CN106291104A - Resonance detector method based on the photovoltaic cluster grid-connected system improving wavelet package transforms - Google Patents

Resonance detector method based on the photovoltaic cluster grid-connected system improving wavelet package transforms Download PDF

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Publication number
CN106291104A
CN106291104A CN201610604422.9A CN201610604422A CN106291104A CN 106291104 A CN106291104 A CN 106291104A CN 201610604422 A CN201610604422 A CN 201610604422A CN 106291104 A CN106291104 A CN 106291104A
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frequency band
frequency
wavelet
decomposition
package transforms
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李鹏
高静
武昭
黄仁乐
孙健
王存平
常乾坤
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State Grid Corp of China SGCC
North China Electric Power University
State Grid Beijing Electric Power Co Ltd
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State Grid Corp of China SGCC
North China Electric Power University
State Grid Beijing Electric Power Co Ltd
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    • GPHYSICS
    • G01MEASURING; TESTING
    • G01RMEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R23/00Arrangements for measuring frequencies; Arrangements for analysing frequency spectra
    • G01R23/16Spectrum analysis; Fourier analysis
    • G01R23/165Spectrum analysis; Fourier analysis using filters
    • G01R23/167Spectrum analysis; Fourier analysis using filters with digital filters

Abstract

A kind of Resonance detector method based on the photovoltaic cluster grid-connected system improving wavelet package transforms, including: primary signal is carried out db40 WAVELET PACKET DECOMPOSITION;Readjust low pass and the arrangement of high pass filter group, obtain by the uniform frequency band of frequency size distribution;) waveforms amplitude presents the frequency band of positive growth always in the uniform frequency band by frequency size distribution that obtains, is photovoltaic cluster grid-connected resonance place frequency band.The present invention is compared with wavelet transformation, and wavelet package transforms can constantly carry out binary partition, the frequency band being evenly distributed to high fdrequency component.And improve wavelet package transforms by readjusting low pass and the arrangement of high pass filter group, original wavelet package transforms is improved, obtained the uniform frequency band by the distribution of frequency size order, improve the accuracy of detection.By checking that waveforms amplitude presents the frequency band of positive growth always, obtain resonance signal place frequency band in photovoltaic cluster grid-connected system.

