CN111984920A - Subsynchronous/supersynchronous harmonic parameter identification method, subsynchronous/supersynchronous harmonic parameter identification device, subsynchronous/supersynchronous harmonic parameter identification equipment and medium - Google Patents
Subsynchronous/supersynchronous harmonic parameter identification method, subsynchronous/supersynchronous harmonic parameter identification device, subsynchronous/supersynchronous harmonic parameter identification equipment and medium Download PDFInfo
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Abstract
The application relates to a sub/super synchronous harmonic parameter identification method, a sub/super synchronous harmonic parameter identification device, a computer device and a computer readable storage medium, wherein the method comprises the steps of obtaining a power signal; discretizing the power signal to obtain a discrete power signal; processing the discrete power signal by using a windowed interpolation FFT (fast Fourier transform) to obtain an amplitude parameter and a frequency parameter of subsynchronous/supersynchronous harmonics in the power signal; and processing the discrete power signal by using the apFFT to obtain a phase parameter of the subsynchronous/supersynchronous harmonic in the power signal. The frequency parameter, the amplitude parameter and the phase parameter of the subsynchronous/supersynchronous harmonic obtained by the method have higher precision, so that the measurement requirement of oscillation detection of a power system is met, and the influence of interference sources such as noise on the identification precision can be effectively reduced.
Description
Technical Field
The present application relates to the field of power system technologies, and in particular, to a sub/super synchronous harmonic parameter identification method, a sub/super synchronous harmonic parameter identification apparatus, a computer device, and a computer-readable storage medium.
Background
At present, new energy represented by wind energy and photovoltaic is developed rapidly, and a power generation mode under the background of the new energy has the advantages of low operation and maintenance cost, flexible installation scale, renewability and the like. Compared with the traditional mode, the new energy power generation shows unique and excellent performance, and meanwhile, the safe and stable operation of a power grid is challenged. Due to the difference of power electronic equipment and power generation mechanisms adopted by new energy power generation and direct current transmission, equipment such as a static var compensator adopted in the new energy power generation process may introduce Subsynchronous/supersynchronous harmonic components into a power grid, and further large-scale power accidents such as Subsynchronous Oscillation (SSO) in the system are caused, so that irretrievable huge economic loss is caused.
The academic research attention of new energy grid connection is focused on higher harmonics (namely integral multiples of 50Hz fundamental waves), while subsynchronous harmonic components and supersynchronous harmonic components are more focused on a generation mechanism and a harmonic source positioning technology, and the subsynchronous/supersynchronous harmonic component detection technology in an actual power grid is not mature. Therefore, the high-accuracy subsynchronous/supersynchronous harmonic parameter identification algorithm has important significance for monitoring and controlling subsequent SSO, ensuring reliable delivery of electric energy, safe and stable operation of extra-high voltage direct current and safe and stable operation of a terminal power grid.
In the conventional technology, Fast Fourier Transform (FFT) is widely used in the technical fields of harmonic analysis and the like due to the characteristics of small calculation amount and analysis delay. However, the non-synchronous sampling and non-integer period truncation can generate frequency spectrum leakage and barrier effect phenomena when the power grid signals are subjected to discrete analysis, and at the moment, the parameters of the harmonic signals are difficult to identify with high precision by using spectral line information, so that the requirement of the harmonic parameter detection function is difficult to meet.
Disclosure of Invention
Based on this, it is necessary to provide a sub/super synchronous harmonic parameter identification method, a sub/super synchronous harmonic parameter identification device, a computer device, and a computer readable storage medium, for solving the technical problem in the conventional technology that the sub/super synchronous harmonic parameter identification cannot be realized with high precision by using an FFT algorithm.
A sub/super-synchronous harmonic parameter identification method, the method comprising:
acquiring a power signal;
discretizing the power signal to obtain a discrete power signal;
processing the discrete power signal by utilizing a windowing interpolation FFT (fast Fourier transform) to obtain an amplitude parameter and a frequency parameter of subsynchronous/supersynchronous harmonics in the power signal; and
and processing the discrete power signal by using an apFFT (adaptive fast Fourier transform algorithm) to obtain a phase parameter of a subsynchronous/supersynchronous harmonic in the power signal.
