Transformer operating status detection method, device, electronic equipment and storage medium

Abstract

The present invention discloses a method, device, electronic device and storage medium for detecting the operating state of a transformer. The method includes: obtaining electrical signal parameter information of multiple branch circuits in the transformer and the network connection relationship between the multiple branch circuits, wherein the multiple branch circuits are used to represent different circuit branches obtained by dividing the winding circuit in the transformer based on the branch nodes in the transformer; constructing a target equivalent circuit model of the transformer based on the electrical signal parameter information and the network connection relationship, wherein the target equivalent circuit model is used to represent an equivalent circuit model established based on the equivalent impedance characteristics of the transformer; generating a simulation frequency response curve based on the target equivalent circuit model; and detecting the operating state of the transformer based on the simulation frequency response curve. The present invention solves the technical problem of low efficiency in detecting the operating state of the transformer in the related art.

Description

Technical Field

[0001] The present invention relates to the field of transformer detection, and in particular to a method, device, electronic equipment and storage medium for detecting the operating status of a transformer. Background Art

[0002] In actual operation, transformers are often impacted by large electric forces caused by short-circuit currents, which can easily cause deformation of transformer windings. Slight winding deformation may not immediately cause transformer failure in a short period of time, but under the cumulative effect of multiple short-circuit current impacts, the insulation strength of the transformer windings continues to decrease, which may cause short circuits between winding turns or serious deformation of the windings, thereby causing more serious damage and ultimately affecting the normal operation of the power grid. Therefore, it is necessary to conduct timely and accurate status detection of the transformer to prevent and reduce the operation risks of the transformer.

[0003] At present, in the relevant technology, it is difficult to timely and accurately obtain the actual state of the winding inside the transformer oil tank only by measurement means, or it is necessary to obtain test data by deforming the actual transformer. The implementation process is relatively complicated and costly. There is a large error between the obtained data and the actual parameter value, resulting in low efficiency in detecting the operating state of the transformer.

[0004] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0005] The embodiments of the present invention provide a method, device, electronic device and storage medium for detecting the operating status of a transformer, so as to at least solve the technical problem of low efficiency in detecting the operating status of a transformer in the related art.

[0006] According to one aspect of an embodiment of the present invention, a method for detecting the operating status of a transformer is provided, comprising: obtaining electrical signal parameter information of multiple branch circuits in the transformer, and a network connection relationship between the multiple branch circuits, wherein the multiple branch circuits are used to represent different circuit branches obtained by dividing the winding circuit in the transformer based on branch nodes in the transformer; constructing a target equivalent circuit model of the transformer based on the electrical signal parameter information and the network connection relationship, wherein the target equivalent circuit model is used to represent an equivalent circuit model established based on an equivalent impedance characteristic of the transformer; generating a simulation frequency response curve based on the target equivalent circuit model, wherein the simulation frequency response curve is used to simulate the actual frequency response characteristics of the transformer; and detecting the operating status of the transformer based on the simulation frequency response curve.

[0007] Optionally, based on the electrical signal parameter information and the network connection relationship, a target equivalent circuit model of the transformer is constructed, including: based on the electrical signal parameter information, determining branch electrical signal relationship expressions of multiple branch circuits, wherein the branch electrical signal relationship expressions are used to represent expressions of constraint relationships between branch voltage vectors and branch current vectors of multiple branch circuits; based on the network connection relationship, determining an association matrix of the target equivalent circuit model, wherein the association matrix is ​​used to represent a matrix of connection relationships between different nodes in the target equivalent circuit model; based on the association matrix, the branch voltage vectors and the branch current vectors in the branch electrical signal relationship expressions, constructing the target equivalent circuit model.

[0008] Optionally, based on the electrical signal parameter information, the branch electrical signal relationship expression of multiple branch circuits is determined, including: obtaining the branch voltage source vector, branch current source vector and branch impedance matrix in the electrical signal parameter information, wherein the branch impedance matrix is ​​used to represent a matrix composed of resistance parameters, capacitance parameters and inductance parameters based on multiple branch circuits; based on the branch voltage source vector, branch current source vector and branch impedance matrix, the branch electrical signal relationship expression is constructed.

[0009] Optionally, based on the branch voltage source vector, the branch current source vector and the branch impedance matrix, a branch electrical signal relationship expression is constructed, including: constructing an initial branch electrical signal relationship expression based on the branch voltage source vector, the branch current source vector and the branch impedance matrix; determining a branch admittance matrix of multiple branch circuits based on an inverse matrix of the branch impedance matrix, wherein the branch admittance matrix is ​​a matrix used to represent the linear relationship between current signals and voltage signals in multiple branch circuits; determining the branch electrical signal relationship expression based on the initial branch electrical signal relationship expression and the branch admittance matrix.

[0010] Optionally, based on the association matrix, the branch voltage vector and the branch current vector in the branch electrical signal relationship expression, a target equivalent circuit model is constructed, including: obtaining initial branch impedance parameters in the electrical signal parameter information, wherein the initial branch impedance parameters include at least resistance parameters, capacitance parameters and inductance parameters of multiple branch circuits; performing parameter search on the initial branch impedance parameters based on a preset bionic population optimization algorithm to obtain target branch impedance parameters, wherein the target branch impedance parameters include at least target resistance parameters, target capacitance parameters and target inductance parameters; based on the target branch impedance parameters, the association matrix, the branch voltage vector and the branch current vector in the branch electrical signal relationship expression, a target equivalent circuit model is constructed.

[0011] Optionally, based on the target equivalent circuit model, a simulation frequency response curve is generated, including: based on the target equivalent circuit model, determining a node voltage equation of the target equivalent circuit model, wherein the node voltage equation is used to describe the relationship between voltages at different nodes in the target equivalent circuit model; based on the node voltage equation, determining node output voltages and node input voltages of different nodes in the target equivalent circuit model; based on the ratio of the node output voltage to the node input voltage, generating a simulation frequency response curve.

[0012] According to another aspect of an embodiment of the present invention, a device for detecting the operating status of a transformer is also provided, including: an acquisition module, used to acquire electrical signal parameter information of multiple branch circuits in the transformer, and a network connection relationship between the multiple branch circuits, wherein the multiple branch circuits are used to represent different circuit branches obtained by dividing the winding circuit in the transformer based on the branch nodes in the transformer; a construction module, used to construct a target equivalent circuit model of the transformer based on the electrical signal parameter information and the network connection relationship, wherein the target equivalent circuit model is used to represent an equivalent circuit model established based on the equivalent impedance characteristics of the transformer; a generation module, used to generate a simulation frequency response curve based on the target equivalent circuit model, wherein the simulation frequency response curve is used to simulate the actual frequency response characteristics of the transformer; and a detection module, used to detect the operating status of the transformer based on the simulation frequency response curve.

[0013] According to another aspect of an embodiment of the present invention, there is further provided an electronic device, comprising: a memory storing an executable program; and a processor for running the program, wherein the method in each embodiment of the present invention is executed when the program is running.

[0014] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is provided. The computer-readable storage medium includes a stored executable program, wherein when the executable program is running, the device where the computer-readable storage medium is located is controlled to execute the methods in various embodiments of the present invention.

[0015] According to another aspect of an embodiment of the present invention, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the method in each embodiment of the present invention is implemented.

[0016] According to another aspect of an embodiment of the present invention, a computer program product is provided, including a non-volatile computer-readable storage medium, wherein the non-volatile computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method in each embodiment of the present invention is implemented.

[0017] According to another aspect of the embodiments of the present invention, a computer program is further provided. When the computer program is executed by a processor, the methods in the embodiments of the present invention are implemented.

[0018] In an embodiment of the present invention, a method for detecting the operating state of a transformer is provided, comprising: obtaining electrical signal parameter information of multiple branch circuits in the transformer, and a network connection relationship between the multiple branch circuits, wherein the multiple branch circuits are used to represent different circuit branches obtained by dividing the winding circuit in the transformer based on branch nodes in the transformer; constructing a target equivalent circuit model of the transformer based on the electrical signal parameter information and the network connection relationship, wherein the target equivalent circuit model is used to represent an equivalent circuit model established based on the equivalent impedance characteristics of the transformer; generating a simulation frequency response curve based on the target equivalent circuit model, wherein the simulation frequency response curve is used to simulate the actual frequency response characteristics of the transformer; and detecting the operating state of the transformer based on the simulation frequency response curve. It is easy to notice that, by acquiring the electrical signal parameter information of multiple branch circuits in the transformer and the network connection relationship between the multiple branch circuits, the present application can more comprehensively understand the circuit structure and connection mode inside the transformer, and can construct a target equivalent circuit model of the transformer that more accurately describes the equivalent impedance characteristics of the transformer. By generating a simulated frequency response curve, the actual frequency response characteristics of the transformer can be simulated, so as to better understand the response of the transformer at different frequencies. By analyzing the simulated frequency response curve, the operating status of the transformer can be detected, potential problems can be discovered in time and corresponding measures can be taken to improve the operating efficiency and reliability of the transformer. In particular, the present application establishes a transformer winding equivalent circuit model that accurately describes the equivalent impedance characteristics of the transformer, and performs frequency response analysis after simulating the model to obtain a frequency response curve that is as consistent as possible with the measured frequency response analysis data. Non-destructive transformer winding fault diagnosis can be performed, which helps to timely and accurately detect the status of the transformer, prevent and reduce the operating risks of the transformer, and thus solves the technical problem of low efficiency in detecting the operating status of the transformer in the related art. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0020] Figure 1 is a flow chart of a method for detecting the operating status of a transformer according to an embodiment of the present invention;

[0021] Figure 2 is a schematic diagram of an optional branch analysis according to an embodiment of the present invention;

[0022] Figure 3 is a flow chart of an optional method for detecting the operating state of a transformer according to an embodiment of the present invention;

[0023] Figure 4 is a schematic diagram of a transformer operating status detection device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0024] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0025] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0026] According to one aspect of an embodiment of the present invention, a method for detecting the operating status of a transformer is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0027] Figure 1 is a flow chart of a method for detecting the operating status of a transformer according to an embodiment of the present invention. Figure 1 As shown, the method comprises the following steps:

[0028] Step S102, obtaining electrical signal parameter information of multiple branch circuits in the transformer and network connection relationships between the multiple branch circuits.

[0029] The plurality of branch circuits are used to represent different circuit branches obtained by dividing the winding circuit in the transformer based on the branch nodes in the transformer.

[0030] The above-mentioned transformer may refer to an electrical device used to change AC and DC voltages in the power field, that is, a power transformer. The transformer may be composed of an iron core and a winding, and may convert the voltage at the input end into the voltage required at the output end through the principle of electromagnetic induction. Optionally, the transformer may be a magnetically controlled distribution transformer, which may be a device that can realize the regulation and control of the transformer through magnetic control technology. The magnetic control technology is used to adjust the output voltage and current of the transformer, thereby realizing precise control of the power system. The type of transformer may also be determined according to actual needs and is not limited here.

[0031] The above-mentioned branch node may refer to a circuit intersection / electrical connection point of the internal circuit of the transformer, for example, it may be an interface or terminal in the transformer. The branch node in the transformer may realize the separation or merging of electrical signals. The branch node may be determined according to actual needs and is not limited here.

[0032] The above-mentioned winding circuit may refer to the winding system inside the transformer, which may include windings on the high-voltage side and the low-voltage side, and may be a component that winds the insulated wire into a certain shape and connects it into a loop to transmit electrical energy. The winding circuit of the transformer may include a high-voltage winding and a low-voltage winding. The high-voltage winding may be connected to the power supply side of the power grid, and the low-voltage winding may be connected to the user side. When current passes through the high-voltage winding, a magnetic field may be generated, and the magnetic field may be induced to the low-voltage winding, thereby converting the voltage. The wires in the winding circuit may be insulated by insulating materials to prevent current leakage or short circuit.

[0033] The above-mentioned multiple branch circuits may refer to branch circuits obtained by dividing / segmenting the winding circuit in the transformer based on branch nodes. The branch circuits may be determined according to actual needs and are not limited here.

[0034] The above-mentioned electrical signal parameter information may refer to parameters of relevant electrical signals of multiple branch circuits / each branch circuit, and may include hardware parameter information of each branch circuit, and actual electrical signal parameters during the operation of the transformer, etc., wherein the hardware parameter information may include hardware parameters of electrical components / equipment in each branch circuit, such as resistance parameters, inductance parameters and capacitance parameters, and the actual electrical signal parameters may include voltage parameters, current parameters and other information during the operation of each branch circuit. The electrical signal parameter information may be determined according to actual needs and is not limited here.

[0035] The above-mentioned network connection relationship may refer to the connection mode and current path between each branch circuit. The network connection relationship may be determined according to actual needs and is not limited here.

[0036] In an optional embodiment, electrical signal parameter information of multiple branch circuits in the transformer and the network connection relationship between the multiple branch circuits can be obtained. Specifically, the transformer can be divided into branch nodes to determine the position and connection relationship of each branch circuit, which can be achieved by analyzing and measuring the circuit diagram of the transformer; electrical signal parameters of each branch circuit can be collected, which can be achieved through sensors or monitoring equipment; the network connection relationship between each branch circuit can be determined, which may include circuit topology, transmission path and other information, which helps to understand the circuit operation status inside the transformer and can provide data support for transformer operation status detection and fault diagnosis.

[0037] Step S104: constructing a target equivalent circuit model of the transformer based on the electrical signal parameter information and the network connection relationship.

[0038] The target equivalent circuit model is used to represent an equivalent circuit model established based on the equivalent impedance characteristics of the transformer.

[0039] The above-mentioned equivalent impedance characteristics may refer to the impedance characteristics of the equivalent circuit exhibited by the transformer during operation. The equivalent impedance characteristics may be represented by a circuit model, which may include elements such as resistance, inductance and capacitance.

