CN104535855A  Electric energy quality disturbing signal detecting algorithm based on discrete orthogonal S transformation  Google Patents
Electric energy quality disturbing signal detecting algorithm based on discrete orthogonal S transformation Download PDFInfo
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 CN104535855A CN104535855A CN201410785364.5A CN201410785364A CN104535855A CN 104535855 A CN104535855 A CN 104535855A CN 201410785364 A CN201410785364 A CN 201410785364A CN 104535855 A CN104535855 A CN 104535855A
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Abstract
The invention relates to a detecting method of power grid disturbing signals in an electric power system, in particular to an electric energy quality disturbing signal detecting algorithm based on discrete orthogonal S transformation. The algorithm comprises the steps that after a frequency variable (representing the center of a frequency band) and the width and time variable (representing a time point) of the frequency band are introduced based on traditional S transformation, discretization orthogonalization processing is carried out on timedomain signals, discrete orthogonal S transformation is obtained, then discrete orthogonal S transformation is applied to carrying out timefrequency analysis on several common electric energy quality disturbing signals, an obtained discrete orthogonal S transformation coefficient matrix is used for locating start and stop disturbing moments, and finally the disturbing signals are detected. According to the algorithm, the start and stop moments of the disturbing signals can be detected accurately and effectively, a new thought is provided for electric energy quality disturbing signal detecting, and development of a disturbing signal analysis method is facilitated.
Description
Technical field
The present invention relates to the detection method of grid disturbance signal in electric system, be specially a kind of Power Quality Disturbance detection algorithm based on Discrete Orthogonal Stransformation.
Background technology
Power quality problem is all a problem received much concern all the time, and in the middle of many power quality problems, complicated Power Quality Disturbance stands in the breach.A large amount of power electronic devices and the use of nonlinear element can produce disturbing signal, detect the start/stop time of these disturbing signals quickly and accurately, for guarantee with improve the quality of power supply most important.
At present, short time discrete Fourier transform (STFT), wavelet transformation, neural network, Stransformation are the methods of common detection Power Quality Disturbance, for nonstatic signals, short time discrete Fourier transform be limited to window function fixed width and can not the high and low frequency composition of detection signal dynamically; Wavelet transformation is by variable window function, although more effectively can detect the frequency content of nonstatic signals, not good for time domain disturbing signal (such as voltage swell, fall temporarily) Detection results; Although neural network effectively can carry out time frequency analysis, first need to train, and need a large amount of prior imformations, therefore calculated amount is comparatively large, and algorithm is complicated, poor real; Stransformation alternatively effectively can analyze the method for timefrequency domain signal, be similar to continuous wavelet transform, but the regulatory factors such as the position of its Gauss function and width are fixed, and cause its adaptive ability poor, timefrequency complex matrixs a large amount of in algorithmic procedure too increases algorithm complex.
More than analyze known, in order to overcome the various problems that traditional time frequency analysis algorithm exists, find a kind of algorithm relatively simple, frequency resolution is high, and the algorithm that accuracy is good is crucial.
Summary of the invention
The present invention effectively can not detect the problem of the start/stop time of disturbing signal in order to the method solving traditional detection Power Quality Disturbance, provide a kind of Power Quality Disturbance detection algorithm based on Discrete Orthogonal Stransformation, this algorithm is applicable to duration power quality disturbances, frequency resolution is high, algorithm is easy, and accuracy is good.
The present invention adopts following technical scheme to realize: a kind of Power Quality Disturbance detection algorithm based on Discrete Orthogonal Stransformation, comprises the following steps:
S1: to Power Quality Disturbance emulation, obtain disturbing signal h (t), and disturbing signal h (t) is sampled;
S2: carry out Discrete Orthogonal Stransformation to the disturbing signal h (t) sampled, obtains Discrete Orthogonal Stransformation matrix of coefficients, draws disturbing signal waveform according to matrix of coefficients;
S3: according to the disturbing signal waveform of matrix of coefficients and drafting, the initial time of amplitude change in final Location perturbation signal and end time.
Abovementioned a kind of Power Quality Disturbance detection algorithm based on Discrete Orthogonal Stransformation, the Discrete Orthogonal Stransformation in described S2 comprises the following steps:
Step one: by the disturbing signal h (t) that sampled through fast fourier transform, obtain frequencyregion signal H (f);
Step 2: the width beta of setpoint frequency variable ν, frequency band and time variable τ trivariablees, then composes initial value to these three variablees, and constructs N number of orthogonal Stransformation basis function vector;
Step 3: create Ramp matrix, in Ramp matrix, element is positive and negative one alternately to occur, namely [1,1 ,1,1 ... ];
Step 4: by frequencyregion signal H (f) in step one after inverse Fourier transform, is multiplied with the orthogonal Stransformation basis function vector that step 2 obtains, then with the Ramp matrix multiple in step 3; Obtain Discrete Orthogonal Stransformation matrix of coefficients;
Step 5: the Discrete Orthogonal Stransformation matrix of coefficients that step 4 obtains draw in MATLAB carry out visual.