Description

Resonance detector method based on the photovoltaic cluster grid-connected system improving wavelet package transforms
Technical field
The present invention relates to a kind of Resonance detector method of photovoltaic cluster grid-connected system.Particularly relate to a kind of little based on improving The Resonance detector method of the photovoltaic cluster grid-connected system of ripple packet transform.
Background technology
The introducing of a large amount of inverters in photovoltaic cluster grid-connected system so that power distribution network becomes containing multiple natural resonance points Complicated high-order LC network.Photovoltaic is exerted oneself and is had undulatory property and wideband spectrality simultaneously, and the harmonic wave in system easily excites resonance phenomena. The resonance that inverter parallel produces can cause grid-connected failure even to damage grid-connection device, sets photovoltaic, power distribution network and user Standby safe operation brings extreme influence.
Low frequency part is only decomposed by each step during wavelet decomposition, and it is uneven that the frequency band obtained divides, and leads The number of writing HFS low frequency resolution and the low temporal resolution of low frequency part.And wavelet package transforms compensate for wavelet transformation not Can be to the shortcoming of high fdrequency component segmentation, it is possible to obtain the frequency band being evenly dividing.Wavelet package transforms can be according to the feature of signal, certainly Adaptively select frequency band so that it is match with the frequency spectrum of signal, improve time frequency resolution.But the frequency that WAVELET PACKET DECOMPOSITION obtains Band is not by frequency size distribution, it is impossible to directly judges resonant frequency range according to the result of WAVELET PACKET DECOMPOSITION, is unfavorable for humorous Shake detection.The present invention readjusts low pass and the arrangement of high pass filter group, proposes one and improves Wavelet Packet Algorithm, it is possible to obtains By the frequency band of frequency size distribution and effectively detect the frequency band range of resonance in photovoltaic cluster grid-connected system.
Resonance in place of being different from harmonic wave is: resonance can make electric current and the distortion of voltage waveform generation aperiodicity even vibrate, And the wave distortion that harmonic wave causes is periodic, wavelet packet analysis result is embodied in resonance signal place band Waveform Amplitude present positive growth always.
Existing harmonic detecting method weak point based on wavelet package transforms is, just for conventional distributed energy Grid-connected system is analyzed, and for the grid-connected more complicated harmonic wave situation caused of distributed energy cluster, does not but have the most in addition Detection is analyzed.The frequency band that the detection method based on wavelet package transforms that in addition, there will be obtains is not by frequency size distribution, and Analyzed just for harmonic wave, and this more serious power quality problem of resonance is not analyzed.
Summary of the invention
The technical problem to be solved is to provide a kind of cluster to distributed energy and is incorporated into the power networks adaptability By force, it is simple to the Resonance detector method based on the photovoltaic cluster grid-connected system improving wavelet package transforms of practical engineering application.
The technical solution adopted in the present invention is: a kind of based on photovoltaic cluster grid-connected system humorous improving wavelet package transforms Shake detection method, comprise the steps:
1) primary signal is carried out db40 WAVELET PACKET DECOMPOSITION;
2) readjust low pass and the arrangement of high pass filter group, obtain by the uniform frequency band of frequency size distribution;
3) step 2) waveforms amplitude presents the frequency band of positive growth always in the uniform frequency band by frequency size distribution that obtains, It is photovoltaic cluster grid-connected resonance place frequency band.
Step 1) described in decomposition be:
If i (n) is primary signal, X(i,j)Represent i-th layer of upper jth wavelet packet coefficient, FhAnd FgIt is respectively wavelet packet to divide Solve low pass and high pass filter coefficient, then WAVELET PACKET DECOMPOSITION is as follows:
X ( 0 , 0 ) = i ( n ) X ( i , 2 j ) = Σ k F h ( k - 2 n ) X ( i - 1 , j ) X ( i , 2 j + 1 ) = Σ k F g ( k - 2 n ) X ( i - 1 , j ) - - - ( 1 )
In formula, FhAnd FgDetermined by wavelet basis, i ∈ N, j=0,1,2,3 ..., 2i-1。
Step 2) including:
(1) sample frequency is set as fs, according to Nyquist's theorem, the frequency band that WAVELET PACKET DECOMPOSITION can detect is [0, fs/ 2], Through one layer of WAVELET PACKET DECOMPOSITION, whole frequency band is divided into low-frequency band [0, fs/22] and high frequency band [fs/22,fs/2];
(2) low frequency signal is by, after down sample, through two layers of decomposition, being divided into again [0, fs/23] and [fs/23,fs/ 22] two frequency bands;
(3) mode as described in (2nd) step, carries out third layer to the decomposition of n-th layer, successively until completing the n-layer set Decompose, i.e. realize the binary partition of low-frequency band;
(4) high-frequency signal is after down sample, and high-frequency signal is first converted into low frequency signal, the most again through two layers of decomposition, High frequency band is divided into [fs/22,fs3/23] and [fs3/23,fs/ 2] two frequency bands;
