High-reliability fault recording acquisition method and device based on centralized research and judgment of power distribution master station

Abstract

The invention provides a high-reliability fault recording acquisition method and device based on centralized research and judgment of a power distribution master station, and the device comprises an aviation plug wire serial connection module which is adaptive to a serial connection cable interface of an on-site primary switch and an FTU (Feeder Terminal Unit); the fault wave recording module is used for acquiring electric quantity waveform data such as voltage and current of a feeder line when the field electric quantity reaches a wave recording condition; the fault recording strengthening module is used for strengthening fault waveform characteristics in combination with wavelet threshold noise reduction and based on a deep learning waveform noise reduction technology; the wave recording file storage module is used for storing the original waveform and the waveform after fault feature enhancement; the wave recording file compression module is used for compressing the wave recording file to obtain a waveform file with a smaller memory; the wave recording file uploading module supports uploading the compressed wave recording file to a master station; and the wireless communication module establishes a wireless communication 104 protocol channel, so that the limitation that 101 protocols are adopted by part of old terminals is solved, and the data transmission rate and stability are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power distribution automation, in particular to a high-reliability fault recording wave collection method and device based on centralized research and judgment of a power distribution master station. BACKGROUND

[0002] In the fault positioning and research of a power distribution network, a power distribution master station centrally researches and analyzes the grounding fault of the power distribution network by collecting voltage, current and other recording wave data from a feeder terminal (FTU), wherein the fault recording wave data of the feeder terminal is a core link of the centralized research and analysis of the master station. However, due to problems such as software version defects, aging of recording wave modules or inability of hardware performance to adapt to the latest software program of the current part of the inventory terminal, the recording wave function is abnormal, data uploading is delayed or invalid, which cannot meet the requirements of high-precision recording wave and timely and intact transmission of the centralized research and judgment algorithm of the master station grounding fault, and affects the accuracy of the fault positioning and analysis of the master station of the power distribution network. The centralized research accuracy of the master station of the power distribution network needs to be improved. Since the current inventory terminal has not reached the equipment retirement age and cannot be replaced in batches, the existing solutions mostly rely on terminal software upgrade or hardware module replacement, but this method has defects such as large amount of reconstruction engineering, long implementation period and poor compatibility of software and hardware. SUMMARY

[0003] Therefore, the purpose of the present application is to provide a high-reliability fault recording wave collection method and device based on centralized research and judgment of a power distribution master station, which is used to solve the problems of non-starting of the fault recording wave function of the inventory terminal, delay of waveform uploading, and incompatibility of the latest version of hardware and software. The method and device collect line fault waveform signals by connecting an independent recording wave collection device between a switch and a feeder terminal (FTU), and enhance the uploading to the power distribution master station, solve the problem of abnormal recording wave function of the terminal that cannot be uploaded to the power distribution master station, ensure complete collection and real-time uploading of fault waveforms, effectively enhance the recording wave function of old terminals, guarantee the reliability of old terminals participating in the centralized research and judgment of the master station, and strongly support the technology of centralized research and judgment of the master station fault.

[0004] To achieve the above purpose, the present application adopts the following technical solution: a high-reliability fault recording wave collection method based on centralized research and judgment of a power distribution master station, comprising the following steps:

[0005] Step S1: When a fault occurs in the power grid, collect the fault recording wave data of the feeder as soon as the recording wave collection device meets the recording wave condition;

[0006] Step S2: After collecting the fault recording wave signal, enhance the collected fault waveform by wavelet threshold denoising and artificial intelligence waveform enhancement method;

[0007] Step S3: setting two memory equal storage space A, storage space B, storage module automatically stores the corresponding fault waveform in storage space A, storage space B, wherein storage space A stores the fault waveform original waveform, and storage space B is used for storing the enhanced fault waveform; if necessary, the power distribution master station checks the difference between the enhanced waveform and the original waveform;

[0008] Step S4: by reducing the fault waveform file memory space, the fault waveform upload speed is improved while the distortion degree of the compressed waveform is not increased;

[0009] Step S5: after receiving the fault recording wave calling instruction of the master station, the wireless communication module is used to transmit the fault waveform file to the power distribution master station by using the latest protocol, and the master station is assisted to realize fault centralized research and judgment.

[0010] In a preferred embodiment, in step S1, the fault recording wave signal contains line phase voltage, phase current, zero sequence voltage and zero sequence current and other characteristic waveforms, and the fault recording wave trigger condition is zero sequence voltage mutation.

[0011] In a preferred embodiment, step S2 specifically includes the following steps:

[0012] Step S2-1: the fault waveform containing noise is decomposed by wavelet transform multi-scale, and a certain fault recording wave signal collected is f(n), n=0, 1,..., N-1, wherein N is the length of the fault recording wave signal, a suitable small base wave and a decomposition scale j are selected to perform wavelet multi-scale decomposition on the fault recording wave signal f(n), and wavelet decomposition coefficients W j,k at each scale are obtained.

