Method, device, equipment, medium and product for constructing current limiting reactor

Abstract

The embodiment of the application provides a current limiting reactor construction method, device, equipment, medium and product, and is applied to the structural design technical field of the reactor. The method comprises the following steps: obtaining basic design parameters of a target reactor, wherein the basic design parameters comprise winding core parameters, oil channel design parameters, iron yoke design parameters and basic inductance parameters of the target reactor; obtaining magnetic property data of a ferromagnetic material of an iron yoke in the target reactor, performing mathematical modeling on the magnetic property data, and generating a dynamic magnetic permeability function model; constructing a magnetic circuit electrical coupling simulation model of the target reactor based on the basic design parameters and the dynamic magnetic permeability function model; performing simulation test based on the magnetic circuit electrical coupling simulation model, obtaining a simulation result, and determining a design scheme of the target reactor based on the magnetic circuit electrical coupling simulation model when the simulation result indicates that the magnetic circuit electrical coupling simulation model is feasible. The technical effect of improving the current limiting stability of the reactor under extreme working conditions is achieved.

Description

Technical Field

[0001] This application relates to the field of reactor structural design technology, and in particular to a method, apparatus, equipment, medium and product for constructing a current-limiting reactor. Background Technology

[0002] High-voltage power systems are the core backbone of modern power transmission, undertaking the critical task of large-capacity, long-distance power transmission. Their safe and stable operation is directly related to the guarantee of electricity supply for industrial production and people's livelihood. Large-capacity oil-immersed current-limiting reactors, as key protective equipment in high-voltage systems, rely on their excellent insulation performance, efficient heat dissipation capabilities, and ultra-large carrying capacity to become the core support for suppressing short-circuit currents, compensating for reactive power, and stabilizing system voltage. Their necessity and core position in the power system are irreplaceable.

[0003] In the existing technology, the construction method of large-capacity oil-immersed current-limiting reactors mainly revolves around normal operating conditions. The conventional construction parameters of the reactor are determined by using the magnetic circuit assumption. Based on the conventional construction parameters, a simulation model is built, and the performance of the prototype under normal operating conditions is tested to verify the inductor stability, heat dissipation effect and other indicators, and then the design scheme is determined.

[0004] Because the existing technology for reactor construction lacks the characteristic changes of the ferromagnetic material used in the yoke during the current limiting process, the simulation model cannot truly reproduce the hysteresis effect and saturation characteristics of the ferromagnetic material, resulting in the technical problem of low current limiting stability of the reactor under extreme operating conditions. Summary of the Invention

[0005] This application provides a method, apparatus, equipment, medium, and product for constructing a current-limiting reactor, which aims to improve the current-limiting stability of the reactor under extreme operating conditions.

[0006] In a first aspect, embodiments of this application provide a method for constructing a current-limiting reactor, including:

[0007] Obtain the basic design parameters of the target reactor, including the core winding parameters, oil passage design parameters, yoke design parameters, and basic inductance parameters of the target reactor;

[0008] The magnetic properties data of the ferromagnetic material of the yoke in the target reactor are obtained, and a dynamic permeability function model is generated by mathematical modeling of the magnetic properties data. The magnetic properties data are obtained by measurement through testing equipment, and the dynamic permeability function describes the nonlinear relationship between magnetic induction intensity and magnetic field strength.

[0009] Based on the basic design parameters and the dynamic permeability function model, a magnetic circuit electrical coupling simulation model of the target reactor is constructed.

[0010] Simulation tests were conducted based on the magnetic circuit electrical coupling simulation model to obtain simulation results. When the simulation results indicated that the magnetic circuit electrical coupling simulation model was feasible, the design scheme of the target reactor was determined based on the magnetic circuit electrical coupling simulation model.

[0011] In one possible implementation, obtaining the basic design parameters of the target reactor includes:

[0012] Based on the power transmission capacity requirements, insulation standards, and heat dissipation requirements of the power system to which the target reactor belongs, the core winding parameters are determined; among them, the core winding parameters include the preset radial width, axial height, number of winding turns, and winding structure;

[0013] Based on the heat dissipation requirements of the target reactor during operation and the performance standards of the insulating medium, the oil passage design parameters are determined; among them, the oil passage design parameters include the preset vertical oil passage width, horizontal oil passage width, number of vertical oil passages, and number of horizontal oil passages;

[0014] Based on the preset magnetic circuit optimization design specifications corresponding to the target reactor, the design parameters of the yoke are determined. Among them, the design parameters of the yoke include the number of segments of the segmented yoke, the preset end distance between the yoke and the winding, and the initial magnetic circuit length and cross-sectional area of ​​each segment of the yoke.

[0015] Based on the power transmission stability requirements of the target reactor during normal operation, the rated inductance in the unsaturated region of the basic inductance parameters is determined.

[0016] In one possible implementation, magnetic property data of the ferromagnetic material of the yoke in the target reactor are obtained, and mathematical modeling is performed on the magnetic property data to generate a dynamic permeability function model, including:

[0017] Based on a preset combination of magnetization parameters, a magnetic field strength that varies continuously from low to high is applied to a ferromagnetic material to obtain magnetic induction intensity data corresponding to different magnetic field strengths.

[0018] Multiple sets of magnetic field strength and magnetic induction intensity data are preprocessed to remove outliers and perform smoothing corrections, while retaining the characteristic data corresponding to hysteresis effect and remanence.

[0019] Based on the analysis of the data variation patterns of multiple sets of magnetic field strength and magnetic induction intensity data, a dynamic permeability function model was obtained.

[0020] In one possible implementation, based on fundamental design parameters and a dynamic permeability function model, a magnetic circuit electrical coupling simulation model of the target reactor is constructed, including:

[0021] Construct the basic simulation framework corresponding to the target reactor;

[0022] The number of turns and winding structure in the core parameters of the winding are transformed into the electrical circuit topology in the basic simulation framework.

[0023] The heat dissipation and insulation performance corresponding to the oil passage design parameters are converted into the medium characteristic parameters in the basic simulation framework.

[0024] The segmented structure, initial magnetic circuit length, and cross-sectional area in the iron yoke design parameters are transformed into the magnetic circuit entity structure in the basic simulation framework.

[0025] By embedding the dynamic permeability function model into the basic simulation framework, the magnetic circuit electrical coupling simulation model of the target reactor is obtained.

[0026] In one possible implementation, simulation tests are performed based on a magnetic circuit electrical coupling simulation model to obtain simulation results, including:

[0027] Obtain the operating boundary conditions of the power system to which the target reactor belongs, and set them as the boundary conditions of the magnetic circuit electrical coupling simulation model; wherein, the boundary conditions include the system rated voltage, rated frequency and normal operating current;

[0028] Input short-circuit current excitations of different amplitudes into the magnetic circuit electrical coupling simulation model and monitor key parameters in real time during the simulation process. Key parameters include reactor impedance change, inductor decay rate, short-circuit current peak suppression effect, and magnetic induction intensity change trend of each section of the iron yoke under different short-circuit current intensities.

[0029] When the key parameters meet the preset feasibility judgment conditions corresponding to the magnetic circuit electrical coupling simulation model, the magnetic circuit electrical coupling simulation model is determined to be feasible, and simulation results are generated.

[0030] When the key parameters do not meet the preset feasibility judgment conditions, determine the infeasibility of the magnetic circuit electrical coupling simulation model and the reasons for its infeasibility, and generate simulation results.

[0031] In one possible implementation, after performing simulation tests based on a magnetic circuit electrical coupling simulation model and obtaining the simulation results, the method further includes:

[0032] When the simulation results indicate that the magnetic circuit electrical coupling simulation model is infeasible, the corresponding reasons for infeasibility are determined based on the simulation results;

[0033] Based on the reasons for infeasibility, the target model parameters that need to be adjusted in the magnetic circuit electrical coupling simulation model are determined;

[0034] Based on the target model parameters, the parameters are adjusted to obtain the updated model parameters. The updated model parameters are then applied to the magnetic circuit electrical coupling simulation model to obtain the updated magnetic circuit electrical coupling simulation model.

[0035] Simulation tests were conducted based on the updated magnetic circuit electrical coupling simulation model, and updated simulation results were obtained.

[0036] Secondly, embodiments of this application provide a current-limiting reactor construction apparatus, comprising:

[0037] The acquisition module is used to acquire the basic design parameters of the target reactor, including the core winding parameters, oil passage design parameters, yoke design parameters, and basic inductance parameters of the target reactor.

[0038] The first processing module is used to acquire the magnetic property data of the ferromagnetic material of the yoke in the target reactor, perform mathematical modeling on the magnetic property data, and generate a dynamic permeability function model. The magnetic property data is obtained by measurement through testing equipment, and the dynamic permeability function describes the nonlinear relationship between magnetic induction intensity and magnetic field strength.

