Transformer evaluation method and system

Abstract

The invention discloses a transformer evaluation method and system, and the method comprises the steps: building a simulation model through employing a preset algorithm according to the actual characteristic curve data of a transformer; performing performance calibration on the simulation model based on the actual characteristic curve data to obtain a calibration model; and based on the calibration model, performing performance evaluation on the transformer to obtain an evaluation result. According to the method, the model is subjected to parameter adjustment by comparing the actual characteristic curve data of the product with the output data of the simulation model, the technical problem that the accuracy of the model is reduced due to lack of actual operation data for calibration of the simulation model is solved, and compared with the prior art, the accuracy of the evaluation result of the simulation model is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of simulation evaluation, and in particular to a transformer evaluation method and system. Background Art

[0002] In the vast field of transformer design and application, simulation models are important tools for predicting and optimizing transformer performance. Their accuracy and reliability are directly related to the efficiency and quality of subsequent product development. The calibration process of simulation models is essentially a bridge that closely connects theoretical models with actual physical phenomena. It requires that model parameters can accurately map key performance indicators such as electrical characteristics, thermal behavior, and mechanical stress distribution of real transformers. This process is not only complex, but also highly dependent on high-quality experimental data and operation records.

[0003] However, in reality, it is often difficult to obtain comprehensive and accurate actual operating data. On the one hand, as the core equipment in the power system, the operating environment of the transformer is complex and changeable, from extreme climate conditions to different load requirements, which greatly increases the difficulty of data collection. On the other hand, the complex electromagnetic field distribution, heat conduction path and nonlinear characteristics of the material inside the transformer make it extremely difficult to directly measure certain key parameters (such as local magnetic flux density, hot spot temperature, etc.), and even almost impossible in some cases.

[0004] This data scarcity directly restricts the depth and breadth of the application of simulation models in transformer magnetothermal coupling analysis, electromagnetic loss calculation, and mechanical structure strength assessment. Without sufficient data support, the model may not be able to accurately capture the dynamic response of the transformer under complex working conditions such as transient overload, harmonic pollution, or long-term aging, which in turn affects the accuracy and credibility of the model prediction results. Therefore, how to effectively overcome the difficulty of data acquisition and use limited data resources to optimize model calibration through advanced data analysis techniques (such as machine learning and data mining) has become a key issue that needs to be urgently addressed in the current transformer simulation field. This requires not only interdisciplinary knowledge integration, but also cooperation within and outside the industry to jointly promote technological innovation, in order to achieve more accurate and efficient transformer performance evaluation and optimization in the future. Summary of the invention

[0005] The purpose of this section is to summarize some aspects of embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0006] In view of the above existing problems, the present invention is proposed. Therefore, the present invention provides a transformer evaluation method to solve the problem of inaccurate transformer simulation model evaluation results caused by lack of actual operation data.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0008] In a first aspect, the present invention provides a transformer evaluation method, comprising:

[0009] According to the actual characteristic curve data of the transformer, a simulation model is constructed using a preset algorithm;

[0010] Performing performance calibration on the simulation model based on the actual characteristic curve data to obtain a calibration model;

[0011] Based on the calibration model, a performance evaluation is performed on the transformer to obtain an evaluation result.

[0012] As a preferred solution of the transformer evaluation method of the present invention, wherein: according to the actual characteristic curve data of the transformer, a simulation model is constructed using a preset algorithm, including:

[0013] Constructing a geometric model of the transformer based on the actual characteristic curve data of the transformer;

[0014] Defining and setting attributes of the geometric model to obtain an initial model;

[0015] Based on the initial model, a simulation model is constructed using a preset algorithm.

[0016] As a preferred solution of the transformer evaluation method of the present invention, the simulation model is calibrated based on the actual characteristic curve data to obtain the calibration model, which includes:

[0017] Acquiring model characteristic curve data through the simulation model;

[0018] Comparing and analyzing the model characteristic curve data with the actual characteristic curve data to obtain a comparison result;

[0019] According to the comparison result, the error source of the simulation model is obtained;

[0020] According to the error source, adjusting the parameters of the simulation model to obtain a calibration model;

[0021] As a preferred embodiment of the transformer evaluation method of the present invention, the method further comprises:

[0022] Inputting the actual characteristic curve data into the calibration model to obtain output data;

[0023] Verifying the calibration model according to the output data to obtain a verification result;

[0024] When the verification result shows that the calibration model output is accurate, the model verification is ended;

[0025] When the verification result is a calibration model output deviation, return to the step of performing performance calibration on the simulation model to obtain a calibration model.

[0026] As a preferred solution of the transformer evaluation method of the present invention, wherein: obtaining the model characteristic curve data through the simulation model includes:

[0027] inputting the actual characteristic curve data into the simulation model;

[0028] The simulation model is used to perform simulation calculations to obtain model characteristic curve data.

