CN114019406A - Distribution line ground fault characteristic value selection method based on wavelet transformation and application - Google Patents
Distribution line ground fault characteristic value selection method based on wavelet transformation and application Download PDFInfo
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- G01R31/50—Testing of electric apparatus, lines, cables or components for short-circuits, continuity, leakage current or incorrect line connections
- G01R31/52—Testing for short-circuits, leakage current or ground faults
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/50—Testing of electric apparatus, lines, cables or components for short-circuits, continuity, leakage current or incorrect line connections
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Abstract
The invention provides a distribution line ground fault characteristic value selection method based on wavelet transformation and application thereof, wherein the characteristic value selection method comprises the following steps: acquiring voltage data and current data of a distribution line to obtain secondary voltage waveforms and current waveforms; respectively carrying out discrete sampling on the secondary voltage waveform and the current waveform to obtain discrete sampling signals; extracting even point data of the discrete sampling signal to obtain an approximate sequence and a detail sequence of the discrete sampling signal; and respectively calculating the frequency domain characteristic value and the time domain characteristic value. Aiming at the problem of low accuracy of distribution line ground fault identification, the invention decomposes the secondary voltage and current of the distribution line by utilizing wavelet transformation, thereby improving the accuracy of the distribution line ground fault.
Description
Technical Field
The invention relates to the technical field of power grid ground fault judgment, in particular to a distribution line ground fault characteristic value selection method based on wavelet transformation and application.
Background
Distribution network operational environment is complicated changeable, because the transformer substation's ground connection mode is mostly ungrounded or through arc suppression coil ground connection, when leading to taking place single-phase ground connection, the transformer substation protection can not discover the trouble and amputate very first time, leads to the distribution line to take the earth fault operation, if produce electric arc, then arouse the trouble easily and enlarge to alternate short circuit, has brought the public safety hidden danger of involving in the electricity even, seriously threatens personal safety. At present, a grounding line selection device is mostly adopted in China to perform line selection tripping on a fault line so as to remove the grounding fault, but the line selection success rate is low due to the fact that the grounding fault is not obvious in characteristic, and fault removal can be performed only in a round-trip mode, so that the fault removal time is increased, and unnecessary power failure of other lines is caused.
Disclosure of Invention
The invention aims to provide a distribution line ground fault characteristic value selection method based on wavelet transformation and application thereof, which can solve the problem of unnecessary influence expansion caused by the fact that ground faults cannot be found in time due to unobvious ground faults in the prior art.
The purpose of the invention is realized by the following technical scheme:
in a first aspect, the invention provides a distribution line ground fault characteristic value selection method based on wavelet transformation, which comprises the following steps:
step S1, acquiring voltage data and current data of the distribution line to obtain secondary voltage waveform and current waveform;
step S2, respectively carrying out discrete sampling on the secondary voltage waveform and the current waveform to obtain discrete sampling signals;
step S3, extracting even point data of the discrete sampling signal to obtain an approximate sequence and a detail sequence of the discrete sampling signal;
and step S4, respectively calculating the frequency domain characteristic value and the time domain characteristic value.
Further, the Mallat algorithm is adopted to carry out secondary voltage waveform and current waveformDiscretizing to obtain discrete sampling signal aj，kWhere j represents the number of layers of decomposition and k represents the number of discrete sampling signal points.
Furthermore, the sum of squares of the detail sequences of each layer obtained by decomposition is taken, and the energy of the detail sequence number of each layer, namely the frequency domain characteristic value, is obtained.
Further, the variation of the peak value and the integral value of the secondary voltage waveform and the current waveform in each period is calculated to obtain a time domain characteristic value.
In a second aspect, the present invention provides a method for determining a ground fault of a distribution line, which determines whether a ground fault occurs on the distribution line by using the frequency domain characteristic value and the time domain characteristic value obtained by the wavelet transform-based method for selecting a ground fault characteristic value of a distribution line according to any one of claims 1 to 4, and by combining with a change of a zero-sequence current of the distribution line.
Aiming at the problem of low accuracy of ground fault identification of the distribution line, the invention provides a method for decomposing secondary voltage and current of the distribution line through wavelet transformation to obtain 5-layer wavelet detail signal energy as a frequency domain characteristic value, and calculating the variation of peak values and integral values of the secondary voltage and current in each period as a time domain characteristic value. And finally, the change of the zero sequence current of the line is combined to assist in judging whether the line has the ground fault or not, so that the accuracy of the ground fault of the distribution line is improved.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a flow chart of a distribution line ground fault characteristic value selection method based on wavelet transformation for judging ground fault according to the present invention;
fig. 2 is a schematic diagram of a three-layer decomposition process of a discrete sampling signal according to the present invention.