(5) mode as described in (4th) step, carries out third layer to the decomposition of n-th layer, successively until completing the n-layer set Decompose, i.e. realize the binary partition of high frequency band, obtain the frequency band being evenly dividing;
(6) the most corresponding filter paths of each node and a frequency band in wavelet packet tree;
(7) set signal and be designated as ' 0 ' through the path of low pass filter, set signal and remember through the path of high pass filter For ' 1 ', then obtain the binary digit that filter paths is corresponding;
(8) can update, during improving wavelet package transforms, the binary digit that filter paths is corresponding, often take one-bit digital Time, by the number of 1 before the left-to-right position checking this numeral, if odd number, then this position digital is negated, if even number, then This position digital is constant;
(9) through readjusting low pass and the arrangement of high pass filter group, a new binary digit, new two are obtained The value of binary digits represents the order of this node, i.e. obtains by the uniform frequency band of frequency size distribution.
The i.e. signal of filter paths described in (6th) step arrive node from left to right the bank of filters of process, described Frequency band is the frequency range that node is corresponding.
The Resonance detector method based on the photovoltaic cluster grid-connected system improving wavelet package transforms of the present invention, with wavelet transformation Comparing, wavelet package transforms can constantly carry out binary partition, the frequency band being evenly distributed to high fdrequency component.And improve little Original wavelet package transforms, by readjusting low pass and the arrangement of high pass filter group, is improved by ripple packet transform, Arrive the uniform frequency band by the distribution of frequency size order, improve the accuracy of detection.By checking that waveforms amplitude presents always The frequency band of positive growth, obtains resonance signal place frequency band in photovoltaic cluster grid-connected system.
Accompanying drawing explanation
Fig. 1 is the schematic diagram of photovoltaic cluster grid-connected system;
Fig. 2 is the schematic diagram of 3 layers of WAVELET PACKET DECOMPOSITION;
Fig. 3 is based on filter bank structure and the schematic diagram of frequency band range thereof improving wavelet package transforms
Fig. 4 is the schematic diagram of the grid-connected resonance current signal of photovoltaic cluster;
Fig. 5 a is the schematic diagram of X (5,0) node improving wavelet package transforms;
Fig. 5 b is the schematic diagram of X (5,1) node improving wavelet package transforms;
Fig. 5 c is the schematic diagram of X (5,3) node improving wavelet package transforms;
Fig. 5 d is the schematic diagram of X (5,2) node improving wavelet package transforms;
Fig. 5 e is the schematic diagram of X (5,6) node improving wavelet package transforms;
Fig. 5 f is the schematic diagram of X (5,7) node improving wavelet package transforms;
Fig. 5 g is the schematic diagram of X (5,5) node improving wavelet package transforms;
Fig. 5 h is the schematic diagram of X (5,4) node improving wavelet package transforms.
Detailed description of the invention
Below in conjunction with embodiment and accompanying drawing to the present invention based on the photovoltaic cluster grid-connected system improving wavelet package transforms Resonance detector method is described in detail.
The Resonance detector method based on the photovoltaic cluster grid-connected system improving wavelet package transforms of the present invention, improves wavelet packet Conversion constantly carries out binary partition to low frequency and high frequency band, and readjusts low pass and the arrangement of high pass filter group, To the uniform frequency band by the distribution of frequency size order.Resonance signal in photovoltaic cluster grid-connected system is improved wavelet packet divide Analysis, extracts waveforms amplitude and presents the frequency band of positive growth, this frequency band i.e. resonance place frequency band always.
The Resonance detector method based on the photovoltaic cluster grid-connected system improving wavelet package transforms of the present invention, including walking as follows Rapid:
1) primary signal is carried out db40 WAVELET PACKET DECOMPOSITION, be not by each frequency band of frequency size distribution, described Decomposition be:
If i (n) is primary signal, X(i,j)Represent i-th layer of upper jth wavelet packet coefficient, FhAnd FgIt is respectively wavelet packet to divide Solve low pass and high pass filter coefficient, then WAVELET PACKET DECOMPOSITION is as follows:
X ( 0 , 0 ) = i ( n ) X ( i , 2 j ) = Σ k F h ( k - 2 n ) X ( i - 1 , j ) X ( i , 2 j + 1 ) = Σ k F g ( k - 2 n ) X ( i - 1 , j ) - - - ( 1 )
In formula, FhAnd FgDetermined by wavelet basis, i ∈ N, j=0,1,2,3 ..., 2i-1。
2) readjust low pass and the arrangement of high pass filter group, obtain by the uniform frequency band of frequency size distribution,
3 layers of WAVELET PACKET DECOMPOSITION schematic diagram are as in figure 2 it is shown, (i j) is the labelling of each node, wherein word after WAVELET PACKET DECOMPOSITION Female i represents Decomposition order, and j represents order.The arrangement readjusting low pass and high pass filter group includes:
(1) sample frequency is set as fs, according to Nyquist's theorem, the frequency band that WAVELET PACKET DECOMPOSITION can detect is [0, fs/ 2], Through one layer of WAVELET PACKET DECOMPOSITION, whole frequency band is divided into low-frequency band [0, fs/22] and high frequency band [fs/22,fs/2];
(2) low frequency signal is by, after down sample, through two layers of decomposition, being divided into again [0, fs/23] and [fs/23,fs/ 22] two frequency bands;