[0029] As a preferred solution of the transformer evaluation method of the present invention, the transformer is evaluated for performance based on the calibration model, and the evaluation results include:

[0030] Inputting parameter data of the transformer into the calibration model, the parameter data including thermal parameters, loss parameters and structural parameters;

[0031] The calibration model is used to analyze and evaluate the magnetothermal coupling, electromagnetic loss and mechanical structure of the transformer to obtain an evaluation result.

[0032] As a preferred embodiment of the transformer evaluation method of the present invention, the method further comprises:

[0033] When the evaluation result is that the transformer performance has deteriorated, obtaining the current performance data and the standard performance data of the transformer according to the magnetothermal coupling, the electromagnetic loss and the mechanical structure;

[0034] The transformer is updated and maintained according to the current performance data and the standard performance data.

[0035] In a second aspect, the present invention provides a system for transformer evaluation, comprising:

[0036] A model building module is used to build a simulation model using a preset algorithm according to the actual characteristic curve data of the transformer;

[0037] A model calibration module, used to perform performance calibration on the simulation model based on the actual characteristic curve data to obtain a calibration model;

[0038] The simulation evaluation module is used to perform performance evaluation on the transformer based on the calibration model to obtain an evaluation result.

[0039] In a third aspect, the present invention provides a computing device, comprising:

[0040] Memory and processor;

[0041] The memory is used to store computer executable instructions, and the processor is used to execute the computer executable instructions. When the computer executable instructions are executed by the processor, the steps of the transformer evaluation method are implemented.

[0042] In a fourth aspect, the present invention provides a computer-readable storage medium storing computer-executable instructions, which implement the steps of the transformer evaluation method when executed by a processor.

[0043] Compared with the prior art, the present invention has the following beneficial effects: the present invention adjusts the model parameters by comparing the actual characteristic curve data of the product and the output data of the simulation model, thereby solving the technical problem that the accuracy of the model is reduced due to the lack of actual operating data used for simulation model calibration. Compared with the prior art, the accuracy of the simulation model evaluation results is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0045] Figure 1 A schematic diagram of the overall process of a transformer evaluation method according to an embodiment of the present invention;

[0046] Figure 2 A schematic diagram of a simplified geometric model of a transformer and a tower in a transformer evaluation method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0047] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0048] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0049] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0050] The present invention is described in detail with reference to schematic diagrams. When describing the embodiments of the present invention, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0051] At the same time, in the description of the present invention, it should be noted that the orientations or positional relationships indicated by the terms "upper, lower, inner and outer" are based on the orientations or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the system or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first, second or third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0052] In the present invention, unless otherwise clearly specified and limited, the terms "install, connect, connect" should be understood in a broad sense, for example: it can be a fixed connection, a detachable connection or an integral connection; it can also be a mechanical connection, an electrical connection or a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0053] Example 1

[0054] Reference Figure 1-2 , as an embodiment of the present invention, provides a transformer evaluation method, comprising:

[0055] S100: constructing a simulation model using a preset algorithm according to actual characteristic curve data of the transformer;

[0056] Preferably, a geometric model of the transformer is constructed according to actual characteristic curve data of the transformer; attributes of the geometric model are defined and set to obtain an initial model; based on the initial model, a simulation model is constructed using a preset algorithm;

[0057] In the embodiment of the present application, a one-to-one geometric simplified model of the transformer and the tower is constructed based on the actual characteristic curve data of the transformer design manual and relevant national standards, including the number of turns, wire diameter, core characteristics and losses, etc. Figure 2 As shown in the figure, an equivalent simplified model of the core structure such as coil wire, winding, and iron core is constructed inside the transformer;

[0058] In an embodiment of the present application, the geometric model is parameterized to define the size and shape parameters of the model, and to set geometric constraints, such as distance, angle, etc., and to assign attributes, such as material properties, color, transparency, etc., and to perform meshing on the geometric model in preparation for subsequent simulation analysis. The model obtained after the above settings is the initial model.

[0059] It should be noted that the preset algorithm is the finite element analysis method. Finite element analysis (FEA) is a numerical calculation method used to solve engineering and physical problems. Based on the initial model and combined with the finite element simulation requirements, the physical structure and design performance requirements corresponding to the transformer model are constructed to obtain a simulation model that can be used for transformer simulation.

[0060] It should also be noted that the actual characteristic curve data is the actual record of the key characteristic parameter data of the product under different working conditions, such as power, efficiency, etc.; the preset algorithm is the finite element analysis method; the simulation model is a mathematical or computational model used to simulate the real-world system. It imitates the working principles and behavioral characteristics of the real system to predict or analyze the performance of the system under different conditions. It can be used to evaluate the performance of the transformer's magnetic thermal coupling, electromagnetic loss, etc.

