CN103105533A - Intelligent analysis method and intelligent analysis system of sub-synchronous oscillation - Google Patents
Intelligent analysis method and intelligent analysis system of sub-synchronous oscillation Download PDFInfo
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Abstract
The invention discloses an intelligent analysis method and an intelligent analysis system of sub-synchronous oscillation. The intelligent analysis method of the sub-synchronous oscillation includes the following steps of generating a correction factor and a transformation factor according to the range of frequency to be analyzed and the refining level of the frequency, obtaining input wave form data and window function data, generating input wave form correction data according to the correction factor, the input wave form data and the window function data, generating frequency spectrum composition of the input wave form data according to the transformation factor and the input wave form correction data, conducting peak value scanning on the frequency spectrum composition, screening out the frequency of a sub-synchronous oscillation component, generating a filter coefficient diagram according to the sampling frequency, the pass-band coefficient, the attenuation band coefficient and the width of a transmission band, mapping the position of each frequency of the sub-synchronous oscillation component on the filter coefficient diagram, assigning value to the coefficient of a modal filter, and generating a synchronous oscillation component according to the input wave form data after initializing the modal filter. The intelligent analysis method and the intelligent analysis system of sub-synchronous oscillation can achieve real-time intelligent analysis and detection of the sub-synchronous oscillation of an electrical power system.
Description
Technical field
The invention relates to the sub-synchronous oscillation analytical technology, particularly about a kind of sub-synchronous oscillation intelligent analysis method and system.
Background technology
In prior art, the analytical approach of sub-synchronous oscillation adopts the spectrum analysis technique of long-time window usually, use the mass data of long-time window (generally being longer than for 10 seconds) due to this Technology Need, real-time analysis is calculated more difficult, the normal method that adopts the ex-post analysis of off-line, namely obtain the test recorder data in test at the scene, then, adopt the spectrum analysis of long-time window to find out the subsynchronous frequency component of wherein containing.Adopt the spectrum analysis technique of long-time window, can make the result of spectrum analysis meticulousr, can distinguish preferably two very near spectrum components that lean on.But owing to must beginning to calculate after the data that gather full whole time window, postpone longer, generation and evolution that can not the real-time follow-up sub-synchronous oscillation.And analyzing is to carry out at frequency domain, can not show the subsynchronous component actual waveform in time domain.
In order to address the above problem, prior art adopts the modal filter technology in the additional damping controller of excitation (SEDC), and subsynchronous frequency component Real-Time Filtering is calculated, and is used for damping and controls.Adopt the modal filter group need to know in advance the frequency of each subsynchronous component, then for each subsynchronous component, the parameter (tuning) of corresponding modal filter is set, the incoming wave graphic data is carried out filtering to be calculated, can at time domain real-time analysis sub-synchronous oscillation, monitor generation and the evolution of subsynchronous component.
But because each frequency component in sub-synchronous oscillation is very approaching each other, can not use broadband filter, can only use narrow band filter, need to measure in advance the frequency of each sub-synchronous oscillation component, adjust the parameter of each modal filter (narrow band filter) with this, in test the generation of real time monitoring subsynchronous component and evolution.Therefore in the situation that the unknown of subsynchronous component frequency can not be used for analysis of experiments, in case and the subsynchronous resonance frequency change, just need to readjust the parameter of modal filter, adaptability is relatively poor.
Summary of the invention
The invention provides a kind of sub-synchronous oscillation intelligent analysis method and system, to realize real-time intelligent analysis and the monitoring of subsynchronous oscillation of electrical power system.