(3) mode as described in (2nd) step, carries out third layer to the decomposition of n-th layer, successively until completing the n-layer set Decompose, i.e. realize the binary partition of low-frequency band;
(4) high-frequency signal is after down sample, and high-frequency signal is first converted into low frequency signal, the most again through two layers of decomposition, High frequency band is divided into [fs/22,fs3/23] and [fs3/23,fs/ 2] two frequency bands;
(5) mode as described in (4th) step, carries out third layer to the decomposition of n-th layer, successively until completing the n-layer set Decompose, i.e. realize the binary partition of high frequency band, obtain the frequency band being evenly dividing;
(6) as it is shown on figure 3, X (n), LP, HP are expressed as primary signal, low pass filter and high pass filter.Small echo The most corresponding filter paths of each node of Bao Shuzhong and a frequency band, wherein, described filter paths i.e. signal arrives Reach node from left to right the bank of filters of process, described frequency band is the frequency range that node is corresponding;
(7) set signal and be designated as ' 0 ' through the path of low pass filter, set signal and remember through the path of high pass filter For ' 1 ', then obtain the binary digit that filter paths is corresponding;
(8) can update, during improving wavelet package transforms, the binary digit that filter paths is corresponding, often take one-bit digital Time, by the number of 1 before the left-to-right position checking this numeral, if odd number, then this position digital is negated, if even number, then This position digital is constant;
(9) through readjusting low pass and the arrangement of high pass filter group, a new binary digit, new two are obtained The value of binary digits represents the order of this node, i.e. obtains by the uniform frequency band of frequency size distribution.
3) step 2) waveforms amplitude presents the frequency band of positive growth always in the uniform frequency band by frequency size distribution that obtains, It is photovoltaic cluster grid-connected resonance place frequency band.
Below, as a example by the photovoltaic cluster grid-connected system shown in Fig. 1, model in MATLAB/SIMULINK, to the present invention The Resonance detector method based on the photovoltaic cluster grid-connected system improving wavelet package transforms proposed carries out simulating, verifying.This photovoltaic collection Group's grid-connected system is made up of photovoltaic array, photovoltaic combining inverter, LCL filter and electrical network, and PVn represents photovoltaic generation unit, udcn、uinvn、ucnAnd ugRepresent DC voltage, inverter side voltage, capacitance voltage and line voltage, i respectively1,n、i2,nAnd ig Represent inverter side inductive current, grid side inductive current and power network current, L respectively1,nAnd R1,nRepresent the inductance of inverter side And resistance, L2,nAnd R2,nRepresent inductance and resistance, the L of grid sidegAnd RgRepresenting electrical network inductance and resistance, PCC represents parallel inverter The points of common connection of device.
If carrying out primary signal based on the 5 layers of decomposition improving wavelet package transforms, taking sample frequency is 6400Hz, through 1 layer After WAVELET PACKET DECOMPOSITION, low-frequency band scope is 0-1600Hz, and high frequency band scope is 1600-3200Hz.Constantly carry out binary system Frequency band divides, and obtains Wavelet packet filtering device group structure and frequency band range thereof as shown in Figure 3.Understand based on improving small echo according to Fig. 3 The signal frequency range of packet transform is as shown in table 2, the node during wherein first row is wavelet packet tree, and the 2nd row are the filters of node correspondence The binary word in ripple device path, the 3rd row be readjust the arrangement of low pass and high pass filter group after, node respective filter road The binary word in footpath, the 4th row be readjust the arrangement of low pass and high pass filter group after, the order of node, the 5th row are nodes Corresponding frequency band.I.e. according to node and the corresponding relation of frequency band improving wavelet package transforms, it may be determined that each node is corresponding Frequency band.Such as, the 7th node, respective filter path is LP-LP-HP-HP-HP, is designated as 00111, obtains new two after improvement Binary digits 00101, the 5th frequency band [500,600Hz] of corresponding WAVELET PACKET DECOMPOSITION.
Table 2 is based on the signal frequency range improving wavelet package transforms
Node Old binary word New binary word Order Frequency band
X(5,0) 00000 00000 0 [0,100Hz]
X(5,1) 00001 00001 1 [100,200Hz]
X(5,2) 00010 00011 3 [300,400Hz]
X(5,3) 00011 00010 2 [200,300Hz]
X(5,4) 00100 00111 7 [700,800Hz]
X(5,5) 00101 00110 6 [600,700Hz]
X(5,6) 00110 00100 4 [400,500Hz]
X(5,7) 00111 00101 5 [500,600Hz]
The harmonic wave of grid-connected current is as shown in Figure 4, it can be seen that resonance phenomena occurs in grid-connected current.The 5 of resonance current Layer db40 improved wavelet packet analysis result as shown in Fig. 5 a, Fig. 5 b, Fig. 5 c, Fig. 5 d, Fig. 5 e, Fig. 5 f, Fig. 5 g, Fig. 5 h, according to The distribution of frequency size order arranges.
From the improvement wavelet analysis result of resonance current signal, improve only X among the component after wavelet package transforms The waveforms amplitude of (5,7) presents positive growth from the t=0 moment always, can obtain the resonance of photovoltaic cluster grid-connected system according to table 2 Frequency band range is [500,600Hz].

