A transformer inter-turn short circuit fault modeling method, system, device and medium

Abstract

The application belongs to the field of power equipment, and discloses a transformer inter-turn short-circuit fault modeling method, system, device and medium, which comprises the following steps: a two-dimensional geometric model of a transformer core and winding is established, the two-dimensional geometric model is discretized and divided into a plurality of magnetic network units to obtain a discrete magnetic network model; a three-dimensional electrostatic field entity model of the winding is constructed, and a distribution capacitance matrix between turns of the winding and to the ground is calculated; a short-circuit grid point is set in the discrete magnetic network model, the short-circuit grid point is connected in parallel to a metallic short-circuit branch model to obtain a short-circuit closed branch; a transformer circuit is obtained, a coupling relationship between the transformer circuit and the discrete magnetic network model is constructed based on the distribution capacitance matrix, and a transformer inter-turn short-circuit fault model is constructed. The application can accurately describe the internal space electromagnetic distribution characteristics and the local nonlinear saturation characteristics of the core of the transformer.

Description

Technical Field

[0001] This invention belongs to the field of power equipment and relates to a method, system, equipment and medium for modeling inter-turn short-circuit faults in transformers. Background Technology

[0002] During normal operation, transformers transfer energy between windings of different voltage levels through magnetic coupling. However, when an inter-turn short-circuit fault occurs, the short-circuited turns form a closed loop, generating a large induced circulating current under the coupling effect of the magnetic field of the remaining normal windings. This leads to severe distortion of the local leakage magnetic field, local magnetization of the core, and significant changes in the equivalent inductance parameters of the windings. Due to the abrupt changes in the spatial distribution and temporal characteristics of the winding electromagnetic parameters, traditional electromagnetic transient models based on linear or quasi-steady-state assumptions are insufficient to accurately simulate the electromagnetic behavior of short-circuit faults within transformers.

[0003] When a metallic inter-turn short-circuit fault occurs, the damaged turns with extremely low contact impedance cause a sharp increase in the short-circuit circulating current, severely disrupting the ampere-turn balance in the fault area. This extreme local overcurrent forcibly alters the distribution path of the main magnetic field inside the transformer, compelling the core region near the fault point to rapidly enter a deep nonlinear saturation state. Due to the significant spatial asymmetry in the internal magnetic circuit of the transformer, this local magnetic saturation and leakage magnetic distortion caused by the short circuit exhibit strong spatial discrete characteristics. Traditional port lumped parameter models struggle to map macroscopic electrical quantities to the microscopic magnetization state at specific internal locations, failing to reflect the true local electromagnetic stress at the short-circuit point. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the prior art and provide a method, system, device and medium for modeling transformer inter-turn short-circuit faults, which can accurately describe the spatial electromagnetic distribution characteristics and local nonlinear saturation characteristics of the core of the transformer.

[0005] To achieve the above objectives, the present invention employs the following technical solution: A method for modeling inter-turn short-circuit faults in transformers includes the following steps: A two-dimensional geometric model of the transformer core and windings is established, and the two-dimensional geometric model is discretized into multiple magnetic network units to obtain a discrete magnetic network model. Construct a three-dimensional electrostatic field solid model of the winding and calculate the distributed capacitance matrix between the winding turns and to ground; In the discrete magnetic network model, short-circuit grid points are set, and the short-circuit grid points are connected in parallel to the metallic short-circuit branch model to obtain the short-circuit closed branch. The transformer circuit is obtained, and based on the distributed capacitance matrix, the coupling relationship between the transformer circuit and the discrete magnetic network model is constructed. Based on the short-circuit closed branch, the magnetomotive force balance boundary conditions before and after the fault are constructed, and the transformer inter-turn short-circuit fault model is constructed according to the magnetomotive force balance boundary conditions.

[0006] Optionally, a two-dimensional geometric model of the transformer core and windings is established, and the two-dimensional geometric model is discretized into multiple magnetic network units to obtain a discrete magnetic network model, including: The magnetic circuit and windings of the transformer core are equivalent to a two-dimensional longitudinal section structure, resulting in a two-dimensional geometric model; The windings and transformer core in the two-dimensional geometric model are discretized along the horizontal and vertical directions to obtain a discrete magnetic network model.

[0007] Optionally, a three-dimensional electrostatic field solid model of the winding is constructed, and the distributed capacitance matrix between the winding turns and to ground is calculated, including: In the three-dimensional electrostatic field solid model, the scalar potential is taken as the unknown quantity, and the spatial electric field distribution in the three-dimensional electrostatic field solid model is solved by the Poisson equation to obtain the scalar potential in the three-dimensional electrostatic field solid model. The electric field intensity and electric displacement vector within the three-dimensional electrostatic field solid model are calculated based on the scalar potential. The energy storage of a three-dimensional electrostatic field solid model is obtained based on the electric field intensity and electric displacement vector; Energy storage based on a three-dimensional electrostatic field solid model is obtained by solving the distributed capacitance matrix between the winding turns and to ground through multiple excitations.

[0008] Optionally, the short-circuit grid points are connected in parallel to the metallic short-circuit branch model to obtain a short-circuit closed branch, including: Obtain the dimensions and contact state of the short-circuited conductors in the short-circuited grid points, and calculate the total equivalent resistance of the metallic short circuit based on the dimensions and contact state of the short-circuited conductors; Substituting the total equivalent resistance as a constant into the discrete magnetic network model yields the short-circuit closed branch.

[0009] Optionally, based on the distributed capacitance matrix, the coupling relationship between the transformer circuit and the discrete magnetic network model is constructed, including: The magnetic network unit includes the winding magnetic network unit and the core magnetic network unit; Based on Kirchhoff's current law and combined with the distributed capacitance matrix on the transformer circuit side, a broadband charge balance constraint equation is established for each winding magnetic network unit. The voltage column vector is obtained by solving the broadband charge balance constraint equation. The discrete magnetomotive force source in the discrete magnetic network model is initially excited by the voltage column vector. The winding current column vector containing primary and secondary side parameters in the transformer circuit is coupled into the winding current column vector of the excited discrete magnetomotive force source in the discrete magnetic network model through the coupling matrix coefficients that reflect the number of turns of the spatial structure line.

