Voltage transformer error state evaluation method, device, equipment and medium

Abstract

The invention discloses a voltage transformer error state evaluation method, device and equipment and a medium, and relates to the technical field of electric power measurement monitoring, and the method comprises the steps: determining a target transformation ratio coefficient of each branch transformer based on the voltage information of a voltage transformer on a bus in a power distribution network in a target time period and the output power of each branch transformer; determining the line resistance of each branch transformer based on the target transformation ratio coefficient and the line unit resistance value, and constructing a line voltage drop model by using the line resistance; determining a transformer transformation ratio coefficient model according to the voltage information, the secondary voltage and the secondary load of each branch transformer, a line voltage drop model and an error back propagation network; and triggering a voltage transformer ratio error determination operation based on the transformer transformation ratio coefficient model, the line voltage drop model and the acquired to-be-processed secondary voltage of the voltage transformer, and obtaining an error state evaluation result by using a target transformer ratio error. According to the invention, the accuracy and reliability of error state evaluation of the voltage transformer can be effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of electric power metering and monitoring, and in particular to a method, device, equipment and medium for evaluating the error state of a voltage transformer. Background Art

[0002] In power systems, distribution transformers and voltage transformers are key components. However, voltage transformers are subject to numerous factors during use, such as installation environment and equipment aging. These factors can lead to errors in the voltage transformers. These errors not only affect the normal operation of the power system but can also cause grid instability and even lead to safety incidents.

[0003] To address these issues, current voltage transformer evaluation schemes use an improved GAT network (Graph Attention Network) to establish a training model linking transformer environmental parameters, low-voltage side load, and the actual transformer ratio. By calculating the transformer ratio, the transformer primary voltage is derived, thereby assessing the transformer's error state. However, since this scheme does not consider the voltage drop between the voltage transformer primary voltage and the transformer primary voltage, it can negatively impact the accuracy and reliability of the evaluation results. Summary of the Invention

[0004] In view of this, the purpose of the present invention is to provide a method, device, equipment and medium for evaluating the error state of a voltage transformer, which can effectively improve the accuracy and reliability of the error state evaluation of the voltage transformer. The specific scheme is as follows:

[0005] In a first aspect, the present application provides a method for evaluating a voltage transformer error state, comprising:

[0006] Determining a target transformation ratio coefficient of each branch transformer based on voltage information of a voltage transformer on a busbar in the distribution network within a target time period, output power of each branch transformer, and the law of conservation of energy;

[0007] Determining the line resistance corresponding to each branch transformer based on the target transformation ratio coefficient and the line unit resistance value, and constructing a line voltage drop model using the line resistance and the line current;

[0008] Perform transformer primary voltage fitting based on the voltage information, the secondary voltage and secondary load of each branch transformer, the line voltage drop model, and the error back propagation network to determine a transformer ratio coefficient model;

[0009] Based on the transformer ratio coefficient model, the line voltage drop model and the collected secondary voltage to be processed of the voltage transformer, a voltage transformer ratio difference determination operation is triggered, and the obtained target transformer ratio difference is used to perform voltage transformer error state evaluation to obtain an error state evaluation result.

[0010] Optionally, determining the target transformation ratio coefficient of each branch transformer based on voltage information of a voltage transformer on a busbar in the distribution network within a target time period, the output power of each branch transformer, and the law of conservation of energy includes:

[0011] Determine a corresponding bus output power based on a first rated transformation ratio and a secondary voltage corresponding to a voltage transformer on a bus in the distribution network, and a second rated transformation ratio and a secondary current corresponding to a current transformer on the bus within a target time period;

[0012] Determining the transformer output power corresponding to each branch transformer based on the secondary voltage, secondary current and power influence coefficient of each branch transformer on the bus within the target time period;

[0013] determining a line loss based on a line loss rate corresponding to the bus and an output power of the bus;

[0014] Determining the corresponding transformer loss power based on the transformer no-load loss, transformer short-circuit loss and transformer load rate corresponding to each branch transformer;

[0015] Determine a corresponding target power loss based on the bus output power, the line loss, the transformer output power corresponding to each branch transformer, the transformer power loss, and the law of conservation of energy;

[0016] A cluster analysis is performed on the target power loss and the bus output power, and the target transformation ratio coefficient of each branch transformer is determined using the cluster analysis results and a neural network algorithm.

[0017] Optionally, determining the line resistance corresponding to each branch transformer based on the target transformation ratio coefficient and the line unit resistance value includes:

[0018] Determining a corresponding line unit resistance value based on the target transformation ratio coefficient and line current corresponding to each branch transformer, and target distance information between each branch transformer and the switchgear station;

[0019] The line resistance corresponding to each of the branch transformers is determined based on the target distance information and the line unit resistance value.