[0013]

[0014] In the formula, n is a discrete signal, j is a decomposition scale, k is a decomposition position, and ψ is a wavelet function.

[0015] Step S2-2: the wavelet decomposition coefficient W j,k is threshold processed to obtain The threshold processing formula is

[0016]

[0017] In the formula, is the wavelet coefficient after threshold processing, sgn is a sign function, λ is a threshold value, σ is a standard deviation of fault recording wave noise, and N is the length of the fault recording wave signal.

[0018] Step S2-3: the is inverse wavelet transformed to obtain the noise-reduced fault recording wave signal

[0019] Step S2-4: AI deep enhancement of the processed signal The input deep neural network model further suppresses periodic interference and repairs distorted waveforms, enhances waveform features and recognition, and finally obtains the enhanced waveforms.

[0020] In a preferred embodiment, in step S5, the latest transmission protocol indicates that the 101 protocol and the 104 protocol conversion function are provided, and the 104 protocol is used for data exchange with the power distribution master station, solving the limitations of the old terminal using the 101 protocol.

[0021] In a preferred embodiment, in step S5, the centralized research and judgment indicates that the field power distribution terminal uploads all fault recording files to the power distribution master station, the power distribution master station extracts waveform features of each terminal for analysis through a research and judgment algorithm, determines the fault type and the line where the fault occurs, and finally gives the corresponding isolation and recovery strategy.

[0022] The application also provides a high-reliability fault recording acquisition device based on centralized research and judgment of a power distribution master station, which runs the high-reliability fault recording acquisition method based on centralized research and judgment of a power distribution master station.

[0023] In a preferred embodiment, when a fault occurs in the distribution network, the fault recording module acquires fault recording data of the feeder as soon as the recording condition of the recording acquisition device is met.

[0024] In a preferred embodiment, the fault recording enhancement module enhances the collected fault waveforms through wavelet threshold denoising and artificial intelligence waveform enhancement methods.

[0025] In a preferred embodiment, the recording file storage module has two memory equal storage spaces A and B.

[0026] The recording file compression module compresses the memory space of the fault waveform file.

[0027] In a preferred embodiment, after receiving the recording call instruction of the master station, the recording file uploading module transmits the fault waveform file to the power distribution master station using the latest protocol through the wireless communication module.

[0028] Compared with the prior art, the application has the following beneficial effects:

[0029] 1) Improve the integrity and quality of fault waveform data, and ensure the accuracy of research and judgment: through the design of dual storage space to realize the redundant backup and dynamic optimization of fault waveform, ensure the complete retention of original data and enhance the traceability of the version, effectively solve the problem of data loss caused by abnormal recording function of traditional terminal. Combined with wavelet threshold denoising and AI deep enhancement technology, the noise interference is reduced while the waveform distortion is repaired, which significantly improves the recognition of fault characteristics, so that the main station can obtain higher quality fault waveform, and provide reliable data basis for subsequent accurate research and judgment.

[0030] 2) Enhance system compatibility and transmission efficiency, support centralized research and judgment of rapid response: through aviation plug stringing and compatibility with original electrical interface, realize plug and play, avoid large-scale modification of existing power distribution terminal (FTU), reduce deployment cost. The protocol conversion function (101 to 104) solves the problem of difficult change of old terminal communication protocol, uses the high speed and stability of 104 protocol, ensures that the enhanced waveform data is efficiently uploaded to the main station. From data acquisition, processing to transmission whole process optimization, ensure the timeliness and accuracy of fault research and judgment, reduce the risk of misjudgment. BRIEF DESCRIPTION OF DRAWINGS

[0031] Fig. 1 The device framework schematic diagram of the preferred embodiment of the application;

[0032] Fig. 2 The wavelet threshold denoising flowchart in the recording wave acquisition method of the preferred embodiment of the application. DETAILED DESCRIPTION

[0033] The application will be further described below in conjunction with the drawings and examples.

[0034] It should be noted that the following detailed description is all exemplary and is intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as generally understood by those skilled in the art to which the present application belongs.

[0035] It should be noted that the terms used herein are only for the purpose of describing the specific embodiments, and are not intended to limit the exemplary embodiments according to the present application; as used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form, and furthermore, it should be understood that when the terms "comprise" and / or "include" are used in the specification, there is a feature, step, operation, device, component and / or combination thereof.

[0036] A high-reliability fault recording wave acquisition method and device based on power distribution main station centralized research and judgment, by stringing an independent recording wave acquisition device between the switch and the feeder terminal (FTU), completing the intelligent transformation of the existing old terminal, ensuring the complete acquisition and real-time uploading of fault waveform.