[0061] S102: calibrating the performance of the simulation model based on the actual characteristic curve data to obtain a calibrated model;

[0062] Preferably, the model characteristic curve data is obtained through the simulation model; the model characteristic curve data is compared and analyzed with the actual characteristic curve data to obtain a comparison result;

[0063] In the embodiment of the present application, the model characteristic curve data is compared with the actual characteristic curve data, and the comparison content includes the curve trend, the specific value of the data, etc., to obtain a comparison result;

[0064] Preferably, according to the comparison result, the error source of the simulation model is obtained; according to the error source, the parameters of the simulation model are adjusted to obtain a calibration model;

[0065] It should be noted that error sources refer to various factors that affect the accuracy and reliability of data during the process of data collection, processing and analysis.

[0066] According to the comparison results, the error between the performance values ​​of different modules of the transformer output by the simulation model and the actual performance values ​​is obtained. When the error amount reaches a level that can affect the performance of the transformer, the module is used as an error source.

[0067] Preferably, the actual characteristic curve data is input into the calibration model to obtain output data; the calibration model is verified according to the output data to obtain a verification result; when the verification result is that the calibration model output is accurate, the model verification is ended; when the verification result is that the calibration model output is deviant, the step of returning to the performance calibration of the simulation model to obtain the calibration model is performed.

[0068] Specifically, the calibration model is verified according to the output data of the model, and the verification methods include data comparison, error analysis, convergence analysis, etc.; when the verification result is that the output of the calibration model is accurate, the model verification is terminated; after the model is verified, if all data meet the standards, it is determined that the verification result is that the output of the calibration model is accurate, indicating that the performance calibration effect of the model meets the requirements, and the model verification is terminated; when the verification result is the output deviation of the calibration model, return to the step of calibrating the performance of the simulation model to obtain the calibration model.

[0069] After the model is verified, if any of the data does not meet the standard, the verification result is determined to be the calibration model output deviation, and the performance calibration of the simulation model is returned to obtain the calibration model step, and the performance calibration of the simulation model is re-performed.

[0070] Preferably, the actual characteristic curve data is input into the simulation model; the simulation model is used to perform simulation calculations to obtain the model characteristic curve data;

[0071] It should be noted that the simulation characteristic parameter data of the transformer is obtained through simulation calculation, which provides reference conditions for error analysis; performance calibration refers to the adjustment and optimization of model parameters in the fields of machine learning, simulation, statistical models, etc., in order to improve the model's prediction accuracy and generalization ability. Model performance calibration is an iterative process that requires continuous adjustment of model parameters, evaluation of model performance, and optimization according to actual application needs; the calibrated model is a simulation model that has undergone performance calibration.

[0072] It should also be noted that the model characteristic curve data is obtained through the simulation model; the performance of the simulation model is calibrated according to the actual characteristic curve data and the model characteristic curve data to obtain a calibrated model, thereby improving the output accuracy of the model.

[0073] S104: Based on the calibration model, the transformer is evaluated for performance to obtain an evaluation result;

[0074] Preferably, parameter data of the transformer is input into the calibration model, the parameter data including thermal parameters, loss parameters and structural parameters;

[0075] In the embodiment of the present application, the parameter data includes thermal parameters, loss parameters and structural parameters.

[0076] Preferably, the magnetothermal coupling, electromagnetic loss and mechanical structure of the transformer are analyzed and evaluated by means of a calibration model to obtain an evaluation result;

[0077] In an embodiment of the present application, relevant performance data such as magnetothermal coupling, electromagnetic loss and mechanical structure of the transformer are calculated through a calibration model, and the performance of the transformer is evaluated based on the output results of the calculation to obtain an evaluation result. When at least one of the data corresponding to modules such as magnetothermal coupling, electromagnetic loss and mechanical structure in the output data of the calibration model has a large error with the standard data, the evaluation result is determined to be a degradation of transformer performance.

[0078] Preferably, when the evaluation result is that the transformer performance has deteriorated, the current performance data and standard performance data of the transformer are obtained according to the magnetothermal coupling, electromagnetic loss and mechanical structure; the transformer is updated and maintained according to the current performance data and the standard performance data;

[0079] It should be noted that the evaluation results are obtained after analyzing the output data of the simulation model, including normal transformer performance and degraded transformer performance; based on the simulation model after performance calibration, the relevant status data of the transformer is input into the model, and the performance of the transformer can be evaluated and adjusted according to the output results of the model.