In one embodiment, the processing the discrete power signal by using a windowed interpolation FFT to obtain the amplitude parameter and the frequency parameter of the sub/super-synchronous harmonic in the power signal includes:
obtaining a length of NpMSD-SCW function of (d);
using said length as NpThe MSD-SCW function of (a) performs truncation weighting on the discrete power signals of the same length;
processing the discrete power signal after the truncation and weighting by using FFT to obtain a first discrete spectrum of the sub/super synchronous harmonic;
at least two spectral lines are selected from the spectral lines on the left side and the right side of the theoretical peak frequency point of the first discrete spectrum to be fitted to obtain a fitted curve;
and obtaining the amplitude parameter and the frequency parameter of the subsynchronous/supersynchronous harmonic according to the fitting curve.
In one embodiment, the acquisition length is NpThe sequence of MSD self-convolution window functions of (a) includes:
obtaining a length of N1Performing p-1 times of self-convolution operation on the discrete MSD window function sequence to obtain a convolution sequence constructed by p discrete MSD window function sequences;
zero padding at the end of the convolution sequence to obtain the length NpMSD-SCW function of (d);
wherein, the N isp＝pN1。
In one embodiment, the fitting at least two spectral lines selected from the spectral lines on the left and right sides of the theoretical peak frequency point of the first discrete spectrum to obtain a fitted curve includes:
finding four maximum spectral lines in the spectral lines on the left side and the right side of the theoretical peak frequency point of the first discrete spectrum;
and fitting the four found spectral lines by using a least square method to obtain the fitting curve.
In one embodiment, the length obtained is NpThe MSD-SCW function of (1) is a fourth order MSD-SCW function.
In one embodiment, the processing the discrete power signal by the apFFT to obtain the phase parameter of the sub/super-synchronous harmonic in the power signal includes:
preprocessing the discrete power signal;
processing the preprocessed discrete power signal by using FFT to obtain a second discrete spectrum;
finding a dominant line of the second discrete spectrum;
and obtaining the phase parameters of the subsynchronous/supersynchronous harmonic according to the main spectral line of the second discrete spectrum.
In one embodiment, the pre-processing the discrete power signal comprises:
aligning by taking the center point of the data sample of the discrete power signal as a reference, and performing cyclic shift processing to obtain a full-phase subsection;
weighting the full-phase subsegment at a first windowing position point and a second windowing position point by adopting a Nuttall single window function; the first windowing position point is a position point of truncated data of the discrete power signal, and the second windowing position point is a position point at which the full-phase subsegment is weighted.
A sub/super-synchronous harmonic parameter identification apparatus, the apparatus comprising:
the acquisition module is used for acquiring the power signal;
the discretization module is used for discretizing the power signal to obtain a discretization power signal;
the first analysis module is used for processing the discrete power signal by utilizing a windowed interpolation FFT (fast Fourier transform) to obtain an amplitude parameter and a frequency parameter of subsynchronous/supersynchronous harmonics in the power signal; and
and the second analysis module is used for processing the discrete power signal by utilizing the apFFT to obtain the phase parameter of the subsynchronous/supersynchronous harmonic in the power signal.
A computer device comprising a memory storing a computer program and a processor implementing the steps of the method as claimed in any one of the preceding claims when the processor executes the computer program.
A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of the preceding claims.
According to the subsynchronous/supersynchronous harmonic parameter identification method, the subsynchronous/supersynchronous harmonic parameter identification device, the computer equipment and the storage medium, the windowed interpolation FFT and the apFFT are combined, so that the precision of the frequency parameter, the amplitude parameter and the phase parameter of the obtained subsynchronous/supersynchronous harmonic is higher, the measurement requirement of oscillation detection of a power system is met, and the influence of interference sources such as noise on the identification precision can be effectively reduced.
Drawings
FIG. 1 is a schematic flow chart of a sub/super-synchronous harmonic parameter identification method according to an embodiment;
FIG. 2 is a flowchart illustrating step S130 according to an embodiment;
FIG. 3 is a flowchart illustrating step S140 according to an embodiment;
FIG. 4 is a graph of 1 to 4 order self-convolution window amplitude-frequency characteristics based on a 5-entry MSD window in one embodiment;
FIG. 5 is a diagram of an FFT four spectral line interpolation algorithm in one embodiment;
FIG. 6 is a graphical representation of the parameter identification results of the present invention and control algorithms in one embodiment;
FIG. 7 is a schematic diagram of the parameter identification results of the present invention and the control algorithm in a white noise background according to an embodiment;
FIG. 8 is a schematic diagram showing the parameter identification results of the algorithm of the present invention and the control group under frequency-varying conditions in one embodiment;
fig. 9 is a block diagram showing the structure of the sub/super-synchronous harmonic parameter identification apparatus according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
In one embodiment, as shown in fig. 1, there is provided a sub/super synchronous harmonic parameter identification method, comprising the steps of:
step S110, a power signal is acquired.
