CN106021805A - Electric energy meter dynamic testing signal fitting method based on HHT analysis - Google Patents
Electric energy meter dynamic testing signal fitting method based on HHT analysis Download PDFInfo
- Publication number
- CN106021805A CN106021805A CN201610394141.5A CN201610394141A CN106021805A CN 106021805 A CN106021805 A CN 106021805A CN 201610394141 A CN201610394141 A CN 201610394141A CN 106021805 A CN106021805 A CN 106021805A
- Authority
- CN
- China
- Prior art keywords
- signal
- amplitude
- harmonic
- energy meter
- frequency
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Computer Hardware Design (AREA)
- Evolutionary Computation (AREA)
- Geometry (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Measuring Frequencies, Analyzing Spectra (AREA)
Abstract
The invention provides an electric energy meter dynamic testing signal fitting method based on HHT analysis. The method comprises the steps that EMD decomposition is conducted on an actually-measured power grid waveform signal to obtain a modulating wave signal representing dynamic voltage fluctuation, a steady-state harmonic signal and an inter-harmonic signal separately; Hilbert transformation and inverse transformation are conducted on the modulating wave signal representing dynamic voltage fluctuation separately to obtain a new analysis signal, an instantaneous amplitude value signal of the analysis signal is solved, EMD decomposition is conducted on the instantaneous amplitude value to obtain amplitude-modulated wave signals, and amplitude value and frequency parameter information of dynamic voltage fluctuation is solved through Hilbert transformation; Hilbert transformation is directly conducted on the steady-state harmonic signal and the inter-harmonic signal to obtain amplitude value and frequency parameter information of harmonic waves and inter-harmonic waves; fitting is conducted through a least square method according to obtained waveform information of the dynamic voltage amplitude-modulated waves, the steady-state harmonic waves and the inter-harmonic waves to obtain a digital signal expression finally used for energy meter dynamic testing.
Description
Technical field
The present invention relates to a kind of electric energy meter dynamic measuring signal approximating method analyzed based on HHT, belong to electric power instrument
Table technical field of measurement and test.
Background technology
In recent years, China's intelligent grid has been enter into the all-round construction stage, and intelligent electric energy meter is as intelligent grid
Important component part is widely used in power information acquisition system and applies.As connecting electrical network and visitor
The key link at family, the electric energy metrical characteristic of intelligent electric energy meter, directly affect the economic profit of electric energy both sides of supply and demand
Benefit.
Along with the fast development of intelligent grid, the metering performance of electric energy meter is proposed new requirement.One be by
Introducing electrical network in new forms of energy such as wind energy, solar energy, tide energies, the novel power supply in electrical network presents relatively Larger Dynamic
Characteristic.Two is that the astable load in power system gets more and more, and makes the power load in electrical network also present dynamic
Step response.Due to being continuously increased of dynamic load, its caused electric energy metrical occurs that the problem of deviation becomes
More and more prominent with important.
But, for a long time, the test to electric energy meter meter characteristic both at home and abroad is all at steady state test signal bar
Carrying out under part, test signal is the most comprehensive with the reflection of Dynamic Signal composition to the stable state included in electrical network,
Therefore, the matching of electric energy meter test signal needs to be more based on electrical network actual operating mode, just can make electric energy
The analysis of table dynamic error characteristic is more accurately rationally.
Summary of the invention
It is an object of the invention to, the problem existed for existing electric energy meter test signal, the present invention proposes one
The electric energy meter dynamic measuring signal approximating method analyzed based on HHT, it is possible to make test signal packet containing actual electric network
Stable state and Dynamic Signal composition, more precisely reflect the practical operation situation of electrical network, dynamic to electric energy meter
The analysis of error characteristics is more accurately rationally.
Realize technical scheme as follows:
A kind of electric energy meter dynamic measuring signal approximating method analyzed based on HHT, comprises the following steps:
(1) actual measurement network wave signal is carried out EMD decomposition, respectively obtain and characterize dynamic electric voltage fluctuation
Modulating wave and stable state harmonic wave, m-Acetyl chlorophosphonazo signal, modulation wave signal frequency is fundamental frequency, stable state harmonic signal
Frequency is first-harmonic integral multiple, and m-Acetyl chlorophosphonazo signal frequency is that first-harmonic is non-integral multiple;
(2) for characterizing the modulation wave signal that dynamic electric voltage fluctuates, it is carried out respectively Hilbert conversion with anti-
Conversion, obtains new analytic signal, solves its instantaneous amplitude, then instantaneous amplitude signal is carried out EMD decomposition,
Obtain each amplitude-modulated wave signal, solved amplitude and the frequency parameter letter of dynamic electric voltage fluctuation by Hilbert conversion
Breath;
(3) for stable state harmonic wave, m-Acetyl chlorophosphonazo signal, directly carry out Hilbert conversion, obtain stable state harmonic wave,
The amplitude of m-Acetyl chlorophosphonazo and frequency parameters information;
(4) according to gained amplitude-modulated wave and harmonic wave, m-Acetyl chlorophosphonazo shape information, method of least square is utilized to be fitted,
Obtain the digital signal expression formula eventually for electric energy meter test.
EMD decomposition of the present invention i.e. empirical mode decomposition process;To the complexity containing multi-signal composition
Waveform, carries out EMD decomposition, obtains the IMF letter of a series of intrinsic mode function, i.e. multi-signal composition
Number, meets its maximum and minimizing envelope symmetrical about time shaft, and zero crossing number with greatly,
Minimum number at most differs the condition of 1 such that it is able to carries out ensuing Hilbert conversion and calculates its wink
Time amplitude and frequency.
Hilbert of the present invention converts, and arbitrary continuous time signal is carried out Hilbert conversion, and signal is each
The amplitude of frequency component keeps constant, and 90 ° of displacements occurs in phase place, and after conversion, signal is with original signal composition altogether
Yoke plural number is right, it is thus achieved that new analytic signal such that it is able to carry out the extraction of instantaneous amplitude and frequency information.
Method of least square of the present invention, for one group of given data, by retrain all data points with
The error sum of squares of match point is minimum, so that it is determined that the parameter value that fitting function model is concrete, obtains matching bent
Line.
The invention has the beneficial effects as follows, owing to the most domestic and international test to electric energy meter meter characteristic is all in stable state
Carry out under test signal conditioning, test the signal reflection to the stable state included in electrical network Yu Dynamic Signal composition
The most comprehensive, therefore, the matching of electric energy meter test signal needs to be more based on electrical network actual operating mode.
And the present invention is by extracting its stable state and Dynamic Signal composition from electrical network measured waveform, including voltage pulsation
With harmonic wave, m-Acetyl chlorophosphonazo information, its design parameter of matching obtains digital signal and tests for electric energy meter, it is possible to
Make test signal more precisely reflect the practical operation situation of electrical network, electric energy meter dynamic error characteristic is divided
Analysis is more accurately rationally.
Accompanying drawing explanation
Fig. 1 is the theory diagram of the inventive method;
Fig. 2 is the EMD decomposition process figure of the present invention;
Fig. 3 is the modulating wave composition that the decomposition of the present invention obtains;
Fig. 4 be the decomposition of the present invention obtain harmonic wave, m-Acetyl chlorophosphonazo composition;
Fig. 5 is multiple amplitude-modulated wave mixed waveform signals of the present invention;
Fig. 6 is the amplitude-modulated wave instantaneous amplitude waveform of the present invention;
Fig. 7 is the instantaneous frequency waveform of the present invention;
Fig. 8 is the harmonic wave of the present invention, m-Acetyl chlorophosphonazo instantaneous amplitude waveform;
Fig. 9 is the harmonic wave of the present invention, m-Acetyl chlorophosphonazo instantaneous frequency waveform.
Detailed description of the invention
The detailed description of the invention of the present invention is as depicted in figs. 1 and 2.Fig. 1 is that the present invention implements schematic diagram, Fig. 2
EMD decomposition process figure for the present invention.
The present embodiment a kind of based on HHT analyze electric energy meter dynamic measuring signal approximating method be embodied as
Under:
(1) first electrical network measured waveform signal is carried out EMD decomposition, obtain the table comprised in waveshape signal
Levy modulating wave and stable state harmonic wave, the IMF signal of m-Acetyl chlorophosphonazo of dynamic electric voltage fluctuation.
Electrical network actual waveform includes multi-signal composition, including the first-harmonic letter modulated through multiple low frequency amplitude-modulated waves
Number and harmonic wave, m-Acetyl chlorophosphonazo signal, waveshape signal form is as follows:
Wherein, miFor the ratio of amplitude-modulated wave amplitude with first-harmonic rated voltage amplitude, fiFor amplitude-modulated wave frequency, f0For base
Ripple power frequency, mjFor harmonic wave, the ratio of m-Acetyl chlorophosphonazo amplitude and first-harmonic rated voltage amplitude, fjFor harmonic wave, m-Acetyl chlorophosphonazo
Frequency.