Abovementioned a kind of Power Quality Disturbance detection algorithm based on Discrete Orthogonal Stransformation, composes initial value to the width beta of frequency variable ν, frequency band and time variable τ trivariablees in described step 2 and follows following provisions: τ=0,1 ... β1; Choosing of ν and β must ensure that the use of each Frequency point once and only uses once, and specify and facilitate three variable assignments more than meeting, introduce variable p, assignment condition is as follows: p=2 ..., log
_{2}(N)1, ν=2
^{(p1)}+ 2
^{(p2)}, β=2
^{(p1)}, τ=0,1 ..., 2
^{(p1)}1.
Abovementioned a kind of Power Quality Disturbance detection algorithm based on Discrete Orthogonal Stransformation, after composing initial value to the width beta of frequency variable ν, frequency band and time variable τ trivariablees in step 2, according to the N number of orthogonal Stransformation basis function vector of following formula construction:
${S\left[k\right]}_{[v,\mathrm{\β},\mathrm{\τ}]}=\frac{1}{\sqrt{\mathrm{\β}}}\underset{f=v\frac{\mathrm{\β}}{2}}{\overset{v+\frac{\mathrm{\β}}{2}1}{\mathrm{\Σ}}}\mathrm{exp}(i2\mathrm{\π}\frac{k}{N}f)\mathrm{exp}\left(i2\mathrm{\π}\frac{\mathrm{\τ}}{\mathrm{\β}}f\right)\mathrm{exp}(\mathrm{i\π\τ}),$ S [k] in formula
_{[ν, β, τ]}represent a kth orthogonal Stransformation basis function vector.
Compared with prior art, the present invention introduces ν, β and τ trivariablees, makes discretize orthogonalization process to Stransformation, by greatly improving frequency resolution to whole traversals of time parameter; By slidingmodel control signal, reduce operand; Discrete Orthogonal Stransformation is used to carry out analyzing and processing to several Power Quality Disturbance, extract the actual parameter of disturbing signal, draw Discrete Orthogonal Stransformation matrix of coefficients figure, accurately detect the disturbance moment, provide a kind of new thinking for Power Quality Disturbance detects, be beneficial to the development of disturbing signal analytical approach.
Accompanying drawing explanation
Fig. 1 is algorithm flow chart of the present invention;
Fig. 2Fig. 6 is Discrete Orthogonal Stransformation disturbing signal analysis result figure, and wherein Fig. 2 is that voltage swell falls analysis result temporarily; Fig. 3 is voltage oscillation analysis result; Fig. 4 is pulse signal analysis result; Fig. 5 is voltage interruption analysis result; Fig. 6 is that the voltage swell containing harmonic wave falls analysis result temporarily.
Embodiment
Based on a Power Quality Disturbance detection algorithm for Discrete Orthogonal Stransformation, comprise the following steps:
S1: utilize MATLAB software to emulate Power Quality Disturbance, obtain disturbing signal h (t), and disturbing signal h (t) is sampled;
S2: carry out Discrete Orthogonal Stransformation to the disturbing signal h (t) sampled, obtains Discrete Orthogonal Stransformation matrix of coefficients, draws disturbing signal waveform according to matrix of coefficients;
S3: according to the waveform of matrix of coefficients and drafting, the initial sum end time of amplitude change in final Location perturbation signal.
Abovementioned a kind of Power Quality Disturbance detection algorithm based on Discrete Orthogonal Stransformation, the Discrete Orthogonal Stransformation in described S2 comprises the following steps:
Step one: by the disturbing signal h (t) that sampled through fast fourier transform, obtain frequencyregion signal H (f);
Step 2: the width beta of setpoint frequency variable ν, frequency band and time variable τ trivariablees, then composes initial value to these three variablees, and constructs N number of orthogonal Stransformation basis function vector;
Step 3: create Ramp matrix, in Ramp matrix, element is positive and negative one alternately to occur, namely [1,1 ,1,1 ... ];
Step 4: by frequencyregion signal H (f) in step one after inverse Fourier transform, is multiplied with the orthogonal Stransformation basis function vector that step 2 obtains, then with the Ramp matrix multiple in step 3; Obtain Discrete Orthogonal Stransformation matrix of coefficients;
Step 5: the Discrete Orthogonal Stransformation matrix of coefficients that step 4 obtains draw in MATLAB carry out visual.