[0020] Optionally, constructing a line voltage drop model using the line resistance and the line current includes:

[0021] A line voltage drop model is determined based on the law of conservation of energy, the line current corresponding to each branch transformer, the line resistance, and the transformer no-load loss.

[0022] Optionally, performing transformer primary voltage fitting using the voltage information, the secondary voltage and secondary load of each branch transformer, the line voltage drop model, and an error back propagation network includes:

[0023] Normalizing the first ambient temperature information, the target transformation ratio coefficient of any branch transformer, the secondary load, and the primary voltage, and inputting the normalized first ambient temperature information, the target transformation ratio coefficient, and the secondary load into a data processing layer configured before an error back propagation network to obtain a data processing result;

[0024] The data processing result is input into the error back propagation network to perform transformer primary voltage fitting, so as to determine the transformer ratio coefficient model based on the fitting result, the voltage information and the corresponding secondary voltage of the branch transformer.

[0025] Optionally, the triggering of a voltage transformer ratio difference determination operation based on the transformer ratio coefficient model, the line voltage drop model, and the collected to-be-processed secondary voltage of the voltage transformer includes:

[0026] Determining a corresponding target transformer primary voltage based on the transformer ratio coefficient model, the collected branch transformer secondary load and second ambient temperature information, and the corresponding target ratio coefficient;

[0027] Determining a target line voltage drop based on the line voltage drop model, and determining a target transformer primary voltage according to the target transformer primary voltage and the target line voltage drop;

[0028] A voltage transformer ratio difference determination operation is triggered by utilizing the target transformer primary voltage and the collected to-be-processed secondary voltage of the voltage transformer to obtain a target transformer ratio difference.

[0029] Optionally, performing voltage transformer error state evaluation using the obtained target transformer ratio difference to obtain an error state evaluation result includes:

[0030] The error state evaluation result is determined by comparing the target mutual inductor ratio difference with a first preset ratio difference threshold and a second preset ratio difference threshold; wherein the first preset ratio difference threshold is smaller than the second preset ratio difference threshold.

[0031] In a second aspect, the present application provides a voltage transformer error state evaluation device, comprising:

[0032] A transformer ratio determination module is used to determine the target ratio coefficient of each branch transformer based on the voltage information of the voltage transformer on the busbar in the distribution network within the target time period, the output power of each branch transformer and the law of conservation of energy;

[0033] a voltage drop model building module, configured to determine a line resistance corresponding to each branch transformer based on the target transformation ratio coefficient and the line unit resistance value, and to build a line voltage drop model using the line resistance and the line current;

[0034] A transformation ratio coefficient model building module is used to perform transformer primary voltage fitting based on the voltage information, the secondary voltage and secondary load of each branch transformer, the line voltage drop model, and the error back propagation network to determine the transformer transformation ratio coefficient model;

[0035] An error state evaluation module is used to trigger a voltage transformer ratio difference determination operation based on the transformer ratio coefficient model, the line voltage drop model and the collected secondary voltage to be processed of the voltage transformer, and use the obtained target transformer ratio difference to perform a voltage transformer error state evaluation to obtain an error state evaluation result.

[0036] In a third aspect, the present application provides an electronic device, comprising:

[0037] Memory, used to store computer programs;

[0038] The processor is configured to execute the computer program to implement the steps of the aforementioned voltage transformer error state evaluation method.

[0039] In a fourth aspect, the present application provides a computer-readable storage medium for storing a computer program, which implements the steps of the aforementioned voltage transformer error state evaluation method when executed by a processor.

[0040] It can be seen that in the present application, the target transformation ratio coefficient of each branch transformer is determined based on the voltage information of the voltage transformer on the bus in the distribution network within the target time period, the output power of each branch transformer and the law of conservation of energy; the line resistance corresponding to each branch transformer is determined based on the target transformation ratio coefficient and the line unit resistance value, and the line voltage drop model is constructed using the line resistance and the line current; the primary voltage of the transformer is fitted through the voltage information, the secondary voltage and secondary load of each branch transformer, the line voltage drop model and the error back propagation network to determine the transformer transformation ratio coefficient model; the voltage transformer ratio difference determination operation is triggered based on the transformer transformation ratio coefficient model, the line voltage drop model and the collected secondary voltage to be processed of the voltage transformer, and the voltage transformer error state evaluation is performed using the obtained target transformer ratio difference to obtain an error state evaluation result. That is, in this application, the target ratio coefficient of each branch transformer is first determined using the voltage information of the voltage transformer on the busbar during the target time period, and then the line voltage drop model is constructed using the target ratio coefficient and the line unit resistance value; then, the transformer primary voltage is fitted based on the line voltage drop model, the secondary voltage and secondary load of each branch transformer, and the error back propagation network to obtain the transformer ratio coefficient model; finally, the voltage transformer error state is evaluated based on the transformer ratio coefficient model, the line voltage drop model, and the collected to-be-processed secondary voltage of the voltage transformer. In this way, the accuracy and reliability of the voltage transformer error state evaluation can be effectively improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0042] Figure 1 A flow chart of a voltage transformer error state evaluation method provided in this application;

