A power data identification method of a power system transformer identification instrument

Abstract

This invention discloses a power data identification method for a power distribution transformer area (PDE) identifier in a power system, relating to the field of PDE identification technology. The method includes: power data identification features for forming a PDE; an identification mechanism for forming a PDE; associating the returned signal with a PDE based on the returned signal and the identification mechanism; a parameter calibration mechanism for PDE formation; the PDE identifier having at least one built-in identification channel; identifying the PDE that generates the noise-reduced signal as the target PDE; and calibrating the noise-reduced signal using the parameter calibration mechanism corresponding to the target PDE to obtain a parameter calibration signal. By utilizing the power data identification features for forming a PDE, the identification mechanism for forming a PDE, and the parameter calibration mechanism for forming a PDE, the method can identify the PDE that generates the noise-reduced signal based on the power data identification features and calibrate the noise-reduced signal using the parameter calibration mechanism corresponding to the target PDE, ensuring higher accuracy of the parameter calibration signal.

Description

Technical Field

[0001] This invention relates to the field of transformer area identification technology, specifically to a method for identifying power data using a transformer area identification device for power systems. Background Technology

[0002] In a power system, a transformer substation refers to the power supply range or area of ​​a single transformer. When a transformer substation identification device acquires data, it collects data from all substations together. This data mixing can lead to difficulties in subsequent processing. Data from different substations exhibits certain differences, and the environments of different substations have varying impacts on the data. When identifying power data, it is necessary to determine the attribution of the power data. Furthermore, to obtain accurate and undisturbed data, targeted calibration is required. However, existing technologies have limited research on this, and the interference factors in the environment are complex. Consequently, the attribution of the acquired data is unclear and contains errors. Summary of the Invention

[0003] To solve the above-mentioned technical problems, a method for identifying power data using a transformer substation identification device for power systems is provided. This technical solution addresses the problems mentioned in the background section.

[0004] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0005] A method for identifying power data using a transformer substation identifier in a power system includes:

[0006] The voltage data information of at least one transformer area is obtained using a transformer area identification device, and the power data identification features of the transformer area are formed based on the voltage data information.

[0007] Based on the identification characteristics of power data, an identification mechanism for transformer substations is formed;

[0008] The transformer area identification device sends at least one reference signal and obtains at least one return signal. Based on the return signal and the identification mechanism, the return signal is associated with the transformer area.

[0009] Based on the returned signals, the operating environment of the transformer area is identified, and a parameter calibration mechanism is established for the transformer area;

[0010] The transformer area identification device has at least one built-in identification channel, which can simultaneously identify the electrical signals of multiple transformer areas;

[0011] When the identification channel is running, the collected electrical signals are filtered and denoised to obtain a denoised signal. Based on the power data identification characteristics, the transformer area that generates the denoised signal is identified as the target transformer area.

[0012] The noise reduction signal is calibrated using the parameter calibration mechanism corresponding to the target station area to obtain the parameter calibration signal.

[0013] Preferably, the process of forming power data identification features for a transformer substation based on voltage data information includes the following steps:

[0014] Voltage data information from the same transformer area is aggregated into a voltage data information set, and the voltage data information set corresponds to the transformer area.

[0015] Extract voltage phase, voltage amplitude, and the transmission / reception time interval of voltage data from voltage data information;

[0016] The (0, 1) interval is divided into equal-interval segments to obtain at least one identification point;

[0017] The identification points are randomly combined to form at least one set of ternary arrays. The identification points in the ternary arrays are sequentially assigned to the voltage phase, voltage amplitude, and transmission / reception time interval. The voltage phase, voltage amplitude, and transmission / reception time interval are multiplied by the assigned identification points to obtain the preliminary voltage phase, preliminary voltage amplitude, and preliminary transmission / reception time interval.

[0018] Obtain at least one existing elementary function, and randomly combine the at least one elementary function to form at least one combined function, wherein the elementary function is a ternary function;

[0019] Substituting the preparatory voltage phase, preparatory voltage amplitude, and preparatory transmission / reception time interval into the combination function yields the characteristic values;

[0020] The maximum and minimum values ​​of the characteristic values ​​corresponding to the voltage data information in the voltage data information set are used as endpoints to form the characteristic interval;

[0021] By taking the intersection of at least one pairwise feature intervals, at least one target interval can be obtained;

[0022] The combination function, the preliminary voltage phase, the preliminary voltage amplitude, and the preliminary receiving and transmitting time interval, which are all empty intervals in the target interval, are used as the target function, the target voltage phase, the target voltage amplitude, and the target receiving and transmitting time interval.

[0023] The target voltage phase, target voltage amplitude, and target transmission / reception time interval are used as power data identification features.

[0024] Preferably, the identification mechanism for forming transformer substations based on power data identification features includes the following steps:

[0025] Obtain actual voltage information, and extract actual phase, actual amplitude, and actual transmission / reception time from the actual voltage information;

[0026] The actual phase, actual amplitude, and actual transmission / reception time are multiplied by the identification points of the target function, target voltage phase, target voltage amplitude, and target transmission / reception time interval, respectively, to obtain the target actual phase, target actual amplitude, and target actual transmission / reception time.

[0027] Substituting the actual phase, actual amplitude, and actual transmission / reception time of the target into the objective function yields the identification value;

[0028] The transformer substations that contain the characteristic intervals with identification values ​​are used as the source of actual voltage information.

[0029] Preferably, the step of associating the returned signal with the station area based on the returned signal and the identification mechanism includes the following steps:

[0030] The voltage data in the returned signal is identified and extracted to obtain the returned voltage phase, returned voltage amplitude, and returned transmission / reception time. The identification mechanism is used to determine the station area that generated the returned signal.

[0031] Preferably, the identification of the operating environment of the transformer substation and the establishment of a parameter calibration mechanism for the substation substation include the following steps:

[0032] Obtain the target elementary function of the returned signal, which is the elementary function that maps the returned signal to the corresponding reference signal;

[0033] To return the signal, randomly match identification points to obtain at least one combination of identification points;

[0034] The target elementary function of at least one returned signal is multiplied by the identification points assigned in the identification point combination and then summed to obtain the preliminary calibration function;

[0035] The returned signal is input into the pre-calibration function to obtain the returned calibration signal, and the environmental influence coefficient between the returned calibration signal and the reference signal is obtained.

[0036] The environmental impact coefficients of all returned signals are then summed to obtain the judgment value of the preliminary calibration function;

[0037] The preliminary calibration function with the smallest judgment value is used as the target calibration function.

[0038] Preferably, obtaining the environmental impact coefficients of the returned calibration signal and the reference signal includes the following steps:

[0039] The feature signal is obtained by subtracting the real-time acquired return signal from the reference signal. Continuous wavelet transform is performed on the characteristic signal to obtain the transform exponent at different time and frequency scales. ;

[0040] in, Indicates the time point of data collection. Indicates the scale parameter. Indicates time parameters;

[0041] Discretize the scale and time parameters to obtain the decomposed transformation exponent matrix. ,in Indicates the first One scale;

[0042] The local energy distribution is calculated for the transformation exponent at each scale, and the calculation expression is as follows:

[0043] ;

[0044] in, This indicates the total number of data collection points. Indicates the first Energy at scale;

[0045] The local nonlinear environmental impact value is calculated at each scale, and the calculation expression is as follows:

[0046] ;

[0047] in, Indicates the first The median of the scaling exponent. This is the self-regulation coefficient. This represents the local nonlinear environmental impact value, and the self-regulation coefficient is set based on experience.

[0048] By varying the fluctuation range of the index at different scales, the environmental impact coefficients at all scales are calculated using the following expression:

[0049] ;

[0050] in, The total number of scales. Indicates the first The ratio of wavelet energy distribution at different scales is calculated using the following expression: , Let A represent the total energy across all scales, and let A represent the environmental impact coefficient.

[0051] Preferably, the identification channel synchronously identifies the electrical signals of multiple transformer substations, including the following steps:

[0052] At least one electrical signal is acquired, and the at least one electrical signal is evenly distributed into the identification channel. The identification channel identifies the distributed electrical signals in sequence.

[0053] Preferably, the step of identifying the transformer area that generates the noise reduction signal based on power data identification features includes the following steps:

[0054] The noise reduction voltage is identified from the noise reduction signal, and the station area that generated the noise reduction signal is obtained by using the noise reduction voltage and the identification mechanism.

[0055] Preferably, identifying the noise-reduced voltage from the noise-reduced signal includes the following steps:

[0056] To identify the pattern of change, the range of signal variation amplitude, the range of variation speed, the period range, and the phase expression in voltage data or non-voltage data are selected as options for identification.

[0057] Obtain at least one first variation law of voltage from voltage data information, and obtain at least one second variation law of non-voltage data information;

[0058] The first variation rule that is consistent with the second variation rule is deleted from the first variation rule. The noise reduction voltage is identified using the deleted first variation rule. When the signal in the noise reduction signal satisfies all the deleted first variation rules, it is identified as the noise reduction voltage.

[0059] Preferably, the calibration of the noise reduction signal using the parameter calibration mechanism corresponding to the target station area includes the following steps:

[0060] The noise reduction signal is calibrated using the target calibration function corresponding to the target station area to obtain the parameter calibration signal.

[0061] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0062] By establishing power data identification features for distribution areas, forming a distribution area identification mechanism, and establishing a parameter calibration mechanism for distribution areas, the distribution areas that generate noise reduction signals can be identified based on the power data identification features. Then, the noise reduction signals are calibrated using the parameter calibration mechanism corresponding to the target distribution area to obtain parameter calibration signals. It can determine the distribution area of ​​the acquired data by establishing power data identification features, and identify environmental data according to the characteristics of the distribution area, thereby forming a calibration mechanism for the distribution area. This allows for different calibrations to be performed according to different distribution areas, ensuring higher accuracy of the parameter calibration signals. Attached Figure Description

[0063] Figure 1 This is a flowchart illustrating the power data identification method of the power distribution transformer identification instrument for power systems according to the present invention.

[0064] Figure 2 This is a schematic diagram of the process of forming power data identification features of a transformer area based on voltage data information according to the present invention;

[0065] Figure 3 This is a flowchart illustrating the identification mechanism for transformer substations based on power data identification features according to the present invention.

[0066] Figure 4 This is a flowchart illustrating the process of identifying the operating environment of a transformer substation and establishing a parameter calibration mechanism for that substation, as described in this invention.

[0067] Figure 5 This is a schematic diagram of the process of identifying the noise reduction voltage from the noise reduction signal according to the present invention. Detailed Implementation

[0068] The following description is intended to disclose the invention and enable those skilled in the art to implement it. The preferred embodiments described below are merely examples, and other obvious variations will occur to those skilled in the art.

[0069] Reference Figure 1 As shown, a method for identifying power data using a transformer substation identifier in a power system includes:

[0070] The voltage data information of at least one transformer area is obtained using a transformer area identification device, and the power data identification features of the transformer area are formed based on the voltage data information.

[0071] Based on the identification characteristics of power data, an identification mechanism for transformer substations is formed;

[0072] The transformer area identification device sends at least one reference signal and obtains at least one return signal. Based on the return signal and the identification mechanism, the return signal is associated with the transformer area.

[0073] Based on the returned signals, the operating environment of the transformer area is identified, and a parameter calibration mechanism is established for the transformer area;

[0074] The transformer area identification device has at least one built-in identification channel, which can simultaneously identify the electrical signals of multiple transformer areas;

[0075] When the identification channel is running, the collected electrical signals are filtered and denoised to obtain a denoised signal. Based on the power data identification characteristics, the transformer area that generates the denoised signal is identified as the target transformer area.

[0076] The noise reduction signal is calibrated using the parameter calibration mechanism corresponding to the target station area to obtain the parameter calibration signal.

[0077] When identifying transformer substations, it is necessary to process the data from different substations. The data from different substations are inherently different because the data from each substation is generated by a single transformer. However, the parameters and operating conditions of the transformers are different, which will result in different characteristics of the data. Therefore, the substation that generated the data can be identified by identifying the characteristics of the data. However, this depends on the actual situation of all transformers and is not based on a fixed pattern. Therefore, corresponding steps will be set up in the subsequent steps to address this issue.

[0078] Meanwhile, the environment in each transformer station is different, and the interference it causes to the data is also different. Furthermore, the electromagnetic interference at different locations within the transformer station is also different. Therefore, all of these factors need to be taken into account during calibration and addressed in the subsequent steps.

[0079] Reference Figure 2 As shown, forming the power data identification features of a transformer substation based on voltage data information includes the following steps:

[0080] Voltage data information from the same transformer area is aggregated into a voltage data information set, and the voltage data information set corresponds to the transformer area.

[0081] Extract voltage phase, voltage amplitude, and the transmission / reception time interval of voltage data from voltage data information;

[0082] The (0, 1) interval is divided into equal-interval segments to obtain at least one identification point;

[0083] The identification points are randomly combined to form at least one set of ternary arrays. The identification points in the ternary arrays are sequentially assigned to the voltage phase, voltage amplitude, and transmission / reception time interval. The voltage phase, voltage amplitude, and transmission / reception time interval are multiplied by the assigned identification points to obtain the preliminary voltage phase, preliminary voltage amplitude, and preliminary transmission / reception time interval.

[0084] Obtain at least one existing elementary function, and randomly combine the at least one elementary function to form at least one combined function, wherein the elementary function is a ternary function;

[0085] Substituting the preparatory voltage phase, preparatory voltage amplitude, and preparatory transmission / reception time interval into the combination function yields the characteristic values;

[0086] The maximum and minimum values ​​of the characteristic values ​​corresponding to the voltage data information in the voltage data information set are used as endpoints to form the characteristic interval;

[0087] By taking the intersection of at least one pairwise feature intervals, at least one target interval can be obtained;

[0088] The combination function, the preliminary voltage phase, the preliminary voltage amplitude, and the preliminary receiving and transmitting time interval, which are all empty intervals in the target interval, are used as the target function, the target voltage phase, the target voltage amplitude, and the target receiving and transmitting time interval.

[0089] The target voltage phase, target voltage amplitude, and target transmission / reception time interval are used as power data identification features.

[0090] Identification requires ensuring that data from different transformer substations do not overlap; otherwise, identification is impossible because directly collected data may overlap. Since the collected data comes from different substations, features from those substations can serve as the basis for identification. However, a suitable mapping method is needed to extract and display these features. Because the method for combining and determining these features is unknown, a random combination method is used to form a preliminary voltage phase, preliminary voltage amplitude, and preliminary transmission / reception time interval, along with a combination function. By substituting the preliminary voltage phase, amplitude, and time interval into the combination function, the target function, target voltage phase, target voltage amplitude, and target transmission / reception time interval are obtained based on the results. The basis for this judgment is that the processed value ranges of data from different substations do not overlap. This involves voltage processing; the collected data includes multiple data types, not just voltage. The voltage data is used to determine the transformer substation.

[0091] Reference Figure 3 As shown, the identification mechanism for transformer substations based on power data identification features includes the following steps:

[0092] Obtain actual voltage information, and extract actual phase, actual amplitude, and actual transmission / reception time from the actual voltage information;

[0093] The actual phase, actual amplitude, and actual transmission / reception time are multiplied by the identification points of the target function, target voltage phase, target voltage amplitude, and target transmission / reception time interval, respectively, to obtain the target actual phase, target actual amplitude, and target actual transmission / reception time.

[0094] Substituting the actual phase, actual amplitude, and actual transmission / reception time of the target into the objective function yields the identification value;

[0095] The transformer substations that contain the characteristic intervals with identification values ​​are used as the source of actual voltage information.

[0096] During the identification process, the actual phase, actual amplitude, and actual transmission / reception time extracted from the actual voltage information need to be processed before they can be substituted into the objective function. During processing, the multiplication coefficients are the identification points for generating the objective function, target voltage phase, target voltage amplitude, and target transmission / reception time interval, respectively.

[0097] Based on the returned signal and identification mechanism, the process of associating the returned signal with the transformer area includes the following steps:

[0098] The voltage data in the returned signal is identified and extracted to obtain the returned voltage phase, returned voltage amplitude, and returned transmission / reception time. The identification mechanism is used to determine the station area that generated the returned signal.

[0099] Reference Figure 4As shown, the identification of the operating environment of the transformer substation and the establishment of a parameter calibration mechanism for the substation include the following steps:

[0100] Obtain the target elementary function of the returned signal, which is the elementary function that maps the returned signal to the corresponding reference signal;

[0101] To return the signal, randomly match identification points to obtain at least one combination of identification points;

[0102] The target elementary function of at least one returned signal is multiplied by the identification points assigned in the identification point combination and then summed to obtain the preliminary calibration function;

[0103] The returned signal is input into the pre-calibration function to obtain the returned calibration signal, and the environmental influence coefficient between the returned calibration signal and the reference signal is obtained.

[0104] The environmental impact coefficients of all returned signals are then summed to obtain the judgment value of the preliminary calibration function;

[0105] The preliminary calibration function with the smallest judgment value is used as the target calibration function.