Specifically, a power signal in the power grid is obtained. Due to the fact that electronic equipment and power supply power generation mechanisms adopted by new energy power generation and direct current transmission are different, subsynchronous/supersynchronous harmonic components are introduced into a power grid, collected power signals in the power grid have signals of the introduced subsynchronous/supersynchronous harmonic components, and then various parameters of the introduced subsynchronous/supersynchronous harmonic waves can be obtained by analyzing the power signals, wherein the parameters include frequency parameters, amplitude parameters and phase parameters.
Step S120, discretizing the power signal to obtain a discrete power signal.
Specifically, the discretization processing is performed on the power signal to obtain a discrete power signal so as to provide sample data for a fourier transform processing process in a subsequent windowed interpolation FFT and full-phase spectrum analysis (apFFT).
Step S130, processing the discrete power signal by using the windowed interpolation FFT to obtain the amplitude parameter and the frequency parameter of the subsynchronous/supersynchronous harmonic in the power signal.
Specifically, discrete power signals need to be sampled and truncated before fast fourier transform, and synchronous sampling and whole-period truncation are difficult to realize by an FFT algorithm, so that spectrum leakage and a fence effect exist when sub/super synchronous harmonic signals are analyzed, and parameter accuracy obtained by analysis is affected. In this embodiment, the windowing interpolation FFT is used to process the discrete power signal to obtain the amplitude parameter and the frequency parameter of the sub/super synchronous harmonic in the power signal, the frequency spectrum leakage can be suppressed by the windowing operation, and the fence effect can be eliminated by the interpolation operation, so that the amplitude parameter and the frequency parameter of the sub/super synchronous harmonic in the power signal obtained by the final processing have higher precision.
Step S140, processing the discrete power signal by using an apFFT to obtain a phase parameter of the sub/super synchronous harmonic in the power signal.
Specifically, the full-phase spectrum analysis (apFFT) is an improved algorithm of the traditional FFT, can improve the fence effect and the truncation effect of the FFT, and has the characteristics of less spectrum leakage and unchanged phase, so that the phase parameter of the subsynchronous/supersynchronous harmonic in the electric power signal obtained by processing the discrete electric power signal by using the apFFT has higher precision.
According to the subsynchronous/supersynchronous harmonic parameter identification method, the windowed interpolation FFT and the apFFT are combined, so that the precision of the frequency parameter, the amplitude parameter and the phase parameter of the obtained subsynchronous/supersynchronous harmonic is higher, the measurement requirement of oscillation detection of a power system is met, and the influence of interference sources such as noise on the identification precision can be effectively reduced.
In another embodiment, the subsynchronous/supersynchronous harmonic parameter identification method comprises the following steps:
step S110, a power signal is acquired.
Step S120, discretizing the power signal to obtain a discrete power signal.
Specifically, a to-be-detected subsynchronous/supersynchronous harmonic signal x (t) containing multiple frequency components is set, and the sampling frequency is fsAfter the step of converting the analog signal into the digital signal, the obtained discrete sequence is as follows:
wherein A ish、fh、
Respectively representing the amplitude, frequency and phase angle parameters of the harmonic signal to be analyzed.
Step S130, processing the discrete power signal by using the windowed interpolation FFT to obtain the amplitude parameter and the frequency parameter of the sub/super synchronous harmonic in the power signal, as shown in fig. 2, wherein the step S130 includes steps S131 to S135.
Step S131, obtaining the length NpMSD-SCW function of.
Specifically, the length N is obtained first1The sequence may be a discrete self-convolution window function sequence based on a 5-term MSD window, and p-1 self-convolution operations are performed on the discrete self-convolution window function sequence to obtain a convolution sequence constructed by p discrete MSD window function sequences. Then, zero filling is carried out at the end of the convolution sequence to obtain the length Np＝pN1MSD self-restriction window (MSD-SCW) function of (1). For example, the length of acquisition is NpThe MSD-SCW function of (1) may be a fourth order MSD-SCW function. Wherein p represents the number of original mother windows,
the time domain expression for MSD is:
wherein, M is the number of terms of the window, and N is 0,1, 2. And, bmThe convergence condition of the cosine window is to be satisfied.
The self convolution operation formula for the time domain discrete MSD function is as follows:
wp(n)＝w(m)*w(m)*...*w(m) (3)
for example, formula (2) may be assigned b0 ═ 0.2734375, b1 ═ 0.4375, b2 ═ 0.21875, b3 ═ 0.0625, and b4 ═ 0.0078125. After assignment, performing 1-p order self convolution operation on the formula (2) according to the formula (3), and then performing zero filling to obtain the length NpMSD-SCW function of.
Step S132, using the length NpThe MSD-SCW function of (a) performs truncation weighting on discrete power signals of the same length.
Step S133, the discrete power signal after the truncation and weighting is processed by FFT to obtain a first discrete spectrum of the sub/super-synchronous harmonic.
Specifically, the length is NpThe MSD-SCW function of (1) truncates the sub/super-synchronous harmonic signal after dispersion. After Discrete Fourier Transform (DFT) is performed on the obtained sequence, the side lobe influence of the negative frequency point peak is ignored, and its discrete spectrum is:
w (·) is the selected truncated window DFT expression, k ═ 0,1,2, …, N-1. For the convenience of analysis and formula derivation, the h-th harmonic is considered, the formula (4) can be simplified to the formula (5), and the modulus of the formula is the spectral line amplitude.
And S134, at least two spectral lines are selected from the spectral lines on the left side and the right side of the theoretical peak frequency point of the first discrete spectrum to be fitted to obtain a fitting curve.
Specifically, the maximum four spectral lines are found from the spectral lines on the left and right sides of the theoretical peak frequency point of the first discrete spectrum, and then the found four spectral lines are fitted by using a least square method based on numerical analysis to obtain a fitting curve.
Setting a theoretical peak frequency point k in a discrete frequency spectrumhThe maximum four spectral lines on the left side and the right side are respectively kh1、kh2、kh3And kh4. The amplitudes of the four spectral lines are respectively y1、y2、y3And y4. Defining frequency correction quantity alpha-kh-kh2-0.5, since 0. ltoreq. kh-kh2Less than or equal to 1, the value range of alpha is alpha E [ -0.5,0.5 [ ]]. The coefficient β is defined as (y)4+3y3-3y2-y1)/(y4+3y3+3y2+y1) Substituting equation (5) therein, the resulting expression can be regarded as a function of β with respect to α, that is, β ═ f (α).
In alpha e-0.5, 0.5]Within the interval, a plurality of points are sampled at equal intervals. Using a derived function of beta with respect to alpha, each alphaiThe corresponding beta can be obtainediThe numerical value is inversely fitted to the formula (6) by the polyfit function in MATLAB, that is, α ═ f is obtained1(β)。
α＝b1β+b3β3+...+b2q+1β2q+1 (7)
Wherein, b1,b3,…,b2q+1Is an approximation coefficient of the polynomial and is odd.
And step S135, obtaining the amplitude parameter and the frequency parameter of the subsynchronous/supersynchronous harmonic according to the fitting curve.
Specifically, after the frequency correction amount is solved, the frequency and amplitude parameters of the h-th harmonic can be identified by the equations (8) and (9).
fh＝khΔf＝(kh2+α+0.5)·fs/N (8)
Step S140, processing the discrete power signal by using an apFFT to obtain a phase parameter of the sub/super synchronous harmonic in the power signal, as shown in fig. 3, wherein the step S140 includes steps S141 to S144.
Step S141, preprocessing the discrete power signal.
Specifically, the data sample center points of the discrete power signals are aligned with each other as a reference, and cyclic shift processing is performed to obtain the full-phase subsegment. Then, the entire phase subsegment is weighted at the first windowed location point and the second windowed location point using a Nuttall single window function. In this embodiment, the first windowing position point is a position point of truncated data of the discrete power signal, and the second windowing position point is a position point at which the full-phase sub-segment is weighted. The Nuttall single window function may be a four-term fifth order Nuttall single window function.
Step S142, processing the preprocessed discrete power signal by using FFT to obtain a second discrete spectrum.
And S143, finding the main spectral line of the second discrete spectrum.
And S144, obtaining the phase parameters of the subsynchronous/supersynchronous harmonic waves according to the main spectral line of the second discrete spectrum.
Illustratively, the value of b for equation (2) is0＝0.3125，b1＝0.46875，b2＝0.1875，b30.03125. If the input signal is a single frequency signal, then:
wherein, ω is0Is the numerical angular frequency of the sequence; theta0Is the initial phase of the sequence. According to the time shift property, the relationship between the output spectrums of the FFT and the apFFT satisfies the following formula:
wherein k belongs to [0, N-1], and X (k) is a frequency spectrum obtained by FFT operation of a signal, namely a second discrete spectrum; g (k) is a frequency spectrum obtained by the signal through the apFFT operation; m represents the number of cyclic shifts performed on the data segment. The sum of the DTFTs of the apFFT then consists of:
wherein, WR(k) A rectangular window function spectrum is represented. The apFFT also has barrier effect and needs parameter correction. Correcting the parameter identification result by using a ratio method, and setting parameters:
the expression (13) can be regarded as an expression of β' with respect toh2Is the dominant line of the second discrete spectrum. Wherein ═ kh-kh2For the frequency offset,' ∈ (-1, 1). After solving, the identification result of the parameters adopting the double-window apFFT is as follows:
ω′0＝(kh2±′)Δω (14)
θ′＝arg[Y(k)]＝θ0 (16)
wherein, ω is0' A ', theta ' represent the parameter identification correction equations for frequency, amplitude and phase, respectively; Δ ω ═ 2 π/N is the frequency resolution; w' (. cndot.) is the DFT expression for the selected truncation window.
In the sub/super synchronous harmonic parameter identification method in the above embodiment, the MSD-CSW function interpolation correction FFT algorithm has high accuracy for identifying the frequency and amplitude parameters of the sub/super synchronous harmonic signal, and the apFFT has a "phase angle fixing characteristic", and can realize the phase detection function with high accuracy.
It should be understood that although the various steps in the flow charts of fig. 1-3 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least some of the steps in fig. 1-3 may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, which are not necessarily performed in sequence, but may be performed in turn or alternately with other steps or at least some of the other steps.
The following explains a specific calculation process of the sub/super-synchronous harmonic parameter identification method in the above embodiment as follows:
firstly, the parameter b0＝0.2734375，b1＝0.4375，b2＝0.21875，b3＝0.0625，b4Equation (2) is assigned to 0.0078125, resulting in a sequence of 5 discrete MSD window functions. When N is much greater than 1, the window function spectrum is simplified to:
the 1 to p-order self convolution operation is performed on the formula (17), and according to the operation theorem of convolution, the spectrum function of the p-order MSD-CSW function based on the MSD mother window shown in the formula (18) can be obtained, and the normalized logarithmic magnitude spectrum of the spectrum is shown in FIG. 4.
As can be seen from fig. 4, regarding the side lobe characteristic index in the log spectrogram, the absolute value of the side lobe peak level of the MSD-SCW function is greatly reduced with the increase of p, and the side lobe attenuation rate is also improved with the increase of p, i.e., the overall side lobe performance is obviously improved with the increase of p. But in contrast, the main lobe width of the SCW function increases (the frequency resolution decreases). Therefore, the invention selects the fourth order MSD-SCW function to carry out truncation weighting on the subsynchronous/supersynchronous harmonic signals.
Still adopt the harmonic signal shown in formula (1), adopt the four orders MSD-SCW function established to weight it, and then carry on DFT operation, obtain the discrete frequency spectrum after the harmonic signal weighting. Normalization processing is carried out on the discrete spectrum, and theoretical peak value frequency point kh2The nearby spectral amplitude distribution is shown in fig. 5. According to the fitting process based on the least square method and the fitting times are set to be 7, the four-spectral-line frequency correction quantity based on the fourth-order MSD-SCW function is obtained as follows:
α＝11.15178β+2.14500β3+0.98275β+0.59174β7 (19)
when N is large, expression (9) can be simplified to expression (20), whereby the amount of computation for amplitude parameter identification can be greatly reduced.
u(α)＝c0+c2α2+...+c2qα2q (21)
Wherein, c0,c2,…,c2qEven coefficients are approximated for the polynomial. In the same way, a set of values of u (α) can be obtained by substituting a set of α, and by performing a polyfit (α, u (α),6) fitting, u (α) of the fourth-order MSD-SCW function can be obtained as:
u(α)＝16037.98610+804.14431α2+20.51964α4+0.35759α6 (22)
still using equation (10), it can be seen from the above that the apFFT algorithm has higher analysis accuracy for the phase parameter through the data preprocessing process. As shown in the formulas (12) and (16), the phase of the main spectrum peak can be directly taken.
The formula (1) is assigned and subjected to simulation analysis, so that the subsynchronous harmonic parameter identification method in the embodiment has high practical value and high-precision detection performance. The three parameters are specifically assigned as shown in table 1, and the key technical problem of the invention is fully considered by setting the parameters, namely the possibility that subsynchronous/supersynchronous interharmonic waves are annihilated by harmonic waves exists and whether the parameter information can be accurately identified when the frequency spectrum interval is close.
TABLE 1
The invention sets the fundamental frequency f0Is 50.1Hz, sampling frequency fsIs 2500 Hz. In order to compare and verify the technical effects generated by the invention, a comparison group algorithm shown in fig. 6 is selected for comparison with the invention, and fig. 6 shows the parameter identification relative error under the steady-state condition by adopting the comparison group algorithm and the invention.
When the amplitude parameter is measured, compared with a classic window interpolation FFT harmonic parameter identification algorithm, the method has the advantage that the accuracy is obviously improved. Compared with the solving result of interpolation FFT based on the addition of a Nuttall truncation window and a Hanning truncation window, the identification precision is improved by 1 to 6 orders of magnitude; for phase parameter measurement, the relative error of phase extraction by adopting the algorithm of the invention is less than 10-10%, and the method is obviously improved compared with other analysis methods. Such as: for 60Hz harmonic phase detection, the relative error of the invention is 10-11%, and the relative error of the interpolation algorithm with Nuttall truncation window is 10-5%, which is improved by 6 orders of magnitude. From the analysis, the invention can accurately analyze the frequency characteristic value when the inter-spectrum interference exists, thereby accurately identifying the parameter of the sub/super synchronous inter-harmonic wave.
Because the actual engineering environment contains a large amount of noise, on the basis of the simulation, white noise with different signal-to-noise ratios (the ratio of the harmonic signal value to the noise ratio is the signal-to-noise ratio) is added to the signal to verify the noise resistance of the invention. FIG. 7 shows the parameter identification results of 25Hz subharmonic amplitude and phase in sequence, and the comparison group is the interpolation FFT identification method with Hamming truncation window. As can be seen from fig. 7, when the noise in the signal is large, the increment of the relative error identified by all algorithms with respect to the amplitude and phase parameters is obvious. As the noise content decreases, the difference from the parameter identification accuracy when no noise is added is gradually reduced. Simulation results show that: the method can effectively overcome the influence of white noise on the identification accuracy of the sub/super-synchronous inter-harmonic component parameters, and has low error variation.
If the sub/super-synchronous inter-harmonics in the actual power grid are subjected to parameter analysis, the influence of frequency variation on the analysis result must be considered. Still adopt the simulation signal in the above-mentioned content to verify the technical effect of the present invention, when the variation interval of the fundamental frequency parameter is set to 49.5-50.5Hz, the parameter identification result of the present invention is shown in fig. 8. When the signal frequency changes, the inter-harmonic signal amplitude parameter identification result based on the method and the parameter identification precision based on the steady-state harmonic condition are basically kept in the same order of magnitude; the relative error identified by the phase parameter of the time-varying inter-harmonic signal is in the range of 10-10% -10-9%, and the relative error under the steady-state condition is basically kept in the range of 10-12%. Therefore, the method has the advantages that the parameter identification error increment is not obvious under the background of frequency fluctuation, and the disadvantage of frequency fluctuation to the sub/super synchronous inter-harmonic signal parameter identification precision can be effectively overcome.
In one embodiment, as shown in fig. 9, there is provided a sub/super-synchronous harmonic parameter identification apparatus including: an acquisition module 910, a discretization module 920, a first analysis module 930, and a second analysis module 940, wherein:
the obtaining module 910 is configured to obtain a power signal. The discretization module 920 is configured to discretize the power signal to obtain a discrete power signal. The first analysis module 930 is configured to process the discrete power signal by using the windowed interpolation FFT to obtain an amplitude parameter and a frequency parameter of the sub/super-synchronous harmonic in the power signal. The second analysis module 940 is configured to process the discrete power signal by using an apFFT to obtain a phase parameter of the sub/super-synchronous harmonic in the power signal.
The specific definition of the sub/super synchronous harmonic parameter identification device can be referred to the definition of the sub/super synchronous harmonic parameter identification method in the above, and is not described herein again. The modules in the subsynchronous/supersynchronous harmonic parameter identification device can be fully or partially realized by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is further provided, which includes a memory and a processor, the memory stores a computer program, and the processor implements the steps of the above method embodiments when executing the computer program.