Abovementioned a kind of Power Quality Disturbance detection algorithm based on Discrete Orthogonal Stransformation, composes initial value to the width beta of frequency variable ν, frequency band and time variable τ trivariablees in described step 2 and follows following provisions: τ=0,1 ... β1; Choosing of ν and β must ensure that the use of each Frequency point once and only uses once, and specify and facilitate three variable assignments more than meeting, introduce variable p, assignment condition is as follows: p=2 ..., log
_{2}(N)1, ν=2
^{(p1)}+ 2
^{(p2)}, β=2
^{(p1)}, τ=0,1 ..., 2
^{(p1)}1.
Abovementioned a kind of Power Quality Disturbance detection algorithm based on Discrete Orthogonal Stransformation, after composing initial value to the width beta of frequency variable ν, frequency band and time variable τ trivariablees in step 2, according to the N number of orthogonal Stransformation basis function vector of following formula construction:
${S\left[k\right]}_{[v,\mathrm{\β},\mathrm{\τ}]}=\frac{1}{\sqrt{\mathrm{\β}}}\underset{f=v\frac{\mathrm{\β}}{2}}{\overset{v+\frac{\mathrm{\β}}{2}1}{\mathrm{\Σ}}}\mathrm{exp}(i2\mathrm{\π}\frac{k}{N}f)\mathrm{exp}\left(i2\mathrm{\π}\frac{\mathrm{\τ}}{\mathrm{\β}}f\right)\mathrm{exp}(\mathrm{i\π\τ}),$ S [k] in formula
_{[ν, β, τ]}represent a kth orthogonal Stransformation basis function vector.
During concrete enforcement, the conversion process of Discrete Orthogonal Stransformation is: the Stransformation of disturbing signal h (t) is defined as follows:
$S\left\{h\left(t\right)\right\}=\underset{\∞}{\overset{\∞}{\∫}}h\left(t\right)\frac{\leftf\right}{\sqrt{2\mathrm{\π}}}{e}^{\frac{{(\mathrm{\τ}t)}^{2}{f}^{2}}{2}}{e}^{i2\mathrm{\πft}}\mathrm{dt},$ In formula,
$\frac{\leftf\right}{\sqrt{2\mathrm{\π}}}{e}^{{(\mathrm{\τ}t)}^{2}{f}^{2}/2}$ For Gauss function, be also frequency sensitive window function simultaneously, for high band, Gaussian window width relative narrower; For lowfrequency range, Gaussian window width is relatively wide; Abovementioned expression formula is transformed into Fourier:
$S\{\mathrm{\τ},f\}=\underset{\∞}{\overset{\∞}{\∫}}H(\mathrm{\α}+f){e}^{\frac{2{\mathrm{\π}}^{2}{\mathrm{\α}}^{2}}{{f}^{2}}}{e}^{i2\mathrm{\π\αt}}\mathrm{d\α},$ Wherein:
$H(\mathrm{\α}+f)=\underset{\∞}{\overset{\∞}{\∫}}h\left(t\right){e}^{i2\mathrm{\π}(\mathrm{\α}+f)t}\mathrm{dt},$ Slidingmodel control is carried out to above formula, obtains N point Stransformation formula:
t=0 ..., N1, introduces ν, β and τ trivariablees, structure Discrete Orthogonal Stransformation basis function vector:
${S\left[k\right]}_{[v,\mathrm{\β},\mathrm{\τ}]}=\frac{1}{\sqrt{\mathrm{\β}}}\underset{f=v\frac{\mathrm{\β}}{2}}{\overset{v+\frac{\mathrm{\β}}{2}1}{\mathrm{\Σ}}}\mathrm{exp}(i2\mathrm{\π}\frac{k}{N}f)\mathrm{exp}\left(i2\mathrm{\π}\frac{\mathrm{\τ}}{\mathrm{\β}}f\right)\mathrm{exp}(\mathrm{i\π\τ}),$ Finally obtain the expression formula of the Discrete Orthogonal Stransformation of disturbing signal h (t):
discrete Orthogonal Stransformation matrix of coefficients is calculated according to above formula.
Below voltage swell fallen temporarily, transient oscillation, pulse signal, voltage interruption, fall these five kinds of common Power Quality Disturbances temporarily containing the voltage swell of harmonic wave and carry out the analysis of Discrete Orthogonal Stransformation.Abovementioned five kinds of disturbing signal fundamental frequencies are 50Hz, and the signal sampling time is 0.2 second, and sampling rate is 2560Hz, and sampling number is 512 points.Discrete Orthogonal Stransformation analysis result is shown in Fig. 2Fig. 6.
