Optimization design method and device for heat dissipation structure of transformer

Abstract

The invention provides a transformer heat dissipation structure optimization design method and device, and relates to the technical field of computers. The method comprises the following steps: determining a corresponding target transformer, creating a three-dimensional model of the target transformer and a use environment by using a three-dimensional modeling tool, and creating a virtual working environment of the target transformer based on a VR (Virtual Reality) technology; importing the three-dimensional model into a target VR platform, setting corresponding platform parameters based on a target transformer, integrating thermal simulation software in a virtual working environment, performing thermal simulation in the virtual working environment based on an actual heating condition and a working environment condition corresponding to the target transformer, and obtaining transformer temperature distribution of the target transformer under different working conditions; a multi-layer fin structure is designed based on transformer temperature distribution, real-time temperature data of the target transformer in the virtual working environment is obtained, and the rotating speed of a cooling fan in the transformer is automatically adjusted based on the real-time temperature data. The optimization efficiency of the heat dissipation structure of the transformer can be improved.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and more specifically, to a method and device for optimizing the design of a transformer heat dissipation structure. Background Art

[0002] With the development of the power industry and the continuous increase in the capacity of power equipment, the heat generated by transformers as an important component of the power system during operation also increases. Excessive temperature will not only reduce the service life of the transformer, but also seriously affect its working performance. Therefore, effective heat dissipation design is crucial to improving the reliability and economy of the transformer.

[0003] At present, the common transformer heat dissipation methods on the market mainly include natural cooling, forced air cooling, oil immersion cooling, etc. However, these traditional heat dissipation methods have certain limitations, such as low heat dissipation efficiency, high noise, and inconvenient maintenance. In recent years, some new heat dissipation technologies and structural designs have emerged, such as the use of efficient heat dissipation materials, optimization of heat sink structure, and introduction of intelligent temperature control systems. However, the existing heat dissipation design schemes still have some shortcomings in practical applications, such as high material costs, increased structural complexity, and difficulties in installation and maintenance.

[0004] From the above, it can be seen that the problem of how to improve the optimization efficiency of the transformer heat dissipation structure still needs to be solved. Summary of the invention

[0005] The present application provides a method and device for optimizing the design of a heat dissipation structure of a transformer, which can solve the problem of how to improve the optimization efficiency of the heat dissipation structure of the transformer in the related art. The technical solution is as follows: According to one aspect of the present application, a method for optimizing the heat dissipation structure of a transformer includes: determining a corresponding target transformer, using a three-dimensional modeling tool to create a three-dimensional model corresponding to the target transformer and a use environment, and creating a virtual working environment corresponding to the target transformer based on VR technology, wherein the virtual working environment includes the physical space where the transformer is located, peripheral equipment, and related facilities; selecting a target VR platform, importing the three-dimensional model into the target VR platform, and setting corresponding platform parameters based on the target transformer, integrating thermal simulation software in the virtual working environment, performing thermal simulation in the virtual working environment based on the actual heating conditions and working environment conditions corresponding to the target transformer, and obtaining the transformer temperature distribution of the target transformer under different working conditions in the virtual working environment; designing a corresponding multi-layer fin structure based on the transformer temperature distribution, obtaining real-time temperature data corresponding to the target transformer in the virtual working environment, and automatically adjusting the speed of the cooling fan in the transformer based on the real-time temperature data; wherein the spacing and thickness between each layer of fins are optimized through CFD simulation.

[0006] In an exemplary embodiment, after designing the corresponding multi-layer fin structure based on the transformer temperature distribution, the method further includes: performing thermal simulation of different multi-layer fin structures in the virtual working environment to obtain heat dissipation data corresponding to the different multi-layer fin structures in the virtual working environment; sorting the heat dissipation data corresponding to all multi-layer fin structures, and determining the corresponding preferred heat dissipation structure set; applying all the preferred heat dissipation structures in the preferred heat dissipation structure set to actual scenarios to determine the optimal heat dissipation structure.

[0007] In an exemplary embodiment, the method further includes: monitoring the temperature data of the inside and heat dissipation structure of the target transformer in real time through a temperature sensor, and recording to form a historical temperature data set; retrieving a pre-trained recognition model, inputting the historical temperature data set into the recognition model for analysis, and obtaining a corresponding temperature change trend; adjusting the heat dissipation strategy based on the temperature change trend, including but not limited to increasing the fan speed in advance or starting additional cooling measures according to expected operating conditions.

[0008] In an exemplary embodiment, the method further includes: determining key parts corresponding to the target transformer, deploying optical fiber temperature sensors at the key parts to form a continuous temperature monitoring network; monitoring the part temperature data of the key parts in real time through the temperature monitoring network, and transmitting the part temperature data to a central control system, the central control system processes the received temperature data to form a temperature distribution diagram, and displays it in real time on a monitoring interface; retrieving the temperature threshold of each key part, detecting whether there is a hot spot based on the temperature threshold and the part temperature data, and triggering an alarm if there is a hot spot.