To achieve these goals, the invention provides a kind of sub-synchronous oscillation intelligent analysis method, the method comprises: generate modifying factor and conversion factor according to frequency range to be analyzed and frequency refinement degree; Obtain incoming wave graphic data and window function data, and generate input waveform modification data according to described modifying factor, incoming wave graphic data and window function data; Consist of according to the frequency spectrum of described conversion factor and the described incoming wave graphic data of described input waveform modification data generation; Described frequency spectrum is consisted of carry out peak value scanning, and filter out the frequency of sub-synchronous oscillation component; Generate filter coefficient table according to sampling rate, passband coefficient, stopband coefficient and passband width; Shine upon the position of frequency in described filter coefficient table of each described sub-synchronous oscillation component, and to the coefficient assignment of modal filter; Described modal filter is carried out generating the sub-synchronous oscillation component according to described incoming wave graphic data after initialization.
Further, generate input waveform modification data according to described modifying factor, incoming wave graphic data and window function data, comprising: the waveform modification data are inputted in the result that obtains and the described window function generation of multiplying each other of multiplying each other of described modifying factor and incoming wave graphic data.
Further, described frequency spectrum is consisted of carry out peak value scanning, and filter out the sub-synchronous oscillation component, comprising: scan the frequency of each peak value in described frequency spectrum formation, go out the frequency of the significant sub-synchronous oscillation component of peak value according to the index screening of default peak value significance.
Further, described incoming wave graphic data comprises: stator voltage, stator current, rotor voltage and rotor current.
To achieve these goals, the invention provides a kind of sub-synchronous oscillation intelligent analysis system, this system comprises: factor generation unit generates modifying factor and conversion factor according to frequency range to be analyzed and frequency refinement degree; Input waveform amending unit obtains incoming wave graphic data and window function data, and generates input waveform modification data according to described modifying factor, incoming wave graphic data and window function data; The frequency spectrum generation unit is used for consisting of according to the frequency spectrum of described conversion factor and the described incoming wave graphic data of described input waveform modification data generation; The frequency screening unit is used for described frequency spectrum is consisted of and carries out peak value scanning, and filters out the frequency of sub-synchronous oscillation component; The filter coefficient table generation unit is used for generating filter coefficient table according to sampling rate, passband coefficient, stopband coefficient and passband width; The assignment unit is used for the frequency of each described sub-synchronous oscillation component of mapping in the position of described filter coefficient table, and to the coefficient assignment of modal filter; Sub-synchronous oscillation component generation unit is used for described modal filter is carried out generating the sub-synchronous oscillation component according to described incoming wave graphic data after initialization.
Further, described input waveform amending unit specifically is used for obtaining the incoming wave graphic data of window function data and input filter, and the waveform modification data are inputted in the result that obtains and the described window function generation of multiplying each other of multiplying each other of described modifying factor and incoming wave graphic data.
Further, described frequency screening unit specifically is used for scanning the frequency that described frequency spectrum consists of each peak value, goes out the frequency of the significant sub-synchronous oscillation component of peak value according to the index screening of default peak value significance.
The beneficial effect of the embodiment of the present invention is, the present invention is based on the smart frequency spectrum analysis of short time window, can complete the mode Filtering Analysis of hands-off tuning, realizes real-time intelligent analysis and the monitoring of subsynchronous oscillation of electrical power system.
Description of drawings
In order to be illustrated more clearly in the embodiment of the present invention or technical scheme of the prior art, the below will do to introduce simply to the accompanying drawing of required use in embodiment or description of the Prior Art, apparently, accompanying drawing in the following describes is only some embodiments of the present invention, for those of ordinary skills, under the prerequisite of not paying creative work, can also obtain according to these accompanying drawings other accompanying drawing.In the accompanying drawings:
Fig. 1 is embodiment of the present invention sub-synchronous oscillation intelligent analysis method process flow diagram;
Fig. 2 is that the embodiment of the present invention is based on the smart frequency spectrum analysis process figure of short time window;
Fig. 3 is the mode Filtering Analysis method flow diagram of embodiment of the present invention hands-off tuning;
Fig. 4 is the composition schematic diagram of embodiment of the present invention sub-synchronous oscillation real-time intelligent analyser;
Fig. 5 is the structural representation of embodiment of the present invention sub-synchronous oscillation intelligent analysis system.
