Secondary short-circuit current calculation method, device and equipment for transformer and storage medium

Abstract

The invention discloses a secondary short-circuit current calculation method and device for a transformer, equipment and a storage medium. The method comprises the steps that residual magnetism of the transformer after primary short circuit and the secondary short-circuit duration of the transformer are acquired; inputting the residual magnetism and the secondary short-circuit duration into a magnetic current model obtained by pre-training, so that the magnetic current model determines a corresponding formula for calculating a secondary short-circuit current according to the secondary short-circuit duration; wherein the magnetic current model comprises a plurality of quadratic polynomials for calculating secondary short-circuit current based on residual magnetism, and each quadratic polynomial corresponds to secondary short-circuit duration; and taking the output of the magnetic current model as a short-circuit current peak value of the transformer in the secondary short circuit. According to the method, the peak value of the secondary short-circuit current is calculated based on the residual magnetism of the transformer after the primary short circuit, and the secondary short-circuit current is calculated without using a current detection instrument, so that the calculation cost is saved, and the calculation efficiency is improved.

Description

Technical Field

[0001] The present invention belongs to the field of electric power, relates to a method for calculating current, and particularly relates to a method, device, equipment and storage medium for calculating the secondary short-circuit current of a transformer. Background Art

[0002] A transformer is an important device in the power system. During its operation, a short-circuit fault can easily cause mechanical damage to the transformer winding, such as winding deformation, rupture of insulating cardboard, etc. Especially in transformers with a voltage level of 110 kV and above, the proportion of winding damage faults caused by short-circuit impacts is the largest.

[0003] When a short-circuit fault occurs in the power system, the circuit breaker will act in time to cut off the faulty circuit for relay protection to ensure the stable operation of the power grid. In the case where the short-circuit fault is an instantaneous fault, the reclosing usually can quickly restore power supply, ensure the normal operation of the power grid, and reduce user losses. In the case where the short-circuit fault is a permanent fault, when the reclosing restores power supply, the circuit breaker will cut off the faulty circuit for the second time, resulting in a secondary short circuit, and the secondary short circuit will cause continuous impact on the power grid in a short time.

[0004] When calculating the short-circuit current, the remanence effect of the transformer has a significant impact on the peak value of the short-circuit current. After the transformer has experienced a short circuit once, there will be some residual magnetic flux in its iron core part, and this part of the remanence will affect the subsequent short-circuit current. In the case of reclosing, the interaction between the remanence effect and the closing phase angle will cause the peak value of the secondary short-circuit current to change. Therefore, considering the influence of remanence on the peak value of the short-circuit current is an important factor in evaluating the short-circuit resistance ability of the transformer. Summary of the Invention

[0005] In view of this, the present invention discloses a method, device, equipment and storage medium for calculating the secondary short-circuit current of a transformer, which can solve the deficiencies existing in the related technologies.

[0006] To achieve the above object, the present invention discloses the following technical solutions:

[0007] According to the first aspect of the present invention, a method for calculating the secondary short-circuit current of a transformer is proposed, and the method includes:

[0008] Obtain the remanence of the transformer after the first short circuit and the secondary short-circuit duration of the transformer;

[0009] Input the remanence and the secondary short-circuit duration into a pre-trained magnetic current model, so that the magnetic current model determines a corresponding formula for calculating the secondary short-circuit current according to the secondary short-circuit duration; wherein, the magnetic current model contains multiple quadratic polynomials for calculating the secondary short-circuit current based on remanence, and each quadratic polynomial corresponds to a secondary short-circuit duration;

[0010] Use the output of the magnetic flux model as the peak short-circuit current of the transformer in the secondary short circuit.