[0009] In an exemplary embodiment, the method further includes: selecting corresponding thermoelectric materials and determining corresponding layout positions in the heat dissipation structure of the target transformer; installing corresponding thermoelectric modules based on the layout positions so that one side of the thermoelectric modules contacts a high temperature area and the other side contacts a low temperature area to form a temperature difference; converting the temperature difference into electrical energy through the thermoelectric modules, and storing the generated electrical energy.

[0010] In an exemplary embodiment, the method further includes: encapsulating the PCM material in a container to form a heat storage unit, and integrating the heat storage unit into the heat dissipation structure.

[0011] According to one aspect of the present application, a transformer heat dissipation structure optimization design device includes: A virtual working environment creation module determines the corresponding target transformer, uses a three-dimensional modeling tool to create a three-dimensional model of the target transformer and the use environment, and uses VR technology to create a virtual working environment corresponding to the target transformer, wherein the virtual working environment includes the physical space where the transformer is located, peripheral equipment and related facilities; A transformer temperature distribution acquisition module selects a target VR platform, imports the three-dimensional model into the target VR platform, sets corresponding platform parameters based on the target transformer, integrates thermal simulation software in a virtual working environment, and performs thermal simulation in the virtual working environment based on the actual heating conditions and working environment conditions corresponding to the target transformer, so as to obtain the transformer temperature distribution of the target transformer under different working conditions in the virtual working environment; A design module is used to design a corresponding multi-layer fin structure based on the temperature distribution of the transformer, obtain the real-time temperature data corresponding to the target transformer in the virtual working environment, and automatically adjust the speed of the cooling fan in the transformer based on the real-time temperature data; wherein the spacing and thickness between each layer of fins are optimized through CFD simulation.

[0012] According to one aspect of the present application, an electronic device includes at least one processor and at least one memory, wherein the memory stores computer-readable instructions; the computer-readable instructions are executed by one or more of the processors, so that the electronic device implements the transformer heat dissipation structure optimization design method as described above.

[0013] According to one aspect of the present application, a storage medium stores computer-readable instructions thereon, and the computer-readable instructions are executed by one or more processors to implement the transformer heat dissipation structure optimization design method as described above.

[0014] According to one aspect of the present application, a computer program product includes computer-readable instructions, which are stored in a storage medium. One or more processors of an electronic device read the computer-readable instructions from the storage medium, load and execute the computer-readable instructions, so that the electronic device implements the transformer heat dissipation structure optimization design method as described above.

[0015] The beneficial effects of the technical solution provided by this application are: By using 3D modeling tools to create a 3D model of the target transformer and creating a virtual working environment based on VR technology, the physical space, peripheral equipment and related facilities of the transformer can be accurately simulated during actual operation, making the simulation results closer to the actual situation. Thermal simulation software is integrated in the virtual working environment to perform thermal simulation based on the actual heating conditions and working environment conditions of the target transformer, and obtain the temperature distribution under different working conditions. This simulation method is faster and more accurate than traditional methods.

[0016] According to the thermal simulation results in the virtual working environment, the multi-layer fin structure is designed, and the spacing and thickness between each layer of fins are optimized through CFD simulation to ensure the best heat dissipation effect. In addition, the temperature data of the transformer is obtained in real time, and the speed of the cooling fan is automatically adjusted according to this data, so that the heat dissipation system can dynamically adapt to different working conditions; through multiple iterations and optimizations in the virtual environment, designers can find potential problems in the early stages of the design and make adjustments quickly, avoiding the high cost and time consumption brought by physical prototyping.

[0017] Through the above process, the optimization efficiency of the transformer heat dissipation structure can be significantly improved, ensuring that the designed heat dissipation system can better adapt to various working conditions in practical applications and improve the reliability and economy of the transformer. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments of the present application. Obviously, the drawings described below are only some embodiments of the present application, and those skilled in the art can obtain other drawings based on these drawings without creative work.

[0019] Figure 1 is a flow chart of a transformer heat dissipation structure optimization design method according to an exemplary embodiment; Figure 2 It is a structural block diagram of a transformer heat dissipation structure optimization design device according to an exemplary embodiment. DETAILED DESCRIPTION

[0020] The embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present application, and cannot be interpreted as limiting the present application.

[0021] It will be understood by those skilled in the art that, unless expressly stated, the singular forms "one", "said", and "the" used herein may also include plural forms. It should be further understood that the term "comprising" used in the specification of the present disclosure refers to the presence of the features, integers, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. It should be understood that when we refer to an element as being "connected" or "coupled" to another element, it may be directly connected or coupled to the other element, or there may be intermediate elements. In addition, the "connection" or "coupling" used herein may include wireless connection or wireless coupling. The term "and / or" used herein includes all or any unit and all combinations of one or more associated listed items.