[0037] In view of the problems of non-enabled fault recording function of inventory terminal, waveform sending delay, and non-adapted software and hardware version, the independent fault recording collection device is connected in series between the switch and the feeder terminal (FTU), the fault recording function is bypassed, and the complete collection and real-time sending of the fault waveform are ensured.

[0038] To achieve the above object, as shown in Figs. 1-2 The present example provides a high-reliability fault recording collection method and device based on centralized research and judgment of the power distribution master station. The method is aimed at the problems of non-enabled fault recording function of inventory terminal, waveform sending delay, and non-adapted software and hardware version. The independent fault recording collection device is connected in series between the switch and the feeder terminal, the noise of the fault recording signal is reduced, the fault recording signal is enhanced, the complete collection and real-time sending of the fault waveform are ensured, and the accuracy of the centralized research and judgment of the power distribution master station is improved. Specifically, the following steps are included:

[0039] Step S1: When a fault occurs in the distribution network, once the fault recording condition of the fault recording collection device is met, the fault recording module of the fault recording collection device collects the fault recording data of the feeder;

[0040] Step S2: After the fault recording collection device collects the fault recording signal, the fault recording strengthening module enhances the collected fault waveform by using the wavelet threshold denoising and artificial intelligence waveform strengthening methods;

[0041] Step S3: The storage module of the fault recording collection device has two memory equal storage spaces A and B built-in. The storage module automatically stores the corresponding fault waveform into the storage spaces A and B. The storage space A stores the original fault waveform for reference, and the storage space B is used to store the enhanced fault waveform. If necessary, the power distribution master station checks the difference between the enhanced waveform and the original waveform, and checks the strengthening module.

[0042] Step S4: The fault recording file compression module uses a fast and reliable compression technology to reduce the memory space of the fault waveform file, improve the uploading speed of the fault waveform, and ensure that the distortion of the compressed waveform does not increase;

[0043] Step S5: After receiving the fault recording call instruction from the master station, the fault recording sending module uses the wireless communication module to transmit the fault waveform file to the power distribution master station according to the latest protocol, and assists the master station to realize the centralized research and judgment of the fault.

[0044] The fault recording collection device is connected in series between the switch and the FTU through an aviation plug, and is completely compatible with the original interface in terms of physical layer and electrical parameters. The fault recording collection device includes a fault recording module, a fault recording strengthening module, a fault recording file storage module, a fault recording file compression module, a fault recording file sending module, and a wireless communication module.

[0045] In step S1, the fault recording signal contains characteristic waveforms such as line phase voltage, phase current, zero sequence voltage and zero sequence current, and the fault recording trigger condition is zero sequence voltage mutation.

[0046] Step S2 specifically includes the following steps:

[0047] Step S2-1: The noise-containing fault waveform is decomposed by wavelet transform multi-scale, and a certain fault recording signal collected is f(n), n=0, 1,..., N-1, wherein N is the length of the fault recording signal, a suitable wavelet and decomposition scale j are selected to perform wavelet multi-scale decomposition on the fault recording signal f(n), and wavelet decomposition coefficients W j,k

[0048]

[0049] Step S2-2: The wavelet decomposition coefficients W j,k are threshold processed to obtain The threshold processing formula is

[0050]

[0051] In the formula, is the wavelet coefficient after threshold processing, sgn is a sign function, λ is a threshold value, σ is a standard deviation of fault recording noise, and N is the length of the fault recording.

[0052] Step S2-3: The is inverse wavelet transformed to obtain a noise-reduced fault recording signal

[0053] Step S2-4: The AI deepens the signal processed by the wavelet It is input into a deep neural network model to further suppress periodic interference and repair distorted waveforms, enhance waveform features and their recognition, and finally obtain the enhanced waveform.

[0054] In step S5, the latest transmission protocol indicates that the fault recording collection device has a 101 protocol and a 104 protocol conversion function, the fault recording collection device and the power distribution master station exchange data using the 104 protocol, solve the limitations of some old terminals using the 101 protocol, and improve the rate and stability of transmission data.

[0055] In step S5, the centralized research and judgment indicates that the field power distribution terminal uploads all fault recording files to the power distribution master station, the power distribution master station extracts waveform features of each terminal for analysis by a research and judgment algorithm, determines the fault type and the line where the fault occurs, and finally gives the corresponding isolation and recovery strategy.

Claims

1. A high-reliability fault recording and acquisition method based on centralized analysis and judgment at a power distribution master station, characterized in that: The following steps are involved: Step S1: When a fault occurs in the distribution network, once the recording conditions of the recording and collection device are met, the fault recording data of the feeder is collected; Step S2: After the fault recording signal is collected, the collected fault waveform is enhanced by wavelet threshold noise reduction and artificial intelligence waveform enhancement method; Step S3: Two storage spaces A and B with equal memory are set up. The storage module automatically stores the corresponding fault waveforms in storage space A and storage space B. Storage space A stores the original fault waveform as a backup, and storage space B is used to store the enhanced fault waveform. If necessary, the power distribution master station verifies the differences between the enhanced waveform and the original waveform. Step S4: By reducing the memory space of the fault waveform file, the fault waveform upload speed is increased while ensuring that the waveform distortion after compression does not increase; Step S5: After receiving the recording and testing instruction from the master station, the wireless communication module adopts the latest protocol to transmit the fault waveform file to the power distribution master station to assist the master station in realizing centralized fault analysis and judgment.

2. A high-reliability fault recording and collection method based on centralized analysis and judgment at a power distribution master station according to claim 1, characterized in that: In step S1, the fault recording signal includes characteristic waveforms such as line phase voltage, phase current, zero-sequence voltage and zero-sequence current, and the fault recording triggering condition is a sudden change in zero-sequence voltage.

3. The high-reliability fault recording and acquisition method based on centralized analysis and judgment at a power distribution master station according to claim 1 is characterized in that: Step S2 specifically includes the following steps: Step S2-1: The noisy fault waveform is decomposed by wavelet multi-scale transformation. The collected discrete fault recording signal is f(n), n = 0, 1, ..., N-1, where N is the length of the fault recording signal. The fault recording signal f(n) is decomposed by wavelet multi-scale transformation by selecting a suitable small fundamental wave and decomposition scale j to obtain the wavelet decomposition coefficient W at each scale. j,k ; Where n is the discrete signal, j is the decomposition scale, k is the decomposition position, and ψ is the wavelet function; Step S2-2: Decompose the wavelet coefficients W j,k Threshold processing is performed to obtain The threshold processing formula is Where, is the wavelet coefficient after threshold processing, sgn is the sign function, λ is the threshold, σ is the standard deviation of the fault recording noise, and N is the length of the fault recording signal; Step S2-3: Perform inverse wavelet transform to obtain noise-reduced fault recording signal Step S2-4: AI deep enhancement of the signal after wavelet processing It is input into the deep neural network model to further suppress periodic interference and repair the distorted waveform, enhance the waveform features and its recognition, and finally obtain the enhanced waveform.

4. The high-reliability fault recording and acquisition method based on centralized analysis and judgment at a power distribution master station according to claim 1 is characterized in that: In step S5, the latest transmission protocol refers to the function of converting between 101 protocol and 104 protocol, and the 104 protocol is used for data exchange with the power distribution master station to solve the limitation of some old terminals using 101 protocol.

5. The high-reliability fault recording and acquisition method based on centralized analysis and judgment at a power distribution master station according to claim 1 is characterized in that: In step S5, the centralized analysis means that the on-site distribution terminal uploads all fault recording files to the distribution master station. The distribution master station extracts the waveform characteristics of each terminal through the analysis algorithm for analysis, determines the fault type and the line where it occurs, and finally gives the corresponding isolation and recovery strategy.

6. A high-reliability fault recording and collection device based on centralized analysis and judgment at a power distribution master station, characterized in that: A high-reliability fault recording and collection method based on centralized analysis and judgment of a power distribution master station as described in any one of claims 1-5 above is run, wherein the recording and collection device is connected in series between the switch and the FTU through an aviation plug, and the physical layer and electrical parameters are fully compatible with the original interface; the recording and collection device includes a fault recording module, a fault recording enhancement module, a recording file storage module, a recording file compression module, a recording file uploading module and a wireless communication module.

7. A high-reliability fault recording and acquisition device based on centralized analysis and judgment at a power distribution master station according to claim 6, characterized in that: When a fault occurs in the distribution network, once the recording conditions of the recording and collecting device are met, the fault recording module collects the fault recording data of the feeder.

8. The high-reliability fault recording and collection device based on centralized analysis and judgment at the power distribution master station according to claim 6 is characterized in that: The fault recording enhancement module enhances the collected fault waveform by using wavelet threshold noise reduction and artificial intelligence waveform enhancement methods.

9. The high-reliability fault recording and acquisition device based on centralized analysis and judgment at the power distribution master station according to claim 6 is characterized in that: The recording file storage module has two built-in storage spaces A and B with equal memory; The waveform file compression module compresses the fault waveform file memory space.

10. The high-reliability fault recording and collection device based on centralized analysis and judgment at a power distribution master station according to claim 6, characterized in that: After receiving the recording and testing command from the master station, the recording file uploading module uses the wireless communication module to transmit the fault waveform file to the power distribution master station using the latest protocol.

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