[0043] Figure 2 A schematic diagram of a distribution network architecture provided for this application;

[0044] Figure 3 A schematic diagram of a transformer ratio coefficient model provided in this application;

[0045] Figure 4 This is a schematic diagram of the structure of a voltage transformer error state evaluation device provided by this application;

[0046] Figure 5This is a structural diagram of an electronic device provided in this application. DETAILED DESCRIPTION

[0047] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0048] Current voltage transformer evaluation schemes use an improved GAT network to establish a training model between transformer environmental parameters, low-voltage side load, and the actual transformer ratio. By calculating the transformer ratio, the transformer primary voltage is derived, thereby evaluating the transformer error state. However, because this scheme does not consider the voltage drop between the voltage transformer primary voltage and the transformer primary voltage, it will have a negative impact on the accuracy and reliability of the evaluation results. To this end, the present application provides a voltage transformer error state evaluation scheme that can effectively improve the accuracy and reliability of voltage transformer error state evaluation.

[0049] See also Figure 1 As shown, an embodiment of the present invention discloses a method for evaluating a voltage transformer error state, comprising:

[0050] Step S11: determining a target transformation ratio coefficient of each branch transformer based on voltage information of a voltage transformer on a busbar in a distribution network within a target time period, output power of each branch transformer, and the law of conservation of energy.

[0051] Specifically, in this embodiment, first, Figure 2When the mutual inductors in the distribution network shown are normal, the transformation ratio coefficient k of each branch transformer under current conditions is calculated based on the law of conservation of energy. Specifically, first, the corresponding bus output power is determined based on the first rated transformation ratio and secondary voltage corresponding to the voltage transformer on the bus in the distribution network during the target time period, and the second rated transformation ratio and secondary current corresponding to the current transformer on the bus; then, the transformer output power corresponding to each branch transformer is determined based on the secondary voltage, secondary current and power influence coefficient of each branch transformer on the bus during the target time period; then, the line loss is determined based on the line loss rate corresponding to the bus and the bus output power; then, the corresponding transformer loss power is determined based on the transformer no-load loss, transformer short-circuit loss and transformer load rate corresponding to each branch transformer; then, the corresponding target loss power is determined based on the bus output power, the line loss and the transformer output power corresponding to each branch transformer, the transformer loss power and the law of conservation of energy; then, the target loss power and the bus output power are clustered and analyzed, and the target transformation ratio coefficient of each branch transformer is determined using the cluster analysis results and the neural network algorithm. The specific steps are as follows:

[0052] 1) Randomly select a period of time when the transformer is normal As the target time period ( is the starting time of the target time period, is the end time of the target time period), calculate the total line power:

[0053] (1);

[0054] Where, , is the secondary voltage of the voltage transformer, is the rated transformation ratio of the voltage transformer; is the secondary current of the current transformer, is the rated transformation ratio of the current transformer; is the power factor; is the bus output power, is the primary voltage of the busbar voltage transformer, is the primary current of the bus voltage transformer.

[0055] 2) Calculation During the time period, the output power of the branch transformer of each line is:

[0056] (2);

[0057] Where, For the current line The secondary voltage measured by the branch transformer, Current line The secondary current measured by the branch transformer is , represents the number of branches; For the current line The power factor of the transformer; It is the first The output power of the branch transformer.

[0058] 3) According to the law of conservation of energy, the line output power It mainly includes branch transformer output power, power loss, and line loss, namely:

[0059] (3);

[0060] Where, , For the No-load loss of branch transformer, For the Short-circuit loss of branch transformer, For the Branch transformer load factor , For the The rated power of a branch transformer is a fixed value. , For the The primary voltage of the branch transformer, is a set constant, is the number of turns of the primary winding, For the The rated transformation ratio of the branch transformer, Take the power frequency , is the cross-sectional area of ​​a single turn coil of the primary winding, For the The voltage amplitude measured on the secondary side of the branch transformer, is the volume of the core. , It is The primary current of the branch transformer, is the rated capacity of the branch transformer, 、 Respectively The primary and secondary side resistance of the branch transformer, , Indicates the The factory resistance of the branch transformer, They are the ambient temperature when leaving the factory and the current ambient temperature. To calculate the commonly used values, the copper conductor is taken as 235, and the aluminum conductor is taken as 225. is the line loss rate. Then, according to formula (3), the power loss can be expressed as:

[0061] (4);

