Power distribution network line fault traveling wave pulse feature extraction method and system

Abstract

The invention discloses a power distribution network line fault traveling wave pulse feature extraction method, which comprises the following steps: 100, collecting line traveling wave current data of a power distribution network within a period of time, and obtaining a line traveling wave current time sequence; 200, constructing a traveling wave current vector matrix based on the line traveling wave current time sequence; 300, acquiring a sample covariance matrix of the traveling wave current vector matrix based on the traveling wave current vector matrix, and acquiring a characteristic root of the traveling wave current vector matrix based on the sample covariance matrix; 400, sorting the characteristic roots, and taking the time sequence corresponding to the traveling wave current vector corresponding to the maximum characteristic root as a suspected fault pulse signal sequence; 500, based on the suspected fault pulse signal sequence, generating a three-dimensional phase space trajectory of the suspected fault pulse signal sequence; 600, on the basis of the three-dimensional phase space trajectory, the specific gravity dimension of the three-dimensional phase space trajectory is obtained; and 700, comparing the specific gravity dimension with a set threshold value, and if the specific gravity dimension is greater than the threshold value, judging that the suspected fault pulse signal sequence contains fault pulses. According to the invention, rapid and accurate identification of the power distribution network line fault traveling wave pulse is realized.

Description

Technical Field

[0001] The present invention relates to a signal detection method and system, and in particular to a line fault signal detection method and system. Background Art

[0002] The current medium and low voltage distribution network is mainly composed of overhead lines, which have complex line structures, numerous branches, and are prone to failure. According to statistics, during the operation of the power system, power outages caused by distribution network failures account for more than 95% of the total power outages. In order to quickly isolate the distribution network system failure and restore the normal operation of the distribution network system, it is necessary to accurately and quickly locate the distribution network fault.

[0003] When a line fails, it will send out a transient signal that propagates along the line network, starting from the fault point, which is called a "traveling wave". By using distributed detection devices to detect the arrival time of traveling waves at different locations, the location of the fault point can be calculated.

[0004] The key to affecting the accuracy of traveling wave positioning is the accurate identification of traveling wave pulses. Since there are many interference signals on the line site and the amplitude of the fault traveling wave signal is small, the traveling wave pulses are often submerged in the noise, which seriously affects the accuracy of fault positioning. Summary of the invention

[0005] One of the purposes of the present invention is to provide a method for extracting features of traveling wave pulses of distribution network line faults, which can realize rapid and accurate identification of traveling wave pulses of faults.

[0006] According to the above invention purpose, the present invention proposes a method for extracting traveling wave pulse characteristics of distribution network line faults, which comprises the steps of:

[0007] 100: collecting line traveling wave current data of the distribution network within a period of time to obtain a line traveling wave current time series;

[0008] 200: constructing a traveling wave current vector matrix based on the traveling wave current time series of the line;

[0009] 300: Acquire a sample covariance matrix based on the traveling wave current vector matrix, and acquire a characteristic root based on the sample covariance matrix;

[0010] 400: Sort the characteristic roots, and use the time series corresponding to the traveling wave current vector corresponding to the largest characteristic root as a suspected fault pulse signal sequence;

[0011] 500: Generate a three-dimensional phase space trajectory based on the suspected fault pulse signal sequence;

[0012] 600: Based on the three-dimensional phase space trajectory, obtain the specific gravity dimension of the three-dimensional phase space trajectory;

[0013] 700: Compare the weight dimension with a set threshold value. If the weight dimension is greater than the threshold value, determine that the suspected fault pulse signal sequence contains a fault pulse.

[0014] Furthermore, in step 100 of the method for extracting traveling wave pulse features of distribution network line faults described in the present invention, the line traveling wave current data of the distribution network within a period of time is collected and normalized to obtain the line traveling wave current time series.

[0015] Furthermore, in the method for extracting the characteristics of the traveling wave pulse of the distribution network line fault described in the present invention, the weight dimension E is obtained based on the following formula:

[0016]

[0017] Among them, r represents the uniform grid division of the three-dimensional phase trajectory diagram into r 3 The size of a single small cube among the small cubes; T r represents the proportion of the three-dimensional phase space trajectory falling into the small cube for the partitions of different sizes r; p t Represents the probability of whether the t-th small cube is occupied in the three-dimensional phase space trajectory.