The IMF component processes that EMD decomposes extraction waveshape signal is specific as follows:
First mixed signal u (t) maximum u is asked for1(t) and minimum u2The average of (t):
Taking its difference with u (t) is:
H=u (t)-n
Substituting u (t) with h and repeat said process, until h meets the feature of IMF function, i.e. maximum is with minimum
The envelope of value is symmetrical about time shaft, and zero crossing number at most differs 1 with very big, minimum number
Condition, now h i.e. can be considered first IMF signal c1。
Take original signal u (t) and c1Difference be:
R=u (t)-c1
Substitute u (t) by difference r and proceed above operation, by that analogy, obtain multiple IMF signal c2、c3Deng
Deng, iteration to r is that monotone decreasing trend can stop, and now has:
The final multiple IMF component of signals decomposing acquisition mixed signal u (t), i.e. frequency is the modulation of first-harmonic power frequency
Ripple signalWith multiple harmonic waves, m-Acetyl chlorophosphonazo signal
Fig. 3 show and decomposes the modulating wave composition obtained;Fig. 4 show and decomposes harmonic wave, the m-Acetyl chlorophosphonazo one-tenth obtained
Point.
(2) for the modulation wave signal characterizing dynamic electric voltage fluctuationTo it
Carrying out Hilbert conversion, after conversion, signal and original signal form a conjugate complex number pair, obtain new analytic signal.
Hilbert for continuous time signal X (t) converts specific as follows:
Take X (t) and Y (t) to combine, available new conjugated complex signal:
Z (t)=X (t)+jY (t)=a (t) eiθ(t)
Wherein, a (t), θ (t) respectively its instantaneous amplitude and phase information:
Then instantaneous frequency is as follows:
Therefore, for modulation wave signalAfter carrying out Hilbert conversion, newly
The instantaneous amplitude of analytic signal be DC component and multiple amplitude-modulated wave sums:
Take instantaneous amplitude a (t), after removing DC component, i.e. can get the mixed signal of multiple amplitude-modulated waveIt is carried out EMD decomposition, process and step 1) identical, each amplitude modulation can be extracted
Ripple mi sin(2πfiT) IMF signal waveform.After it is carried out Hilbert conversion respectively, according to above-mentioned formula,
Obtain instantaneous amplitude and the instantaneous frequency waveform of each amplitude-modulated wave.
Fig. 5 is multiple amplitude-modulated wave mixed waveform signals;Fig. 6 is amplitude-modulated wave instantaneous amplitude waveform;Fig. 7 is amplitude modulation
Ripple instantaneous frequency waveform.
(3) for stable state harmonic wave, m-Acetyl chlorophosphonazo signalOwing to being decomposed by EMD
Arrive the IMF signal m of each harmonic wave, m-Acetyl chlorophosphonazo compositionjsin(2πfjT), Hilbert therefore can directly be carried out
Conversion, then by the instantaneous amplitude of step (2) and instantaneous frequency formula, it is thus achieved that each harmonic wave, m-Acetyl chlorophosphonazo
Instantaneous amplitude and instantaneous frequency waveform.
Fig. 8 is the instantaneous amplitude waveform of harmonic wave, m-Acetyl chlorophosphonazo;Fig. 9 is the instantaneous frequency waveform of harmonic wave, m-Acetyl chlorophosphonazo.
(4) according to above step gained amplitude-modulated wave and harmonic wave, the instantaneous amplitude of m-Acetyl chlorophosphonazo and the ripple of instantaneous frequency
Shape information, utilizes method of least square to be fitted, and fit procedure is specific as follows:
First determine the function model of matched curve, due to the waveform of required matching be each amplitude-modulated wave with harmonic wave,
The instantaneous amplitude of m-Acetyl chlorophosphonazo and instantaneous frequency, therefore function model i.e. linear function m and f.
Then it is determined by normal equation and solves parameter.Assume the instantaneous amplitude m of matching a certain amplitude-modulated wave msin (2 π ft)
Curve, has obtained instantaneous amplitude curve data (ti,mi) (i=1,2 ..., n), n is the number of curve data point, then matching
Target is:
The condition i.e. derivative that above formula meets is 0, it may be assumed that
Can obtain:
Instantaneous frequency f curve fitting process is ibid.
Final obtain each amplitude-modulated wave characterizing dynamic electric voltage fluctuation and stable state harmonic wave, m-Acetyl chlorophosphonazo instantaneous amplitude with
Instantaneous frequency m and f parameter value, obtain being analyzed by electrical network measured waveform, can be used for electric energy meter and dynamically survey
The digital signal of examination:
The present invention is by extracting its stable state and Dynamic Signal composition from electrical network measured waveform, including voltage pulsation
With harmonic wave, m-Acetyl chlorophosphonazo information, its design parameter of matching obtains digital signal and tests for electric energy meter, it is possible to
Make test signal more precisely reflect the practical operation situation of electrical network, electric energy meter dynamic error characteristic is divided
Analysis is more accurately rationally.
Claims (4)
1. the electric energy meter dynamic measuring signal approximating method analyzed based on HHT, it is characterised in that said method comprising the steps of:
(1) actual measurement network wave signal is carried out EMD decomposition, respectively obtain modulating wave and stable state harmonic wave, the m-Acetyl chlorophosphonazo signal characterizing dynamic electric voltage fluctuation, modulation wave signal frequency is fundamental frequency, and stable state harmonic frequency signal is first-harmonic integral multiple, and m-Acetyl chlorophosphonazo signal frequency is that first-harmonic is non-integral multiple;
(2) for the modulation wave signal characterizing dynamic electric voltage fluctuation, it is carried out respectively Hilbert conversion and inverse transformation, obtain new analytic signal, solve its instantaneous amplitude, again instantaneous amplitude signal is carried out EMD decomposition, obtain each amplitude-modulated wave signal, solved amplitude and the frequency parameters information of dynamic electric voltage fluctuation by Hilbert conversion;
(3) for stable state harmonic wave, m-Acetyl chlorophosphonazo signal, directly carry out Hilbert conversion, obtain stable state harmonic wave, the amplitude of m-Acetyl chlorophosphonazo and frequency parameters information;
(4) according to gained amplitude-modulated wave and harmonic wave, m-Acetyl chlorophosphonazo shape information, utilize method of least square to be fitted, obtain the digital signal expression formula eventually for electric energy meter test.
A kind of electric energy meter dynamic measuring signal approximating method analyzed based on HHT, it is characterised in that described EMD decomposition i.e. empirical mode decomposition process;To the complicated wave form containing multi-signal composition, carry out EMD decomposition, obtain a series of intrinsic mode function, the i.e. IMF function of multi-signal composition, meet its maximum symmetrical about time shaft with minimizing envelope, and zero crossing number at most differs the condition of 1 with very big, minimum number such that it is able to carry out ensuing Hilbert conversion and calculate its instantaneous amplitude and frequency.
A kind of electric energy meter dynamic measuring signal approximating method analyzed based on HHT, it is characterized in that, described Hilbert converts, arbitrary continuous time signal is carried out Hilbert conversion, the amplitude of each frequency component of signal keeps constant, and 90 ° of displacements occurs in phase place, and after conversion, signal and original signal form a conjugate complex number pair, obtain new analytic signal such that it is able to carry out the extraction of instantaneous amplitude and frequency information.
