CN107561400A - A kind of distribution network short circuit fault quick determination method based on real-time wavelet conversion - Google Patents
A kind of distribution network short circuit fault quick determination method based on real-time wavelet conversion Download PDFInfo
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Abstract
The invention discloses a kind of distribution network short circuit fault quick determination method based on real-time wavelet conversion, comprise the following steps：Step 1, the sampling for three-phase current signal being fixed sample frequency obtains the sampled signal of three-phase current, then multi-scale wavelet transformation is carried out to the sampled signal of three-phase current and obtains the three-phase wavelet coefficient under the 3rd yardstick, the absolute value sum of the three-phase wavelet coefficient under the 3rd yardstick is the characteristic quantity of short trouble；Step 2, if the threshold value of short trouble is T, if the characteristic quantity of the short trouble under any time, more than T, there occurs short trouble for distribution.The present invention realizes the quick identification of distribution line short trouble.
Description
Technical field
The invention belongs to intelligent distribution network system technical field of relay protection, is related to a kind of matching somebody with somebody based on real-time wavelet conversion
Network short circuit fault quick determination method, it is mainly used in middle pressure fault current limiter (FCL, Fault Current
Limiter in), for quickly identifying the timely limiting short-circuit current of middle voltage distribution networks short trouble.
Background technology
Failure in power system is as caused by short circuit mostly, it may occur however that short circuit be generally divided into：Three-phase shortcircuit, two
Mutually short circuit, two-phase grounding fault and single-line to ground fault.Operation of Electric Systems experience have shown that, it is various types of short circuit in, three
The probability minimum but the influence most serious to power system that mutually short circuit occurs.When distribution line occurs short-circuit, primary cut-out
Disconnect to protect power system security rapidly, the drop-out current of distribution primary cut-out is generally 20KA, 25kA, 31.5kA at present
Deng.But with developing rapidly for power network, being continuously increased for city and center of industry load capacity, cause short circuit current level drastically
Rise, be even more than the ability that the breaker that circuit is installed cut-offs short circuit current, seriously endangered the safe for operation of power network.
A kind of solution is to change the bigger breaker of capacity, but this mode is invested larger and has a limitation；Another kind solves
Method is to use fault current limiter (hereinafter referred to as current limiter), is not changing the situation of existing electric network composition and more exchange device
Under, by system short-circuit current limit in allowed band.
The fault detection method of current limiter sampling at present be mainly according to the virtual value of curtage signal, instantaneous value,
The features such as slope are judged.But signal is the complicated transient signal containing noise jamming in itself, and simultaneity factor is in running
It is middle can be put into by high-power load caused by impact, factor of shoving etc. caused by no-load transformer input influenceed, existing calculation
Method is difficult to accurate failure judgement in the case where interference is larger, in addition, system also has one to the real-time of fault detection algorithm
Fixed requirement.For example, signal virtual value is calculated according to Fast Fourier Transform (FFT) to detect short trouble, even if using half-wave Fu
In leaf, for detection time also at least in more than 10ms, the hysteresis quality of algorithm can influence the promptness of device limiting short-circuit current, may
Breaker can be caused can not to disconnect the short circuit current more than itself connecting-disconnecting function, serious threat Operation of Electric Systems safety.
The content of the invention
A kind of the shortcomings that it is an object of the invention to overcome above-mentioned prior art, there is provided distribution based on real-time wavelet conversion
Short trouble quick determination method, this method carries out multi-resolution decomposition using db4 small echos to systematic sampling electric current, with the 3rd yardstick
Wavelet coefficient sum and current instantaneous value threshold value are as short trouble comprehensive criterion, to realize the quick of distribution line short trouble
Identification.
To reach above-mentioned purpose, the present invention is achieved using following technical scheme：
A kind of distribution network short circuit fault quick determination method based on real-time wavelet conversion, comprises the following steps：
Step 1：The sampling for three-phase current signal being fixed sample frequency obtains the sampled signal of three-phase current, then
Multi-scale wavelet transformation is carried out to the sampled signal of three-phase current and obtains the three-phase wavelet coefficient under the 3rd yardstick, under the 3rd yardstick
Three-phase wavelet coefficient absolute value sum be short trouble characteristic quantity；
Step 2：If the threshold value of short trouble is T, if the characteristic quantity of the short trouble under any time is more than T, distribution
There occurs short trouble.
