CN109726490A - A kind of more sinusoidal signal design methods of low-frequency range for the identification of POWER SYSTEM STATE spatial model - Google Patents
A kind of more sinusoidal signal design methods of low-frequency range for the identification of POWER SYSTEM STATE spatial model Download PDFInfo
- Publication number
- CN109726490A CN109726490A CN201910002124.6A CN201910002124A CN109726490A CN 109726490 A CN109726490 A CN 109726490A CN 201910002124 A CN201910002124 A CN 201910002124A CN 109726490 A CN109726490 A CN 109726490A
- Authority
- CN
- China
- Prior art keywords
- low
- frequency range
- sinusoidal signal
- norm
- column vector
- 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.)
- Granted
Links
Landscapes
- Supply And Distribution Of Alternating Current (AREA)
Abstract
The invention discloses a kind of more sinusoidal signal design methods of low-frequency range for the identification of POWER SYSTEM STATE spatial model, include the following steps: each harmonic component amplitude, each frequencies of harmonic components and the sampling length that determine the more sinusoidal signal x (t) of low-frequency range；Then the crest factor of the more sinusoidal signal x (t) of low-frequency range is defined, and crest factor minimization problem is converted are as follows: is gradually increased lpThe p value of norm solves harmonic phaseThe column vector p of compositionp, make the l of the more sinusoidal signal x (t) of low-frequency rangepNorm minimum；Finally algorithm is used to solve problem: p sets gradually as 4,8,16,32,64,128,256,512 ...；To the p value of each setting, column vector p is solved using gauss-newton method joint Levenberg-Marquart algorithmp, make the l of x (t)pNorm minimum；When p is set as 512, it can meet and approach requirement, so far, the more sinusoidal signal x (t) of the low-frequency range met the requirements, which solve, to be finished.The input signal that the method for the present invention designs, while meeting the limitation of time domain waveform amplitude and requiring to concentrate requirement with frequency domain energy.
Description
Technical field
The present invention relates to the interleaving techniques fields of electric system identification and signal processing, in particular to a kind of to be used for power train
The more sinusoidal signal design methods of low-frequency range of system Stute space model identification.
Technical background
With the development of interconnected network, low-frequency oscillation problem of the electric system in 0.1 to 2.5 hertz of band limits is prominent
Out, it needs to solve by installing low-frequency oscillation of electric power system controller.Low-frequency oscillation of electric power system controller design relies on
POWER SYSTEM STATE spatial model needs to solve Stute space model identification first in practical power systems engineering design to ask
Topic.In order to ensure that electric system energy safe and stable operation in identification process, Practical Project generally use small size disturbing signal to electricity
Force system is motivated, and electric system excitation input and response output signal are then acquired, and carries out phase by System Discrimination algorithm
The inearized model identification answered.At this point, the source as identification work, the small size disturbing signal of use just become decision power train
The key factor of system Stute space model identification success or not.
Currently, the small size disturbing signal that Practical Project uses has white noise signal and limited frequency band by low-pass filter
Pseudo-random signal.Two class signals are larger in 0.1 to 2.5 hertz of frequency range self-energy that low-frequency oscillation is concerned about, but in the care
There are certain energy other than frequency range, when causing to carry out Stute space model identification to electric system, input signal energy is inadequate
It concentrates, the signal-to-noise ratio of system output response signal reduces, to affect the precision of POWER SYSTEM STATE spatial model identification.
Summary of the invention
It is an object of the invention to overcome shortcoming and deficiency in the prior art, provide a kind of empty for POWER SYSTEM STATE
Between the more sinusoidal signal design methods of low-frequency range of Model Distinguish both meet electric system to make the obtained input signal of design
The time domain waveform amplitude of Stute space model identification, which limits, to be required, and is met its frequency domain energy and concentrated requirement.