[0062] Where, Indicates power loss; For the The no-load loss of the branch transformer is a fixed value. That is, we can first select The data of approximately the same time period are analyzed. Considering that the size of the branch transformer ratio is mainly affected by the load, when there are approximately the same When the branch transformer The value remains basically unchanged. If we further select the 、 When the line loss rate Therefore, the transformer data is screened twice, the first time through 、 Screen the time period when the secondary voltage and secondary load are basically non-fluctuating, and then use the DBSCAN clustering algorithm (Density-Based Spatial Clustering of Applications with Noise, a density-based clustering algorithm) to cluster the secondary voltage and secondary load. 、 Perform cluster analysis on two variables and select transformer data in the same category to construct the formula:

[0063] (5);

[0064] in, , Indicates the The branch transformer is in the The sample data required for the above steps collected at the moment, , , , for transformer data under the same category, Basically the same. Using neural network algorithm, the parameters can be calculated , No. Target ratio coefficient of branch transformer (Take a positive number).

[0065] Step S12: determining the line resistance corresponding to each branch transformer based on the target transformation ratio coefficient and the line unit resistance value, and constructing a line voltage drop model using the line resistance and the line current.

[0066] Specifically, in this embodiment, after obtaining the target transformation ratio coefficient of each branch transformer, the line resistance is first calculated using the target transformation ratio coefficient, and then the line voltage drop model is constructed according to the line resistance.

[0067] In this embodiment, the calculation of line resistance is first performed by determining the corresponding line unit resistance value based on the target ratio coefficient and line current corresponding to each branch transformer, and the target distance information between each branch transformer and the switch station; then, the line resistance corresponding to each branch transformer is determined based on the target distance information and the line unit resistance value. The relevant calculation process is as follows:

[0068] 1) Determine the Primary voltage of branch transformer :

[0069] (6);

[0070] 2) Determine the The line voltage drop of the branch transformer is :

[0071] (7);

[0072] 3) At the same time, ,in Indicates a branch The current, Indicates a branch The resistance, Indicates the current The distance between each branch transformer and the switchgear station, is the resistance per unit length. Then:

[0073] (8);

[0074] Where, is the secondary current of the current transformer; is the rated transformation ratio of the current transformer.

[0075] 4) Based on formulas (6) to (8), calculate the unit resistance of the line . Thus constructing the line resistance of each branch :

[0076] (9).

[0077] Furthermore, after obtaining the line resistance, to calculate the line voltage drop, it is also necessary to evaluate the branch in real time. Current , and then combine the law of conservation of energy and transformer no-load loss to determine the line voltage drop model. The relevant steps are as follows:

[0078] 1) Evaluate line current based on the law of conservation of energy :

[0079] (10);

[0080] 2) Obtain line current based on formula (10) , and then each branch builds a line voltage drop model:

[0081] (11).

[0082] Step S13: performing transformer primary voltage fitting based on the voltage information, the secondary voltage and secondary load of each branch transformer, the line voltage drop model, and the error back propagation network to determine a transformer ratio coefficient model.

[0083] Specifically, after obtaining the line voltage drop model, this embodiment uses the mutual inductor secondary voltage, the transformer secondary voltage, and the line voltage drop model to construct a transformer ratio coefficient model. That is, first, the first ambient temperature information, the target ratio coefficient of any branch transformer, the secondary load, and the primary voltage are normalized, and the normalized first ambient temperature information, the target ratio coefficient, and the secondary load are input into the data processing layer configured before the error back propagation network to obtain the data processing result; then, the data processing result is input into the error back propagation network to perform transformer primary voltage fitting, so as to determine the transformer ratio coefficient model based on the fitting result, the voltage information, and the corresponding secondary voltage of the branch transformer. The relevant steps are as follows:

[0084] 1) Calculation of transformer ratio coefficient.

[0085] In actual operation, based on the obtained transformer secondary voltage , transformer secondary voltage , line voltage drop , the transformer primary voltage can be calculated and target ratio coefficient :

[0086] (12);

[0087] (13);

[0088] Where, is the secondary voltage of the voltage transformer; is the rated transformation ratio of the voltage transformer; is the line voltage drop.

[0089] 2) Construction of transformer ratio coefficient model.

[0090] In order to speed up the calculation of transformer ratio, the branch transformer The value is affected by the transformer secondary load and ambient temperature. , secondary load , ambient temperature is the input, transformer primary voltage The BP (Back Propagation) neural network algorithm is used to build an online evaluation model for transformer ratio. The relationship between the ambient temperature and the load is that this embodiment adds a data processing layer before the BP network, such as Figure 3 As shown in the figure, the relationship between variables can be further explored to improve the fitting accuracy and speed of the model.