Further improve of the invention is：
In step 1, the characteristic quantity of short trouble is obtained using following methods：
Step 1-1：The first sampled signal for sampling to obtain three-phase current signal is fixed sample frequency is initial
Sampled signal；
Step 1-2：If repetition factor i=0；
Step 1-3：Any phase current in three-phase current is extracted as current phase current, extracts current phase current from X1+2i
The continuous 50 sampled value X started1+2i、X2+2i、……X50+2i；
Step 1-4：Smoothing factor under first yardstick is obtained by formula (1)：
Wherein A1_ (1+i), A1_ (2+i) ... A1_ (22+i) be the first yardstick under smoothing factor, h (1) ..., h (7),
H (8) is wavelet transformation low pass filter system number；
Step 1-5：Smoothing factor under second yardstick is obtained by formula (2)：
Wherein A2_ (1+i), A2_ (2+i) ... A2_ (8+i) are the smoothing factor under the second yardstick；
Step 1-6：Wavelet coefficient under 3rd yardstick is obtained by formula (3)：
D3_ (1+i)=A2_ (1+2i) * g (8)+A2_ (2+2i) * g (7)+...+A2_ (7+2i) * g (2)+A2_ (8+2i) *
g(1) (3)
Wherein, g (1), g (2) ..., g (8) are wavelet transformation high-pass filter system number；D3_ (1+i) is under the 3rd yardstick
Wavelet coefficient；
Step 1-7：Repeat step 1-3 to step 1-6, until three-phase current all by as current phase current, obtains the 3rd
Three-phase wavelet coefficient under yardstick；
Step 1-8：The absolute value sum of three-phase wavelet coefficient under 3rd yardstick is the characteristic quantity of short trouble；
Step 1-9：I=i+1, with X1+2i、X2+2i、…X50+2iFor original sampled signal, repeat step 1-3 to step 1-8,
Obtain the characteristic quantity of the short trouble under different time.
In step 1, choose Daubechies small echos db4 and multi-scale wavelet transformation is carried out to the sampled signal of three-phase current.
Fixed sampling frequency in step 1 is more than or equal to 6400Hz.
Compared with prior art, the invention has the advantages that：
First, the present invention is not influenceed by position of failure point, failure initial phase angle, can identify Arbitrary Fault point and it is any just
Short trouble under phase angle, and can with the noise in system operation, shove, the interference that load impact etc. is brought carries out area
Point；Secondly, the present invention forms comprehensive criterion with current instantaneous value threshold value, used on the basis of accurately detection line short fault
Family can be set according to actual track situation to current limiter threshold limit, and by setting the threshold value, adjustment current limiter limits short
The peak value of road electric current；Finally, for the present invention using every 8 sampled points as primary fault detection cycle, detection cycle is shorter, is adapted to application
In real-time detecting system.
Brief description of the drawings
Fig. 1 is the schematic diagram of multi-scale wavelet transformation；
Fig. 2 is the schematic flow sheet for updating Fault Identification characteristic quantity by Wavelet transformation in real time；
Fig. 3 is the ABC three-phase current oscillograms that experiment simulation obtains；
Fig. 4 is the 3rd multi-scale wavelet coefficient sequence that the three-phase current that experiment simulation obtains obtains through real-time wavelet recursive algorithm
Row；
Fig. 5 is to take B phase currents to carry out each layer wavelet coefficient sequence that multi-scale wavelet decomposition obtains；
Fig. 6 is the time distribution map used in identifying system short trouble of the present invention.
Embodiment
The present invention is described in further detail below in conjunction with the accompanying drawings：
Referring to Fig. 1-6, distribution network short circuit fault quick determination method of the present invention based on real-time wavelet conversion, including following step
Suddenly：
Step 1, the sampling that sample frequency three-phase current signal is fixed obtains the sampled signal of three-phase current, then
Real-time multi-scale wavelet transformation is carried out to the sampled signal of three-phase current and obtains the three-phase wavelet coefficient under the 3rd yardstick, described the
The absolute value sum of three-phase wavelet coefficient under three yardsticks is the characteristic quantity of short trouble；
The present invention chooses Daubechies small echos db4 and carries out real-time multi-scale wavelet change to the sampled signal of three-phase current
Change.Effective bearing length of db4 small echos is 8, i.e., the length that each wavelet mother function carries out convolution with signal is limited.
Fixed sampling frequency in the present invention is more than or equal to 6400Hz.
For the present invention using every 8 sampled points as primary fault detection cycle, detection cycle is shorter, is suitably applied real-time detection
System.
Specific method is：
Step 11, the first sampled signal obtained using three-phase current signal being fixed sample frequency sample is initially adopts
Sample signal；
Step 12, if repetition factor i=0；
Step 13, any phase current in three-phase current is extracted as current phase current, extracts current phase current from initial
Preceding 52 sampled value X that sampled signal starts1+2i、X2+2i、……X50+2i；
Step 14, the smoothing factor under the first yardstick is obtained by formula (1)：
Wherein A1_ (1+i), A1_ (2+i) ... A1_ (22+i) be the first yardstick under smoothing factor, h (1) ..., h (7),
H (8) is wavelet transformation low pass filter system number；
Step 15, the smoothing factor under the second yardstick is obtained by formula (2)：
Wherein A2_ (1+i), A2_ (2+i) ... A2_ (8+i) are the smoothing factor under the second yardstick；
Step 16, the wavelet coefficient under the 3rd yardstick is obtained by formula (3)：
D3_ (1+i)=A2_ (1+2i) * g (8)+A2_ (2+2i) * g (7)+...+A2_ (7+2i) * g (2)+A2_ (8+2i) *
g(1) (3)
Wherein, g (1), g (2) ..., g (8) are wavelet transformation high-pass filter system number；D3_ (1+i) is under the 3rd yardstick
Any phase wavelet coefficient；
Step 17, repeat step 13 is to step 16, until three-phase current all by as current phase current, obtains the 3rd yardstick
Under three-phase wavelet coefficient；
Step 18, the absolute value sum of the three-phase wavelet coefficient under the 3rd yardstick is the characteristic quantity of short trouble；
Step 19, i=i+1, with X1+2i、X2+2i、…X50+2iFor original sampled signal, repeat step 13 to step 18, obtain
The characteristic quantity of short trouble under to different time；
Step 20, if the threshold value of short trouble is T, if the characteristic quantity of the short trouble under any instant more than T, this when
There occurs short trouble for the distribution at quarter.
As shown in figure 3, sampled signal X1、X2……XnThrough three layers of wavelet decomposition, wavelet coefficient D3_n is obtained, to reduce number
According to redundancy, every layer of wavelet transform result carries out next layer of decomposition again after down-sampling, and signal can have by three layers of wavelet decomposition
Effect filters out the influence with interference such as noise.The recursive algorithm according to Fig. 2, after D3_1 is obtained, to calculate next wavelet systems
Number D3_2, then need to update 2 smoothing factors A2_9, A2_10 of second layer wavelet transformation, that is, update the 4 of first layer wavelet transformation
Individual smoothing factor A1_23 to A1_26, i.e., it need to update the sampled data X of 8 primary signals51~X58。
Analysis of experimental results：
It is 1.5s that system, which sets simulation time, is 0.1985s as Fig. 3 impact loads put into the moment, no-load transformer is thrown
It is 0.2364s constantly to enter, and the three phase short circuit fault moment is 0.5228s.Emulate the yardstick of three-phase current the 3rd under wavelet coefficient it
It is set as 400 with sum threshold values, instantaneous current threshold is set as 10kA.When impact load making time, no-load transformer input
Between, the three-phase shortcircuit time randomly generated respectively by the computer CPU time, short circuit trouble point is arranged to 2km away from power supply distance.Examine
Consider actual application environment, the random noise that signal to noise ratio is 10db is added on the basis of original sampled signal.Fig. 5 is B phases electricity
Result of the signal through multi-resolution decomposition is flowed, due to noise jamming, first layer wavelet coefficient d1 is without obvious mutation, it is impossible to as identification
The criterion of short trouble.And wavelet coefficient d3 is obtained through three layers of wavelet decomposition, it can significantly identify system short-circuit feature.By
Each phase wavelet coefficient is had a great influence in the failure initial phase angle of each phase current of short-circuit moment, c phases when short-circuit as seen from Figure 4
Electric current wavelet coefficient d3c and unobvious, therefore take three-phase current wavelet coefficient sum sum more reliable as short-circuit criterion, and
Shoved caused by no-load transformer input, the random input of impact load influences less for compartment system short trouble.