[0011] As a preferred solution, the multiple quadratic polynomials include a first polynomial, a second polynomial, and a third polynomial;

[0012] The first polynomial is: when the short-circuit duration is 60 ms, the short-circuit current after reclosing is calculated as:

[0013] I m = -192875.24x 2 + 1277837.72x - 2066355.96;

[0014] The second polynomial is:

[0015] I m = -125334.46x 2 + 691925.55x - 910502.47;

[0016] The third polynomial is:

[0017] I m = 799.14x 2 - 3727.83x + 38903.64;

[0018] Where x represents the residual magnetism of the transformer after the first short circuit, the secondary short-circuit duration corresponding to the first polynomial is 60 ms, the secondary short-circuit duration corresponding to the second polynomial is 120 ms, and the secondary short-circuit duration corresponding to the third polynomial is 200 ms.

[0019] As a preferred solution, before calculating the secondary short-circuit current, the method further includes:

[0020] Obtain the structural information of the iron core and winding of the transformer, and establish a geometric model of the transformer according to the structural information;

[0021] Set the constitutive relationship of the iron core part of the geometric model to the J-A model, and determine the model parameters of the J-A model according to the silicon content of the silicon steel sheet of the transformer;

[0022] Construct a simulation system for the transformer fault according to the voltage level, wiring method, and the geometric model of the transformer, and obtain a training data set through the simulation system; where each training sample in the training data set includes the secondary short-circuit duration, the residual magnetism of the transformer after the first short circuit, and the peak secondary short-circuit current;

[0023] Train the magnetic flux model according to the training data set.

[0024] As a preferred solution, the model parameters include: saturation magnetization Ms, domain wall density a, pinning loss kp, magnetization reversibility cr, and inter-domain coupling α;

[0025] When the silicon content of the silicon steel sheet of the transformer is 2%, the saturation magnetization Ms is 1e6 A / m, the domain wall density a is 60 A / m, the pinning loss kp is 100 A / m, the magnetization reversibility cr is 0.3, and the inter-domain coupling α is 1.5e-5.

[0026] As a preferred solution, obtaining the training data set through the simulation system includes:

[0027] Set the primary open circuit time t of the transformer in the simulation system 1 , reclosing time t 2 , secondary open circuit time t 3 , the output time step is t 4 , and the tolerance is controlled by the physical field;

[0028] Set the rated voltage of the high voltage side of the transformer in the simulation system to the rated voltage value, and set the resistance value to the system impedance value.

[0029] According to the second aspect of the present invention, a device for calculating the secondary short-circuit current of a transformer is proposed. The device includes:

[0030] The first acquisition unit: acquires the residual magnetism after the primary short circuit of the transformer and the secondary short circuit duration of the transformer;

[0031] The input unit: inputs the residual magnetism and the secondary short circuit duration into a pre-trained magnetic flux model, so that the magnetic flux model determines a corresponding formula for calculating the secondary short circuit current according to the secondary short circuit duration; wherein, the magnetic flux model contains multiple quadratic polynomials for calculating the secondary short circuit current based on the residual magnetism, and each quadratic polynomial corresponds to a secondary short circuit duration;

[0032] The output unit: takes the output of the magnetic flux model as the short-circuit current peak value of the transformer during the secondary short circuit.

[0033] As a preferred solution, the multiple quadratic polynomials include a first polynomial, a second polynomial, and a third polynomial;

[0034] The first polynomial is: when the short circuit duration is 60 ms, the short circuit current calculation after reclosing is:

[0035] I m =-192875.24x2 +1277837.72x - 2066355.96;

[0036] The second polynomial is:

[0037] I m = -125334.46x 2 +691925.55x - 910502.47;

[0038] The third polynomial is:

[0039] I m = 799.14x 2 -3727.83x + 38903.64;

[0040] Where x represents the residual magnetism of the transformer after the first short circuit, the second short - circuit duration corresponding to the first polynomial is 60 ms, the second short - circuit duration corresponding to the second polynomial is 120 ms, and the second short - circuit duration corresponding to the third polynomial is 200 ms.

