Transformer resistance parameter online monitoring method and system based on winding temperature change

Abstract

The invention discloses a transformer resistance parameter on-line monitoring method and system based on winding temperature change, and relates to the technical field of transformer winding deformation parameter monitoring method.The method comprises the steps that an oil temperature sensor is used for measuring the oil temperature of a transformer, a 1: 1 simulation model is established, and the relation between winding temperature distribution and winding height is obtained; according to the actual position of an oil baffle plate of a transformer, regionalization analysis is carried out on temperature distribution of a winding, a relational expression between winding temperature distribution and winding height of each region is obtained through curve fitting, an oil temperature sensor is used for obtaining oil temperature values of boundaries of each region, average value operation and summation operation are carried out according to the fitted relational expression, and the oil temperature values of the boundaries of the regions are obtained. And obtaining the current transformer winding temperature. And finally, calculating a resistance parameter changing along with the temperature according to the thermal characteristics of the wire. According to the method, the top oil temperature value is corrected, so that the winding temperature quickly approaches the real situation, and the resistance parameter for monitoring the deformation of the transformer winding is quickly and effectively calculated.

Description

Technical Field

[0001] The present invention relates to the technical field of transformer winding deformation parameter monitoring methods, and in particular to a transformer resistance parameter online monitoring method and system based on winding temperature changes. Background Art

[0002] Power transformers are crucial to ensuring the reliability of power systems. Power transformers operating in power grids will inevitably be impacted by various short-circuit faults, especially outlet or near-area short-circuits, which are more harmful to them. The huge electric force generated by the short-circuit current and the instantaneous rapid heating of the windings may cause the transformer windings to change in axial and radial dimensions, twist and bulge, or even inter-circuit faults. In addition, accidental collisions during transportation of transformers may also cause deformation of the windings and displacement of the body. Winding deformation has become the main cause of health hazards and failures of transformers.

[0003] At present, the commonly used transformer winding deformation detection methods include: short-circuit reactance method, low-voltage pulse method and frequency response analysis method, etc. These methods all require the transformer to be shut down for offline detection, and cannot monitor the transformer winding condition at any time and find faults in real time. Online monitoring and diagnosis that does not affect the operating status of the transformer is the development direction of the transformer monitoring system. Because the transformer short-circuit impedance and the inductance component in the impedance are related to the geometric size and relative position of the winding, the technology of analyzing the health status of the winding by online detection of the short-circuit reactance change of the transformer is gradually gaining attention. As the key parameter for online detection of transformer parameters, the accuracy of the measurement of winding resistance has a great influence on the identification result of the inductance component.

[0004] In order to solve the above problems, the present invention proposes an online monitoring method for transformer winding deformation resistance parameters based on winding temperature changes. The method accurately measures the winding resistance and performs correction in combination with the winding temperature changes, providing key parameters for real-time monitoring of the health status of the transformer winding, thereby improving the safety and reliability of transformer operation. Summary of the invention

[0005] In view of the above existing problems, the present invention aims to monitor the transformer winding resistance in real time to ensure its safe and stable operation. Through oil temperature sensor measurement, 1:1 simulation model establishment, layered regional analysis and curve fitting, the problem of winding temperature distribution being difficult to measure accurately is solved; combining material properties and temperature coefficient calculation, the resistance change is accurately calculated, solving the problem of resistance changing with temperature being difficult to calculate; through temperature gradient correction and equivalent circuit parameter identification, the real-time update and monitoring of winding resistance parameters are realized, improving the operating reliability and maintenance efficiency of the transformer.

[0006] In order to solve the above technical problems, an online monitoring method of transformer resistance parameters based on winding temperature change is proposed, including:

[0007] The oil temperature of the transformer is measured by an oil temperature sensor, and a temperature sampling point is set at the position of the transformer oil baffle. A 1:1 simulation model is established to obtain the relationship between the initial winding temperature distribution and the winding height. The temperature distribution of the winding is analyzed in a layered and regionalized manner. The relationship between the winding temperature distribution and the winding height in all regions is fitted by curve fitting. The temperature coefficient of the winding is obtained according to the material properties, and the resistance parameter that changes with temperature is calculated. According to the oil temperature at the corresponding position of the sampling point, the winding temperature in the area where the oil baffle is located is calculated after temperature gradient correction. The average winding temperature is calculated by fitting the curve and the resistance parameter that changes with temperature is updated.

[0008] As a preferred solution of the transformer resistance parameter online monitoring method based on winding temperature change described in the present invention, wherein: the measuring of the transformer oil temperature includes selecting a thermocouple high-precision temperature sensor to measure the transformer top oil temperature, the oil tank inlet oil temperature, and the radiator outlet oil temperature.

[0009] The establishment of the 1:1 simulation model includes using 3D modeling software SolidWorks to draw 1:1 scale three-dimensional models of the transformer radiator and windings of each voltage level, using finite element analysis software COMSOL to mesh the 3D model, generate fluid domain meshes and solid domain meshes, and perform mesh quality inspection.

[0010] As a preferred solution of the transformer resistance parameter online monitoring method based on winding temperature change described in the present invention, wherein: the relationship between the winding temperature distribution and the winding height is obtained, including importing a 3D model in the simulation software, setting the operating parameters of the transformer, changing the load after rated operation, and recording the temperature change. According to the recording results, the relationship function between the initial winding temperature at the transformer oil baffle position and the winding height is extracted through the fluid-temperature field coupling model:

[0011]

[0012] Where T(z) is the temperature distribution function at the winding height z, I is the total number of meshes, i is the mesh number index, and ρ i is the density function of the ith grid, ΔV i is the volume of the i-th grid, Q i is the heat flux density of the ith grid, Q total is the total heat flux density of the entire winding, T i is the center temperature of the ith grid, T Ref is the reference temperature, is the variance of the temperature distribution of the ith grid, is the variance of the time-varying temperature distribution, μ tis the time average temperature, and t is the time variable.

[0013] As a preferred solution of the transformer resistance parameter online monitoring method based on winding temperature change described in the present invention, the layered regional analysis includes obtaining the winding temperature distribution according to the T(z) values ​​at different heights, dividing the winding into layers z'1, z'2, z'3 and z'4 according to the position of the oil baffle, performing layered curve fitting on all temperature data ∑T(z) values ​​of each layer, performing regional fitting according to the layers z'1, z'2, z'3 and z'4, and obtaining the relationship between the fitted temperature and the winding height as follows:

[0014]

[0015] in, as well as is the average winding temperature value after fitting in the area divided by the oil baffle position, is the average winding height of each layer, a 0 , …, a 8 is the fitting parameter, a 0 =361.01, a 1 =0.01124, a 2 =361.23, a 3 =0.0091, a 4 =361.38, a 5 =0.0084, a 6 =345.47, a 7 =0.086, a 8 =-0.0000958.

[0016] The average value of the winding temperature change The winding resistance is calculated as:

[0017]

[0018] Among them, R 0 is the resistance before temperature change, R 1 is the resistance after temperature change, and are the average winding temperature values ​​at the corresponding time before and after the temperature change, respectively, and α is the temperature coefficient of the winding.

[0019] Obtain the temperature coefficient α of the winding based on the material properties:

[0020]

[0021] Among them, z min For z 1 、z 2 、z3 and z 4 The minimum height of each winding layer area, z max For z 1 、z 2 、z 3 and z 4 The maximum height of each winding layer area, J is the number of winding layers, j is the current layer index, Γ(j) is the gamma function for normalization, is the derivative of the winding temperature with height, z'j is the height of the j-th winding, a is the fitting parameter describing the non-uniformity of temperature distribution, is the derivative of the winding resistance with temperature, R Ref is the resistance of the winding at the reference temperature.

[0022] According to the temperature change result, the resistance parameter of the winding resistance is updated.

[0023] As a preferred solution of the transformer resistance parameter online monitoring method based on winding temperature change described in the present invention, wherein: the resistance parameter of the winding resistance update includes, when the temperature changes slowly, that is, the temperature does not change by more than 1 degree Celsius in one hour, each round of sampling cycle is at the ms level, and the oil temperature value at the start time of each round of sampling is used to respectively calculate the winding average temperature, and then the formula for the winding resistance value calculated from the winding average temperature is:

[0024] R 1 (T r1 2) = R 1 (T r1 1)[1+α(T r1 2-T r1 1)]

[0025] R 2 (T r2 2) = R 2 (T r2 1)[1+α(T r2 2-T r2 1)]

[0026] Among them, T r1 1 and T r2 1 represents t 1 The average temperature of the primary and secondary windings at the moment, T r1 2 and T r2 2 respectively represent t 2 The average temperature of the primary and secondary windings at that moment.

[0027] As a preferred embodiment of the transformer resistance parameter online monitoring method based on winding temperature change described in the present invention, the temperature gradient correction includes: when the temperature changes rapidly, that is, the temperature changes by more than 1 degree Celsius within one hour, m (z n ) Update the winding temperature T'(z) in the area where the oil baffle is located:

[0028]

[0029] Among them, G m (z n ) is the mth sampling point at height z n The temperature gradient correction value at , M is the number of sampling points considered, w m is the weight factor of the mth sampling point, z n,m is the height of the mth sampling point, δ z,m is the height range affected by the temperature gradient considered at the mth sampling point, is the temperature gradient at the mth sampling point varying with height z', t m is the time point of the mth sampling point, β is a temperature gradient influencing factor greater than zero, which adjusts the sensitivity of the correction value.

[0030] Update the relationship function between the initial winding temperature and the winding height to T'(z):

[0031]

[0032] Where T'(z) is the corrected temperature of the winding at height z, Γ(w) is the weight factor in the gamma function processing integral, ΔT is the temperature variation range, μ i is the average temperature distribution of the ith grid, T is the temperature variable, γ is the order of integration, z n is the height of the nth sampling point.

[0033] After updating T'(z), re-perform layered curve fitting to obtain the new average winding temperature in each area as well as And calculate the average winding temperature:

[0034]

[0035] The winding resistance is calculated by the winding temperature change:

[0036]

[0037] Among them, R' 0 To update the resistance before the temperature change, R' 1 To update the resistance after temperature change, and They are the average temperature values ​​of the winding at the corresponding time before and after the temperature change, respectively.

[0038] As a preferred solution of the transformer resistance parameter online monitoring method based on winding temperature change described in the present invention, wherein: the resistance parameter of the winding resistance update also includes a formula for online detection of winding deformation, the resistance parameter is a key input quantity of the formula, a T-type equivalent circuit of the transformer is established, the transformer phasor equation is listed according to the T-type equivalent circuit, and the relationship between each transformer input signal and the winding parameter is established. The transformer phasor equation is:

[0039]

[0040] Transform the established T-type equivalent circuit phasor equation into the standard form of least squares:

[0041]

[0042] Among them, k is the transformer ratio, and the resistance parameter r 1 、r 2 As the identification inductance L 1 , L 2 The key input quantity.

[0043] Another object of the present invention is to provide an online monitoring system for transformer resistance parameters based on winding temperature changes. The present invention realizes accurate monitoring of transformer winding temperature and real-time update of resistance parameters to prevent faults and improve operational safety. The system ensures the accuracy of temperature data through a data acquisition and processing module, solves the problem of uneven winding temperature distribution and resistance value calculation through a temperature distribution analysis and resistance calculation module, and dynamically adjusts the resistance value through a resistance parameter online monitoring and update module, which collaboratively solves the real-time and accuracy problems of transformer monitoring, reduces fault risks, provides technical support for maintenance and fault diagnosis, enhances operational stability and prolongs service life.

[0044] As a preferred solution of the transformer resistance parameter online monitoring system based on winding temperature change described in the present invention, it is characterized by including a data acquisition and processing module, a temperature distribution analysis and resistance calculation module, and a resistance parameter online monitoring and updating module.

[0045] The data acquisition and processing module is responsible for collecting the temperature data and related parameters of the transformer, ensuring the accuracy of the data through high-precision measuring equipment, and pre-processing the collected data for use in subsequent modules.

[0046] The temperature distribution analysis and resistance calculation module uses the collected data in combination with the established 1:1 simulation model to analyze the temperature distribution of the transformer winding and calculate the average temperature of the winding. The simulation software performs fluid-temperature field coupling analysis to obtain the relationship between the winding temperature distribution and the height, and performs curve fitting. According to the temperature coefficient and material properties of the winding, the resistance parameter that changes with temperature is calculated.

[0047] The online monitoring and updating module of the resistance parameter adjusts the calculation of the resistance value according to the temperature change. When the temperature changes slowly, the oil temperature value at the start of each round of sampling is used to calculate the average temperature of the winding, and then the winding resistance value is calculated from the average temperature of the winding. When the temperature changes rapidly, the winding temperature is updated by the temperature gradient correction value, and the resistance value is recalculated. According to the T-type equivalent circuit and the transformer phasor equation, the resistance parameter is updated and used to identify the key parameters of inductance and capacitance.

[0048] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and is characterized in that when the processor executes the computer program, the steps of the method described in the online monitoring of transformer resistance parameters based on winding temperature changes are implemented.

[0049] A computer-readable storage medium stores a computer program, wherein when the computer program is executed by a processor, the steps of the method described in the online monitoring of transformer resistance parameters based on winding temperature changes are implemented.

[0050] Beneficial effects of the present invention: The present invention provides an effective method for real-time monitoring of the health status of transformer windings by accurately measuring the resistance of transformer windings and correcting the temperature change of the windings. By accurately monitoring the winding resistance, abnormal conditions that may occur during the operation of the transformer, such as overheating, short circuit or aging of the winding, can be discovered in time. If these abnormal conditions are not discovered and handled in time, they may cause transformer failures and even cause serious safety accidents. Therefore, through the technical means of the present invention, it is possible to achieve real-time monitoring of the state of the transformer windings, and obtain the health parameters of the windings in time, so as to discover potential problems at an early stage and take corresponding maintenance measures to ensure the safe operation of the transformer. In addition, in the process of measuring the winding resistance, the present invention takes into account the influence of temperature changes on the resistance measurement, and improves the accuracy of the measurement through temperature correction technology. Temperature is an important factor affecting the resistance value. The resistance value of the winding at different temperatures will be different. Therefore, through temperature correction, the measurement error caused by temperature changes can be eliminated, thereby obtaining a more accurate winding resistance value. This provides reliable data support for the accurate evaluation of the operating status of the transformer. Through the above method, the present invention not only improves the accuracy of transformer winding health status monitoring, but also enhances the safety and reliability of transformer operation, reduces unexpected shutdown and maintenance costs caused by winding failures, and has important practical application value and broad promotion prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work, among which:

[0052] Figure 1 An overall flow chart of a method for online monitoring of transformer resistance parameters based on winding temperature changes provided by an embodiment of the present invention.

[0053] Figure 2 A transformer 3D simulation model diagram of a method for online monitoring of transformer resistance parameters based on winding temperature changes provided by an embodiment of the present invention.

[0054] Figure 3 A schematic diagram of the position of an oil baffle plate of a transformer in an online monitoring method of transformer resistance parameters based on winding temperature changes provided by an embodiment of the present invention.

[0055] Figure 4 A transformer winding hot spot temperature cloud diagram of a transformer resistance parameter online monitoring method based on winding temperature change provided by an embodiment of the present invention.

[0056] Figure 5 A fitting curve diagram of the relationship between transformer winding temperature and winding height in an online transformer resistance parameter monitoring method based on winding temperature change provided by an embodiment of the present invention.

[0057] Figure 6 A 3D model of a transformer for an online monitoring method of transformer resistance parameters based on winding temperature changes provided by an embodiment of the present invention.

[0058] Figure 7 A 2D transformer model of an online transformer resistance parameter monitoring method based on winding temperature change provided by an embodiment of the present invention.

[0059] Figure 8 A two-dimensional symmetrical geometric meshing diagram showing meshing quality statistics of a transformer resistance parameter online monitoring method based on winding temperature changes provided by an embodiment of the present invention.

[0060] Fig. 9 A three-dimensional geometric meshing diagram showing meshing quality statistics of a transformer resistance parameter online monitoring method based on winding temperature changes provided by an embodiment of the present invention.

[0061] Fig.10 A schematic diagram of a two-dimensional oil channel model of an online monitoring method for transformer resistance parameters based on winding temperature changes provided by an embodiment of the present invention.

[0062] Fig.11 A two-dimensional temperature distribution diagram of a transformer temperature distribution simulation result under rated working conditions of an online monitoring method for transformer resistance parameters based on winding temperature change provided by an embodiment of the present invention.

[0063] Fig.12 A three-dimensional temperature distribution diagram of a transformer temperature distribution simulation result under rated working conditions of an online monitoring method for transformer resistance parameters based on winding temperature change provided by an embodiment of the present invention.

[0064] Fig.13 A system solution flow chart of a transformer resistance parameter online monitoring system based on winding temperature change provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0065] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0066] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0067] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor is it an embodiment that is mutually exclusive with other embodiments, either individually or selectively.

[0068] The present invention is described in detail with reference to schematic diagrams. When describing the embodiments of the present invention, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0069] At the same time, in the description of the present invention, it should be noted that the directions or positional relationships indicated by the terms "upper, lower, inner and outer" are based on the directions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as limiting the present invention. In addition, the terms "first, second or third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0070] In the present invention, unless otherwise clearly specified and limited, the terms "install, connect, connect" should be understood in a broad sense, for example: it can be a fixed connection, a detachable connection or an integral connection; it can also be a mechanical connection, an electrical connection or a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0071] Example 1, reference Figure 1-Figure 5 , which is the first embodiment of the present invention, provides an online monitoring method for transformer resistance parameters based on winding temperature change, comprising:

[0072] S1: Use the oil temperature sensor to measure the transformer oil temperature, set the temperature sampling point at the transformer oil baffle, establish a 1:1 simulation model, and obtain the relationship between the initial winding temperature distribution and the winding height.

[0073] Furthermore, an oil temperature sensor is installed in the transformer oil area corresponding to the oil baffle position of the transformer. The sensor type is a thermocouple high-precision temperature sensor, and the temperature data is recorded in real time through the data acquisition system, including measuring the transformer top oil temperature, oil tank inlet oil temperature, and radiator outlet oil temperature.

[0074] The 1:1 simulation model establishment includes using 3D modeling software SolidWorks to draw 1:1 scale three-dimensional models of the transformer heat sink and windings of each voltage level, ensuring that the model details are accurate for the accuracy of subsequent calculations.

[0075] Finite element analysis software COMSOL is used to mesh the 3D model. The density of meshing should be adjusted according to actual needs to ensure that there is enough mesh density in key areas to obtain accurate temperature field distribution data. Generate meshes for fluid and solid domains, and perform mesh quality checks to ensure that the mesh quality meets the calculation requirements.

[0076] It should be noted that the 3D model is imported into the simulation software, and the operating parameters of the transformer are set. After rated operation, the load is changed and the temperature change is recorded. According to the recording results, the relationship function between the initial winding temperature and the winding height at the transformer oil baffle position is extracted through the fluid-temperature field coupling model:

[0077]

[0078] Where T(z) is the temperature distribution function at the winding height z, I is the total number of meshes, i is the mesh number index, and ρ i is the density function of the ith grid, ΔV i is the volume of the i-th grid, Q i is the heat flux density of the ith grid, Q total is the total heat flux density of the entire winding, T i is the center temperature of the ith grid, T Ref is the reference temperature, is the variance of the temperature distribution of the ith grid, is the variance of the time-varying temperature distribution, μ t is the time average temperature, and t is the time variable.

[0079] S2: Perform a layered and regionalized analysis on the temperature distribution of the windings. By fitting the curves, the relationship between the winding temperature distribution and the winding height in all regions is obtained. The temperature coefficient of the winding is obtained according to the material properties and the resistance parameters that vary with temperature are calculated.

[0080] Furthermore, the winding temperature distribution is obtained according to the T(z) values ​​at different heights. The winding is layered into z'1, z'2, z'3 and z'4 according to the position of the oil baffle. All temperature data ∑T(z) values ​​of each layer are fitted by layered curves. According to the layers z'1, z'2, z'3 and z'4, regional fitting is performed. The relationship between the fitted temperature and the winding height is obtained as follows:

[0081]

[0082] in, as well as is the average winding temperature value after fitting in the area divided by the oil baffle position, is the average winding height of each layer, a 0 , …, a 8 is the fitting parameter, a 0 =361.01, a 1 =0.01124, a 2 =361.23, a 3 =0.0091, a 4 =361.38, a 5 =0.0084, a 6 =345.47, a 7 =0.086, a 8 =-0.0000958.

[0083] The average value of the winding temperature change The winding resistance is calculated as:

[0084]

[0085] Among them, R 0 is the resistance before temperature change, R 1 is the resistance after temperature change, and are the average winding temperature values ​​at the corresponding time before and after the temperature change, respectively, and α is the temperature coefficient of the winding.

[0086] Obtain the temperature coefficient α of the winding based on the material properties:

[0087]

[0088] Among them, z min For z 1 、z 2 、z 3 and z 4 The minimum height of each winding layer area, z max For z 1 、z 2、z 3 and z 4 The maximum height of each winding layer area, J is the number of winding layers, j is the current layer index, Γ(j) is the gamma function for normalization, is the derivative of the winding temperature with height, z'j is the height of the j-th winding, a is the fitting parameter describing the non-uniformity of temperature distribution, is the derivative of the winding resistance with temperature, R Ref is the resistance of the winding at the reference temperature.

[0089] According to the temperature change result, the resistance parameter of the winding resistance is updated.

[0090] It should be noted that when the temperature changes slowly, that is, the temperature does not change by more than 1 degree Celsius within an hour, and the sampling period of each round is at the ms level, the oil temperature value at the start of each round of sampling is used to calculate the average winding temperature, and then the formula for the winding resistance value calculated from the average winding temperature is:

[0091] R 1 (T r1 2) = R 1 (T r1 1)[1+α(T r1 2-T r1 1)]

[0092] R 2 (T r2 2) = R 2 (T r2 1)[1+α(T r2 2-T r2 1)]

[0093] Among them, T r1 1 and T r2 1 represents t 1 The average temperature of the primary and secondary windings at the moment, T r1 2 and T r2 2 respectively represent t 2 The average temperature of the primary and secondary windings at that moment.

[0094] S3: According to the oil temperature at the corresponding position of the sampling point, the winding temperature in the area where the oil baffle is located is calculated after temperature gradient correction, the average winding temperature is calculated by fitting the curve and the resistance parameter that changes with temperature is updated.

[0095] Furthermore, when the temperature changes rapidly, that is, the temperature changes by more than 1 degree Celsius within an hour, the temperature gradient correction value G m (z n ) Update the winding temperature T'(z) in the area where the oil baffle is located:

[0096]

[0097] Among them, G m (z n ) is the mth sampling point at height z n The temperature gradient correction value at , M is the number of sampling points considered, w m is the weight factor of the mth sampling point, z n,m is the height of the mth sampling point, δ z,m is the height range affected by the temperature gradient considered at the mth sampling point, is the temperature gradient at the mth sampling point varying with height z', t m is the time point of the mth sampling point, β is a temperature gradient influencing factor greater than zero, which adjusts the sensitivity of the correction value.

[0098] Update the relationship function between the initial winding temperature and the winding height to T'(z):

[0099]

[0100] Where T'(z) is the corrected temperature of the winding at height z, Γ(w) is the weight factor in the gamma function processing integral, ΔT is the temperature variation range, μ i is the average temperature distribution of the ith grid, T is the temperature variable, γ is the order of integration, z n is the height of the nth sampling point.

[0101] After updating T'(z), re-perform layered curve fitting to obtain the new average winding temperature in each area as well as And calculate the average winding temperature:

[0102]

[0103] The winding resistance is calculated by the winding temperature change:

[0104]

[0105] Among them, R' 0 To update the resistance before the temperature change, R' 1 To update the resistance after temperature change, and They are the average temperature values ​​of the winding at the corresponding time before and after the temperature change, respectively.

[0106] The formula for online detection of winding deformation uses the resistance parameter as the key input of the formula. The T-type equivalent circuit of the transformer is established. The transformer phasor equation is listed based on the T-type equivalent circuit. At the same time, the relationship between each input signal of the transformer and the winding parameters is established. The transformer phasor equation is:

[0107]

[0108] Transform the established T-type equivalent circuit phasor equation into the standard form of least squares:

[0109]

[0110] Among them, k is the transformer ratio, and the resistance parameter r 1 、r 2 As the identification inductance L 1 , L 2 The key input quantity.

[0111] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

[0112] Example 2, reference Figure 6-Figure 12 An embodiment of the present invention provides an online monitoring method for transformer resistance parameters based on winding temperature changes. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through experiments.

[0113] A S11-MR-400 / 10 three-phase distribution transformer was taken as the research object. According to the actual parameters of the transformer, the 2D and 3D finite element models of the transformer were built using COMSOL finite element software. The 3D model of the transformer is shown in Figure 2. Figure 6 As shown, the transformer 2D model is as follows Figure 7 As shown. The transformer winding inductance parameters and overall temperature distribution are calculated under 2D and 3D finite element models respectively, and compared with the experimental values. Finally, a modeling method that is simple to operate, easy to implement, and more suitable for practical engineering applications is selected to solve the winding parameters and analyze the changing trends of the winding parameters under different operating conditions for subsequent analysis.

[0114] Whether it is 2D modeling or 3D modeling, establishing a reasonable model based on the full simulation of the actual structure of the transformer is conducive to improving the probability of smooth segmentation of the model structure and making the segmentation unit shape more regular. Whether the mesh segmentation shape is regular is related to whether the structural model can be solved smoothly, and it plays an important role in the calculation speed and accuracy. In order to ensure the regularity of the mesh segmentation shape of each part of the transformer model and improve the accuracy of the entire model solution, the model is selected for intelligent segmentation. Multi-physics field coupling modeling is performed on the transformer, and the geometric model after mesh segmentation is as follows Figure 8 shown.

[0115] Table 1 Statistics of grid parameters

[0116]

[0117] The quality of mesh cells is a key factor in measuring mesh performance. The optimal value is 1. If the cell quality is too low, the solution will not achieve the desired accuracy. Figure 8 It can be seen from Table 1 that the average unit quality of the grids divided in this paper is much higher than 0.5.

[0118] Since the volume of the stays and washers is almost negligible, their resistance to the horizontal and vertical oil channels is almost negligible, so their negative impact on the winding operating temperature and oil flow is also very small. Therefore, in the subsequent calculation results, a simple mode should be used to ignore the negative impact of the stays and washers on the operating temperature. The three-dimensional model and two-dimensional axisymmetric model of the oil-immersed transformer were constructed: (1) For the three-dimensional model, the geometric parts such as the oil tank, transformer oil, core, winding, and oil flow inlet and outlet are established, and the oil channels between the coils and coils are merged into a piece of copper material. (2) For the two-dimensional axisymmetric model, structural parts such as washers, pressure plates, stays, etc. are not considered. The model mainly includes transformer oil, core, winding, but takes into account the oil channels between each coil and coil. (3) The volume reference temperature of fluids and solids is the current ambient temperature.

[0119] When the oil-immersed transformer is in normal operation, the core and winding will consume energy, which will be converted into heat, thereby increasing the temperature inside the transformer. This heat energy is mainly composed of core loss and winding loss, and Maxwell's equations can be used to calculate the internal loss of the oil-immersed transformer.

[0120] The main forms of heat dissipation in oil-immersed transformers are: (1) Heat conduction: The heat generated by winding loss and core loss will be transferred to the outer surface due to heat conduction. Heat conduction often occurs between solids; (2) Thermal convection: Whenever a fluid passes through the heating windings and core in the transformer, a convection heat transfer phenomenon will occur. The fluid will take away some of the heat from the solid, thereby reducing the temperature of the solid. (3) Thermal radiation: As long as there is a temperature difference between objects, thermal radiation will be generated. The influence of thermal radiation is often ignored in the temperature simulation calculation of transformer windings, but thermal radiation is an inherent property of all objects. All objects in nature are constantly emitting electromagnetic waves to the surroundings. When electromagnetic waves pass through objects, their wavelengths will change, resulting in different effects, some of which can significantly increase the temperature of the object.

[0121] Fluid field settings of simulation software, fluid field refers to the distribution and movement of fluid in space. In order to calculate the fluid field, some regulations are given, which are called boundary conditions. Boundary conditions are information such as the velocity and pressure of the fluid at the edge. Without boundary conditions, the specific situation of the fluid field cannot be determined. The oil flow properties of transformer oil belong to incompressible Newtonian fluids. The commonly used boundary conditions are no-slip wall boundaries: it means that the velocity of the fluid on the solid surface is zero. This boundary condition is suitable for viscous fluids, that is, there is no relative motion between the fluid and the solid.

[0122] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

[0123] Embodiment 3, the third embodiment of the present invention, is different from the first two embodiments in that:

[0124] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the 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, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, and other media that can store program codes.

[0125] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0126] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0127] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0128] Example 4, reference Fig.13 , which is the fourth embodiment of the present invention, provides an online monitoring system for transformer resistance parameters based on winding temperature changes, including a data acquisition and processing module, a temperature distribution analysis and resistance calculation module, and a resistance parameter online monitoring and update module.

[0129] The data acquisition and processing module is responsible for collecting the temperature data and related parameters of the transformer, ensuring the accuracy of the data through high-precision measuring equipment, and pre-processing the collected data for use in subsequent modules.

[0130] The temperature distribution analysis and resistance calculation module uses the collected data and the established 1:1 simulation model to analyze the temperature distribution of the transformer winding and calculate the average temperature of the winding. The simulation software is used to perform fluid-temperature field coupling analysis, obtain the relationship between the winding temperature distribution and the height, and perform curve fitting. According to the temperature coefficient and material properties of the winding, the resistance parameters that change with temperature are calculated.

[0131] The online monitoring and updating module of the resistance parameter adjusts the calculation of the resistance value according to the temperature change. When the temperature changes slowly, the oil temperature value at the start of each round of sampling is used to calculate the average winding temperature, and then the winding resistance value is calculated from the average winding temperature. When the temperature changes rapidly, the winding temperature is updated by the temperature gradient correction value, and the resistance value is recalculated. According to the T-type equivalent circuit and the transformer phasor equation, the resistance parameters are updated and used to identify the key parameters of inductance and capacitance.

[0132] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A transformer resistance parameter online monitoring method based on winding temperature change, characterized in that: include, The oil temperature of the transformer is measured using an oil temperature sensor, a temperature sampling point is set at the oil baffle of the transformer, a 1:1 simulation model is established, and the relationship between the initial winding temperature distribution and the winding height is obtained; Conduct layered and regional analysis on the temperature distribution of the windings, and use curve fitting to find the relationship between the winding temperature distribution and the winding height in all regions. Obtain the temperature coefficient of the windings based on the material properties and calculate the resistance parameters that vary with temperature. According to the oil temperature at the corresponding position of the sampling point, the winding temperature in the area where the oil baffle is located is calculated after temperature gradient correction. The average winding temperature is calculated by fitting the curve and the resistance parameter that changes with temperature is updated.

2. The method for online monitoring of transformer resistance parameters based on winding temperature change according to claim 1, characterized in that: The transformer oil temperature measurement includes selecting a thermocouple high-precision temperature sensor to measure the transformer top oil temperature, the oil tank inlet oil temperature, and the radiator outlet oil temperature; The establishment of the 1:1 simulation model includes using 3D modeling software SolidWorks to draw 1:1 scale three-dimensional models of the transformer radiator and windings of each voltage level, using finite element analysis software COMSOL to mesh the 3D model, generate fluid domain meshes and solid domain meshes, and perform mesh quality inspection.

3. The method for online monitoring of transformer resistance parameters based on winding temperature change according to claim 2, characterized in that: The method of obtaining the relationship between the winding temperature distribution and the winding height includes importing a 3D model into the simulation software, setting the operating parameters of the transformer, changing the load after rated operation, recording the temperature change, and extracting the relationship function between the initial winding temperature at the transformer oil baffle position and the winding height through a fluid-temperature field coupling model according to the recording results: Where T(z) is the temperature distribution function at the winding height z, I is the total number of meshes, i is the mesh number index, and ρ i is the density function of the ith grid, ΔV i is the volume of the i-th grid, Q i is the heat flux density of the ith grid, Q total is the total heat flux density of the entire winding, T i is the center temperature of the ith grid, T Ref is the reference temperature, is the variance of the temperature distribution of the ith grid, is the variance of the time-varying temperature distribution, μ t is the time average temperature, and t is the time variable.

4. The method for online monitoring of transformer resistance parameters based on winding temperature change according to claim 3, characterized in that: The layered regional analysis includes obtaining the winding temperature distribution according to the T(z) values ​​at different heights, dividing the winding into layers z'1, z'2, z'3 and z'4 according to the position of the oil baffle, performing layered curve fitting on all the temperature data ∑T(z) values ​​of each layer, performing regional fitting according to the layers z'1, z'2, z'3 and z'4, and obtaining the relationship between the fitted temperature and the winding height as follows: in, as well as is the average winding temperature value after fitting in the area divided by the oil baffle position, is the average winding height of each layer, a0, ..., a8 are fitting parameters, a0 = 361.01, a1 = 0.01124, a2 = 361.23, a3 = 0.0091, a4 = 361.38, a5 = 0.0084, a6 = 345.47, a7 = 0.086, a8 = -0.0000958; The average value of the winding temperature change The winding resistance is calculated as: Among them, R0 is the resistance before temperature change, R1 is the resistance after temperature change, and are the average winding temperature values ​​at the corresponding time before and after the temperature change, respectively, and α is the temperature coefficient of the winding; Obtain the temperature coefficient α of the winding based on the material properties: Among them, z min is the minimum height of each winding layer area of ​​z1, z2, z3 and z4, max is the maximum height of each winding layer area of ​​z1, z2, z3 and z4, J is the number of winding layers, j is the current layer index, Γ(j) is the gamma function for normalization, is the derivative of the winding temperature with height, z'j is the height of the j-th winding, a is the fitting parameter describing the non-uniformity of temperature distribution, is the derivative of the winding resistance with temperature, R Ref is the resistance of the winding at the reference temperature; According to the temperature change result, the resistance parameter of the winding resistance is updated.

5. The method for online monitoring of transformer resistance parameters based on winding temperature change according to claim 4, characterized in that: The resistance parameter for updating the winding resistance includes: when the temperature changes slowly, that is, the temperature does not change by more than 1 degree Celsius within an hour, each round of sampling cycle is at the ms level, and the oil temperature value at the start time of each round of sampling is used to calculate the average winding temperature, and then the formula for the winding resistance value calculated from the average winding temperature is: R1(T r1 2)=R1(T r1 1)[1+α(T r1 2-T r1 1)] R2(T r2 2)=R2(T r2 1)[1+α(T r2 2-T r2 1)] Among them, T r1 1 and T r2 1 represents the average temperature of the primary and secondary windings at time t1, T r1 2 and T r2 2 represent the average temperatures of the primary and secondary windings at time t2 respectively.

6. The method for online monitoring of transformer resistance parameters based on winding temperature change according to claim 5, characterized in that: The temperature gradient correction includes: when the temperature changes rapidly, that is, the temperature changes by more than 1 degree Celsius within an hour, the temperature gradient correction value G m (z n ) Update the winding temperature T'(z) in the area where the oil baffle is located: Among them, G m (z n ) is the mth sampling point at height z n The temperature gradient correction value at , M is the number of sampling points considered, w m is the weight factor of the mth sampling point, z n,m is the height of the mth sampling point, δ z,m is the height range affected by the temperature gradient considered at the mth sampling point, is the temperature gradient at the mth sampling point varying with height z', t m is the time point of the mth sampling point, β is a temperature gradient influencing factor greater than zero, which adjusts the sensitivity of the correction value; Update the relationship function between the initial winding temperature and the winding height to T'(z): Where T'(z) is the corrected temperature of the winding at height z, Γ(w) is the weight factor in the gamma function processing integral, ΔT is the temperature variation range, μ i is the average temperature distribution of the ith grid, T is the temperature variable, γ is the order of integration, z n is the height of the nth sampling point; After updating T'(z), re-perform layered curve fitting to obtain the new average winding temperature in each area as well as And calculate the average winding temperature: The winding resistance is calculated by the winding temperature change: Where R'0 is the resistance before the updated temperature change, and R'1 is the resistance after the updated temperature change. and They are the average temperature values ​​of the winding at the corresponding time before and after the temperature change, respectively.

7. The method for online monitoring of transformer resistance parameters based on winding temperature change according to claim 6, characterized in that: The resistance parameter for updating the winding resistance also includes a formula for online detection of winding deformation, the resistance parameter is a key input quantity of the formula, a T-type equivalent circuit of the transformer is established, the transformer phasor equation is listed according to the T-type equivalent circuit, and the relationship between each input signal of the transformer and the winding parameters is established. The transformer phasor equation is: Transform the established T-type equivalent circuit phasor equation into the standard form of least squares: Among them, k is the transformer ratio, and the resistance parameters r1 and r2 are used as the key input quantities for identifying the inductors L1 and L2.

8. A system using the transformer resistance parameter online monitoring method based on winding temperature change as claimed in any one of claims 1 to 7, characterized in that: It includes data acquisition and processing module, temperature distribution analysis and resistance calculation module, and resistance parameter online monitoring and update module; The data acquisition and processing module is responsible for collecting the temperature data and related parameters of the transformer, ensuring the accuracy of the data through high-precision measuring equipment, and pre-processing the collected data for use in subsequent modules; The temperature distribution analysis and resistance calculation module uses the collected data in combination with the established 1:1 simulation model to analyze the temperature distribution of the transformer winding and calculate the average temperature of the winding. The simulation software performs fluid-temperature field coupling analysis to obtain the relationship between the winding temperature distribution and the height, and performs curve fitting. According to the temperature coefficient and material properties of the winding, the resistance parameter that changes with temperature is calculated; The resistance parameter online monitoring and updating module adjusts the calculation of the resistance value according to the temperature change. When the temperature changes slowly, the oil temperature value at the start time of each sampling round is used to calculate the average winding temperature, and then the winding resistance value is calculated from the average winding temperature; when the temperature changes rapidly, the winding temperature is updated by the temperature gradient correction value, and the resistance value is recalculated. According to the T-type equivalent circuit and the transformer phasor equation, the resistance parameter is updated and used to identify the key parameters of the inductance and capacitance.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method for online monitoring of transformer resistance parameters based on winding temperature changes described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for online monitoring of transformer resistance parameters based on winding temperature changes according to any one of claims 1 to 7 are implemented.

Images