Claims (4)

1. a Resonance detector method based on the photovoltaic cluster grid-connected system improving wavelet package transforms, it is characterised in that include Following steps:
1) primary signal is carried out db40 WAVELET PACKET DECOMPOSITION;
2) readjust low pass and the arrangement of high pass filter group, obtain by the uniform frequency band of frequency size distribution;
3) step 2) waveforms amplitude presents the frequency band of positive growth always in the uniform frequency band by frequency size distribution that obtains, it is Photovoltaic cluster grid-connected resonance place frequency band.
2. obtain described Resonance detector side based on the photovoltaic cluster grid-connected system improving wavelet package transforms according to claim 1 Method, it is characterised in that step 1) described in decomposition be:
If i (n) is primary signal, X(i,j)Represent i-th layer of upper jth wavelet packet coefficient, FhAnd FgIt is respectively WAVELET PACKET DECOMPOSITION low pass With high pass filter coefficient, then WAVELET PACKET DECOMPOSITION is as follows:
X ( 0 , 0 ) = i ( n ) X ( i , 2 j ) = Σ k F h ( k - 2 n ) X ( i - 1 , j ) X ( i , 2 j + 1 ) = Σ k F g ( k - 2 n ) X ( i - 1 , j ) - - - ( 1 )
In formula, FhAnd FgDetermined by wavelet basis, i ∈ N, j=0,1,2,3 ..., 2i-1。
Resonance detector method based on the photovoltaic cluster grid-connected system improving wavelet package transforms the most according to claim 1, It is characterized in that, step 2) including:
(1) sample frequency is set as fs, according to Nyquist's theorem, the frequency band that WAVELET PACKET DECOMPOSITION can detect is [0, fs/ 2], pass through One layer of WAVELET PACKET DECOMPOSITION, whole frequency band is divided into low-frequency band [0, fs/22] and high frequency band [fs/22,fs/2];
(2) low frequency signal is by, after down sample, through two layers of decomposition, being divided into again [0, fs/23] and [fs/23,fs/22] two Individual frequency band;
(3) mode as described in (2nd) step, carries out third layer successively to the decomposition of n-th layer, until the n-layer completing to set is decomposed, I.e. realize the binary partition of low-frequency band;
(4) high-frequency signal is after down sample, and high-frequency signal is first converted into low frequency signal, the most again through two layers of decomposition, high frequency Frequency band is divided into [fs/22,fs3/23] and [fs3/23,fs/ 2] two frequency bands;
(5) mode as described in (4th) step, carries out third layer successively to the decomposition of n-th layer, until the n-layer completing to set is decomposed, I.e. realize the binary partition of high frequency band, obtain the frequency band being evenly dividing;
(6) the most corresponding filter paths of each node and a frequency band in wavelet packet tree;
(7) set signal and be designated as ' 0 ' through the path of low pass filter, set signal and be designated as through the path of high pass filter ' 1 ', then obtain the binary digit that filter paths is corresponding;
(8) can update, during improving wavelet package transforms, the binary digit that filter paths is corresponding, when often taking one-bit digital, by The number of 1 before the left-to-right position checking this numeral, if odd number, then this position digital is negated, if even number, then this position Numeral is constant;
(9) through readjusting low pass and the arrangement of high pass filter group, a new binary digit, new binary system are obtained The value of numeral represents the order of this node, i.e. obtains by the uniform frequency band of frequency size distribution.
Resonance detector method based on the photovoltaic cluster grid-connected system improving wavelet package transforms the most according to claim 3, It is characterized in that, the i.e. signal of filter paths described in (6th) step arrive node from left to right the bank of filters of process, described Frequency band be the frequency range that node is corresponding.
CN201610604422.9A 2016-07-28 2016-07-28 Resonance detector method based on the photovoltaic cluster grid-connected system improving wavelet package transforms Pending CN106291104A (en)

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Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102305892A (en) * 2011-07-13 2012-01-04 上海仪器仪表研究所 Novel power grid harmonic detection analysis device
CN102721890A (en) * 2012-07-02 2012-10-10 上海仪器仪表研究所 Practical monitoring device for virtual terminal power grid
WO2014052738A1 (en) * 2012-09-28 2014-04-03 Wayne State University Ion current use for combustion resonance detection, reduction and engine control
CN105223403A (en) * 2015-08-27 2016-01-06 南京南瑞太阳能科技有限公司 The wavelet packet extracting method of a kind of combining inverter net side resonance current information

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102305892A (en) * 2011-07-13 2012-01-04 上海仪器仪表研究所 Novel power grid harmonic detection analysis device
CN102721890A (en) * 2012-07-02 2012-10-10 上海仪器仪表研究所 Practical monitoring device for virtual terminal power grid
WO2014052738A1 (en) * 2012-09-28 2014-04-03 Wayne State University Ion current use for combustion resonance detection, reduction and engine control
CN105223403A (en) * 2015-08-27 2016-01-06 南京南瑞太阳能科技有限公司 The wavelet packet extracting method of a kind of combining inverter net side resonance current information

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
肖华锋 等: "规模化并网逆变器网侧谐振电流信息的小波包提取方法", 《电力自动化设备》 *
薛蕙 等: "小波包变换(W PT)频带划分特性的分析", 《电力系统及其自动化学报》 *

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Application publication date: 20170104