[0010] Optionally, a transformer inter-turn short-circuit fault model is constructed based on the magnetomotive force balance boundary conditions, including: The winding magnetic network unit with inter-turn insulation failure is taken as the fault winding magnetic network unit. The equivalent magnetic resistance of the leakage magnetic path between the fault winding magnetic network unit and the adjacent iron core and winding is obtained, and the local equivalent leakage inductance is calculated. In the metallic short circuit branch model, the total equivalent resistance of the metallic short circuit is combined with the local equivalent leakage inductance to construct the local fault state equation. A transformer inter-turn short-circuit fault model is constructed by simultaneously applying broadband charge balance constraint equations, local fault state equations, and magnetomotive force balance boundary conditions.

[0011] Optionally, the magnetic potential equilibrium boundary conditions before and after the fault include: During steady-state operation, the magnetomotive force balance boundary condition of the transformer is:

[0012] in, This indicates the total number of turns in the primary winding of the transformer. This represents the primary current before the fault occurred. This indicates the total number of turns in the secondary winding of the transformer. This indicates the secondary current before the fault occurred. This represents the equivalent magnetizing current of the transformer, and the primary current before the fault occurs is defined as... Secondary current before the fault occurred The positive direction is determined by the generation of a magnetomotive force in their respective windings that is in the same direction as the main magnetic flux. When an inter-turn short-circuit fault is triggered at a set time, the magnetomotive force balance boundary condition is:

[0013] in, This indicates the number of effective primary-side turns that were not short-circuited after the fault occurred. This represents the primary current after a fault occurs. This represents the secondary current after a fault occurs. This indicates the number of short-circuited turns in which an inter-turn short-circuit fault occurred. This indicates the local short-circuit circulating current after a fault occurs. The equivalent excitation current after a fault occurs is represented by the primary current after a fault occurs. Secondary current after a fault occurs The positive direction is determined by the generation of a magnetomotive force in their respective windings that is in the same direction as the main magnetic flux.

[0014] A transformer inter-turn short-circuit fault modeling system includes: The discrete magnetic network model construction module is used to establish a two-dimensional geometric model of the transformer core and windings, and to discretize the two-dimensional geometric model into multiple magnetic network units to obtain a discrete magnetic network model. The distributed capacitance matrix calculation module is used to construct a three-dimensional electrostatic field solid model of the winding and calculate the distributed capacitance matrix between the winding turns and to ground. The short-circuit closed branch acquisition module is used to set short-circuit grid points in the discrete magnetic network model, connect the short-circuit grid points in parallel to the metallic short-circuit branch model, and obtain the short-circuit closed branch. The transformer inter-turn short-circuit fault model establishment module is used to obtain the transformer circuit, construct the coupling relationship between the transformer circuit and the discrete magnetic network model based on the distributed capacitance matrix, construct the magnetomotive force balance boundary conditions before and after the fault based on the short-circuit closed branch, and construct the transformer inter-turn short-circuit fault model according to the magnetomotive force balance boundary conditions.

[0015] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the transformer inter-turn short-circuit fault modeling method.

[0016] A computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the transformer inter-turn short-circuit fault modeling method.

[0017] Compared with the prior art, the present invention has the following beneficial effects: This invention constructs a coupling relationship between the transformer circuit and the discrete magnetic network model, and combines this with the magnetomotive force balance boundary conditions before and after the fault. Based on this coupling relationship and the magnetomotive force balance boundary conditions before and after the fault, a transformer inter-turn short-circuit fault model is constructed, which can accurately describe the spatial electromagnetic distribution characteristics of the transformer and the local nonlinear saturation characteristics of the core. It reproduces the process in which the short-circuit circulating current induces severe distortion of the local leakage magnetic field, forcing the adjacent core into deep nonlinear saturation.

[0018] Furthermore, the transformer entity is discretized into a two-dimensional discrete magnetic network model, which reduces the computational load while meeting the accuracy requirements of simulation calculations. This segmented modeling approach allows for flexible setting of short circuits in specific winding segments within the two-dimensional geometric model, enabling the simulation of inter-turn short-circuit faults at different locations within the transformer. This provides a foundation for calculating the local leakage magnetic field distribution and nonlinear magnetization state of the core caused by metallic short circuits in single turns or a few turns.

[0019] Furthermore, by constructing a three-dimensional electrostatic field solid model of the transformer winding, the spatial electric field distribution is solved using scalar potential as the unknown quantity, and the distributed capacitance matrix between the winding turns and to ground is obtained by storing energy in the three-dimensional electrostatic field solid model. This allows for the accurate extraction of the spatial distributed capacitance inside the transformer, which can be used to calculate the high-frequency transmission channel established by the distributed capacitance matrix on the circuit network side of the transformer.

[0020] Furthermore, short-circuit grid points are connected in parallel to the metallic short-circuit branch model, and the total equivalent resistance of the metallic short circuit is set based on the minute contact resistance affected by the degree of insulation damage. The fault point, exhibiting a constant minute impedance characteristic, is connected as a very small constant to the discrete magnetic network model to induce local short-circuit circulating currents. Attached Figure Description

[0021] Figure 1 This is a flowchart of a transformer inter-turn short-circuit fault modeling method in Embodiment 1 of the present invention.

[0022] Figure 2 This is a schematic diagram of the winding magnetic network unit structure in Embodiment 1 of the present invention.

[0023] Figure 3 This is a schematic diagram of the iron core magnetic network unit structure in Embodiment 1 of the present invention.

[0024] Figure 4 This is a schematic diagram of the overall architecture of the discrete magnetic network model coupled with the transformer circuit in Embodiment 1 of the present invention.

[0025] Figure 5 The figure shows the simulation results of the transient response of the primary current and short-circuit circulating current when a metallic inter-turn short-circuit fault occurs in the transformer in Embodiment 1 of the present invention. Detailed Implementation

[0026] The technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings.

