as the edges, corners, and areas near coils, the rules require a smaller mesh size for finer meshing. For regions with regular shapes and relatively gentle electromagnetic variations, the rules allow for a slightly larger mesh size to improve computational efficiency while maintaining simulation accuracy.

[0111] Furthermore, the preset solution conditions are pre-defined parameter settings used in the electromagnetic simulation solution process, mainly including the maximum number of iterations, the percentage error, and the adaptive frequency. The maximum number of iterations limits the number of calculation loops in the solution process to avoid excessive computation time due to too many iterations; the percentage error sets the accuracy requirement for the solution results, and the solution is considered converged when the error of the calculation result is less than this percentage; the frequency needs to be set according to the actual operating frequency of the transformer to simulate the electromagnetic environment of the transformer under real operating conditions.

[0112] Step S22: Set surface impedance boundary conditions on the concentrated current structure.

[0113] It should be noted that the surface impedance boundary condition is a boundary setting method used in electromagnetic simulation, suitable for conductor structures with significant skin effects. This condition transforms the solution of the electromagnetic field inside the conductor into the solution of the electromagnetic field on the conductor surface, ignoring the details of the current distribution inside the conductor and only considering the current concentration effect on the surface, thus simplifying the calculation process while ensuring calculation accuracy. When setting this condition, the surface impedance value needs to be calculated based on the conductor's material properties such as resistivity and permeability, and the simulation frequency, and then this value is assigned to the surface of the structure to simulate the physical phenomenon of current concentrating on the surface of the structure.

[0114] Understandably, based on the material properties of condensed current structural components, such as tank walls and pull plates, including the resistivity and permeability of the materials; and based on the frequency in the preset solution conditions, combined with the resistivity and permeability of the materials, the surface impedance values ​​of these condensed current structural components are calculated using relevant physical principles; then, in the electromagnetic simulation software, the surface area of ​​each condensed current structural component is selected, and the calculated surface impedance values ​​are input into the boundary condition setting interface to assign surface impedance boundary conditions to these structural components; after the settings are completed, the simulation software will simulate the concentrated flow state of current on the surface of the condensed current structural component based on the boundary conditions in subsequent calculations, without the need to perform detailed electromagnetic field calculations inside the structural components, thus ensuring accurate simulation of the skin effect and simplifying the calculation process.

[0115] Step S23: Set current excitation conditions at the coil cross-section of the three-dimensional model of the power transformer.

[0116] It should be noted that the coil cross-section refers to the annular region that the coil presents on a plane perpendicular to its axis.

[0117] Furthermore, current excitation conditions refer to the parameter settings for simulating the actual operating current input applied to the coil in electromagnetic simulation. These mainly include current magnitude, current type, and current phase. The current magnitude needs to be determined based on the transformer's rated current and the number of coil turns. The current type is usually set to stranded to simulate the actual coil's conductor structure. The current phase needs to be set according to the transformer's three-phase connection method to simulate the real three-phase current operating environment.

[0118] Understandably, in the 3D model of the power transformer, the cross-sectional area of ​​the coil is located, which is the annular surface of the coil perpendicular to the axial direction. Next, the magnitude of the current excitation is determined based on the transformer's design parameters, calculated by multiplying the transformer's rated current by the number of coil turns, ensuring that the excitation current can simulate the current load of the coil during actual operation. Then, the current type is selected and set to stranded, which more accurately simulates the actual coil structure composed of multiple stranded wires, avoiding calculation errors caused by the skin effect. Finally, based on the operating characteristics of the three-phase transformer, the phases of the current excitation for the three-phase coils are set separately, with the current phases of the three-phase coils differing by 120 degrees to simulate the phase relationship of the three-phase currents during actual transformer operation. After completing all parameter settings, the current excitation conditions are saved in the electromagnetic simulation software to provide current input simulation for subsequent electromagnetic simulation calculations.

[0119] Step S24: The meshing structure is meshed according to the preset meshing rules to obtain the target electromagnetic meshing model.

[0120] It should be noted that the target electromagnetic meshing model refers to the three-dimensional model of a power transformer containing discrete mesh elements obtained after meshing the structural components according to preset meshing rules. In this model, the meshed structural components have been decomposed into multiple small mesh elements, each with clear geometric coordinates and material properties, which can be recognized by electromagnetic simulation software and used for numerical calculations. It is the basic model for solving electromagnetic simulations.

[0121] Understandably, the process involves importing a 3D model of a power transformer into electromagnetic simulation software, selecting specific meshing components such as the tank, web, limb plates, and tension plates, and then calling preset meshing rules. Based on the rules' requirements for mesh type and size in different regions, appropriate mesh types are selected for each meshing component, such as tetrahedral or hexahedral meshes. For edges, corners, and areas near coils where electromagnetic changes are drastic, smaller mesh sizes are used for finer meshing to accurately capture the details of electromagnetic field changes. For areas with more regular shapes and relatively gentle electromagnetic changes, the mesh size is appropriately increased to reduce the number of computational units and computational load. After meshing, the mesh quality of each component is checked to ensure no distorted meshes affect computational accuracy, ultimately forming a target electromagnetic meshing model containing discrete mesh units.

[0122] Step S25: Perform electromagnetic simulation calculations on the target electromagnetic partitioning model to obtain the losses of the transformer structural components.

[0123] Understandably, the target electromagnetic partitioning model is loaded into the electromagnetic simulation software, and the set surface impedance boundary conditions and current excitation conditions are confirmed to be correctly associated with the model. Then, the preset solution conditions are called, and parameters such as the maximum number of iterations, error percentage, and frequency are input into the solution settings interface of the simulation software. After the simulation software is started, it will perform electromagnetic field numerical calculations based on the mesh elements of the target electromagnetic partitioning model and according to the preset solution conditions. During the calculation process, the software will simulate the flow state of current in each structural component, analyze the distribution law of electromagnetic field, and calculate the loss of each structural component due to electromagnetic action based on the material properties and electromagnetic characteristics of the structural components. When the simulation calculation reaches the preset maximum number of iterations or the error is less than the set error percentage, the solution process stops, and the simulation software will automatically output the loss data of each structural component, that is, obtain the transformer structural component loss.

[0124] Step S30: Solve the temperature field based on the losses of the transformer structural components to obtain the initial temperature rise result.

[0125] It should be understood that temperature field solution refers to the process of using temperature simulation software, combined with structural component loss data, to simulate the temperature distribution of each structural component during transformer operation, and to calculate the temperature change and final temperature value of the structural components.