[0091] First, compare the transformation ratio , ambient temperature, secondary load, and primary voltage data are normalized to obtain normalized data 、 ,in, is the normalized transformation ratio , is the normalized ambient temperature, is the normalized transformer secondary load, is the normalized primary voltage of the transformer. Input the normalized data into the data processing layer:

[0092] (14);

[0093] Where, are the set thresholds respectively; For nonlinear functions, you can choose a step function; is the set weight parameter; They are the transformation ratio, ambient temperature and transformer secondary load after processing by the data processing layer. The function is as follows, where It can refer to the formula (14) 、 or .

[0094] (15).

[0095] After being processed by the data processing layer, Input the BP model and fit the transformer primary voltage to obtain the transformer ratio coefficient model.

[0096] Step S14: triggering a voltage transformer ratio difference determination operation based on the transformer ratio coefficient model, the line voltage drop model, and the collected to-be-processed secondary voltage of the voltage transformer, and performing a voltage transformer error state evaluation using the obtained target transformer ratio difference to obtain an error state evaluation result.

[0097] Specifically, in this embodiment, after completing the construction of the transformer ratio coefficient model, the obtained transformer ratio coefficient model can be used to evaluate the voltage transformer error state. That is, first, based on the transformer ratio coefficient model and the collected branch transformer secondary load and second ambient temperature information, the corresponding target ratio coefficient is determined to determine the corresponding target transformer primary voltage; then, based on the line voltage drop model, the target line voltage drop is determined, and the target transformer primary voltage is determined according to the target transformer primary voltage and the target line voltage drop; then, the target transformer primary voltage and the collected voltage transformer to be processed secondary voltage are used to trigger the voltage transformer ratio difference determination operation to obtain the target transformer ratio difference. Afterwards, the error state evaluation result is determined by comparing the target transformer ratio difference with the first preset ratio difference threshold and the second preset ratio difference threshold; wherein, the first preset ratio difference threshold is less than the second preset ratio difference threshold. The relevant steps are as follows:

[0098] 1) Based on the constructed transformer ratio coefficient model, the transformer primary voltage is calculated;

[0099] 2) Determine the line voltage drop based on the line voltage drop model, and calculate the primary voltage of the voltage transformer through the transformer primary voltage and line voltage drop. ;

[0100] 3) Calculate the transformer ratio coefficient through the primary voltage of the voltage transformer and the collected secondary voltage to be processed, and make status judgment:

[0101] ;

[0102] Where, Indicates the rated transformation ratio of the voltage transformer, is the obtained mutual inductor ratio difference.

[0103] 4) Compare the mutual inductor ratio difference and the ratio difference threshold. For example, when the ratio difference threshold is and When, if , then it is determined that the voltage transformer is normal; if , then the voltage transformer alarm is triggered; if , it is determined that the voltage transformer is abnormal.

[0104] In summary, in this embodiment, based on the law of conservation of energy, the transformer ratio under current load conditions is calculated. Based on the current ratio information, the resistance of each line is calculated, and the line current calculation model is further calculated, thereby constructing a line voltage drop model. The actual ratio k can be calculated based on the line voltage drop, the transformer secondary voltage, the rated ratio, and the transformer secondary voltage. To reduce the amount of calculation, an improved neural network model is used to construct a ratio coefficient model based on the k value under normal conditions, the transformer secondary load, and temperature data. Based on the ratio coefficient model established under normal transformer conditions, the voltage transformer error state during operation is evaluated online. That is, in this embodiment, on the one hand, a line-end voltage comparison method that considers the voltage drop of the distribution network line is studied; on the other hand, a mathematical model for voltage transformer metering misalignment assessment that integrates the transformer output ratio and line voltage drop is studied to improve the accuracy of voltage transformer assessment.

[0105] In addition, based on the above method steps, Technical verification was carried out on eight voltage transformers in the substation. The evaluation results of the method described in this embodiment were compared with the actual transformer power outage verification results, as shown in Table 1 below. The evaluation results are consistent with the actual power outage results.

[0106] Table 1

[0107]

[0108] It can be seen that in this application, the target transformation ratio coefficient of each branch transformer is determined based on the voltage information of the voltage transformer on the bus in the distribution network within the target time period, the output power of each branch transformer and the law of conservation of energy; the line resistance corresponding to each branch transformer is determined based on the target transformation ratio coefficient and the line unit resistance value, and the line voltage drop model is constructed using the line resistance and line current; the primary voltage of the transformer is fitted through the voltage information, the secondary voltage and secondary load of each branch transformer, the line voltage drop model and the error back propagation network to determine the transformer transformation ratio coefficient model; the voltage transformer ratio difference determination operation is triggered based on the transformer transformation ratio coefficient model, the line voltage drop model and the collected secondary voltage to be processed of the voltage transformer, and the voltage transformer error state evaluation is performed using the obtained target transformer ratio difference to obtain an error state evaluation result. That is, in this application, the target ratio coefficient of each branch transformer is first determined using the voltage information of the voltage transformer on the busbar during the target time period, and then the line voltage drop model is constructed using the target ratio coefficient and the line unit resistance value; then, the transformer primary voltage is fitted based on the line voltage drop model, the secondary voltage and secondary load of each branch transformer, and the error back propagation network to obtain the transformer ratio coefficient model; finally, the voltage transformer error state is evaluated based on the transformer ratio coefficient model, the line voltage drop model, and the collected to-be-processed secondary voltage of the voltage transformer. In this way, the accuracy and reliability of the voltage transformer error state evaluation can be effectively improved.

