Virtual clock calibration method and device for power distribution network, terminal equipment and storage medium
By performing multi-band filtering and autocorrelation calculations on the power distribution network signals, generating confidence scores and performing weighted fusion, the problem of poor accuracy in virtual clock calibration under event-free conditions is solved, and high-precision time synchronization is achieved.
Patent Information
- Application Number
- CN202511672855.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-14
- Publication Date
- 2026-02-06
AI Technical Summary
Existing virtual clock calibration methods for power distribution networks suffer from poor accuracy when no events occur, leading to the accumulation of synchronization errors and affecting the accuracy and reliability of traveling wave fault location.
By acquiring the power signal from the distribution network, the signal is decomposed into frequency band signals of different frequencies using a multi-band filter. Autocorrelation is performed to generate confidence scores. Weighted fusion is then performed based on the confidence scores to obtain the fused time delay. The future time delay trend is obtained through fitting. The external time signal or the future time delay trend is used as a virtual clock reference for calibration.
In the absence of external events, the calibration accuracy of the virtual clock in the distribution network is improved, the impact of noise on delay estimation is reduced, and the accuracy of time synchronization is ensured.
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Figure CN121477573A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to the technical field of power distribution network, and particularly relates to a virtual clock calibration method and device for power distribution network, a terminal device and a storage medium. BACKGROUND
[0002] In modern power distribution networks, traveling wave fault location technology is widely researched and applied, and the premise is that each measurement point has high-precision time synchronization. The most common synchronization method at present is to rely on global navigation satellite system (GNSS) time service combined with local crystal oscillator counting. However, when GNSS signals are affected by bad weather, building shielding, electromagnetic interference or human interference, short-term interruption or precision decline may occur, which will directly affect the accuracy and reliability of traveling wave fault location. The existing technology usually corrects the clock deviation of the power distribution network through external trigger events (such as natural traveling waves, operating waves, etc.), but in the case of no event occurring for a long time, the system clock may gradually drift, resulting in synchronization error accumulation. Therefore, the existing virtual clock calibration method for power distribution network has the problem of poor accuracy when no event occurs. SUMMARY
[0003] The present application provides a virtual clock calibration method and device for power distribution network, a terminal device and a storage medium, which can solve the problem of poor accuracy of the existing virtual clock calibration method for power distribution network when no event occurs.
[0004] The virtual clock calibration method for power distribution network provided by the present application comprises the following steps: acquiring power signals of each moment of the power distribution network; decomposing the power signals into several band signals of different frequencies through a multi-band filter; performing autocorrelation operation on each band signal, and generating a confidence level of each band signal based on the autocorrelation operation result; obtaining the importance of each band signal according to the confidence level, and then taking the importance of all band signals at the current moment as a weight to perform weighted fusion on each band signal, and obtaining the fusion time delay of the power signal at the current moment; sequencing the fusion time delay corresponding to each moment of the power signal according to the time sequence, and obtaining the time delay sequence of the power distribution network; fitting the time delay sequence to obtain the future time delay trend of the power distribution network; judging the external time service signal: if the external time service signal is normal, taking the external time service signal as the reference of the virtual clock; if the external time service signal is abnormal, taking the future time delay trend as the reference of the virtual clock.
[0005] Further, the frequency band signals include a power fundamental component signal in a first frequency range, a plurality of harmonic component signals in a second frequency range, and a high-frequency background noise component signal in a third frequency range.
[0006] Further, the autocorrelation operation on each of the frequency band signals includes: Periodic characteristics and peak value information of each of the frequency band signals are extracted through the autocorrelation algorithm; The periodic characteristics and the peak value information are screened to obtain signal-to-noise ratio data, autocorrelation peak position, and autocorrelation peak strength information, and the signal-to-noise ratio data, the autocorrelation peak position, and the autocorrelation peak strength information are taken as autocorrelation operation results.
[0007] Further, the confidence level of each of the frequency band signals is generated based on the autocorrelation operation results, including: The confidence level of each of the frequency band signals is calculated according to the signal-to-noise ratio data and the autocorrelation peak strength information by substituting into a confidence level calculation formula.