A kind of electric energy meter dynamic measuring signal approximating method analyzed based on HHT, it is characterized in that, described method of least square, for one group of given data, minimum with the error sum of squares of match point by retraining all data points, so that it is determined that the parameter value that fitting function model is concrete, obtain matched curve.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201610394141.5A CN106021805A (en) | 2016-06-06 | 2016-06-06 | Electric energy meter dynamic testing signal fitting method based on HHT analysis |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201610394141.5A CN106021805A (en) | 2016-06-06 | 2016-06-06 | Electric energy meter dynamic testing signal fitting method based on HHT analysis |
Publications (1)
Publication Number | Publication Date |
---|---|
CN106021805A true CN106021805A (en) | 2016-10-12 |
Family
ID=57090762
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201610394141.5A Pending CN106021805A (en) | 2016-06-06 | 2016-06-06 | Electric energy meter dynamic testing signal fitting method based on HHT analysis |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN106021805A (en) |
Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN106779470A (en) * | 2017-01-04 | 2017-05-31 | 南京工程学院 | A kind of voltage flicker detection algorithm based on improvement HHT |
CN109358230A (en) * | 2018-10-29 | 2019-02-19 | 国网甘肃省电力公司电力科学研究院 | A kind of micro-capacitance sensor is fallen into a trap and the Intelligent electric-energy metering method of m-Acetyl chlorophosphonazo |
CN109490622A (en) * | 2018-11-10 | 2019-03-19 | 王浩 | A kind of electricity data calibration technology based on tri-state information |
Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101566649A (en) * | 2009-05-27 | 2009-10-28 | 重庆大学 | Harmonic detection method in a power system |
CN104459597A (en) * | 2014-11-14 | 2015-03-25 | 国家电网公司 | Electric energy measuring technical analysis platform under non-linear loads |
-
2016
- 2016-06-06 CN CN201610394141.5A patent/CN106021805A/en active Pending
Patent Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101566649A (en) * | 2009-05-27 | 2009-10-28 | 重庆大学 | Harmonic detection method in a power system |
CN104459597A (en) * | 2014-11-14 | 2015-03-25 | 国家电网公司 | Electric energy measuring technical analysis platform under non-linear loads |
Non-Patent Citations (2)
Title |
---|
江辉 等: "基于希尔伯特-黄变换的电压闪变测量方法", 《电网技术》 * |
谢家安: "提取电压闪变参数的一种新方法", 《电网与清洁能源》 * |
Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN106779470A (en) * | 2017-01-04 | 2017-05-31 | 南京工程学院 | A kind of voltage flicker detection algorithm based on improvement HHT |
CN109358230A (en) * | 2018-10-29 | 2019-02-19 | 国网甘肃省电力公司电力科学研究院 | A kind of micro-capacitance sensor is fallen into a trap and the Intelligent electric-energy metering method of m-Acetyl chlorophosphonazo |
CN109490622A (en) * | 2018-11-10 | 2019-03-19 | 王浩 | A kind of electricity data calibration technology based on tri-state information |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN102841251B (en) | Electric car charging station harmonic wave detection method in microgrid | |
CN106908665B (en) | A kind of one-phase AC-system dq decomposition impedance measurement method | |
CN105004939A (en) | Composite electric energy quality disturbance signal quantitative analysis method | |
CN102288807A (en) | Method for measuring electric network voltage flicker | |
CN105445541A (en) | Method for adaptively calculating power under arbitrary frequencies | |
CN104182914A (en) | Wind power output time series modeling method based on fluctuation characteristics | |
CN103454537A (en) | Wind power generation low-voltage ride-through detection equipment and method based on wavelet analysis | |
CN104714075B (en) | A kind of electric network voltage flicker envelope parameters extracting method | |
CN111308260B (en) | Electric energy quality monitoring and electric appliance fault analysis system based on wavelet neural network and working method thereof | |
CN102520245A (en) | Micro-grid harmonic and inter-harmonic analysis method based on cubic spline interpolation waveform reconstruction | |
CN104316894A (en) | Simulation and calibration method for practical running environment of electric energy meter | |
CN106021805A (en) | Electric energy meter dynamic testing signal fitting method based on HHT analysis | |
CN104539293A (en) | Electricity travelling wave signal reconstructing method based on compressed sensing | |
CN105675956A (en) | Voltage flicker detection method based on windowing interpolation short-time Fourier transform | |
CN105866571A (en) | Transient electric energy quality signal analysis method based on high-frequency harmonic compensation iteration EMD | |
CN109800520A (en) | A kind of electric automobile charging station Harmonic Modeling method neural network based | |
CN112986775A (en) | Active calibration method for partial discharge pulse phase | |
CN103487687B (en) | Nonstandard variable ratio voltage transformer calibrating method | |
CN113937764A (en) | Low-voltage distribution network high-frequency measurement data processing and topology identification method | |
CN104617578A (en) | Method for acquiring available power transmission capability of power system with wind power plant | |
CN208443997U (en) | A kind of mutual inductor dynamic error test macro | |
CN101806835B (en) | Interharmonics measuring meter based on envelope decomposition | |
CN107167658B (en) | A kind of jamproof electric system fundamental frequency of high-precision and Method for Phase Difference Measurement | |
CN106383280B (en) | The voltage transformer Model test Method of line model is maked somebody a mere figurehead based on two nodes | |
CN202886585U (en) | On-line test device for voltage/current transformer |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
C06 | Publication | ||
PB01 | Publication | ||
C10 | Entry into substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
RJ01 | Rejection of invention patent application after publication | ||
RJ01 | Rejection of invention patent application after publication |
Application publication date: 20161012 |