Fig. 6 show the rapidity of inventive algorithm identifying system short trouble, has transferred the real-time of .mat file edits
Small echo recursive algorithm, the short trouble carried out on Matlab platforms under 1000 random fault initial phase angles quickly identify emulation
Experiment.Wherein x coordinate is test number (TN), and y coordinate representation tests the time used in wavelet algorithm detection failure every time, and unit is
ms.It can be seen from the results that using db4 small echos carry out wavelet decomposition after, with the wavelet coefficient under the yardstick of three-phase current the 3rd it
, as short trouble comprehensive criterion, short trouble can be identified within 5ms, now short circuit current phase with current instantaneous value
To smaller, system will not be damaged.
The technological thought of above content only to illustrate the invention, it is impossible to protection scope of the present invention is limited with this, it is every to press
According to technological thought proposed by the present invention, any change done on the basis of technical scheme, claims of the present invention is each fallen within
Protection domain within.
Claims (4)
1. a kind of distribution network short circuit fault quick determination method based on real-time wavelet conversion, it is characterised in that comprise the following steps：
Step 1：The sampling for three-phase current signal being fixed sample frequency obtains the sampled signal of three-phase current, then to three
The sampled signal of phase current carries out multi-scale wavelet transformation and obtains the three-phase wavelet coefficient under the 3rd yardstick, and three under the 3rd yardstick
The absolute value sum of phase wavelet coefficient is the characteristic quantity of short trouble；
Step 2：If the threshold value of short trouble is T, if the characteristic quantity of the short trouble under any time occurs more than T, distribution
Short trouble.
2. the distribution network short circuit fault quick determination method according to claim 1 based on real-time wavelet conversion, its feature exist
In in step 1, the characteristic quantity of short trouble is obtained using following methods：
Step 1-1：The first sampled signal obtained using three-phase current signal being fixed sample frequency sample is initial samples
Signal；
Step 1-2：If repetition factor i=0；
Step 1-3：Any phase current in three-phase current is extracted as current phase current, extracts current phase current from X1+2iStart
Continuous 50 sampled value X1+2i、X2+2i、……、X50+2i；
Step 1-4：Smoothing factor under first yardstick is obtained by formula (1)：
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Step 1-5：Smoothing factor under second yardstick is obtained by formula (2)：
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<mi>i</mi>
</mrow>
<mo>)</mo>
</mrow>
<mo>*</mo>
<mi>h</mi>
<mrow>
<mo>(</mo>
<mn>7</mn>
<mo>)</mo>
</mrow>
<mo>+</mo>
<mn>...</mn>
<mo>+</mo>
<mi>A</mi>
<mn>1</mn>
<mo>_</mo>
<mrow>
<mo>(</mo>
<mrow>
<mn>9</mn>
<mo>+</mo>
<mn>2</mn>
<mi>i</mi>
</mrow>
<mo>)</mo>
</mrow>
<mo>*</mo>
<mi>h</mi>
<mrow>
<mo>(</mo>
<mn>2</mn>
<mo>)</mo>
</mrow>
<mo>+</mo>
<mi>A</mi>
<mn>1</mn>
<mo>_</mo>
<mrow>
<mo>(</mo>
<mrow>
<mn>10</mn>
<mo>+</mo>
<mn>2</mn>
<mi>i</mi>
</mrow>
<mo>)</mo>
</mrow>
<mo>*</mo>
<mi>h</mi>
<mrow>
<mo>(</mo>
<mn>1</mn>
<mo>)</mo>
</mrow>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<mn>......</mn>
</mtd>
</mtr>
<mtr>
<mtd>
<mrow>
<mi>A</mi>
<mn>2</mn>
<mo>_</mo>
<mrow>
<mo>(</mo>
<mrow>
<mn>8</mn>
<mo>+</mo>
<mi>i</mi>
</mrow>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mi>A</mi>
<mn>1</mn>
<mo>_</mo>
<mrow>
<mo>(</mo>
<mrow>
<mn>15</mn>
<mo>+</mo>
<mn>2</mn>
<mi>i</mi>
</mrow>
<mo>)</mo>
</mrow>
<mo>*</mo>
<mi>h</mi>
<mrow>
<mo>(</mo>
<mn>8</mn>
<mo>)</mo>
</mrow>
<mo>+</mo>
<mi>A</mi>
<mn>1</mn>
<mo>_</mo>
<mrow>
<mo>(</mo>
<mrow>
<mn>2</mn>
<mo>+</mo>
<mn>2</mn>
<mi>i</mi>
</mrow>
<mo>)</mo>
</mrow>
<mo>*</mo>
<mi>h</mi>
<mrow>
<mo>(</mo>
<mn>7</mn>
<mo>)</mo>
</mrow>
<mo>+</mo>
<mn>...</mn>
<mo>+</mo>
<mi>A</mi>
<mn>1</mn>
<mo>_</mo>
<mrow>
<mo>(</mo>
<mrow>
<mn>21</mn>
<mo>+</mo>
<mn>2</mn>
<mi>i</mi>
</mrow>
<mo>)</mo>
</mrow>
<mo>*</mo>
<mi>h</mi>
<mrow>
<mo>(</mo>
<mn>2</mn>
<mo>)</mo>
</mrow>
<mo>+</mo>
<mi>A</mi>
<mn>1</mn>
<mo>_</mo>
<mrow>
<mo>(</mo>
<mrow>
<mn>22</mn>
<mo>+</mo>
<mn>2</mn>
<mi>i</mi>
</mrow>
<mo>)</mo>
</mrow>
<mo>*</mo>
<mi>h</mi>
<mrow>
<mo>(</mo>
<mn>1</mn>
<mo>)</mo>
</mrow>
</mrow>
</mtd>
</mtr>
</mtable>
</mfenced>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>2</mn>
<mo>)</mo>
</mrow>
</mrow>
Wherein A2_ (1+i), A2_ (2+i) ..., A2_ (8+i) are the smoothing factor under the second yardstick；
Step 1-6：Wavelet coefficient under 3rd yardstick is obtained by formula (3)：
D3_ (1+i)=A2_ (1+2i) * g (8)+A2_ (2+2i) * g (7)+...+A2_ (7+2i) * g (2)+A2_ (8+2i) * g (1) (3)
Wherein, g (1), g (2) ..., g (8) are wavelet transformation high-pass filter system number；D3_ (1+i) is small under the 3rd yardstick
Wave system number；
Step 1-7：Repeat step 1-3 to step 1-6, until three-phase current all by as current phase current, obtains the 3rd yardstick
Under three-phase wavelet coefficient；
Step 1-8：The absolute value sum of three-phase wavelet coefficient under 3rd yardstick is the characteristic quantity of short trouble；
Step 1-9：I=i+1, with X1+2i、X2+2i、…、X50+2iFor original sampled signal, repeat step 1-3 obtains to step 1-8
The characteristic quantity of short trouble under different time.
3. the distribution network short circuit fault quick determination method according to claim 1 or 2 based on real-time wavelet conversion, its feature
It is, in step 1, chooses Daubechies small echos db4 and multi-scale wavelet transformation is carried out to the sampled signal of three-phase current.
4. the distribution network short circuit fault quick determination method according to claim 1 or 2 based on real-time wavelet conversion, its feature
It is, the fixed sampling frequency in step 1 is more than or equal to 6400Hz.
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