Embodiment
For the purpose, technical scheme and the advantage that make the embodiment of the present invention is clearer, below in conjunction with accompanying drawing, the embodiment of the present invention is described in further details.At this, illustrative examples of the present invention and explanation thereof are used for explanation the present invention, but not as a limitation of the invention.
It is relatively poor that the present invention will solve long-time window spectrum analysis real-time traditional in the subsynchronous oscillation of electrical power system analysis, and the relatively poor problem of mode Filtering Analysis adaptability.Realization reaches the real-time intelligent analysis of subsynchronous oscillation of electrical power system and the purpose of monitoring based on the mode Filtering Analysis of smart frequency spectrum analysis and the hands-off tuning of short time window.
To achieve these goals, as shown in Figure 1, the present embodiment provides a kind of sub-synchronous oscillation intelligent analysis method, and the method comprises the mode Filtering Analysis step based on the smart frequency spectrum analytical procedure of short time window and hands-off tuning.
Smart frequency spectrum analytical procedure based on the short time window is the step S101 to S104 of Fig. 1, is described in detail below in conjunction with frequency-domain analysis method shown in Figure 2.
That frequency spectrum in frequency-domain analysis incoming wave graphic data consists of based on the smart frequency spectrum analysis of short time window, namely calculate in 10Hz～50Hz frequency range based on the incoming wave graphic data of short time window (being generally for 1 second), size at the contained component of each Frequency point place's input waveform, and adopt statistical method, search out the comparatively significant Frequency point in spectrum peak, thereby judge whether to contain subsynchronous component, if having determine simultaneously its frequency values.
S101: generate modifying factor and conversion factor according to frequency range to be analyzed and frequency refinement degree.
According to the frequency range of prepare analyzing (due to the scope of sub-synchronous oscillation at 10Hz～50Hz, so the frequency range of analyzing generally should be preset in 10Hz～50Hz) and the refinement degree of frequency (generally should be better than 0.1Hz), calculates modifying factor α n according to following formula:
θ wherein
0=2*3.14*f1/fs, wherein,
N=1,2 ... N, f1 is the left side dividing value (for example f1=10) of the scope of the sub-synchronous oscillation of analysis, f2 is the right dividing value (for example f2=50) of the scope of the sub-synchronous oscillation of analysis, fs is sample frequency (for example fs=1000), m for the frequency line number analyzed (m=1000 for example, this moment, the frequency degree of refinement was (50-10)/1000=0.04Hz), N is the number of input one frame data, and j is the symbol of the imaginary part of plural number.
According to preparing the frequency range of analyzing, the degree of refinement of frequency, draw conversion factor β n according to following formula:
θ wherein
0=2*3.14*f1/fs, wherein,
N=1,2 ... N, f1 is the left side dividing value (for example f1=10) of the scope of the sub-synchronous oscillation of analysis, f2 is the right dividing value (for example f2=50) of the scope of the sub-synchronous oscillation of analysis, fs is sample frequency (for example fs=1000), m for the frequency line number analyzed (m=1000 for example, this moment, the frequency degree of refinement be (50-10)/1000=0.04Hz), N is for inputting the number of frame data.
S102: obtain incoming wave graphic data and window function data, and generate input waveform modification data according to described modifying factor, incoming wave graphic data Xn and window function data.
The incoming wave graphic data of input filter comprises: the data such as stator voltage, stator current, rotor voltage and rotor current, the window function data are: 0.42-0.5*cos (2*3.14*n/ (N-1))+0.08*cos (4*3.14*n/ (N-1)).
Generating input waveform modification data according to modifying factor, incoming wave graphic data and window function data refers to the waveform modification data are inputted in the result that obtains and the window function generation of multiplying each other of multiplying each other of modifying factor and incoming wave graphic data.Incoming wave graphic data Xn is time domain full mold data, α n is the replica data, α n*Xn (the n=1 that modifying factor and incoming wave graphic data multiply each other and obtain, 2 ... N) be time domain replica data, (0.42-0.5*cos (2*3.14*n/ (N-1))+0.08*cos (4*3.14*n/ (N-1)) multiplies each other, and draws input waveform modification data with data α n*Xn and window function.