[0008] Further, the signal-to-noise ratio data includes a current signal-to-noise ratio value and a maximum signal-to-noise ratio value, and the autocorrelation peak strength information includes a current autocorrelation peak strength and a maximum autocorrelation peak strength; the confidence level calculation formula includes: In the formula, is the confidence level, is the current autocorrelation peak strength, is the current signal-to-noise ratio value, is the maximum autocorrelation peak strength, is the maximum signal-to-noise ratio value, , are weight coefficients of different indicators, and .
[0009] Further, the importance of each frequency band signal is obtained according to the confidence level, including: taking the confidence level as a weight, taking the autocorrelation peak position of the frequency band signal corresponding to the confidence level as a time delay, multiplying the time delay by the weight to obtain the importance of each frequency band signal.
[0010] Further, the future time delay trend of the power distribution network is obtained by fitting the time delay sequence, including: The time delay sequence is decomposed through a sliding window algorithm to obtain a fixed offset and a time drift of the time delay sequence; The fixed offset and the time drift of the time delay sequence are fitted through a linear regression method to obtain the future time delay trend of the power distribution network.
[0011] The application further provides another embodiment of a virtual clock calibration device for a power distribution network, comprising a data acquisition module, a data decomposition module, a data calculation module, a weighted fusion module, a sequence generation module, a data fitting module and a result generation module. The data acquisition module is configured to acquire power signals of the power distribution network at each time point. The data decomposition module is configured to decompose the power signals into band signals of different frequencies through a multi-band filter. The data calculation module is configured to perform autocorrelation operation on each band signal and generate a confidence level of each band signal based on the autocorrelation operation result. The weighted fusion module is configured to obtain an importance degree of each band signal according to the confidence level, and then perform weighted fusion on each band signal by taking the importance degrees of all band signals at the current time point as weights to obtain a fusion time delay of the power signal at the current time point. The sequence generation module is configured to sort the fusion time delays corresponding to the power signals at each time point in chronological order to obtain a time delay sequence of the power distribution network. The data fitting module is configured to fit the time delay sequence to obtain a future time delay trend of the power distribution network. The result generation module is configured to judge an external time signal, and if the external time signal is normal, take the external time signal as a reference of the virtual clock, and if the external time signal is abnormal, take the future time delay trend as the reference of the virtual clock.
[0012] The application further provides another embodiment of a terminal device, comprising a processor, a memory and a computer program stored in the memory and configured to be executed by the processor, wherein the processor implements the steps of the virtual clock calibration method for the power distribution network provided by the application when executing the computer program.
[0013] The application further provides another embodiment of a computer readable storage medium, comprising a stored computer program, wherein the computer program controls a device where the computer readable storage medium is located to execute the steps of the virtual clock calibration method for the power distribution network provided by the application when running.
[0014] The application has the following beneficial effects: The application discloses a virtual clock calibration method for a power distribution network. BRIEF DESCRIPTION OF DRAWINGS
[0015] In order to more clearly illustrate the technical solutions of the present application, the following will briefly introduce the drawings needed in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without any creative effort.
[0016] Figure 1 FIG. 1 is a flowchart of a virtual clock calibration method for a power distribution network according to an embodiment of the present application; Figure 2 FIG. 2 is a structural diagram of a virtual clock calibration device for a power distribution network according to an embodiment of the present application; Figure 3 FIG. 3 is a fused time delay sliding window least square fitting diagram according to an embodiment of the present application. DETAILED DESCRIPTION
[0017] In order to make the purpose, technical solutions and advantages of the present application clearer, the technical solutions in the present application will be described clearly and completely in the following with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without any creative effort are within the protection scope of the present application.
[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of this application; the use of the terms "including," "comprising," or "having" and variations thereof herein is intended to be broad and encompass the terms "consisting of" and "consisting essentially of" and variations thereof. Unless otherwise required by context, singular terms shall include pluralities and vice versa. Unless otherwise required by context, the use herein of the singular is also to be construed as a use of the plural and vice versa.
[0019] In the description of the embodiments of the present application, the technical terms "first", "second", etc. are only used to distinguish different objects, and cannot be understood as indicating or implying relative importance or implicitly indicating the number, specific order or primary and secondary relationship of the indicated technical features. In the description of the embodiments of the present application, the meaning of "multiple" is more than two, unless otherwise explicitly specified.
[0020] Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearance of the phrase in various places in the specification does not necessarily all refer to the same embodiment, nor is it necessarily independent or alternative embodiments to each other. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.
[0021] In the description of the embodiments of the present application, the term "and / or" is only a description of the association relationship of the associated objects, which means that there can be three relationships, for example, A and / or B, which can represent the three cases of A alone, A and B together, and B alone. In addition, the character " / " in this paper generally represents that the front and rear associated objects are a "or" relationship.
[0022] In the description of the embodiments of the present application, the term "multiple" refers to more than two (including two), and similarly, "multiple groups" refers to more than two groups (including two groups), and "multiple pieces" refers to more than two pieces (including two pieces).
[0023] In the description of the embodiments of the present application, unless otherwise explicitly specified and limited, the technical terms "mounting", "connecting", "connecting", "fixing" and the like should be broadly understood, for example, it can be fixedly connected, or it can be detachably connected, or it can be integrated; it can be mechanical connection, or it can be electrical connection; it can be directly connected, or it can be indirectly connected through an intermediate medium; it can be the internal communication of two elements or the interaction relationship between two elements. For those skilled in the art, the specific meaning of the above terms in the embodiments of the present application can be understood according to the specific circumstances.
[0024] Reference Figure 1To solve the problem of poor accuracy of the virtual clock calibration method for the power distribution network in the prior art when no event occurs, an embodiment of the present application provides a virtual clock calibration method for a power distribution network, comprising: 101. Obtain a power signal of the power distribution network at each moment.
[0025] 102. Decompose the power signal into several frequency band signals of different frequencies through a multi-band filter.
[0026] In the embodiment, the frequency band signals include a power frequency fundamental component signal in a first frequency range, several harmonic component signals in a second frequency range, and a high-frequency background noise component signal in a third frequency range.
[0027] In a specific embodiment, the decomposition mode of the multi-band filter is realized by at least one of a wavelet packet decomposition, a band-pass filtering, or an empirical mode decomposition.
[0028] In a specific embodiment, the power signal collected at the measuring point is decomposed into the power frequency fundamental component signal, the several harmonic component signals, and the high-frequency background noise component signal through the multi-band filter. In the embodiment, the wavelet packet decomposition method is used to perform multi-band decomposition on the collected signal to obtain the 50 Hz (i.e., the first frequency range in the present application) power frequency fundamental component signal, the 150 Hz (i.e., the second frequency range in the present application) third-order harmonic component signal, and the 5-20 kHz (i.e., the third frequency range in the present application) high-frequency background noise component signal.
[0029] 103. Perform autocorrelation operation on each of the frequency band signals, and generate a confidence level of each of the frequency band signals based on the autocorrelation operation result.
[0030] In the embodiment, the autocorrelation operation on each of the frequency band signals comprises: extracting periodic characteristics and peak value information of each of the frequency band signals through an autocorrelation algorithm; screening the periodic characteristics and the peak value information to obtain signal-to-noise ratio data, autocorrelation peak position, and autocorrelation peak intensity information, and taking the signal-to-noise ratio data, the autocorrelation peak position, and the autocorrelation peak intensity information as the autocorrelation operation result.
[0031] In a specific embodiment, the autocorrelation algorithm includes a fast Fourier transform-based autocorrelation method or an improved autocorrelation method based on phase accumulation, and the autocorrelation algorithm extracts the periodic characteristics and the peak value information of the frequency band signal to improve the reliability of time delay estimation.
[0032] In the embodiment, the generation of the confidence level of each of the frequency band signals based on the autocorrelation operation result comprises: Based on the signal-to-noise ratio data and the autocorrelation peak intensity information, the confidence level of each frequency band signal is calculated by substituting them into the confidence calculation formula.
[0033] In this embodiment, the signal-to-noise ratio (SNR) data includes: the current SNR value and the maximum SNR value; the autocorrelation peak intensity information includes: the current autocorrelation peak intensity and the maximum autocorrelation peak intensity; the confidence calculation formula includes: In the formula, For confidence level, The current autocorrelation peak intensity, This is the current signal-to-noise ratio value. The maximum autocorrelation peak intensity, This is the maximum signal-to-noise ratio value. , These are the weighting coefficients for different indicators, and .