[0040] The above-mentioned target equivalent circuit model may refer to a model established based on the equivalent impedance characteristics of the transformer. By modeling the equivalent circuit of the transformer, the operating status of the transformer can be more accurately monitored in actual operation. The target equivalent circuit model may include equivalent circuit parameters of the transformer, such as resistance, inductance and capacitance. The equivalent circuit parameters can be obtained through actual testing or simulation analysis, and can reflect the electrical characteristics of the transformer. By modeling the equivalent circuit of the transformer, the operating status of the transformer can be better understood and analyzed, including changes in parameters such as current, voltage, and power. The target equivalent circuit model can be used to monitor the performance and operating status of the transformer, such as detecting current and voltage imbalance, loss, temperature changes, etc. By real-time monitoring of the equivalent circuit model of the transformer, problems can be discovered and solved in a timely manner to ensure safe operation and stable performance of the transformer.

[0041] The target equivalent circuit model can be a lumped parameter equivalent circuit model of the transformer winding circuit. The lumped parameter equivalent circuit model can refer to a simplified circuit model that abstracts the transformer winding circuit into basic components such as resistance, inductance and capacitance, which is used to simulate the circuit behavior of the transformer. The lumped parameter equivalent circuit model can include parameters such as the saturation characteristics and magnetic permeability of the magnetic core to describe the propagation and change of the magnetic field in the transformer; it can include parameters such as the resistance, inductance and capacitance of the primary and secondary sides to describe the electrical characteristics of the transformer in the circuit; it can describe the mutual inductance between the primary and secondary sides to represent the transformation ratio and coupling degree of the transformer. By establishing a lumped parameter equivalent circuit model, the electrical performance of the transformer, such as voltage, current, power loss, etc., can be predicted through a simplified circuit analysis method. The target equivalent circuit model can be determined according to actual needs and is not limited here.

[0042] In an optional embodiment, a target equivalent circuit model of the transformer can be constructed based on the acquired electrical signal parameter information and network connection relationship using a modeling method of an equivalent circuit model. The target equivalent circuit model can mainly include parameters such as equivalent resistance, inductance, capacitance, etc. of the transformer, and can be appropriately corrected and adjusted according to actual conditions. In the process of constructing the target equivalent circuit model, the equivalent impedance characteristics of the transformer can be analyzed, which can include parameters such as frequency response, impedance size, phase angle, etc., which can help determine the performance and stability of the transformer under operating conditions. Through the above steps, a target equivalent circuit model of the transformer can be constructed based on the electrical signal parameter information and network connection relationship, which can help monitor and analyze the operating status of the transformer in real time, and help users better understand the working conditions and characteristics of the transformer, thereby optimizing the design and operating parameters and improving the efficiency and reliability of the transformer.

[0043] Step S106: generating a simulation frequency response curve based on the target equivalent circuit model.

[0044] Among them, the simulated frequency response curve is used to simulate the actual frequency response characteristics of the transformer.

[0045] The above-mentioned actual frequency response characteristics may refer to the response of the transformer to the applied voltage frequency during operation. In actual operation, the frequency response characteristics of the transformer may be affected by many factors, such as the structure, material, and wiring method of the transformer. By analyzing and testing the actual frequency response characteristics of the transformer, the performance of the transformer at different frequencies can be evaluated, providing a reference for the detection of the operating status of the transformer, and also providing an important reference for the design and optimization of the transformer.

[0046] The above-mentioned simulated frequency response curve may refer to the response characteristic curve of the transformer at different frequencies obtained by simulation technology. The simulated frequency response curve may use frequency as the horizontal axis and amplitude or phase as the vertical axis to represent the transmission characteristics of the transformer at different frequencies. The simulated frequency response curve may use a frequency response analysis (Frequency Response Analysis, FRA) curve. The frequency response analysis curve may represent the response of the system to input signals of different frequencies. The specific type of the simulated frequency response curve may also be determined according to actual needs and is not limited here.

[0047] In an optional embodiment, a simulation frequency response curve can be generated based on the target equivalent circuit model to simulate the actual frequency response characteristics of the transformer. Specifically, based on the target equivalent circuit model, in the circuit simulation software, electrical signals of different frequencies can be input as excitation signals, and the frequency response of the circuit, that is, the relationship between the amplitude and phase of the output signal and the input signal, can be obtained through simulation calculation. The generated frequency response curve is analyzed, and the simulation results are compared with the actual observation results to evaluate the accuracy and applicability of the model. Through the above steps, a simulation frequency response curve can be generated based on the target equivalent circuit model to simulate the actual frequency response characteristics of the transformer and provide a reference for the detection of the operating status of the transformer. The frequency response analysis curve can include an amplitude-frequency characteristic curve and a phase-frequency characteristic curve. The amplitude-frequency characteristic curve represents how the gain of the system changes with frequency, and the phase-frequency characteristic curve represents how the phase of the system changes with frequency. By analyzing these curves, we can obtain important information such as system stability, frequency response range and filtering characteristics. The frequency response curve of the transformer can be obtained by performing frequency response tests or simulation analysis on the transformer. In actual operation, the transmission characteristics of the transformer will change with the change of frequency, which can be displayed by the frequency response curve. By analyzing the frequency response curve of the transformer, we can understand the transmission characteristics of the transformer at different frequencies, including amplitude-frequency characteristics, phase-frequency characteristics, etc. By analyzing the frequency response curve of the transformer, we can evaluate the performance of the transformer, detect abnormalities in the transmission characteristics, and optimize the design of the transformer. It can also be used to diagnose transformer faults, such as damaged windings or insulation problems. The simulated frequency response curve of the transformer is a simulated display of the transmission characteristics of the transformer at different frequencies, which is convenient for understanding the operating status of the transformer and diagnosing transformer faults.

[0048] Step S108: detecting the operating state of the transformer based on the simulated frequency response curve.

[0049] In an optional embodiment, the response characteristics of the transformer at different frequencies can be analyzed based on the obtained simulated frequency response curve, which may include the amplitude-frequency characteristics, phase-frequency characteristics, etc. of the frequency response. By analyzing the frequency response curve, it can be determined whether the transformer has abnormal conditions, such as winding short circuit, insulation breakdown, etc., so as to detect the operating status of the transformer. The abnormal conditions of the transformer can be discovered in time and then handled in time to avoid further damage to the transformer and ensure the safe and stable operation of the power system. Through the above steps, the operating status of the transformer can be effectively detected based on the simulated frequency response curve of the transformer, thereby improving the reliability and stability of the power system.