In order to achieve the above object, the present invention adopts the following technical scheme that:
A kind of more sinusoidal signal design methods of low-frequency range for the identification of POWER SYSTEM STATE spatial model, including following steps
It is rapid:
Initiation parameter:
S1, the total sampling number for determining the more sinusoidal signal x (t) of low-frequency range are N, then each sampled point of x (t) is represented sequentially as
x(t0), x (t1) ..., x (tN-1)；
S2, according to the time-domain expression of the more sinusoidal signal x (t) of low-frequency range are as follows:It determines
Each harmonic component amplitude a of the more sinusoidal signal x (t) of low-frequency rangeuWith each frequencies of harmonic components ωu, wherein u=1,2 ..., Nu, Nu≤
N/2, NuFor the number of sinusoidal harmonics frequency component；
The problem of designing low-frequency range more sinusoidal signal x (t) describes and conversion:
S3, the discrete l for defining the more sinusoidal signal x (t) of low-frequency rangepNorm isDiscrete l∞Norm isWherein xn=x (tn), n=0,1 ..., N-1；P value is positive integer；The then more sinusoidal signal x of low-frequency range
(t) crest factor CrIt may be expressed as:l2(xn) indicate the more sinusoidal signal x (t) of low-frequency range l2Model
Number；
S4, first harmonic phase for enabling the more sinusoidal signal x (t) of low-frequency rangeBy remaining harmonic phaseWith one
NpThe column vector p of × 1 dimension indicates, wherein Np=Nu-1；U=2,3 ..., Nu；Due to the l of x (t)2Norm and harmonic phaseNothing
It closes, then the crest factor C of the more sinusoidal signals of low-frequency rangerMinimization problem conversion are as follows: solve harmonic phaseThe column of composition to
P is measured, the peak value l of x (t) is made∞(x (p, t)) is minimum；
S5, the problem of step S4, is converted are as follows: solve a real value phase angle vector p∞∈RNp, so that in all alternative column
Vector p ∈ RNpThe peak value of middle x (t) is minimum, i.e. l∞(x(p∞,t))≤l∞(x(p,t)),
S6, basisUsing l that can be micro-pNorm carrys out the l of Step wise approximation non-differentiability∞Norm is used in combination
lpThe optimal solution p of normpCome approximate instead of l∞The optimal solution p of norm∞, therefore the problem of step S5, is further converted to: it is gradually increased
lpThe p value of norm, and column vector p is solved to each p valuep, make the l of x (t)pNorm minimum；
Column vector p is solved using algorithmpAnd the more sinusoidal signal x (t) of low-frequency range:
S7, to set gradually p be 4,8,16,32,64,128,256,512；To the p value of each setting, using Gauss ox
The method of pausing joint Levenberg-Marquart algorithm solves column vector pp, make the l of x (t)pNorm minimum, i.e. solution column vector p4So that x
(t) l4Norm minimum, then by p4As p8Initial value, solve column vector p8So that the l of x (t)8Norm minimum, according to this class
It pushes away；
S8, when p is set as 512, can meet and approach requirement, i.e. p∞≈p512；So far, the low-frequency range met the requirements is more
Sinusoidal signal x (t) solution finishes.
It is described that Levenberg-Marquart algorithm is combined using gauss-newton method as a preferred technical solution, in step S7
Solve column vector pp, specifically include the following steps:
S71, by lpNorm is rewritten asWherein e is the column vector that N × 1 is tieed up, each element e in en=xn q, n
=0,1 ..., N-1, q=p/2；The transposition of subscript T expression vector；
S72, Jacobian matrix J is solved, specific as follows:
Define Jacobian matrix each elementIt further calculates to obtainIt enablesWherein n=0,1 ..., N-1, u
=1,2 ..., Nu, then have:
WhereinU=1,2 ..., Nu, v=1,2 ..., Nu；
S73, to Gaussian weighting marks equation p(i)=p(i-1)-[J(i-1)TJ(i-1)+Λ(i-1)]-1J(i-1)Te(i-1)It is iterated
Straight cause p convergence is solved, wherein Λ(i-1)It is the Levenberg-Marquart matrix an of positive definite.
The present invention has the following advantages compared with the existing technology and effect: the present invention is believed by sinusoidal more than specified low-frequency range
Number each harmonic component amplitude au, each frequencies of harmonic components ωuAnd sampling length N, one group of parameter of signal is solved with algorithmWherein u=1,2 ..., Nu, Nu≤ N/2, so that the maximum value of the more sinusoidal signal x (t) of low-frequency range is as far as possible
It is small, it is required so that input signal be made both to be able to satisfy Time Domain Amplitude limitation, keeps it smaller to the disturbance of system, and can be by input signal
Energy concentrate on the frequency range being concerned about, the energy without concern for frequency range is almost nil.With traditional small size pumping signal design side
Method is compared, and the method for the present invention solves input signal energy and do not concentrate, the low problem of the signal-to-noise ratio of output response signal, the present invention
The designed more sinusoidal signals of low-frequency range compare other low-frequency range pumping signals and are more suitable for POWER SYSTEM STATE spatial model
Identification.