[0041] As a preferred solution, before calculating the secondary short - circuit current, the device further includes:

[0042] A second acquisition unit: acquiring the structural information of the iron core and winding of the transformer, and establishing a geometric model of the transformer according to the structural information;

[0043] A setting unit: setting the constitutive relationship of the iron - core part of the geometric model to the J - A model, and determining the model parameters of the J - A model according to the silicon content of the silicon steel sheet of the transformer;

[0044] A simulation unit: constructing a simulation system for the transformer fault according to the voltage level, wiring mode of the transformer and the geometric model, and obtaining a training data set through the simulation system; wherein, each training sample in the training data set includes the secondary short - circuit duration, the residual magnetism of the transformer after the first short circuit, and the peak value of the secondary short - circuit current;

[0045] A training unit: training the magnetic - current model according to the training data set

[0046] According to the third aspect of the present invention, an electronic device is proposed, including:

[0047] A processor;

[0048] A memory for storing instructions executable by the processor;

[0049] Wherein, the processor realizes the steps of the method as described in the first aspect by running the executable instructions.

[0050] According to a fourth aspect of the present invention, there is provided a computer-readable storage medium having computer instructions stored thereon, which when executed by a processor implement the steps of the method as described in the first aspect.

[0051] As can be seen from the above technical solutions, the method for calculating the secondary short-circuit current of a transformer disclosed in the present invention calculates the peak value of the secondary short-circuit current based on the residual magnetism after the first short-circuit of the transformer. On the one hand, without using a current detection instrument, the calculation of the secondary short-circuit current is realized, thus saving the calculation cost and improving the calculation efficiency. On the other hand, not only the influence of the residual magnetism on the magnitude of the short-circuit current is considered, but also the influence of the secondary short-circuit duration is considered, making the calculation result more accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 is a flowchart of a method for calculating the secondary short-circuit current of a transformer provided by an exemplary embodiment.

[0053] Figure 2 is a schematic structural diagram of a device provided by an exemplary embodiment.

[0054] Figure 3 is a block diagram of a device for calculating the secondary short-circuit current of a transformer provided by an exemplary embodiment. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0055] Here, the exemplary embodiments will be described in detail, and the examples are shown in the drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with one or more embodiments of the present invention. On the contrary, they are only examples of devices and methods consistent with some aspects of one or more embodiments of the present invention as detailed in the appended claims.

[0056] It should be noted that: in other embodiments, the steps of the corresponding methods are not necessarily executed in the order shown and described in the present invention. In some other embodiments, the steps included in the method may be more or less than those described in the present invention. In addition, a single step described in the present invention may be decomposed into multiple steps for description in other embodiments; and multiple steps described in the present invention may also be combined into a single step for description in other embodiments.

[0057] To further illustrate the present invention, the following embodiments are provided:

[0058] Transformer is an important device in the power system. During its operation, short - circuit faults are extremely likely to cause mechanical damage to the transformer windings, such as winding deformation, insulation paperboard rupture, etc. Especially in transformers with a voltage level of 110 kV and above, the winding damage faults caused by short - circuit impacts account for the largest proportion.

[0059] When a short - circuit fault occurs in the power system, the circuit breaker will act promptly to cut off the faulty circuit for relay protection to ensure the stable operation of the power grid. In the case where the short - circuit fault is an instantaneous fault, the reclosing usually can quickly restore power supply, ensure the normal operation of the power grid, and reduce user losses. In the case where the short - circuit fault is a permanent fault, when the reclosing restores power supply, the circuit breaker will cut off the faulty circuit for the second time, resulting in a secondary short - circuit. The secondary short - circuit will cause continuous impacts on the power grid in a short time.

[0060] When calculating the short - circuit current, the residual magnetic effect of the transformer has a significant impact on the peak value of the short - circuit current. After the transformer experiences a short - circuit once, there will be some residual magnetic flux in its iron core part. This part of the residual magnetic flux will affect the subsequent short - circuit current. In the case of reclosing, the interaction between the residual magnetic effect and the closing phase angle will cause changes in the peak value of the secondary short - circuit current. Therefore, considering the influence of residual magnetism on the peak value of the short - circuit current is an important factor in evaluating the short - circuit resistance ability of the transformer.