[0050] In an embodiment of the present invention, a method for detecting the operating state of a transformer is provided, comprising: obtaining electrical signal parameter information of multiple branch circuits in the transformer, and a network connection relationship between the multiple branch circuits, wherein the multiple branch circuits are used to represent different circuit branches obtained by dividing the winding circuit in the transformer based on branch nodes in the transformer; constructing a target equivalent circuit model of the transformer based on the electrical signal parameter information and the network connection relationship, wherein the target equivalent circuit model is used to represent an equivalent circuit model established based on the equivalent impedance characteristics of the transformer; generating a simulation frequency response curve based on the target equivalent circuit model, wherein the simulation frequency response curve is used to simulate the actual frequency response characteristics of the transformer; and detecting the operating state of the transformer based on the simulation frequency response curve. It is easy to notice that, by acquiring the electrical signal parameter information of multiple branch circuits in the transformer and the network connection relationship between the multiple branch circuits, the present application can more comprehensively understand the circuit structure and connection mode inside the transformer, and can construct a target equivalent circuit model of the transformer that more accurately describes the equivalent impedance characteristics of the transformer. By generating a simulated frequency response curve, the actual frequency response characteristics of the transformer can be simulated, so as to better understand the response of the transformer at different frequencies. By analyzing the simulated frequency response curve, the operating status of the transformer can be detected, potential problems can be discovered in time and corresponding measures can be taken to improve the operating efficiency and reliability of the transformer. In particular, the present application establishes a transformer winding equivalent circuit model that accurately describes the equivalent impedance characteristics of the transformer, and performs frequency response analysis after simulating the model to obtain a frequency response curve that is as consistent as possible with the measured frequency response analysis data. Non-destructive transformer winding fault diagnosis can be performed, which helps to timely and accurately detect the status of the transformer, prevent and reduce the operating risks of the transformer, and thus solves the technical problem of low efficiency in detecting the operating status of the transformer in the related art.

[0051] Optionally, based on the electrical signal parameter information and the network connection relationship, a target equivalent circuit model of the transformer is constructed, including: based on the electrical signal parameter information, determining branch electrical signal relationship expressions of multiple branch circuits, wherein the branch electrical signal relationship expressions are used to represent expressions of constraint relationships between branch voltage vectors and branch current vectors of multiple branch circuits; based on the network connection relationship, determining an association matrix of the target equivalent circuit model, wherein the association matrix is ​​used to represent a matrix of connection relationships between different nodes in the target equivalent circuit model; based on the association matrix, the branch voltage vectors and the branch current vectors in the branch electrical signal relationship expressions, constructing the target equivalent circuit model.

[0052] In an optional embodiment, a branch electrical signal relationship expression of each branch circuit can be established based on the circuit structure and parameter information of the transformer. The branch electrical signal relationship expression can be obtained by analyzing parameters such as voltage, current and impedance in the circuit, and is used to represent the constraint relationship between each branch circuit; the association matrix of the target equivalent circuit model can be determined based on the network connection relationship of the transformer, and the association matrix can be used to represent the connection relationship between different nodes in the transformer, including the main voltage nodes and branch nodes; finally, the target equivalent circuit model can be constructed by integrating the branch voltage vector and the branch current vector in the association matrix and the branch electrical signal relationship expression. The target equivalent circuit model can be used to monitor and analyze the operating status of the transformer, so as to promptly discover possible problems and repair them.

[0053] Optionally, based on the electrical signal parameter information, the branch electrical signal relationship expression of multiple branch circuits is determined, including: obtaining the branch voltage source vector, branch current source vector and branch impedance matrix in the electrical signal parameter information, wherein the branch impedance matrix is ​​used to represent a matrix composed of resistance parameters, capacitance parameters and inductance parameters based on multiple branch circuits; based on the branch voltage source vector, branch current source vector and branch impedance matrix, the branch electrical signal relationship expression is constructed.

[0054] In an optional embodiment, a branch electrical signal relationship expression can be constructed based on the acquired electrical signal parameter information. Specifically, the branch voltage source vector, branch current source vector and branch impedance matrix in the electrical signal parameter information can be obtained, and the voltage and current signal data of each branch of the transformer can be obtained through sensors or measuring instruments, which can include each branch voltage source vector and current source vector. According to the branch voltage and current signal data, the impedance parameters of the branch can be calculated and integrated into a branch impedance matrix. The branch impedance matrix can include parameters such as resistance, capacitance and inductance; according to the branch voltage source vector, the branch current source vector and the branch impedance matrix, a branch electrical signal relationship expression can be established. The branch electrical signal relationship expression describes the relationship between voltage, current and impedance, and can be used to analyze the operating status of each branch in the circuit. Through the branch electrical signal relationship expression, the voltage and current distribution between the branches of the transformer can be further analyzed to detect whether there is an abnormality or fault.

[0055] Optionally, based on the branch voltage source vector, the branch current source vector and the branch impedance matrix, a branch electrical signal relationship expression is constructed, including: constructing an initial branch electrical signal relationship expression based on the branch voltage source vector, the branch current source vector and the branch impedance matrix; determining a branch admittance matrix of multiple branch circuits based on an inverse matrix of the branch impedance matrix, wherein the branch admittance matrix is ​​a matrix used to represent the linear relationship between current signals and voltage signals in multiple branch circuits; determining the branch electrical signal relationship expression based on the initial branch electrical signal relationship expression and the branch admittance matrix.

[0056] The above-mentioned branch voltage source vector can represent the voltage signal of each branch, and can be represented by a vector. Each element of the vector can correspond to the voltage signal of a branch. The branch voltage source vector can also be determined according to actual needs, which is not limited here.

[0057] The above-mentioned branch current source vector can represent the current signal of each branch, and can be represented by a vector. Each element of the vector can correspond to the current signal of a branch. The branch current source vector can be determined according to actual needs and is not limited here.

[0058] The above-mentioned branch impedance matrix can represent the impedance relationship of each branch and can be represented by a matrix. The main diagonal elements of the matrix can be the impedance values ​​of each branch, and the non-diagonal elements represent the mutual impedance between branches. The branch impedance matrix can also be determined according to actual needs and is not limited here.

[0059] In an optional embodiment, an initial branch electrical signal relationship expression can be constructed by a branch voltage source vector, a branch current source vector and a branch impedance matrix. An initial branch electrical signal relationship expression can be constructed based on the branch voltage source vector, the branch current source vector and the branch impedance matrix. Based on the inverse matrix of the branch impedance matrix, a branch admittance matrix of multiple branch circuits can be determined. The branch admittance matrix can be used to represent the linear relationship between current signals and voltage signals in multiple branch circuits. Finally, based on the initial branch electrical signal relationship expression and the branch admittance matrix, a branch electrical signal relationship expression can be determined. The voltage signal and current signal in the initial branch electrical signal relationship expression can be substituted into the linear relationship of the branch admittance matrix to obtain a final branch electrical signal relationship expression. Through the above steps, a linear relationship between branch electrical signals can be established, thereby detecting and monitoring the operating status of the transformer.

[0060] The present application provides an optional method for establishing a target equivalent circuit model, which can be used to establish a lumped parameter equivalent circuit model of a magnetically controlled distribution transformer winding. Specifically, a generalized branch circuit can be established. When establishing a transformer winding equivalent circuit matrix algorithm, a branch equation can be established. Figure 2 is a schematic diagram of an optional branch analysis according to an embodiment of the present invention, such as Figure 2 As shown, it represents any branch in the transformer winding circuit. Figure 2 Middle I k We can express the current in the kth branch, I sk It can represent the current source current of the k branch, U sk It can represent the voltage source voltage of the k-branch, Z k It can represent the impedance of the k-branch, and "+" and "-" can represent the flow direction of the electrical signal, that is, the electrical signal flows from "+" to "-". Considering that the model can contain multiple branches, when each branch is included, the initial branch electrical signal relationship expression can be obtained according to the relationship between the branch voltage and current, which can be expressed as follows:

[0061] U = ZI - ZIs + Us;

[0062] Among them, U and I are the branch voltage vector and branch current vector respectively; Is is the branch current source vector; Us is the branch voltage source vector; Z is the branch impedance matrix.

[0063] Since Y=Z -1 , that is, the branch admittance matrix of multiple branch circuits can be determined based on the inverse matrix of the branch impedance matrix, and the initial branch electrical signal relationship expression can be expressed as:

[0064] I=YU-YUs+Is;

[0065] Wherein, Y is the branch admittance matrix. Considering that the transformer winding lumped parameter equivalent circuit model of the present application may not contain a branch current source, the initial branch electrical signal relationship expression can be simplified to obtain the branch electrical signal relationship expression, which can be expressed as follows;

[0066] I=YU-YUs;

[0067] Based on the network connection relationship, the association matrix A of the target equivalent circuit model can be determined, so that the target equivalent circuit model can be constructed based on the association matrix, the branch voltage vector and the branch current vector in the branch electrical signal relationship expression, that is, the equivalent circuit equation matrix is ​​established. According to Kirchhoff's current law and Kirchhoff's voltage law, the target equivalent circuit model can be obtained, which can be expressed as follows:

[0068]

[0069] Among them, A is the association matrix of the equivalent circuit, the dimension can be (n+1)×(3n+3), and can also be determined according to actual needs, which is not limited here; Un is the node voltage vector, and the target equivalent circuit model can also be determined according to actual needs, which is not limited here.

[0070] Optionally, based on the association matrix, the branch voltage vector and the branch current vector in the branch electrical signal relationship expression, a target equivalent circuit model is constructed, including: obtaining initial branch impedance parameters in the electrical signal parameter information, wherein the initial branch impedance parameters include at least resistance parameters, capacitance parameters and inductance parameters of multiple branch circuits; performing parameter search on the initial branch impedance parameters based on a preset bionic population optimization algorithm to obtain target branch impedance parameters, wherein the target branch impedance parameters include at least target resistance parameters, target capacitance parameters and target inductance parameters; based on the target branch impedance parameters, the association matrix, the branch voltage vector and the branch current vector in the branch electrical signal relationship expression, a target equivalent circuit model is constructed.

[0071] The preset bionic population optimization algorithm mentioned above may refer to a preset optimization algorithm based on bionic principles, which can simulate the process of population evolution in nature and find the optimal solution through competition, cooperation and adaptation among individuals in the population. In the preset bionic population optimization algorithm, the initial state and parameter settings of the population can be determined in advance, and may include genetic algorithms, particle swarm optimization, ant colony algorithms, etc., and the solution to the problem is optimized through different population evolution strategies and parameter settings. Optionally, the preset bionic population optimization algorithm may adopt the Mayfly algorithm. Algorithm) can be an optimization algorithm based on the survival behavior of mayflies in nature. The mayfly algorithm simulates the ability of mayflies to efficiently complete tasks within a short life cycle, and solves optimization problems by simulating the reproduction, food search, and predation escape behaviors of mayflies. The mayfly individual in the algorithm represents a candidate solution in the solution space. The competition and cooperation relationships in nature are simulated through interactions between mayflies such as pheromones, food, and predation. The mayfly algorithm has good global search capabilities and convergence speed when solving optimization problems, and is suitable for solving a variety of optimization problems.

[0072] In an optional embodiment, electrical signal parameter information of the transformer during operation can be obtained, which may include resistance, capacitance and inductance parameters of each branch, and can be obtained through transformer operation data or specific test equipment; the initial branch impedance parameters can be searched based on a preset bionic population optimization algorithm: after obtaining the initial branch impedance parameters, these parameters are searched and optimized using a preset bionic population optimization algorithm to obtain target branch impedance parameters that are closer to the actual situation. The biological evolution process can be simulated to find the optimal solution through continuous iteration; a target equivalent circuit model can be constructed based on the obtained target branch impedance parameters, the correlation matrix, and the branch voltage vector and branch current vector in the branch electrical signal relationship expression. The target equivalent circuit model can better describe the circuit characteristics of the transformer and help further analyze and detect the operating status of the transformer.

[0073] The present application provides a method for performing parameter search on initial branch impedance parameters based on a preset bionic population optimization algorithm to obtain target branch impedance parameters and then construct a target equivalent circuit model. The method can be a method for performing parameter optimization on a winding equivalent circuit model of a multifunctional magnetically controlled distribution transformer based on an ephemera algorithm. The method can be divided into the following steps: determining an input value, a parameter search process of an ephemera algorithm, setting an output value, and determining whether the optimization is completed. Specifically, the following steps can be included:

[0074] Determination of input values, which may include initial parameters of the transformer winding equivalent circuit model and related parameters required by the mayfly algorithm. The initial parameters of the transformer winding equivalent circuit may include at least resistance parameters, capacitance parameters and inductance parameters of multiple branch circuits, that is, initial values ​​of resistance (R), inductance (L), capacitance (C), etc.; parameters related to the mayfly algorithm may include: population size (N), the number of mayflies; maximum number of iterations (MaxGen), the maximum number of iterations for the algorithm to run; mating probability (Pm), the probability of mayflies mating; mutation probability (Pm), the probability of mayflies mutation, and other parameters specific to the mayfly algorithm may also be included, such as the life cycle and sex ratio of mayflies.

[0075] The parameter search process of the mayfly algorithm, the mayfly algorithm can be an optimization algorithm based on the life cycle behavior of the mayfly, specifically, it can include initializing the population, generating N mayfly individuals, each individual represents a parameter combination of the transformer winding equivalent circuit model; evaluating the fitness, calculating the fitness of each mayfly individual, the fitness function is determined according to the model parameter optimization target, such as minimizing the total loss or error of the circuit; selecting, selecting the mayfly individual with higher fitness according to the fitness value; mating and mutation, optimizing Preferably, the mayfly individuals can mate and generate new mayfly individuals by exchanging some parameters of the two mayfly individuals. The mating probability Pm determines the frequency of mating. Preferably, the mayfly individuals can mutate and randomly change some parameters of the mayfly individuals to increase the diversity of the population. The mutation probability Pm determines the frequency of mutation. The population can be updated and the old population can be replaced by the generated new mayfly individuals. The termination condition can be to stop the algorithm when the maximum number of iterations is reached or the fitness value reaches a predetermined threshold.

[0076] The output value setting may include at least target resistance parameters, target capacitance parameters and target inductance parameters, that is, optimized transformer winding equivalent circuit model parameters, optimized resistance (R_opt), optimized inductance (L_opt) and optimized capacitance (C_opt). The target branch impedance parameters may enable the circuit model to achieve optimal performance indicators, such as minimizing loss or error.

[0077] The judgment of the completion of optimization can include the number of iterations, the algorithm reaches the maximum number of iterations MaxGen; fitness convergence, in several consecutive generations, the change range of the optimal fitness value of the population is less than the preset threshold ε; performance indicators, the performance indicators of the model, such as loss or error, reach the expected target value.

[0078] Through the above steps, the mayfly algorithm can be used to effectively optimize the parameters of the multifunctional magnetically controlled distribution transformer winding equivalent circuit model, thereby improving the performance of the target equivalent circuit model.

[0079] Optionally, based on the target equivalent circuit model, a simulation frequency response curve is generated, including: based on the target equivalent circuit model, determining a node voltage equation of the target equivalent circuit model, wherein the node voltage equation is used to describe the relationship between voltages at different nodes in the target equivalent circuit model; based on the node voltage equation, determining node output voltages and node input voltages of different nodes in the target equivalent circuit model; based on the ratio of the node output voltage to the node input voltage, generating a simulation frequency response curve.

[0080] In an optional embodiment, a target equivalent circuit model can be established according to the structure and parameters of the transformer, and the voltage equations at different nodes in the target equivalent circuit model can be obtained according to the basic principles and methods of circuit analysis, and the node voltage equations can describe the voltage relationship between the nodes in the target equivalent circuit model; the output voltage and input voltage of each node can be solved according to the node voltage equations of the target equivalent circuit model, and the node output voltage and the node input voltage can reflect the voltage distribution of the transformer at different nodes; the transfer function of the transformer at different frequencies can be obtained by calculating the ratio of the node output voltage to the node input voltage, and the simulated frequency response curve of the transformer can be drawn according to the modulus and phase angle of the transmission function, and the simulated frequency response curve can reflect the response characteristics of the transformer at different frequencies, helping users understand the operating status and performance of the transformer.

[0081] The present application provides a method for generating a simulation frequency response curve. Specifically, the target equivalent circuit model can be substituted into the initial branch electrical signal relationship expression to obtain the node voltage equation of the winding lumped parameter equivalent circuit, that is, the node voltage equation of the target equivalent circuit model, which can be expressed as:

[0082] AYA T U n =AYUs-AI s ;

[0083] Considering that the frequency response curve can be expressed as the ratio of the transformer winding frequency response to the output voltage and the input voltage, and Un can be solved by the node voltage equation of the target equivalent circuit model, the frequency response required by this application can be the ratio of the n+1th node voltage Un(n+1,1) of the equivalent circuit Un to the input voltage Un(1,1). Since the input voltage is known, the frequency response calculation formula of the transformer winding lumped parameter equivalent circuit, that is, the simulation frequency response curve (FRA) can be expressed as:

[0084] ;

[0085] The specific form of the simulated frequency response curve (FRA) can also be determined according to actual needs and is not limited here.

[0086] With the access of new energy power generation systems with high volatility and the application of a large number of highly nonlinear power electronic equipment in distribution networks, the diversity and complexity of distribution transformer loads have increased significantly. In new power systems, a large number of power electronic devices and unbalanced loads cause increasingly serious power quality pollution due to their own nonlinearity during operation, which puts higher requirements on the power quality of the power system. Traditional distribution transformers cannot meet the requirements. As a new type of power equipment with both voltage regulation and reactive power compensation capabilities, magnetically controlled distribution transformers have the advantages of compact structure, high reliability, and flexible control. Therefore, the application of multifunctional magnetically controlled distribution transformers is of great significance to the construction and development of new power systems. The normal operation of multifunctional magnetically controlled distribution transformers is related to the stability and reliability of the power system. However, in actual operation, the transformer The transformer is often impacted by the huge electric force caused by short-circuit current, which can easily cause deformation of its winding. Slight deformation of the winding may not immediately cause transformer failure in a short period of time, but under the cumulative effect of multiple short-circuit current impacts, the insulation strength of the transformer winding continues to decrease, which may cause short circuit between winding turns or serious deformation of the winding, thereby causing serious damage or transformer explosion, and ultimately affecting the normal operation of the power grid. This application proposes to establish an accurate transformer winding equivalent circuit model, and perform frequency response analysis after simulating the transformer winding equivalent circuit model to obtain a frequency response curve that is as consistent as possible with the measured frequency response analysis (FRA) data. Non-destructive transformer winding fault diagnosis can be performed, which helps to timely and accurately detect the status of the transformer, thereby preventing and reducing transformer operation risks.

[0087] At present, the establishment of transformer winding equivalent circuit model mainly calculates the resistance, inductance and capacitance parameters of the transformer winding lumped parameter equivalent network model by finite element method, analytical formula or a combination of the two. At present, it is difficult to establish a corresponding relationship between the obtained FRA curve and the winding enclosed in the oil tank only by measurement means. In addition, in order to study the changes in the winding frequency response curve under different winding deformation types and different deformation degrees, the method of trying to obtain the FRA curve by deforming the actual transformer is very complicated and expensive. In order to obtain the FRA curve to establish the transformer winding equivalent circuit model, both the analytical method and the finite element method are based on the simplified transformer winding structure for calculation, which is not suitable for the new multifunctional magnetically controlled distribution transformer, and there is a large error between the obtained parameter values ​​and the actual parameter values.

[0088] This application proposes to establish a lumped parameter equivalent circuit model of a magnetically controlled distribution transformer, and derive a calculation method for the frequency response curve of the lumped parameter equivalent circuit model of the transformer winding, and then optimize the parameters of the model through the mayfly algorithm, and finally complete the establishment of the lumped parameter equivalent circuit model of the multifunctional magnetically controlled distribution transformer after parameter optimization. This application can solve the above-mentioned technical problems existing in the prior art, and provides a multifunctional magnetically controlled distribution transformer winding equivalent circuit modeling method based on the mayfly optimization algorithm, and optimizes the parameters of the established lumped parameter equivalent circuit model of the magnetically controlled distribution transformer through the mayfly algorithm, improves the consistency of the obtained FRA curve with the measured FRA curve, and performs more accurate detection and prediction of the status and potential risks of the transformer. This method is applicable to new multifunctional magnetically controlled distribution transformers, consumes less computing resources, is economical, and has a broad application prospect.

[0089] This application proposes a method for modeling the equivalent circuit of a multifunctional magnetically controlled distribution transformer winding based on the ephemera optimization algorithm. Figure 3 is a flow chart of an optional method for detecting the operating status of a transformer according to an embodiment of the present invention, such as Figure 3 As shown, the process may include the following steps:

[0090] Step S302, obtaining electrical signal parameter information of multiple branch circuits in the transformer and network connection relationships between the multiple branch circuits.

[0091] Step S304, based on the electrical signal parameter information, determine the branch electrical signal relationship expressions of the plurality of branch circuits; based on the network connection relationship, determine the association matrix of the target equivalent circuit model.