[0039] The second processing module is used to construct a magnetic circuit electrical coupling simulation model of the target reactor based on the basic design parameters and the dynamic permeability function model.

[0040] The third processing module is used to perform simulation tests based on the magnetic circuit electrical coupling simulation model, obtain simulation results, and determine the design scheme of the target reactor based on the magnetic circuit electrical coupling simulation model when the simulation results indicate that the magnetic circuit electrical coupling simulation model is feasible.

[0041] In one possible implementation, the acquisition module is further configured to:

[0042] Based on the power transmission capacity requirements, insulation standards, and heat dissipation requirements of the power system to which the target reactor belongs, the core winding parameters are determined; among them, the core winding parameters include the preset radial width, axial height, number of winding turns, and winding structure;

[0043] Based on the heat dissipation requirements of the target reactor during operation and the performance standards of the insulating medium, the oil passage design parameters are determined; among them, the oil passage design parameters include the preset vertical oil passage width, horizontal oil passage width, number of vertical oil passages, and number of horizontal oil passages;

[0044] Based on the preset magnetic circuit optimization design specifications corresponding to the target reactor, the design parameters of the yoke are determined. Among them, the design parameters of the yoke include the number of segments of the segmented yoke, the preset end distance between the yoke and the winding, and the initial magnetic circuit length and cross-sectional area of ​​each segment of the yoke.

[0045] Based on the power transmission stability requirements of the target reactor during normal operation, the rated inductance in the unsaturated region of the basic inductance parameters is determined.

[0046] In one possible implementation, the first processing module is further configured to:

[0047] Based on a preset combination of magnetization parameters, a magnetic field strength that varies continuously from low to high is applied to a ferromagnetic material to obtain magnetic induction intensity data corresponding to different magnetic field strengths.

[0048] Multiple sets of magnetic field strength and magnetic induction intensity data are preprocessed to remove outliers and perform smoothing corrections, while retaining the characteristic data corresponding to hysteresis effect and remanence.

[0049] Based on the analysis of the data variation patterns of multiple sets of magnetic field strength and magnetic induction intensity data, a dynamic permeability function model was obtained.

[0050] In one possible implementation, the second processing module is further configured to:

[0051] Construct the basic simulation framework corresponding to the target reactor;

[0052] The number of turns and winding structure in the core parameters of the winding are transformed into the electrical circuit topology in the basic simulation framework.

[0053] The heat dissipation and insulation performance corresponding to the oil passage design parameters are converted into the medium characteristic parameters in the basic simulation framework.

[0054] The segmented structure, initial magnetic circuit length, and cross-sectional area in the iron yoke design parameters are transformed into the magnetic circuit entity structure in the basic simulation framework.

[0055] By embedding the dynamic permeability function model into the basic simulation framework, the magnetic circuit electrical coupling simulation model of the target reactor is obtained.

[0056] In one possible implementation, the third processing module is further configured to:

[0057] Obtain the operating boundary conditions of the power system to which the target reactor belongs, and set them as the boundary conditions of the magnetic circuit electrical coupling simulation model; wherein, the boundary conditions include the system rated voltage, rated frequency and normal operating current;

[0058] Input short-circuit current excitations of different amplitudes into the magnetic circuit electrical coupling simulation model and monitor key parameters in real time during the simulation process. Key parameters include reactor impedance change, inductor decay rate, short-circuit current peak suppression effect, and magnetic induction intensity change trend of each section of the iron yoke under different short-circuit current intensities.

[0059] When the key parameters meet the preset feasibility judgment conditions corresponding to the magnetic circuit electrical coupling simulation model, the magnetic circuit electrical coupling simulation model is determined to be feasible, and simulation results are generated.

[0060] When the key parameters do not meet the preset feasibility judgment conditions, determine the infeasibility of the magnetic circuit electrical coupling simulation model and the reasons for its infeasibility, and generate simulation results.

[0061] In one possible implementation, the third processing module is further configured to:

[0062] When the simulation results indicate that the magnetic circuit electrical coupling simulation model is infeasible, the corresponding reasons for infeasibility are determined based on the simulation results;

[0063] Based on the reasons for infeasibility, the target model parameters that need to be adjusted in the magnetic circuit electrical coupling simulation model are determined;

[0064] Based on the target model parameters, the parameters are adjusted to obtain the updated model parameters. The updated model parameters are then applied to the magnetic circuit electrical coupling simulation model to obtain the updated magnetic circuit electrical coupling simulation model.

[0065] Simulation tests were conducted based on the updated magnetic circuit electrical coupling simulation model, and updated simulation results were obtained.

[0066] Thirdly, embodiments of this application provide an electronic device, including: a memory and a processor;

[0067] The memory stores instructions that the computer executes;

[0068] The processor executes computer execution instructions stored in memory, causing the processor to perform the first aspect above and various possible implementations of the first aspect.

[0069] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the first aspect and various possible implementations thereof.

[0070] Fifthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the first aspect and various possible implementations thereof.

[0071] This application provides a method, apparatus, equipment, medium, and product for constructing a current-limiting reactor. The method obtains fundamental design parameters of the target reactor, including winding core parameters, oil channel design parameters, yoke design parameters, and basic inductance parameters. Simultaneously, it tests the ferromagnetic material of the yoke to obtain magnetic property data. Using this magnetic property data, a dynamic permeability function model corresponding to the ferromagnetic material is derived. Based on this dynamic permeability function model and the previously obtained fundamental design parameters, a magnetic circuit electrical coupling simulation model for the reactor is constructed. Simulation tests are performed on this model. When the simulation results indicate that the model is feasible, a design scheme for reactor construction is determined based on the simulation model, thereby achieving the purpose of constructing a current-limiting reactor. Compared with existing technologies, this application builds a simulation model of magnetic circuit electrical coupling, deeply integrates dynamic permeability function with structural parameters, and realistically reproduces the coupling process of material saturation and inductance change under short-circuit conditions. Finally, simulation tests ensure that the design scheme can adapt to the material saturation characteristics, so that the reactor can still maintain stable inductance under extreme short circuits, effectively suppressing short-circuit current peaks, and achieving the technical effect of improving the stability of current limiting of the reactor under extreme conditions. Attached Figure Description

[0072] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0073] Figure 1 A flowchart illustrating the current-limiting reactor construction method provided in this application. Figure 1 ;

[0074] Figure 2 This application provides a schematic diagram of the geometric structure of a reactor.

[0075] Figure 3 This application provides a schematic diagram of the yoke dimensions of a reactor.

[0076] Figure 4 A schematic diagram of the magnetic characteristic curve of the iron yoke of a reactor provided in this application;

[0077] Figure 5 A schematic diagram of the test results of a small-scale reactor provided in this application;

[0078] Figure 6 A flowchart illustrating the current-limiting reactor construction method provided in this application. Figure 2 ;

[0079] Figure 7 A flowchart illustrating the current-limiting reactor construction method provided in this application. Figure 3 ;

[0080] Figure 8 This application provides a schematic diagram of the resistance reactance variation of a small-scale reactor under different currents.

[0081] Figure 9 A schematic diagram of the current-limiting reactor construction device provided in this application;

[0082] Figure 10 A schematic diagram of the structure of the electronic device provided in this application.

[0083] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0084] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0085] In existing technologies, the main approach to constructing large-capacity oil-immersed current-limiting reactors in the power system field is as follows: parameter calculations are performed based on the linear magnetic circuit assumption, and simulation analysis is conducted using a fixed inductance model. This leads to a suitable design scheme for the current-limiting inductor.

[0086] However, due to the lack of simulation testing of ferromagnetic material properties in the construction of simulation models in existing technical solutions, existing reactor design schemes cannot cover the saturation of ferromagnetic materials under extreme short-circuit faults. Therefore, existing technologies have the technical problem of low current-limiting stability of reactors under extreme conditions.

[0087] To address the aforementioned technical problems, this application proposes the following technical concept: Integrating the magnetic properties of ferromagnetic materials into the reactor construction process. Specifically, by combining the nonlinear magnetization characteristics and saturation laws of ferromagnetic materials, the winding structure, number of turns, and segmented design and size allocation of the yoke are specifically optimized to lay a structural foundation for delaying material saturation and maintaining inductance stability. By testing the magnetic property data of the ferromagnetic material, a dynamic permeability function model is generated to accurately quantify the nonlinear relationship between magnetic induction intensity and magnetic field strength. A simulation model is built to deeply integrate the dynamic permeability function with structural parameters, realistically reproducing the coupling process of material saturation and inductance change under short-circuit conditions. Simulation tests ensure that the design scheme can adapt to the saturation characteristics of ferromagnetic materials, ultimately enabling the reactor to maintain stable inductance even under extreme short-circuit conditions, effectively suppressing short-circuit current peaks, thereby achieving the technical effect of improving the current-limiting stability of the reactor under extreme conditions.