[0109] See also Figure 4 As shown, the embodiment of the present application also discloses a voltage transformer error state evaluation device, including:

[0110] The transformer ratio determination module 11 is configured to determine a target ratio coefficient of each branch transformer based on voltage information of a voltage transformer on a busbar in the distribution network within a target time period, the output power of each branch transformer, and the law of conservation of energy;

[0111] a voltage drop model building module 12, configured to determine the line resistance corresponding to each branch transformer based on the target transformation ratio coefficient and the line unit resistance value, and to build a line voltage drop model using the line resistance and the line current;

[0112] A transformation ratio coefficient model building module 13 is used to perform transformer primary voltage fitting based on the voltage information, the secondary voltage and secondary load of each branch transformer, the line voltage drop model, and the error back propagation network to determine the transformer transformation ratio coefficient model;

[0113] The error state evaluation module 14 is used to trigger a voltage transformer ratio difference determination operation based on the transformer ratio coefficient model, the line voltage drop model and the collected secondary voltage to be processed of the voltage transformer, and use the obtained target transformer ratio difference to perform a voltage transformer error state evaluation to obtain an error state evaluation result.

[0114] It can be seen that in this application, the target ratio coefficient of each branch transformer is first determined by using the voltage information of the voltage transformer on the busbar during the target time period, and then the line voltage drop model is constructed using the target ratio coefficient and the line unit resistance value; then, the transformer primary voltage is fitted based on the line voltage drop model, the secondary voltage and secondary load of each branch transformer, and the error back propagation network to obtain the transformer ratio coefficient model; finally, the voltage transformer error state is evaluated based on the transformer ratio coefficient model, the line voltage drop model, and the collected to-be-processed secondary voltage of the voltage transformer. In this way, the accuracy and reliability of the voltage transformer error state evaluation can be effectively improved.

[0115] In some specific embodiments, the transformer ratio determination module 11 can be specifically used to: determine the corresponding bus output power based on the first rated ratio and secondary voltage corresponding to the voltage transformer on the bus in the distribution network within the target time period, and the second rated ratio and secondary current corresponding to the current transformer on the bus; determine the transformer output power corresponding to each branch transformer based on the secondary voltage, secondary current and power influence coefficient of each branch transformer on the bus within the target time period; determine the line loss based on the line loss rate corresponding to the bus and the bus output power; determine the corresponding transformer loss power based on the transformer no-load loss, transformer short-circuit loss and transformer load rate corresponding to each branch transformer; determine the corresponding target loss power based on the bus output power, the line loss and the transformer output power corresponding to each branch transformer, the transformer loss power and the law of conservation of energy; determine the target ratio coefficient of each branch transformer by performing cluster analysis on the target loss power and the bus output power, and using the cluster analysis results and the neural network algorithm.

[0116] In some specific embodiments, the voltage drop model construction module 12 can be specifically used to: determine the corresponding line unit resistance value based on the target transformation ratio coefficient and line current corresponding to each branch transformer, and the target distance information between each branch transformer and the switchgear; determine the line resistance corresponding to each branch transformer based on the target distance information and the line unit resistance value.

[0117] In some specific embodiments, the voltage drop model building module 12 can be specifically used to determine the line voltage drop model based on the law of conservation of energy, the line current corresponding to each branch transformer, the line resistance and the transformer no-load loss.

[0118] In some specific embodiments, the transformation ratio coefficient model construction module 13 can be specifically used to: use the first ambient temperature information, the target transformation ratio coefficient of any branch transformer, the secondary load and the primary voltage for normalization, and input the normalized first ambient temperature information, the target transformation ratio coefficient and the secondary load into the data processing layer configured before the error back propagation network to obtain a data processing result; by inputting the data processing result into the error back propagation network, the primary voltage of the transformer is fitted, so as to determine the transformer transformation ratio coefficient model based on the fitting result, the voltage information and the corresponding secondary voltage of the branch transformer.

[0119] In some specific embodiments, the error state evaluation module 14 can be specifically used to: determine the corresponding target transformer primary voltage based on the transformer ratio coefficient model and the collected branch transformer secondary load and second ambient temperature information, and the corresponding target ratio coefficient; determine the target line voltage drop based on the line voltage drop model, and determine the target transformer primary voltage based on the target transformer primary voltage and the target line voltage drop; use the target transformer primary voltage and the collected to-be-processed secondary voltage of the voltage transformer to trigger the voltage transformer ratio difference determination operation to obtain the target transformer ratio difference.

[0120] In some specific embodiments, the error state evaluation module 14 can be specifically used to: determine the error state evaluation result by comparing the target mutual inductor ratio difference with a first preset ratio difference threshold and a second preset ratio difference threshold; wherein the first preset ratio difference threshold is smaller than the second preset ratio difference threshold.

[0121] Furthermore, the embodiment of the present application also discloses an electronic device, Figure 5 This is a structural diagram of an electronic device 20 according to an exemplary embodiment. The content in the diagram should not be considered as any limitation to the scope of application of the present application.

[0122] Figure 5This is a schematic diagram of the structure of an electronic device 20 provided in an embodiment of the present application. The electronic device 20 may specifically include: at least one processor 21, at least one memory 22, a power supply 23, a communication interface 24, an input / output interface 25, and a communication bus 26. The memory 22 is used to store a computer program, which is loaded and executed by the processor 21 to implement the relevant steps of the voltage transformer error state assessment method disclosed in any of the aforementioned embodiments. Furthermore, the electronic device 20 in this embodiment may specifically be an electronic computer.

[0123] In this embodiment, the power supply 23 is used to provide operating voltage for each hardware device on the electronic device 20; the communication interface 24 can create a data transmission channel between the electronic device 20 and the external device. The communication protocol it follows is any communication protocol that can be applied to the technical solution of this application and is not specifically limited here; the input and output interface 25 is used to obtain external input data or output data to the outside world. Its specific interface type can be selected according to specific application needs and is not specifically limited here.

[0124] In addition, the memory 22, as a carrier for resource storage, can be a read-only memory, random access memory, disk or CD, etc. The resources stored thereon can include an operating system 221, a computer program 222, etc., and the storage method can be temporary storage or permanent storage.

[0125] The operating system 221 is used to manage and control the hardware devices and computer program 222 on the electronic device 20, and can be Windows Server, Netware, Unix, Linux, etc. In addition to including a computer program capable of implementing the voltage transformer error state assessment method performed by the electronic device 20 disclosed in any of the aforementioned embodiments, the computer program 222 can further include a computer program capable of implementing other specific tasks.

[0126] Furthermore, the present application discloses a computer-readable storage medium for storing a computer program; wherein, when executed by a processor, the computer program implements the aforementioned method for estimating the error state of a voltage transformer. The specific steps of this method can be referred to the corresponding contents disclosed in the aforementioned embodiments and will not be repeated here.

[0127] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from the other embodiments. Reference can be made to the descriptions of the identical or similar parts between the various embodiments. For the devices disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple, and the relevant parts can be referred to the descriptions of the methods.

[0128] Professionals may further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the above description has generally described the components and steps of each example according to their functions. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0129] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein may be implemented directly using hardware, a software module executed by a processor, or a combination of the two. The software module may be placed in random access memory (RAM), internal memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

[0130] Finally, it should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of additional identical elements in the process, method, article, or device comprising the element.

[0131] The above is a detailed introduction to the technical solution provided by the present application. Specific examples are used herein to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea. At the same time, for those skilled in the art, according to the ideas of the present application, there may be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A method for evaluating a voltage transformer error state, characterized in that: include: Determining a target transformation ratio coefficient of each branch transformer based on voltage information of a voltage transformer on a busbar in the distribution network within a target time period, output power of each branch transformer, and the law of conservation of energy; Determining the line resistance corresponding to each branch transformer based on the target transformation ratio coefficient and the line unit resistance value, and constructing a line voltage drop model using the line resistance and the line current; Perform transformer primary voltage fitting based on the voltage information, the secondary voltage and secondary load of each branch transformer, the line voltage drop model, and the error back propagation network to determine a transformer ratio coefficient model; Based on the transformer ratio coefficient model, the line voltage drop model and the collected secondary voltage to be processed of the voltage transformer, a voltage transformer ratio difference determination operation is triggered, and the obtained target transformer ratio difference is used to perform voltage transformer error state evaluation to obtain an error state evaluation result.