[0061] To solve the problem of calculating the current peak value during the secondary short - circuit of the transformer, the present invention proposes a method for calculating the secondary short - circuit current of the transformer.

[0062] Figure 1 It is a flowchart of a method for calculating the secondary short - circuit current of the transformer provided by an exemplary embodiment. As Figure 1 shown, the method may include the following steps:

[0063] Step 102, obtain the residual magnetism of the transformer after the first short - circuit and the secondary short - circuit duration of the transformer.

[0064] After the transformer experiences the first short - circuit and is switched off, there may be residual magnetism in the iron core. After reclosing, the short - circuit current is affected by the combined action of the exciting magnetic flux generated by the power supply and the residual magnetic flux in the iron core. If the two directions are the same, it is called positive residual magnetism; if the two directions are opposite, it is called negative residual magnetism. If affected by positive residual magnetism after reclosing, the short - circuit current will increase; if affected by negative residual magnetism after reclosing, the short - circuit current will decrease.

[0065] Step 104: Input the residual magnetism and the secondary short - circuit duration into a pre - trained magnetic current model, so that the magnetic current model determines a corresponding formula for calculating the secondary short - circuit current according to the secondary short - circuit duration. Among them, the magnetic current model contains multiple quadratic polynomials for calculating the secondary short - circuit current based on the residual magnetism, and each quadratic polynomial corresponds to a secondary short - circuit duration.

[0066] In one embodiment, the multiple quadratic polynomials include a first polynomial, a second polynomial, and a third polynomial.

[0067] The first polynomial is: When the short - circuit duration is 60 ms, the short - circuit current after reclosing is calculated as:

[0068] I m =-192875.24x 2 +1277837.72x - 2066355.96;

[0069] The second polynomial is:

[0070] I m =-125334.46x 2 +691925.55x - 910502.47;

[0071] The third polynomial is:

[0072] I m =799.14x 2 -3727.83x + 38903.64;

[0073] Among them, x represents the residual magnetism of the transformer after the first short - circuit, I m represents the peak value of the secondary short - circuit current of the transformer. The secondary short - circuit duration corresponding to the first polynomial is 60 ms, the secondary short - circuit duration corresponding to the second polynomial is 120 ms, and the secondary short - circuit duration corresponding to the third polynomial is 200 ms.

[0074] Of course, the polynomials are not limited to the above three. For example, it can also include polynomials corresponding to other secondary short - circuit durations, or the short - circuit duration can be not limited to specific values but a duration range, and the present invention does not limit this.

[0075] Step 106: Use the output of the magnetic current model as the peak value of the short - circuit current in the secondary short - circuit of the transformer.

[0076] In this embodiment, the peak value of the secondary short-circuit current is calculated based on the residual magnetism after the first short circuit of the transformer. On the one hand, without using a current detection instrument, the calculation of the secondary short-circuit current is realized, thus saving the calculation cost and improving the calculation efficiency. On the other hand, not only the influence of the residual magnetism on the magnitude of the short-circuit current is considered, but also the influence of the secondary short-circuit duration is taken into account, making the calculation result more accurate.

[0077] In one embodiment, before calculating the secondary short-circuit current, the method further includes: obtaining the structural information of the iron core and winding of the transformer, and establishing a geometric model of the transformer according to the structural information; setting the constitutive relationship of the iron core part of the geometric model to the J-A model, and determining the model parameters of the J-A model according to the silicon content of the silicon steel sheet of the transformer; constructing a simulation system for the transformer fault according to the voltage level, wiring method, and the geometric model of the transformer, and obtaining a training data set through the simulation system; wherein each training sample in the training data set includes the secondary short-circuit duration, the residual magnetism after the first short circuit of the transformer, and the peak value of the secondary short-circuit current; training the magnetic current model according to the training data set.

[0078] The Jiles-Atherton model (J-A model) is a microscopic model that describes the magnetization process of magnetic materials and is widely used in the analysis of the magnetization characteristics of soft magnetic materials. This model can better simulate the hysteresis loop of magnetic materials, that is, the relationship curve between the magnetization intensity and the magnetic field intensity.