Detailed Description
The embodiments of the present disclosure are described in detail below with reference to the accompanying drawings.
The embodiments of the present disclosure are described below with specific examples, and other advantages and effects of the present disclosure will be readily apparent to those skilled in the art from the disclosure in the specification. It is to be understood that the described embodiments are merely illustrative of some, and not restrictive, of the embodiments of the disclosure. The disclosure may be embodied or carried out in various other specific embodiments, and various modifications and changes may be made in the details within the description without departing from the spirit of the disclosure. It is to be noted that the features in the following embodiments and examples may be combined with each other without conflict. All other embodiments, which can be derived by a person skilled in the art from the embodiments disclosed herein without making any creative effort, shall fall within the protection scope of the present disclosure.
The invention discloses a distribution line ground fault characteristic value selection method based on wavelet transformation, which comprises the following steps as shown in figure 1:
and step S1, acquiring voltage data and current data of the distribution line to obtain a secondary voltage waveform and a current waveform.
Step S2, respectively carrying out discrete sampling on the secondary voltage waveform and the current waveform to obtain a discrete sampling signal aj,k。
Due to the randomness and instability of the ground fault, voltage signals and current signals belong to unstable signals with more singular points, a wavelet base with better singularity detection characteristics is adopted, and the wavelet base has the characteristics of symmetry, regularity, limited tight support and high moment of disappearance. The wavelet bases can adopt Harr, DaubechiesN, Biorthogonal Nr.Nd, Coiffets N, Symlets N and the like, the invention takes the Symlets 2 wavelet base as an example for explanation, the support width is 3, the number of vanishing moments is 4, the length of the filter is 4, and the wavelet base has orthogonality and approximate symmetry.
When the original discrete signal is convolved with the wavelet basis, the boundary problem occurs at the boundary because the data length is not equal to the wavelet basis length, and the effective operation cannot be performed, so that the boundary continuation processing is needed. The period extension can well solve the signal mutation brought by the extension signal to the original signal, and the original signal can be perfectly extended without increasing the mutation signal only by ensuring that a complete current period is adopted during real-time sampling. The invention solves the boundary problem of the original data by adopting a period continuation mode.
The invention adopts sym2 wavelet base, decomposes the secondary voltage and current signals acquired by the three-phase mutual inductor through the Mallat algorithm, can conveniently transplant the wavelet transformation algorithm into the embedded system, can greatly reduce the calculation amount during the wavelet transformation, reduces the operation pressure of the CPU, and has great significance for the monitoring system needing real-time calculation.
Further, step S2 includes: j-layer wavelet transform discrete sampling signal a for quickly calculating voltage waveform or current waveform by adopting Mallat algorithmj，k。
According to Mallat algorithm, firstly discretizing the secondary voltage and current waveforms of the line to obtain discrete sampling signals aj，kWhere j represents the number of layers to be decomposed, the present invention is illustrated by taking a five-layer decomposition as an example (j is 5), and k represents the number of discrete sampling signal points, which depends on the sampling rate of the sampling system.
Step S3, extracting discrete sampling signal aj，kThe approximate sequence and the detail sequence of the discrete sampling signal are obtained from the even-numbered point data.
Digital filter h determined by sym2 wavelet basiskAnd gkThe function is to extract the even-numbered point data of the discrete sampling signal, and then the approximate sequence a of the j-1 level can be obtainedj-1，kAnd detail sequence dj-1,kBy analogy, the sequence a can be obtained finally0,kAnd d0,kA obtained in this processj-m,kIs an approximate sequence of signals obtained by the m-th decomposition, dj-m,kI.e., the discrete wavelet coefficients obtained from the m-th decomposition, and the process is repeated until the last layer is decomposed. Taking the three-layer decomposition process as an example, the decomposition process is shown in fig. 2.
Discrete sampling signal aj,kUsing a digital filter hkAnd gkGradually decompose its approximate sequence { aj-m,k}m＜j,m∈ZAnd its detail sequence dj-m,k}m＜j,m∈Z。
And step S4, respectively calculating the frequency domain characteristic value and the time domain characteristic value.