S103: consist of according to the frequency spectrum of described conversion factor and the described incoming wave graphic data of described input waveform modification data generation.Conversion factor β n obtains in the above, and conversion factor β n and input waveform modification data are done following convolution algorithm:
λ＝α1*X1*β
N+α2*X2*β
N-1+……+α
N*X
N*β
1
The result that obtains is namely that the frequency spectrum of incoming wave graphic data in the predeterminated frequency scope consists of.
S104: described frequency spectrum is consisted of carry out peak value scanning, and filter out the frequency of sub-synchronous oscillation component.
Scan the frequency of each peak value in described frequency spectrum formation, and count the significance degree of each peak value, go out the significant frequency of peak value according to the index screening of default peak value significance, can judge whether to contain subsynchronous component, if having determined simultaneously its frequency values.
The mode Filtering Analysis step of hands-off tuning is the step S105 to S107 of Fig. 1, describes mode Filtering Analysis how to realize hands-off tuning in detail below in conjunction with Fig. 3.
S105: generate filter coefficient table according to sampling rate, passband coefficient, stopband coefficient and passband width.
According to sampling rate (1000Hz), passband coefficient (0.1db), stopband coefficient (60db), the parameters such as passband width (5Hz), (for example Filter Design Toolbox in Matlab) calculates filter coefficient table by filter-design software.This filter coefficient table can realize by the double-precision floating points array of 94 row 17 row, and every delegation of array is the integrity coefficient of a digital filter, below is two row wherein:
double?COE[94][17]＝{
…………
{7.961763969823331e+000，-2.775376335240645e+001，5.532493575728520e+001，-6.898013604194000e+001，5.508471157768973e+001，-2.751326971296128e+001，7.858502394504878e+000，-9.827445927252109e-001，-4.441704141550790e-005，3.198612407154106e-004，-9.870514695213828e-004，1.692032909508284e-003，-1.740248944965106e-003，1.073903578982141e-003，-3.681827754526516e-004，5.410250216697629e-005，3.135394100260578e-003}，
{7.957985876155535e+000，-2.773120841444045e+001，5.526876692384941e+001，-6.890544950929723e+001，5.502878663323315e+001，-2.749091021972249e+001，7.854773301524098e+000，-9.827445927252219e-001，-4.439596420901040e-005，3.195999998685667e-004，-9.860442046231988e-004，1.690193178722904e-003，-1.738476992000138e-003，1.073029541890383e-003，-3.680080617810694e-004，5.410250216692425e-005，3.135394100260578e-003}，
…………
}
S106: shine upon the position of frequency in described filter coefficient table of each described sub-synchronous oscillation component, and to the coefficient assignment of modal filter.
Frequency according to each sub-synchronous oscillation component that obtains in step S104, by mapping calculation (to the frequency rounding operation of above-mentioned each sub-synchronous oscillation component, result deducts side-play amount 10 again, namely draw the relevant position in filter coefficient table), find suitable coefficient in filter coefficient table, and to the coefficient assignment of each modal filter.
S107: described modal filter is carried out generating the sub-synchronous oscillation component according to described incoming wave graphic data after initialization.
Adopt the wave filter of state space construction, namely carry out the filtering of Zn+1=A*Zn+B*Xn and Yn=C*Zn+D*Xn and calculate, wherein A, B, C, D are matrix of coefficients, and the data in matrix of coefficients are the coefficient of the relevant position in filter coefficient table.Zn is current time state space vector, and Zn+1 is next state space vector constantly, and Xn is the input quantity of current time, and Yn is the filtering output quantity of current time.
Zn is initially 0, uses front 10 seconds long sampled data input filters of current time, and after as above filtering was calculated, Zn wherein namely completed the initialization of modal filter.
Utilize the input filter data (stator voltage, stator current, rotor voltage and rotor current) of input filter to carry out above-mentioned filtering calculating to initialized above-mentioned modal filter, just obtained the subsynchronous component of stator voltage, stator current, rotor voltage and rotor current.
Utilize existing sub-synchronous oscillation real-time intelligent analyser, adopt above analytical approach, just can realize the real-time intelligent analysis of subsynchronous oscillation of electrical power system and the purpose of monitoring.
the generator unit stator voltage of voltage transformer (VT) secondary is adopted the LV25P of LEM company to isolate and is depressurized to signal to be measured in the 5V scope, the stator current amount of current transformer secondary is isolated with the CASR6NP of LEM company and change signal to be measured in the 5V scope, use the rear generation of the AD210AN isolation signal to be measured of ADI company after being depressurized in the 5V scope to generator amature voltage with resitstance voltage divider, generate signal to be measured after using the AD210AN isolation after adopting instrument amplifier AD620 to be amplified in the 5V scope to the generator rotor current signal of coming from shunt.To forming digital quantity with the analog signals sampling, be input to the TMS320C6747 digital signal processor of TI company, use above algorithm, draw the frequency spectrum of input signal and the instantaneous value of subsynchronous component.Fig. 4 is the composition schematic diagram of sub-synchronous oscillation real-time intelligent analyser.
The beneficial effect of the embodiment of the present invention is, the present invention is based on the smart frequency spectrum analysis of short time window, can complete the mode Filtering Analysis of hands-off tuning, realizes real-time intelligent analysis and the monitoring of subsynchronous oscillation of electrical power system.
As shown in Figure 5, the invention provides a kind of sub-synchronous oscillation intelligent analysis system, this system comprises: factor generation unit 501, input waveform amending unit 502, frequency spectrum generation unit 503, frequency screening unit 504, filter coefficient table generation unit 505, assignment unit 506 and sub-synchronous oscillation component generation unit 507.
θ wherein
0=23.14*f1/fs, wherein,
N=1,2 ... N, f1 is the left side dividing value (for example f1=10) of the scope of the sub-synchronous oscillation of analysis, f2 is the right dividing value (for example f2=50) of the scope of the sub-synchronous oscillation of analysis, fs is sample frequency (for example fs=1000), m for the frequency line number analyzed (m=1000 for example, this moment, the frequency degree of refinement be (50-10)/1000=0.04Hz), N is for inputting the number of frame data.
θ wherein
0=2*3.14*f1/fs, wherein,
N=1,2 ... N, f1 is the left side dividing value (for example f1=10) of the scope of the sub-synchronous oscillation of analysis, f2 is the right dividing value (for example f2=50) of the scope of the sub-synchronous oscillation of analysis, fs is sample frequency (for example fs=1000), m for the frequency line number analyzed (m=1000 for example, this moment, the frequency degree of refinement be (50-10)/1000=0.04Hz), N is for inputting the number of frame data.
Input waveform amending unit 502 obtains incoming wave graphic data and window function data, and generates input waveform modification data according to described modifying factor, incoming wave graphic data and window function data.
The incoming wave graphic data of input filter comprises: the data such as stator voltage, stator current, rotor voltage and rotor current, the window function data are: 0.42-0.5*cos (2*3.14*n/ (N-1))+0.08*cos (4*3.14*n/ (N-1)).
Input waveform amending unit 502 generates input waveform modification data according to modifying factor, incoming wave graphic data and window function data and specifically refers to: input waveform amending unit 502 is inputted the waveform modification data with the result that obtains and the window function generation of multiplying each other of multiplying each other of modifying factor and incoming wave graphic data.Incoming wave graphic data Xn is time domain full mold data, α n is the replica data, α n*Xn (the n=1 that modifying factor and incoming wave graphic data multiply each other and obtain, 2 ... N) be time domain replica data, (0.42-0.5*cos (2*3.14*n/ (N-1))+0.08*cos (4*3.14*n/ (N-1)) multiplies each other, and draws input waveform modification data with data α n*Xn and window function.
Frequency spectrum generation unit 503 is used for consisting of according to the frequency spectrum of described conversion factor and the described incoming wave graphic data of described input waveform modification data generation.
Conversion factor β n obtains in the above, and 503 couples of conversion factor β n of frequency spectrum generation unit and input waveform modification data are done following convolution algorithm:
λ＝α1*X1*β
N+α2*X2*β
N-1+……+α
N*X
N*β
1
The result that obtains is namely that the frequency spectrum of incoming wave graphic data in the predeterminated frequency scope consists of.
The frequency of each peak value during the frequency screening unit 504 described frequency spectrums of scanning consist of, and count the significance degree of each peak value, go out the significant frequency of peak value according to the index screening of default peak value significance, can judge whether to contain subsynchronous component, if having determined simultaneously its frequency values.
Filter coefficient table generation unit 505 is used for generating filter coefficient table according to sampling rate, passband coefficient, stopband coefficient and passband width.
According to sampling rate (1000Hz), passband coefficient (0.1db), stopband coefficient (60db), the parameters such as passband width (5Hz), (for example Filter Design Toolbox in Matlab) calculates filter coefficient table by filter-design software.
Sub-synchronous oscillation component generation unit 507 is used for described modal filter is carried out generating the sub-synchronous oscillation component according to described incoming wave graphic data after initialization.
Sub-synchronous oscillation component generation unit 507 adopts the wave filter of state space construction, namely carrying out the filtering of Zn+1=A*Zn+B*Xn and Yn=C*Zn+D*Xn calculates, wherein A, B, C, D are matrix of coefficients, and the data in matrix of coefficients are the coefficient of the relevant position in filter coefficient table.Zn is current time state space vector, and Zn+1 is next state space vector constantly, and Xn is the input quantity of current time, and Yn is the filtering output quantity of current time.
Zn is initially 0, uses front 10 seconds long sampled data input filters of current time, and after as above filtering was calculated, Zn wherein namely completed the initialization of modal filter.
Sub-synchronous oscillation component generation unit 507 utilizes the input filter data (stator voltage, stator current, rotor voltage and rotor current) of input filter to carry out above-mentioned filtering to initialized above-mentioned modal filter and calculates, and has just obtained the subsynchronous component of stator voltage, stator current, rotor voltage and rotor current.
The beneficial effect of the embodiment of the present invention is, the present invention is based on the smart frequency spectrum analysis of short time window, can complete the mode Filtering Analysis of hands-off tuning, realizes real-time intelligent analysis and the monitoring of subsynchronous oscillation of electrical power system.
Above-described specific embodiment; purpose of the present invention, technical scheme and beneficial effect are further described; institute is understood that; the above is only specific embodiments of the invention; the protection domain that is not intended to limit the present invention; within the spirit and principles in the present invention all, any modification of making, be equal to replacement, improvement etc., within all should being included in protection scope of the present invention.
Claims (8)
1. a sub-synchronous oscillation intelligent analysis method, is characterized in that, described method comprises:
Generate modifying factor and conversion factor according to frequency range to be analyzed and frequency refinement degree;
Obtain incoming wave graphic data and window function data, and generate input waveform modification data according to described modifying factor, incoming wave graphic data and window function data;
Consist of according to the frequency spectrum of described conversion factor and the described incoming wave graphic data of described input waveform modification data generation;
Described frequency spectrum is consisted of carry out peak value scanning, and filter out the frequency of sub-synchronous oscillation component;
Generate filter coefficient table according to sampling rate, passband coefficient, stopband coefficient and passband width;
Shine upon the position of frequency in described filter coefficient table of each described sub-synchronous oscillation component, and to the coefficient assignment of modal filter;
Described modal filter is carried out generating the sub-synchronous oscillation component according to described incoming wave graphic data after initialization.
2. the method for claim 1, is characterized in that, generates input waveform modification data according to described modifying factor, incoming wave graphic data and window function data, comprising:
The multiply each other result that obtains and described window function of described modifying factor and incoming wave graphic data multiplied each other and generate input waveform modification data.
3. the method for claim 1, is characterized in that, described frequency spectrum consisted of carry out peak value scanning, and filter out the sub-synchronous oscillation component, comprising:
Scan the frequency of each peak value in described frequency spectrum formation, go out the frequency of the significant sub-synchronous oscillation component of peak value according to the index screening of default peak value significance.
4. the method for claim 1, is characterized in that, described incoming wave graphic data comprises: stator voltage, stator current, rotor voltage and rotor current.
5. a sub-synchronous oscillation intelligent analysis system, is characterized in that, described system comprises:
Factor generation unit is used for generating modifying factor and conversion factor according to frequency range to be analyzed and frequency refinement degree;
Input waveform amending unit is used for obtaining incoming wave graphic data and window function data, and generates input waveform modification data according to described modifying factor, incoming wave graphic data and window function data;
The frequency spectrum generation unit is used for consisting of according to the frequency spectrum of described conversion factor and the described incoming wave graphic data of described input waveform modification data generation;
The frequency screening unit is used for described frequency spectrum is consisted of and carries out peak value scanning, and filters out the frequency of sub-synchronous oscillation component;
The filter coefficient table generation unit is used for generating filter coefficient table according to sampling rate, passband coefficient, stopband coefficient and passband width;
The assignment unit is used for the frequency of each described sub-synchronous oscillation component of mapping in the position of described filter coefficient table, and to the coefficient assignment of modal filter;
Sub-synchronous oscillation component generation unit is used for described modal filter is carried out generating the sub-synchronous oscillation component according to described incoming wave graphic data after initialization.
6. system as claimed in claim 5, it is characterized in that, described input waveform amending unit specifically is used for obtaining the incoming wave graphic data of window function data and input filter, and the waveform modification data are inputted in the result that obtains and the described window function generation of multiplying each other of multiplying each other of described modifying factor and incoming wave graphic data.
7. system as claimed in claim 5, is characterized in that, described frequency screening unit specifically is used for scanning the frequency that described frequency spectrum consists of each peak value, goes out the frequency of the significant sub-synchronous oscillation component of peak value according to the index screening of default peak value significance.
8. system as claimed in claim 5, is characterized in that, described incoming wave graphic data comprises: stator voltage, stator current, rotor voltage and rotor current.
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| CN110412349A (en) * | 2019-08-27 | 2019-11-05 | 四川大学 | Synchronized phasor data sub-synchronous oscillation parameter identification method based on interpolated DFT |
| CN112446290A (en) * | 2020-10-19 | 2021-03-05 | 电子科技大学 | Key parameter identification method for wind power subsynchronous oscillation |
| CN112748285A (en) * | 2020-12-21 | 2021-05-04 | 中国航天科工集团八五一一研究所 | Phase measurement method based on intelligent tracking correlation operation |
| CN115060995A (en) * | 2022-06-14 | 2022-09-16 | 费莱(浙江)科技有限公司 | Harmonic management method and system for intelligent filtering |
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| CN110412349A (en) * | 2019-08-27 | 2019-11-05 | 四川大学 | Synchronized phasor data sub-synchronous oscillation parameter identification method based on interpolated DFT |
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| CN112748285B (en) * | 2020-12-21 | 2023-04-28 | 中国航天科工集团八五一一研究所 | Phase measurement method based on intelligent tracking correlation operation |
| CN115060995A (en) * | 2022-06-14 | 2022-09-16 | 费莱(浙江)科技有限公司 | Harmonic management method and system for intelligent filtering |
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