CN109687474A - Referential current detection algorithm and system based on Kalman filtering - Google Patents

Referential current detection algorithm and system based on Kalman filtering Download PDF

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Publication number
CN109687474A
CN109687474A CN201811392500.9A CN201811392500A CN109687474A CN 109687474 A CN109687474 A CN 109687474A CN 201811392500 A CN201811392500 A CN 201811392500A CN 109687474 A CN109687474 A CN 109687474A
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current
load
kalman filtering
referential
phase
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程新功
李发磊
张永峰
宗西举
张静亮
殷文月
于明珠
邵振振
赵义上
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Shandong East Ding Electric Co Ltd
University of Jinan
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Shandong East Ding Electric Co Ltd
University of Jinan
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/18—Arrangements for adjusting, eliminating or compensating reactive power in networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/16—Matrix or vector computation, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/01—Arrangements for reducing harmonics or ripples
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/26—Arrangements for eliminating or reducing asymmetry in polyphase networks
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • 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
    • Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
    • Y02E40/30—Reactive power compensation
    • 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
    • Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
    • Y02E40/40—Arrangements for reducing harmonics
    • 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
    • Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
    • Y02E40/50—Arrangements for eliminating or reducing asymmetry in polyphase networks

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Mathematical Physics (AREA)
  • Power Engineering (AREA)
  • General Physics & Mathematics (AREA)
  • Pure & Applied Mathematics (AREA)
  • Mathematical Optimization (AREA)
  • Mathematical Analysis (AREA)
  • Data Mining & Analysis (AREA)
  • Theoretical Computer Science (AREA)
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  • Databases & Information Systems (AREA)
  • Software Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • Supply And Distribution Of Alternating Current (AREA)

Abstract

The invention discloses a kind of referential current detection algorithm and system based on Kalman filtering, comprising: the load current instantaneous value in measurement threephase load；It is converted using clark, by the load current instantaneous value conversion in threephase load into alpha-beta two-phase orthogonal coordinate system: obtaining instantaneous active electric current i by coordinate transformpWith reactive current iq；Based on ip_iqEstablish discrete system state equation and measurement equation；Using Kalman filter to ipAnd iqIt is filtered, obtains DC component；Fundamental positive sequence electric current is obtained by coordinate inverse transformation, fundamental positive sequence electric current and load current are subtracted each other to obtain total compensation electric current.The method of the present invention can quickly track the variation of load current, compensation current-order reference signal be detected, compared with the algorithm for using Butterworth LPF, its detection speed is fast, real-time is good, and three-phase amplitude fluctuations are small, so that compensation speed is faster, effect is more reliable.

Description

Referential current detection algorithm and system based on Kalman filtering
Technical field
The present invention relates to the referential current detection algorithms and system of a kind of Kalman filtering.
Background technique
With the development of power electronics technology and application, power electronic equipment are widely used in three-phase four-wire system power train The harm such as system, gets worse harmonic pollution, grid loss is caused to increase, and electrical equipment service life is reduced.Threephase load connects Enter easily asymmetry, make three-phase imbalance, power equipment can be burnt by generating neutral line current if neutral line current is excessive.It is most of Electric energy regulator has the function of that compensation harmonic, compensating three-phase unbalance etc. improve power quality.And compensate current-order The real-time of signal detection is to influence one of electric energy regulator compensation effect principal element.
Traditional referential current detection algorithm has Fast Fourier Transform (FFT) (FFT) algorithm, discrete fourier in frequency domain to become (DFT) algorithm etc. is changed, but due to algorithm comparison complexity, calculation amount is larger, and it is bigger to generate delay；Mainly there is base in time domain In the i of instantaneous reactive power theoryp-iqMethod and id-iqMethod commonly uses Butterworth filter (Butterworth in algorithm Filter, BF) to ip(or id) and iqIt is filtered to obtain DC component, then carries out inverse transformation, but the delay that BF itself is intrinsic Characteristic, so that detection real-time is poor.
