Relevance regulation and control influence simulation method for dry-type transformer

Abstract

The invention discloses a relevance regulation and control influence simulation method for a dry-type transformer, and relates to the technical field of transformer testing, target components are determined according to components of the dry-type transformer, and a corresponding analog simulation structure is constructed; acquiring a hardware parameter item and an operation parameter item related to each target component, and associating the hardware parameter item and the operation parameter item with the corresponding target component in the analog simulation structure; acquiring real-time operation data of each target component in the operation process of the transformer, and determining hardware relevance among the target components and parameter relevance among the parameter items based on the real-time operation data; and importing the determined hardware relevance and parameter relevance into an analog simulation structure for simulation, and determining a parameter surge point of each target component, so that the transformer can better control the operation data of the transformer in the actual operation process, and the service life of the transformer is further prolonged.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of transformer testing, in particular to a correlation regulation influence simulation method for dry-type transformers. BACKGROUND

[0002] As a key equipment in power systems, dry-type transformers are widely used in high-rise buildings, airports, subways and other places with high fire prevention requirements. The operation performance of dry-type transformers is influenced by the correlation of various factors, and the correlation regulation influence simulation is of great significance. With the development of smart grids, the demand for accurate regulation of dry-type transformers is increasing, but there is a lack of effective correlation regulation influence simulation method, making it difficult to fully grasp the coupling mechanism of various factors under different working conditions and to achieve accurate regulation.

[0003] Under different operating parameters, the temperature of the components will change differently, and abnormal component temperature will affect the operation performance of the equipment. How to find the parameter critical point that causes abnormal temperature change through simulation by analyzing the influence of operating parameters on temperature, so as to measure the adaptive operating parameters of each component in the transformer, avoid running the transformer under abnormal parameters in advance, and thus improve the service life of the transformer, is the problem we need to solve. Therefore, the present application provides a correlation regulation influence simulation method for dry-type transformers. SUMMARY

[0004] The present application relates to the technical field of transformer testing, in particular to a correlation regulation influence simulation method for dry-type transformers.

[0005] The present application relates to the technical field of transformer testing, in particular to a correlation regulation influence simulation method for dry-type transformers.

[0006] Determine the target components of the dry-type transformer, and construct the corresponding simulation structure;

[0007] Obtain the hardware parameter items and operating parameter items involved in each target component, and associate them with the corresponding target components in the simulation structure;

[0008] Collect real-time operating data of each target component during the operation of the transformer, and determine the hardware correlation between each target component and the parameter correlation between each parameter item based on the real-time operating data;

[0009] Import the determined hardware correlation and parameter correlation into the simulation structure for simulation to determine the parameter critical point of each target component.

[0010] Further, obtain each component of the dry-type transformer, and select the components to be simulated as target components according to the needs;

[0011] According to each target component in the simulation software to create a corresponding simulation structure, and according to the circuit connection relationship of each target component, the simulation structure is connected correspondingly, and the simulation simulation structure of the dry-type transformer is obtained.

[0012] Further, the hardware parameter item includes an electrical parameter item and a temperature parameter item, the electrical parameter item includes: rated voltage, rated current, no-load loss and load loss; the temperature parameter item includes: winding hot spot temperature;

[0013] The running parameter item includes input voltage, input current, output voltage, output current and hardware temperature.

[0014] Further, the real-time running data includes input voltage, input current, output voltage, output current and temperature;

[0015] For each target component, a corresponding time coordinate system is constructed, and corresponding data change curves, i.e., input voltage change curve, input current change curve, output voltage change curve, output current change curve and temperature change curve, are generated in the time coordinate system according to the obtained real-time running data.

[0016] Further, the process of determining the hardware correlation between each target component based on the real-time running data includes:

[0017] Any target component is taken as a reference component, and other target components having a direct circuit connection relationship with the reference component are marked;

[0018] If the marked target component is connected to the input end of the reference component, the target component is recorded as an upper component, and if it is connected to the output end of the reference component, the target component is recorded as a lower component;

[0019] According to the circuit connection relationship between the upper component, the lower component and the reference component, the hardware correlation between the upper component, the lower component and the reference component is determined, and the corresponding hardware correlation coefficient is obtained; when the circuit connection relationship is a parallel relationship, the hardware correlation is parallel hardware, and when the circuit connection relationship is a series relationship, the hardware correlation is series hardware.