[0079] The model parameters of the Jiles-Atherton model include: saturation magnetization Ms, domain wall density a, pinning loss kp, magnetization reversibility cr, and inter-domain coupling α. The Jiles-Atherton model is a phenomenological model that is not based on microscopic physical mechanisms but can well describe the hysteresis phenomenon in the magnetization process. This model is very useful in engineering applications, especially in the design of electromagnetic devices such as motors, transformers, and sensors.

[0080] The training of the magnetic current model mainly includes training the coefficients in the multiple quadratic polynomials for calculating the secondary short-circuit current based on the residual magnetism included in the magnetic current model. Taking the third polynomial as an example, in "I m = 799.14x 2 - 3727.83x + 38903.64", "799.14, -3727.83, 38903.64" are all obtained through training.

[0081] In addition, the data obtained by the simulation system can be divided into a training data set and a validation data set. The training data set is used to train the magnetic flux model, and the validation data set is used to verify the calculation accuracy of the magnetic flux model. If the magnetic flux model does not achieve the expected effect, training continues until the calculation effect of the magnetic flux model reaches the expectation.

[0082] Further, the model parameters include: saturation magnetization Ms, domain wall density a, pinning loss kp, magnetization reversibility cr, and inter-domain coupling α; when the silicon content of the silicon steel sheet of the transformer is 2%, the saturation magnetization Ms is 1e6 A / m, the domain wall density a is 60 A / m, the pinning loss kp is 100 A / m, the magnetization reversibility cr is 0.3, and the inter-domain coupling α is 1.5e-5.

[0083] In one embodiment, obtaining the training data set through the simulation system includes: setting the primary open circuit time t of the transformer in the simulation system 1 , reclosing time t 2 , secondary open circuit time t3, the output time step is t4, and the tolerance is controlled by the physical field; setting the rated voltage of the high voltage side of the transformer in the simulation system to the rated voltage value and the resistance value to the system impedance value.

[0084] For example: the rated voltage of the high voltage side is set to the rated voltage value, and the resistance value is set to the system impedance value. Taking a certain 110 kV transformer as an example, its high voltage side voltage is set to 110 kV, the high voltage side resistance is set to 1.4 Ω, the short-circuit phase resistance of the low voltage side is set to 0.001 Ω, and the normal phase resistance is set to 100 Ω. Set t 1 to 150 ms, t 2 to 400 ms, t 3 to 600 ms, and set t 4 to 1 ms.

[0085] A method for calculating the secondary short-circuit current of a transformer according to the present invention establishes a geometric model and a circuit structure for finite element simulation based on the voltage level and impedance parameters of the transformer, combined with the core and winding structure of the transformer itself, and couples the two. By setting the constitutive relationship of the core part as the hysteresis Jiles-Atherton model, and determining the values of the saturation magnetization intensity Ms, domain wall density a, pinning loss kp, magnetization reversibility cr, and inter-domain coupling α in the model according to the type of silicon steel sheet. Then, set the initial short-circuit time t1, initial open-circuit time t2, reclosing time t3, and total simulation time t4 of the transformer according to the actual working conditions required for calculation. Finally, establish a study and perform calculations to obtain the waveform of the short-circuit current after the transformer winding recloses. Compared with the existing calculation methods for the short-circuit current after transformer reclosing, the present invention adopts the hysteresis Jiles-Atherton model, fully considering the influence of residual magnetism on the magnitude of the short-circuit current, making the calculation results more accurate.

[0086] Figure 2 is a schematic structural diagram of a device provided by an exemplary embodiment. Please refer to Figure 2 , at the hardware level, the device includes a processor 202, an internal bus 204, a network interface 206, a memory 208, and a non-volatile memory 210. Of course, there may also be other hardware required for other functions. One or more embodiments of the present invention can be implemented based on a software method. For example, the processor 202 reads the corresponding computer program from the non-volatile memory 210 into the memory 208 and then runs it. Of course, in addition to the software implementation method, one or more embodiments of the present invention do not exclude other implementation methods, such as logic devices or a combination of software and hardware. That is, the execution subject of the following processing flow is not limited to each logic unit, and can also be hardware or logic devices.