[0088] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0089] Figure 1 A flowchart illustrating the current-limiting reactor construction method provided in this application. Figure 1 ,like Figure 1 As shown, the method includes:

[0090] S101. Obtain the basic design parameters of the target reactor.

[0091] In this step, the basic design parameters include the core winding parameters, oil channel design parameters, yoke design parameters, and basic inductance parameters of the target reactor. The target reactor refers to the current-limiting reactor to be designed to meet the specific power system requirements. The basic design parameters are the set of core parameters supporting the reactor's structural design and performance realization, forming the basis for subsequent simulation modeling and scheme determination. The core winding parameters determine the winding's electromagnetic performance and structural stability, directly affecting inductance and current-limiting effectiveness. The oil channel design parameters ensure the reactor's heat dissipation efficiency and insulation performance, adapting to the cooling requirements of oil-immersed structures. The yoke design parameters determine the magnetic circuit distribution and delay ferromagnetic material saturation; the yoke employs a segmented design. The basic inductance parameters include the rated inductance in the unsaturated region, i.e., the stable inductance value under normal operating conditions, which is the fundamental guarantee for current-limiting effectiveness.

[0092] Alternatively, one possible way to obtain the basic design parameters is as follows:

[0093] S1011. Determine the core winding parameters based on the power transmission capacity requirements, insulation standards, and heat dissipation requirements of the power system to which the target reactor belongs.

[0094] In this step, the core winding parameters include the preset radial width, axial height, number of turns, and winding structure. The transmission capacity requirement refers to the upper limit of the power transmission scale of the high-voltage power system to which the target reactor belongs, determining the winding's load-bearing capacity. Insulation standards refer to the insulation performance specifications that power equipment must follow, ensuring no breakdown risk under high-voltage environments. Heat dissipation requirements refer to the heat dissipation standards that the reactor must meet during operation to prevent excessive oil temperature from degrading the insulation. The radial width of the winding refers to its dimension in the radial direction, affecting the winding's mechanical strength and magnetic circuit coupling effect. The axial height of the winding refers to its dimension in the axial direction, directly related to the number of turns and heat dissipation area. The number of turns refers to the number of wire turns in the winding, a core parameter determining the inductance. The winding structure refers to the arrangement and connection method of the winding wires, affecting magnetic circuit uniformity and current-limiting stability.

[0095] For example, the power transmission capacity requirement is 200MVA, the heat dissipation requirement is winding temperature rise ≤65K, and the insulation standard is the preset insulation design specification.

[0096] Based on the rated voltage of the power system (500kV) and the effective cross-sectional area of ​​the core column (0.05m²), the initial estimated number of winding turns is 1000-1500 turns. A conductor diameter of 0.01m and an insulation thickness of 0.001m per turn are selected. The total insulation thickness of the 1200-turn winding plus the total conductor width equals 0.04065m, meaning the radial width is determined to be 40.65mm. Considering the core column height of 1.465m, magnetic coupling efficiency, and heat dissipation uniformity, the axial height is determined to be 14.65mm. A double-layer lap winding structure is adopted, with an inter-turn insulation spacing of 0.001m, meeting the 1050kV withstand voltage requirement. The determined core winding parameters are verified: the rated current carrying capacity of the 1200-turn winding is 230A, matching a 200MVA capacity; the heat dissipation area corresponding to the radial / axial dimensions meets the temperature rise ≤65K requirement. The final core winding parameters are then determined.

[0097] S1012. Based on the heat dissipation requirements of the target reactor during operation and the performance standards of the insulating medium, determine the oil passage design parameters.

[0098] In this step, the oil channel design parameters include the preset vertical oil channel width, horizontal oil channel width, number of vertical oil channels, and number of horizontal oil channels. The loss dissipation requirement refers to the standard by which the heat generated during the operation of the target reactor must be dissipated through the oil channels; this requirement aims to prevent the degradation of the insulating oil. The insulation medium performance standard refers to the electrical and thermal performance specifications that the cooling and insulation medium of the oil-immersed reactor must meet. The vertical oil channel width refers to the gap dimension of the vertical oil channels in the target reactor; this parameter affects the heat dissipation efficiency of the target reactor in the vertical direction. The horizontal oil channel width refers to the gap dimension of the horizontal oil channels in the target reactor; this parameter affects the heat dissipation efficiency of the target reactor in the horizontal direction. The number of vertical oil channels refers to the number of oil channels set in the vertical direction, matching the radial width of the winding. The number of horizontal oil channels refers to the number of oil channels set in the horizontal direction, matching the axial width of the winding.

[0099] S1013. Based on the preset magnetic circuit optimization design specifications corresponding to the target reactor, determine the design parameters of the iron yoke.

[0100] In this step, the yoke design parameters include the number of segments in the segmented yoke, the preset end distance between the yoke and the winding, and the initial magnetic circuit length and cross-sectional area of ​​each yoke segment. The preset magnetic circuit optimization design specification refers to the standard guiding the yoke structural design. A segmented yoke refers to a structural design that divides the yoke into multiple segments, delaying overall saturation through reasonable size allocation. The preset end distance between the yoke and the winding refers to the gap size between the yoke and the winding, used to ensure insulation performance and optimize the magnetic circuit boundary. The initial magnetic circuit length of each yoke segment refers to the length of each yoke segment along the magnetic circuit transmission path; this parameter affects the magnetic flux transmission efficiency of the yoke in the target reactor. The cross-sectional area of ​​each yoke segment refers to the cross-sectional area of ​​each yoke segment; this parameter affects the yoke's magnetic flux carrying capacity.

[0101] Optionally, the design parameters of the yoke can be determined as follows: Based on a pre-defined magnetic circuit optimization design specification, determine the segmentation method of the yoke. Combine the dimensions and position of the windings to determine the end distance between the yoke and the windings. Based on the principle of uniform magnetic flux distribution, allocate the initial magnetic circuit length and cross-sectional area of ​​each yoke segment.

[0102] For example, based on the pre-defined magnetic circuit optimization specifications, the segmentation method of the yoke is determined to be a three-segment yoke. Considering the insulation requirement of ≥300mm between the yoke and windings, the pre-defined end distance between the yoke and windings is determined to be 350mm. Based on the principle of uniform magnetic flux distribution, the initial magnetic circuit lengths of each yoke segment are allocated, resulting in lengths of 550mm for the first segment, 500mm for the second segment, and 550mm for the third segment. The effective cross-sectional area of ​​the current core column is A. c =0.025m 2 Therefore, the cross-sectional area of ​​each section of the yoke is determined to be 0.025m².

[0103] S1014. Based on the power transmission stability requirements during normal operation of the target reactor, determine the unsaturated region rated inductance in the basic inductance parameters.

[0104] In this step, the power transmission stability requirement refers to ensuring that grid voltage fluctuations and power transmission efficiency meet requirements during normal operation of the target reactor. The unsaturated region rated inductance refers to the stable inductance value of the target reactor under normal operating conditions. The method for determining the unsaturated region rated inductance in this step is shown in Formula 1:

[0105]

[0106] in, Rated inductance in the unsaturated region; Where is the vacuum permeability; N is the total number of turns in the winding; The effective cross-sectional area of ​​the iron core column is given; for stepped cross-sections, the equivalent area needs to be calculated. This represents the total length of the magnetic circuit of the iron core column; It is the equivalent air gap length, including the gap between the iron core laminations and the insulation air gap.

[0107] For example, Figure 2 This is a schematic diagram of the geometric structure of a reactor provided in this application. Figure 3 This application provides a schematic diagram of the yoke dimensions of a reactor, as shown below. Figure 2 and Figure 3 As shown, the basic design parameters of this reactor include: winding radial width 40.65mm, winding axial height 14.65mm, vertical oil passage width 6mm, horizontal oil passage width 4mm, vertical oil passage type 3, and number of horizontal oil passages 107. The yoke dimensions are: inner ring width 2670mm, outer ring width 3210mm, inner ring length 3732mm, outer ring length 4272mm, and end distance between the yoke and winding 350mm. The yoke's side thickness in the horizontal direction is 270mm, the length of the horizontal end section is 973mm, and the length of the horizontal middle section is 893mm.

[0108] S102. Obtain the magnetic property data of the ferromagnetic material of the yoke in the target reactor, perform mathematical modeling on the magnetic property data, and generate a dynamic permeability function model.

[0109] In this step, the magnetic property data are obtained by measuring with testing equipment, and the dynamic permeability function describes the nonlinear relationship between magnetic induction intensity and magnetic field intensity.

[0110] Alternatively, one possible implementation of generating the dynamic permeability function model is as follows:

[0111] S1021. Based on a preset combination of magnetization parameters, apply a continuously varying magnetic field strength from low to high to the ferromagnetic material to obtain magnetic induction intensity data corresponding to different magnetic field strengths.

[0112] In this step, the preset magnetic ring parameter combination refers to the parameters such as the magnetic field strength test range, test step size, and frequency pre-set to cover the full magnetization stage of the ferromagnetic material. The continuously varying magnetic field strength refers to the magnetic field strength signal that gradually increases from low to high, and this signal needs to cover the complete intensity range from unsaturated to saturated. Magnetic induction intensity data refers to the magnetic induction intensity value corresponding to the ferromagnetic material under different magnetic field strengths.

[0113] For example, the magnetic flux density data can be obtained by: pre-setting a combination of magnetization parameters including: magnetic field strength range of 0~300 A / m, step size of 1 A / m, and magnetization frequency of 50 Hz. Using testing equipment, a continuously increasing magnetic field strength from 0 A / m to 300 A / m is applied to the ferromagnetic material sample of the target reactor, with a 0.1 s pause at each step to ensure data stability. 301 sets of data corresponding to magnetic field strength and magnetic flux density are recorded. Data deviating from the overall trend are discarded, and the remaining valid data, covering the complete range from unsaturated to saturated, is retained.

[0114] S1022. Preprocess multiple sets of magnetic field strength and magnetic induction intensity data, remove abnormal data and perform smoothing correction, and retain the characteristic data corresponding to hysteresis effect and remanence phenomenon.

[0115] In this step, outlier data refers to data points that do not conform to the overall trend and need to be removed. Smoothing correction refers to reducing data fluctuations so that the resulting curve more closely reflects the true magnetization behavior of ferromagnetic materials. Hysteresis response characteristic data refers to the residual magnetism that should remain in a ferromagnetic material after magnetization and the removal of an externally applied magnetic field. Remanence characteristic data refers to the specific data manifestation of the hysteresis effect, i.e., the residual magnetic flux density value.

[0116] For example, the smoothing process can be achieved by performing a 3-point moving average on the magnetic flux density values ​​in the range of 50~250 A / m, for example:

[0117] The original magnetic field strength is 95 A / m: the magnetic induction intensity is 1.38 T; the magnetic field strength is 100 A / m: the magnetic induction intensity is 1.4 T; the magnetic field strength is 105 A / m: the magnetic induction intensity is 1.42 T. After smoothing, the magnetic induction intensity of the magnetic field strength of 100 A / m is (1.38 + 1.4 + 1.42) / 3 = 1.4 T.

[0118] The first and last data are as follows: magnetic field strength is 0 A / m, magnetic induction intensity is 0; magnetic field strength is 300 A / m, magnetic induction intensity is 1.95 T, and the original values ​​are retained.

[0119] S1023. Based on the analysis of the data variation patterns of multiple sets of magnetic field strength and magnetic induction intensity data, a dynamic permeability function model is obtained.

[0120] In this step, data variation analysis refers to trend analysis of multiple sets of preprocessed magnetic field strength and magnetic induction intensity data to clarify the variation characteristics of the unsaturated and saturated regions. The dynamic permeability function model refers to a mathematical model that quantitatively describes the relationship between magnetic field strength and magnetic induction intensity.

[0121] Optionally, the dynamic permeability function model is determined by performing nonlinear fitting based on multiple sets of magnetic field strength and magnetic flux density data to obtain nonlinear functional expressions for the magnetic field strength and magnetic flux density. Based on the definition of permeability, the dynamic permeability function model is derived. Here, permeability is defined as magnetic flux density equal to magnetic field strength divided by magnetic field strength.

[0122] For example, Figure 4 A schematic diagram of the magnetic characteristic curve of the iron yoke of a reactor is provided in this application, as shown below. Figure 4 As shown, the vertical axis B refers to the magnetic field strength, in tons (T), ranging from 0 to 2.0, and the horizontal axis H refers to the magnetic flux density, in amperes (A / m), ranging from 0 to 300. The red curve represents the magnetic characteristic curve of the reactor's yoke, exhibiting the typical nonlinear magnetization law of ferromagnetic materials: in the initial stage, the magnetic flux density B increases rapidly with the magnetic field strength H, then gradually enters the saturation region, and the growth of B tends to level off. The nonlinear function expression obtained through fitting is shown in Equation 2:

[0123]

[0124] Where x refers to the magnetic field strength, and F(x) refers to the magnetic induction intensity.

[0125] Based on the nonlinear function expression and the definition of permeability, the derived dynamic permeability function model is shown in Equation 3:

[0126]

[0127] in, This refers to the dynamic permeability, and x refers to the magnetic field strength.

[0128] S103. Based on the basic design parameters and the dynamic permeability function model, a magnetic circuit electrical coupling simulation model of the target reactor is constructed.

[0129] In this step, the magnetic circuit-electric coupling simulation model integrates the magnetic circuit characteristics and electrical characteristics of the target reactor, and can be used to simulate the interaction of multiple physics fields. This simulation model can be constructed by building the physical structures of the electrical and magnetic circuits based on fundamental design parameters, embedding a dynamic permeability model to establish the coupling relationship between the magnetic and electrical circuits, thereby constructing the magnetic circuit-electric coupling simulation model.

[0130] It should be noted that the specific implementation method for constructing the magnetic circuit electrical coupling simulation model is detailed below. Figure 2 Further explanation will be provided in the embodiments shown, and will not be repeated here.

[0131] S104. Conduct simulation tests based on the magnetic circuit electrical coupling simulation model, obtain simulation results, and when the simulation results indicate that the magnetic circuit electrical coupling simulation model is feasible, determine the design scheme of the target reactor based on the magnetic circuit electrical coupling simulation model.

[0132] Optionally, one possible way to determine the design scheme of the target reactor is to extract the winding core parameters, oil passage design parameters, yoke design parameters, and basic inductance parameters corresponding to the magnetic circuit electrical coupling simulation model, and generate the corresponding design scheme.

[0133] It should be noted that after determining the corresponding design scheme, a physical test model of the target reactor is constructed based on the design scheme. This physical test model is used to verify the design scheme of the target reactor in a physical manner.

[0134] For example, it can be verified based on a physical test model whether the reactor corresponding to this design scheme satisfies the condition that the impedance decreases as the current increases. Figure 5 A schematic diagram illustrating the test results of a small-scale reactor provided in this application. Figure 5 As shown, the horizontal axis represents current in amperes (A), ranging from 0 to 250 ohms; the vertical axis represents impedance in amperes (Ω). The range is 5.25 to 5.55. A small-scale reactor refers to a physical test model of a 500kV oil-immersed current-limiting reactor. Figure 5 During the test, the impedance initially decreased slowly from 5.519Ω, then rapidly dropped to 5.44Ω after 83A, at which point the yoke was saturated. As the degree of saturation increased, the impedance decreased rapidly, finally reaching 5.27Ω at 210A, and then stabilized. The test results were used to verify consistency with the simulation results of the magnetic circuit electrical coupling simulation model of the target reactor. When consistency was confirmed, the test was considered successful.

[0135] The method for constructing a current-limiting reactor provided in this application involves acquiring the core winding parameters, oil passage design parameters, yoke design parameters, and basic inductance parameters of the target reactor. Simultaneously, the magnetic properties of the ferromagnetic material of the yoke are obtained through testing. A dynamic permeability function model corresponding to the ferromagnetic material is derived using this magnetic property data. Based on this model and the previously acquired basic design parameters, a magnetic circuit electrical coupling simulation model for the reactor is constructed. Simulation tests are performed on this model. When the simulation results indicate that the model is feasible, a design scheme for reactor construction is determined based on this model, thereby achieving the purpose of constructing a current-limiting reactor. Compared with existing technologies, this application builds a simulation model of magnetic circuit electrical coupling, deeply integrates dynamic permeability function with structural parameters, and realistically reproduces the coupling process of material saturation and inductance change under short-circuit conditions. Finally, simulation tests ensure that the design scheme can adapt to the material saturation characteristics, so that the reactor can still maintain stable inductance under extreme short circuits, effectively suppressing short-circuit current peaks, and achieving the technical effect of improving the stability of current limiting of the reactor under extreme conditions.

[0136] Figure 6 A flowchart illustrating the current-limiting reactor construction method provided in this application. Figure 2 ,like Figure 2 As shown, the method includes:

[0137] S601. Construct the basic simulation framework corresponding to the target reactor.

[0138] In this step, the basic simulation framework refers to the basic environment in the simulation platform that includes geometric modeling, physical field definition, and solver parameter settings.

[0139] Alternatively, one possible implementation of the basic simulation framework is as follows:

[0140] b1. Select a suitable simulation platform based on the type of the target reactor and the specific simulation requirements.

[0141] b2. When the core, windings and yoke of the target reactor are symmetrically distributed, two-dimensional axisymmetric modeling can be selected as the modeling method.

[0142] b3. Set the physical field type to transient magnetic field and circuit, and set the coupling mode to magnetic field-circuit bidirectional coupling.

[0143] b4. Set the solver type to transient solver, set the time range to 0~0.1s, the transient process of short-circuit fault is usually completed within 0.1s, set the time step to 0.001s, and set the relative error threshold to 1e-6, which is 0.000001.

[0144] b5. Import the parameters from steps b2 to b4, and build a basic simulation framework based on these parameters.

[0145] S602. Convert the number of winding turns and winding structure in the core parameters of the winding into the electrical circuit topology in the basic simulation framework.

[0146] In this step, the electrical circuit topology refers to the structural model in the simulation that describes the electrical connection method, number of turns distribution, and port definition of the winding. This structure needs to be used to reflect the actual winding method and circuit characteristics of the winding.

[0147] Optionally, winding turn conversion refers to allocating the designed total number of winding turns to the simulation topology according to the winding structure, ensuring that the number of turns is consistent with the actual design. Winding structure conversion refers to converting any of the actual winding methods, such as single-layer winding, double-layer lap winding, and segmented winding, into the loop connection method in the simulation, ensuring that the magnetic coupling efficiency is consistent with the actual one.

[0148] S603. Convert the heat dissipation and insulation performance corresponding to the oil passage design parameters into the dielectric characteristic parameters in the basic simulation framework.

[0149] In this step, the dielectric characteristic parameters refer to the set of parameters describing the physical properties of the insulating oil in the simulation, including thermal and electrical characteristic parameters, which directly affect heat dissipation efficiency and insulation reliability. The thermal characteristic parameters include thermal conductivity and specific heat capacity, while the electrical characteristic parameters include dielectric constant and breakdown voltage.

[0150] Optionally, heat dissipation performance conversion refers to converting the size and distribution of the oil channels into parameters such as the convective heat transfer coefficient and heat dissipation area of ​​the insulating oil, ensuring that the simulation can accurately simulate the heat dissipation process of the reactor. Insulation performance conversion refers to converting the width and spacing of the oil channels into the dielectric strength parameters of the insulating oil, ensuring that the simulation can simulate the withstand voltage characteristics of the insulating oil and avoid inter-turn and inter-winding discharges between the winding and the yoke.

[0151] For example, the way to convert the heat dissipation performance and insulation performance corresponding to the oil channel design parameters into the dielectric characteristic parameters in the basic simulation framework can be as follows:

[0152] c1. The key structural parameters extracted from the oil passage design parameters are: vertical oil passage width 6mm, number 3; horizontal oil passage width 4mm, number 107; and total oil passage length: winding axial height 14.65mm or radial width 40.65mm.

[0153] c2. Calculate the total heat dissipation area of ​​the oil channels: The heat dissipation area of ​​a single vertical oil channel is width × length × 2, the heat dissipation area of ​​a single horizontal oil channel is width × length × 2, and the total heat dissipation area is the sum of the total heat dissipation area of ​​the vertical oil channels and the total heat dissipation area of ​​the horizontal oil channels.

[0154] c3. The standard characteristic parameters of the insulating oil used in the current target reactor are:

[0155] Thermal properties: thermal conductivity k = 0.14 W / (m·K), specific heat capacity c = 2000 J / (kg·K), density ρ = 890 kg / m³.

[0156] Electrical characteristics: dielectric constant ε = 2.2, breakdown voltage U b =75kV, volume resistivity ρ v =1×10 14 Ω·m.

[0157] Based on the oil channel size and insulating oil flow velocity, c3 derives a convective heat transfer coefficient of 50 W / (m²·K).

[0158] c4. In the basic simulation framework, select all oil channel regions and create the material properties of the insulating oil. Input the thermal characteristic parameters: thermal conductivity 0.14 W / (m·K), specific heat capacity 2000 J / (kg·K), density 890 kg / m³; input the electrical characteristic parameters: dielectric constant 2.2, volume resistivity 1×10⁻⁶. 14 Ω·m; Related heat dissipation parameters: In the transient magnetic field simulation, set the convective heat transfer boundary conditions for the oil channel region, input the convective heat transfer coefficient of 50W / (m²·K), and the ambient temperature of 25℃.

[0159] S604. Transform the segmented structure, initial magnetic circuit length, and cross-sectional area in the yoke design parameters into the magnetic circuit entity structure in the basic simulation framework.

[0160] In this step, the magnetic circuit entity structure refers to the geometric model in the simulation that describes the physical form, segmentation method, and dimensional parameters of the yoke.

[0161] For example, the parameters can be transformed into the magnetic circuit entity structure in the basic simulation framework in the following ways:

[0162] The following parameters were extracted from the yoke design: number of segments n=3, length of segment 1 l1=1.2m, cross-sectional area A1=0.04m², length of segment 2 l2=1.0m, cross-sectional area A2=0.04m², length of segment 3 l3=1.2m, cross-sectional area A3=0.04m², distance from winding end d=350mm, and material is silicon steel sheet.

[0163] Accordingly, the supplementary magnetic circuit characteristic parameters are: the basic permeability of the iron yoke material when unsaturated is μ = 1 × 10⁻⁶. -4 H / m, saturation magnetic flux density B s =2.0T.

[0164] The transformed basic simulation framework's magnetic circuit structure is as follows: The first yoke segment: axial length 1.2m, radial thickness 0.2m (cross-sectional area 0.2m × 0.2m = 0.04m²), located on the left side of the winding, 350mm from the winding end; the second yoke segment: axial length 1.0m, radial thickness 0.2m, located on the right side of the winding, 350mm from the winding end; the third yoke segment: axial length 1.2m, radial thickness 0.2m, connected to the top of the first and second yoke segments, forming a closed magnetic circuit. The three yoke segments are seamlessly connected (inter-segment gap ≤ 0.001m), ensuring a closed magnetic circuit and no magnetic flux leakage.

[0165] It should be noted that the material properties of silicon steel sheets can also be created for the iron yoke entity. Input the basic parameters, magnetic properties: basic permeability 1×10⁻⁶. -4 H / m, saturation magnetic flux density 2.0T; and physical properties: density 7800kg / m³, thermal conductivity 45W / (m·K), resistivity 4×10⁻⁶. -7 Ω·m.

[0166] S605. Embed the dynamic permeability function model into the basic simulation framework to obtain the magnetic circuit electrical coupling simulation model of the target reactor.

[0167] In this step, the dynamic permeability function embedding refers to importing the nonlinear fitting formula into the properties of the iron yoke material, so that the simulation model can dynamically calculate the permeability under different magnetic field strengths.

[0168] It should be noted that after obtaining the magnetic circuit electrical coupling simulation model, the model can be verified. The specific verification includes: function embedding verification, coupling relationship verification, and model integrity verification.

[0169] For example, the verification of a magnetic circuit electrical coupling simulation model can be performed as follows:

[0170] Function embedding verification: Based on the magnetic circuit electrical coupling simulation model, a magnetic field strength of 100 A / m is applied. The magnetic induction intensity calculated by the simulation model is 1.38 T. At this time, the magnetic induction intensity value corresponding to the magnetic field strength of 100 A / m is calculated by using the fitting formula corresponding to the dynamic permeability function model. When the error between the magnetic induction intensity value calculated by fitting and the magnetic induction intensity value simulated is less than or equal to 1%, the function embedding verification is determined to be successful.

[0171] Coupling relationship verification: Based on the magnetic circuit electrical coupling simulation model, a short-circuit current of 200mA is applied as an excitation. At this time, the current has reached the saturation point of the ferromagnetic material of the iron yoke. If the output results of the magnetic circuit electrical coupling simulation model show that the permeability decreases with the increase of the magnetic field strength and the inductance decreases with the decrease of the permeability, then it is determined that the current growth rate is consistent with the inductance, and the coupling relationship verification is successful.

[0172] It should be noted that the coupling relationship verification uses the verification logic of saturated inductance. When the applied current has not reached the saturation point of the material, as the current increases, the corresponding magnetic field strength increases, and the magnetic flux density also increases linearly. Furthermore, the inductance at this point is the rated inductance in the unsaturated region, a fixed parameter. When the current increases to the saturation point, the increase in magnetic flux density becomes much smaller. Even with continuously increasing current, the increase in magnetic flux density is very small. At this point, the inductance will decrease significantly with increasing current. The essence of this decrease in inductance is that the permeability of the material decays under a strong magnetic field environment; therefore, the permeability is in a decreasing state.