1. voltage swell falls signal analysis temporarily: can find out in Fig. 2, between 148153 sampled point, occurs obvious spike between 348351 sampled point.The catastrophe point of amplitude is described, namely disturbance start/stop time is the 148th point and the 348th point respectively.
2. transient oscillation analysis: can find out in Fig. 3, there is spike in the 152nd point, in the middle part of the image of the 354th point, colour band interrupts.The start/stop time (the 152nd point and the 354th point) of oscillator signal disturbance can be found out clearly by figure.
3. pulse signal analysis: can find out in Fig. 4, there is spike in 262265 sampled point.The catastrophe point of amplitude is described, namely disturbance start/stop time is the 262nd point and the 265th point respectively.
4., between 201204 sampled point, between 304307 sampled point, there is obvious spike in voltage interruption analysis: can find out in Fig. 5.The catastrophe point of amplitude is described, namely disturbance start/stop time is the 201st point and the 304th point respectively.
5. the voltage swell containing harmonic wave falls analysis temporarily: can find out in Fig. 6, between 193196 sampled point, occur obvious spike between 358360 sampled point.The catastrophe point of amplitude is described, namely disturbance start/stop time is the 193rd point and the 358th point respectively.
Claims (4)
1., based on a Power Quality Disturbance detection algorithm for Discrete Orthogonal Stransformation, it is characterized in that comprising the following steps:
S1: to Power Quality Disturbance emulation, obtain disturbing signal h (t), and disturbing signal h (t) is sampled;
S2: carry out Discrete Orthogonal Stransformation to the disturbing signal h (t) sampled, obtains Discrete Orthogonal Stransformation matrix of coefficients, draws disturbing signal waveform according to matrix of coefficients;
S3: according to the disturbing signal waveform of matrix of coefficients and drafting, the initial time of amplitude change in final Location perturbation signal and end time.
2. a kind of Power Quality Disturbance detection algorithm based on Discrete Orthogonal Stransformation according to claim 1, is characterized in that the Discrete Orthogonal Stransformation in described S2 comprises the following steps:
Step one: by the disturbing signal h (t) that sampled through fast fourier transform, obtain frequencyregion signal H (f);
Step 2: the width beta of setpoint frequency variable ν, frequency band and time variable τ trivariablees, then composes initial value to these three variablees, and constructs N number of orthogonal Stransformation basis function vector;
Step 3: create Ramp matrix, in Ramp matrix, element is positive and negative one and alternately occurs, namely [1,1 ,1,1 ... ];
Step 4: by frequencyregion signal H (f) in step one after inverse Fourier transform, is multiplied with the orthogonal Stransformation basis function vector that step 2 obtains, then with the Ramp matrix multiple in step 3; Obtain Discrete Orthogonal Stransformation matrix of coefficients;
Step 5: the Discrete Orthogonal Stransformation matrix of coefficients that step 4 obtains draw in MATLAB carry out visual.
3. a kind of Power Quality Disturbance detection algorithm based on Discrete Orthogonal Stransformation according to claim 2, it is characterized in that composing initial value to the width beta of frequency variable ν, frequency band and time variable τ trivariablees in described step 2 follows following provisions: τ=0,1 ... β1; Choosing of ν and β must ensure that the use of each Frequency point once and only uses once.
4. a kind of Power Quality Disturbance detection algorithm based on Discrete Orthogonal Stransformation according to claim 2, after it is characterized in that composing initial value to the width beta of frequency variable ν, frequency band and time variable τ trivariablees in step 2, according to the N number of orthogonal Stransformation basis function vector of following formula construction:
${S\left[k\right]}_{[v,\mathrm{\β},\mathrm{\τ}]}=\frac{1}{\sqrt{\mathrm{\β}}}\underset{f=v\frac{\mathrm{\β}}{2}}{\overset{v+\frac{\mathrm{\β}}{2}1}{\mathrm{\Σ}}}\mathrm{exp}(i2\mathrm{\π}\frac{k}{N}f)\mathrm{exp}\left(i2\mathrm{\π}\frac{\mathrm{\τ}}{\mathrm{\β}}f\right)\mathrm{exp}(\mathrm{i\π\τ})$ S [k] in formula
_{[ν, β, τ]}represent a kth orthogonal Stransformation basis function vector.
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CN103323702A (en) *  20130528  20130925  西南交通大学  Composite power quality disturbing signal identifying method 
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Application publication date: 20150422 