Detailed description of the invention
Fig. 1 is the more sinusoidal signal design methods of low-frequency range for the identification of POWER SYSTEM STATE spatial model of the present embodiment
Flow chart；
Fig. 2 is the time domain waveform of three kinds of low-frequency range input signals in an application example of the present embodiment；
Fig. 3 is the frequency-domain waveform of three kinds of low-frequency range input signals in an application example of the present embodiment；
Fig. 4 is electric system wiring diagram based on an application example of the present embodiment；
Fig. 5 is the frequency-domain waveform of the corresponding output signal of three kinds of input signals in an application example of the present embodiment.
Specific embodiment
In order to which the purpose of the present invention, technical solution and advantage is more clearly understood, with reference to the accompanying drawings and embodiments,
The present invention is further described in detail.It should be appreciated that described herein, the specific embodiments are only for explaining the present invention,
It is not limited to the present invention.
Embodiment
In the present embodiment, the time-domain expression of the more sinusoidal signals of low-frequency range are as follows:Wherein t
For time, au、ωuWithAmplitude, frequency and the phase of respectively u-th multifrequency sinusoid component, NuFor sinusoidal harmonics frequency component
Number.
Define the crest factor of the more sinusoidal signals of low-frequency range are as follows:When wherein t is sampling
Between, N is total sampling number (i.e. the total length of signal) of the more sinusoidal signals of low-frequency range, and max () representative takes in bracket array most
Big value；Obviously, CrSize reflect signal in the fluctuation situation of time domain: the frequency domain characteristic of Setting signal x (t), signal x (t)
Time domain fluctuation get over hour, then its CrIt is smaller.
The more sinusoidal signal designs of low-frequency range, refer to a of Setting signalu、ωu、NuAnd sampling length N, it is solved with algorithmTo obtain one group of parameter of signalWherein u=1,2 ..., Nu, target is so that how sinusoidal low-frequency range is
The crest factor C of signal x (t)rIt is as small as possible, wherein t=t0, t1..., tN-1, so that the input signal for obtaining design, both full
The time domain waveform amplitude of sufficient POWER SYSTEM STATE spatial model identification, which limits, to be required, and is met its frequency domain energy and concentrated requirement.
As shown in Figure 1, a kind of low-frequency range for POWER SYSTEM STATE Stute space model identification of the present embodiment is mostly just
String signal design method, includes the following steps:
Initiation parameter:
S1, the total sampling number (i.e. the total length of signal) for determining the more sinusoidal signal x (t) of low-frequency range are N, then x's (t) is each
Sampled point is represented sequentially as x (t0), x (t1) ..., x (tN-1)；
S2, each harmonic component amplitude a for determining the more sinusoidal signal x (t) of low-frequency rangeuWith each frequencies of harmonic components ωu, wherein u
=1,2 ..., Nu, Nu≤ N/2, NuFor the number of sinusoidal harmonics frequency component；
The problem of designing low-frequency range more sinusoidal signal x (t) describes and conversion:
S3, the discrete l for defining the more sinusoidal signal x (t) of low-frequency rangepNorm isDiscrete l∞Norm isWherein xn=x (tn), n=0,1 ..., N-1；P value is positive integer；The then more sinusoidal signal x of low-frequency range
(t) crest factor CrIt may be expressed as:l2(xn) indicate the more sinusoidal signal x (t) of low-frequency range l2Model
Number；
S4, first harmonic phase for enabling the more sinusoidal signal x (t) of low-frequency rangeBy remaining harmonic phaseWith one
NpThe column vector p of × 1 dimension indicates, wherein Np=Nu-1；U=2,3 ..., Nu；Due to the l of x (t)2Norm and harmonic phaseNothing