[0173] Optionally, the calculation method for the rated inductance in the unsaturated region as a fixed value in the coupling relationship verification is as shown in Formula 1 above, and the calculation method for the dynamic inductance in the saturated region is as shown in Formula 4:

[0174]

[0175] in, The dynamic inductance in the saturation region varies with the magnetic flux density B. is the nonlinear permeability of the ferromagnetic material, and N is the total number of turns in the winding; The effective cross-sectional area of ​​the iron core column is given; for stepped cross-sections, the equivalent area needs to be calculated. This represents the total length of the magnetic circuit of the iron core column; This represents the equivalent air gap length. The nonlinear permeability is calculated using Equation 5:

[0176]

[0177] in, The saturation magnetic flux density of ferromagnetic materials; denoted as σ0, where σ0 is the maximum permeability of the ferromagnetic material; k is the nonlinear fitting coefficient, which is determined based on experimental data of the specific ferromagnetic material and can range from 3 to 5; B is the actual magnetic induction intensity of the iron core.

[0178] Based on the above embodiments, this application further describes how to obtain corresponding simulation results by performing simulation tests based on the magnetic circuit electrical coupling simulation model. Figure 7 A flowchart illustrating the current-limiting reactor construction method provided in this application. Figure 3 ,like Figure 7 As shown, the method includes:

[0179] S701. Obtain the operating boundary conditions of the power system to which the target reactor belongs, and set them as the boundary conditions of the magnetic circuit electrical coupling simulation model.

[0180] In this step, the boundary conditions include the system's rated voltage, rated frequency, and normal operating current. Specifically, the boundary conditions refer to the core operating parameters of the target reactor's power system, such as the power system's rated voltage, rated frequency, normal operating current, and short-circuit current withstand limit.

[0181] Optionally, the runtime boundary conditions can be obtained as follows:

[0182] The core operating parameters are extracted from the basic configuration parameters of the target reactor power system, and these operating parameters are set as the boundary conditions of the magnetic circuit electrical coupling simulation model during the simulation test.

[0183] For example, if the rated voltage of the power system is 500kV, the rated frequency is 50Hz, the normal operating current is 100A, and the voltage source type is a sinusoidal line voltage, then these parameters are input as boundary conditions into the electrical ports of the magnetic circuit electrical coupling simulation model. Short-circuit fault parameters are also set during model simulation to construct the boundary conditions of the magnetic circuit electrical coupling simulation model.

[0184] It should be noted that the short-circuit fault parameters refer to the time setting for triggering the short-circuit fault and the short-circuit current excitation amplitude setting.

[0185] For example, the boundary conditions are: the voltage source type is a three-phase sine wave, the line voltage is 500kV, the frequency is 50Hz, and the initial current is 100A; a three-phase short circuit is triggered at 0.01s, and the short-circuit current excitation amplitude is set to be continuous at 50A, 100A, 150A, 200A, 250A, and 300A.

[0186] S702. Input short-circuit current excitations of different amplitudes into the magnetic circuit electrical coupling simulation model and monitor key parameters in real time during the simulation process.

[0187] In this step, short-circuit current excitation refers to the current input signal simulating a short-circuit fault in the power grid during simulation. This signal is set with different amplitude gradients to test the reactor's performance under varying fault severity. Key parameters include reactor impedance changes under different short-circuit current intensities, inductance decay rate, short-circuit current peak suppression effect, and the magnetic flux density variation trend of each section of the yoke.

[0188] Alternatively, the method for inputting short-circuit current excitation and monitoring key parameters can be:

[0189] Determine the short-circuit current excitation scheme for simulation testing, along with the key parameters to be monitored, by importing files or using default parameters. Input the set short-circuit current excitation gradient into the magnetic circuit electrical coupling simulation model sequentially; monitor parameter change curves in real time: whether the impedance decreases with increasing current, whether the inductance decays, and whether the yoke magnetic flux density reaches saturation. Simultaneously record the critical current at which the yoke enters saturation, the abrupt change point in the inductance decay rate, and the parameter values ​​corresponding to the peak short-circuit current.

[0190] For example, Figure 8 This application provides a schematic diagram illustrating the resistance variation of a small-scale reactor under different currents. Figure 8 As shown, the horizontal axis represents current in amperes (A), ranging from 0 to 250 ohms; the vertical axis represents impedance in amperes (Ω). The range is from 2.9 to 3.25. The small-model reactor refers to a magnetic circuit electrical coupling simulation model of a 500kV current-limiting reactor. Figure 8 Simulation results show that as the simulation current increases, the impedance of the small model reactor gradually decreases, and as the saturation degree of the yoke increases, the degree of impedance decrease gradually increases.

[0191] It should be noted that the monitored peak short-circuit current needs to be matched with the calculated result to determine whether the calculated result is consistent with the monitored result, thus enabling simulation verification. To determine whether the magnetic flux density of the iron yoke has reached the saturation magnetic flux density, it is necessary to monitor the current magnetic flux density of the iron yoke and determine whether this parameter value has reached the preset saturation magnetic flux density.

[0192] Optionally, the current limiting calculation method for the short-circuit current is shown in Formula 6:

[0193]

[0194] in, This is the peak value of the short-circuit current; The system's rated voltage is taken from the line voltage. f is the saturation region reactance; f is the system rated frequency. The magnetic circuit saturation coefficient is... As a saturation effect correction term, magnetic circuit saturation will reduce the equivalent reactance of the magnetic circuit, thereby increasing the short-circuit current. Therefore, the saturation effect correction term is used to quantify the degree of influence of saturation on the short-circuit current.

[0195] Optionally, the magnetic flux density of the iron yoke is the actual magnetic flux density of the iron yoke, and this parameter is calculated as shown in Formula 7:

[0196]

[0197] in, The actual magnetic flux density of the iron yoke; This represents the total magnetic flux of the iron core. I represents the effective cross-sectional area of ​​the yoke; I represents the actual winding current. For iron core column magnetic reluctance; This refers to the total magnetic reluctance of the segmented yoke; Let be the cross-sectional area of ​​the i-th segment of the yoke, and n be the number of segments in the segmented yoke. This refers to the permeability of the i-th segment of the iron yoke. This refers to the magnetic circuit length of the i-th segment of the yoke.

[0198] S703. When the key parameters meet the preset feasibility judgment conditions corresponding to the magnetic circuit electrical coupling simulation model, the magnetic circuit electrical coupling simulation model is determined to be feasible, and simulation results are generated.

[0199] In this step, the preset feasibility judgment conditions refer to the performance standards determined based on the safety requirements of the power system and the design objectives of the target reactor, used to determine whether the obtained magnetic circuit electrical coupling simulation model meets the actual application requirements. The simulation results refer to comprehensive data including key parameter data, variation curves, and feasibility judgment conclusions.

[0200] For example, the preset feasibility judgment conditions are: under a maximum short-circuit current of 300A, the inductor attenuation rate is ≤50%; the short-circuit current peak suppression rate is ≥25%; after the yoke enters saturation, the impedance fluctuation is ≤0.02Ω; and the system voltage fluctuation amplitude is ≤±5%.

[0201] Based on the extracted key parameters, the maximum short-circuit current is 300A, the inductance attenuation rate is 46.5%, the short-circuit current peak suppression rate is 19%, the impedance fluctuation is 0.01Ω, and the voltage fluctuation is ±3%. Each key parameter was verified to confirm that the current magnetic circuit electrical coupling simulation model meets the preset feasibility judgment conditions.

[0202] S704. When the key parameters do not meet the preset feasibility judgment conditions, determine the infeasibility of the magnetic circuit electrical coupling simulation model and the reasons for its infeasibility, and generate simulation results.

[0203] In this step, the infeasibility cause refers to the fundamental factor that causes the key parameters to not meet the preset feasibility judgment conditions. The simulation results obtained under the infeasibility condition may include specific data on the key parameters not meeting the preset feasibility judgment conditions, analysis of the infeasibility cause, and targeted improvement strategy suggestions.

[0204] For example, the key data are: under a short-circuit current of 300A, the inductor attenuation rate is 60%, the short-circuit current peak suppression rate is 20%, the impedance fluctuation is 0.02Ω, and the voltage fluctuation is ±4%. The inductor attenuation rate and the short-circuit current peak suppression rate do not meet the preset feasibility judgment condition of inductor attenuation rate ≤50% and short-circuit current peak suppression rate ≥25% under a maximum short-circuit current of 300A. Therefore, the preset feasibility judgment condition is not met.