The frequency domain feature value and the time domain feature value of the wavelet transform are calculated respectively, and specifically, the step S4 includes:
and taking the square sum of the detail sequences of each layer obtained by decomposition to obtain the energy of the detail sequence number of each layer, namely the frequency domain characteristic value. And calculating the variation of the peak value and the integral value of the voltage and the current in each period to obtain a time domain characteristic value.
In order to increase the identification dimension of the fault characteristic value, the invention introduces time domain characteristic quantities which are respectively the peak value variation quantity and the variation quantity of the integral value of the secondary voltage and the current waveform in each period, because when a line has an earth fault, a large amount of high-frequency signals introduced due to the randomness of the earth fault and the arc extinction can be generated, the variation of the peak value and the integral value of the waveform in each period can be caused, the variation rate is used as an auxiliary criterion for judging whether the earth fault occurs or not, the identification dimension of the time domain variation is supplemented, and the identification precision of the earth fault is increased.
The wavelet transform has adjustability and spatial locality, is a local analysis tool for time and frequency, and can carry out detailed analysis on each part of a signal through the telescopic translation operation of a wavelet basis function according to specific requirements, so that not only can the frequency components of each part be obtained, but also the time distribution of the frequency components in the signal can be obtained. The discrete wavelet transform Mallat fast algorithm is adopted to decompose the secondary voltage and current acquired by a three-phase mutual inductor of a distribution line in real time, the secondary voltage and current characteristic values when single-phase grounding occurs can be obtained by analyzing the 5-layer wavelet decomposition detail energy, the characteristic values are analyzed, the monitoring of the operation state of the distribution line can be realized, the grounding fault is alarmed, and the grounding line selection device is assisted to carry out fault line removal.
The invention realizes the idea that: the method comprises the steps of adopting wavelet transformation to analyze a fault arc current signal, firstly selecting a wavelet base of the wavelet transformation, determining a boundary continuation mode, then selecting a fault characteristic value based on the wavelet transformation according to the characteristics of a fault voltage signal and a fault current signal, and finally adding an arc characteristic value based on time domain change as an auxiliary criterion in order to make up the defects of the wavelet transformation.
The invention also provides a method for judging the distribution line ground fault, which judges whether the distribution line has the ground fault or not by utilizing the frequency domain characteristic value and the time domain characteristic value obtained by the wavelet transform-based distribution line ground fault characteristic value selection method and combining the change of the zero sequence current of the line.
The above description is for the purpose of illustrating embodiments of the invention and is not intended to limit the invention, and it will be apparent to those skilled in the art that any modification, equivalent replacement, or improvement made without departing from the spirit and principle of the invention shall fall within the protection scope of the invention.
Claims (5)
1. The distribution line ground fault characteristic value selection method based on wavelet transformation is characterized by comprising the following steps of:
step S1, acquiring voltage data and current data of the distribution line to obtain secondary voltage waveform and current waveform;
step S2, respectively carrying out discrete sampling on the secondary voltage waveform and the current waveform to obtain discrete sampling signals;
step S3, extracting even point data of the discrete sampling signal to obtain an approximate sequence and a detail sequence of the discrete sampling signal;
and step S4, respectively calculating the frequency domain characteristic value and the time domain characteristic value.
2. The distribution line ground fault eigenvalue selection method based on wavelet transformation as recited in claim 1, wherein a Mallat algorithm is adopted to discretize the secondary voltage waveform and the current waveform to obtain a discrete sampling signal aj,kWhere j represents the number of decomposed layers and k represents the discrete sampled signalAnd (6) counting the number of points.
3. The distribution line ground fault eigenvalue selection method based on wavelet transformation as recited in claim 1, wherein the energy of each layer of detail sequence number, i.e. frequency domain eigenvalue, is obtained by taking the square sum of each layer of detail sequence obtained by decomposition.
4. The distribution line ground fault characteristic value selection method based on wavelet transformation as recited in claim 1, wherein time domain characteristic values are obtained by calculating the variation of peak values and integral values of secondary voltage waveforms and current waveforms per cycle.
5. A method for judging the ground fault of a distribution line is characterized in that whether the ground fault occurs to the distribution line is judged by utilizing the frequency domain characteristic value and the time domain characteristic value which are obtained by the wavelet transform-based distribution line ground fault characteristic value selection method according to any one of claims 1 to 4 and combining the change of zero sequence current of the line.
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