[0106] When calibrating data, it is necessary to ensure that the calibrated data is as consistent as possible with data free from environmental interference. To this end, at least one reference signal is sent and at least one return signal is acquired. By comparing the two, a mapping relationship for calibration can be established. The reference signals are transmitted to different locations in different stations. During calibration, it is necessary to ensure that the difference between the calibrated return signal and the reference signal is small enough. Therefore, it is necessary to characterize the difference between the two. Here, the environmental influence coefficient is used for characterization. Since many reference signals and return signals are involved, the target calibration function is quite difficult to determine. Therefore, by identifying the target elementary functions, a function that maps the return signal to the reference signal can be obtained. However, the target elementary functions are different from each other. Therefore, it is necessary to finally obtain a unified function that can map the return signal to the reference signal with the smallest possible difference. Since the function itself has continuity, among the functions that are combined according to the proportion of the corresponding identification points, there must be a function that meets the requirements. By filtering according to the environmental influence coefficient, the target calibration function can be obtained.

[0107] Obtaining the environmental impact coefficients of the returned calibration signal and the reference signal includes the following steps:

[0108] The feature signal is obtained by subtracting the real-time acquired return signal from the reference signal. Continuous wavelet transform is performed on the characteristic signal to obtain the transform exponent at different time and frequency scales. ;

[0109] in, Indicates the time point of data collection. Indicates the scale parameter. Indicates time parameters;

[0110] Discretize the scale and time parameters to obtain the decomposed transformation exponent matrix. ,in Indicates the first One scale;

[0111] The local energy distribution is calculated for the transformation exponent at each scale, and the calculation expression is as follows:

[0112] ;

[0113] in, This indicates the total number of data collection points. Indicates the first Energy at scale;

[0114] The local nonlinear environmental impact value is calculated at each scale, and the calculation expression is as follows:

[0115] ;

[0116] in, Indicates the first The median of the scaling exponent. This is the self-regulation coefficient. This represents the local nonlinear environmental impact value, and the self-regulation coefficient is set based on experience.

[0117] By varying the fluctuation range of the index at different scales, the environmental impact coefficients at all scales are calculated using the following expression:

[0118] ;

[0119] in, The total number of scales. Indicates the first The ratio of wavelet energy distribution at different scales is calculated using the following expression: , Let A represent the total energy across all scales, and let A represent the environmental impact coefficient.

[0120] When identifying the gap, since the returned signal and the reference signal are not simple numerical values ​​but signal data, the difference obtained by subtracting them is still a signal and cannot be directly judged. Therefore, it is necessary to convert them into numerical values ​​through a series of transformations to characterize the gap. Here, wavelet transform is used to process the signal, decompose it into multiple variables, and obtain the gap by modulo calculation.

[0121] The identification channel simultaneously identifies electrical signals from multiple transformer substations, including the following steps:

[0122] At least one electrical signal is acquired, and the at least one electrical signal is evenly distributed into the identification channel. The identification channel identifies the distributed electrical signals in sequence.

[0123] Identifying the transformer substations that generate noise-reducing signals based on power data identification characteristics includes the following steps:

[0124] The noise reduction voltage is identified from the noise reduction signal, and the station area that generated the noise reduction signal is obtained by using the noise reduction voltage and the identification mechanism.

[0125] Reference Figure 5 As shown, identifying the noise-reduced voltage from the noise-reduced signal includes the following steps:

[0126] To identify the pattern of change, the range of signal variation amplitude, the range of variation speed, the period range, and the phase expression in voltage data or non-voltage data are selected as options for identification.

[0127] Obtain at least one first variation law of voltage from voltage data information, and obtain at least one second variation law of non-voltage data information;

[0128] The first variation rule that is consistent with the second variation rule is deleted from the first variation rule. The noise reduction voltage is identified using the deleted first variation rule. When the signal in the noise reduction signal satisfies all the deleted first variation rules, it is identified as the noise reduction voltage.

[0129] The noise reduction signal contains different data, including voltage and other data. In this solution, the identification of the transformer area mainly depends on voltage. Therefore, it is necessary to identify the noise reduction voltage based on the data pattern of voltage. Since the variation patterns of different types of data are different, a comprehensive judgment can be made based on their value range. For this reason, it is necessary to determine the pattern that is only related to voltage and make the voltage judgment based on it.

[0130] The calibration of the noise reduction signal using the parameter calibration mechanism corresponding to the target station area includes the following steps:

[0131] The noise reduction signal is calibrated using the target calibration function corresponding to the target station area to obtain the parameter calibration signal.

[0132] During calibration, since the environmental influence on the signal is consistent, the parameter calibration mechanism corresponding to the target station area is used to calibrate all signals.

[0133] Furthermore, this solution also proposes a storage medium on which a computer-readable program is stored. When the computer-readable program is invoked, the power data identification method of the power distribution transformer identification instrument described above is executed.

[0134] It is understandable that the storage medium can be a magnetic medium, such as a floppy disk, hard disk, or magnetic tape; an optical medium, such as a DVD; or a semiconductor medium, such as a solid-state drive (SSD).

[0135] In summary, the advantages of this invention are as follows: by forming power data identification features for a transformer substation, establishing a transformer substation identification mechanism, and establishing a parameter calibration mechanism for the transformer substation, it is possible to identify the transformer substation that generates the noise reduction signal based on the power data identification features. Furthermore, by using the parameter calibration mechanism corresponding to the target transformer substation, the noise reduction signal is calibrated to obtain a parameter calibration signal. It can determine the transformer substation from which the data is acquired by forming power data identification features, and identify environmental data based on the characteristics of the transformer substation, thereby forming a calibration mechanism specific to the transformer substation. This allows for different calibrations to be performed according to different transformer substations, ensuring higher accuracy of the parameter calibration signal.

[0136] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention. The scope of protection claimed by the appended claims and their equivalents is defined.

Claims

1. A method for identifying power data using a transformer substation identification device in a power system, characterized in that, include: The voltage data information of at least one transformer area is obtained using a transformer area identification device, and the power data identification features of the transformer area are formed based on the voltage data information. Based on the identification characteristics of power data, an identification mechanism for transformer substations is formed; The transformer area identification device sends at least one reference signal and obtains at least one return signal. Based on the return signal and the identification mechanism, the return signal is associated with the transformer area. Based on the returned signals, the operating environment of the transformer area is identified, and a parameter calibration mechanism is established for the transformer area; The transformer area identification device has at least one built-in identification channel, which can simultaneously identify the electrical signals of multiple transformer areas; When the identification channel is running, the collected electrical signals are filtered and denoised to obtain a denoised signal. Based on the power data identification characteristics, the transformer area that generates the denoised signal is identified as the target transformer area. The noise reduction signal is calibrated using the parameter calibration mechanism corresponding to the target station area to obtain the parameter calibration signal; The identification of the operating environment of the transformer area and the establishment of a parameter calibration mechanism for the transformer area include the following steps: Obtain the target elementary function of the returned signal, which is the elementary function that maps the returned signal to the corresponding reference signal; To return the signal, randomly match identification points to obtain at least one combination of identification points; The target elementary function of at least one returned signal is multiplied by the identification points assigned in the identification point combination and then summed to obtain the preliminary calibration function; The returned signal is input into the pre-calibration function to obtain the returned calibration signal, and the environmental influence coefficient between the returned calibration signal and the reference signal is obtained. The environmental impact coefficients of all returned signals are then summed to obtain the judgment value of the preliminary calibration function; The preliminary calibration function with the smallest judgment value is used as the target calibration function; The process of obtaining the environmental impact coefficients of the returned calibration signal and the reference signal includes the following steps: The feature signal is obtained by subtracting the real-time acquired return signal from the reference signal. Continuous wavelet transform is performed on the characteristic signal to obtain the transform exponent at different time and frequency scales. ; in, Indicates the time point of data collection. Indicates the scale parameter. Indicates time parameters; Discretize the scale and time parameters to obtain the decomposed transformation exponent matrix. ,in Indicates the first One scale; The local energy distribution is calculated for the transformation exponent at each scale, and the calculation expression is as follows: ； in, This indicates the total number of data collection points. Indicates the first Energy at scale; The local nonlinear environmental impact value is calculated at each scale, and the calculation expression is as follows: ； in, Indicates the first The median of the scaling index. This is the self-regulation coefficient. This represents the local nonlinear environmental impact value, and the self-regulation coefficient is set based on experience. By varying the fluctuation range of the index at different scales, the environmental impact coefficients at all scales are calculated using the following expression: ； in, The total number of scales. Indicates the first The wavelet energy distribution ratio at different scales is calculated using the following expression: , Let A represent the total energy across all scales, and let A represent the environmental impact coefficient.

2. The power data identification method of a power distribution transformer identification instrument for a power system according to claim 1, characterized in that, The process of forming power data identification features for a transformer substation based on voltage data information includes the following steps: Voltage data information from the same transformer area is aggregated into a voltage data information set, and the voltage data information set corresponds to the transformer area. Extract voltage phase, voltage amplitude, and the transmission / reception time interval of voltage data from voltage data information; The (0, 1) interval is divided into equal-interval segments to obtain at least one identification point; The identification points are randomly combined to form at least one set of ternary arrays. The identification points in the ternary arrays are sequentially assigned to the voltage phase, voltage amplitude, and transmission / reception time interval. The voltage phase, voltage amplitude, and transmission / reception time interval are multiplied by the assigned identification points to obtain the preliminary voltage phase, preliminary voltage amplitude, and preliminary transmission / reception time interval. Obtain at least one existing elementary function, and randomly combine the at least one elementary function to form at least one combined function, wherein the elementary function is a ternary function; Substituting the preparatory voltage phase, preparatory voltage amplitude, and preparatory transmission / reception time interval into the combination function yields the characteristic values; The maximum and minimum values ​​of the characteristic values ​​corresponding to the voltage data information in the voltage data information set are used as endpoints to form the characteristic interval; By taking the intersection of at least one pairwise feature intervals, at least one target interval can be obtained; The combination function, the preliminary voltage phase, the preliminary voltage amplitude, and the preliminary receiving and transmitting time interval, which are all empty intervals in the target interval, are used as the target function, the target voltage phase, the target voltage amplitude, and the target receiving and transmitting time interval. The target voltage phase, target voltage amplitude, and target transmission / reception time interval are used as power data identification features.

3. The power data identification method of a power distribution transformer identification instrument for a power system according to claim 2, characterized in that, The identification mechanism for transformer substations based on power data identification features includes the following steps: Obtain actual voltage information, and extract actual phase, actual amplitude, and actual transmission / reception time from the actual voltage information; The actual phase, actual amplitude, and actual transmission / reception time are multiplied by the identification points of the target function, target voltage phase, target voltage amplitude, and target transmission / reception time interval, respectively, to obtain the target actual phase, target actual amplitude, and target actual transmission / reception time. Substituting the actual phase, actual amplitude, and actual transmission / reception time of the target into the objective function yields the identification value; The transformer substations that contain the characteristic intervals with identification values ​​are used as the source of actual voltage information.

4. The power data identification method of a power distribution transformer identification instrument for a power system according to claim 3, characterized in that, The method of associating returned signals with transformer substations based on the returned signal and identification mechanism includes the following steps: The voltage data in the returned signal is identified and extracted to obtain the returned voltage phase, returned voltage amplitude, and returned transmission / reception time. The identification mechanism is used to determine the station area that generated the returned signal.

5. The power data identification method of a power distribution transformer area identifier for a power system according to claim 4, characterized in that, The identification channel simultaneously identifies electrical signals from multiple transformer substations, including the following steps: At least one electrical signal is acquired, and the at least one electrical signal is evenly distributed into the identification channel. The identification channel identifies the distributed electrical signals in sequence.

6. The power data identification method of a power distribution transformer area identifier for a power system according to claim 5, characterized in that, The process of identifying the transformer substations that generate noise-reduced signals based on power data identification features includes the following steps: The noise reduction voltage is identified from the noise reduction signal, and the station area that generated the noise reduction signal is obtained by using the noise reduction voltage and the identification mechanism.

7. The power data identification method of a power distribution transformer identification instrument for a power system according to claim 6, characterized in that, The process of identifying the noise-reduced voltage from the noise-reduced signal includes the following steps: To identify the pattern of change, the range of signal variation amplitude, the range of variation speed, the period range, and the phase expression in voltage data or non-voltage data are selected as options for identification. Obtain at least one first variation law of voltage from voltage data information, and obtain at least one second variation law of non-voltage data information; The first variation rule that is consistent with the second variation rule is deleted from the first variation rule. The noise reduction voltage is identified using the deleted first variation rule. When the signal in the noise reduction signal satisfies all the deleted first variation rules, it is identified as the noise reduction voltage.

8. The power data identification method of a power distribution transformer identification instrument for a power system according to claim 7, characterized in that, The calibration of the noise reduction signal using the parameter calibration mechanism corresponding to the target station area includes the following steps: The noise reduction signal is calibrated using the target calibration function corresponding to the target station area to obtain the parameter calibration signal.

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