Digital twinborn model calculation method considering magnetic thermal fluid field coupling of high-voltage reactor

Abstract

The invention discloses a digital twinborn model calculation method considering high-voltage reactor magnetic thermal fluid field coupling. The main heat source for heating in the working process of the high-voltage reactor is loss, and when the loss of an iron core is calculated, the hysteresis characteristic of a material needs to be considered firstly. According to the method, a Jiles-Atherton model (J-A model) is utilized to analyze hysteresis characteristics of an iron core, then a magnetic field of the high-voltage reactor is simulated, and a magnetic-thermal coupling finite element analysis model of the high-voltage reactor is established. And finally, calculating a heat source of the electric reactor based on a loss calculation method of the hysteresis characteristic of the iron core, and simulating a temperature field of the electric reactor. The hysteresis model constructed on the basis of the J-A model is convenient to solve, and the loss of the high-voltage reactor can be better predicted and analyzed by combining temperature field calculation simulation of the reactor. The loss of the reactor is calculated based on the method, the method can be used for realizing digital twinning of the high-voltage reactor, and the operation condition of the high-voltage reactor is accurately evaluated.

Description

Technical Field

[0001] The present invention belongs to the field of power equipment condition assessment, and particularly relates to the field of real-time calculation of high-voltage reactor losses. Background Art

[0002] To better adapt to the higher power demand brought about by the rapid growth of the domestic economy and the increasing national consumption level, China's power grid has been significantly upgraded in terms of transmission distance, transmission capacity, and voltage level. The rapid expansion of the grid scale has led to more line losses of reactive power in the power system during power transmission under the action of high voltage levels. Reactors have inductive characteristics and play a key role in compensating reactive power, suppressing power frequency voltage and switching overvoltage in the circuit, and improving the power supply quality of the grid. The losses of iron-core reactors are inevitable during their operation, and the losses will be dissipated in the form of heat, which will cause the temperature of the reactor to rise and affect its normal operation. In modern power systems, the connected loads are gradually diversified, bringing a large number of harmonics to the grid. To ensure the stable operation of the reactor, it is necessary to grasp its dynamic and thermal stability, and the first step in analyzing this problem is to study the magnetic field problem of the reactor. By studying the hysteresis characteristics of ferromagnetic materials, the main sources of iron-core reactor losses can be understood. The calculation of losses is the prerequisite for temperature field calculation and also the basic work for maintaining the safe operation of the reactor. Based on the analysis of losses, the temperature field analysis of the reactor is carried out, which is of great significance for realizing the safe, stable, and economic operation of the power grid.

[0003] After retrieval, the application publication number CN114218821A discloses a calculation method for mechanical fatigue of a three-dimensional finite element multi-physical field high-voltage shunt reactor, including the steps of: obtaining the mechanical structure parameters and electrical parameters of the reactor; establishing a three-dimensional finite element model including the iron core, winding, oil tank, and clamping parts according to the mechanical structure parameters and electrical parameters of the reactor; setting the parameters of the three-dimensional finite element model; setting the physical field; calculating the magnetic field distribution inside the high-voltage shunt reactor; calculating the magnetostriction distribution of the iron core; calculating the Maxwell stress tensor of the iron core cake; calculating the Lorentz force of the winding; calculating the vibration stress of the high-voltage shunt reactor oil tank; applying the calculated vibration stress to the reactor to obtain the calculation result of the deformation amount of the reactor structural parts under the action of the magnetic field effect, and generating a stress distribution diagram; observing the stress distribution diagram, calculating the parts of the reactor structural parts that are prone to mechanical fatigue, and predicting the possible positions of mechanical failures after the equipment is put into operation.

[0004] In the prior art, Patent CN114218821A proposes a calculation method for mechanical fatigue of a three-dimensional finite element multi-physical field high-voltage shunt reactor, which mainly focuses on the mechanical fatigue problem of the reactor. By calculating parameters such as magnetic field distribution, magnetostriction distribution, and Maxwell stress tensor, the mechanical fatigue parts of the reactor structural parts are predicted. The patent has the following deficiencies:

[0005] 1. Failure to consider hysteresis characteristics: This patent does not cover the hysteresis characteristics of the iron core material, resulting in inaccurate calculation of iron core losses and inability to accurately reflect the actual loss situation of the reactor under alternating magnetic fields.

[0006] 2. Lack of multi-physics field coupling analysis: This patent mainly focuses on mechanical fatigue problems and does not fully consider the coupling effects of magnetic field, temperature field, and fluid field, making it impossible to comprehensively evaluate the thermal stability and cooling effect of the reactor.