[0034] 104. Based on the confidence level, obtain the importance of each frequency band signal, and then use the importance of all frequency band signals at the current moment as weights to perform weighted fusion of each frequency band signal to obtain the fusion delay of the power signal at the current moment.
[0035] In this embodiment, obtaining the importance of each frequency band signal based on the confidence level includes: using the confidence level as a weight, using the autocorrelation peak position of the frequency band signal corresponding to the confidence level as a time delay, and multiplying the time delay by the weight to obtain the importance of each frequency band signal.
[0036] In a specific embodiment, to better illustrate how the fusion latency is obtained, see the following example: Within a set 50ms time window, autocorrelation calculations were performed on signals in each frequency band, and the autocorrelation peak and its amplitude were extracted to determine the reliability of the time delay information for that frequency band. The autocorrelation analysis yielded the following results: the peak position of the power frequency fundamental component signal (i.e., the autocorrelation peak position described in this invention) was 0.5μs, with a peak intensity of 0.90; the peak position of the third harmonic component signal was 0.7μs, with a peak intensity of 0.72; and the peak position of the high-frequency background noise component signal was 0.9μs, with a peak intensity of 0.55. A higher autocorrelation peak value indicates more reliable time delay information for that frequency band.
[0037] The SNR data and autocorrelation peak intensity information are substituted into the confidence calculation formula to generate the confidence, and the confidence is used as the weight: the fundamental component signal is 0.50, the third harmonic component signal is 0.30, and the high-frequency background noise component signal is 0.20. The higher the confidence of the frequency band, the greater the weight in the fusion calculation, which can effectively suppress the influence of noise on time delay estimation.
[0038] The fusion time delay is μs, thereby synthesizing the contributions of different frequency band signals and reducing the deviation caused by high-frequency noise.
[0039] 105. In chronological order, sort the fusion time delay corresponding to the power signal at each time to obtain a time delay sequence of the power distribution network.
[0040] 106. Fit the time delay sequence to obtain a future time delay trend of the power distribution network.
[0041] In this embodiment, fitting the time delay sequence to obtain a future time delay trend of the power distribution network comprises: decomposing the time delay sequence by a sliding window algorithm to obtain a fixed offset and a time drift of the time delay sequence; fitting the fixed offset and the time drift of the time delay sequence by a linear regression method to obtain the future time delay trend of the power distribution network.
[0042] In a specific embodiment, the linear regression method uses a least squares regression algorithm to correct short-term synchronization errors caused by time drift.
[0043] In a specific embodiment, the fused time delay sequence is statistically modeled by a sliding window algorithm to decompose it into a fixed offset and a time drift, and a linear regression method is used to fit the future drift trend. In this embodiment, a 500ms sliding window is used to calculate a fused time delay sequence containing 10 elements (0.64, 0.66, 0.67, 0.69, 0.72, 0.74, 0.75, 0.77, 0.79, 0.81) (unit: μs), and a linear regression method is used to fit, as shown in FIG. 6, to obtain a fixed offset of 0.64 μs and a drift rate of 0.38 μs / s. The linear regression is used to predict the drift of the next 100ms to obtain a drift prediction of about 0.85 μs, which provides a basis for virtual calibration. Figure 3
[0044] 107. Determine the external time signal: if the external time signal is normal, use the external time signal as the reference of the virtual clock; if the external time signal is abnormal, use the future time delay trend as the reference of the virtual clock.
[0045] In a specific embodiment, if the external time synchronization signal experiences a short-term error or fails, it can be considered that the external time synchronization signal is abnormal.
