Electromagnetic transient simulation and mapping method and system for multi-physics field coupling

Abstract

The invention discloses an electromagnetic transient simulation and mapping method and system oriented to multi-physics field coupling, and belongs to the technical field of substation digital operation and maintenance and electromagnetic simulation. Deploying multiple types of sensors in a transformer substation, preprocessing the acquired multi-physical field data, and fusing with the three-dimensional twinborn model; a coupling algorithm is adopted to carry out multi-physical field coupling analysis, multi-physical quantity display and thermodynamic diagram superposition are realized, and scene evolution change simulation under various typical working conditions is supported; a micro-service architecture is adopted to construct a digital twin system, double closed-loop verification of simulation and actual measurement is performed through actual measurement data and simulation data of a real-model test field, model optimization is completed, and real-time mapping of electromagnetic transient dynamic simulation and a transformer substation physical entity is realized. The method improves the precision of model and entity mapping, meets the requirements of real-time tracking and response of the electromagnetic transient change of the transformer substation, adapts to the digital transformation of different transformer substations, and provides a basis for the operation and maintenance of the transformer substations.

Description

Technical Field

[0001] This invention belongs to the field of digital operation and maintenance and electromagnetic simulation technology of substations, specifically involving an electromagnetic transient simulation and mapping method and system for multi-physics coupling. Background Technology

[0002] Currently, many efforts prioritize improving the quality and reliability of IoT sensors for power transmission and transformation systems, with specific improvements implemented across multiple stages, including R&D, production, and selection, to ensure the effectiveness of state sensing for power transmission and transformation equipment. However, the intensity and distribution patterns of the electromagnetic environment in substations are not fully understood, and the electromagnetic compatibility performance requirements for different types and installation locations of sensors are unclear. This leads to sensor susceptibility to interference, frequent failures, and low operational reliability, hindering the effectiveness of state sensing. Existing electromagnetic transient simulation methods tend to focus on single-field analysis, neglecting the coupling effects between electromagnetic fields and multiple fields such as temperature and stress fields. These couplings are crucial for sensor performance degradation. Furthermore, the models used in simulations are mostly offline and static, lacking sufficient real-time mapping accuracy to physical entities, making it impossible to dynamically simulate actual operating conditions and hindering decisions regarding sensor selection, installation, and reliability improvement. Therefore, in summary, current electromagnetic transient simulation methods fail to effectively integrate multi-field coupling effects, rely heavily on offline static modeling, lack sufficient real-time mapping accuracy to physical entities, and cannot dynamically simulate actual operating conditions, thus failing to meet the real-time tracking and response requirements for electromagnetic transient changes in substations. Summary of the Invention

[0003] This invention provides an electromagnetic transient simulation and mapping method and system oriented towards multi-physics coupling. The purpose is to solve the problems in the existing electromagnetic transient simulation methods, which cannot effectively combine multi-field coupling effects, the models are mostly offline static modeling, the real-time mapping accuracy with physical entities is insufficient, and they cannot dynamically simulate actual working conditions, making it difficult to meet the real-time tracking and response requirements of electromagnetic transient changes in substations.

[0004] To achieve the above objectives, the present invention adopts the following technical solution: This invention provides an electromagnetic transient simulation and mapping method for multi-physics coupling, comprising the following steps: S1. Digitally model the physical entity of the substation, and use multi-technology fusion to collect substation equipment and architecture data to build a three-dimensional twin model; Among them, the 3D twin model is either pre-built or updated according to actual needs, and can be called repeatedly; S2. Based on the three-dimensional twin model, deploy multiple types of sensors at preset locations in the substation to build a real-time acquisition network; preprocess the acquired multi-physics field data, and fuse the preprocessed data with the three-dimensional twin model through data assimilation technology to achieve dynamic matching between data and model parameters; S3. Based on the fused data and the 3D twin model, a coupling algorithm is used to perform multiphysics coupling analysis, realize the display of multiple physical quantities and the overlay of heat maps, and support the simulation of scene evolution and changes under various typical working conditions. S4. Based on the results of coupling analysis, a digital twin system is constructed using a microservice architecture. Typical primary equipment in the substation is selected as the verification object. The system performs dual closed-loop verification of simulation and measurement through measured data from a real-world test site and simulation data. This completes model optimization and enables real-time mapping between electromagnetic transient dynamic simulation and the physical entity of the substation.