[0007] 3. Failure to integrate with the Internet of Things (IoT) platform: This patent does not combine the calculation results with the IoT platform, precluding real-time monitoring of the reactor's operating status and digital twin implementation.

[0008] The present invention overcomes the above deficiencies in the following ways:

[0009] 1. Introduction of the Jiles-Atherton hysteresis model: The Jiles-Atherton (J-A) model is used to accurately simulate the hysteresis characteristics of the iron core material. Combining with the loss separation theory, the total iron core losses are precisely calculated, providing a reliable basis for the thermal stability analysis of the reactor.

[0010] 2. Multi-physics field coupling analysis: The present invention combines the magnetic-thermal-fluid coupling analysis method to comprehensively consider the interactions of multiple physical fields such as magnetic field, heat generation and transfer, and fluid cooling effect during the operation of the reactor, improving the accuracy and reliability of condition assessment.

[0011] 3. Integration with the IoT platform: The calculation results of the finite element model are exported and uploaded in a format supported by the IoT platform, enabling real-time monitoring of the operating status of high-voltage reactors and digital twin implementation, providing timely and accurate data support for the operation and maintenance of power systems. Summary of the Invention

[0012] The present invention aims to solve the problems of the above prior art. A digital twin model calculation method considering the coupling of magnetic-thermal-fluid fields of high-voltage reactors is proposed. The technical solution of the present invention is as follows:

[0013] A digital twin model calculation method considering the coupling of magnetic-thermal-fluid fields of high-voltage reactors, comprising the following steps:

[0014] a) Use the Jiles-Atherton hysteresis model (J-A model) to simulate the hysteresis characteristics of the iron core, and combine with the loss separation theory to construct a dynamic hysteresis model for calculating the total iron core losses;

[0015] b) Combine the J-A hysteresis model with the basic equations of the electromagnetic field to construct a finite element model for calculating the magnetic field distribution of high-voltage reactors;

[0016] c) Using the results of the finite element model of the reactor magnetic field in step b), combined with the magneto-thermal-fluid coupling analysis method, construct a finite element model that can fit the losses and temperature field of the high-voltage reactor, and upload it to the Internet of Things platform to achieve the digital twin of the high-voltage reactor.

[0017] 2. The method for constructing a hysteresis model according to claim 1, wherein the Jiles-Atherton model can accurately simulate the hysteresis loop of ferromagnetic materials within an alternating magnetization cycle, and the area of the hysteresis loop corresponds to the core loss.

[0018] Further, the core loss includes hysteresis loss and dynamic loss, where the hysteresis loss is directly calculated by the J-A model, and the dynamic loss is calculated through the anhysteretic magnetization curve, and the anhysteretic magnetization curve is expressed as: where M an is the anhysteretic magnetization intensity, M s is the saturation magnetization intensity, H is the magnetic field intensity, a represents a parameter related to the shape of the anhysteretic magnetization curve, and α is the parameter of the magnetization intensity coupling between magnetic domains.

[0019] Further, for the anhysteretic magnetization curve, a total magnetization equation for static hysteresis loss is constructed according to the law of conservation of energy,

[0020]

[0021] where M = M irr + M rev , M irr represents the irreversible magnetization component, M rev represents the reversible magnetization component, c represents the reversible magnetization coefficient, δ is the positive and negative direction coefficient that changes with time, and k represents the change in the energy lost by each magnetic domain unit during magnetization.

[0022] Further, in step b), a finite element model for calculating the magnetic field distribution of the high-voltage reactor is constructed by combining the J-A hysteresis model and the basic equations of electromagnetic fields, specifically including:

[0023] Conduct a simulation study on the magnetic field distribution of the reactor under the working conditions; among them, the differential form of the Maxwell basic equations of electromagnetic fields is: where, H represents the magnetic field intensity (A / m); J represents the current density (A / m 2 ); E represents the electric field intensity (V / m); B represents the magnetic induction intensity (T); D represents the electric flux density (C / m 2 ); ρ represents the charge density (C / m 3 ).

[0024] Further, in step c), using the results of the finite element model of the reactor magnetic field in step b) and combining the magneto-thermal-fluid coupling analysis method, a finite element model capable of fitting the losses and temperature field of the high-voltage reactor is constructed, specifically including: For the magneto-thermal-fluid coupling analysis method, first, magneto-thermal coupling analysis is performed. In the three-dimensional field, the magnetic field and eddy current field are analyzed using the finite element method. The basic equations based on the A-φ method are as follows: A is the magnetic vector potential; φ is the electric scalar potential; σ is the electrical conductivity; v is the magnetic resistivity; J0 is the current density of the coil.