[0126] It should be noted that the initial temperature rise result refers to the temperature rise value of each structural component of the transformer under specific operating conditions, obtained through temperature field calculation. This result reflects the temperature rise of each structural component under the current structural parameters and operating conditions.

[0127] Understandably, the transformer structural component loss data is imported into the temperature simulation software, and then the parameters are set. First, the heat source is set by importing the structural component loss surface density calculated from the electromagnetic field simulation into the temperature simulation model, ensuring the heat source distribution matches the structural component loss distribution to accurately simulate the heat generation source. Next, heat transfer parameters are set, including the thermal conductivity, convective heat transfer coefficient, and emissivity of each structural component material. Different materials have different thermal conductivity; for example, the thermal conductivity of silicon steel sheets, copper, and transformer oil needs to be set separately based on their actual physical properties. The convective heat transfer coefficient is determined based on the cooling method, such as natural or forced convection, and the flow state of the cooling medium. The emissivity also needs to be set based on the material surface characteristics to accurately simulate the heat conduction within the structural components and the convective and radiative heat transfer processes with the surrounding medium.

[0128] Next, mesh generation is performed for key structural components such as the fuel tank, web, limb plates, and tension plates. The mesh generation should be consistent with or have good compatibility with the mesh generation in the electromagnetic simulation to ensure that the electromagnetic loss heat source can be accurately mapped into the temperature field model. At the same time, the mesh size is adjusted according to the degree of temperature change. Small mesh size is used for denser meshing in areas with large temperature changes, such as hot spots, areas in direct contact with heat sources, and interfaces between different materials. The mesh size is appropriately increased in areas with uniform temperature distribution. After the parameter settings are completed, the temperature simulation software is started to solve the temperature field. After the solution is completed, the software will output the temperature distribution data of each structural component and calculate the difference between the temperature of each structural component and the ambient temperature to obtain the initial temperature rise result.

[0129] In one feasible implementation, step S30 may include steps S31 to S34:

[0130] Step S31: Obtain the preset temperature field mesh division rules.

[0131] It should be noted that the preset temperature field mesh generation rules are pre-defined standards and requirements used to guide the mesh generation of structural components in the 3D model of power transformers for temperature field simulation. These rules determine the mesh type and size based on the temperature field distribution characteristics, the geometry of the structural components, and the required simulation accuracy. For example, for areas with drastic temperature changes, such as hot spots on structural components, areas in direct contact with heat sources, and interfaces between different materials, the rules require a smaller mesh size for finer meshing to accurately capture temperature gradient changes. For areas with relatively uniform temperature distribution, such as regularly shaped structural components far from heat sources, the rules allow for a slightly larger mesh size to reduce computational load while maintaining simulation accuracy.

[0132] Step S32: Set the heat transfer parameters according to the losses of the transformer structural components.

[0133] It should be noted that heat transfer parameters are physical parameters used to describe the heat transfer characteristics of various structural components and cooling media in a transformer. These mainly include the thermal conductivity, convective heat transfer coefficient, and emissivity of the materials. Thermal conductivity reflects the ability of a material to conduct heat internally; different materials have different thermal conductivity values, such as silicon steel sheets, copper, and transformer oil, each with its own specific values. Convective heat transfer coefficient reflects the ability of the structural component surface to exchange heat with the surrounding fluid, such as transformer oil; its value varies depending on the cooling method, such as natural or forced convection, and the fluid flow state. Emissivity reflects the ability of the structural component surface to transfer heat through thermal radiation; it is related to material surface characteristics such as roughness and color. These parameters collectively determine the efficiency and path of heat transfer inside the transformer and are key input parameters for solving the temperature field.

[0134] Understandably, the process involves analyzing the distribution and magnitude of losses in each structural component to identify areas of concentrated heat sources. Next, for different structural components and cooling media, thermal conductivity is set based on their material properties. For example, the thermal conductivity of silicon steel sheets is set for the core model, copper for the coil model, and transformer oil for the cooling area. For structural components with high losses and concentrated heat, the accuracy of their material thermal conductivity is reconfirmed to ensure consistency with actual material properties. Convective heat transfer coefficients are set according to the cooling method and fluid flow state. If the transformer uses natural convection cooling and the fluid flow around the loss concentration area is slow, a relatively low convective heat transfer coefficient is set; if forced convection cooling is used or the fluid flow in the loss concentration area is fast, a relatively high convective heat transfer coefficient is set. Finally, emissivity is set based on the surface characteristics of each structural component. For example, the surface emissivity of metallic structural components is set according to their surface treatment method, such as plating or exposure. After setting all heat transfer parameters, the parameters are associated with the corresponding structural components in the 3D model of the power transformer to ensure accurate retrieval of heat transfer parameters for each region during subsequent temperature field calculations.

[0135] Step S33: Mesh the structural components in the three-dimensional model of the power transformer according to the preset temperature field meshing rules to obtain the target temperature meshing model.

[0136] It should be noted that the target temperature meshing model refers to the model formed after the meshing structure in the three-dimensional model of the power transformer is meshed according to the preset temperature field meshing rules, and can be used for temperature field solving.

[0137] Understandably, in temperature field simulation software, a 3D model of a power transformer is loaded, and the meshing structural components in the model, such as the tank, web, limb plates, and tension plates, are selected. Then, the pre-defined temperature field meshing rules are called, and meshing is performed according to the requirements of the rules for different regions. For regions with drastic temperature changes, such as hot spots of structural components, areas in direct contact with heat sources, and interfaces between different materials, a smaller mesh size is used for densification according to the rules. For example, the mesh size is set to a small value to accurately capture subtle temperature changes. For regions with relatively uniform temperature distribution, such as structural components with regular shapes and far from heat sources, the mesh size is appropriately increased according to the rules to reduce the number of mesh elements and reduce the computational load.

[0138] Step S34: Solve the temperature field of the target temperature division model according to the heat transfer parameters to obtain the initial temperature rise result.