[0092] Step S306, initialize the preset bionic population optimization algorithm, evaluate the adaptability, verify the constraints (that is, the mating and mutation process of the above-mentioned optimization algorithm), and when the constraints are met, calculate the fitness and update the optimal solution; when the constraints are not met, replace the current solution with the nearest feasible solution that can meet the constraints, calculate the fitness and update the optimal solution; update the population, determine whether the number of iterations has been reached, and when the number of iterations has not been reached, jump to the step of evaluating the adaptability, and when the number of iterations has been reached, execute step S308.

[0093] Step S308, construct a target equivalent circuit model based on the target branch impedance parameter, the correlation matrix, the branch voltage vector and the branch current vector in the branch electrical signal relationship expression; generate a simulation frequency response curve based on the target equivalent circuit model; and detect the operating state of the transformer based on the simulation frequency response curve. The process ends.

[0094] This application establishes a lumped parameter equivalent circuit model of the winding of a magnetically controlled distribution transformer and derives a method for calculating the frequency response curve of the lumped parameter equivalent circuit model of the transformer winding. The model can then be optimized using an ephemeral algorithm. When the parameter offset is less than the allowable parameter offset, the establishment of the lumped parameter equivalent circuit model of the multifunctional magnetically controlled distribution transformer after parameter optimization is completed.

[0095] Based on the transformer operating condition detection method proposed in this application, a preset bionic population optimization algorithm can be used to obtain optimized parameters and construct a more accurate transformer winding equivalent circuit model; a FRA curve that is more consistent with the actual winding can be obtained in a concise, efficient and economical manner; and a foundation can be laid for subsequent in-depth research on the relationship between the FRA curve and the winding parameters, and then accurately identifying transformer winding faults.

[0096] According to another aspect of an embodiment of the present invention, a device for detecting the operating status of a transformer is also provided. The system can execute the method for detecting the operating status of the transformer of the above embodiment. The specific implementation method and preferred application scenario are the same as those of the above embodiment and will not be repeated here.

[0097] Figure 4 is a schematic diagram of a transformer operating status detection device according to an embodiment of the present application, such as Figure 4 As shown, the device includes the following: an acquisition module 402 , a construction module 404 , a generation module 406 and a detection module 408 .

[0098] Among them, the acquisition module 402 is used to obtain the electrical signal parameter information of multiple branch circuits in the transformer and the network connection relationship between the multiple branch circuits, wherein the multiple branch circuits are used to represent different circuit branches obtained by dividing the winding circuit in the transformer based on the branch nodes in the transformer; the construction module 404 is used to construct a target equivalent circuit model of the transformer based on the electrical signal parameter information and the network connection relationship, wherein the target equivalent circuit model is used to represent an equivalent circuit model established based on the equivalent impedance characteristics of the transformer; the generation module 406 is used to generate a simulation frequency response curve based on the target equivalent circuit model, wherein the simulation frequency response curve is used to simulate the actual frequency response characteristics of the transformer; the detection module 408 is used to detect the operating status of the transformer based on the simulation frequency response curve.

[0099] Among them, the construction module is also used to determine the branch electrical signal relationship expressions of multiple branch circuits based on the electrical signal parameter information, wherein the branch electrical signal relationship expressions are used to represent the expressions of the constraint relationships between the branch voltage vectors and the branch current vectors of the multiple branch circuits; based on the network connection relationship, determine the association matrix of the target equivalent circuit model, wherein the association matrix is ​​used to represent the matrix of the connection relationship between different nodes in the target equivalent circuit model; based on the association matrix, the branch voltage vectors and the branch current vectors in the branch electrical signal relationship expressions, construct the target equivalent circuit model.

[0100] Among them, the construction module is also used to obtain the branch voltage source vector, branch current source vector and branch impedance matrix in the electrical signal parameter information, wherein the branch impedance matrix is ​​used to represent a matrix composed of resistance parameters, capacitance parameters and inductance parameters based on multiple branch circuits; based on the branch voltage source vector, branch current source vector and branch impedance matrix, a branch electrical signal relationship expression is constructed.

[0101] Among them, the construction module is also used to construct an initial branch electrical signal relationship expression based on the branch voltage source vector, the branch current source vector and the branch impedance matrix; based on the inverse matrix of the branch impedance matrix, determine the branch admittance matrix of multiple branch circuits, wherein the branch admittance matrix is ​​a matrix used to represent the linear relationship between current signals and voltage signals in multiple branch circuits; based on the initial branch electrical signal relationship expression and the branch admittance matrix, determine the branch electrical signal relationship expression.

[0102] Among them, the construction module is also used to obtain the initial branch impedance parameters in the electrical signal parameter information, wherein the initial branch impedance parameters at least include the resistance parameters, capacitance parameters and inductance parameters of multiple branch circuits; based on the preset bionic population optimization algorithm, the initial branch impedance parameters are searched to obtain the target branch impedance parameters, wherein the target branch impedance parameters at least include the target resistance parameters, target capacitance parameters and target inductance parameters; based on the target branch impedance parameters, the association matrix, the branch voltage vector and the branch current vector in the branch electrical signal relationship expression, a target equivalent circuit model is constructed.

[0103] Among them, the generation module is also used to determine the node voltage equation of the target equivalent circuit model based on the target equivalent circuit model, wherein the node voltage equation is used to describe the relationship between the voltages at different nodes in the target equivalent circuit model; based on the node voltage equation, determine the node output voltage and node input voltage of different nodes in the target equivalent circuit model; based on the ratio of the node output voltage to the node input voltage, generate a simulation frequency response curve.

[0104] An embodiment of the present application further provides an electronic device, comprising: a memory storing an executable program; and a processor for running the program, wherein the program executes the methods in various embodiments of the present invention when running.

[0105] The above-mentioned memory may refer to a device inside a computer for storing data and programs, and may include memory, hard disk, etc., wherein the memory may be used to temporarily store running programs and data, the hard disk may be used to store programs and data for a long time, and the memory may be used to enable the computer to read and write data, and execute programs; the above-mentioned processor may be responsible for executing instructions in computer programs and performing data processing, and may be responsible for controlling and executing various operations, including arithmetic operations, logical operations, data transmission, etc.

[0106] An embodiment of the present application further provides a computer-readable storage medium, which includes a stored executable program, wherein when the executable program is running, the device where the computer-readable storage medium is located is controlled to execute the methods in various embodiments of the present invention.

[0107] The above-mentioned computer storage medium may refer to a medium in a computer memory used to store certain discontinuous physical quantities. Computer storage media mainly include semiconductors, magnetic cores, magnetic drums, magnetic tapes, laser disks, etc.; the stored program included in the computer-readable storage medium may be a set of instructions that can be recognized and executed by a computer, running on an electronic computer, and is an information tool that meets certain needs of people.

[0108] An embodiment of the present application further provides a computer program product, including a computer program, which implements the methods in various embodiments of the present invention when executed by a processor.

[0109] The above-mentioned computer program product may refer to a software program that has been written, tested and released and can be run on a computer or other device. The computer program product may include an application, an operating system, tool software, etc., which is used to implement specific functions or solve specific problems.

[0110] An embodiment of the present application further provides a computer program product, including a non-volatile computer-readable storage medium, wherein the non-volatile computer-readable storage medium is used to store a computer program, and when the computer program is executed by a processor, the method in each embodiment of the present invention is implemented.

[0111] The above-mentioned non-volatile computer-readable storage medium may refer to a medium for storing data. The non-volatile computer-readable storage medium can keep the data from being lost when the power is off, and can be used to store long-term data, such as operating systems, applications, and user files. The non-volatile storage medium may include hard disk drives, solid-state drives, optical disks, and flash memory storage devices, etc.

[0112] The embodiments of the present application further provide a computer program, which implements the methods in the above-mentioned embodiments of the present invention when executed by a processor.

[0113] The above-mentioned computer program may refer to a collection of instructions used to tell a computer to perform a specific task or operation. A computer program may be written by a programmer using a specific programming language and may include algorithms, data structures, logic, and control flows. A computer program may be used for a variety of purposes, including application software, operating systems, and the like.

[0114] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0115] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units can be a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0116] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0117] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0118] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk, etc. Various media that can store program codes.

[0119] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for detecting the operating status of a transformer, characterized in that: include: Acquire electrical signal parameter information of a plurality of branch circuits in the transformer and network connection relationships between the plurality of branch circuits, wherein the plurality of branch circuits are used to represent different circuit branches obtained by dividing the winding circuit in the transformer based on branch nodes in the transformer; Based on the electrical signal parameter information and the network connection relationship, a target equivalent circuit model of the transformer is constructed, wherein the target equivalent circuit model is used to represent an equivalent circuit model established based on an equivalent impedance characteristic of the transformer, and the equivalent impedance characteristic is used to represent the impedance characteristic of the equivalent circuit exhibited by the transformer during operation, and the target equivalent circuit model at least includes a lumped parameter equivalent circuit model of a transformer winding circuit, and the lumped parameter equivalent circuit model is used to represent that the winding circuit of the transformer is abstracted as a simplified circuit model including resistance, inductance and capacitance; Based on the target equivalent circuit model, generating a simulation frequency response curve, wherein the simulation frequency response curve is used to simulate actual frequency response characteristics of the transformer; Based on the simulated frequency response curve, the operating state of the transformer is detected.

2. The method for detecting the operating status of a transformer according to claim 1, characterized in that: Based on the electrical signal parameter information and the network connection relationship, constructing a target equivalent circuit model of the transformer, including: Based on the electrical signal parameter information, determining branch electrical signal relationship expressions of the plurality of branch circuits, wherein the branch electrical signal relationship expressions are used to represent expressions of constraint relationships between branch voltage vectors and branch current vectors of the plurality of branch circuits; Based on the network connection relationship, determining an association matrix of the target equivalent circuit model, wherein the association matrix is ​​used to represent a matrix of connection relationships between different nodes in the target equivalent circuit model; The target equivalent circuit model is constructed based on the association matrix, the branch voltage vector and the branch current vector in the branch electrical signal relationship expression.

3. The method for detecting the operating status of a transformer according to claim 2, characterized in that: Determining branch electrical signal relationship expressions of the plurality of branch circuits based on the electrical signal parameter information includes: Acquire a branch voltage source vector, a branch current source vector and a branch impedance matrix in the electrical signal parameter information, wherein the branch impedance matrix is ​​used to represent a matrix composed of resistance parameters, capacitance parameters and inductance parameters based on the plurality of branch circuits; The branch electrical signal relationship expression is constructed based on the branch voltage source vector, the branch current source vector and the branch impedance matrix.

4. The method for detecting the operating status of a transformer according to claim 3, characterized in that: Based on the branch voltage source vector, the branch current source vector and the branch impedance matrix, constructing the branch electrical signal relationship expression, including: Constructing an initial branch electrical signal relationship expression based on the branch voltage source vector, the branch current source vector and the branch impedance matrix; Determine a branch admittance matrix of the plurality of branch circuits based on an inverse matrix of the branch impedance matrix, wherein the branch admittance matrix is ​​a matrix for representing a linear relationship between current signals and voltage signals in the plurality of branch circuits; The branch electrical signal relationship expression is determined based on the initial branch electrical signal relationship expression and the branch admittance matrix.

5. The method for detecting the operating status of a transformer according to claim 2, characterized in that: The target equivalent circuit model is constructed based on the association matrix, the branch voltage vector and the branch current vector in the branch electrical signal relationship expression, including: Acquire initial branch impedance parameters in the electrical signal parameter information, wherein the initial branch impedance parameters at least include resistance parameters, capacitance parameters, and inductance parameters of the multiple branch circuits; Performing parameter search on the initial branch impedance parameters based on a preset bionic population optimization algorithm to obtain target branch impedance parameters, wherein the target branch impedance parameters at least include target resistance parameters, target capacitance parameters, and target inductance parameters; The target equivalent circuit model is constructed based on the target branch impedance parameter, the association matrix, the branch voltage vector and the branch current vector in the branch electrical signal relationship expression.

6. The method for detecting the operating status of a transformer according to claim 1, characterized in that: Based on the target equivalent circuit model, a simulation frequency response curve is generated, including: Based on the target equivalent circuit model, determining a node voltage equation of the target equivalent circuit model, wherein the node voltage equation is used to describe the relationship between voltages at different nodes in the target equivalent circuit model; Based on the node voltage equation, determining the node output voltage and the node input voltage of the different nodes in the target equivalent circuit model; The simulated frequency response curve is generated based on the ratio of the node output voltage to the node input voltage.

7. A transformer operating status detection device, characterized in that: include: An acquisition module, used to acquire electrical signal parameter information of a plurality of branch circuits in the transformer, and network connection relationships between the plurality of branch circuits, wherein the plurality of branch circuits are used to represent different circuit branches obtained by dividing the winding circuit in the transformer based on the branch nodes in the transformer; A construction module, configured to construct a target equivalent circuit model of the transformer based on the electrical signal parameter information and the network connection relationship, wherein the target equivalent circuit model is used to represent an equivalent circuit model established based on an equivalent impedance characteristic of the transformer, the equivalent impedance characteristic is used to represent the impedance characteristic of the equivalent circuit exhibited by the transformer during operation, and the target equivalent circuit model at least includes a lumped parameter equivalent circuit model of a transformer winding circuit, and the lumped parameter equivalent circuit model is used to represent that the winding circuit of the transformer is abstracted as a simplified circuit model including resistance, inductance and capacitance; A generating module, configured to generate a simulated frequency response curve based on the target equivalent circuit model, wherein the simulated frequency response curve is used to simulate an actual frequency response characteristic of the transformer; A detection module is used to detect the operating state of the transformer based on the simulated frequency response curve.

8. An electronic device, characterized in that: include: A memory storing an executable program; A processor is used to run the program, wherein the program, when running, executes the method for detecting the operating status of a transformer as described in any one of claims 1 to 7.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored executable program, wherein when the executable program is executed, the device where the storage medium is located is controlled to execute the transformer operating status detection method according to any one of claims 1 to 7.

10. A computer program product, characterized in that It comprises a computer program, which, when executed by a processor, implements the method for detecting the operating state of a transformer according to any one of claims 1 to 7.

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