It closes, then the crest factor C of the more sinusoidal signals of low-frequency rangerMinimization problem conversion are as follows: solve harmonic phaseThe column of composition to
P is measured, the peak value l of x (t) is made∞(x (p, t)) is minimum；
S5, the problem of step S4, is converted are as follows: solve a real value phase angle vector p∞∈RNp, so that in all alternative column
Vector p ∈ RNpThe peak value of middle x (t) is minimum, i.e. l∞(x(p∞,t))≤l∞(x(p,t)),
S6, basisUsing l that can be micro-pNorm carrys out the l of Step wise approximation non-differentiability∞Norm is used in combination
lpThe optimal solution p of normpCome approximate instead of l∞The optimal solution p of norm∞, therefore the problem of step S5, is further converted to: it is gradually increased
lpThe p value of norm, and column vector p is solved to each p valuep, make the l of x (t)pNorm minimum；
Column vector p is solved using algorithmpAnd the more sinusoidal signal x (t) of low-frequency range:
S7, to set gradually p be 4,8,16,32,64,128,256,512；To the p value of each setting, using Gauss ox
The method of pausing joint Levenberg-Marquart algorithm solves column vector pp, make the l of x (t)pNorm minimum, i.e. solution column vector p4So that x
(t) l4Norm minimum, then by p4As p8Initial value, solve column vector p8So that the l of x (t)8Norm minimum, according to this class
It pushes away；Wherein, column vector p is solvedpSpecifically include the following steps:
S71, by lpNorm is rewritten asWherein e is the column vector that N × 1 is tieed up, each element e in en=xn q,
N=0,1 ..., N-1, q=p/2；The transposition of subscript T expression vector；
S72, Jacobian matrix J is solved, specific as follows:
Define Jacobian matrix each elementIt further calculates to obtainIt enablesWherein n=0,1 ..., N-1, u
=1,2 ..., Nu, then have:
WhereinU=1,2 ..., Nu, v=1,2 ..., Nu；
S73, to Gaussian weighting marks equation p(i)=p(i-1)-[J(i-1)TJ(i-1)+Λ(i-1)]-1J(i-1)Te(i-1)It is iterated
Straight cause p convergence is solved, wherein Λ(i-1)It is the Levenberg-Marquart matrix an of positive definite.
S8, when p is set as 512, can meet and approach requirement, i.e. p∞≈p512；So far, the low-frequency range met the requirements is more
Sinusoidal signal x (t) solution finishes.
One application example of the method for the present invention introduced below.
The more sinusoidal signals of low-frequency range that a frequency domain energy concentrates on 0.1-2.5 hertz are generated with the method for the present invention, are used in combination
Conventional method generates the pseudo-random signal of the white noise signal and limited frequency band Jing Guo low-pass filter.Wherein, by low pass filtered
The white noise signal of wave device is to be filtered white noise signal with the 5 rank Butterworth filters that cutoff frequency is 2.5 hertz
It obtains, the pseudo-random signal of limited frequency band is will to pass through the amplitude of the white noise signal of low-pass filter according to the positive weight bearing of symbol
± 1p.u. is newly assigned a value of to obtain.Three kinds of low-frequency range input signal length are 100s, and sample rate is 100Hz, and signal is existed
The amplitude of time domain is limited between ± 0.1p.u..
Fig. 2 is the time domain waveform of three kinds of low-frequency range input signals；Fig. 3 is the frequency-domain waveform of three kinds of low-frequency range input signals,
Its ordinate is the amplitude of fourier coefficient.From figure 3, it can be seen that the energy of the more sinusoidal signals of low-frequency range nearly all concentrates on closing
The frequency range (0.1-2.5 hertz) of the heart, however the pseudo-random signal of white noise signal and limited frequency band Jing Guo low-pass filter has
Part energy has exceeded the frequency range of care.The more sinusoidal signals of low-frequency range and the pseudo-random signal of limited frequency band are being concerned about frequency range
Energy be it is comparable, the two is all higher than the white noise signal of low-pass filtering in the energy for being concerned about frequency range.