[0139] Understandably, the target temperature partitioning model is loaded into the temperature field simulation software, and the determined heat transfer parameters, including the thermal conductivity, convective heat transfer coefficient, and emissivity of each structural component and cooling medium, are accurately associated with the corresponding grid cells or structural component regions of the model. The transformer structural component loss data is used as the heat source, and the loss surface density is accurately distributed to each grid cell of the target temperature partitioning model according to the correspondence of the grid cells, ensuring that the heat source distribution is consistent with the actual loss distribution. Then, relevant parameters for temperature field solving are set, such as the solution time step and convergence criteria, and the simulation software is started to solve the temperature field. During the solution process, the software calculates the heat conduction, convection, and radiation exchange processes of each grid cell based on the heat transfer parameters and heat source distribution, iteratively updating the temperature values ​​of each cell until the calculation results meet the convergence criteria, i.e., the temperature difference between two adjacent iterations is less than a set threshold. After the solution is completed, the software outputs the temperature value of each grid cell for each structural component. Subtracting the ambient temperature from the temperature value of each structural component yields the temperature rise value of each structural component, i.e., the initial temperature rise result.

[0140] Step S40: Obtain the temperature rise determination result based on the initial temperature rise result and the preset temperature rise threshold, and determine the target temperature rise result based on the temperature rise determination result to complete the temperature rise prediction of the transformer structural components.

[0141] It should be noted that the temperature rise judgment result is a conclusion drawn from comparing the initial temperature rise result with the preset temperature rise threshold to determine whether the temperature rise of each structural component of the transformer meets the requirements. If the initial temperature rise result of all structural components is less than or equal to the preset temperature rise threshold, the judgment result is that the temperature rise is qualified; if the initial temperature rise result of some structural components is greater than the preset temperature rise threshold, the judgment result is that the temperature rise is unqualified.

[0142] Furthermore, the target temperature rise result is determined based on the temperature rise judgment result and is ultimately used to characterize the temperature rise state of the transformer structural components. If the temperature rise judgment result is qualified, the target temperature rise result is the initial temperature rise result; if the temperature rise judgment result is unqualified, the transformer structural parameters need to be optimized and adjusted, and the temperature rise prediction needs to be carried out again until a temperature rise result that meets the preset temperature rise threshold requirement is obtained. This qualified temperature rise result is the target temperature rise result.

[0143] In one feasible implementation, steps S50 to S80 may be included after step S40:

[0144] Step S50: Determine the target cloud map components, simulation parameters, and simulation results based on the target temperature rise results.

[0145] It should be noted that the target cloud map component is a set of key elements used to generate temperature cloud maps, including transformer structural objects such as tanks, pull plates, and webs that need to display temperature distribution.

[0146] In addition, simulation parameters are various key calculation parameters set throughout the temperature rise prediction process, including boundary conditions such as surface impedance boundary conditions, current excitation magnitude and phase, mesh generation rules, maximum number of iterations, error percentage, and frequency in the electromagnetic simulation stage, as well as heat transfer parameters such as thermal conductivity, convective heat transfer coefficient, emissivity, mesh generation rules, and solution convergence criteria in the temperature field solution stage.

[0147] In addition, the simulation results are various data results obtained through simulation calculations during the temperature rise prediction process. In addition to the target temperature rise result, it also includes transformer structural component loss data such as core loss, coil loss, and tank eddy current loss during the electromagnetic simulation stage, electromagnetic field distribution data, and original data of temperature distribution of each structural component, hot spot temperature location and value during the temperature field solution stage.

[0148] Step S60: Generate a target display cloud map based on the target cloud map component.

[0149] Understandably, the target display cloud map is a graphical representation of the temperature distribution of various structural components of a transformer, generated based on the target cloud map component and displayed using an intuitive color gradient. Different colors in the cloud map represent different temperature ranges, clearly showing the temperature differences on the surface of the structural components. This helps relevant personnel quickly identify hot temperature areas and temperature change trends.

[0150] Understandably, the process of generating a target display cloud map based on the target cloud map component involves the following steps: First, a temperature cloud map generation tool is invoked, and the target cloud map component is imported into the tool, including the selected structural component object data, color mapping rules, and display perspective parameters. Next, the tool reads the temperature distribution data of the corresponding structural component from the target temperature rise result, associates the data with the three-dimensional geometric model of the structural component, ensuring that each location on the surface of the structural component corresponds to a unique temperature value. Following the set color mapping rules, areas with different temperature values ​​on the surface of the structural component are assigned corresponding colors, and color legends are generated to indicate the temperature range corresponding to each color. Then, based on the set display perspective, the display angle of the structural component model is adjusted. For example, the overall view displays the temperature rise distribution of all key structural components from directly in front of or diagonally above the transformer, while the close-up view focuses on and magnifies the hot spots in the tank or pull plate. Finally, the generated cloud map is rendered to ensure natural color transitions and clear temperature boundaries, forming a target display cloud map that intuitively reflects the temperature distribution of the structural components.

[0151] Figure 5 This is a target display cloud diagram provided for Embodiment 1 of the temperature rise prediction method for transformer structural components in this application.

[0152] like Figure 5 As shown, the target cloud map's color gradient transitions from blue to red, representing the temperature change from low to high. The color bar, located on the left side of the graph, clearly indicates the temperature range corresponding to different colors, in degrees Celsius (°C). The color bar gradually transitions from dark blue at the bottom (representing the lowest temperature of 0.0019045°C) to red at the top (representing the highest temperature of 16.334°C). The model's shape shows the geometric features of the structural component, with red areas representing higher-temperature regions, which are hotspots, and blue areas representing lower-temperature regions. The graph also includes textual information, showing the model type as "Temperature" (in degrees Celsius (°C), the simulation time "Time 1s," and the maximum and minimum temperatures (Max 16.334, Min 0.0019045). Furthermore, the graph also indicates the locations of the highest and lowest temperatures in the model, respectively. This type of 3D model is typically used to analyze the temperature distribution of structural components under specific conditions to evaluate their thermal performance.

[0153] Step S70: Generate a simulation report based on the simulation parameters and simulation results.

[0154] It should be noted that the simulation report is a document formed after systematically organizing the entire process of temperature rise prediction for transformer structural components, parameter settings, and result data. The report should include basic transformer design information, detailed simulation parameters, simulation result data, result analysis, and conclusions and recommendations. It is characterized by standardized format and complete content, and is an important document for recording the temperature rise prediction process, presenting prediction results, and supporting design decisions. It can be used for design archiving, engineering review, or technical exchange.

[0155] Understandably, the report summarizes the conclusions of the entire analysis process, evaluates the temperature rise performance of the transformer structural components, provides a clear conclusion on whether it meets the protocol requirements, and proposes recommendations for transformer design and operation. Users only need to click the one-click generate button, and the system can automatically generate a standardized and complete analysis report based on the above content, improving work efficiency and report standardization.