[0020] Further, the process of parameter correlation between each parameter item includes:

[0021] According to the input voltage change curve, the input current change curve, the output voltage change curve, the output current change curve and the temperature change curve of the reference component;

[0022] A plurality of sampling points are randomly generated on the time coordinate system abscissa, and the input voltage, input current, output voltage, output current and temperature corresponding to each sampling point are obtained;

[0023] By comparing the adjacent sampling points with each other, a plurality of sets of input voltage difference values, input current difference values, output voltage difference values, output current difference values and temperature change values are obtained, and a corresponding sampling parameter change set is obtained by summarizing;

[0024] According to the input voltage difference values, input current difference values, output voltage difference values, output current difference values k and temperature change values in the sampling parameter change set;

[0025] The input voltage-temperature correlation coefficient, the input current-temperature correlation coefficient, the output voltage-temperature correlation coefficient and the output current-temperature correlation coefficient are obtained respectively.

[0026] Further, the determined hardware correlation and parameter correlation are introduced into the simulation structure for simulation, and the process of determining the parameter critical point of each target component is as follows:

[0027] The corresponding simulation data set of the dry-type transformer is generated, and the simulation data set includes simulation input voltage, simulation input current, simulation output voltage and simulation output current;

[0028] According to the simulation data set, the simulation structure is simulated to obtain a simulation data set of each target component, and the simulation data set includes simulation input voltage, simulation input current, simulation output voltage and simulation output current;

[0029] According to the simulation data set and the corresponding correlation coefficient, the corresponding simulation temperature is obtained, that is, the simulation input voltage, the simulation input current, the simulation output voltage and the simulation output current and the corresponding correlation coefficient respectively obtain the corresponding simulation temperature, and the corresponding simulation temperature change curve is generated;

[0030] The obtained simulation temperature is compared with the corresponding winding hot spot temperature;

[0031] When the simulation temperature reaches the winding hot spot temperature, the simulation is paused, the slope of each position of the generated simulation temperature change curve is obtained, and the position of the maximum slope is recorded as the first parameter critical point;

[0032] After the first parameter critical point is obtained, the simulation is continued, when any one of the simulation input voltage, the simulation input current, the simulation output voltage and the simulation output current reaches the corresponding rated voltage and rated current, the simulation is stopped, and the simulation temperature change curve of each position from when the simulation temperature reaches the winding hot spot temperature to when the simulation is stopped is obtained, and the corresponding position is recorded as the second parameter critical point.

[0033] Compared with the prior art, the beneficial effects of the present application are:

[0034] The real-time operation data of each target component in the dry-type transformer is acquired, the hardware correlation between the target components and the parameter correlation between the parameter items are obtained according to the acquired real-time operation data, so that the simulation of the simulation structure is supported, the simulation data generated by the dry-type transformer under the simulation data set is obtained, and the parameter excitation point of each target component is obtained, so that the operation data of the transformer in the actual operation process is better controlled, and the service life of the transformer is prolonged. BRIEF DESCRIPTION OF DRAWINGS

[0035] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed in the embodiments will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments described in the present application, and other drawings can also be obtained by those skilled in the art according to these drawings.

[0036] Figure 1 Flowchart of the present application. DETAILED DESCRIPTION

[0037] As shown in the figure, the correlation regulation and control simulation method of the dry-type transformer comprises: Figure 1

[0038] Determine the target components according to the components of the dry-type transformer, and construct the corresponding simulation simulation structure;

[0039] Acquire the hardware parameter items and operation parameter items related to each target component, and associate them with the corresponding target components in the simulation simulation structure;

[0040] Collect the real-time operation data of each target component in the operation process of the transformer, and determine the hardware correlation between each target component and the parameter correlation between each parameter item based on the real-time operation data;

[0041] Import the determined hardware correlation and parameter correlation into the simulation simulation structure for simulation, and determine the parameter excitation point of each target component.

[0042] It should be further pointed out that in the specific implementation process, each component of the dry-type transformer is acquired, and the component to be simulated is selected as the target component according to the need;

[0043] According to each target component, the corresponding simulation structure is created in the simulation software, and the simulation structure is connected according to the circuit connection relationship of each target component, so that the simulation simulation structure of the dry-type transformer is obtained; it should be pointed out that the simulation software usually adopts ANSYS software, and other simulation software can also be selected according to actual needs. ​

[0044] It needs to be further explained that, in the specific implementation process, the process of obtaining the parameter items involved in each target component and associating them with the corresponding simulation structure in the simulation simulation structure includes:

[0045] Creating a corresponding parameter item for each target component corresponding to the simulation structure; wherein the hardware parameter item includes an electrical parameter item and a temperature parameter item, the electrical parameter item includes: rated voltage, rated current, no-load loss and load loss; the temperature parameter item includes: winding hot spot temperature;

[0046] The operating parameter item includes input voltage, input current, output voltage, output current and hardware temperature;

[0047] The set operating parameter item and hardware parameter item are associated with the corresponding simulation structure in the simulation simulation structure to form a parameter item set corresponding to each simulation structure.

[0048] It needs to be further explained that, in the specific implementation process, the process of collecting real-time operating data of each target component during transformer operation includes:

[0049] Each target component in the transformer is installed with a corresponding data acquisition terminal, and the real-time operating data of each target component is obtained in real time through the data acquisition terminal;

[0050] The real-time operating data includes input voltage, input current, output voltage, output current and temperature;

[0051] A corresponding time coordinate system is constructed for each target component, and a corresponding data change curve, i.e. input voltage change curve, input current change curve, output voltage change curve, output current change curve and temperature change curve, is generated in the time coordinate system according to the obtained real-time operating data.

[0052] It needs to be further explained that, in the specific implementation process, the process of determining the hardware correlation between each target component based on the real-time operating data includes:

[0053] Any target component is taken as a reference component, and other target components having a direct circuit connection relationship with the reference component are marked;

[0054] If the marked target component is connected to the input end of the reference component, the target component is recorded as an upper component, and if it is connected to the output end of the reference component, the target component is recorded as a lower component;

[0055] According to the circuit connection relationship among the upper-level component, the lower-level component and the reference component, the hardware correlation among the upper-level component, the lower-level component and the reference component is determined, and the corresponding hardware correlation coefficient is obtained; it should be noted that the circuit connection relationship includes parallel relationship and series relationship, when the circuit connection relationship is parallel relationship, the hardware correlation is parallel hardware, and when the circuit connection relationship is series relationship, the hardware correlation is series hardware.

[0056] It should be further explained that, in the specific implementation process, when the hardware correlation between the reference component and the corresponding upper-level component is parallel hardware:

[0057] Each upper-level component with the hardware correlation of parallel hardware is labeled and recorded as i, wherein i = 1, 2, …, n;

[0058] The output current corresponding to the upper-level component labeled i is recorded as S i coui ;

[0059] The hardware correlation coefficient between the reference component and the upper-level component labeled i is recorded as Y SG i , wherein:

[0060] Y SG i = S i coui / (S i cou1 + S i cou2 + S i cou3 + … + S i coun );

[0061] On the other hand, when the hardware correlation between the reference component and the corresponding upper-level component is series hardware, the hardware correlation coefficient is 1;

[0062] Similarly, the lower-level component with the hardware correlation of parallel hardware is labeled and recorded as j, wherein j = 1, 2, …, m;

[0063] The input current corresponding to the lower-level component labeled j is recorded as S i cinj ;

[0064] The hardware correlation coefficient between the reference component and the lower-level component labeled j is recorded as Y XG j , wherein:

[0065] Y XG j = S i cinj / (S i cin1 + S i cin2 + S i cin3 + … + S i cinn );

[0066] On the other hand, when the hardware correlation of the reference component and the corresponding lower-level component is series hardware, the hardware correlation coefficient is 1.

[0067] It should be further explained that, in the specific implementation process, the process of parameter correlation between various parameter items includes:

[0068] According to the input voltage variation curve, the input current variation curve, the output voltage variation curve, the output current variation curve, and the temperature variation curve of the reference component;

[0069] Randomly generating a plurality of sampling points on the time coordinate system abscissa, and obtaining the input voltage, input current, output voltage, output current, and temperature corresponding to each sampling point;

[0070] Comparing adjacent sampling points with each other to obtain a plurality of groups of input voltage difference values, input current difference values, output voltage difference values, output current difference values, and temperature variation values, and collecting to obtain the corresponding sampling parameter variation set;

[0071] Labeling each sampling parameter variation set, denoted as k, where k = 1, 2, …, s;

[0072] The input voltage difference value in the sampling parameter variation set with label k is denoted as Us k , the input current difference value Is k , the output voltage difference value Ur k , the output current difference value Ir k , and the temperature variation value W k .

[0073] The input voltage-temperature correlation coefficient C(Us k , W k ), the input current-temperature correlation coefficient C(Is k , W k ), the output voltage-temperature correlation coefficient C(Ur k , W k ), and the output current-temperature correlation coefficient C(Ir k , W k ) are obtained, respectively, where:

[0074]

[0075] wherein, is the mean value of the input voltage difference value, is the mean value of the input current difference value, is the mean value of the output voltage difference value, is the mean value of the output current difference value, is the mean value of the temperature variation value.

[0076] It needs to be further explained that in the specific implementation process, the determined hardware correlation and parameter correlation are introduced into the simulation simulation structure for simulation to determine the parameter critical point of each target component, and the specific process is:

[0077] The corresponding simulation data set is generated for the dry-type transformer, and the simulation data set includes simulation input voltage, simulation input current, simulation output voltage, and simulation output current.

[0078] According to the simulation data set, the simulation simulation structure is simulated to obtain the simulation data set of each target component, and the simulation data set includes simulation input voltage, simulation input current, simulation output voltage, and simulation output current.

[0079] According to the simulation data set and the corresponding correlation coefficient, the corresponding simulation temperature is obtained, that is, the simulation input voltage, simulation input current, simulation output voltage, and simulation output current and the corresponding correlation coefficient respectively obtain the corresponding simulation temperature, and the maximum value of the obtained simulation temperature is taken as the final simulation temperature, and the corresponding simulation temperature change curve is generated,

[0080] It needs to be noted that after the hardware correlation and parameter correlation are introduced into the simulation simulation structure in the ANSYS software, the simulation data set is generated, and the simulation input voltage and simulation input current in the simulation data set are continuous data, then the obtained simulation output voltage, simulation output current, and temperature are also continuous data.

[0081] The obtained simulation temperature is compared with the corresponding winding hot spot temperature.

[0082] When the simulation temperature reaches the winding hot spot temperature, the simulation is paused, the slope of each position of the generated simulation temperature change curve is obtained, and the position of the maximum slope is recorded as the first parameter critical point, and the simulation input voltage, simulation input current, simulation output voltage, and simulation output current corresponding to the first parameter critical point are obtained.

[0083] After obtaining the first parameter critical point, the simulation is continued, when any parameter of the simulation input voltage, simulation input current, simulation output voltage, and simulation output current reaches the corresponding rated voltage and rated current, the simulation is stopped, and the slope of each position of the simulation temperature change curve from when the simulation temperature reaches the winding hot spot temperature to when the simulation is stopped is obtained, and the corresponding position is recorded as the second parameter critical point.

[0084] It needs to be noted that the first parameter critical point only has an impact on the target component itself, and the second parameter critical point also has an impact on other target components that exist in an upper and lower relationship with the target component, and the degree of influence depends on the corresponding hardware correlation.

[0085] The above merely describes the preferred embodiments of the present application, and is not intended to limit the present application in any form. Although the present application has been disclosed with the preferred embodiments as above, it is not intended to limit the present application. Any person skilled in the art can make some changes or modifications to the above disclosed technical content to make equivalent embodiments with equivalent changes, as long as the changes or modifications do not deviate from the technical solution of the present application. Any modification or equivalent replacement to the above embodiments based on the technical essence of the present application still falls within the scope of the technical solution of the present application.

Claims

1. A simulation method for the regulatory influence of the correlation of dry transformers, characterized in that, The application relates to a method for determining parameter critical points of target components in a dry-type transformer. The method comprises the following steps: determining target components according to constituent components of the dry-type transformer, and constructing a corresponding simulation structure; obtaining hardware parameter items and operation parameter items related to each target component, and associating the hardware parameter items and the operation parameter items with corresponding target components in the simulation structure; collecting real-time operation data of each target component during transformer operation, and determining hardware correlation between each target component and parameter correlation between each parameter item based on the real-time operation data; 2. The method of claim 1, wherein the method further comprises: introducing the determined hardware correlation and parameter correlation into the simulation structure for simulation, and determining parameter critical points of each target component. constituent components of the dry-type transformer are obtained, and target components to be simulated are selected according to requirements; 3. The method of claim 2, wherein the method further comprises: a corresponding simulation structure is created in simulation software according to each target component, and the simulation structure is connected according to circuit connection relationships of each target component, so that a simulation structure of the dry-type transformer is obtained. The hardware parameter items include electrical parameter items and temperature parameter items, the electrical parameter items include rated voltage, rated current, no-load loss and load loss, and the temperature parameter items include winding hot-spot temperature.

4. The method of claim 3, wherein the method further comprises: The operation parameter items include input voltage, input current, output voltage, output current and hardware temperature. The real-time operation data include input voltage, input current, output voltage, output current and temperature.

5. The method of claim 4, wherein the method further comprises: A corresponding time coordinate system is constructed for each target component, and corresponding data change curves, i.e. input voltage change curve, input current change curve, output voltage change curve, output current change curve and temperature change curve, are generated in the time coordinate system according to the obtained real-time operation data. The process of determining hardware correlation between each target component based on the real-time operation data comprises the following steps: any target component is taken as a reference component, and other target components having a direct circuit connection relationship with the reference component are marked; if the marked target component is connected with an input end of the reference component, the target component is taken as an upper component, and if the marked target component is connected with an output end of the reference component, the target component is taken as a lower component; 6. The method of claim 5, wherein the method further comprises: hardware correlation between the upper component, the lower component and the reference component is determined according to the circuit connection relationship between the upper component, the lower component and the reference component, and corresponding hardware correlation coefficients are obtained; when the circuit connection relationship is a parallel relationship, the hardware correlation is parallel hardware, and when the circuit connection relationship is a series relationship, the hardware correlation is series hardware. The process of determining parameter correlation between each parameter item comprises the following steps: according to the input voltage change curve, the input current change curve, the output voltage change curve, the output current change curve and the temperature change curve of the reference component; a plurality of sampling points are randomly generated on the horizontal coordinate of the time coordinate system, and input voltage, input current, output voltage, output current and temperature corresponding to each sampling point are obtained; the adjacent sampling points are compared with each other, a plurality of groups of input voltage difference, input current difference, output voltage difference, output current difference and temperature change value are obtained, and a corresponding sampling parameter change set is obtained by summarizing. According to the input voltage difference, the input current difference, the output voltage difference, the output current difference k, and the temperature change value in the input parameter change set; Obtain the input voltage-temperature correlation coefficient, the input current-temperature correlation coefficient, the output voltage-temperature correlation coefficient, and the output current-temperature correlation coefficient respectively.

7. The method of claim 6, wherein the method further comprises: The process of importing the determined hardware correlation and parameter correlation into the simulation structure for simulation to determine the parameter excitation point of each target component is: Generate a corresponding simulation data set for the dry-type transformer, wherein the simulation data set includes a simulation input voltage, a simulation input current, a simulation output voltage, and a simulation output current; Simulate the simulation structure according to the simulation data set to obtain a simulation data set of each target component, wherein the simulation data set includes a simulation input voltage, a simulation input current, a simulation output voltage, and a simulation output current; According to the simulation data set and the corresponding correlation coefficient, obtain the corresponding simulation temperature, that is, the simulation input voltage, the simulation input current, the simulation output voltage, and the simulation output current, and the corresponding correlation coefficient respectively obtain the corresponding simulation temperature, and generate a corresponding simulation temperature change curve; Compare the obtained simulation temperature with the corresponding winding hot spot temperature; When the simulation temperature reaches the winding hot spot temperature, pause the simulation, obtain the slope of each position of the generated simulation temperature change curve, and mark the position of the maximum slope as the first parameter excitation point; After obtaining the first parameter excitation point, continue the simulation, when any one of the simulation input voltage, the simulation input current, the simulation output voltage, and the simulation output current reaches the corresponding rated voltage and rated current, stop the simulation, and obtain the slope of each position of the simulation temperature change curve from when the simulation temperature reaches the winding hot spot temperature to when the simulation is stopped, and mark the corresponding position as the second parameter excitation point.

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