[0005] In some implementations, in S1, the multi-source data acquisition methods include laser scanning, UAV mapping, and reverse engineering of high-precision CAD drawings; the acquired substation equipment and architecture data include geometric data and three-dimensional material data of the substation equipment and architecture.

[0006] Furthermore, in S1, the accuracy of the 3D twin model satisfies the following formula: ; ; ; in, This refers to the geometric length error between the model's shape and the actual equipment. To account for the position and shape errors of the connecting components, This represents the angular error.

[0007] In some implementations, in S2, the multiple types of sensors include a high-sensitivity broadband electromagnetic sensor, a temperature sensor, and a flow sensor; data preprocessing includes noise filtering, outlier removal, and data standardization; the data standardization formula is as follows: ; in, The original data, The mean of the data. This represents the standard deviation of the data.

[0008] In some implementations, in S2, the data assimilation technique employs the Kalman filter algorithm to achieve dynamic matching between measurement data and model parameters through state equations and observation equations.

[0009] In some implementations, in S3, the multiphysics field includes a magnetic field, a temperature field, and an electric field; the coupling algorithm includes a finite element-boundary element hybrid algorithm that satisfies the field quantity coupling balance equations, including the electric field control equation, the magnetic field control equation, and the temperature field control equation.

[0010] In some implementations, the electric field control equations in S3 include the following formulas: ; in, Where is the dielectric constant. For electric potential, Charge density; The magnetic field control equations include the following formulas: ; in Permeability, For vector magnetic potential, For electrical conductivity, Current density; The temperature field governing equations include the following formulas: ; in, Where c is density and c is specific heat capacity. Let q be the temperature, k be the thermal conductivity, and q be the intensity of the internal heat source.

[0011] In some implementations, the microservice architecture in S4 includes a data acquisition module, a model management module, a simulation calculation module, and a visualization module. These modules communicate via RESTful interfaces. The system is compatible with WebGL, DirectX, and Unity3D modeling standards and supports deployment across Windows and Linux operating systems. The data transmission latency between modules satisfies the following formula: ; in, This represents the time consumed for a single data transfer between modules.

[0012] In some implementations, in S4, typical primary equipment in a substation includes transformers and circuit breakers. Measured data are obtained through transient voltage injection tests; the relative error between model predictions and measured values ​​is controlled within 5%, as per the standard formula below: ; in, These are the model's predicted values. These are measured values.

[0013] This invention also provides an electromagnetic transient simulation and mapping system for multi-physics coupling, used to implement the aforementioned electromagnetic transient simulation and mapping method for multi-physics coupling, including a three-dimensional twin model module, a data model fusion module, a coupling analysis module, and a simulation mapping module, wherein: 3D Twin Model Module: Used for digital modeling of the physical entity of a substation. It uses a combination of multiple technologies to collect substation equipment and architecture data and construct a 3D twin model. Among them, the 3D twin model is either pre-built or updated according to actual needs, and can be called repeatedly; Data model fusion module: Based on a 3D twin model, it deploys multiple types of sensors at preset locations in the substation to build a real-time acquisition network; it preprocesses the acquired multi-physics data, and fuses the preprocessed data with the 3D twin model through data assimilation technology to achieve dynamic matching of data and model parameters; Coupled Analysis Module: Based on the fused data and the 3D twin model, it uses a coupling algorithm to perform multiphysics coupling analysis, realize the display of multiple physical quantities and the overlay of heat maps, and support the simulation of scene evolution and changes under various typical working conditions; Simulation mapping module: Based on the results of coupling analysis, it uses a microservice architecture to build a digital twin system, selects typical primary equipment in the substation as the verification object, and performs dual closed-loop verification of simulation and measurement through real-world test field measured data and simulation data to complete model optimization and realize real-time mapping between electromagnetic transient dynamic simulation and substation physical entities.