[0156] Determine the fixed format and content framework of the simulation report, including the report title, table of contents, basic transformer information section, simulation parameters section, simulation results section, results analysis section, conclusions and recommendations section, etc.; then, in the basic transformer information section, fill in the transformer's rated capacity, voltage level, core type such as three-phase three-limb or three-phase five-limb design parameters, which are extracted from the initially obtained transformer design parameters.

[0157] In the simulation parameters section, the simulation parameters are categorized and filled in according to the two stages of electromagnetic simulation and temperature field solution. Electromagnetic simulation parameters include boundary condition settings such as the surface impedance value of concentrated current structural components, current excitation magnitude and phase, mesh generation rules such as mesh size of different regions, maximum number of iterations, error percentage, and frequency. Temperature field solution parameters include the thermal conductivity of each material, convective heat transfer coefficient, emissivity, mesh generation rules, and solution convergence criteria, ensuring that each parameter has a clear value and description.

[0158] In the simulation results section, summarize and fill in the confirmed simulation results, including the specific values ​​of loss data for each structural component, such as core loss, coil loss, and tank eddy current loss; the target temperature rise results for each structural component; and the hot spot temperature, along with a table of key temperature distribution data. In the results analysis section, analyze whether the temperature rise of each structural component meets the requirements based on the preset temperature rise threshold. If optimization is required, explain the reasons for optimization, such as the initial temperature rise of a certain structural component exceeding the standard, optimization measures such as adding strip magnetic shielding to the tank, and a comparison of results before and after optimization. Finally, in the conclusions and recommendations section, clearly state the overall conclusion of the temperature rise prediction, such as the temperature rise of all structural components meeting the preset threshold requirements, and provide recommendations for transformer design or operation, such as suggesting attention to the heat dissipation design of a certain hot spot area. After completing all the content, format the report to ensure that the font, line spacing, and chart positions are consistent and standardized, and generate a complete simulation report.

[0159] Step S80: Visualize the temperature rise prediction based on the target cloud map and simulation report.

[0160] It should be understood that the visualization of temperature rise forecasts is the process of presenting target cloud maps and key information from simulation reports in a graphical and intuitive way. This process is not limited to simply displaying cloud maps or report text; rather, through a well-designed layout, it integrates cloud maps and core data from the report, such as hotspot temperatures, key loss values, conclusions, and recommendations, enabling viewers to quickly and comprehensively understand the results and core information of the temperature rise forecast. Common presentation formats include screen visualizations or a combination of text and graphics in printed documents.

[0161] Understandably, the visualization format needs to be determined, such as screen display or printed display. If screen display is chosen, appropriate display software or platform should be selected. Next, key information from the target display cloud map and simulation report needs to be filtered and integrated. Core content should be extracted from the simulation report, including basic transformer information such as rated capacity, voltage level, target temperature rise results for each structural component (especially hotspot temperature values), and whether the simulation conclusions meet preset threshold requirements. From the target display cloud map, the cloud map that best reflects the key temperature rise situation should be selected, such as the overall structural temperature rise cloud map and close-up cloud maps of hotspot areas. This allows relevant viewers to quickly grasp the temperature rise distribution of transformer structural components, core temperature rise data, and whether it meets design requirements, thus completing the visual presentation of temperature rise prediction.

[0162] This embodiment provides a method for predicting the temperature rise of transformer structural components. By constructing a detailed three-dimensional model of the power transformer, performing accurate electromagnetic simulation calculations, and solving the temperature field, it solves the technical problem of insufficient calculation accuracy in predicting the temperature rise of transformer structural components using traditional methods. This method achieves the beneficial effects of improving the accuracy of temperature rise analysis, realizing automated modeling and simulation, optimizing structural parameters to improve transformer performance, reducing experimental costs and development cycles, and enhancing design flexibility and scalability.

[0163] Based on the first embodiment of this application, in the second embodiment of this application, the content that is the same as or similar to that in the first embodiment described above can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 6 Step S40 of the method for predicting the temperature rise of transformer structural components includes steps S41 to S43:

[0164] Step S41: When the initial temperature rise result is greater than the preset temperature rise threshold, determine the model of the component to be optimized based on the initial temperature rise result, and optimize the model of the component to be optimized to obtain the optimized model.

[0165] It should be noted that the component model to be optimized refers to the 3D model of the structural component whose initial temperature rise is greater than the preset temperature rise threshold. In other words, it is the structural component model whose temperature rise needs to be reduced by adjusting its structural parameters. The determination of the component model to be optimized must be based on the comparison between the initial temperature rise and the preset threshold.

[0166] It should be understood that model optimization refers to the process of adjusting and modifying the structural parameters of the component model to reduce its temperature rise. The optimization method needs to be determined based on the type of component to be optimized and the cause of excessive temperature rise. For example, for a fuel tank model, optimization can be achieved by adding strip magnetic shielding to the surface of the fuel tank; for a pull plate model, optimization can be achieved by slotting the pull plate; for a clamping component model, optimization can be achieved by changing the material to low-magnetic steel or non-magnetic steel, or by adding lung-shaped magnetic shielding. The core objective of model optimization is to ensure that the temperature rise of the optimized structural component meets the preset threshold requirements.

[0167] Furthermore, the optimized model is a new three-dimensional model of the structural component obtained by adjusting the structural parameters of the component model to be optimized. This model retains the basic functions and assembly relationships of the original model, but the key structural parameters have been modified according to the optimization requirements.

[0168] Understandably, based on the comparison between the initial temperature rise and the preset temperature rise threshold, structural components with initial temperature rise exceeding the preset threshold are selected, and their corresponding 3D models are identified as component models to be optimized. For each component model to be optimized, a corresponding optimization scheme is formulated and implemented: For the fuel tank component model, since its excessive temperature rise may be due to excessive eddy current losses, strip magnetic shielding is added to the surface of the fuel tank. The length, width, thickness, and distribution of the magnetic shielding are determined, and these strip magnetic shielding structures are constructed based on the original fuel tank model to complete the optimization of the fuel tank model; For the pull plate component model, since its excessive temperature rise may be due to current concentration, the pull plate model is slotted. The location, width, and depth of the slots are determined, and slots of corresponding dimensions are created on the original pull plate model using geometric modeling tools to complete the optimization of the pull plate model. If there are other component models to be optimized, such as clamp models, optimization can be carried out by changing the material to low-magnetic steel or non-magnetic steel, or by adding lung lobe magnetic shielding, depending on the reason for the excessive temperature rise. Finally, the optimized models corresponding to all component models to be optimized are obtained.