[0027] Example 1: This embodiment uses a three-phase, three-limb dry-type transformer as the research object. Its basic operating parameters are set as follows: rated capacity S = 30kVA, rated voltage... 2000 / 380V, rated frequency f The frequency is 50Hz, and the connection group is a typical Dyn11 (D: delta connection on the high-voltage side, y: star connection on the low-voltage side; n: neutral point lead-out on the low-voltage side; 11: 30° phase difference between high and low voltage). Under rated operating conditions, the primary side rated current... The rated current of the secondary side is 8.66A. The value is 45.58A. Regarding the physical structure and material selection, the core is a three-column design, using cold-rolled grain-oriented silicon steel sheets of grade 30Q130, with a saturation magnetic induction intensity of 45.58A. The rated operating magnetic flux density is 1.95. The setting is 1.65T. The main column diameter is 110mm, the core width is 175mm, and the core height is 290mm.

[0028] like Figure 1 As shown, this embodiment provides a transformer inter-turn short-circuit fault modeling method based on magnetic networks, which solves the problem of low accuracy in transient behavior calculation caused by the traditional electromagnetic transient model under metallic inter-turn short-circuit faults inside the transformer due to insufficient extraction of the underlying magnetomotive force balance relationship, spatial distributed capacitance and local nonlinear magnetization state.

[0029] Includes the following steps: (1) Establish a two-dimensional geometric model of the transformer core and windings, and discretize the two-dimensional geometric model into multiple magnetic network units to obtain a discrete magnetic network model.

[0030] (2) Construct a three-dimensional electrostatic field solid model of the winding and calculate the distributed capacitance matrix between the winding turns and to ground.

[0031] (3) Set short-circuit grid points in the discrete magnetic network model, and connect the short-circuit grid points in parallel to the metallic short-circuit branch model to obtain the short-circuit closed branch.

[0032] (4) Obtain the transformer circuit, construct the coupling relationship between the transformer circuit and the discrete magnetic network model based on the distributed capacitance matrix, construct the magnetic potential balance boundary conditions before and after the fault based on the short-circuit closed branch, and construct the transformer inter-turn short-circuit fault model based on the magnetic potential balance boundary conditions.

[0033] The specific steps (1) are as follows: A solid-domain geometric model of the transformer was established using ANSYS (Swanson Analysis Systems, Inc., a computer-aided engineering software) 3D geometric modeling software. In the actual structure, the transformer core has a certain longitudinal depth, and its magnetic flux distribution exhibits three-dimensional characteristics. To meet the accuracy requirements of the simulation calculation while reducing the computational load, structural details in the longitudinal depth direction of the core were ignored, and the core magnetic circuit and winding entity were equivalent to a two-dimensional longitudinal section structure, i.e., a two-dimensional geometric model.

[0034] For a three-phase, three-limb transformer, this embodiment employs a strategy of modeling the faulty phase and using equivalent boundaries for the healthy phase: For the target phase A, which experiences an inter-turn short circuit, a two-dimensional discrete magnetic network model with the A-phase main column as the center is established; the non-faulty phases B and C are equivalently loaded onto the upper and lower yoke nodes with rated current sources, participating in the solution as part of the magnetomotive force balance boundary conditions. This strategy reduces the computational load while preserving the three-phase magnetic coupling effect and meeting the simulation accuracy requirements.

[0035] The windings and core are discretized both laterally and longitudinally, resulting in a 10×4 magnetic network unit (40 units) for the two-dimensional longitudinal section structure, thus obtaining a discrete magnetic network model. This model includes both winding and core magnetic network units. This segmented modeling approach allows for flexible setting of short circuits in specific winding segments within the solid-state geometric model, enabling the configuration of inter-turn short-circuit faults at different locations within the transformer.

[0036] In constructing the discrete magnetic network model, based on the dimensions and reluctance characteristics of the windings and core, constant and nonlinear reluctance are calculated: The dimensions and reluctance characteristics of the windings and core are set. For the main core section, its cross-sectional area is set to 86.6 cm². 2 To simultaneously reflect all effective magnetic flux paths and yoke width extension along the lamination depth direction, the longitudinal reluctance equivalent cross-sectional area of ​​each core magnetic network unit is taken as 13200 mm², based on the effective area actually carrying the magnetic flux. 2 The magnetic circuit length is 10.3 mm; the equivalent cross-sectional area of ​​the transverse magnetic reluctance is taken as 2091 mm² based on the leakage magnetic channel between the winding and the core. 2 The magnetic circuit length is 60mm.

[0037] The constant reluctance of the winding magnetic network unit is calculated using the following formula:

[0038]

[0039] in, This indicates the constant magnetic reluctance of the winding magnetic network unit in the vertical direction. This indicates that the equivalent magnetic path length of the winding magnetic network unit in the vertical direction is 29mm. This represents the equivalent absolute permeability of the winding magnetic network unit. Since the winding is mainly composed of a composite of copper and insulating materials, it exhibits paramagnetism. Approximately equal to the permeability of free space for , The equivalent cross-sectional area of ​​the winding magnetic network unit in the vertical direction is... , This indicates the constant magnetic reluctance of the winding magnetic network unit in the horizontal direction. This indicates that the equivalent magnetic path length of the winding magnetic network unit in the horizontal direction is 12mm. The equivalent cross-sectional area of ​​the winding magnetic network unit in the horizontal direction is... .

[0040] In this embodiment, the core is made of multiple silicon steel sheets. Based on the magnetization curve of the actual silicon steel sheets, the operating point is tracked using the following real-time equation to obtain the differential relative permeability of the core: The formula for calculating the differential relative permeability of the iron core is:

[0041] in, The differential relative permeability of the iron core is represented by the slope of the local tangent of the magnetization curve of the silicon steel sheet at the instantaneous operating point during the solution process. This ensures that the nonlinear characteristics of the iron core reluctance unit in the deep saturation stage are accurately reflected. It indicates the magnetic flux density inside the iron core. The permeability in a vacuum is , This indicates the strength of the magnetic field inside the iron core. This represents a differential operator.