[0018] Further, in step 700 of the method for extracting traveling wave pulse features of distribution network line faults described in the present invention, the threshold is selected from the range of 0.55-0.65.

[0019] Furthermore, the method for extracting the characteristics of traveling wave pulses of distribution network line faults described in the present invention further includes step 800: when it is determined that the suspected fault pulse signal sequence contains a fault pulse, an alarm signal is output.

[0020] Another object of the present invention is to provide a distribution network line fault traveling wave pulse feature extraction system, which can realize rapid and accurate identification of fault traveling wave pulses.

[0021] According to the above invention purpose, the present invention proposes a distribution network line fault traveling wave pulse feature extraction system, which includes:

[0022] A signal acquisition module collects line traveling wave current data of the distribution network over a period of time to obtain a line traveling wave current time series;

[0023] A matrix construction module, which constructs a traveling wave current vector matrix based on the line traveling wave current time series;

[0024] An extraction module, which obtains a sample covariance matrix based on the traveling wave current vector matrix, and obtains a characteristic root based on the sample covariance matrix;

[0025] A sorting module, which sorts the characteristic roots and uses the time series corresponding to the traveling wave current vector corresponding to the largest characteristic root as a suspected fault pulse signal sequence;

[0026] A trajectory generation module, which generates a three-dimensional phase space trajectory based on the suspected fault pulse signal sequence;

[0027] A judgment module obtains a weight dimension of the three-dimensional phase space trajectory based on the three-dimensional phase space trajectory; and compares the weight dimension with a set threshold value. If the weight dimension is greater than the threshold value, it is determined that the suspected fault pulse signal sequence contains a fault pulse.

[0028] Furthermore, in the distribution network line fault traveling wave pulse feature extraction system described in the present invention, the signal acquisition module collects the line traveling wave current data of the distribution network within a period of time, and normalizes the data to obtain the line traveling wave current time series.

[0029] Furthermore, in the distribution network line fault traveling wave pulse feature extraction system of the present invention, the judgment module obtains the weight dimension E based on the following formula:

[0030]

[0031] Among them, r represents the uniform grid division of the three-dimensional phase trajectory diagram into r 3 The size of a single small cube among the small cubes; T r represents the proportion of the three-dimensional phase space trajectory falling into the small cube for the partitions of different sizes r; p t Represents the probability of whether the t-th small cube is occupied in the three-dimensional phase space trajectory.

[0032] Furthermore, in the distribution network line fault traveling wave pulse feature extraction system described in the present invention, the threshold is selected from the range of 0.55-0.65.

[0033] Furthermore, the distribution network line fault traveling wave pulse feature extraction system described in the present invention also includes an alarm module, and when it is determined that the suspected fault pulse signal sequence contains a fault pulse, the alarm module outputs an alarm signal.

[0034] The method for extracting the characteristics of traveling wave pulses of distribution network line faults described in the present invention uses a nonlinear time series analysis method to extract a data window suspected of containing traveling wave pulses for a fault traveling wave current signal using a matrix characteristic root analysis, and then uses a phase space trajectory analysis method to convert the traveling wave pulse current signal into a trajectory curve in a three-dimensional phase space, and then extract the characteristic value of the phase space trajectory curve, thereby realizing rapid and accurate identification of traveling wave pulses of distribution network line faults.

[0035] The distribution network line fault traveling wave pulse feature extraction system described in the present invention has the same advantages and beneficial effects. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 A flow chart showing the steps of a method for extracting traveling wave pulse features of a distribution network line fault according to the present invention in one embodiment.

[0037] Figure 2 The figure shows a suspected fault pulse signal obtained in a specific example of the method for extracting the characteristics of a traveling wave pulse of a distribution network line fault described in the present invention.

[0038] Figure 3 The three-dimensional phase space trajectory of a suspected fault pulse signal obtained by the distribution network line fault traveling wave pulse feature extraction method described in the present invention in a specific example is shown.