[0087] Please refer to Figure 3 , a device for calculating the secondary short-circuit current of a transformer can be applied to a device as shown in Figure 3 to implement the technical solution of the present invention. The device may include:

[0088] A first acquisition unit 302 for acquiring the residual magnetism after the first short circuit of the transformer and the secondary short-circuit duration of the transformer;

[0089] An input unit 304 for inputting the residual magnetism and the secondary short-circuit duration into a pre-trained magnetic current model, so that the magnetic current model determines a corresponding formula for calculating the secondary short-circuit current according to the secondary short-circuit duration; wherein, the magnetic current model contains multiple quadratic polynomials for calculating the secondary short-circuit current based on the residual magnetism, and each quadratic polynomial corresponds to a secondary short-circuit duration;

[0090] An output unit 306, configured to use the output of the magnetic flux model as the peak short-circuit current of the transformer in a secondary short circuit.

[0091] Optionally, the multiple quadratic polynomials include a first polynomial, a second polynomial, and a third polynomial;

[0092] The first polynomial is: when the short-circuit duration is 60 ms, the short-circuit current after reclosing is calculated as:

[0093] I m = -192875.24x 2 + 1277837.72x - 2066355.96;

[0094] The second polynomial is:

[0095] I m = -125334.46x 2 + 691925.55x - 910502.47;

[0096] The third polynomial is:

[0097] I m = 799.14x 2 - 3727.83x + 38903.64;

[0098] Wherein, x represents the residual magnetism of the transformer after the first short circuit, the second polynomial corresponds to a secondary short-circuit duration of 60 ms, the second polynomial corresponds to a secondary short-circuit duration of 120 ms, and the third polynomial corresponds to a secondary short-circuit duration of 200 ms.

[0099] Optionally, before calculating the secondary short-circuit current, the device further includes:

[0100] A second acquisition unit 308, configured to acquire the structural information of the iron core and winding of the transformer, and establish a geometric model of the transformer according to the structural information;

[0101] A setting unit 310, configured to set the constitutive relationship of the iron core part of the geometric model to the J-A model, and determine the model parameters of the J-A model according to the silicon content of the silicon steel sheet of the transformer;

[0102] A simulation unit 312, configured to construct a simulation system for the transformer fault according to the voltage level, wiring mode, and the geometric model of the transformer, and obtain a training data set through the simulation system; wherein, each training sample in the training data set includes a secondary short-circuit duration, the residual magnetism of the transformer after the first short circuit, and the peak secondary short-circuit current;

[0103] A training unit 314 for training the magnetic flux model according to the training data set.

[0104] Optionally, the model parameters include: saturation magnetization Ms, domain wall density a, pinning loss kp, magnetization reversibility cr, and inter-domain coupling α;

[0105] When the silicon content of the silicon steel sheet of the transformer is 2%, the saturation magnetization Ms is 1e6 A / m, the domain wall density a is 60 A / m, the pinning loss kp is 100 A / m, the magnetization reversibility cr is 0.3, and the inter-domain coupling α is 1.5e-5.

[0106] Optionally, the training unit 314 is specifically configured to:

[0107] Set the primary open circuit time t of the transformer in the simulation system 1 , reclosing time t 2 , secondary open circuit time t 3 , with the output time step being t 4 , and the tolerance is controlled by the physical field;

[0108] Set the rated voltage of the high voltage side of the transformer in the simulation system to the rated voltage value, and set the resistance value to the system impedance value.

[0109] The system, device, module or unit illustrated in the above embodiments can be specifically implemented by a computer chip or entity, or by a product with certain functions. A typical implementation device is a computer, and the specific form of the computer can be a personal computer, laptop computer, cellular phone, camera phone, smart phone, personal digital assistant, media player, navigation device, email transceiver device, game console, tablet computer, wearable device, or a combination of any several of these devices.