[0042] Then, the nonlinear magnetic reluctance of the iron core magnetic network unit is calculated:

[0043] in, This indicates the nonlinear reluctance of the iron core magnetic network unit. This represents the equivalent magnetic circuit length of a core magnetic network unit. This represents the differential relative permeability of the iron core, which exhibits nonlinear time-varying characteristics. This represents the equivalent cross-sectional area of ​​the iron core magnetic network unit along the magnetic flux direction. In the discrete magnetic network model of this embodiment, the equivalent magnetic path length of the iron core magnetic network unit... With equivalent cross-sectional area The specific value depends on the physical location of the core magnetic network unit in the transformer: when the unit is located in the core main column, it carries the main magnetic flux, and the set equivalent magnetic circuit length... It is 10.3 mm, with an equivalent cross-sectional area. The equivalent magnetic path length is 13200 mm²; when the element is located in the upper and lower yokes and the transverse leakage magnetic channel, the set equivalent magnetic path length is... It is 60 mm, with an equivalent cross-sectional area It is 2091 mm².

[0044] Step (2) specifically involves: A three-dimensional electrostatic field solid model of the transformer winding was constructed using ANSYS's three-dimensional dynamic electromagnetic field simulation tool.

[0045] In this three-dimensional electrostatic field solid model, the scalar potential is taken as the unknown quantity, and the spatial electric field distribution within the three-dimensional electrostatic field solid model is solved by the following Poisson equation:

[0046] in, Represents the vector differential operator. The dielectric constant of vacuum is , This represents the relative permittivity of the insulating medium in three directional vectors. For epoxy casting materials used as the primary insulating medium, The typical value for dry-type transformers is set to 3.5. This represents the scalar potential within a three-dimensional electrostatic field solid model. ρ vol This represents the volume charge density.

[0047] After obtaining the scalar potential, the electric field intensity and electric displacement vector within the three-dimensional electrostatic field solid model are further calculated, and expressed as:

[0048]

[0049] in, Represents the electric field intensity vector. This represents the electric displacement vector.

[0050] After obtaining the electric field intensity vector and electric displacement vector, the energy storage of the three-dimensional electrostatic solid model can be calculated by integrating the electric field energy density within the solution domain. The volume integral formula is as follows:

[0051] in, Indicates the first i The first winding magnetic network unit and the first j Energy storage in a three-dimensional electrostatic field solid model between winding magnetic network units, caused by potential difference. This represents the effective volume of the solution domain in which the electric field distribution is located. V Represents the volume of the solution domain. V The integration operation performed It represents the volume of a tiny element in three-dimensional space.

[0052] Furthermore, based on the energy storage of the three-dimensional electrostatic field solid model, the distributed capacitance matrix between the winding turns and to ground is further calculated. Specifically, for a three-dimensional electrostatic field solid model containing N winding magnetic network units, the following steps are taken sequentially: i Apply potential to each winding magnetic network unit The potential of the remaining winding magnetic network units is 0, and the volume integral formula is used to solve for the first... i Energy storage of the electrostatic field within each winding magnetic network unit W i This leads to the self-capacitance:

[0053] Then let the first i , j The two winding magnetic network units are respectively applied + and Potential and solve for energy storage This leads to the mutual capacitance:

[0054] in, Indicates the first j Energy storage of the electrostatic field within a winding magnetic network unit.

[0055] By using the above-mentioned method of inverse problem-solving through multiple incentives, all... i , j After combining, the complete product is obtained. Order distributed capacitance matrix .

[0056] Step (3) specifically involves: In the discrete magnetic network model, short-circuit grid points are defined and connected in parallel to the metallic short-circuit branch model to obtain a short-circuit closed branch. It is assumed that the inter-turn insulation of the short-circuit grid points has completely broken down, and the fault points exhibit constant, small impedance characteristics.

[0057] Based on the dimensions and contact conditions of the short-circuited conductors in the short-circuit grid, the total equivalent resistance of a metallic short circuit is calculated using the following formula:

[0058] in, This represents the total equivalent resistance of an inter-turn metallic short circuit. This represents the resistivity of the winding conductor. This indicates the equivalent length of the line turns where the short circuit occurred. Represents the equivalent cross-sectional area of ​​a short-circuited conductor. This represents the minute contact resistance affected by the degree of insulation damage. In transient simulation, it represents the total equivalent resistance of an inter-turn metallic short circuit. It is used as an extremely small constant to access the short-circuit grid point to induce a huge local short-circuit circulation. .

[0059] In this embodiment, the total equivalent resistance of the inter-turn metallic short circuit is calculated and set based on the conductor cross-sectional area and metallic contact characteristics of the 30kVA dry-type transformer. The Ω is 1mΩ, so as to fully excite Figure 5 The local short-circuit circulation shown is in the hundreds of amperes.

[0060] Step (4) specifically involves: The discrete magnetic network model, distributed capacitance matrix, and short-circuit closed branches are integrated into an electromagnetic transient co-simulation calculation based on MATLAB (Matrix Laboratory) / Simulink (a multi-domain dynamic system simulation software). The solution step size for the transient co-simulation is set to 10. The short-circuit closed branch is closed 70ms after the transient simulation reaches steady state to trigger a fault. A transient coupled equation set (transformer inter-turn short-circuit fault model) is constructed and solved bidirectionally under the constraint of magnetomotive force balance boundary conditions to complete the establishment of the transformer inter-turn short-circuit fault model. The transient simulation results of the severe distortion of the local leakage magnetic field and the deep nonlinear saturation evolution of the iron core are output through the transformer inter-turn short-circuit fault model.