[0039] Figure 4 The diagram shows the architecture of the distribution network line fault traveling wave pulse feature extraction system in one embodiment of the present invention. DETAILED DESCRIPTION

[0040] The method and system for extracting traveling wave pulse characteristics of distribution network line faults described in the present invention will be further explained and illustrated below in conjunction with the accompanying drawings and specific embodiments of the specification. However, such explanation and illustration do not constitute an improper limitation on the technical solution of the present invention.

[0041] In some embodiments, the method for extracting the characteristics of a traveling wave pulse of a distribution network line fault may include the steps of:

[0042] 100: Collect the line traveling wave current data of the distribution network within a period of time, perform normalization processing on it, and obtain a normalized line traveling wave current time series, for example, a line traveling wave current time series i(t)={i1,i2,i3,...,i N}.

[0043] 200: Construct the traveling wave current vector matrix I based on the line traveling wave current time series:

[0044] For a line with a length of N, the traveling wave current time series i(t) = {i1, i2, i3, ..., i N}, divide it into N m m small segments, with a construction length of N m The m-dimensional phasor sequence I:

[0045]

[0046] Where m is the dimension of the traveling wave current vector matrix, which also represents the data filtering window; I is Nm The traveling wave current vector matrix consists of m-dimensional points.

[0047] 300: Obtain the sample covariance matrix S based on the traveling wave current vector matrix:

[0048]

[0049] In the formula, I T is the conjugate matrix of I.

[0050] Calculate its characteristic roots based on the sample covariance matrix S:

[0051] In linear algebra, an eigenvalue is when the product of a matrix and a vector is equal to the product of the vector and a constant. This constant is the eigenvalue. For a matrix S and a non-zero vector x, if the following conditions are met:

[0052] Sx=λx

[0053] Where λ is a constant, then λ is called the eigenvalue of the matrix S, and x is called the eigenvector corresponding to the eigenvalue λ.

[0054] The method for solving the characteristic roots of the matrix can be solved using the eigenvalue decomposition method in the textbook.

[0055] 400: Sort the characteristic roots and sort the traveling wave current vector I corresponding to the largest characteristic root max The corresponding time series As a suspected fault pulse signal sequence. Figure 2 The figure shows a suspected fault pulse signal sequence obtained in a specific example.

[0056] 500: Based on the suspected fault pulse signal sequence, generate its three-dimensional phase space trajectory, where the coordinate of a point on the trajectory is expressed as (x t ,y t , z t ):

[0057] x t =i max (t-2τ)

[0058] y t =i max (t-τ)

[0059] z t =i max (t)

[0060] Where t represents time t, τ Represents a sampling period.

[0061] Figure 3 Shows the Figure 2 The three-dimensional phase space trajectory generated by the suspected fault pulse signal sequence is shown.

[0062] 600: Based on the three-dimensional phase space trajectory, the specific dimension E of the three-dimensional phase space trajectory is obtained by the following formula:

[0063] For a three-dimensional phase space trajectory, the cubic region where the trajectory coordinates of the phase plane are located is divided into r 3 In some more specific implementations, a binary matrix D∈r may be used. 3 To represent the judgment result, the binary matrix elements are 0 or 1, 0 indicates that the small cube contains a phase trajectory point, and 1 indicates that the small cube is not occupied by the phase trajectory.

[0064] In this way, in some more specific embodiments, the specific gravity dimension E can be calculated based on the following formula:

[0065]

[0066] Among them, r represents the uniform grid division of the three-dimensional phase trajectory diagram into r 3 The size of a single small cube among the small cubes; T r represents the proportion of the three-dimensional phase space trajectory falling into the small cube for the partitions of different sizes r; p t Represents the probability of whether the t-th small cube is occupied in the three-dimensional phase space trajectory.

[0067] 700: Setting a threshold, comparing the calculated weight dimension E with the set threshold, if it is greater than the threshold, determining that the suspected fault pulse signal sequence contains a fault pulse.

[0068] In some more specific embodiments, the threshold value may be selected from the empirical value range of 0.55-0.65. For example, in a specific example, the threshold value is 0.6.