Fig. 4 is 10 machine of New England, the 39 node standard test system of the present embodiment foundation, and it includes 10 generators, 39
Bus, load and 34 transmission lines of electricity at 19.The rated frequency of the system is 60Hz, and mains voltage grade is 345kV, wherein
G1 machine is the equal check-ins of external electrical network, and G2 machine is balancing machine.Above-mentioned three kinds of low-frequency range input signals are attached to G9 respectively
The excitation voltage reference end of number generator, and taking the frequency of G9 machine connection No. 38 buses of bus is output signal, compares three kinds
In the case of output signal frequency domain energy distribution.
Fig. 5 is frequency-domain waveform corresponding to output signal in the case of three kinds.As can be seen that the more sinusoidal signals of low-frequency range and having
The corresponding output signal of the pseudo-random signal of frequency limit band is higher than in the energy for being concerned about frequency range to be believed by the white noise of low-pass filter
The energy of number corresponding output signal.In addition, the corresponding output of the more sinusoidal signals of pseudo-random signal and low-frequency range of limited frequency band
Signal is of substantially equal in the energy for being concerned about frequency range, but the corresponding output signal of pseudo-random signal of limited frequency band is in unconcerned 0-
The energy of 0.1 hertz of frequency range is also quite large, will bring noise effect, influences System Identification Accuracy.In conclusion low-frequency range is mostly just
The corresponding output signal-noise ratio highest of string signal is recognized most useful for electric system.
The embodiments described above only express several embodiments of the present invention, and the description thereof is more specific and detailed, but simultaneously
Limitations on the scope of the patent of the present invention therefore cannot be interpreted as.It should be pointed out that for those of ordinary skill in the art
For, without departing from the inventive concept of the premise, various modifications and improvements can be made, these belong to guarantor of the invention
Protect range.Therefore, the scope of protection of the patent of the present invention should subject to the claims.
Claims (2)
1. a kind of more sinusoidal signal design methods of low-frequency range for the identification of POWER SYSTEM STATE spatial model, which is characterized in that
Include the following steps:
Initiation parameter:
S1, the total sampling number for determining the more sinusoidal signal x (t) of low-frequency range are N, then each sampled point of x (t) is represented sequentially as x
(t0), x (t1) ..., x (tN-1)；
S2, according to the time-domain expression of the more sinusoidal signal x (t) of low-frequency range are as follows:Determine low-frequency range
Each harmonic component amplitude a of more sinusoidal signal x (t)uWith each frequencies of harmonic components ωu, wherein u=1,2 ..., Nu, Nu≤ N/2, Nu
For the number of sinusoidal harmonics frequency component；
The problem of designing low-frequency range more sinusoidal signal x (t) describes and conversion:
S3, the discrete l for defining the more sinusoidal signal x (t) of low-frequency rangepNorm isDiscrete l∞Norm isWherein xn=x (tn), n=0,1 ..., N-1；P value is positive integer；The then more sinusoidal signal x of low-frequency range
(t) crest factor CrIt may be expressed as:l2(xn) indicate the more sinusoidal signal x (t) of low-frequency range l2Model
Number；
S4, first harmonic phase for enabling the more sinusoidal signal x (t) of low-frequency rangeBy remaining harmonic phaseWith a Np×
The column vector p of 1 dimension indicates, wherein Np=Nu-1；U=2,3 ..., Nu；Due to the l of x (t)2Norm and harmonic phaseIt is unrelated, then
The crest factor C of the more sinusoidal signals of low-frequency rangerMinimization problem conversion are as follows: solve harmonic phaseThe column vector p of composition, makes
The peak value l of x (t)∞(x (p, t)) is minimum；
S5, the problem of step S4, is converted are as follows: solve a real value phase angle vector p∞∈RNp, so that in all alternative column vectors
p∈RNpThe peak value of middle x (t) is minimum, i.e. l∞(x(p∞,t))≤l∞(x(p,t)),
S6, basisUsing l that can be micro-pNorm carrys out the l of Step wise approximation non-differentiability∞Norm, and use lpModel
Several optimal solution ppCome approximate instead of l∞The optimal solution p of norm∞, therefore the problem of step S5, is further converted to: it is gradually increased lpModel
Several p values, and column vector p is solved to each p valuep, make the l of x (t)pNorm minimum；
Column vector p is solved using algorithmpAnd the more sinusoidal signal x (t) of low-frequency range:
S7, to set gradually p be 4,8,16,32,64,128,256,512；To the p value of each setting, using gauss-newton method
Joint Levenberg-Marquart algorithm solves column vector pp, make the l of x (t)pNorm minimum, i.e. solution column vector p4So that x (t)
L4Norm minimum, then by p4As p8Initial value, solve column vector p8So that the l of x (t)8Norm minimum, and so on；
S8, when p is set as 512, can meet and approach requirement, i.e. p∞≈p512；So far, how sinusoidal the low-frequency range met the requirements is
Signal x (t) solution finishes.