[0046] like Figure 2 As shown, based on the above method embodiments, corresponding apparatus embodiments are provided; An embodiment of the present invention provides a virtual clock calibration device for a power distribution network, comprising: a data acquisition module 201, a data decomposition module 202, a data calculation module 203, a weighted fusion module 204, a sequence generation module 205, a data fitting module 206, and a result generation module 207. The data acquisition module is used to acquire the power signal of the power distribution network at every moment; The data decomposition module is used to decompose the power signal into several frequency band signals of different frequencies through a multi-band filter. The data calculation module is used to perform autocorrelation calculation on each frequency band signal and generate the confidence level of each frequency band signal based on the autocorrelation calculation result. The weighted fusion module is used to obtain the importance of each frequency band signal based on the confidence level, and then use the importance of all frequency band signals at the current moment as weights to perform weighted fusion on each frequency band signal to obtain the fusion delay of the power signal at the current moment. The sequence generation module is used to sort the fusion delay corresponding to the power signal at each moment according to the chronological order to obtain the delay sequence of the distribution network. The data fitting module is used to fit the time delay sequence to obtain the future time delay trend of the power distribution network; The result generation module is used to judge the external time signal: if the external time signal is normal, the external time signal is used as the reference of the virtual clock; if the external time signal is abnormal, the future delay trend is used as the reference of the virtual clock.
[0047] It is understood that the above-described device embodiments correspond to the method embodiments of the present invention, and can implement the virtual clock calibration method for power distribution networks provided by any of the above-described method embodiments of the present invention.
[0048] It should be noted that the device embodiments described above are merely illustrative, and some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, in the accompanying drawings of the device embodiments provided by this invention, the connection relationships between modules indicate that they have communication connections, which can specifically be implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement this without any creative effort.
[0049] On the basis of the above-mentioned embodiment of the virtual clock calibration method for power distribution network, another embodiment of the present application provides a terminal device, which comprises a processor, a memory and a computer program stored in the memory and configured to be executed by the processor, and when the processor executes the computer program, the virtual clock calibration method for power distribution network of any one of the embodiments of the present application is realized.
[0050] For example, in this embodiment, the computer program can be divided into one or more modules, which are stored in the memory and executed by the processor to complete the present application. The one or more modules can be a series of computer program instruction segments capable of completing a specific function, which are used to describe the execution process of the computer program in the terminal device.
[0051] The terminal device can be a desktop computer, a notebook computer, a palm computer, a cloud server and other computing devices. The terminal device can include, but is not limited to, a processor and a memory.
[0052] The processor can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor, etc. The processor is the control center of the terminal device, and connects all parts of the terminal device through various interfaces and lines.
[0053] On the basis of the above-mentioned method embodiment, another embodiment of the present application provides a computer readable storage medium, which comprises a stored computer program, wherein when the computer program runs, the device where the computer readable storage medium is located executes the virtual clock calibration method for power distribution network of any one of the above-mentioned method embodiments of the present application.
[0054] The modules / units integrated in the device / terminal equipment, if realized in the form of software function units and sold or used as independent products, can be stored in a computer readable storage medium. Based on this understanding, all or part of the processes in the above-mentioned embodiment methods can also be completed by a computer program instructing related hardware, and the computer program can be stored in a computer readable storage medium. When the computer program is executed by a processor, the steps of each method embodiment can be implemented. The computer program includes computer program code, which can be in the form of source code, object code, executable files or some intermediate forms, etc. The computer readable medium can include any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal and software distribution medium, etc.
[0055] The above is the preferred embodiment of the present application. It should be pointed out that for those skilled in the art, without departing from the principles of the present application, a number of improvements and refinements can be made, which are also considered within the scope of protection of the present application.
Claims
1. A method for virtual clock calibration for power distribution networks, characterized in that, The method comprises the following steps: acquiring power signals of a power distribution network at each time point; decomposing the power signals into band signals of different frequencies through a multi-band filter; performing autocorrelation operation on each band signal, and generating a confidence level of each band signal based on the autocorrelation operation result; obtaining an importance degree of each band signal according to the confidence level, and then weighting and fusing each band signal by taking the importance degrees of all band signals at the current time point as weights to obtain a fusion time delay of the power signal at the current time point; sequentially sorting the fusion time delays corresponding to the power signals at each time point to obtain a time delay sequence of the power distribution network; fitting the time delay sequence to obtain a future time delay trend of the power distribution network; judging an external time signal: if the external time signal is normal, taking the external time signal as a reference of a virtual clock; and if the external time signal is abnormal, taking the future time delay trend as the reference of the virtual clock. The band signals comprise a fundamental wave component signal in a first frequency range, a plurality of harmonic component signals in a second frequency range, and a high-frequency background noise component signal in a third frequency range.