[0069] In addition, in some implementations, step 800 may be performed after step 700: when it is determined that the suspected fault pulse signal sequence contains a fault pulse, an alarm signal is output.

[0070] In another embodiment, the present invention further proposes a distribution network line fault traveling wave pulse feature extraction system, which includes:

[0071] A signal acquisition module 101 collects line traveling wave current data of the distribution network within a period of time to obtain a line traveling wave current time series;

[0072] A matrix construction module 102, which constructs a traveling wave current vector matrix based on the line traveling wave current time series;

[0073] An extraction module 103, which obtains a sample covariance matrix based on the traveling wave current vector matrix, and obtains a characteristic root based on the sample covariance matrix;

[0074] A sorting module 104, which sorts the characteristic roots and uses the time series corresponding to the traveling wave current vector corresponding to the largest characteristic root as a suspected fault pulse signal sequence;

[0075] A trajectory generation module 105, which generates a three-dimensional phase space trajectory based on the suspected fault pulse signal sequence;

[0076] The judgment module 106 obtains the weight dimension of the three-dimensional phase space trajectory based on the three-dimensional phase space trajectory; and compares the weight dimension with a set threshold value. If the weight dimension is greater than the threshold value, it is determined that the suspected fault pulse signal sequence contains a fault pulse.

[0077] In some more specific implementations, the signal acquisition module 101 acquires line traveling wave current data of the distribution network within a period of time, and performs normalization processing on the data to obtain the line traveling wave current time series.

[0078] In some more specific implementations, the determination module 106 obtains the specific gravity dimension E based on the following formula:

[0079]

[0080] Among them, r represents the uniform grid division of the three-dimensional phase trajectory diagram into r 3 The size of a single small cube among the small cubes; T r represents the proportion of the three-dimensional phase space trajectory falling into the small cube for the partitions of different sizes r; p t Represents the probability of whether the t-th small cube is occupied in the three-dimensional phase space trajectory.

[0081] In some embodiments, the distribution network line fault traveling wave pulse feature extraction system described in the present invention may further include an alarm module 107. When it is determined that the suspected fault pulse signal sequence contains a fault pulse, the alarm module 107 outputs an alarm signal.

[0082] In the present invention, the signal acquisition module 101, the matrix construction module 102, the extraction module 103, the sorting module 104, the trajectory generation module 105, the judgment module 106 and the alarm module 107 can be implemented in any appropriate manner, for example, they can take the form of a microprocessor or a processor and a computer-readable medium storing a computer-readable program code (such as software or firmware) that can be executed by the (micro)processor, a logic gate, a switch, an application specific integrated circuit (ASIC), a programmable logic controller and an embedded microcontroller. Examples of controllers include but are not limited to the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20 and Silicone Labs C8051F320.

[0083] In addition, those skilled in the art also know that, in addition to implementing the controller in a purely computer-readable program code, it is entirely possible to implement the same function in each module in the form of a logic gate, a switch, a dedicated integrated circuit, a programmable logic controller, and an embedded microcontroller by logically programming the method steps. Therefore, such a module can be considered as a hardware component, and the means for implementing various functions included therein can also be considered as a structure within the hardware component. Or even, the means for implementing various functions can be considered as both a software module for implementing the method and a structure within the hardware component.

[0084] It should be noted that the prior art in the protection scope of the present invention is not limited to the embodiments given in the present application documents. All prior art that does not contradict the scheme of the present invention, including but not limited to prior patent documents, prior public publications, prior public uses, etc., can be included in the protection scope of the present invention.

[0085] In addition, the combination of the various technical features in this case is not limited to the combination described in the claims of this case or the combination described in the specific embodiments. All technical features recorded in this case can be freely combined or combined in any way unless there is a contradiction between them.

[0086] It should also be noted that the above-listed embodiments are only specific embodiments of the present invention. Obviously, the present invention is not limited to the above embodiments, and similar changes or modifications made therewith can be directly derived or easily associated with the contents disclosed by those skilled in the art from the present invention, and all should belong to the protection scope of the present invention.

Claims

1. A method for extracting the characteristics of traveling wave pulses of distribution network line faults, characterized in that: Includes steps: 100: collecting line traveling wave current data of the distribution network within a period of time to obtain a line traveling wave current time series; 200: constructing a traveling wave current vector matrix based on the traveling wave current time series of the line; 300: Acquire a sample covariance matrix based on the traveling wave current vector matrix, and acquire a characteristic root based on the sample covariance matrix; 400: Sort the characteristic roots, and use the time series corresponding to the traveling wave current vector corresponding to the largest characteristic root as a suspected fault pulse signal sequence; 500: Generate a three-dimensional phase space trajectory based on the suspected fault pulse signal sequence; 600: Based on the three-dimensional phase space trajectory, obtain a specific dimension E of the three-dimensional phase space trajectory; 700: Compare the weight dimension with a set threshold value. If the weight dimension is greater than the threshold value, determine that the suspected fault pulse signal sequence contains a fault pulse.

2. The method for extracting the characteristics of the traveling wave pulse of the distribution network line fault according to claim 1, characterized in that: In step 100, line traveling wave current data of a distribution network within a period of time is collected and normalized to obtain the line traveling wave current time series.

3. The method for extracting the characteristics of the traveling wave pulse of the distribution network line fault according to claim 1, characterized in that: The specific gravity dimension E is obtained based on the following formula: Among them, r represents the uniform grid division of the three-dimensional phase trajectory diagram into r 3 The size of a single small cube among the small cubes; T r represents the proportion of the three-dimensional phase space trajectory falling into the small cube for the partitions of different sizes r; p t Represents the probability of whether the t-th small cube is occupied in the three-dimensional phase space trajectory.

4. The method for extracting the characteristics of the traveling wave pulse of the distribution network line fault according to claim 1, characterized in that: In step 700, the threshold is selected from the range of 0.55-0.

65.

5. The method for extracting the characteristics of the traveling wave pulse of the distribution network line fault according to claim 1, characterized in that: The method further comprises step 800: when it is determined that the suspected fault pulse signal sequence contains a fault pulse, outputting an alarm signal.

6. A distribution network line fault traveling wave pulse feature extraction system, characterized in that: include: A signal acquisition module collects line traveling wave current data of the distribution network over a period of time to obtain a line traveling wave current time series; A matrix construction module, which constructs a traveling wave current vector matrix based on the line traveling wave current time series; An extraction module, which obtains a sample covariance matrix based on the traveling wave current vector matrix, and obtains a characteristic root based on the sample covariance matrix; A sorting module, which sorts the characteristic roots and uses the time series corresponding to the traveling wave current vector corresponding to the largest characteristic root as a suspected fault pulse signal sequence; A trajectory generation module, which generates a three-dimensional phase space trajectory based on the suspected fault pulse signal sequence; A judgment module, which obtains the specific gravity dimension of the three-dimensional phase space trajectory based on the three-dimensional phase space trajectory; And the proportion dimension is compared with a set threshold value. If it is greater than the threshold value, it is determined that the suspected fault pulse signal sequence contains a fault pulse.

7. The distribution network line fault traveling wave pulse feature extraction system according to claim 6, characterized in that: The signal acquisition module acquires line traveling wave current data of the distribution network within a period of time, and performs normalization processing on the data to obtain the line traveling wave current time series.

8. The distribution network line fault traveling wave pulse feature extraction system according to claim 6, characterized in that: The judgment module obtains the specific gravity dimension E based on the following formula: Among them, r represents the uniform grid division of the three-dimensional phase trajectory diagram into r 3 The size of a single small cube among the small cubes; T r represents the proportion of the three-dimensional phase space trajectory falling into the small cube for the partitions of different sizes r; p t Represents the probability of whether the t-th small cube is occupied in the three-dimensional phase space trajectory.

9. The distribution network line fault traveling wave pulse feature extraction system according to claim 6, characterized in that: The threshold value is selected from the range of 0.55-0.

65.

10. The distribution network line fault traveling wave pulse feature extraction system according to claim 6, characterized in that: It also includes an alarm module, which outputs an alarm signal when it is determined that the suspected fault pulse signal sequence contains a fault pulse.

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