[0205] The current yoke design parameters are: 2 segments, lengths of 1.5m + 1.9m, and cross-sectional area of ​​0.03m² for each segment. Magnetic flux density calculations show that the magnetic flux density of the first segment is 2.1T, exceeding the saturation flux density of 2.0T, thus causing premature local saturation of the yoke. The rapid decrease in permeability of the first segment leads to a decrease in the total permeability, resulting in excessively rapid inductance decay and insufficient current limiting effect.

[0206] S705. When the simulation results indicate that the magnetic circuit electrical coupling simulation model is infeasible, determine the corresponding reasons for infeasibility based on the simulation results.

[0207] In this step, the data in the simulation results are stored in a structured format. The method for determining the infeasibility reasons is to use keywords in the structured data for matching, thereby extracting the infeasibility reasons when the magnetic circuit coupling simulation model is infeasible.

[0208] For example, if the currently determined infeasibility cause is: the inductor attenuation rate is greater than the upper limit of the inductor attenuation rate in the preset feasibility judgment conditions, the short-circuit current peak suppression rate is lower than the lower limit of the suppression rate in the preset feasibility judgment conditions, and all other parameters are normal, then the feasibility impact chain is: insufficient number of yoke segments and uneven distribution of magnetic circuit length, leading to concentrated magnetic flux and premature local magnetic saturation, ultimately making it infeasible. The analysis process of the feasibility impact chain is as follows: calculate the magnetic field strength of each yoke segment, calculate the total magnetic voltage drop of the yoke based on the magnetic induction intensity of each yoke segment and the magnetic circuit length, and if the calculation result indicates that the magnetic field strength of a certain yoke segment is too high, it indicates that the yoke has premature local magnetic saturation and has caused a decrease in the total permeability, thus clarifying the analysis chain of infeasibility causes. The calculation method of the magnetic field strength of the yoke is shown in Formula 8:

[0209]

[0210] Where H(B) is the magnetic field strength of the iron yoke, and B is the magnetic induction loudness of the iron yoke. Let be the permeability of the iron yoke. The saturation magnetic flux density of the ferromagnetic material of the iron yoke; denoted as σ0, where σ0 is the maximum permeability of the ferromagnetic material of the yoke, and k is the nonlinear fitting coefficient.

[0211] The corresponding total magnetic voltage drop of the iron yoke is calculated as shown in Formula 9:

[0212]

[0213] in, is the total magnetic voltage drop of the iron yoke; n is the number of segments in the segmented iron yoke; Let be the magnetic field strength of the i-th segment of the iron yoke. Let be the magnetic circuit length of the i-th segment of the yoke. Let be the magnetic flux density of the i-th segment of the iron yoke.

[0214] S706. Determine the target model parameters that need to be adjusted in the magnetic circuit electrical coupling simulation model based on the reasons for infeasibility.

[0215] In this step, the target model parameters refer to the simulation model parameters that need to be adjusted based on the reasons for infeasibility.

[0216] Optionally, the target model parameters are determined by: determining the adjustment direction based on the reasons for infeasibility; determining the target model parameters based on the adjustment direction; determining the range and specific values ​​of the target model parameters; and clarifying a list of target model parameters, which includes the target model parameters that need to be adjusted and their specific parameter values.

[0217] S707. Adjust the parameters based on the target model parameters to obtain the updated model parameters, and update the updated model parameters into the magnetic circuit electrical coupling simulation model to obtain the updated magnetic circuit electrical coupling simulation model.

[0218] In this step, updating the model parameters refers to adjusting the final parameters according to the target model parameters, which are then used to replace the original parameters in the simulation model. Updating the magnetic circuit electrical coupling simulation model refers to embedding the updated parameters into the complete simulation model, thereby identifying the structural defects of the original model.

[0219] For example, the adjustment direction determined based on the infeasibility reason is: increase the number of yoke segments, optimize the length distribution, increase the cross-sectional area, and disperse the magnetic flux to delay saturation. The selected target model parameters are: the number of yoke segments, the length of each segment, and the cross-sectional area of ​​each segment. The target model parameters are calculated to obtain specific parameter values. The adjusted parameters need to be verified. After adjusting the number of yoke segments from 2 to n, the verification method for the length of each segment and the cross-sectional area of ​​each segment is as shown in Formula 10:

[0220]

[0221] in, This refers to the cross-sectional area, This refers to the magnetic circuit length of the yoke. This refers to the permeability of the iron yoke. When Equation 10 holds true, it is determined that adjusting the parameters is feasible, resulting in an updated magnetic circuit electrical coupling simulation model.

[0222] S708. Based on the updated magnetic circuit electrical coupling simulation model, simulation tests were conducted to obtain updated simulation results.

[0223] In this step, updating the simulation results refers to conducting simulation tests based on the updated magnetic circuit electrical coupling simulation model and outputting the key parameter data and feasibility judgment conclusions corresponding to the simulation results. If the updated simulation results indicate that they do not meet the preset feasibility judgment conditions, the above model parameter update process is repeated until the simulation results indicate that the simulation model is feasible.

[0224] Figure 9 A schematic diagram of the current-limiting reactor construction device provided in this application is shown below. Figure 9 As shown, the current-limiting reactor construction device provided in this embodiment includes:

[0225] The acquisition module 901 is used to acquire the basic design parameters of the target reactor, including the core winding parameters, oil passage design parameters, yoke design parameters, and basic inductance parameters of the target reactor.

[0226] The first processing module 902 is used to acquire the magnetic property data of the ferromagnetic material of the yoke in the target reactor, perform mathematical modeling on the magnetic property data, and generate a dynamic permeability function model. The magnetic property data is obtained by measurement through testing equipment, and the dynamic permeability function describes the nonlinear relationship between magnetic induction intensity and magnetic field intensity.

[0227] The second processing module 903 is used to construct a magnetic circuit electrical coupling simulation model of the target reactor based on the basic design parameters and the dynamic permeability function model.

[0228] The third processing module 904 is used to perform simulation tests based on the magnetic circuit electrical coupling simulation model, obtain simulation results, and determine the design scheme of the target reactor based on the magnetic circuit electrical coupling simulation model when the simulation results indicate that the magnetic circuit electrical coupling simulation model is feasible.

[0229] Alternatively, in one possible implementation, the acquisition module 901 is further used for:

[0230] Based on the power transmission capacity requirements, insulation standards, and heat dissipation requirements of the power system to which the target reactor belongs, the core winding parameters are determined; among them, the core winding parameters include the preset radial width, axial height, number of winding turns, and winding structure.

[0231] Based on the heat dissipation requirements of the target reactor during operation and the performance standards of the insulating medium, the oil channel design parameters are determined; among them, the oil channel design parameters include the preset vertical oil channel width, horizontal oil channel width, number of vertical oil channels, and number of horizontal oil channels.

[0232] Based on the preset magnetic circuit optimization design specifications corresponding to the target reactor, the design parameters of the yoke are determined. Among them, the design parameters of the yoke include the number of segments of the segmented yoke, the preset end distance between the yoke and the winding, and the initial magnetic circuit length and cross-sectional area of ​​each segment of the yoke.

[0233] Based on the power transmission stability requirements of the target reactor during normal operation, the rated inductance in the unsaturated region of the basic inductance parameters is determined.

[0234] Optionally, in one possible implementation, the first processing module 902 is further configured to:

[0235] Based on a preset combination of magnetization parameters, a magnetic field strength that varies continuously from low to high is applied to a ferromagnetic material to obtain magnetic induction intensity data corresponding to different magnetic field strengths.

[0236] Multiple sets of magnetic field strength and magnetic induction intensity data are preprocessed to remove outliers and perform smoothing corrections, while retaining the characteristic data corresponding to hysteresis effect and remanence.

[0237] Based on the analysis of the data variation patterns of multiple sets of magnetic field strength and magnetic induction intensity data, a dynamic permeability function model was obtained.

[0238] Optionally, in one possible implementation, the second processing module 903 is further configured to:

[0239] Construct the basic simulation framework corresponding to the target reactor.

[0240] The number of turns and winding structure in the core parameters of the winding are transformed into the electrical circuit topology in the basic simulation framework.

[0241] The heat dissipation and insulation performance corresponding to the oil passage design parameters are converted into medium characteristic parameters in the basic simulation framework.

[0242] The segmented structure, initial magnetic circuit length, and cross-sectional area in the yoke design parameters are transformed into the magnetic circuit entity structure in the basic simulation framework.

[0243] By embedding the dynamic permeability function model into the basic simulation framework, the magnetic circuit electrical coupling simulation model of the target reactor is obtained.

[0244] Alternatively, in one possible implementation, the third processing module 904 is further configured to:

[0245] Obtain the operating boundary conditions of the power system to which the target reactor belongs, and set them as the boundary conditions of the magnetic circuit electrical coupling simulation model; the boundary conditions include the system rated voltage, rated frequency and normal operating current.