In an embodiment, a computer-readable storage medium is provided, on which a computer program is stored which, when being executed by a processor, carries out the steps of the above-mentioned method embodiments.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database or other medium used in the embodiments provided herein can include at least one of non-volatile and volatile memory. Non-volatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical storage, or the like. Volatile Memory can include Random Access Memory (RAM) or external cache Memory. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), among others.
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A sub/super synchronous harmonic parameter identification method, the method comprising:
acquiring a power signal;
discretizing the power signal to obtain a discrete power signal;
processing the discrete power signal by utilizing a windowing interpolation FFT (fast Fourier transform) to obtain an amplitude parameter and a frequency parameter of subsynchronous/supersynchronous harmonics in the power signal; and
and processing the discrete power signal by using an apFFT (adaptive fast Fourier transform algorithm) to obtain a phase parameter of a subsynchronous/supersynchronous harmonic in the power signal.
2. The method of claim 1, wherein the processing the discrete power signal using a windowed interpolation FFT to obtain magnitude and frequency parameters of sub/super-synchronous harmonics in the power signal comprises:
obtaining a length of NpMSD-SCW function of (d);
using said length as NpThe MSD-SCW function of (a) performs truncation weighting on the discrete power signals of the same length;
processing the discrete power signal after the truncation and weighting by using FFT to obtain a first discrete spectrum of the sub/super synchronous harmonic;
at least two spectral lines are selected from the spectral lines on the left side and the right side of the theoretical peak frequency point of the first discrete spectrum to be fitted to obtain a fitted curve;
and obtaining the amplitude parameter and the frequency parameter of the subsynchronous/supersynchronous harmonic according to the fitting curve.
3. The method of claim 2, wherein the acquisition length is NpThe sequence of MSD self-convolution window functions of (a) includes:
obtaining a length of N1Performing p-1 times of self-convolution operation on the discrete MSD window function sequence to obtain a convolution sequence constructed by p discrete MSD window function sequences;
zero padding at the end of the convolution sequence to obtain the length NpMSD-SCW function of (d);
wherein, the p represents the number of original mother windows, and the Np＝pN1。
4. The method of claim 2, wherein fitting at least two spectral lines selected from the spectral lines to the left and right of the theoretical peak frequency bin of the first discrete spectrum to obtain a fitted curve comprises:
finding four maximum spectral lines in the spectral lines on the left side and the right side of the theoretical peak frequency point of the first discrete spectrum;
and fitting the four found spectral lines by using a least square method to obtain the fitting curve.
5. The method according to any one of claims 2 to 4, wherein the length obtained is NpThe MSD-SCW function of (1) is a fourth order MSD-SCW function.
6. The method of claim 1, wherein the processing the discrete power signal with the apFFT to obtain the phase parameter of the subsynchronous/supersynchronous harmonic in the power signal comprises:
preprocessing the discrete power signal;
processing the preprocessed discrete power signal by using FFT to obtain a second discrete spectrum;
finding a dominant line of the second discrete spectrum;
and obtaining the phase parameters of the subsynchronous/supersynchronous harmonic according to the main spectral line of the second discrete spectrum.
7. The method of claim 6, wherein the pre-processing the discrete power signal comprises:
aligning by taking the center point of the data sample of the discrete power signal as a reference, and performing cyclic shift processing to obtain a full-phase subsection;
weighting the full-phase subsegment at a first windowing position point and a second windowing position point by adopting a Nuttall single window function; the first windowing position point is a position point of truncated data of the discrete power signal, and the second windowing position point is a position point at which the full-phase subsegment is weighted.
8. A sub/super-synchronous harmonic parameter identification apparatus, the apparatus comprising:
the acquisition module is used for acquiring the power signal;
the discretization module is used for discretizing the power signal to obtain a discretization power signal;
the first analysis module is used for processing the discrete power signal by utilizing a windowed interpolation FFT (fast Fourier transform) to obtain an amplitude parameter and a frequency parameter of subsynchronous/supersynchronous harmonics in the power signal; and
and the second analysis module is used for processing the discrete power signal by utilizing the apFFT to obtain the phase parameter of the subsynchronous/supersynchronous harmonic in the power signal.
9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any of claims 1 to 7.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 7.
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