[0169] In one feasible implementation, step S41 may include steps S411 to S413:

[0170] Step S411: When the initial temperature rise result is greater than the preset temperature rise threshold, determine the model of the component to be optimized based on the initial temperature rise result.

[0171] Understandably, the initial temperature rise results are compared one by one with the preset temperature rise thresholds. The comparison covers all key structural components in the 3D model of the power transformer, including the core, coils, tank, web, limb plates, tie plates, ferrule magnetic shielding, and tank magnetic shielding. For each component, its initial temperature rise result is checked to see if it exceeds the corresponding preset temperature rise threshold. If the initial temperature rise result of one or more components is found to be greater than its corresponding preset temperature rise threshold, it indicates that these components have an overheating risk, and the current structural parameters cannot meet the temperature rise requirements. The 3D models corresponding to these components that exceed the threshold need to be marked as models to be optimized. For example, the tank model and tie plate model with excessive initial temperature rise are identified as models to be optimized, providing clear optimization targets for subsequent optimization scheme development.

[0172] Step S412: Determine the target optimization scheme based on the model of the component to be optimized, wherein the target optimization scheme includes the target optimization material and / or the target optimization strategy.

[0173] It should be noted that the target optimization scheme is a model of the component to be optimized, and a targeted solution that includes material adjustments and / or structural adjustments to ensure that its temperature rise meets the preset threshold requirements. Its core is to select an appropriate method, either material replacement or structural modification, or a combination of both, based on the type of component to be optimized and the root cause of the excessive temperature rise, to reduce the component's temperature rise.

[0174] Furthermore, the target optimization material refers to a novel material selected to replace the original material and reduce temperature rise in the model of the component to be optimized, addressing the issue of excessive temperature rise. These materials typically possess physical properties such as magnetic permeability, resistivity, and thermal conductivity that are better suited to the operational requirements of the component to be optimized. For example, if a clamping component model experiences excessive temperature rise due to high magnetic loss, the target optimization material could be low-magnetic or non-magnetic steel. These materials have lower magnetic permeability, effectively reducing magnetic loss and thus lowering temperature rise. Similarly, if a structural component experiences heat accumulation due to poor thermal conductivity, the target optimization material could be a metal material with higher thermal conductivity to improve heat dissipation efficiency.

[0175] Another type of target optimization strategy refers to a specific plan to adjust the structural layout and shape of the component model to reduce temperature rise based on its structural characteristics and the reasons for excessive temperature rise. This approach does not require material replacement; temperature rise can be improved simply by changing structural parameters. Common target optimization strategies include adding magnetic shielding to the surface of structural components and slotting the components. For example, when the temperature rise of a fuel tank model exceeds the limit, the target optimization strategy could be to add strip magnetic shielding to the surface of the fuel tank. This magnetic shielding alters the electromagnetic field distribution and reduces eddy current losses in the tank wall. Similarly, when the temperature rise of a pull plate model exceeds the limit, the target optimization strategy could be to slot the pull plate. This slotting alters the current path, reduces current concentration, and decreases localized losses and temperature rise.

[0176] Understandably, by analyzing the type, structural characteristics, and core causes of excessive temperature rise in the model of the component to be optimized, and combining transformer design principles and engineering practice experience, a suitable optimization scheme is formulated. If the model of the component to be optimized is a clamping component model, and analysis shows that its excessive temperature rise is due to the high magnetic permeability of the original material leading to excessive magnetic loss, then the target optimization material is determined to be low-magnetic steel or non-magnetic steel. By replacing the material, magnetic loss is reduced to control the temperature rise. If the model of the component to be optimized is an oil tank model, and analysis shows that its excessive temperature rise originates from a large amount of eddy current loss generated on the oil tank wall under the action of alternating electromagnetic field, then the target optimization strategy is determined to be to add a strip magnetic shield on the surface of the oil tank to block part of the magnetic field and reduce eddy current generation. If the model of the component to be optimized is a pull plate model, the excessive temperature rise is due to the current in the pull plate area. Concentration leads to excessive local losses. In this case, the target optimization strategy is to slot the tie plate to disperse the current and reduce the local current density and losses. If the model of the component to be optimized has multiple causes of excessive temperature rise, or the effect of a single optimization method is limited, the target optimization material and target optimization strategy can be determined at the same time. For example, if a structural component has both excessive material loss and poor heat dissipation caused by its structure, it can be replaced with a target optimization material with low loss and high thermal conductivity. At the same time, the target optimization strategy of adjusting the structural shape can be adopted. The dual measures ensure that the temperature rise is reduced to within the threshold range.

[0177] Step S413: Optimize the model of the component to be optimized according to the target optimization scheme to obtain the optimized model.

[0178] Understandably, based on the determined target optimization scheme, i.e., the target optimization material and / or the target optimization strategy, specific optimization operations are performed on the model of the component to be optimized. If the determined optimization scheme is to use the target optimization material, for example, if the component model to be optimized is a clamping model and the target optimization material is low-magnetic steel, then in the 3D modeling tool, the original material properties of the clamping model are replaced with the material properties of low-magnetic steel, including updating parameters such as magnetic permeability, resistivity, and thermal conductivity, to ensure that the model's material properties are consistent with the target optimization material. The clamping model after the material replacement is the optimized model.

[0179] If the determined optimization scheme adopts a target optimization strategy, such as an oil tank model, and the target optimization strategy is to add strip magnetic shielding, the length, width, thickness, and distribution position of the strip magnetic shielding on the oil tank surface are determined according to design principles. Then, in a 3D modeling tool, based on the geometry of the original oil tank model, a 3D structure of the strip magnetic shielding that meets the parameter requirements is constructed at the specified position. The magnetic shielding structure is then integrated with the original oil tank model through Boolean operations to form an optimized oil tank model with strip magnetic shielding. If the determined optimization scheme simultaneously adopts a target optimization material and a target optimization strategy, such as a component model that needs to be replaced with a high thermal conductivity material and have its structure slotted, the model's material properties are first replaced, and then slotting is performed at the specified position of the model according to the slotting parameters. Finally, an optimized model with both new material properties and a new structural form is obtained. After optimization, the assembly compatibility of the optimized model with other structural component models is checked to ensure there are no assembly conflicts, ultimately resulting in an optimized model that meets the requirements.

[0180] Step S42: Perform simulation analysis based on the optimized model to obtain the temperature rise determination result.