The prior art proposes that comprehensive utilization mean filter and BF can obtain good detection accuracy and good dynamic Response, but two filters are utilized simultaneously, increase the complexity of algorithm；The prior art utilizes a kind of New variable step-size LMS To realize ip_iqThe function of low-pass filter in theory controls step using error current and the auto-correlation function of last error It is long to update, the interference of noise is eliminated to a certain extent, but track waveform to generate certain steady output rate error, and work as When load sudden change, tracking accuracy can be decreased.
Summary of the invention
In order to solve the problem above-mentioned, the referential current detection algorithm that the invention proposes a kind of based on Kalman filtering and System can quickly track the variation of load current, detect compensation current-order reference signal, and compensation speed faster, is imitated Fruit is more reliable.
To achieve the goals above, the present invention adopts the following technical scheme:
In one or more embodiments, a kind of referential current detection algorithm based on Kalman filtering is disclosed, is wrapped It includes:
Measure the load current instantaneous value i in threephase loada, ib, ic；
It is converted using clark, by the load current instantaneous value conversion in threephase load into alpha-beta two-phase orthogonal coordinate system:
Instantaneous active electric current i is obtained by coordinate transformpWith reactive current iq；
Based on ip_iqEstablish discrete system state equation and measurement equation；
Using Kalman filter to watt current ipWith reactive current iqIt is filtered, obtains DC component；
Fundamental positive sequence electric current is obtained by coordinate inverse transformation, fundamental positive sequence electric current is subtracted each other with load current and is always compensated Electric current.
Further, it is converted using clark, the load current instantaneous value conversion in threephase load is orthogonal to alpha-beta two-phase In coordinate system, specifically:
Wherein,
Further, it is converted using clark, obtains instantaneous active electric current i by coordinate transformpWith reactive current iq, specifically Are as follows:
Wherein,ω is fundamental wave frequency.
Further, it is based on ip_iqDiscrete system state equation and measurement equation are established, specifically:
For watt current ip:
Wherein,For state-transition matrix, Hp1×16For calculation matrix, Xp16×1(k+1) become for watt current state Flow control k+1 value, Xp16×1(k) be k-th of value of watt current state variable, w (k) be process noise, v (k) be measurement noise, Zp (k) is watt current measured value；
For reactive current iq:
For state-transition matrix, Hq1×16For calculation matrix, Xq16×1It (k+1) is reactive current state variable Kth+1 value, Xq16×1(k) be k-th of value of reactive current state variable, w (k) be process noise, v (k) is measurement noise, zq It (k) is reactive current measured value.
Further, using Kalman filter to watt current ipWith reactive current iqIt is filtered, obtains direct current point Amount, specifically:
According to established discrete system state equation and measurement equation, state variable initial value is set, substitutes into Kalman's filter In wave algorithmic formula, recursion is circuited sequentially, obtains the state variable at each moment, wherein Xq111And Xp111Respectively fundamental active DC component and fundamental wave reactive power DC component；By Xq111And Xp111Three-phase fundamental current is just obtained after carrying out inverse transformation.
A kind of referential current detection system based on Kalman filtering disclosed in one or more embodiments, including Server, the server include memory, processor and storage on a memory and the computer that can run on a processor Program, the processor realize the above-mentioned referential current detection method based on Kalman filtering when executing described program.
A kind of computer readable storage medium disclosed in one or more embodiments, is stored thereon with computer journey Sequence, the program execute the above-mentioned referential current detection method based on Kalman filtering when being executed by processor.
Compared with prior art, the beneficial effects of the present invention are:
The method of the present invention can quickly track the variation of load current, detect compensation current-order reference signal, with It is compared using the algorithm of Butterworth LPF, detection speed is fast, real-time is good, and three-phase amplitude fluctuations are small, to make Obtain compensation speed faster, effect is more reliable.
Detailed description of the invention
The accompanying drawings constituting a part of this application is used to provide further understanding of the present application, and the application's shows Meaning property embodiment and its explanation are not constituted an undue limitation on the present application for explaining the application.
Fig. 1 is the referential current detection method flow diagram based on Kalman filtering；
Fig. 2 is threephase load current waveform figure；
Fig. 3 is the compensation current command signal waveform diagram based on KF；
Fig. 4 is the three-phase fundamental current signal waveforms based on KF；
Fig. 5 is the three-phase fundamental current steady state error waveform diagram based on KF；
Fig. 6 is the three-phase fundamental current steady state error waveform diagram based on KF after shock load；
Fig. 7 is the compensation current command signal waveform diagram based on Butterworth LPF；
Fig. 8 is the three-phase fundamental current waveform diagram based on Butterworth LPF；
Fig. 9 is the three-phase fundamental current steady state error waveform diagram based on Butterworth LPF；
Figure 10 is the three-phase fundamental current steady state error waveform diagram based on Butterworth LPF after shock load.
Specific embodiment
It is noted that following detailed description is all illustrative, it is intended to provide further instruction to the application.Unless another It indicates, all technical and scientific terms that the present invention uses have logical with the application person of an ordinary skill in the technical field The identical meanings understood.
It should be noted that term used herein above is merely to describe specific embodiment, and be not intended to restricted root According to the illustrative embodiments of the application.As used herein, unless the context clearly indicates otherwise, otherwise singular Also it is intended to include plural form, additionally, it should be understood that, when in the present specification using term "comprising" and/or " packet Include " when, indicate existing characteristics, step, operation, device, component and/or their combination.
Embodiment one
A kind of referential current detection algorithm based on Kalman filtering is disclosed in one or more embodiments, is such as schemed Shown in 1, comprising: first to ia, ib, icCarry out clark transformation and C2s/2rTransformation obtains ip, iq.It is based on i againp_iqEstablish discrete system After system state equation and measurement equation, using Kalman filter to ip, iqIt is filtered, obtains DC component, pass through inverse transformation After obtain fundamental positive sequence electric current, then subtract each other to obtain total compensation electric current with load current.
Load current instantaneous value i in threephase loada, ib, icIt is obtained by current transformer measurement.Asymmetrical three-phase is negative Load current is expressed as follows in loading system:
Wherein subscript 1,2,0 respectively indicate positive sequence, negative phase-sequence, zero-sequence component；I0=I0nsin(hwt+θ0n) it is zero-sequence current Component, n are the highest subharmonic of required consideration, θhFor the phase angle of h subharmonic current；I1hFor the width of h subharmonic forward-order current Value, I2hPosition h subharmonic negative sequence component amplitude；The π of ω=2 f is fundamental wave frequency.
It is converted using clark, by threephase load current transformation into alpha-beta two-phase orthogonal coordinate system:
Wherein:Then substitute into:
By upper formula it is found that the i after coordinate transformα, iβIn be free of zero-sequence component.
And then it converts and obtains instantaneous active and reactive current:
Wherein:
Formula is substituted into obtain:
At this point, ip, iqInclude DC component and AC compounent.
Based on ip_iqEstablish state equation and measurement equation；To formula (4):
With ipFor, for ipIn n-th harmonic have:
Decomposition obtains:
Then any subharmonic all contains there are four component.
To select state variable:
So discrete state equations of nth harmonic are as follows:
And state-transition matrix φ=I4For 4 rank unit matrixs；The first bit digital 1,2 represents positive sequence, bears in subscript in formula Sequence, intermediate n represent overtone order, and what third bit digital 1,2 represented is positive sequence, which component in negative phase-sequence.
Equation must be measured according to formula (6) are as follows:
Wherein Hp (k)=[cos (n-1) δ-sin (n-1) δ-cos (n+1) δ sin (n+1) δ]
Wherein: δ=ω kT, T are the sampling periods, and k is sampled point.
If considering fundamental wave and multiple harmonic simultaneously, as long as accordingly the state variable of fundamental wave and each harmonic group in order It closes and constitutes a state column vector, column write state equation and measurement equation.
Similarly to iqEstablish the discrete state equations and measurement equation of nth harmonic:
Wherein:
Hq (k)=[cos (n-1) δ sin (n-1) δ cos (n+1) δ sin (n+1) δ].
Consider that nonlinear load electric current main component not only contains fundamental wave and also contains harmonic wave, mainly consider 3,5,7 subharmonic, Then there are 16 state variables.It establishes respectively and is based on ip_iqDiscrete system equation.
For ipHave:
Wherein,For state-transition matrix, Hp1×16For calculation matrix, Xp16×1(k+1) become for watt current state Flow control k+1 value, Xp16×1(k) be k-th of value of watt current state variable, w (k) be process noise, v (k) be measurement noise, Zp (k) is watt current measured value；
Wherein, state-transition matrix:For 16 rank unit matrixs；
Calculation matrix:
Hp1 × 16=[1 0-cos2 δ sin2 δ cos2 δ-sin2 δ-cos4 δ sin4 δ
cos4δ -sin4δ -cos6δ sin6δ cos6δ -sin 6δ -cos8δ sin8δ]
Similarly for iqHave:
Wherein,For state-transition matrix, Hq1×16For calculation matrix, Xq16×1(k+1) become for reactive current state Kth+1 value, Xq of amount16×1(k) be k-th of value of reactive current state variable, w (k) be process noise, v (k) is that measurement is made an uproar Sound, zq (k) are reactive current measured value.
Wherein state-transition matrix:As 16 rank unit matrixs；
Calculation matrix:
Hq1 × 16=[1 0 cos2 δ sin2 δ cos2 δ sin2 δ cos4 δ sin4 δ
cos4δ sin4δ cos6δ sin6δ cos6δ sin6δ cos8δ sin8δ]
After establishing system discrete equation, state variable initial value, i are setpAnd iqTake identical initial value: X (0 | 0)=[0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]T, covariance initial value P (0 | 0)=10I16×16, systematic procedure noise and measurement noise Selection the speed and precision of filtering can be had an impact, comprehensively consider and take R=0.01, Q=0.012I16×16.Then card is substituted into In Kalman Filtering algorithmic formula, recursion is circuited sequentially, obtains the state variable at each moment, wherein Xq111And Xp111It is straight for fundamental wave Flow component.So, it is only necessary to Xq111And Xp111Just obtain three-phase fundamental current after carrying out inverse transformation, then with threephase load electric current Subtract each other, finally obtain need compensate generally refer to enable electric current.
According to above-mentioned listed initial value and the state-transition matrix and observing matrix of foundation, Kalman filtering is proposed by verifying Device detection algorithm validity emulates threephase load unbalanced harmonic electric current by MATLAB.And with use The command signal and fundamental current that the detection algorithm of Butterworth low-pass filter obtains are compared analysis.Emulation power supply System is three-phase four-wire system, and input voltage 380v, threephase load is that three-phase diode inverter bridge band hinders inductive load, and B phase is simultaneously Join a single-phase diode inverter bridge band resistance inductive load, fundamental frequency f=50hz, sample frequency 100khz, simulation time For 0.4s.In 0.2s, it is in parallel one in B and hinders inductive load.
Definition calculates the method that three-phase current instantaneous value reaches stable point: taking each phase cycle length to be equal to each other excessive It period and stable period is made the difference with the current instantaneous value of corresponding points, is denoted as steady state error, when three-phase current instantaneous value steady state error | e | when < 0.01A, then it is assumed that the moment is at the time of reaching stable.
Three-phase imbalance load harmonic current is as shown in Fig. 2, as can be seen from FIG. 2, emulation starts load current amplitude fluctuations It is small, but ripple content is big.It is calculated according to definition, begins to pass through 3600 points (1.8 periods) back loading electric current from emulation Ripple reduction reaches stable.In 20k point (0.2s) after shock load, it is calculated according to definition and is just reached by 850 points Stablize.Reach stable state by 0.43 cyclic loading electric current i.e. after shock load.
The three-phase compensating instruction signal obtained based on Kalman filter is as shown in figure 3, three-phase fundamental current such as Fig. 4 institute Show.
Detection algorithm it can be seen from Fig. 3,4 based on KF can detecte to obtain three-phase compensating instruction signal and stabilization and Balance three-phase fundamental current.Since emulation, according to the method that definition calculates stable point, obtain as shown in figure 5, at 1100 points (0.55 period) three-phase fundamental current steady state error afterwards | e | < 0.01A, then three-phase fundamental current reaches stable.When three-phase base After wave electric current is stablized, calculating three-phase fundamental current peak value, accidentally absolute value of the difference is both less than 0.01A two-by-two, therefore works as three-phase base current Also reach three-phase equilibrium when reaching stable.
After shock load at 0.2s, the detection algorithm based on Kalman filter can also obtain three-phase compensating instruction letter Number and stablize and balance three-phase fundamental current.According to the method that definition calculates stable point, obtain as shown in fig. 6, negative from impact After load after 1200 points (0.6 period) steady state error | e | < 0.01A, then three-phase fundamental current reaches stable.Work as three-phase After fundamental current is stablized, calculating three-phase fundamental current peak value, absolute difference is both less than 0.01A two-by-two, therefore works as three-phase base current Also reach three-phase equilibrium when reaching stable.
For the real-time for comparing mentioned algorithm, it is compared with the detection algorithm of Butterworth low-pass filter.Fig. 7, Fig. 8 is respectively the three-phase compensation current command signal and three-phase fundamental current that the algorithm obtains.
Since emulation, according to the method that definition calculates stable point, as shown in figure 9, three after 2 periods (4000 points) Phase fundamental current steady state error | e | < 1A, until the 4.5th period (9000 points) steady state error afterwards | and e | < 0.01A.Calculate 4.5 Three-phase fundamental wave peak point current Difference after a period, obtaining worst error absolute value is 0.11A.
After shock load at 0.2s, passed through after shock load as shown in Figure 10 according to the method that definition calculates stable point Cross 2 periods () steady state error afterwards at 4000 points | e | < 0.5A, until the 4.5th period (9000 points) steady state error afterwards | e | < 0.01A.Three-phase fundamental wave peak point current Difference after 4.5 periods is calculated, obtaining worst error absolute value is 0.36A.
According to the above analysis, the fundamental current of three-phase equilibrium can be detected using the detection algorithm of two kinds of filters and is needed The three-phase imbalance harmonic current to be compensated.When the command signal that detection algorithm based on KF obtains compensates, three-phase fundamental wave Electric current reaches stable and equilibrium state by 0.55 period；And the detection algorithm based on Butterworth LPF, need 4.5 Just reach stable state after a period, and three-phase amplitude has fluctuation.
After system shock load, it can detect that the three-phase for needing to compensate is uneven using the detection algorithm of two kinds of filters Weigh harmonic current and three-phase equilibrium fundamental current.When the compensating instruction signal obtained using the detection algorithm of KF is compensated, three Phase fundamental current reaches stable and equilibrium state by 0.6 period.And when being based on Butterworth LPF, three-phase fundamental wave electricity Stream needs 4.5 periods to can be only achieved stable state, and three-phase amplitude has fluctuation.
Therefore the compensation Current Detection Algorithm based on KF proposed, the variation of load current can be quickly tracked, is detected Current-order reference signal is compensated out, compared with the algorithm for using Butterworth LPF, detection speed is fast, real-time is good, And three-phase amplitude fluctuations are small, so that compensation speed is faster, effect is more reliable.
Embodiment two
A kind of referential current detection system based on Kalman filtering disclosed in one or more embodiments, including Server, the server include memory, processor and storage on a memory and the computer that can run on a processor Program, the processor realize the referential current detection side based on Kalman filtering described in embodiment one when executing described program Method.
Embodiment three
A kind of computer readable storage medium disclosed in one or more embodiments, is stored thereon with computer journey Sequence executes the referential current detection method based on Kalman filtering described in embodiment one when the program is executed by processor.
Above-mentioned, although the foregoing specific embodiments of the present invention is described with reference to the accompanying drawings, not protects model to the present invention The limitation enclosed, those skilled in the art should understand that, based on the technical solutions of the present invention, those skilled in the art are not Need to make the creative labor the various modifications or changes that can be made still within protection scope of the present invention.

Claims (7)

1. a kind of referential current detection algorithm based on Kalman filtering characterized by comprising
Measure the load current instantaneous value i in threephase loada, ib, ic；
It is converted using clark, by the load current instantaneous value conversion in threephase load into alpha-beta two-phase orthogonal coordinate system:
Instantaneous active electric current i is obtained by coordinate transformpWith reactive current iq；
Based on ip_iqEstablish discrete system state equation and measurement equation；
Using Kalman filter to watt current ipWith reactive current iqIt is filtered, obtains DC component；
Fundamental positive sequence electric current is obtained by coordinate inverse transformation, fundamental positive sequence electric current and load current are subtracted each other to obtain total compensation electricity Stream.
2. a kind of referential current detection algorithm based on Kalman filtering as described in claim 1, which is characterized in that utilize Clark transformation, by the load current instantaneous value conversion in threephase load into alpha-beta two-phase orthogonal coordinate system, specifically:
Wherein,
3. a kind of referential current detection algorithm based on Kalman filtering as described in claim 1, which is characterized in that utilize Clark transformation, obtains instantaneous active electric current i by coordinate transformpWith reactive current iq, specifically:
Wherein,ω is fundamental wave frequency.
4. a kind of referential current detection algorithm based on Kalman filtering as described in claim 1, which is characterized in that be based on ip_ iqDiscrete system state equation and measurement equation are established, specifically:
For watt current ip:
Wherein,For state-transition matrix, Hp1×16For calculation matrix, Xp16×1It (k+1) is watt current state variable kth + 1 value, Xp16×1(k) be k-th of value of watt current state variable, w (k) be process noise, v (k) is measurement noise, zp (k) For watt current measured value；
For reactive current iq:
For state-transition matrix, Hq1×16For calculation matrix, Xq16×1It (k+1) is the kth+1 of reactive current state variable A value, Xq16×1(k) be k-th of value of reactive current state variable, w (k) be process noise, v (k) is measurement noise, zq (k) is Reactive current measured value.
5. a kind of referential current detection algorithm based on Kalman filtering as described in claim 1, which is characterized in that utilize card Thalmann filter is to watt current ipWith reactive current iqIt is filtered, obtains DC component, specifically:
According to established discrete system state equation and measurement equation, state variable initial value is set, Kalman filtering is substituted into and calculates In method formula, recursion is circuited sequentially, obtains the state variable at each moment, wherein Xq111And Xp111Respectively fundamental active direct current Component and fundamental wave reactive power DC component；By Xq111And Xp111Three-phase fundamental current is just obtained after carrying out inverse transformation.
6. a kind of referential current detection system based on Kalman filtering, which is characterized in that including server, the server packet The computer program that includes memory, processor and storage on a memory and can run on a processor, the processor execute Claim 1-5 described in any item referential current detection methods based on Kalman filtering are realized when described program.
7. a kind of computer readable storage medium, is stored thereon with computer program, which is characterized in that the program is held by processor Perform claim requires the described in any item referential current detection methods based on Kalman filtering of 1-5 when row.
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CN110768666A (en) * 2019-10-28 2020-02-07 南京工程学院 Kalman filter-based double-synchronous coordinate system decoupling phase-locked loop system and method
CN113741344A (en) * 2021-08-03 2021-12-03 南京工大数控科技有限公司 Intelligent fault diagnosis system and method for numerical control machine tool
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