[0110] In a typical configuration, a computer includes one or more processors (CPUs), an input / output interface, a network interface, and a memory.

[0111] The memory may include non-permanent memory in the computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of, for example, read-only memory (ROM) or flash memory (flash RAM). The memory is an example of a computer-readable medium.

[0112] A computer-readable medium includes permanent and non-permanent, removable and non-removable media that can implement information storage by any method or technology. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette tapes, disk storage, quantum memory, graphene-based storage media, or other magnetic storage devices, or any other non-transmission medium that can be used to store information accessible by a computing device. As defined herein, a computer-readable medium does not include transitory computer-readable media, such as modulated data signals and carrier waves.

[0113] For the computer-readable medium (or, computer-readable storage medium) described above or in any other form, computer instructions can be stored thereon, and when executed by a processor, one or more of the above-described embodiments are implemented, thereby implementing the technical solution of the present invention.

[0114] The present invention also proposes a computer program, which when executed by a processor implements one or more of the above-described embodiments, thereby implementing the technical solution of the present invention. Among them, the computer program can be specifically recorded on the computer-readable medium described above or in any other form, and the present invention does not limit this.

[0115] It should also be noted that the term "comprises", "comprising", or any other variation thereof is intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the statement "comprising a..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that comprises the element.

[0116] The above describes specific embodiments of the present invention. Other embodiments are within the scope of the appended claims. In some cases, the acts or steps recited in the claims can be performed in a different order than in the embodiments and still achieve the desired result. Additionally, the processes depicted in the figures do not necessarily require the particular order or sequential order shown to achieve the desired result. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0117] The terms used in one or more embodiments of the present invention are for the purpose of describing particular embodiments only and are not intended to limit one or more embodiments of the present invention. The singular forms "a", "said", and "the" used in one or more embodiments of the present invention and the appended claims are also intended to include the plural forms unless the context clearly dictates otherwise. It should also be understood that the term "and / or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.

[0118] It should be understood that although the terms first, second, third, etc. may be used in one or more embodiments of the present invention to describe various information, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from each other. For example, without departing from the scope of one or more embodiments of the present invention, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the word "if" as used herein may be interpreted as "when" or "while" or "in response to determining".

[0119] The above description is only a preferred embodiment of one or more embodiments of the present invention and is not intended to limit one or more embodiments of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of one or more embodiments of the present invention shall be included within the scope of protection of one or more embodiments of the present invention.

Claims

1. A method for calculating secondary short-circuit current of a transformer, characterized in that: The method comprises: Obtaining the residual magnetism of the transformer after the initial short circuit and the secondary short circuit duration of the transformer; The residual magnetism and the secondary short-circuit duration are input into a pre-trained magnetic flow model, so that the magnetic flow model determines a corresponding formula for calculating the secondary short-circuit current according to the secondary short-circuit duration; wherein the magnetic flow model includes a plurality of quadratic polynomials for calculating the secondary short-circuit current based on the residual magnetism, and each quadratic polynomial corresponds to a secondary short-circuit duration; The output of the magnetic flow model is used as the short-circuit current peak value of the transformer in the secondary short circuit.

2. The method according to claim 1, characterized in that The multiple quadratic polynomials include a first polynomial, a second polynomial, and a third polynomial; The first polynomial is: When the short circuit duration is 60ms, the short circuit current after reclosing is calculated as: I m =-192875.24x 2 +1277837.72x-2066355.96; The second polynomial is: I m =-125334.46x 2 +691925.55x-910502.47; The third polynomial is: I m =799.14x 2 -3727.83x+38903.64; Among them, x represents the residual magnetism of the transformer after the initial short circuit, the secondary short circuit time corresponding to the first polynomial is 60ms, the secondary short circuit time corresponding to the second polynomial is 120ms, and the secondary short circuit time corresponding to the third polynomial is 200ms.

3. The method according to claim 1, characterized in that: Before calculating the secondary short-circuit current, the method further includes: Acquiring structural information of the core and windings of the transformer, and establishing a geometric model of the transformer according to the structural information; The constitutive relationship of the core part of the geometric model is set as a JA model, and the model parameters of the JA model are determined according to the silicon content of the silicon steel sheet of the transformer; A simulation system for the transformer fault is constructed according to the voltage level, wiring mode and geometric model of the transformer, and a training data set is obtained through the simulation system; wherein each training sample in the training data set includes the secondary short circuit duration, the residual magnetism of the transformer after the initial short circuit, and the secondary short circuit current peak value; The magnetic flow model is trained according to the training data set.

4. The method according to claim 3, characterized in that The model parameters include: saturation magnetization Ms, domain wall density a, pinning loss kp, magnetization reversibility cr and inter-domain coupling α; When the silicon content of the silicon steel sheet of the transformer is 2%, the saturation magnetization Ms is 1e6A / m, the domain wall density a is 60A / m, the pinning loss kp is 100A / m, the magnetization reversibility cr is 0.3, and the inter-domain coupling α is 1.5e-5.

5. The method according to claim 3, characterized in that: The step of obtaining a training data set through the simulation system includes: The first circuit breaking time t1, the reclosing time t2, and the secondary circuit breaking time t3 of the transformer in the simulation system are set, the output time step is t4, and the tolerance is controlled by the physical field; The rated voltage on the high-voltage side of the transformer in the simulation system is set to the rated voltage value, and the resistance value is set to the system impedance value.

6. A secondary short-circuit current calculation device for a transformer, characterized in that: The device comprises: A first acquisition unit: acquiring the residual magnetism of the transformer after the initial short circuit and the secondary short circuit duration of the transformer; Input unit: input the residual magnetism and the secondary short-circuit duration into a pre-trained magnetic flow model, so that the magnetic flow model determines a corresponding formula for calculating the secondary short-circuit current according to the secondary short-circuit duration; wherein the magnetic flow model includes a plurality of quadratic polynomials for calculating the secondary short-circuit current based on the residual magnetism, and each quadratic polynomial corresponds to a secondary short-circuit duration; Output unit: using the output of the magnetic flow model as the short-circuit current peak value of the transformer in the secondary short circuit.

7. The device according to claim 6, characterized in that The multiple quadratic polynomials include a first polynomial, a second polynomial, and a third polynomial; The first polynomial is: When the short circuit duration is 60ms, the short circuit current after reclosing is calculated as: I m =-192875.24x 2 +1277837.72x-2066355.96; The second polynomial is: I m =-125334.46x 2 +691925.55x-910502.47; The third polynomial is: I m =799.14x 2 -3727.83x+38903.64; Among them, x represents the residual magnetism of the transformer after the initial short circuit, the secondary short circuit time corresponding to the first polynomial is 60ms, the secondary short circuit time corresponding to the second polynomial is 120ms, and the secondary short circuit time corresponding to the third polynomial is 200ms.

8. The device according to claim 6, characterized in that Before calculating the secondary short-circuit current, the device further includes: A second acquisition unit: acquiring structural information of the core and windings of the transformer, and establishing a geometric model of the transformer according to the structural information; A setting unit: setting the constitutive relationship of the core part of the geometric model to a JA model, and determining the model parameters of the JA model according to the silicon content of the silicon steel sheet of the transformer; Simulation unit: constructing a simulation system for the transformer fault according to the voltage level, wiring mode and geometric model of the transformer, and obtaining a training data set through the simulation system; wherein each training sample in the training data set includes the secondary short circuit duration, the residual magnetism of the transformer after the initial short circuit, and the secondary short circuit current peak value; Training unit: training the magnetic flow model according to the training data set.

9. An electronic device, characterized in that: include: processor; a memory for storing processor-executable instructions; The processor implements the steps of the method according to any one of claims 1 to 5 by running the executable instructions.

10. A computer-readable storage medium having computer instructions stored thereon, characterized in that: When the instruction is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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