[0181] It should be understood that the simulation analysis here refers to the electromagnetic simulation calculation and temperature field solution process carried out again based on the optimized model, which is consistent with the initial simulation process. This includes determining the concentrated current structural components, meshed structural components, preset meshing rules and preset solution conditions in the optimized transformer model, setting surface impedance boundary conditions and current excitation conditions, performing meshing, conducting electromagnetic simulation to obtain new structural component losses, setting heat transfer parameters based on the new losses, performing temperature field meshing and temperature field solution, and finally obtaining the temperature rise determination result.

[0182] Step S43: When the temperature rise determination result is less than or equal to the preset temperature rise threshold, the temperature rise determination result is taken as the target temperature rise result.

[0183] It should be noted that the temperature rise determination result is based on the temperature rise values ​​of each structural component obtained after simulation analysis using the optimized model; that is, the difference between the optimized temperature value of each structural component and the ambient temperature. This result is used to determine whether the optimized structural parameters make the temperature rise of each structural component meet the preset threshold requirements.

[0184] Understandably, the temperature rise prediction result is compared one by one with the preset temperature rise threshold, covering all structural components, including both optimized and unoptimized ones. Each structural component's temperature rise prediction result is checked to ensure it is less than or equal to its corresponding preset temperature rise threshold. If all structural components meet this condition, the structural optimization scheme is effective, and the optimized structural parameters ensure the temperature rise of each component meets design requirements. In this case, the temperature rise prediction result is directly determined as the target temperature rise result. After determining the target temperature rise result, subsequent steps are taken. Based on this target temperature rise result, the target cloud map components, simulation parameters, and simulation results are determined, thereby generating the target display cloud map and simulation report, completing the entire temperature rise prediction process.

[0185] In one feasible implementation, when the initial temperature rise result is less than or equal to a preset temperature rise threshold, the initial temperature rise result is taken as the target temperature rise result.

[0186] Understandably, the initial temperature rise result is compared one by one with the preset temperature rise threshold. The comparison covers all key structural components of the transformer, such as the core, coils, tank, web, limb plates, and tie plates. Each structural component's initial temperature rise result is checked to ensure it is less than or equal to its corresponding preset temperature rise threshold.

[0187] If the initial temperature rise of all structural components meets the condition of being less than or equal to the preset temperature rise threshold, it means that the current structural parameters of the transformer can make the temperature rise of each structural component meet the design requirements, and no structural optimization adjustment is required. At this time, the initial temperature rise result is directly determined as the target temperature rise result, which provides a basis for the subsequent determination of cloud map components, simulation parameters and simulation results.

[0188] This embodiment provides a method for predicting the temperature rise of transformer structural components. By determining the component model to be optimized when the initial temperature rise exceeds a preset threshold, implementing model optimization, conducting simulation analysis, and determining the target temperature rise when the temperature rise determination result meets the preset threshold, this method solves the technical problem of efficiently and accurately predicting the temperature rise of transformer structural components during the design phase and optimizing them in a timely manner to meet the requirements of safe operation. It achieves the beneficial effects of improving the accuracy of temperature rise prediction, optimizing the design process, reducing the risk of overheating, shortening the product development cycle, and improving the reliability and economy of transformers.

[0189] For example, to help understand the implementation process of the transformer structural component temperature rise prediction method obtained by combining this embodiment with the above embodiment one, please refer to... Figure 7 , Figure 7 A simplified flowchart of a method for predicting the temperature rise of transformer structural components is provided, specifically:

[0190] The process begins with data reading and processing module 1, which includes data reading module 1-1 and design principle matching module 1-2. This module is responsible for acquiring the necessary information for 3D modeling of the transformer and providing data support for subsequent work. Next is 3D modeling module 2, which consists of core lamination module 2-1, coil modeling module 2-2, and structural component modeling module 2-3. Based on the transmitted model parameters, it establishes a 3D model of the power transformer and assigns material properties.

[0191] The process then proceeds to electromagnetic simulation module 3, which includes boundary condition setting module 3-1, current excitation setting module 3-2, mesh setting module 3-3, and solution condition setting module 3-4. These modules perform electromagnetic simulation based on the 3D model to obtain the losses of the transformer structural components. Next is temperature simulation module 4, which includes heat source setting module 4-1, heat transfer parameter setting module 4-2, and mesh generation setting module 4-3. This module couples the structural component losses calculated from the electromagnetic field simulation to this module for temperature field solving.

[0192] The structural parameter optimization module 5 follows, consisting of the structural component temperature rise evaluation module 5-1 and the iterative optimization module 5-2. It determines whether the temperature rise of the structural component meets the requirements; if not, iterative optimization of the structure is performed. Finally, there is the verification post-processing module 6, which includes the temperature cloud map module 6-1 and the one-click report generation module 6-2, providing users with temperature rise cloud maps of the structural component and generating detailed result reports.

[0193] The flowchart clearly illustrates the entire process from data acquisition, 3D modeling, electromagnetic simulation, temperature simulation, structural parameter optimization to final verification and post-processing. Each module has its specific function and role, working together to achieve efficient analysis and optimization of temperature rise in transformer structural components. This automated and intelligent solution significantly improves the accuracy of temperature rise prediction, reduces errors caused by traditional empirical formulas or simplified models, enables automated modeling and simulation, optimizes structural parameters to improve transformer performance, reduces experimental costs and development cycles, and enhances design flexibility and scalability.

[0194] It should be noted that the above examples are only for understanding this application and do not constitute a limitation on the temperature rise prediction method of the transformer structural components of this application. Any simple modifications based on this technical concept are within the protection scope of this application.

[0195] This application also provides a temperature rise prediction device for transformer structural components; please refer to [reference needed]. Figure 8 The temperature rise prediction device for transformer structural components includes:

[0196] Data acquisition module 10 is used to acquire a preset temperature rise threshold and a three-dimensional model of the power transformer;

[0197] Simulation calculation module 20 is used to perform electromagnetic simulation calculations on the three-dimensional model of the power transformer to obtain the losses of the transformer structural components.

[0198] Temperature calculation module 30 is used to solve the temperature field based on the losses of transformer structural components and obtain the initial temperature rise result;

[0199] The temperature rise prediction module 40 is used to obtain the temperature rise judgment result based on the initial temperature rise result and the preset temperature rise threshold, and to determine the target temperature rise result based on the temperature rise judgment result, so as to complete the temperature rise prediction of the transformer structural components.

[0200] The temperature rise prediction device for transformer structural components provided in this application employs the temperature rise prediction method for transformer structural components described in the above embodiments, which can solve the technical problem of insufficient calculation accuracy in temperature rise prediction of transformer structural components. Compared with the prior art, the beneficial effects of the temperature rise prediction device for transformer structural components provided in this application are the same as those of the temperature rise prediction method for transformer structural components provided in the above embodiments, and other technical features in the temperature rise prediction device for transformer structural components are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.

[0201] In one embodiment, the simulation calculation module 20 is further configured to determine concentrated current structural components, meshed structural components, preset meshing rules, and preset solution conditions in the three-dimensional model of the power transformer; set surface impedance boundary conditions on the concentrated current structural components; set current excitation conditions at the coil cross-section of the three-dimensional model of the power transformer; perform meshing on the meshed structural components according to the preset meshing rules to obtain the target electromagnetic meshing model; and perform electromagnetic simulation calculations on the target electromagnetic meshing model according to the preset solution conditions, surface impedance boundary conditions, and current excitation conditions to obtain the transformer structural component losses.

[0202] In one embodiment, the temperature solving module 30 is further configured to obtain a preset temperature field mesh division rule; set heat transfer parameters according to the transformer structural component losses; perform mesh division on the mesh division structural components in the three-dimensional model of the power transformer according to the preset temperature field mesh division rule to obtain a target temperature division model; and solve the temperature field of the target temperature division model according to the heat transfer parameters to obtain the initial temperature rise result.

[0203] In one embodiment, the temperature rise prediction module 40 is further configured to determine the component model to be optimized based on the initial temperature rise result when the initial temperature rise result is greater than the preset temperature rise threshold, and optimize the component model to obtain an optimized model; perform simulation analysis based on the optimized model to obtain a temperature rise determination result; and take the temperature rise determination result as the target temperature rise result when the temperature rise determination result is less than or equal to the preset temperature rise threshold.

[0204] In one embodiment, the temperature rise prediction module 40 is further configured to: determine the component model to be optimized based on the initial temperature rise result when the initial temperature rise result is greater than a preset temperature rise threshold; determine the target optimization material and / or target optimization strategy based on the component model to be optimized; and optimize the component model to be optimized based on the target optimization material and / or target optimization strategy to obtain an optimized model.

[0205] In one embodiment, the temperature rise prediction module 40 is further configured to determine the target cloud map component, simulation parameters, and simulation results based on the target temperature rise result; generate a target display cloud map based on the target cloud map component; generate a simulation report based on the simulation parameters and simulation results; and perform a temperature rise prediction visualization display based on the target display cloud map and simulation report.

[0206] In one embodiment, the data acquisition module 10 is further configured to acquire core structure parameters, coil structure parameters, and transformer design parameters; establish an initial core model based on the core structure parameters; construct a spatial structure of windows and oil channels based on the initial core model to obtain a target core model, wherein the target core model represents the material properties of silicon steel sheets; establish a three-dimensional coil model based on the coil structure parameters, wherein the three-dimensional coil model represents the material properties of copper; perform data matching in a preset design principle database based on the transformer design parameters to obtain structural component design parameters, and establish a three-dimensional model of the structural component based on the structural component design parameters.

[0207] This application provides a temperature rise prediction device for transformer structural components. The temperature rise prediction device for transformer structural components includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the temperature rise prediction method for transformer structural components in the above embodiment 1.

[0208] The following is for reference. Figure 9 This document illustrates a structural schematic diagram of a temperature rise prediction device suitable for implementing the embodiments of this application for transformer structural components. The temperature rise prediction device for transformer structural components in the embodiments of this application may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital radio receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Description), PMPs (Portable Media Players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 9 The temperature rise prediction device for the transformer structure shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0209] like Figure 9 As shown, the temperature rise prediction device for transformer structural components may include a processing unit 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in ROM (Read Only Memory) 1002 or a program loaded from storage device 1003 into RAM (Random Access Memory) 1004. RAM 1004 also stores various programs and data required for the operation of the temperature rise prediction device for transformer structural components. The processing unit 1001, ROM 1002, and RAM 1004 are interconnected via bus 1005. Input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to I / O interface 1006: input devices 1007 including, for example, touchscreens, touchpads, keyboards, mice, image sensors, microphones, accelerometers, gyroscopes, etc.; output devices 1008 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 1003 including, for example, magnetic tapes, hard disks, etc.; and communication devices 1009. Communication device 1009 allows the temperature rise prediction device for transformer structures to communicate wirelessly or wiredly with other devices to exchange data. Although the figure shows a temperature rise prediction device for a transformer structure with various systems, it should be understood that it is not required to implement or possess all the systems shown. More or fewer systems can be implemented or possessed alternatively.

[0210] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from ROM 1002. When the computer program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0211] The temperature rise prediction device for transformer structural components provided in this application, employing the temperature rise prediction method for transformer structural components described in the above embodiments, can solve the technical problem of insufficient calculation accuracy in temperature rise prediction of transformer structural components. Compared with the prior art, the beneficial effects of the temperature rise prediction device for transformer structural components provided in this application are the same as those of the temperature rise prediction method for transformer structural components provided in the above embodiments, and other technical features of this temperature rise prediction device for transformer structural components are the same as those disclosed in the method of the previous embodiment, and will not be repeated here.

[0212] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0213] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0214] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, the computer-readable program instructions being used to execute the temperature rise prediction method for transformer structural components in the above embodiments.

[0215] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections with one or more wires, portable computer disks, hard disks, RAM (Random Access Memory), ROM (Read Only Memory), Erasable Programmable Read Only Memory (EPROM), optical fiber, CD-ROM (CD-Read Only Memory), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0216] The aforementioned computer-readable storage medium may be included in the temperature rise prediction device of the transformer structural component; or it may exist independently and not assembled into the temperature rise prediction device of the transformer structural component.

[0217] The aforementioned computer-readable storage medium carries one or more programs. When these programs are executed by the transformer structural component temperature rise prediction device, the transformer structural component temperature rise prediction device: acquires a preset temperature rise threshold and a three-dimensional model of the power transformer; performs electromagnetic simulation calculations on the three-dimensional model of the power transformer to obtain the transformer structural component losses; solves the temperature field based on the transformer structural component losses to obtain initial temperature rise results; obtains a temperature rise determination result based on the initial temperature rise result and the preset temperature rise threshold, and determines the target temperature rise result based on the temperature rise determination result, thereby completing the temperature rise prediction of the transformer structural component.

[0218] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as "C" or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including LAN (Local Area Network) or WAN (Wide Area Network)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0219] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0220] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0221] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the temperature rise prediction method for the above-described transformer structural components, thereby solving the technical problem of insufficient calculation accuracy in the temperature rise prediction of transformer structural components. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as the beneficial effects of the temperature rise prediction method for transformer structural components provided in the above embodiments, and will not be repeated here.

[0222] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the temperature rise prediction method for transformer structural components as described above.

[0223] The computer program product provided in this application can solve the technical problem of insufficient calculation accuracy in predicting the temperature rise of transformer structural components. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as those of the temperature rise prediction method for transformer structural components provided in the above embodiments, and will not be repeated here.

[0224] The above are only some embodiments of this application and do not limit the patent scope of this application. All equivalent structural transformations made under the technical concept of this application and using the contents of the specification and drawings of this application, or direct / indirect applications in other related technical fields, are included in the patent protection scope of this application.

Claims

1. A method of temperature rise prediction of a transformer structure, characterized by, The method comprises: acquiring a preset temperature rise threshold and a three-dimensional model of a power transformer; performing electromagnetic simulation calculation on the three-dimensional model of the power transformer to obtain transformer structural component loss; solving a temperature field according to the transformer structural component loss to obtain an initial temperature rise result; obtaining a temperature rise determination result according to the initial temperature rise result and the preset temperature rise threshold, and determining a target temperature rise result according to the temperature rise determination result to complete temperature rise prediction of the transformer structural component.

2. The method of claim 1, wherein, The step of performing electromagnetic simulation calculation on the three-dimensional model of the power transformer to obtain transformer structural component loss comprises: determining a concentrated current structural component, a grid division structural component, a preset grid division rule and a preset solving condition in the three-dimensional model of the power transformer; setting a surface impedance boundary condition on the concentrated current structural component; setting a current excitation condition at a coil cross section of the three-dimensional model of the power transformer; performing grid division on the grid division structural component according to the preset grid division rule to obtain a target electromagnetic division model; performing electromagnetic simulation calculation on the target electromagnetic division model according to the preset solving condition, the surface impedance boundary condition and the current excitation condition to obtain transformer structural component loss.

3. The method of claim 1, wherein, The step of solving a temperature field according to the transformer structural component loss to obtain an initial temperature rise result comprises: acquiring a preset temperature field grid division rule; setting a heat transfer parameter according to the transformer structural component loss; performing grid division on the grid division structural component in the three-dimensional model of the power transformer according to the preset temperature field grid division rule to obtain a target temperature division model; solving a temperature field of the target temperature division model according to the heat transfer parameter to obtain an initial temperature rise result.

4. The method of claim 1, wherein, The step of obtaining a temperature rise determination result according to the initial temperature rise result and the preset temperature rise threshold, and determining a target temperature rise result according to the temperature rise determination result comprises: when the initial temperature rise result is greater than the preset temperature rise threshold, determining a to-be-optimized component model according to the initial temperature rise result, and performing model optimization on the to-be-optimized component model to obtain an optimized model; performing simulation analysis according to the optimized model to obtain a temperature rise determination result; when the temperature rise determination result is less than or equal to the preset temperature rise threshold, taking the temperature rise determination result as the target temperature rise result.

5. The method of claim 4, wherein, The step of, when the initial temperature rise result is greater than the preset temperature rise threshold, determining a to-be-optimized component model according to the initial temperature rise result, and performing model optimization on the to-be-optimized component model to obtain an optimized model comprises: when the initial temperature rise result is greater than the preset temperature rise threshold, determining a to-be-optimized component model according to the initial temperature rise result; determining a target optimization scheme according to the to-be-optimized component model, wherein the target optimization scheme comprises a target optimization material and / or a target optimization strategy; performing model optimization on the to-be-optimized component model according to the target optimization scheme to obtain an optimized model.

6. The method of claim 1, wherein, After the step of obtaining the temperature rise judgment result according to the initial temperature rise result and the preset temperature rise threshold, and determining the target temperature rise result according to the temperature rise judgment result to complete the temperature rise prediction of the transformer structural part, the method further comprises the steps of: determining a target cloud component, simulation parameters and a simulation result according to the target temperature rise result; generating a target display cloud map according to the target cloud component; generating a simulation report according to the simulation parameters and the simulation result; performing visual display of the temperature rise prediction according to the target display cloud map and the simulation report.

7. The method of claim 1, wherein, The three-dimensional model of the power transformer comprises a target core model, a coil three-dimensional model and a structural part three-dimensional model; Before the steps of obtaining the preset temperature rise threshold and the three-dimensional model of the power transformer, the method further comprises the steps of: obtaining core structure parameters, coil structure parameters and transformer design parameters; establishing an initial core model according to the core structure parameters; constructing the spatial structure of the window and the oil channel according to the initial core model to obtain the target core model, wherein the target core model is of a silicon steel sheet material attribute; establishing the coil three-dimensional model according to the coil structure parameters, wherein the coil three-dimensional model is of a copper material attribute; performing data matching in a preset design principle database according to the transformer design parameters to obtain structural part design parameters, and establishing the structural part three-dimensional model according to the structural part design parameters.

8. A temperature rise prediction device for a transformer structural component, characterized in that, The device comprises: a data acquisition module configured to obtain a preset temperature rise threshold and a three-dimensional model of a power transformer; a simulation calculation module configured to perform electromagnetic simulation calculation on the three-dimensional model of the power transformer to obtain transformer structural part loss; a temperature solving module configured to perform temperature field solving according to the transformer structural part loss to obtain an initial temperature rise result; a temperature rise prediction module configured to obtain a temperature rise judgment result according to the initial temperature rise result and the preset temperature rise threshold, and determine a target temperature rise result according to the temperature rise judgment result to complete the temperature rise prediction of the transformer structural part.

9. A temperature rise prediction device for transformer structural components, characterized in that, The device comprises a memory, a processor and a computer program stored on the memory and executable on the processor, and the computer program is configured to implement the steps of the temperature rise prediction method of the transformer structural part according to any one of claims 1 to 7.

10. A storage medium, characterized by The storage medium is a computer readable storage medium, and the storage medium stores a computer program, and the computer program is executed by the processor to implement the steps of the temperature rise prediction method of the transformer structural part according to any one of claims 1 to 7.

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