[0022] The transformer heat dissipation structure optimization design method provided in the present application can effectively improve the accuracy of the transformer heat dissipation structure optimization design. Accordingly, the transformer heat dissipation structure optimization design method is suitable for a transformer heat dissipation structure optimization design device, and the transformer heat dissipation structure optimization design device can be deployed in electronic equipment.

[0023] In order to make the objectives, technical solutions and advantages of the present application clearer, the implementation methods of the present application will be further described in detail below in conjunction with the accompanying drawings.

[0024] See also Figure 1 The embodiment of the present application provides a method for optimizing the heat dissipation structure of a transformer, which is applicable to electronic equipment. The electronic equipment may be Figure 1 The server side in the implementation environment is shown.

[0025] In the following method embodiments, for ease of description, the execution subject of each step of the method is taken as an electronic device as an example for illustration, but this does not constitute a specific limitation.

[0026] like Figure 1 As shown, the method may include the following steps: S100, determining a corresponding target transformer, using a three-dimensional modeling tool to create a three-dimensional model corresponding to the target transformer and the use environment, and creating a virtual working environment corresponding to the target transformer based on VR technology.

[0027] First, the transformer model for which the heat dissipation structure is to be optimized is identified, and the corresponding target transformer is determined, including its electrical parameters, size and other basic information; then, a 3D modeling software (such as SolidWorks, AutoCAD, CATIA, etc.) is used to create a 3D model of the target transformer, including the transformer body, internal components (such as coils, cores) and casing; and at the same time, a 3D model of the physical space where the target transformer is located is created, including the installation location, peripheral equipment (such as switchgear, cable trays), ventilation system, etc.; the 3D model can accurately reflect the real physical characteristics of the transformer and its use environment, providing a basis for subsequent virtual simulation.

[0028] It should be pointed out here that the physical space, peripheral equipment and related facilities where the target transformer is located in the virtual working environment should be constructed to ensure that they are consistent with the actual situation; VR technology provides an immersive experience, allowing users to more intuitively understand and analyze the working environment of the transformer; through the virtual working environment, engineers can more easily observe and experiment, and improve the optimization efficiency of the heat dissipation structure.

[0029] S110, selecting a target VR platform, importing the three-dimensional model into the target VR platform, setting corresponding platform parameters based on the target transformer, integrating thermal simulation software in the virtual working environment, performing thermal simulation in the virtual working environment based on the actual heating situation and working environment conditions corresponding to the target transformer, and obtaining the transformer temperature distribution of the target transformer under different working conditions in the virtual working environment.

[0030] Among them, a suitable VR platform is selected according to the specific needs of the optimized design, such as Unity, Unreal Engine, etc., and then the created 3D model can be imported into the selected VR platform, and the relevant parameters of the VR platform, such as physical properties, material properties, etc., are set according to the type of target transformer; by setting the correct parameters, the transformer behavior in the virtual environment is ensured to be consistent with the actual one, and the selection of a suitable VR platform can improve development efficiency and shorten the development cycle.

[0031] During the thermal simulation process, thermal simulation software (such as ANSYS Fluent, Star-CCM+, etc.) can be integrated into the VR platform to perform thermal simulation. According to the actual heating conditions and working environment conditions of the target transformer, simulation parameters such as ambient temperature and air flow speed can be set. Then, thermal simulation can be run in a virtual environment to obtain the temperature distribution of the transformer under different working conditions.

[0032] Through thermal simulation, the temperature distribution of the transformer under different working conditions can be accurately analyzed to provide data support for subsequent heat dissipation design; and based on the simulation results, potential hot spots can be discovered to optimize the heat dissipation structure of the target transformer.

[0033] S120, designing a corresponding multi-layer fin structure based on the temperature distribution of the transformer, obtaining corresponding real-time temperature data of the target transformer in the virtual working environment, and automatically adjusting the rotation speed of a cooling fan in the transformer based on the real-time temperature data.

[0034] Among them, according to the results of thermal simulation, a multi-layer fin structure is designed to improve the heat dissipation performance. The spacing and thickness between each layer of fins are optimized through CFD simulation to ensure maximum heat dissipation efficiency. It should be pointed out that the fin structure is well matched with the transformer body without affecting the functions of other components. The optimized fin structure design can improve the heat dissipation efficiency and reduce the operating temperature of the transformer.

[0035] In addition, the real-time temperature data of the target transformer type is obtained in the virtual environment. Based on the real-time temperature data, the speed of the cooling fan is automatically adjusted through a preset algorithm to maintain the best heat dissipation effect, thereby ensuring that the fan speed can be dynamically adjusted under different working conditions to adapt to temperature changes.

[0036] By executing steps S100 to S120, the transformer heat dissipation structure optimization design method based on VR technology and CFD simulation can achieve accurate design and optimization of the transformer heat dissipation structure. This method not only improves the heat dissipation efficiency and reduces the operating temperature, but also achieves energy saving and noise reduction by dynamically adjusting the cooling fan speed, thereby significantly improving the operating stability and service life of the transformer.