[0080] The above is a schematic scheme of a transformer evaluation method of this embodiment. It should be noted that the technical scheme of the transformer evaluation system and the technical scheme of the above transformer evaluation method belong to the same concept, and the details of the technical scheme of the transformer evaluation system in this embodiment that are not described in detail can all be referred to the description of the technical scheme of the above transformer evaluation method.

[0081] In this embodiment, the transformer evaluation system includes:

[0082] A model building module is used to build a simulation model using a preset algorithm according to the actual characteristic curve data of the transformer;

[0083] A model calibration module is used to calibrate the performance of the simulation model based on actual characteristic curve data to obtain a calibrated model;

[0084] The simulation evaluation module is used to evaluate the performance of the transformer based on the calibration model and obtain the evaluation results.

[0085] This embodiment also provides a computing device, which is applicable to transformer evaluation, and includes:

[0086] Memory and processor; the memory is used to store computer executable instructions, and the processor is used to execute computer executable instructions to implement the transformer evaluation method proposed in the above embodiment.

[0087] This embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, the transformer evaluation method proposed in the above embodiment is implemented.

[0088] The storage medium proposed in this embodiment and the transformer evaluation method proposed in the above embodiment belong to the same inventive concept. The technical details not fully described in this embodiment can be referred to the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0089] Through the above description of the implementation methods, the technicians in the relevant field can clearly understand that the present invention can be implemented by means of software and necessary general hardware, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ReadOnly, Memory, ROM), random access memory (RandomAccess Memory, RAM), flash memory (FLASH), hard disk or optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform the methods of various embodiments of the present invention.

[0090] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A transformer evaluation method, characterized in that: include: According to the actual characteristic curve data of the transformer, a simulation model is constructed using a preset algorithm; Performing performance calibration on the simulation model based on the actual characteristic curve data to obtain a calibration model; Based on the calibration model, a performance evaluation is performed on the transformer to obtain an evaluation result.

2. The transformer evaluation method according to claim 1, characterized in that: According to the actual characteristic curve data of the transformer, the simulation model is constructed using the preset algorithm, including: Constructing a geometric model of the transformer based on the actual characteristic curve data of the transformer; Defining and setting attributes of the geometric model to obtain an initial model; Based on the initial model, a simulation model is constructed using a preset algorithm.

3. The transformer evaluation method according to claim 1 or 2, characterized in that: The simulation model is calibrated based on the actual characteristic curve data to obtain a calibration model, including: Acquiring model characteristic curve data through the simulation model; Comparing and analyzing the model characteristic curve data with the actual characteristic curve data to obtain a comparison result; According to the comparison result, the error source of the simulation model is obtained; According to the error source, parameters of the simulation model are adjusted to obtain a calibration model.

4. The transformer evaluation method according to claim 3, characterized in that: Also includes, Inputting the actual characteristic curve data into the calibration model to obtain output data; Verifying the calibration model according to the output data to obtain a verification result; When the verification result shows that the calibration model output is accurate, the model verification is ended; When the verification result is a calibration model output deviation, return to the step of performing performance calibration on the simulation model to obtain a calibration model.

5. The transformer evaluation method according to claim 4, characterized in that: Acquiring model characteristic curve data through the simulation model includes: inputting the actual characteristic curve data into the simulation model; The simulation model is used to perform simulation calculations to obtain model characteristic curve data.

6. The transformer evaluation method according to claim 5, characterized in that: Based on the calibration model, the transformer is evaluated for performance, and the evaluation results include: Inputting parameter data of the transformer into the calibration model, the parameter data including thermal parameters, loss parameters and structural parameters; The calibration model is used to analyze and evaluate the magnetothermal coupling, electromagnetic loss and mechanical structure of the transformer to obtain an evaluation result.

7. The transformer evaluation method according to claim 6, characterized in that: Also includes, When the evaluation result is that the transformer performance has deteriorated, obtaining the current performance data and the standard performance data of the transformer according to the magnetothermal coupling, the electromagnetic loss and the mechanical structure; The transformer is updated and maintained according to the current performance data and the standard performance data.

8. A system for transformer evaluation, characterized in that: include, A model building module is used to build a simulation model using a preset algorithm according to the actual characteristic curve data of the transformer; A model calibration module, used to perform performance calibration on the simulation model based on the actual characteristic curve data to obtain a calibration model; The simulation evaluation module is used to perform performance evaluation on the transformer based on the calibration model to obtain an evaluation result.

9. An electronic device, comprising: Memory and processor; The memory is used to store computer executable instructions, and the processor is used to execute the computer executable instructions. When the computer executable instructions are executed by the processor, the steps of the transformer evaluation method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing computer-executable instructions, wherein the computer-executable instructions, when executed by a processor, implement the steps of the transformer evaluation method according to any one of claims 1 to 7.

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