2. low-frequency range more sinusoidal signal design sides according to claim 1 for the identification of POWER SYSTEM STATE spatial model
Method, which is characterized in that described that column vector p is solved using gauss-newton method joint Levenberg-Marquart algorithm in step S7p,
Specifically include the following steps:
S71, by lpNorm is rewritten asWherein e is the column vector that N × 1 is tieed up, each element e in en=xn q, n=0,
1 ..., N-1, q=p/2；The transposition of subscript T expression vector；
S72, Jacobian matrix J is solved, specific as follows:
Define Jacobian matrix each elementIt further calculates to obtain
It enablesWherein n=0,1 ..., N-1, u=1,2 ..., Nu, then have:
WhereinU=1,2 ..., Nu, v=1,2 ..., Nu；
S73, to Gaussian weighting marks equation p(i)=p(i-1)-[J(i-1)TJ(i-1)+Λ(i-1)]-1J(i-1)Te(i-1)It is iterated solution
Straight cause p restrains, wherein Λ(i-1)It is the Levenberg-Marquart matrix an of positive definite.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910002124.6A CN109726490B (en) | 2019-01-02 | 2019-01-02 | Low-frequency band multi-sine signal design method for power system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910002124.6A CN109726490B (en) | 2019-01-02 | 2019-01-02 | Low-frequency band multi-sine signal design method for power system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109726490A true CN109726490A (en) | 2019-05-07 |
| CN109726490B CN109726490B (en) | 2020-09-22 |
Family
ID=66299553
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910002124.6A Active CN109726490B (en) | 2019-01-02 | 2019-01-02 | Low-frequency band multi-sine signal design method for power system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109726490B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112098721A (en) * | 2020-08-13 | 2020-12-18 | 闽南理工学院 | Harmonic detection method based on state space model |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20110146406A1 (en) * | 2009-07-15 | 2011-06-23 | Ata Engineering, Inc. | Methods and apparatus for vibration testing using multiple sine sweep excitation |
| CN102621891A (en) * | 2012-03-26 | 2012-08-01 | 哈尔滨工业大学 | Method for identifying inertial parameters of six-degree-of-freedom parallel mechanism |
| CN103226039A (en) * | 2013-04-08 | 2013-07-31 | 哈尔滨工程大学 | Harmonic identification method of sinusoidal vibration test of electrohydraulic servo vibration table |
| CN103488078A (en) * | 2013-07-18 | 2014-01-01 | 清华大学 | Excitation signal optimization method for improving closed-loop identification accuracy of power system |
| CN108280593A (en) * | 2018-02-24 | 2018-07-13 | 山东大学 | Time-lag power system stability method of discrimination based on IGD-IRK |
| CN108493936A (en) * | 2018-05-03 | 2018-09-04 | 浙江九州量子信息技术股份有限公司 | The improved method of low-frequency oscillation of electric power system estimation based on subspace state space system identification |
| CN108932215A (en) * | 2018-05-21 | 2018-12-04 | 华南理工大学 | A kind of more sinusoidal signal design methods of low-frequency range for the identification of electric system multiple-input and multiple-output inearized model |
-
2019
- 2019-01-02 CN CN201910002124.6A patent/CN109726490B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20110146406A1 (en) * | 2009-07-15 | 2011-06-23 | Ata Engineering, Inc. | Methods and apparatus for vibration testing using multiple sine sweep excitation |
| CN102621891A (en) * | 2012-03-26 | 2012-08-01 | 哈尔滨工业大学 | Method for identifying inertial parameters of six-degree-of-freedom parallel mechanism |
| CN103226039A (en) * | 2013-04-08 | 2013-07-31 | 哈尔滨工程大学 | Harmonic identification method of sinusoidal vibration test of electrohydraulic servo vibration table |
| CN103488078A (en) * | 2013-07-18 | 2014-01-01 | 清华大学 | Excitation signal optimization method for improving closed-loop identification accuracy of power system |
| CN108280593A (en) * | 2018-02-24 | 2018-07-13 | 山东大学 | Time-lag power system stability method of discrimination based on IGD-IRK |