[0037] It should be pointed out here that after designing the corresponding multi-layer fin structure based on the transformer temperature distribution, in order to determine the optimal heat dissipation structure, the method further performs the following steps: S121, performing thermal simulation of different multi-layer fin structures in a virtual working environment to obtain heat dissipation data corresponding to the different multi-layer fin structures in the virtual working environment.

[0038] Among them, based on the preliminary designed multi-layer fin structure, several different variants are designed, and each variant may involve fine-tuning of factors such as the spacing, thickness, and shape of the fins; and in the virtual working environment, for each different fin structure variant, corresponding thermal simulation parameters are set, including ambient temperature, air flow velocity, etc.; then, the thermal simulation software integrated in the VR platform is used to perform thermal simulation on each fin structure variant to obtain its heat dissipation data in the virtual working environment, such as temperature distribution, heat flux density, etc.

[0039] By performing thermal simulation on different fin structure variants in a virtual environment, the heat dissipation effect of each design can be fully evaluated, and the heat dissipation data obtained provides rich data support for the subsequent selection of the optimal structure.

[0040] S122, sorting the heat dissipation data corresponding to all the multi-layer fin structures, and determining the corresponding optimal heat dissipation structure set.

[0041] Among them, the heat dissipation data of all fin structure variants are sorted, including key indicators such as the highest temperature point, average temperature, temperature difference distribution, etc., and then all fin structure variants are sorted according to the key indicators of heat dissipation effect (such as maximum temperature, average temperature, etc.). According to the sorting results, the top few fin structure variants with the best heat dissipation effects can be selected to form a preferred heat dissipation structure set.

[0042] First, through sorting and selection, the fin structure with the best heat dissipation effect can be quickly identified, providing candidate solutions for subsequent practical applications; secondly, the preferred range can be narrowed down to reduce the workload and cost of subsequent practical tests.

[0043] S123, applying all the preferred heat dissipation structures in the preferred heat dissipation structure set to an actual scenario to determine an optimal heat dissipation structure.

[0044] Among them, each structural variant in the preferred heat dissipation structure set is applied to the actual transformer heat dissipation system for actual testing. The heat dissipation effect of each fin structure is monitored in the actual working environment, and the temperature distribution, heat flux density and other data during actual operation are recorded. The actual test results are compared with the virtual simulation results, the actual heat dissipation effect is analyzed, and the optimal heat dissipation structure is determined. Based on the actual test results, the fin structure with the best heat dissipation effect is finally determined to provide the most optimized design solution for actual production.

[0045] By executing steps S121 to S123, thermal simulations of different multi-layer fin structures are performed in a virtual working environment, and a preferred heat dissipation structure set is selected based on the simulation results. Finally, the preferred structure is applied to the actual scene to determine the optimal heat dissipation structure. This series of steps can ensure the reliability and effectiveness of the final design. This method not only improves the scientificity and accuracy of the heat dissipation structure design, but also verifies the feasibility of the design through actual tests, thereby significantly improving the performance and stability of the transformer heat dissipation system.

[0046] In the process of optimizing the design, the method also includes: S111, monitor the temperature data of the inside and heat dissipation structure of the target transformer in real time through a temperature sensor, and record and form a historical temperature data set.

[0047] Temperature sensors are installed at key locations of the target transformer (such as coils, cores, cooling fins, etc.). The temperature sensors continuously collect temperature data inside the target transformer and the cooling structure, and send the data to the data processing center in real time through data transmission equipment (such as wireless transmission modules). The real-time collected temperature data is recorded to form a historical temperature data set for subsequent analysis.

[0048] S112, calling a pre-trained recognition model, inputting a historical temperature data set into the recognition model for analysis, and obtaining a corresponding temperature change trend.

[0049] The recognition model training process includes the following steps: 1. Data collection: Historical data collection: Collect temperature data of the transformer under different working conditions, including internal temperature, heat dissipation structure temperature, ambient temperature, etc.; Working condition information: Record various working condition information of the transformer during operation, such as load conditions, environmental conditions (temperature, humidity, etc.), fan speed, etc.

[0050] 2. Data preprocessing: Data cleaning: remove invalid data, fill missing values, and correct outliers; Feature engineering: extract key features that affect temperature change trends, such as sliding windows and periodic features of time series data; Data standardization: standardize the data to ensure that the data is compared on the same scale.

[0051] 3. Data division: Data segmentation: Divide the data set into training set, validation set and test set, with the general ratio of 70% training set, 15% validation set and 15% test set, to ensure that the data distribution of the training set, validation set and test set is as consistent as possible.

[0052] 4. Model selection and training: Model selection: Select a model suitable for time series analysis, such as ARIMA (autoregressive integrated moving average model), LSTM (long short-term memory network), GRU (gated recurrent unit), etc.; Model initialization: Initialize model parameters, such as weights, biases, etc.; Loss function: Define loss function, such as mean square error (MSE), root mean square error (RMSE), etc.; Optimization algorithm: Select an appropriate optimization algorithm, such as Adam, RMSprop, etc.; Iterative training: Use the training set data for multiple iterative training, and update the model parameters after each iteration until the loss function converges or reaches the predetermined training rounds.

[0053] 5. Model validation and tuning: Cross-validation: Use validation set data to validate the model and evaluate the generalization ability of the model; Hyperparameter tuning: Adjust the model's hyperparameters, such as learning rate, number of hidden layers, time step, etc., based on the performance on the validation set; Performance evaluation: Use test set data to evaluate the final performance of the model.

[0054] 6. Model deployment: Model preservation: Save the trained model for subsequent use; Interface development: Develop an API interface so that the model can receive real-time temperature data and output temperature change trend predictions.

[0055] By selecting a pre-trained temperature change trend recognition model and then inputting the historical temperature data set into the recognition model, the recognition model will process and analyze the data, and the recognition model outputs a trend forecast of temperature change, including the temperature change trend in the future; through model analysis, future temperature change trends can be predicted.

[0056] S113: Adjust the heat dissipation strategy based on the temperature change trend, including but not limited to increasing the fan speed in advance or starting additional cooling measures according to the expected working conditions.

[0057] Among them, based on the analysis results of historical data, a more scientific heat dissipation strategy can be formulated, and the heat dissipation strategy can be dynamically adjusted according to the changes in actual working conditions to ensure that the transformer always operates within a safe temperature range. In addition, increase the fan speed in advance: If it is predicted that the temperature will rise in the future, the speed of the cooling fan can be increased in advance to enhance the heat dissipation effect; start additional cooling measures: If it is predicted that the temperature will rise significantly, additional cooling measures can be started, such as starting the backup cooling system or increasing the flow of the cooling medium.

[0058] It should be pointed out here that by real-time monitoring of the temperature data inside the target transformer and the heat dissipation structure, and adjusting the heat dissipation strategy based on these data, the heat dissipation effect of the transformer can be finely managed and optimized. This method can not only monitor the temperature changes of the transformer in real time, but also predict future temperature trends through the analysis of historical data, and take heat dissipation measures in advance, thereby significantly improving the operational stability and safety of the transformer.

[0059] For the key parts of the target transformer, the embodiment of the present application also includes: S114, determining the key parts corresponding to the target transformer, deploying optical fiber temperature sensors at the key parts, and forming a continuous temperature monitoring network.

[0060] Among them, fiber optic temperature sensors are installed in these key locations. Fiber optic sensors have the characteristics of high precision and strong anti-electromagnetic interference ability, and are suitable for use in the high-temperature environment inside the transformer. Multiple fiber optic temperature sensors are connected to form a continuous temperature monitoring network. By deploying sensors at key locations to form a continuous monitoring network, the temperature changes inside the transformer can be fully covered.

[0061] S115, monitor the temperature data of key parts in real time through the temperature monitoring network, and transmit the temperature data to the central control system. The central control system processes the received temperature data, forms a temperature distribution diagram, and displays it in real time on the monitoring interface.

[0062] Among them, the optical fiber temperature sensor continuously collects temperature data of key parts and sends it to the central control system in real time through data transmission equipment (such as optical fiber communication system). The central control system processes the received temperature data, including data cleaning, calibration, format conversion, etc., and the central control system generates a temperature distribution map based on the processed temperature data to display the temperature conditions of key parts of the transformer. The temperature distribution map is displayed in real time on the monitoring interface (such as large-screen display, monitoring room terminal, etc.) for operators to view at any time.

[0063] S116, retrieve the temperature threshold of each key part, detect whether there is a hot spot based on the temperature threshold and the part temperature data, and trigger an alarm if there is a hot spot.

[0064] First, according to the design specifications and operating experience of the transformer, a reasonable temperature threshold is set for each key part to ensure that the threshold will not be exceeded under normal operating conditions; the central control system detects the temperature data of each part in real time according to the set temperature threshold to determine whether there is a situation where the threshold is exceeded. Once the temperature of a part exceeds the set threshold, the system considers that an overheat point has appeared in that part. When an overheat point is detected, the central control system triggers the alarm mechanism and reminds the operator through sound and light alarms, text message notifications, etc.

[0065] In a virtual working environment, fiber optic temperature sensors are deployed at key locations of the transformer to form a continuous temperature monitoring network. The temperature data is monitored and processed in real time through a central control system, and a temperature distribution diagram is generated and displayed on the monitoring interface. Hot spots can be detected in time and alarms can be triggered by setting temperature thresholds. In the process of optimizing the heat dissipation structure design of the transformer, the heat dissipation structure can ensure the safety and stability of the transformer operation, thereby achieving the optimization efficiency of the transformer heat dissipation structure.

[0066] During the design process, when designing the corresponding heat dissipation structure, the following designs are performed on the heat dissipation structure, specifically including: S124, selecting corresponding thermoelectric materials, and determining corresponding arrangement positions in the heat dissipation structure of the target transformer.

[0067] Among them, according to the operating temperature range of the transformer and the characteristics of the heat dissipation structure, suitable thermoelectric materials are selected. Commonly used thermoelectric materials include bismuth telluride (Bi2Te3), lead selenide (PbSe), etc. These materials have high thermoelectric conversion efficiency; in the heat dissipation structure of the transformer, the optimal layout position of the thermoelectric module is determined, usually selecting an area with a larger temperature gradient, such as the side of the heat dissipation fin close to the high temperature area, so that a larger temperature difference can be formed, which is conducive to thermoelectric conversion.

[0068] S125, installing corresponding thermoelectric modules based on the arrangement position, so that one side of the thermoelectric module contacts the high temperature area and the other side contacts the low temperature area, thereby forming a temperature difference.

[0069] Among them, the thermoelectric modules are installed according to the predetermined layout positions. Make sure that one side of the thermoelectric module is in close contact with the high-temperature area (such as near the transformer coil) and the other side is in close contact with the low-temperature area (such as the outside of the heat sink fins or the cooling medium), optimize the contact between the thermoelectric module and the high-temperature area and the low-temperature area, ensure good heat conduction, and reduce heat loss.

[0070] S126, converting the temperature difference into electrical energy through a thermoelectric module, and storing the generated electrical energy.

[0071] Among them, the thermoelectric module uses the temperature difference to generate the potential difference, thereby converting thermal energy into electrical energy. This process is based on the Seebeck effect, that is, when two different materials come into contact, the temperature difference will generate voltage, and the electrical energy generated by the thermoelectric module is transmitted through the circuit to the energy storage device (such as a battery or supercapacitor) for storage. The energy storage device needs to have good charging and discharging performance to ensure the effective use of electrical energy.

[0072] By selecting appropriate thermoelectric materials and installing thermoelectric modules in the heat dissipation structure of the target transformer, the temperature difference can be converted into electrical energy and stored. This method not only takes energy utilization into consideration during the optimization design process, but also optimizes the heat dissipation effect of the transformer and reduces energy waste.

[0073] During the design process, considering the rapid temperature changes inside the transformer, in order to cope with the situation where the transformer suddenly experiences a large temperature rise in a short period of time, the PCM material is encapsulated in a container to form a heat storage unit, and the heat storage unit is integrated into the heat dissipation structure.

[0074] It should be pointed out here that the appropriate phase change material should be selected according to the temperature range and heat dissipation requirements of the transformer operation. PCM materials should have a high latent heat value, good thermal stability and chemical stability. Commonly used PCM materials include paraffin, fatty acid esters, salt hydrates, etc.

[0075] As for packaging container design, a suitable container is designed to encapsulate the PCM material. The container should have good sealing to prevent PCM leakage and should have sufficient strength to withstand the stress caused by temperature changes.

[0076] For the packaging process: put the PCM material into the designed container, ensure that the PCM material is filled evenly and leave enough expansion space to accommodate the volume change during the phase change process.

[0077] The packaged heat storage unit is installed in the designated position of the heat dissipation structure. It can be installed by bonding, embedding or fixing the bracket. It is necessary to ensure that the heat storage unit works in coordination with other parts of the heat dissipation structure, such as with the heat dissipation fins, cooling fans, etc., to form an efficient heat dissipation system.

[0078] By encapsulating PCM materials in containers to form heat storage units and integrating these heat storage units into the heat dissipation structure of the transformer, effective management of the transformer operating temperature can be achieved. This method not only improves the efficiency and stability of the heat dissipation system, but also effectively absorbs and releases heat through the phase change process of the PCM material, reduces temperature fluctuations, and improves the operating safety and service life of the transformer. Therefore, this PCM material-based heat storage unit integration solution can improve the performance of the transformer heat dissipation system.

[0079] The following is an embodiment of the device of the present application, which can be used to execute the transformer heat dissipation structure optimization design method involved in the present application. For details not disclosed in the embodiment of the device of the present application, please refer to the method embodiment of the transformer heat dissipation structure optimization design method involved in the present application.

[0080] See also Figure 2 , the embodiment of the present application provides a transformer heat dissipation structure optimization design device, including but not limited to: A virtual working environment creation module 200 determines a corresponding target transformer, creates a three-dimensional model of the target transformer and the use environment using a three-dimensional modeling tool, and creates a virtual working environment corresponding to the target transformer based on VR technology, wherein the virtual working environment includes the physical space where the transformer is located, peripheral equipment, and related facilities; The transformer temperature distribution acquisition module 210 selects a target VR platform, imports the three-dimensional model into the target VR platform, sets corresponding platform parameters based on the target transformer, integrates thermal simulation software in the virtual working environment, and performs thermal simulation in the virtual working environment based on the actual heating situation and working environment conditions corresponding to the target transformer, so as to obtain the transformer temperature distribution of the target transformer under different working conditions in the virtual working environment; The design module 220 is used to design a corresponding multi-layer fin structure based on the temperature distribution of the transformer, obtain the corresponding real-time temperature data of the target transformer in the virtual working environment, and automatically adjust the speed of the cooling fan in the transformer based on the real-time temperature data; wherein the spacing and thickness between each layer of fins are optimized through CFD simulation.

[0081] In an exemplary embodiment, the device further includes but is not limited to: A heat dissipation data acquisition module performs thermal simulation of different multi-layer fin structures in a virtual working environment to obtain heat dissipation data corresponding to different multi-layer fin structures in the virtual working environment; A sorting module, used to sort the heat dissipation data corresponding to all multi-layer fin structures and determine the corresponding preferred heat dissipation structure set; The optimal heat dissipation structure determination module applies all the preferred heat dissipation structures in the preferred heat dissipation structure set to actual scenarios to determine the optimal heat dissipation structure.

[0082] In an exemplary embodiment, the device further includes but is not limited to: The historical temperature data set recording module monitors the temperature data of the target transformer and the heat dissipation structure in real time through the temperature sensor, and is used to record and form a historical temperature data set; The recognition model retrieval module is used to retrieve the pre-trained recognition model, input the historical temperature data set into the recognition model for analysis, and obtain the corresponding temperature change trend; The heat dissipation strategy adjustment module is used to adjust the heat dissipation strategy based on the temperature change trend, including but not limited to increasing the fan speed in advance or starting additional cooling measures according to the expected working conditions.

[0083] In an exemplary embodiment, the device further includes but is not limited to: The key part determination module is used to determine the key parts corresponding to the target transformer and deploy optical fiber temperature sensors at the key parts to form a continuous temperature monitoring network; The part temperature data monitoring module is used to monitor the part temperature data of key parts in real time through the temperature monitoring network, and transmit the part temperature data to the central control system. The central control system processes the received temperature data, forms a temperature distribution diagram, and displays it in real time on the monitoring interface; The detection module retrieves the temperature threshold of each key part and uses it to detect whether there is a hot spot based on the temperature threshold and the part temperature data. If there is a hot spot, an alarm is triggered.

[0084] In an exemplary embodiment, the device further includes but is not limited to: A layout position determination module selects corresponding thermoelectric materials to determine corresponding layout positions in the heat dissipation structure of the target transformer; A thermoelectric module installation module is used to install the corresponding thermoelectric module based on the arrangement position, so that one side of the thermoelectric module contacts the high temperature area and the other side contacts the low temperature area to form a temperature difference; The storage module converts the temperature difference into electrical energy through the thermoelectric module and is used to store the generated electrical energy.

[0085] In an exemplary embodiment, the device further includes but is not limited to: The PCM material is encapsulated in a container to form a heat storage unit, and the heat storage unit is integrated into a heat dissipation structure.

[0086] It should be noted that the transformer heat dissipation structure optimization design device provided in the above embodiment only uses the division of the above-mentioned functional modules as an example when performing the transformer heat dissipation structure optimization design. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the transformer heat dissipation structure optimization design device will be divided into different functional modules to complete all or part of the functions described above.

[0087] In addition, the transformer heat dissipation structure optimization design device and the transformer heat dissipation structure optimization design method provided in the above embodiments belong to the same concept, and the specific manner in which each module performs the operation has been described in detail in the method embodiment and will not be repeated here.

[0088] According to one aspect of the present application, an electronic device includes at least one processor and at least one memory, wherein the memory stores computer-readable instructions; the computer-readable instructions are executed by one or more of the processors, so that the electronic device implements the transformer heat dissipation structure optimization design method as described above.

[0089] In addition, a storage medium is provided in an embodiment of the present application, on which computer-readable instructions are stored, and the computer-readable instructions are executed by one or more processors to implement the transformer heat dissipation structure optimization design method as described above.

[0090] In an embodiment of the present application, a computer program product is provided. The computer program product includes computer-readable instructions. The computer-readable instructions are stored in a storage medium. One or more processors of an electronic device read the computer-readable instructions from the storage medium, load and execute the computer-readable instructions, so that the electronic device implements the transformer heat dissipation structure optimization design method as described above.

[0091] Compared with related technologies, virtual reality technology and thermal simulation can quickly iterate and optimize the heat dissipation structure during the design phase, saving a lot of time and cost; through real-time monitoring, temperature change trend prediction and abnormal warning mechanism, potential heat dissipation problems can be discovered and solved in time, improving the reliability of the system; through energy recovery of thermoelectric modules and heat storage of PCM materials, the originally wasted heat energy is effectively utilized, improving energy utilization efficiency; through multi-layer fin structure optimization, real-time monitoring and dynamic adjustment of heat dissipation strategy, the stability and safety of transformer operation are significantly improved. Through the above process, the optimization efficiency of the transformer heat dissipation structure can be significantly improved, ensuring that the designed heat dissipation system can better adapt to various working conditions in actual applications, and improving the reliability and economy of the transformer.

[0092] It should be understood that, although the steps in the flowchart of the accompanying drawings are displayed in sequence as indicated by the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least a part of the steps in the flowchart of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a part of the sub-steps or stages of other steps.

[0093] The above description is only a partial implementation method of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A transformer heat dissipation structure optimization design method, characterized in that: include: Determine the corresponding target transformer, use a three-dimensional modeling tool to create a three-dimensional model of the target transformer and the use environment, and create a virtual working environment corresponding to the target transformer based on VR technology, wherein the virtual working environment includes the physical space where the transformer is located, peripheral equipment and related facilities; Select a target VR platform, import the three-dimensional model into the target VR platform, set corresponding platform parameters based on the target transformer, integrate thermal simulation software in the virtual working environment, perform thermal simulation in the virtual working environment based on the actual heating situation and working environment conditions corresponding to the target transformer, and obtain the transformer temperature distribution of the target transformer under different working conditions in the virtual working environment; A corresponding multi-layer fin structure is designed based on the temperature distribution of the transformer, real-time temperature data corresponding to the target transformer in a virtual working environment is obtained, and the rotation speed of a cooling fan in the transformer is automatically adjusted based on the real-time temperature data; wherein the spacing and thickness between each layer of fins are optimized through CFD simulation.

2. The method according to claim 1, characterized in that After designing a corresponding multi-layer fin structure based on the transformer temperature distribution, the method further includes: Performing thermal simulation of different multi-layer fin structures in the virtual working environment to obtain heat dissipation data corresponding to the different multi-layer fin structures in the virtual working environment; Sorting the heat dissipation data corresponding to all multi-layer fin structures and determining the corresponding optimal heat dissipation structure set; All the preferred heat dissipation structures in the preferred heat dissipation structure set are applied to actual scenarios to determine the optimal heat dissipation structure.

3. The method according to claim 2, characterized in that The method further comprises: The temperature sensor monitors the temperature data inside the target transformer and the heat dissipation structure in real time, and records the temperature data to form a historical temperature data set; Retrieving a pre-trained recognition model, inputting the historical temperature data set into the recognition model for analysis, and obtaining a corresponding temperature change trend; The heat dissipation strategy is adjusted based on the temperature change trend, including but not limited to increasing the fan speed in advance or starting additional cooling measures according to the expected working conditions.

4. The method according to claim 3, characterized in that The method further comprises: Determine the key parts corresponding to the target transformer, deploy optical fiber temperature sensors at the key parts to form a continuous temperature monitoring network; The temperature data of key parts are monitored in real time through the temperature monitoring network, and the temperature data is transmitted to the central control system. The central control system processes the received temperature data, forms a temperature distribution diagram, and displays it in real time on the monitoring interface; The temperature threshold of each key part is retrieved, and whether there is a hot spot is detected based on the temperature threshold and the temperature data of the part. If there is a hot spot, an alarm is triggered.

5. The method according to claim 1, characterized in that The method further comprises: Selecting corresponding thermoelectric materials and determining corresponding arrangement positions in the heat dissipation structure of the target transformer; Install the corresponding thermoelectric modules based on the arrangement position, so that one side of the thermoelectric modules contacts the high temperature area and the other side contacts the low temperature area to form a temperature difference; The temperature difference is converted into electrical energy through the thermoelectric module, and the generated electrical energy is stored.

6. The method according to claim 1, characterized in that The method further comprises: The PCM material is encapsulated in a container to form a heat storage unit, and the heat storage unit is integrated into a heat dissipation structure.

7. A transformer heat dissipation structure optimization design device, characterized in that: include: A virtual working environment creation module determines the corresponding target transformer, uses a three-dimensional modeling tool to create a three-dimensional model of the target transformer and the use environment, and uses VR technology to create a virtual working environment corresponding to the target transformer, wherein the virtual working environment includes the physical space where the transformer is located, peripheral equipment and related facilities; A transformer temperature distribution acquisition module selects a target VR platform, imports the three-dimensional model into the target VR platform, sets corresponding platform parameters based on the target transformer, integrates thermal simulation software in a virtual working environment, and performs thermal simulation in the virtual working environment based on the actual heating conditions and working environment conditions corresponding to the target transformer, so as to obtain the transformer temperature distribution of the target transformer under different working conditions in the virtual working environment; A design module is used to design a corresponding multi-layer fin structure based on the temperature distribution of the transformer, obtain the real-time temperature data corresponding to the target transformer in the virtual working environment, and automatically adjust the speed of the cooling fan in the transformer based on the real-time temperature data; wherein the spacing and thickness between each layer of fins are optimized through CFD simulation.

8. An electronic device, characterized in that: include: at least one processor and at least one memory, wherein: The memory has computer-readable instructions stored thereon; The computer-readable instructions are executed by one or more of the processors, so that the electronic device implements the transformer heat dissipation structure optimization design method according to any one of claims 1 to 6.

9. A storage medium having computer-readable instructions stored thereon, characterized in that: The computer-readable instructions are executed by one or more processors to implement the transformer heat dissipation structure optimization design method according to any one of claims 1 to 6.

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