[0061] First, on the circuit network side of the transformer, in order to take into account the high-frequency transmission channel established by the distributed capacitance matrix in step (2), the broadband charge balance constraint equations of each winding magnetic network unit are established according to Kirchhoff's current law:

[0062] in, This represents the distributed capacitance matrix extracted in step (2). This represents the voltage column vector of the winding magnetic network unit. This represents the total current injected by the external power source at the node: for both the first and last nodes connected to the external power source, Equal to the external power supply current, for the nodes inside the winding magnetic network unit, constrained by Kirchhoff's current law, at the node... To satisfy the charge conservation relationship, the two types of nodal equations are combined to form a complete set of circuit-side constraint equations. This is the sum of the conduction currents flowing through the winding branch and the short-circuit branch. Describes the differential operator. Represents time. Voltage column vector obtained from solving the broadband charge balance constraint equation. It serves as the initial electrodynamic source for subsequent discrete magnetomotive force source excitation.

[0063] Secondly, the coupling relationship between the transformer main circuit and the discrete magnetic network model is constructed, i.e., the coupling matrix equation. Among them, the discrete magnetomotive force source vector equation and the winding current column vector equation are:

[0064] in, This represents the column vector of excited discrete magnetomotive force sources in the discrete magnetic network model. ， … Indicates the first The first to the second The specific components of a discrete magnetomotive force source. This represents the winding current column vector containing primary and secondary side parameters. This represents the primary winding current variable in a discrete magnetic network model. This represents the secondary winding current variable in a discrete magnetic network model.

[0065] The coupling matrix equation for the current in the transformer circuit to the excitation potential in the discrete magnetic network model is expressed as:

[0066] in, This represents the coupling matrix coefficients that reflect the number of turns of the spatial structure lines.

[0067] Using the constant and nonlinear reluctance calculated in step (1), the matrix equation of Ohm's law for the magnetic circuit of the discrete magnetic network model is established, and the column vector of alternating magnetic flux in each branch of all magnetic network units is solved. :

[0068] in, Let each branch be a column vector of alternating magnetic flux. The equivalent reluctance matrix is ​​composed of the constant reluctance calculated in step (1) and the nonlinear iron core reluctance.

[0069] The alternating magnetic flux column vector of each branch is fed back as the induced electromotive force in the transformer circuit, and the control relationship is as follows:

[0070] in, This represents the induced electromotive force generated within the winding magnetic network unit. This indicates the number of wire turns in the corresponding winding magnetic network unit. Indicates from The magnetic flux passing through the corresponding magnetic network unit is extracted according to the topology of the winding magnetic network. Represents the global rate of change of magnetic flux. Describes the differential operator. Indicates time.

[0071] Next, taking the winding magnetic network unit where the inter-turn insulation has failed as the faulty winding magnetic network unit, and based on the short-circuit closed branch connected in step (3), establish the local fault state equation:

[0072] The local fault state equation determines the local short-circuit circulating current excited by the induced electromotive force. The transient response amplitude. Among them, From The induced electromotive force extracted from the faulty winding magnetic network unit. The total equivalent resistance of the inter-turn metallic short circuit calculated in step (3); The local equivalent leakage inductance corresponding to the faulty winding magnetic network unit is obtained by extracting the equivalent magnetic reluctance of the leakage magnetic path from the faulty winding unit to adjacent iron cores and windings from the discrete magnetic network model, that is:

[0073] in, This indicates the number of short-circuited turns in which an inter-turn short-circuit fault occurred. The equivalent magnetic reluctance of the leakage magnetic path is extracted from the constant horizontal magnetic reluctance of the winding magnetic network unit established in step (1) and calculated in combination with the local mesh topology of the branch in which it is located.

[0074] The specific magnetic potential balance boundary conditions before and after the fault include: During steady-state operation, the boundary condition equation for the transformer's magnetomotive force balance is:

[0075] in, This indicates the total number of turns in the primary winding of the transformer. This represents the primary current before the fault occurred. This indicates the total number of turns in the secondary winding of the transformer. This indicates the secondary current before the fault occurred. This represents the equivalent magnetizing current of the transformer, and the primary current before the fault occurs is defined as... Secondary current before the fault occurred The positive direction is determined by the generation of a magnetomotive force in their respective windings that is in the same direction as the main magnetic flux.

[0076] When an inter-turn short-circuit fault is triggered at a set time, the magnetomotive force balance boundary condition equation for the short-circuit turn effect is expressed as:

[0077] in, This indicates the number of effective primary-side turns that were not short-circuited after the fault occurred. This represents the primary current after a fault occurs. This represents the secondary current after a fault occurs. This indicates the number of short-circuited turns in which an inter-turn short-circuit fault occurred. This indicates the local short-circuit circulating current after a fault occurs. The equivalent excitation current after a fault occurs is represented by the primary current after a fault occurs. Secondary current after a fault occurs The positive direction is determined by the generation of a magnetomotive force in their respective windings that is in the same direction as the main magnetic flux.

[0078] Furthermore, the physical structure strictly satisfies the conservation constraint equation for the total number of turns:

[0079] In this embodiment, the total number of turns of the primary winding of the transformer is set. The total number of turns in the secondary winding is 400. The number of turns is 76. For the high-voltage side winding's magnetic network unit division, each winding magnetic network unit contains 20 turns. Therefore, when an internal metallic short circuit occurs in a certain high-voltage winding network unit, the number of faulty turns is... The value is 20 turns, which corresponds to the number of effective primary-side turns that were not short-circuited after a fault. It has 380 turns.

[0080] The purpose of the above magnetic potential balance boundary conditions is to serve as a global energy conservation constraint, which can effectively correct the accumulated truncation error caused by local deep saturation distortion in the discrete magnetic network model, and provide a definite convergence trajectory for the nonlinear Newton-Raphson iteration of the transient coupled equation set (transformer inter-turn short-circuit fault model), avoiding the solver from diverging in the deep nonlinear region, and ensuring the rigor and numerical stability of the calculation results.

[0081] Finally, the broadband charge balance constraint equation, the local fault state equation, and the magnetomotive force balance boundary conditions are combined to construct a transformer inter-turn short-circuit fault model based on the magnetomotive force balance boundary conditions.

[0082] A bidirectional coupled solution is used to solve the transformer inter-turn short-circuit fault model, obtaining the changes in winding current and local short-circuit circulating current throughout the fault process. The specific solution process is as follows: At the start of each simulation time step, the winding current column vector from the previous time step is used. The current discrete magnetomotive force source is calculated and excited through the aforementioned coupling matrix equation. .