2. The voltage transformer error state evaluation method according to claim 1, characterized in that: The determining of the target transformation ratio coefficient of each branch transformer based on the voltage information of the voltage transformer on the busbar in the distribution network within the target time period, the output power of each branch transformer, and the law of conservation of energy includes: Determine a corresponding bus output power based on a first rated transformation ratio and a secondary voltage corresponding to a voltage transformer on a bus in the distribution network, and a second rated transformation ratio and a secondary current corresponding to a current transformer on the bus within a target time period; Determining the transformer output power corresponding to each branch transformer based on the secondary voltage, secondary current and power influence coefficient of each branch transformer on the bus within the target time period; determining a line loss based on a line loss rate corresponding to the bus and an output power of the bus; Determining the corresponding transformer loss power based on the transformer no-load loss, transformer short-circuit loss and transformer load rate corresponding to each branch transformer; Determine a corresponding target power loss based on the bus output power, the line loss, the transformer output power corresponding to each branch transformer, the transformer power loss, and the law of conservation of energy; A cluster analysis is performed on the target power loss and the bus output power, and the target transformation ratio coefficient of each branch transformer is determined using the cluster analysis results and a neural network algorithm.

3. The voltage transformer error state evaluation method according to claim 1, characterized in that: The determining of the line resistance corresponding to each branch transformer based on the target transformation ratio coefficient and the line unit resistance value includes: Determining a corresponding line unit resistance value based on the target transformation ratio coefficient and line current corresponding to each branch transformer, and target distance information between each branch transformer and the switchgear station; The line resistance corresponding to each of the branch transformers is determined based on the target distance information and the line unit resistance value.

4. The voltage transformer error state evaluation method according to claim 1, characterized in that: The constructing of a line voltage drop model using the line resistance and the line current includes: A line voltage drop model is determined based on the law of conservation of energy, the line current corresponding to each branch transformer, the line resistance, and the transformer no-load loss.

5. The voltage transformer error state evaluation method according to claim 1, characterized in that: The transformer primary voltage fitting is performed using the voltage information, the secondary voltage and secondary load of each branch transformer, the line voltage drop model, and the error back propagation network, including: Normalizing the first ambient temperature information, the target transformation ratio coefficient of any branch transformer, the secondary load, and the primary voltage, and inputting the normalized first ambient temperature information, the target transformation ratio coefficient, and the secondary load into a data processing layer configured before an error back propagation network to obtain a data processing result; The data processing result is input into the error back propagation network to perform transformer primary voltage fitting, so as to determine the transformer ratio coefficient model based on the fitting result, the voltage information and the corresponding secondary voltage of the branch transformer.

6. The method for evaluating the error state of a voltage transformer according to any one of claims 1 to 5, characterized in that: The voltage transformer ratio difference determination operation triggered by the to-be-processed secondary voltage of the voltage transformer based on the transformer ratio coefficient model, the line voltage drop model, and the collected voltage transformer includes: Determining a corresponding target transformer primary voltage based on the transformer ratio coefficient model, the collected branch transformer secondary load and second ambient temperature information, and the corresponding target ratio coefficient; Determining a target line voltage drop based on the line voltage drop model, and determining a target transformer primary voltage according to the target transformer primary voltage and the target line voltage drop; A voltage transformer ratio difference determination operation is triggered by utilizing the target transformer primary voltage and the collected to-be-processed secondary voltage of the voltage transformer to obtain a target transformer ratio difference.

7. The voltage transformer error state evaluation method according to claim 1, characterized in that: The step of using the obtained target transformer ratio difference to perform voltage transformer error state evaluation to obtain an error state evaluation result includes: The error state evaluation result is determined by comparing the target mutual inductor ratio difference with a first preset ratio difference threshold and a second preset ratio difference threshold; wherein the first preset ratio difference threshold is smaller than the second preset ratio difference threshold.

8. A voltage transformer error state evaluation device, characterized in that: include: A transformer ratio determination module is used to determine the target ratio coefficient of each branch transformer based on the voltage information of the voltage transformer on the busbar in the distribution network within the target time period, the output power of each branch transformer and the law of conservation of energy; a voltage drop model building module, configured to determine a line resistance corresponding to each branch transformer based on the target transformation ratio coefficient and the line unit resistance value, and to build a line voltage drop model using the line resistance and the line current; A transformation ratio coefficient model building module is used to perform transformer primary voltage fitting based on the voltage information, the secondary voltage and secondary load of each branch transformer, the line voltage drop model, and the error back propagation network to determine the transformer transformation ratio coefficient model; An error state evaluation module is used to trigger a voltage transformer ratio difference determination operation based on the transformer ratio coefficient model, the line voltage drop model and the collected secondary voltage to be processed of the voltage transformer, and use the obtained target transformer ratio difference to perform a voltage transformer error state evaluation to obtain an error state evaluation result.

9. An electronic device, characterized in that: include: Memory, used to store computer programs; A processor, configured to execute the computer program to implement the voltage transformer error state evaluation method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that Used to store a computer program, which, when executed by a processor, implements the voltage transformer error state evaluation method according to any one of claims 1 to 7.

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