[0025] Further, after the magneto-thermal coupling analysis, magneto-thermal-fluid coupling is analyzed. Considering the natural convection situation, it is analyzed using the Navier-Stokes equation with penalty function: where v represents the vector of fluid velocity; g = 9.8 m / s 2 ; η is the fluid viscosity coefficient; β is the fluid extension coefficient; α represents the penalty number, is the time derivative, T is the absolute temperature (K), T0 is the initial temperature, and ρ0 is the mass density at temperature T0.

[0026] Further, the calculation results of the finite element model are exported and uploaded in a format supported by the Internet of Things platform to realize real-time monitoring of the magneto-thermal-fluid coupling state of the high-voltage reactor, so as to serve the digital twin and condition assessment of the high-voltage reactor.

[0027] The advantages and beneficial effects of the present invention are as follows:

[0028] The innovation points of the present invention are mainly reflected in the following steps and the beneficial effects brought by these steps. These innovation points are not easy to think of because they combine the coupling problems of multiple complex physical fields with digital twin technology and the Internet of Things platform, realizing the accurate assessment of the operating state of the high-voltage reactor. This combination requires interdisciplinary knowledge and innovative thinking.

[0029] Innovation points and beneficial effects

[0030] 1. Using the Jiles-Atherton hysteresis model to simulate the hysteresis characteristics of the iron core

[0031] Beneficial effect: The J-A model can accurately describe the hysteresis phenomenon of ferromagnetic materials under alternating magnetic fields, providing a scientific basis for accurately calculating the total losses of the iron core of the high-voltage reactor. This makes the calculation of iron core losses more accurate, helping to more accurately predict the thermal stability and lifespan of the reactor under different operating conditions.

[0032] The construction of the hysteresis model requires an in-depth understanding of the microscopic magnetization mechanism and complex magnetization process of the material, and the parameterization method of the J-A model is relatively complex and not easily directly applied to the real-time condition assessment of high-voltage reactors.

[0033] 2. Construct a finite element model by combining the magneto-thermal-fluid coupling analysis method

[0034] Beneficial effects: Through magneto-thermal-fluid coupling analysis, it is possible to comprehensively consider the interaction of multiple physical fields such as the magnetic field, heat generation and transfer, and fluid cooling effect during the operation of high-voltage reactors, improving the accuracy and reliability of condition assessment.

[0035] The multi-physical field coupling analysis of high-voltage reactors needs to solve complex physical problems and high-precision numerical simulation problems. The implementation of this cross-field coupling analysis method requires a profound understanding of electromagnetics, thermodynamics, fluid mechanics, and numerical calculation methods, and also requires the development or use of high-performance computing platforms to support this coupling analysis.

[0036] 3. Combine the calculation model with the Internet of Things platform

[0037] Beneficial effects: Combining the calculation model based on finite element analysis with the Internet of Things platform can realize the real-time monitoring of the operating state of high-voltage reactors, provide timely and accurate data support for the operation and maintenance of the power system, and improve the operation efficiency and safety of the power grid.

[0038] Combining highly specialized physical field calculation models with Internet of Things technology requires overcoming technical challenges such as data transmission, protocol compatibility, and real-time performance, and requires the calculation model to be able to respond quickly to meet the needs of online monitoring and analysis, which is relatively rare in the monitoring of traditional power equipment.

[0039] Summary

[0040] The innovation of the present invention lies in the comprehensive application of the J-A hysteresis model, multi-physical field coupling finite element analysis method, and Internet of Things technology to achieve real-time and accurate assessment of the operating state of high-voltage reactors. The proposal of this method not only requires an in-depth understanding of the modeling methods of each physical field but also requires cross-disciplinary technical integration capabilities, so it is not easily thought of, but it has important value for the operation management and condition assessment of high-voltage reactors and even the entire power system. Description of the Drawings

[0041] Figure 1 It is a flowchart for implementing the digital twin model considering the magneto-thermal-fluid multi-physical field coupling of the high-voltage reactor provided by the preferred embodiment of the present invention;

[0042] Figure 2 It is a flowchart of magneto-thermal-fluid coupling analysis. Detailed Implementation Manner

[0043] Next, in combination with the accompanying drawings in the embodiments of the present invention, the technical solutions in the embodiments of the present invention will be clearly and detailedly described. The described embodiments are only a part of the embodiments of the present invention.

[0044] The technical solution for the present invention to solve the above technical problems is:

[0045] As Figure 1 and 2 shown, a digital twin model calculation method considering the coupling of the magnetic-thermal fluid field of a high-voltage reactor includes the following steps:

[0046] a) Use the Jiles-Atherton hysteresis model (J-A model) to simulate the hysteresis characteristics of the iron core, and combine the loss separation theory to construct a dynamic hysteresis model to calculate the total iron core loss;

[0047] b) Combine the J-A hysteresis model with the basic equations of the electromagnetic field to construct a finite element model for calculating the magnetic field distribution of the high-voltage reactor;

[0048] c) Utilize the results of the reactor magnetic field finite element model in step b), combine the magnetic-thermal fluid coupling analysis method, construct a finite element model that can fit the losses and temperature field of the high-voltage reactor, and upload it to the Internet of Things platform to achieve the digital twin of the high-voltage reactor.

[0049] 2. The method for constructing a hysteresis model according to claim 1, wherein the Jiles-Atherton model can accurately simulate the hysteresis loop of ferromagnetic materials within an alternating magnetization cycle, and the area of the hysteresis loop corresponds to the iron core loss.

[0050] Furthermore, the iron core loss includes hysteresis loss and dynamic loss, wherein the hysteresis loss is directly calculated by the J-A model, and the dynamic loss is calculated through the non-hysteretic magnetization curve, and the non-hysteretic magnetization curve is expressed as: where M an is the non-hysteretic magnetization intensity, M s is the saturation magnetization intensity, H is the magnetic field intensity, a represents a parameter related to the shape of the non-hysteretic magnetization curve, and α is the parameter of the magnetization intensity coupling between magnetic domains.

[0051] Preferably, for the non-hysteretic magnetization curve, a static hysteresis loss total magnetization equation is constructed according to the law of conservation of energy,

[0052]

[0053] where M = M irr + M rev , M irr represents the irreversible magnetization component, M revIt represents the reversible magnetization component, c represents the reversible magnetization coefficient, δ is the positive and negative direction coefficient varying with time, and k represents the change in the energy lost by each magnetic domain unit during magnetization.

[0054] Preferably, in step b), the J-A hysteresis model is combined with the basic equations of the electromagnetic field to construct a finite element model for calculating the magnetic field distribution of the high-voltage reactor, specifically including:

[0055] Carry out a simulation study on the magnetic field distribution of the reactor under the working conditions; among them, the differential form of the Maxwell basic equations of the electromagnetic field is: Among them, H represents the magnetic field strength (A / m); J represents the current density (A / m 2 ); E represents the electric field strength (V / m); B represents the magnetic induction intensity (T); D represents the electric flux density (C / m 2 ); ρ represents the charge density (C / m 3 ).

[0056] Preferably, in step c), using the results of the finite element model of the reactor magnetic field in step b), combined with the magneto-thermal-fluid coupling analysis method, construct a finite element model that can fit the losses and temperature field of the high-voltage reactor, specifically including: The magneto-thermal-fluid coupling analysis method first requires magneto-thermal coupling analysis. In a three-dimensional field, the finite element method is used to analyze the magnetic field and eddy current field. The basic equation based on the A-φ method is as follows: A is the magnetic vector potential; φ is the electric scalar potential; σ is the conductivity; v is the magnetic resistivity; J0 is the current density of the coil.

[0057] Preferably, after the magneto-thermal coupling analysis, then analyze the magneto-thermal-fluid coupling. Considering the natural convection situation, use the Navier-Stokes equation with penalty function to analyze it: Among them, v represents the vector of the fluid velocity; g = 9.8m / s 2 ; η is the fluid viscosity coefficient; β is the fluid extension coefficient; a represents the penalty number, is the time derivative, T is the absolute temperature (K), T0 is the initial temperature, and ρ0 is the mass density at the temperature of T0.

[0058] Preferably, the calculation results of the finite element model are exported and uploaded in a format supported by the Internet of Things platform to realize real-time monitoring of the magneto-thermal-fluid coupling state of the high-voltage reactor, so as to serve the digital twin and condition assessment of the high-voltage reactor.

[0059] The systems, devices, modules, or units illustrated in the above embodiments can be specifically implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer can be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or any combination of these devices.

[0060] Computer-readable media includes both permanent and non-permanent, removable and non-removable media and can store information by any method or technology. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transitory media that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media such as modulated data signals and carrier waves.

[0061] It should also be noted that the term "comprising", "including", or any other variant thereof is intended to cover non-exclusive inclusion, such that a process, method, commodity, or device comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, commodity, or device. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, commodity, or device comprising the element.

[0062] The above embodiments should be understood as being only for illustrative purposes of the present invention and not for limiting the protection scope of the present invention. After reading the content recorded in the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent changes and modifications also fall within the scope defined by the claims of the present invention.