[0083] Based on the differential relative permeability of the iron core at the previous time step operating point Update the equivalent magnetoresistive matrix The nonlinear reluctance component of the iron core is solved by addressing the aforementioned Ohm's law matrix equation for the magnetic circuit, and based on the discrete magnetomotive force source. This yields the current alternating magnetic flux column vectors for each branch. .

[0084] Based on the current alternating magnetic flux column vectors of each branch Extract the magnetic flux passing through each winding magnetic network unit. Calculate the induced electromotive force using the time derivative of magnetic flux. And feed it back to the transformer circuit side, using induced electromotive force. Update the local fault state equations.

[0085] Based on the updated local fault state equations, the transformer inter-turn short-circuit fault model is updated, and the winding current column vector at the current time step is solved. With local short-circuit circulation .

[0086] To address the nonlinear characteristics of the iron core, a nonlinear Newton-Raphson iterative method is employed in each time step until both magnetic flux and current simultaneously satisfy the convergence criterion.

[0087] After the current time step is solved, time advances to the next time step until the total simulation duration ends.

[0088] This embodiment successfully simulates the broadband and local spatial transient evolution of a transformer during an internal metallic inter-turn short-circuit fault by constructing a discrete magnetic network model of the core and windings containing a distributed magnetic network. This method reproduces the physical process by which a large short-circuit circulating current induces severe distortion of the local leakage magnetic field, forcing adjacent cores into deep nonlinear saturation. It also reveals in depth the nonlinear magnetization and electromagnetic coupling characteristics of the equipment under metallic inter-turn short-circuit faults at different locations and with different turn ratios.

[0089] Figure 2 and Figure 3 These are schematic diagrams of the magnetic network unit structure of the transformer winding and the iron core in this embodiment. This represents the equivalent winding resistance on the transformer circuit side within the winding magnetic network unit. C The equivalent distributed capacitance between turns and to ground of the magnetic network unit of this winding is the equivalent distributed capacitance of all winding magnetic network units inside the transformer when performing bidirectional electromagnetic transient coupling calculations. C Together, they constitute the global distributed capacitance matrix in the aforementioned broadband charge balance constraint equation. . This represents the constant magnetic reluctance of the winding magnetic network unit in the vertical direction. This indicates the constant magnetic reluctance of the winding magnetic network unit in the horizontal direction. This represents the nonlinear reluctance of the core magnetic network unit. To accurately assess the impact of inter-turn faults within the transformer windings on the spatial magnetic circuit distribution, this embodiment discretizes the transformer entity into a two-dimensional discrete magnetic network model. The winding magnetic network unit is set as a linear reluctance characterizing healthy turns, while the core magnetic network unit is set as a dynamic nonlinear reluctance based on the actual material magnetization curve. This discrete magnetic network model primarily reflects the broadband magnetic field transmission characteristics of the transformer, providing a physical network for calculating the local leakage magnetic field distribution and the nonlinear magnetization state of the core caused by metallic short circuits in a single turn or a few turns.

[0090] Figure 4 This is a schematic diagram of the overall architecture of the discrete magnetic network model coupled with the transformer circuit in this embodiment. In the discrete magnetic network model, the winding magnetic network unit is located within the thick black box area in the diagram, representing the magnetic flux transmission path in the winding region. The core magnetic network unit is represented by reluctance branches arranged adjacent to the thick black box area, mainly including upper and lower transverse reluctance chains and longitudinal reluctance branches, representing the core main column, upper and lower yokes, and their adjacent magnetic flux paths. The dashed line represents the transformer circuit. It represents the equivalent external AC power supply on the primary side of the transformer, providing external node injection current excitation for the system's broadband charge balance constraint equations. The diagram shows the equivalent load resistance connected to the secondary side of the transformer. The diamond-shaped blocks represent electromagnetic couplers, indicating the coupling relationship between the transformer circuit and the discrete magnetic network model. The architecture achieves numerical interaction between the circuit network and the magnetic network units through a discrete magnetomotive force source and a controlled induced electromotive force. For inter-turn metallic short-circuit scenarios within the transformer, this architecture supports the connection of a metallic short-circuit branch model with constant characteristics at preset short-circuit grid points through logical expansion of the matrix dimension. Under the constraint of magnetomotive force balance boundary conditions, this architecture achieves macro- and micro-level collaborative calculation of the power frequency current distribution within the closed short-circuit turn and its impact on the demagnetization of the local main magnetic flux, without requiring changes to the electromagnetic topology of the transformer body.

[0091] Figure 5 To obtain the transient response waveform of the transformer metallic inter-turn short-circuit fault based on the transformer inter-turn short-circuit fault model in this embodiment through bidirectional coupling solution, the waveform was compared with the calculation results of the finite element reference model. Figure 5 As shown in the lower waveform, due to the purely metallic contact at the fault point, a high-amplitude power-frequency short-circuit circulating current is generated in the short-circuit branch after the fault. This waveform exhibits a smooth sinusoidal evolution without high-frequency pulses or zero-crossing distortion. Affected by the demagnetizing effect of this localized large short-circuit current, the iron core near the fault point enters a deep nonlinear saturation state, leading to… Figure 5The primary current waveform at the top exhibits a corresponding flat-top distortion. Simulation comparison results show that the discrete magnetic network model established in this embodiment can accurately reproduce the physical process of low-frequency large current sudden change under constant impedance fault. Its calculation results are consistent with the finite element model, verifying the accuracy and reliability of this embodiment in analyzing the local magnetic circuit saturation and underlying electromagnetic coupling mechanism inside the transformer.

[0092] To address the limitations of traditional lumped parameter models in reflecting the distribution of the magnetic field inside a transformer, this embodiment employs a two-dimensional discrete magnetic network model. This model can accurately capture the local leakage magnetic field distortion caused by metallic inter-turn short-circuit currents, as well as the nonlinear saturation evolution process of the adjacent core, effectively improving the calculation accuracy of the local electromagnetic state inside the transformer.