[0246] Input short-circuit current excitations of different amplitudes into the magnetic circuit electrical coupling simulation model and monitor key parameters in real time during the simulation process. Key parameters include reactor impedance changes, inductor decay rate, short-circuit current peak suppression effect, and magnetic induction intensity change trend of each section of the iron yoke under different short-circuit current intensities.

[0247] When the key parameters meet the preset feasibility judgment conditions corresponding to the magnetic circuit electrical coupling simulation model, the magnetic circuit electrical coupling simulation model is determined to be feasible, and simulation results are generated.

[0248] When the key parameters do not meet the preset feasibility judgment conditions, determine the infeasibility of the magnetic circuit electrical coupling simulation model and the reasons for its infeasibility, and generate simulation results.

[0249] Alternatively, in one possible implementation, the third processing module 904 is further configured to:

[0250] When the simulation results indicate that the magnetic circuit electrical coupling simulation model is infeasible, the corresponding reasons for infeasibility are determined based on the simulation results.

[0251] Based on the reasons for infeasibility, the target model parameters that need to be adjusted in the magnetic circuit electrical coupling simulation model are determined.

[0252] Based on the target model parameters, the parameters are adjusted to obtain the updated model parameters. The updated model parameters are then applied to the magnetic circuit electrical coupling simulation model to obtain the updated magnetic circuit electrical coupling simulation model.

[0253] Simulation tests were conducted based on the updated magnetic circuit electrical coupling simulation model, and updated simulation results were obtained.

[0254] The apparatus provided in this embodiment can execute the method provided in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0255] Figure 10 A schematic diagram of the structure of the electronic device provided in this application. Figure 10 As shown, the electronic device provided in this embodiment includes at least one processor 1001 and a memory 1002. Optionally, the device further includes a communication component 1003. The processor 1001, memory 1002, and communication component 1003 are connected via a bus 1004.

[0256] In the specific implementation process, at least one processor 1001 executes computer execution instructions stored in memory 1002, causing at least one processor 1001 to execute the above-mentioned current-limiting reactor construction method or method.

[0257] The specific implementation process of processor 1001 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.

[0258] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0259] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage device.

[0260] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0261] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0262] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the above-described method.

[0263] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0264] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components in the device.

[0265] The division of units is merely a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0266] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0267] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0268] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0269] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0270] Finally, it should be noted that other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein, and is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

Claims

1. A method for constructing a current-limiting reactor, characterized in that, include: Obtain the basic design parameters of the target reactor, including the core winding parameters, oil passage design parameters, yoke design parameters, and basic inductance parameters of the target reactor; The magnetic property data of the ferromagnetic material of the yoke in the target reactor are obtained, and the magnetic property data are mathematically modeled to generate a dynamic permeability function model. The magnetic property data is obtained by measurement through testing equipment, and the dynamic permeability function describes the nonlinear relationship between magnetic induction intensity and magnetic field intensity. Based on the basic design parameters and the dynamic permeability function model, a magnetic circuit electrical coupling simulation model of the target reactor is constructed. Simulation tests are performed based on the magnetic circuit electrical coupling simulation model to obtain simulation results. When the simulation results indicate that the magnetic circuit electrical coupling simulation model is feasible, the design scheme of the target reactor is determined based on the magnetic circuit electrical coupling simulation model.

2. The method according to claim 1, characterized in that, The acquisition of the basic design parameters of the target reactor includes: Based on the power transmission capacity requirements, insulation standards, and heat dissipation requirements of the power system to which the target reactor belongs, the core parameters of the winding are determined; wherein, the core parameters of the winding include the preset radial width, axial height, number of winding turns, and winding structure; Based on the heat dissipation requirements and insulation medium performance standards during the operation of the target reactor, the oil passage design parameters are determined; wherein, the oil passage design parameters include preset vertical oil passage width, horizontal oil passage width, number of vertical oil passages, and number of horizontal oil passages; Based on the preset magnetic circuit optimization design specifications corresponding to the target reactor, the design parameters of the yoke are determined; wherein, the design parameters of the yoke include the number of segments of the segmented yoke, the preset end distance between the yoke and the winding, and the initial magnetic circuit length and cross-sectional area of ​​each segment of the yoke. Based on the power transmission stability requirements of the target reactor during normal operation, the unsaturated region rated inductance in the basic inductance parameters is determined.

3. The method according to claim 1, characterized in that, The process of acquiring magnetic property data of the ferromagnetic material of the yoke in the target reactor, and mathematically modeling the magnetic property data to generate a dynamic permeability function model includes: Based on a preset combination of magnetization parameters, a magnetic field strength that varies continuously from low to high is applied to the ferromagnetic material to obtain magnetic induction intensity data corresponding to different magnetic field strengths. Multiple sets of magnetic field strength and magnetic induction intensity data are preprocessed to remove outliers and perform smoothing corrections, while retaining the characteristic data corresponding to hysteresis effect and remanence. Based on the analysis of the data variation patterns of multiple sets of magnetic field strength and magnetic induction intensity data, the dynamic permeability function model is obtained.

4. The method for constructing a current-limiting reactor according to claim 2, characterized in that, The construction of the magnetic circuit electrical coupling simulation model of the target reactor based on the basic design parameters and the dynamic permeability function model includes: Construct the basic simulation framework corresponding to the target reactor; The number of turns and winding structure in the core parameters of the winding are transformed into the electrical circuit topology in the basic simulation framework. The heat dissipation and insulation performance corresponding to the oil passage design parameters are converted into the medium characteristic parameters in the basic simulation framework. The segmented structure, initial magnetic circuit length, and cross-sectional area in the iron yoke design parameters are converted into the magnetic circuit entity structure in the basic simulation framework. By embedding the dynamic permeability function model into the basic simulation framework, the magnetic circuit electrical coupling simulation model of the target reactor is obtained.

5. The method for constructing a current-limiting reactor according to claim 1, characterized in that, The simulation test based on the magnetic circuit electrical coupling simulation model yields simulation results, including: Obtain the operating boundary conditions of the power system to which the target reactor belongs, and set them as the boundary conditions of the magnetic circuit electrical coupling simulation model; wherein, the boundary conditions include the system rated voltage, rated frequency and normal operating current; Input short-circuit current excitations of different amplitudes into the magnetic circuit electrical coupling simulation model and monitor key parameters in real time during the simulation process; among which, the key parameters include the reactor impedance change, inductor decay rate, short-circuit current peak suppression effect, and the magnetic induction intensity change trend of each section of the iron yoke under different short-circuit current intensities; When the key parameters meet the preset feasibility judgment conditions corresponding to the magnetic circuit electrical coupling simulation model, the magnetic circuit electrical coupling simulation model is determined to be feasible, and the simulation results are generated. When the key parameters do not meet the preset feasibility judgment conditions, the infeasibility of the magnetic circuit electrical coupling simulation model and the reasons for its infeasibility are determined, and the simulation results are generated.

6. The method according to claim 5, characterized in that, After obtaining the simulation results by performing simulation tests based on the magnetic circuit electrical coupling simulation model, the method further includes: When the simulation results indicate that the magnetic circuit electrical coupling simulation model is infeasible, the corresponding reasons for infeasibility are determined based on the simulation results; Based on the aforementioned reasons for infeasibility, the target model parameters that need to be adjusted in the magnetic circuit electrical coupling simulation model are determined; Based on the target model parameters, the parameters are adjusted to obtain updated model parameters. The updated model parameters are then updated into the magnetic circuit electrical coupling simulation model to obtain the updated magnetic circuit electrical coupling simulation model. Simulation tests were conducted based on the updated magnetic circuit electrical coupling simulation model to obtain updated simulation results.

7. A current-limiting reactor construction device, characterized in that, include: The acquisition module is used to acquire the basic design parameters of the target reactor, including the winding core parameters, oil passage design parameters, yoke design parameters, and basic inductance parameters of the target reactor. The first processing module is used to acquire magnetic property data of the ferromagnetic material of the yoke in the target reactor, perform mathematical modeling on the magnetic property data, and generate a dynamic permeability function model; the magnetic property data is obtained by measurement through testing equipment, and the dynamic permeability function describes the nonlinear relationship between magnetic induction intensity and magnetic field strength; The second processing module is used to construct a magnetic circuit electrical coupling simulation model of the target reactor based on the basic design parameters and the dynamic permeability function model. The third processing module is used to perform simulation tests based on the magnetic circuit electrical coupling simulation model, obtain simulation results, and determine the design scheme of the target reactor based on the magnetic circuit electrical coupling simulation model when the simulation results indicate that the magnetic circuit electrical coupling simulation model is feasible.

8. An electronic device, characterized in that, include: Memory, processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory, causing the processor to perform the method as described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1-6.

10. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method described in any one of claims 1-6.

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