Claims

1. A digital twin model calculation method considering the magnetothermal fluid field coupling of a high-voltage reactor, characterized in that: The following steps are involved: a) Use the Jiles-Atherton hysteresis model (JA model) to simulate the hysteresis characteristics of the core, and build a dynamic hysteresis model in combination with the loss separation theory to calculate the total loss of the core; b) Combining the JA hysteresis model with the basic electromagnetic field equation, a finite element model for calculating the magnetic field distribution of the high-voltage reactor is constructed; c) Using the reactor magnetic field finite element model results of step b), combined with the magnetic-thermal fluid coupling analysis method, a finite element model capable of fitting the high-voltage reactor loss and temperature field is constructed, and uploaded to the Internet of Things platform to realize the digital twin of the high-voltage reactor.

2. The digital twin model calculation method considering the magnetothermal fluid field coupling of the high-voltage reactor according to claim 1 is characterized in that: The Jiles-Atherton model can accurately simulate the hysteresis loop of a ferromagnetic material in an alternating magnetization cycle, and the area of ​​the hysteresis loop corresponds to the core loss.

3. The digital twin model calculation method considering the magnetothermal fluid field coupling of the high-voltage reactor according to claim 2 is characterized in that: The core loss includes hysteresis loss and dynamic loss, wherein the hysteresis loss is directly calculated by the JA model, and the dynamic loss is calculated by the hysteresis-free magnetization curve, which is expressed as: Among them, M an is the hysteresis-free magnetization, M s is the saturation magnetization, H is the magnetic field intensity, a is a parameter related to the shape of the hysteresis-free magnetization curve, and α is a parameter for the magnetization intensity coupling between magnetic domains. Coth is the hyperbolic cotangent function, defined as Where cosh(x) and sinh(x) are are the hyperbolic cosine and hyperbolic sine functions.

4. The digital twin model calculation method considering the magnetothermal fluid field coupling of the high-voltage reactor according to claim 3 is characterized in that: The hysteresis-free magnetization curve is used to construct the static hysteresis loss total magnetization equation according to the law of conservation of energy. Where M = M irr +M rev , M irr represents the irreversible magnetization component, M rev represents the reversible magnetization component, c represents the reversible magnetization coefficient, δ is the positive and negative direction coefficient that changes with time, and k represents the change in the energy lost by each magnetic domain unit when it is magnetized.

5. The digital twin model calculation method considering the magnetothermal fluid field coupling of the high-voltage reactor according to claim 2 is characterized in that: The step b) combines the JA hysteresis model with the basic electromagnetic field equation to construct a finite element model for calculating the magnetic field distribution of the high-voltage reactor, specifically comprising: The magnetic field distribution of the reactor under working conditions is simulated and studied; the differential form of Maxwell's basic equations of the electromagnetic field is: Where, H represents the magnetic field intensity (A / m); J represents the current density (A / m 2 ); E represents the electric field intensity (V / m); B represents the magnetic induction intensity (T); D represents the electric flux density (C / m 2 );ρ represents the charge density (C / m 3 ).

6. The digital twin model calculation method considering the magnetothermal fluid field coupling of the high-voltage reactor according to claim 1 is characterized in that: The step c) uses the reactor magnetic field finite element model result of step b) and combines the magneto-thermal fluid coupling analysis method to construct a finite element model that can fit the high-voltage reactor loss and temperature field, specifically including: the magneto-thermal fluid coupling analysis method first analyzes the magneto-thermal coupling, and uses the finite element method to analyze the magnetic field and eddy current field in a three-dimensional field. The basic equation based on the A-φ method is as follows: A is the magnetic vector potential; φ is the electric scalar potential; σ is the conductivity; v is the magnetic resistivity; J0 is the current density of the coil.

7. The digital twin model calculation method considering the magnetothermal fluid field coupling of the high-voltage reactor according to claim 6 is characterized in that: After the magnetic-thermal coupling analysis, the magnetic-thermal-fluid coupling is analyzed, and the natural convection is considered and analyzed using the Navier-Stokes equation with penalty function: Where v represents the vector of fluid velocity; g = 9.8 m / s 2 ; η is the fluid viscosity coefficient; β is the fluid extension coefficient; α represents the penalty number, is the time derivative, T is the absolute temperature (K), T0 is the initial temperature, and ρ0 is the mass density at T0 temperature.

8. The digital twin model calculation method considering the magnetothermal fluid field coupling of the high-voltage reactor according to any one of claims 1 to 7 is characterized in that: The calculation results of the finite element model are exported and uploaded in a format supported by the Internet of Things platform, so as to realize real-time monitoring of the magnetic-thermal-fluid coupling state of the high-voltage reactor to serve the digital twin and state evaluation of the high-voltage reactor.

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