[0014] Compared with existing technologies, the electromagnetic transient simulation and mapping method and system for multi-physics coupling of the present invention has the following advantages: This invention presents an electromagnetic transient simulation and mapping method oriented towards multi-physics coupling. Through coupled analysis of magnetic, temperature, and electric fields, it accurately identifies the core influencing factors of sensor performance degradation, compensating for the shortcomings of single-field analysis and breaking free from the constraints of offline static modeling. Through real-time data fusion and dynamic simulation, it realistically simulates the actual operating conditions of substations, solving the problem of insufficient model-physical entity mapping accuracy. The modeling accuracy of this invention reaches the millimeter level, with model geometric errors ≤ ±5mm, connection component position and shape errors ≤ ±3mm, and angular errors ≤ ±3°, providing a precise foundation for simulation analysis. Data processing latency is ≤ 500ms, and inter-module data transmission latency is ≤ 100ms, meeting the real-time tracking and response requirements of electromagnetic transient changes in substations. This invention employs a dual closed-loop verification mechanism of simulation and measurement, controlling the relative error between model predictions and measured values ​​within 5%, ensuring the accuracy of data output. It provides electromagnetic environment zoning and sensor classification schemes, and clarifies sensor selection criteria and installation locations through the analytic hierarchy process, reducing sensor interference and failure probability. This invention supports simulation of at least three typical operating conditions, including normal operation and transient fault conditions, comprehensively covering core substation operation and maintenance scenarios. It helps improve the efficiency of state perception, and the system is compatible with multiple modeling standards such as WebGL and DirectX. It supports deployment across Windows and Linux operating systems and adapts to the digital transformation needs of different substations. It provides data support for the entire process of sensor research and development, production, selection, and installation, responds to the requirements for improving the quality of IoT sensors in power transmission and transformation, and provides intuitive basis for substation operation and maintenance decisions through visualization of multiple physical quantities and scenario evolution simulation, promoting the upgrade of operation and maintenance models to digitalization and intelligence. Attached Figure Description

[0015] The accompanying drawings are provided to further understand the invention and constitute a part of this invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0016] Figure 1 This is a schematic diagram of the flowchart of an electromagnetic transient simulation and mapping method for multi-physics coupling according to the present invention. Figure 2 This is a schematic diagram of the digital modeling framework for an electromagnetic transient simulation and mapping method oriented towards multi-physics coupling according to the present invention. Figure 3 This is a schematic diagram of the data integration and allocation framework for an electromagnetic transient simulation and mapping method oriented towards multi-physics coupling according to the present invention. Figure 4 This is a schematic diagram of the multiphysics coupling analysis framework of an electromagnetic transient simulation and mapping method for multiphysics coupling according to the present invention. Figure 5 This is a schematic diagram of the simulation and real-time mapping verification framework for an electromagnetic transient simulation and mapping method oriented towards multi-physics coupling according to the present invention. Figure 6 This is a schematic diagram of the electromagnetic environment partitioning and sensor classification framework of an electromagnetic transient simulation and mapping method for multi-physics coupling according to the present invention. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can be arranged and designed in various different configurations.

[0018] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to indicate that selected embodiments of the invention are based on the embodiments in this invention. All other embodiments obtained by those skilled in the art without inventive effort are within the scope of protection of this invention. It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, elements defined by the phrase "comprising one..." do not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element. It should be noted that the apparatus and methods disclosed in the embodiments herein can also be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings show the architecture, functions, and operations of possible implementations of apparatus, methods, and computer program products according to various embodiments herein. In this respect, each block in a flowchart or block diagram may represent a module, program, or part 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 marked in the blocks may occur in a different order than those marked in the accompanying drawings. For example, two consecutive 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 a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system to perform the specified function or action, or can be implemented using a combination of dedicated hardware and computer instructions. In addition, the functional modules in the various embodiments of this article can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0019] This paper proposes a method for electromagnetic transient simulation and mapping based on multi-physics coupling, which has the functions of electromagnetic environment zoning and sensor classification. It solves the limitations of existing single-field analysis and static modeling, with a model relative error of ≤5% and a delay that meets real-time requirements. This provides technical support for sensor selection and installation as well as substation operation and maintenance.

[0020] Based on this, the present invention provides an electromagnetic transient simulation and mapping method for multi-physics coupling, comprising the following steps: S1. Digitally model the physical entity of the substation, and use multi-technology fusion to collect substation equipment and architecture data to build a three-dimensional twin model; Among them, the 3D twin model is either pre-built or updated according to actual needs, and can be called repeatedly; S2. Based on the three-dimensional twin model, deploy multiple types of sensors at preset locations in the substation to build a real-time acquisition network; preprocess the acquired multi-physics field data, and fuse the preprocessed data with the three-dimensional twin model through data assimilation technology to achieve dynamic matching between data and model parameters; S3. Based on the fused data and the 3D twin model, a coupling algorithm is used to perform multiphysics coupling analysis, realize the display of multiple physical quantities and the overlay of heat maps, and support the simulation of scene evolution and changes under various typical working conditions. S4. Based on the results of coupling analysis, a digital twin system is constructed using a microservice architecture. Typical primary equipment in the substation is selected as the verification object. The system performs dual closed-loop verification of simulation and measurement through measured data from a real-world test site and simulation data. This completes model optimization and enables real-time mapping between electromagnetic transient dynamic simulation and the physical entity of the substation.

[0021] This invention presents an electromagnetic transient simulation and mapping method for multi-physics coupling. First, it employs multiple technologies, including laser scanning, to construct a millimeter-precision 3D twin model. Then, it deploys data from various types of sensors, preprocesses it, and fuses it with the model using a Kalman filter algorithm. Next, a hybrid finite element-boundary element algorithm is used to complete the coupled analysis and scenario simulation of the magnetic field, temperature field, and electric field. Finally, a system is built based on a microservice architecture, and the model is validated and optimized through a dual closed-loop "simulation-experiment" process. The method also features electromagnetic environment zoning and sensor classification capabilities, overcoming the limitations of existing technologies in single-field analysis and static modeling. The model's relative error is ≤5%, and the latency meets real-time requirements, providing support for sensor selection and installation, as well as substation operation and maintenance.

[0022] This invention also provides an electromagnetic transient simulation and mapping system for multiphysics coupling, including a three-dimensional twin model module, a data model fusion module, a coupling analysis module, and a simulation mapping module, wherein: 3D Twin Model Module: Used for digital modeling of the physical entity of a substation. It uses a combination of multiple technologies to collect substation equipment and architecture data and construct a 3D twin model. Among them, the 3D twin model is either pre-built or updated according to actual needs, and can be called repeatedly; Data model fusion module: Based on a 3D twin model, it deploys multiple types of sensors at preset locations in the substation to build a real-time acquisition network; it preprocesses the acquired multi-physics data, and fuses the preprocessed data with the 3D twin model through data assimilation technology to achieve dynamic matching of data and model parameters; Coupled Analysis Module: Based on the fused data and the 3D twin model, it uses a coupling algorithm to perform multiphysics coupling analysis, realize the display of multiple physical quantities and the overlay of heat maps, and support the simulation of scene evolution and changes under various typical working conditions; Simulation mapping module: Based on the results of coupling analysis, it uses a microservice architecture to build a digital twin system, selects typical primary equipment in the substation as the verification object, and performs dual closed-loop verification of simulation and measurement through real-world test field measured data and simulation data to complete model optimization and realize real-time mapping between electromagnetic transient dynamic simulation and substation physical entities.

[0023] The present invention will be further described in detail below through specific embodiments.

[0024] like Figures 1-6 As shown, this invention provides an electromagnetic transient simulation and mapping method based on multi-physics coupling. Step S1: Digital modeling of the physical entity of the substation. This involves using a combination of technologies such as laser scanning, UAV mapping, and reverse engineering of high-precision CAD drawings to collect core data such as the geometric dimensions and three-dimensional material appearance of the equipment and structure within the substation. Algorithms such as point cloud processing and surface reconstruction are used to construct a detailed three-dimensional twin model with millimeter-level accuracy, ensuring a high degree of consistency with the actual physical entity of the substation. Step S2: Multi-physics data integration and allocation in substations. High-sensitivity, wide-bandwidth electromagnetic sensors, temperature sensors, flow sensors, and other types of physical field monitoring equipment are deployed at key locations in the substation to build a real-time data acquisition network covering the entire station. The measurement data is transmitted to the digital twin system in real time. After preprocessing the acquired data, such as noise filtering, outlier removal, and data standardization, data assimilation technology is used to fuse the multi-physics measurement data with the digital twin model. The model parameters and boundary conditions are adjusted in real time to achieve dynamic real-time allocation of the electromagnetic field in the substation. Step S3: Multi-physics coupling analysis of substations. This step integrates multi-physics coupling algorithms to achieve intuitive display of physical quantity data such as magnetic field, temperature field, and electric field on the platform. It also overlays and displays the intensity distribution heat map of various physical quantities around the equipment, supporting the simulation of physical scene evolution and changes under different time periods or typical operating conditions such as normal operation and fault transients. At the same time, it optimizes the data transmission and processing efficiency of the platform to ensure real-time data processing and rapid model updates, meeting the real-time data display needs of substations. Step S4: Electromagnetic transient dynamic simulation and real-time mapping verification. A highly scalable and reliable digital twin system is built based on a microservice architecture. The system functions are broken down into multiple independent modules such as data acquisition, model management, simulation calculation, and visualization, which facilitates subsequent upgrades and maintenance. Typical primary equipment such as transformers and circuit breakers in a real-world outdoor test field are selected as verification objects. Measured data is obtained through transient voltage injection tests and compared with simulation data to complete model verification and optimization, ensuring the accuracy and reliability of the model.