2. The method for virtual clock calibration of an electric distribution network of claim 1, wherein, The autocorrelation operation on each band signal comprises the following steps:
3. The method for virtual clock calibration of an electric distribution network according to claim 2, characterized in that, extracting periodic characteristics and peak value information of each band signal through an autocorrelation algorithm; screening the periodic characteristics and the peak value information to obtain signal-to-noise ratio data, autocorrelation peak position and autocorrelation peak strength information, and taking the signal-to-noise ratio data, the autocorrelation peak position and the autocorrelation peak strength information as the autocorrelation operation result. The confidence level of each band signal is generated based on the autocorrelation operation result, which comprises the following steps:
4. The method for virtual clock calibration of an electric distribution network according to claim 3, characterized in that, substituting the signal-to-noise ratio data and the autocorrelation peak strength information into a confidence level calculation formula to calculate the confidence level of each band signal. The signal-to-noise ratio data comprises a current signal-to-noise ratio value and a maximum signal-to-noise ratio value; the autocorrelation peak strength information comprises a current autocorrelation peak strength and a maximum autocorrelation peak strength; and the confidence level calculation formula comprises:
5. The method for virtual clock calibration of an electric distribution network according to claim 4, characterized in that, The importance degree of each band signal is obtained according to the confidence level, which comprises the following steps: taking the confidence level as a weight, taking the autocorrelation peak position of the confidence level corresponding band signal as a time delay, multiplying the time delay by the weight to obtain the importance degree of each band signal. In the formula, is the confidence, is the current autocorrelation peak value intensity, is the current signal-to-noise ratio value, is the maximum autocorrelation peak value intensity, is the maximum signal-to-noise ratio value, , are weight coefficients of different indexes respectively, and .
6. The method for virtual clock calibration of an electric distribution network of claim 5, wherein, The future time delay trend of the power distribution network is obtained by fitting the time delay sequence, which comprises the following steps:
7. The method for virtual clock calibration of an electric distribution network according to claim 6, characterized in that, decomposing the time delay sequence through a sliding window algorithm to obtain a fixed offset and a time drift of the time delay sequence; fitting the fixed offset and the time drift of the time delay sequence through a linear regression method to obtain the future time delay trend of the power distribution network. The method comprises the following steps:
8. A virtual clock calibration apparatus for a power distribution network, characterized by, a data acquisition module, a data decomposition module, a data calculation module, a weighting fusion module, a sequence generation module, a data fitting module and a result generation module; the data acquisition module is used to acquire power signals of a power distribution network at each time point; the data decomposition module is used to decompose the power signals into band signals of different frequencies through a multi-band filter; The data calculation module is configured to perform autocorrelation operation on each of the frequency band signals, and generate a confidence level of each of the frequency band signals based on a result of the autocorrelation operation; The weighted fusion module is configured to obtain an importance degree of each of the frequency band signals according to the confidence level, and then perform weighted fusion on each of the frequency band signals by taking the importance degrees of all the frequency band signals at the current moment as weights to obtain a fusion time delay of the power signal at the current moment; The sequence generation module is configured to sort the fusion time delays corresponding to the power signals at each moment in chronological order to obtain a time delay sequence of the power distribution network; The data fitting module is configured to fit the time delay sequence to obtain a future time delay trend of the power distribution network; The result generation module is configured to judge an external time signal: if the external time signal is normal, taking the external time signal as a reference of the virtual clock; if the external time signal is abnormal, taking the future time delay trend as the reference of the virtual clock. A computer program product comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor implements the method for calibrating a virtual clock of a power distribution network according to any one of claims 1-7 when executing the computer program.
9. A terminal device, comprising: The computer program product comprises:
10. A computer-readable storage medium, characterized in that, a stored computer program, wherein the computer program controls a device where the computer readable storage medium is located to implement the method for calibrating a virtual clock of a power distribution network according to any one of claims 1-7 when the computer program is running.