[0093] This embodiment integrates the short-circuit grid points of the discrete magnetic network model with the metallic short-circuit branch model. This structure not only accurately reflects the large current characteristics caused by the small contact resistance of the short-circuit grid points, but also preserves the transmission path of transient pulses in the discrete magnetic network model, achieving a comprehensive analysis of the broadband transient characteristics of transformer inter-turn short circuits.

[0094] This embodiment constructs a coupling matrix between the discrete magnetomotive force vector and the winding current vector, and applies magnetomotive force balance boundary conditions for the pre-fault steady-state and post-fault damaged states. This approach ensures the rigor of the short-circuit energy transfer and excitation potential cancellation process, significantly improving the reliability and accuracy of the inter-turn short-circuit electromagnetic transient co-simulation.

[0095] Example 2: In this embodiment, a transformer inter-turn short-circuit fault modeling system is provided. This system can be used to implement the above-mentioned transformer inter-turn short-circuit fault modeling method. Specifically, the transformer inter-turn short-circuit fault modeling system includes a discrete magnetic network model construction module, a distributed capacitance matrix calculation module, a short-circuit closed branch acquisition module, and a transformer inter-turn short-circuit fault model establishment module.

[0096] The discrete magnetic network model construction module is used to establish a two-dimensional geometric model of the transformer core and windings, and to discretize the two-dimensional geometric model into multiple magnetic network units to obtain a discrete magnetic network model.

[0097] The distributed capacitance matrix calculation module is used to construct a three-dimensional electrostatic field solid model of the winding and calculate the distributed capacitance matrix between the winding turns and to ground.

[0098] The short-circuit closed branch acquisition module is used to set short-circuit grid points in the discrete magnetic network model, connect the short-circuit grid points in parallel to the metallic short-circuit branch model, and obtain the short-circuit closed branch.

[0099] The transformer inter-turn short-circuit fault model establishment module is used to obtain the transformer circuit. Based on the distributed capacitance matrix, it constructs the coupling relationship between the transformer circuit and the discrete magnetic network model. Based on the short-circuit closed branch, it constructs the magnetomotive force balance boundary conditions before and after the fault, and constructs the transformer inter-turn short-circuit fault model according to the magnetomotive force balance boundary conditions.

[0100] Example 3: This embodiment provides a computer device including a processor and a memory. The memory stores a computer program, which includes program instructions. The processor executes the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), but it can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), or field-programmable gate arrays (FPGAs). Gate Array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc., are the computing and control core of computer equipment. They are suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions to realize corresponding method flows or corresponding functions. The processor described in this embodiment of the invention can be used for the operation of the transformer inter-turn short-circuit fault modeling method, including: establishing a two-dimensional geometric model of the transformer core and windings, discretizing the two-dimensional geometric model into multiple magnetic network units to obtain a discrete magnetic network model; constructing a three-dimensional electrostatic field solid model of the windings, calculating the distributed capacitance matrix between winding turns and to ground; setting short-circuit grid points in the discrete magnetic network model, connecting the short-circuit grid points in parallel to the metallic short-circuit branch model to obtain a short-circuit closed branch; obtaining the transformer circuit, constructing the coupling relationship between the transformer circuit and the discrete magnetic network model based on the distributed capacitance matrix, constructing the magnetomotive force balance boundary conditions before and after the fault based on the short-circuit closed branch, and constructing the transformer inter-turn short-circuit fault model according to the magnetomotive force balance boundary conditions.

[0101] Example 4: This embodiment provides a computer-readable storage medium (Memory), which is a memory device in a terminal device used to store programs and data. It is understood that the computer-readable storage medium here can include both the built-in storage medium in a computer device and extended storage media supported by the computer device. The computer-readable storage medium provides storage space that stores the operating system of the computer device. Furthermore, this storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more computer programs (including program code). It should be noted that the computer-readable storage medium here can be high-speed RAM (Random Access Memory) or non-volatile memory, such as at least one disk storage device.

[0102] One or more instructions stored in a computer-readable storage medium can be loaded and executed by a processor to implement the corresponding steps of the transformer inter-turn short-circuit fault modeling method in the above embodiments. One or more instructions in the computer-readable storage medium are loaded and executed by the processor as follows: establish a two-dimensional geometric model of the transformer core and windings, discretize the two-dimensional geometric model into multiple magnetic network units to obtain a discrete magnetic network model; construct a three-dimensional electrostatic field solid model of the windings, and calculate the distributed capacitance matrix between winding turns and to ground; set short-circuit grid points in the discrete magnetic network model, and connect the short-circuit grid points in parallel to the metallic short-circuit branch model to obtain a short-circuit closed branch; obtain the transformer circuit, construct the coupling relationship between the transformer circuit and the discrete magnetic network model based on the distributed capacitance matrix, construct the magnetomotive force balance boundary conditions before and after the fault based on the short-circuit closed branch, and construct the transformer inter-turn short-circuit fault model according to the magnetomotive force balance boundary conditions.

[0103] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, optical storage, etc.) containing computer-usable program code.

[0104] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0105] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0106] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0107] In the above embodiments of this application, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0108] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

[0109] It should be understood that the above description is for illustrative purposes and not for limitation. Many embodiments and applications beyond the examples provided will become apparent to those skilled in the art upon reading the above description.

Claims

1. A method for modeling inter-turn short-circuit faults in transformers, characterized in that, Includes the following processes: A two-dimensional geometric model of the transformer core and windings is established, and the two-dimensional geometric model is discretized into multiple magnetic network units to obtain a discrete magnetic network model. Construct a three-dimensional electrostatic field solid model of the winding and calculate the distributed capacitance matrix between the winding turns and to ground; In the discrete magnetic network model, short-circuit grid points are set, and the short-circuit grid points are connected in parallel to the metallic short-circuit branch model to obtain the short-circuit closed branch. The transformer circuit is obtained, and based on the distributed capacitance matrix, the coupling relationship between the transformer circuit and the discrete magnetic network model is constructed. Based on the short-circuit closed branch, the magnetomotive force balance boundary conditions before and after the fault are constructed, and the transformer inter-turn short-circuit fault model is constructed according to the magnetomotive force balance boundary conditions.

2. The transformer inter-turn short-circuit fault modeling method according to claim 1, characterized in that, A two-dimensional geometric model of the transformer core and windings is established. This two-dimensional geometric model is then discretized into multiple magnetic network units, resulting in a discrete magnetic network model, including: The magnetic circuit and windings of the transformer core are equivalent to a two-dimensional longitudinal section structure, resulting in a two-dimensional geometric model. The windings and transformer core in the two-dimensional geometric model are discretized along the horizontal and vertical directions to obtain a discrete magnetic network model.

3. The transformer inter-turn short-circuit fault modeling method according to claim 1, characterized in that, Calculate the distributed capacitance matrix between winding turns and to ground, including: In the three-dimensional electrostatic field solid model, the scalar potential is taken as the unknown quantity, and the spatial electric field distribution in the three-dimensional electrostatic field solid model is solved by the Poisson equation to obtain the scalar potential in the three-dimensional electrostatic field solid model. The electric field intensity and electric displacement vector within the three-dimensional electrostatic field solid model are calculated based on the scalar potential. The energy storage of a three-dimensional electrostatic field solid model is obtained based on the electric field intensity and electric displacement vector; Energy storage based on a three-dimensional electrostatic field solid model is obtained by solving the distributed capacitance matrix between the winding turns and to ground through multiple excitations.

4. The transformer inter-turn short-circuit fault modeling method according to claim 1, characterized in that, By connecting the short-circuit grid points in parallel to the metallic short-circuit branch model, a short-circuit closed branch is obtained, including: Obtain the dimensions and contact state of the short-circuited conductors in the short-circuited grid points, and calculate the total equivalent resistance of the metallic short circuit based on the dimensions and contact state of the short-circuited conductors; Substituting the total equivalent resistance as a constant into the discrete magnetic network model yields the short-circuit closed branch.

5. The transformer inter-turn short-circuit fault modeling method according to claim 1, characterized in that, Based on the distributed capacitance matrix, the coupling relationship between the transformer circuit and the discrete magnetic network model is constructed, including: The magnetic network unit includes the winding magnetic network unit and the core magnetic network unit; Based on Kirchhoff's current law and combined with the distributed capacitance matrix on the transformer circuit side, a broadband charge balance constraint equation is established for each winding magnetic network unit. The voltage column vector is obtained by solving the broadband charge balance constraint equation. The voltage column vector is used as the initial electromotive force source to initially excite the discrete magnetomotive force source in the discrete magnetic network model. The winding current column vector containing the primary and secondary side parameters of the transformer circuit is coupled into the column vector of the excited discrete magnetomotive force source in the discrete magnetic network model through the coupling matrix coefficients that reflect the number of turns of the spatial structure line.

6. The transformer inter-turn short-circuit fault modeling method according to claim 5, characterized in that, A transformer inter-turn short-circuit fault model is constructed based on the magnetomotive force balance boundary conditions, including: The winding magnetic network unit with inter-turn insulation failure is taken as the fault winding magnetic network unit. The equivalent magnetic resistance of the leakage magnetic path between the fault winding magnetic network unit and the adjacent iron core and winding is obtained, and the local equivalent leakage inductance is calculated. In the metallic short circuit branch model, the total equivalent resistance of the metallic short circuit is combined with the local equivalent leakage inductance to construct the local fault state equation. A transformer inter-turn short-circuit fault model is constructed by simultaneously applying broadband charge balance constraint equations, local fault state equations, and magnetomotive force balance boundary conditions.

7. The transformer inter-turn short-circuit fault modeling method according to claim 1, characterized in that, The magnetic potential equilibrium boundary conditions before and after the fault include: During steady-state operation, the magnetomotive force balance boundary condition of the transformer is: in, This indicates the total number of turns in the primary winding of the transformer. This represents the primary current before the fault occurred. This indicates the total number of turns in the secondary winding of the transformer. This indicates the secondary current before the fault occurred. This represents the equivalent magnetizing current of the transformer, and the primary current before the fault occurs is defined as... Secondary current before the fault occurred The positive direction is determined by the generation of a magnetomotive force in their respective windings that is in the same direction as the main magnetic flux. When an inter-turn short-circuit fault is triggered at a set time, the magnetomotive force balance boundary condition is: in, This indicates the number of effective primary-side turns that were not short-circuited after the fault occurred. This represents the primary current after a fault occurs. This represents the secondary current after a fault occurs. This indicates the number of short-circuited turns in which an inter-turn short-circuit fault occurred. This indicates the local short-circuit circulating current after a fault occurs. The equivalent excitation current after a fault occurs is represented by the primary current after a fault occurs. Secondary current after a fault occurs The positive direction is determined by the generation of a magnetomotive force in their respective windings that is in the same direction as the main magnetic flux.

8. A transformer inter-turn short-circuit fault modeling system, characterized in that, include: The discrete magnetic network model construction module is used to establish a two-dimensional geometric model of the transformer core and windings, and to discretize the two-dimensional geometric model into multiple magnetic network units to obtain a discrete magnetic network model. The distributed capacitance matrix calculation module is used to construct a three-dimensional electrostatic field solid model of the winding and calculate the distributed capacitance matrix between the winding turns and to ground. The short-circuit closed branch acquisition module is used to set short-circuit grid points in the discrete magnetic network model, connect the short-circuit grid points in parallel to the metallic short-circuit branch model, and obtain the short-circuit closed branch. The transformer inter-turn short-circuit fault model establishment module is used to obtain the transformer circuit, construct the coupling relationship between the transformer circuit and the discrete magnetic network model based on the distributed capacitance matrix, construct the magnetomotive force balance boundary conditions before and after the fault based on the short-circuit closed branch, and construct the transformer inter-turn short-circuit fault model according to the magnetomotive force balance boundary conditions.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the transformer inter-turn short-circuit fault modeling method as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the transformer inter-turn short-circuit fault modeling method as described in any one of claims 1 to 7.

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