[0025] Furthermore, the multi-technology fusion methods in step S1 include laser scanning, UAV mapping, and reverse engineering of high-precision CAD drawings. Data processing employs point cloud processing and surface reconstruction algorithms. The geometric accuracy error of the model is less than ±5mm, the position and shape error of the connecting parts is less than ±3mm, and the angle error is less than ±3. Its standardized formula is: ; ; ; in, This refers to the geometric length error between the model's shape and the actual equipment. To account for the position and shape errors of the connecting components, This refers to the angular error of the connecting components.

[0026] Furthermore, in step S2, the sensors include a high-sensitivity broadband electromagnetic sensor, a temperature sensor, and a flow sensor. The data acquisition network covers key areas of the substation. Data preprocessing includes noise filtering, outlier removal, and data standardization. The data standardization formula is: ; in, The original data, The mean of the data. The standard deviation of the data; Data assimilation techniques employ the Kalman filter algorithm, through the state equation: + ; With observation equations: ; To achieve dynamic matching between measurement data and model parameters, in, Let A be the system state at time k, A be the state transition matrix, and B be the control input matrix. To control the input, For process noise, Here, H represents the observed values, and H is the observation matrix. To observe noise.

[0027] Furthermore, in step S3, the multiphysics fields include magnetic field, temperature field, and electric field. The coupling analysis employs a finite element-boundary element hybrid algorithm, satisfying the field quantity coupling equilibrium equations: Electric field governing equations: ; in, Where is the dielectric constant. For electric potential, Charge density; Magnetic field control equations: ; in, Permeability, For vector magnetic potential, For electrical conductivity, For current density, For time; Temperature field governing equations: ; in, For density, For specific heat capacity, For temperature, Thermal conductivity, Intensity of the internal heat source; The aim is to employ adaptive mesh rendering technology, and the scene evolution simulation should support at least three typical operating conditions, including normal operation and transient fault states, while ensuring that data processing latency meets the following requirements: ( (Total latency from data acquisition to result display).

[0028] Furthermore, the microservice architecture in step S4 includes four core modules: data acquisition, model management, simulation calculation, and visualization. These modules communicate via RESTful interfaces. The system is compatible with modeling standards such as WebGL, DirectX, and Unity3D, supports deployment across Windows and Linux operating systems, and ensures that data transmission latency between modules meets the following requirements: ( (Time consumed for a single data transfer between modules).

[0029] Furthermore, in step S4, the real-time mapping verification adopts a dual closed-loop mechanism of "simulation-experimental measurement." Typical primary equipment such as transformers and circuit breakers from a real-world outdoor test site are selected as verification objects. Measured data is obtained through transient voltage injection tests. The relative error between the model prediction and the measured value is controlled within 5%, and its standard formula is: ; in, These are the model's predicted values. These are measured values.

[0030] Furthermore, it also includes substation transient electromagnetic environment zoning and sensor classification functions. Based on the coupling analysis results, a zoning evaluation index system is constructed, and the analytic hierarchy process (AHP) is used to determine the sensor classification thresholds. The classification weights are calculated to satisfy the following: ; in, For the first The weight of each evaluation indicator, For the first The eigenvector components of the judgment matrix for each indicator, where n is the total number of evaluation indicators, provide a basis for sensor selection and installation location optimization.

[0031] The working principle of the electromagnetic transient simulation and mapping method for multi-physics coupling in this invention is as follows: This invention constructs a high-precision digital twin foundation for physical entities, employing a fusion of multiple technologies including laser scanning, UAV mapping, and reverse engineering from high-precision CAD drawings to comprehensively collect core data such as the geometric dimensions, material properties, and appearance of substation equipment and architecture. The data is processed through point cloud processing and surface reconstruction algorithms to construct a 3D twin model with millimeter-level precision. The geometric accuracy error of the model is ≤±5mm, and the error related to connecting components is ≤±3mm, ensuring a high degree of consistency between the digital model and the physical entity, providing a precise geometric and physical foundation for subsequent simulation and mapping.

[0032] The method of this invention achieves dynamic matching between real-time data and the model through data integration and allocation. Multiple types of sensors, including electromagnetic, temperature, and flow sensors, are deployed at key locations in the substation to build a real-time acquisition network covering the entire station. After noise filtering, outlier removal, and data standardization preprocessing, the acquired data is dynamically fused with the digital twin model using state equations and observation equations constructed through the Kalman filter algorithm. This allows for real-time adjustment of model parameters and boundary conditions, enabling the digital model to respond in real-time to changes in the state of physical entities.

[0033] The method of this invention performs multiphysics coupling analysis to reconstruct the complex evolution of electromagnetic transients. It integrates a finite element-boundary element hybrid algorithm to perform coupled calculations on electric, magnetic, and temperature fields, ensuring the accuracy of the analysis through corresponding field quantity coupling balance equations. Adaptive mesh rendering technology is used to generate heatmaps of physical quantity intensity distribution, intuitively presenting the multiphysics distribution. It also supports scenario evolution simulations for at least three typical operating conditions, including normal operation and fault transients, with a data processing latency of ≤500ms, enabling real-time tracking and dynamic simulation of electromagnetic transient changes. Finally, this invention verifies accuracy and reliability through simulation and mapping, ensuring this accuracy and reliability through a closed-loop mechanism. A digital twin system is built based on a microservice architecture, comprising four core modules: data acquisition, model management, simulation calculation, and visualization. These modules communicate via RESTful interfaces, with data transmission latency ≤100ms, ensuring efficient system operation. Employing a dual closed-loop mechanism of simulation and field measurement, the invention selects transformers, circuit breakers, and other equipment from a real-world test site. Measured data is obtained through transient voltage injection tests and compared with simulation results. The relative error between model predictions and measured values ​​is controlled within 5%, continuously optimizing the model to achieve accurate real-time mapping between digital simulation and physical entities.

[0034] Furthermore, this invention can also employ additional functional support to optimize sensor deployment and operation and maintenance decisions. Based on the results of multi-physics coupling analysis, it constructs a substation transient electromagnetic environment zoning evaluation index system and uses the analytic hierarchy process (AHP) to determine sensor classification thresholds and weights, providing data support for the scientific selection of sensors and optimization of installation locations. This further improves the reliability of substation status perception and, in turn, ensures the data input quality of the entire simulation and mapping system, thus possessing certain practical significance.

[0035] Finally, it should be noted that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Anyone skilled in the art can readily implement the present invention according to the description and above. Any modifications, alterations, or equivalent variations made using the technical content disclosed above are equivalent embodiments of the present invention. Furthermore, any modifications, alterations, or variations made to the above embodiments based on the essential technology of the present invention are still within the protection scope of the present invention.

Claims

1. A method for multi-physical field coupling oriented electromagnetic transient simulation and mapping, characterized in that, Comprise the following steps: S1, the physical entity of the transformer substation is digitally modeled, the multi-technology fusion means is used to collect the data of the equipment and architecture of the transformer substation, and a three-dimensional twin model is constructed; Among them, the three-dimensional twin model is constructed in advance or updated according to actual needs, and can be repeatedly called; S2, based on the three-dimensional twin model, a plurality of types of sensors are deployed at the preset positions of the transformer substation, and a real-time acquisition network is constructed; the preprocessed multi-physical field data is fused with the three-dimensional twin model through data assimilation technology, and dynamic matching of data and model parameters is realized; S3, based on the fused data and the three-dimensional twin model, a coupling algorithm is used for multi-physical field coupling analysis, multi-physical quantity display and thermal map superposition are realized, and scene evolution change simulation under multiple typical working conditions is supported; S4, based on the results of the coupling analysis, a digital twin system is constructed using a micro-service architecture, a typical primary equipment of the transformer substation is selected as a verification object, a simulation and a real measurement double closed loop verification are performed through real test field measured data and simulation data, model optimization is completed, and real-time mapping of electromagnetic transient dynamic simulation and the physical entity of the transformer substation is realized.

2. The method of claim 1, wherein, In the S1, the multi-source data acquisition means includes laser scanning, unmanned aerial vehicle surveying and mapping, and high-precision CAD drawing reverse engineering means; the collected data of the equipment and architecture of the transformer substation includes geometric data and three-dimensional material data of the equipment and architecture of the transformer substation.

3. The method of claim 2, wherein, In the S1, the accuracy of the three-dimensional twin model satisfies the following formula: ； ； ； wherein, is the geometric length error of the model shape to the actual device, is the position shape error of the connecting part, is the angle error.

4. The method of claim 1, wherein, In the S2, the plurality of types of sensors include high-sensitivity wide-band electromagnetic sensors, temperature sensors and flow sensors; the data preprocessing includes noise filtering, outlier rejection and data standardization; the data standardization formula is as follows: ； wherein, is the original data, is the data mean, is the data standard deviation.

5. The method of claim 1, wherein, In the S2, the data assimilation technology uses Kalman filter algorithm to realize dynamic matching of measured data and model parameters through state equation and observation equation.

6. The method of claim 1, wherein, In the S3, the multi-physical field includes magnetic field, temperature field and electric field; the coupling algorithm includes finite element-boundary element hybrid algorithm, and satisfies the field quantity coupling balance equation including electric field control equation, magnetic field control equation and temperature field control equation.

7. The method of claim 1, wherein, In the S3, the electric field control equation includes the following formula: ； wherein, is the dielectric constant, is the electric potential, is the charge density; The magnetic field control equation includes the following formula: ； where μ is the magnetic permeability, is the vector magnetic potential, is the electric conductivity, is the current density, is time; The temperature field control equation includes the following formula: ； wherein, is the density, c is the specific heat capacity, is the temperature, k is the thermal conductivity, q is the internal heat source intensity.

8. The method of claim 1, wherein, In the S4, the micro-service architecture includes a data acquisition module, a model management module, a simulation calculation module and a visualization presentation module, each module communicates through a RESTful interface, the system is compatible with WebGL, DirectX and Unity3D modeling standards, and supports cross-Windows, Linux operating system deployment; the data transmission delay between modules satisfies the following formula: ； wherein, is the time spent for a single data transfer between modules.

9. The method of claim 1, wherein, In the S4, the typical primary equipment of the transformer substation includes a transformer and a circuit breaker, and the measured data is obtained through a transient voltage injection test; the relative error between the model prediction value and the measured value is controlled within 5%, and the standard formula is as follows: ； wherein, is the model predicted value, is the measured value.

10. A multi-physical field coupling oriented electromagnetic transient simulation and mapping system, characterized in that, The electromagnetic transient simulation and mapping method for multi-physical field coupling according to any one of claims 1-9 comprises a three-dimensional twin model module, a data model fusion module, a coupling analysis module, and a simulation mapping module, wherein: The three-dimensional twin model module is used for digital modeling of physical entities of a substation, adopts multi-technology fusion means to collect substation equipment and architecture data, and constructs a three-dimensional twin model; The three-dimensional twin model is pre-constructed or updated according to actual requirements, and can be repeatedly called; The data model fusion module is used for deploying multiple types of sensors at preset positions of the substation based on the three-dimensional twin model, constructing a real-time acquisition network, pre-processing the collected multi-physical field data, and fusing the pre-processed data with the three-dimensional twin model through data assimilation technology to realize dynamic matching of data and model parameters; The coupling analysis module is used for multi-physical field coupling analysis based on the fused data and the three-dimensional twin model, using a coupling algorithm to realize multi-physical quantity display and thermal map superposition, and supporting scene evolution change simulation under multiple typical working conditions; The simulation mapping module is used for constructing a digital twin system based on the results of the coupling analysis, selecting typical primary equipment of the substation as a verification object, and performing double closed-loop verification of simulation and actual measurement through real test field measured data and simulation data, completing model optimization, realizing electromagnetic transient dynamic simulation, and real-time mapping of the substation physical entities.

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