| CN108493936A (en) * | 2018-05-03 | 2018-09-04 | 浙江九州量子信息技术股份有限公司 | The improved method of low-frequency oscillation of electric power system estimation based on subspace state space system identification |
| CN108932215A (en) * | 2018-05-21 | 2018-12-04 | 华南理工大学 | A kind of more sinusoidal signal design methods of low-frequency range for the identification of electric system multiple-input and multiple-output inearized model |
Non-Patent Citations (3)
| Title |
|---|
| JUNBO ZHANG 等: "Instantaneous sensitivity identification in power systems - challenges and technique roadmap", 《2016 IEEE POWER AND ENERGY SOCIETY GENERAL MEETING (PESGM)》 * |
| 叶丰 等: "基于低速采样的多正弦波信号频率估计", 《SIGNAL PROCESSING》 * |
| 孔祥臻: "气动比例系统的动态特性与控制研究", 《中国优秀硕士学位论文全文数据库（信息科技辑）》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112098721A (en) * | 2020-08-13 | 2020-12-18 | 闽南理工学院 | Harmonic detection method based on state space model |
| CN112098721B (en) * | 2020-08-13 | 2023-05-26 | 闽南理工学院 | Harmonic detection method based on state space model |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109726490B (en) | 2020-09-22 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Prince et al. | Modeling, parameter measurement, and control of PMSG-based grid-connected wind energy conversion system | |
| Biricik et al. | Real‐time control of shunt active power filter under distorted grid voltage and unbalanced load condition using self‐tuning filter | |
| CN110112769A (en) | Virtual synchronous machine exports feedback adaptive control method | |
| CN107121609A (en) | A kind of electric network impedance on-line identification method and device that injection is disturbed based on PRBS | |
| CN103701152B (en) | The method and system of the flickering carry-over factor acquisition that a kind of photo-voltaic power generation station is grid-connected | |
| Tugulea | Criteria for the definition of the electric power quality and its measurement systems | |
| CN105048995B (en) | Butterworth digital filter and realize the adaptive filtering method of frequency using it | |
| Litrán et al. | Electromagnetic compatibility analysis of a control strategy for a hybrid active filter | |
| CN108414838B (en) | Method for measuring line impedance of inverter parallel system | |
| CN103197130A (en) | Power grid voltage ZCP (Zero Crossing Point) detecting method and device | |
| Silsüpür et al. | Flicker source detection methods based on IEC 61000-4-15 and signal processing techniques–a review | |
| KR101325473B1 (en) | A motor monitoring system | |
| CN109726490A (en) | A kind of more sinusoidal signal design methods of low-frequency range for the identification of POWER SYSTEM STATE spatial model | |
| Hosseini | The operation and model of UPQC in voltage sag mitigation using EMTP by direct method | |
| CN103134969B (en) | A kind of power factor corrector and phase voltage method of estimation | |
| CN108932215A (en) | A kind of more sinusoidal signal design methods of low-frequency range for the identification of electric system multiple-input and multiple-output inearized model | |
| Kumar et al. | PI, fuzzy logic controlled shunt active power filter for three-phase four-wire systems with balanced, unbalanced and variable loads | |
| George et al. | A novel, DSP based algorithm for optimizing the harmonics and reactive power under non-sinusoidal supply voltage conditions | |
| CN104393777B (en) | Half-bridge module multi-level converter submodule voltage control method | |
| CN104393780B (en) | Full-bridge modules multi-level converter submodule voltage control method | |
| CN107634657B (en) | Predictive control method and device for matrix converter | |
| CN103454505B (en) | Based on open phase detection method and the circuit of harmonic detecting | |
| CN113358922B (en) | Fundamental wave, harmonic wave and inter-harmonic wave electric energy power measurement method of unsteady state power grid signal | |
| CN105958510B (en) | SOC chip for power grid monitoring and control equipment | |
| CN205960648U (en) | Chain type static synchronous compensator control system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |