Harmonic measurement method, system, device and storage medium based on self-compensating FFT

Abstract

A harmonic measurement method, system, device and storage medium based on self-compensating FFT belong to the technical field of power system signal analysis and solve the problem of how to achieve accurate measurement of harmonics. The present invention samples the voltage and current data of the power system after selecting the sampling frequency and the number of sampling points, then performs preliminary data processing, applies an appropriate window function, selects appropriate zero-filling points, and applies a radix-2 FFT on this basis. On the basis of obtaining the frequency and amplitude, a high-precision self-compensation algorithm is proposed to achieve mutual compensation of frequency and amplitude, accurately eliminate frequency offset and amplitude error, effectively improve the measurement accuracy of harmonic frequency and amplitude, and thus ensure the reliability of power system measurement and control. The present invention provides a more efficient and accurate harmonic monitoring solution for the power system.

Description

Technical Field

[0001] The present invention belongs to the technical field of power system signal analysis, and relates to a harmonic measurement method, system, equipment and storage medium based on self-compensating FFT. Background Art

[0002] With the continuous improvement of social electrification and the integration of numerous new energy projects, power electronic equipment, inverters, and various complex loads have been widely used in power grids. Harmonic pollution in power systems is becoming increasingly serious. The presence of these harmonics not only affects the operating efficiency and equipment life of power systems, but can also cause system failures, equipment overheating, and even damage. Harmonic analysis has become an integral part of power system operation and maintenance. Accurate detection and analysis of harmonic signals is crucial for stable grid operation, equipment protection, and power quality. Accurate detection and analysis of harmonics is a key task in power quality monitoring in power systems.

[0003] The Fast Fourier Transform (FFT) converts discrete signals from the time domain to the frequency domain by using infinitely long trigonometric functions as basis functions. This provides effective estimates of frequency and amplitude, making it a standard method for harmonic analysis in power systems. However, the FFT method still has some significant limitations in practical applications.

[0004] First, because the FFT assumes periodic signals, while real signals are often finite in length, the resulting spectral leakage and picket fence effect can affect the accuracy of frequency and amplitude measurements. Second, the FFT cannot effectively address inaccurate frequency alignment, resulting in significant calculation errors, particularly in the detection of higher-order harmonics. To improve measurement accuracy and reduce the impact of spectral leakage and picket fence effects on calculation results, a large number of window functions have been proposed and applied to the FFT. Windowed FFTs reduce spectral leakage by introducing window functions. Commonly used window functions include rectangular windows, Hanning windows, Hamming windows, and Blackman windows. Window functions weight the time-domain signal, resulting in smooth transitions at the time-domain endpoints, thereby reducing spectral leakage caused by truncation. In power system harmonic analysis, windowed FFTs have become a standard method for improving frequency estimation accuracy. Although windowed FFTs can effectively reduce spectral leakage and improve frequency estimation, due to the weighted nature of the window function, they cannot completely eliminate frequency alignment errors. When various window functions are applied, the frequency error can reach up to half the FFT's frequency resolution. Zero padding can produce a smoother frequency response on the spectrum, making frequency interpolation more accurate and therefore used in FFT calculations. Zero padding effectively refines the spectrum, reducing spectral leakage and improving the accuracy of frequency and amplitude estimation by increasing spectral resolution. However, zero padding only improves spectral smoothness and does not truly increase the frequency resolution of the FFT, as FFT resolution is still limited by the sampling frequency and data length. Summary of the Invention

[0005] The technical solution of the present invention is used to solve the problem of how to achieve accurate measurement of harmonics.

[0006] The present invention solves the above technical problems through the following technical solutions:

[0007] The present invention provides a harmonic measurement method based on self-compensating FFT, comprising the following steps:

[0008] S1 selects the sampling frequency and number of sampling points, discretely collects the current and voltage data signals of the N-point power system, recorded as x1(n), and performs filtering on the collected N-point data signals x1(n);

[0009] S2 selects a window function to perform windowing processing on the N-point data signal x(n) obtained by filtering, and obtains the N-point discrete sampling data signal x after windowing. w (n);

[0010] S3 is the N-point discrete sampling data signal x after windowing w (n) is filled with zero to obtain the zero-filled data signal x at point N0 w0 (n);

[0011] S4 fills the data signal x with zero w0 (n) performing radix-2 FFT calculation to obtain the frequency spectrum and amplitude spectrum of the data signal;

[0012] S5 searches for amplitude information greater than a set threshold based on the amplitude spectrum, and obtains the frequency compensation coefficient of each index point by combining the amplitude peak and the amplitude of its adjacent spectrum lines;

[0013] S6 performs fitting calculation based on the obtained frequency compensation coefficient of each index point to obtain the amplitude compensation coefficient of each index point;

[0014] S7 calculates the precise frequency and amplitude of each index point after compensation based on the obtained frequency compensation coefficient and amplitude compensation coefficient of each index point.

[0015] Furthermore, the method for searching for amplitude information greater than a set threshold based on the amplitude spectrum is as follows: for the mth harmonic, select spectrum line k m and its left and right spectral lines k m-1 、k m+1 , where spectral line k m The amplitude is the largest, k m-1 =k m -1,k m+1 =k m +1; the amplitudes of the corresponding spectral lines are A m-1 、A m 、A m+1 , the relationship among the three is A m-1 m >A m+1 , A m-1 and A m+1 The size relationship depends on the position of the spectrum line k0 of the real spectrum. m On the left or right side, if k0 is on the spectrum line k m On the left, then A m-1 >A m+1 , whereas A m-1 m+1 .

[0016] Furthermore, the frequency compensation coefficient is obtained by performing secondary interpolation on the amplitude information, and its calculation formula is as follows:

[0017]

[0018] Wherein, α is the frequency compensation coefficient.

[0019] Furthermore, the amplitude compensation coefficient is calculated as follows: the corrected frequency is obtained according to the frequency compensation coefficient, and then the spectrum line k is obtained. m The frequency correction amount is taken as the value, and after calculating the hth harmonic, the amplitude compensation coefficient is obtained by fitting. ​​

[0020] Furthermore, the calculation formula of the amplitude compensation coefficient is as follows:

[0021] β=g(δf0)

[0022] Where β is the amplitude compensation coefficient, g(δf0) is the polynomial fitting formula, and δf0 is the spectrum line k m Frequency correction amount.

[0023] Furthermore, the calculation formula for the precise frequency and amplitude of each index point after compensation is as follows:

[0024]

[0025] A0=βA m

[0026]

[0027] Where k is the corrected spectral line, A0 is the corrected amplitude, and Δf is the relative frequency resolution after zero padding.

[0028] The present invention also provides a harmonic measurement system based on self-compensating FFT, comprising:

[0029] The data acquisition and preprocessing module is used to discretely collect the current and voltage data signals of the power system and filter the collected data signals;

[0030] A data windowing module is used to perform windowing processing on the filtered data signal to obtain a windowed discrete sampling data signal;

[0031] A data zero-filling module is used to fill the windowed discrete sampling data signal with zeros to obtain a zero-filled data signal;

[0032] A self-compensation module is used to perform radix-2 FFT calculation on the zero-filled data signal and calculate the frequency compensation coefficient and amplitude compensation coefficient of each index point;

[0033] The output module is used to output the precise frequency and amplitude of each index point after compensation.

[0034] Furthermore, the method for calculating the frequency compensation coefficient and the amplitude compensation coefficient of each index point is as follows:

[0035] 1) Searching for amplitude information greater than a set threshold based on the amplitude spectrum;

[0036] 2) Obtain the frequency compensation coefficient by performing secondary interpolation based on the amplitude information;

[0037] 3) According to the frequency compensation coefficient, the corrected frequency is obtained, and then the spectrum line k is obtained mThe frequency correction amount is taken as the value, and after calculating the hth harmonic, the amplitude compensation coefficient is obtained by fitting.

[0038] Furthermore, the method for searching for amplitude information greater than a set threshold based on the amplitude spectrum is as follows: for the mth harmonic, select spectrum line k m and its left and right spectral lines k m-1 、k m+1 , where spectral line k m The amplitude is the largest, k m-1 =k m -1,k m+1 =k m +1; the amplitudes of the corresponding spectral lines are A m-1 、A m 、A m+1 , the relationship among the three is A m-1 m >A m+1 , A m-1 and A m+1 The size relationship depends on the position of the spectrum line k0 of the real spectrum. m On the left or right side, if k0 is on the spectrum line k m On the left, then A m-1 >A m+1 , whereas A m-1 m+1 .

[0039] Furthermore, the frequency compensation coefficient is calculated as follows:

[0040]

[0041] Wherein, α is the frequency compensation coefficient.

[0042] Furthermore, the calculation formula of the amplitude compensation coefficient is as follows:

[0043] β=g(δf0)

[0044] Where β is the amplitude compensation coefficient, g(δf0) is the polynomial fitting formula, and δf0 is the spectrum line k m Frequency correction amount.

[0045] Furthermore, the calculation formula for the precise frequency and amplitude of each index point after compensation is as follows:

[0046]

[0047] A0=βA m

[0048]

[0049] ​​Where k is the corrected spectral line, A0 is the corrected amplitude, and Δf is the relative frequency resolution after zero padding.

[0050] The present invention also provides a device including a memory and a processor, wherein the memory is used to store a program that supports the processor to execute the above-mentioned harmonic measurement method based on self-compensating FFT, and the processor is configured to execute the program stored in the memory.

[0051] The present invention also provides a storage medium having a computer program stored thereon. When the computer program is run by a processor, the steps of the above-mentioned harmonic measurement method based on self-compensating FFT are executed.

[0052] The beneficial effects of the present invention are:

[0053] The present invention samples the voltage and current data of the power system after selecting the sampling frequency and number of sampling points, then performs preliminary data processing, applies an appropriate window function, selects an appropriate zero-filling point, and applies a radix-2 FFT on this basis. On the basis of obtaining the frequency and amplitude, a high-precision self-compensation algorithm is proposed to achieve mutual compensation of frequency and amplitude, which can effectively improve the measurement accuracy of harmonic frequency and amplitude, thereby ensuring the reliability of power system measurement and control, and has very good application prospects.

[0054] The method of the present invention accurately eliminates frequency offset and amplitude error through frequency compensation and amplitude compensation, greatly improving the estimation accuracy of frequency and amplitude. While improving the harmonic measurement accuracy, it fully considers the limited storage space and sampling frequency, avoids the storage pressure caused by increasing the number of sampling points, and provides a more efficient and accurate harmonic monitoring solution for the power system.

[0055] The present invention performs self-compensation correlation calculation between frequency and amplitude on processed data to obtain corrected frequency and amplitude, and provides a high-precision algorithm with low operating cost and strong applicability for the calculation of harmonics in engineering applications.

[0056] The present invention not only rationally allocates the number of sampling points and reduces storage pressure, but also achieves highly accurate output results. Windowing and zero-padding provide reliable solutions for situations with insufficient sampling points, limited sampling frequency resolution, high host computer storage pressure, and spectrum leakage. Furthermore, a self-compensating correlation calculation between frequency and amplitude is performed on the processed data to obtain corrected, high-precision frequency and amplitude. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 is a flow chart of a harmonic measurement method based on self-compensating FFT according to a first embodiment of the present invention;

[0058] Figure 24 is a block diagram of a harmonic measurement system based on self-compensating FFT according to a second embodiment of the present invention;

[0059] Figure 3 This is a frequency error comparison diagram of the method of the present invention and the methods using FFT, windowed FFT, and windowed zero-filled FFT;

[0060] Figure 4 This is a frequency error comparison diagram of the method of the present invention and the methods using FFT, windowed FFT, and windowed zero-filled FFT. DETAILED DESCRIPTION

[0061] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0062] The technical solution of the present invention is further described below with reference to the accompanying drawings and specific embodiments:

[0063] Example 1

[0064] like Figure 1 As shown, this embodiment provides a harmonic measurement method based on self-compensating FFT, including the following steps:

[0065] Step 1: Select the sampling frequency and the number of sampling points, discretely collect the current and voltage data signals of the N-point power system, record them as x1(n), and filter the collected N-point data signals x1(n).

[0066] Let the sampling frequency be f s , then the frequency resolution is f s / N, the sampled data signal after filtering is expressed as follows:

[0067]

[0068] Where x(n) is the current and voltage discrete sampling data signal after filtering, n = 0, 1, 2..., N-1, h is the highest order of the added harmonic, A m is the amplitude of the mth harmonic, f m is the frequency of the mth harmonic, φ m is the phase of the mth harmonic.

[0069] Step 2: Based on the N-point data signal x(n) obtained by filtering in step 1, a window function is selected to perform windowing processing on it to obtain the N-point discrete sampling data signal x after windowing.w (n).

[0070] N-point discrete sampling data signal x after windowing w The formula for (n) is as follows:

[0071]

[0072] x w (n) = x(n)·w b-h (n)

[0073] Where w b-h (n) is the four-term Blackman-Harris window function.

[0074] Step 3: After adding window, the N-point discrete sampling data signal x w (n) is filled with zero to obtain the zero-filled data signal x at point N0 w0 (n).

[0075] Zero-fill data signal x w0 The formula for (n) is as follows:

[0076]

[0077] Wherein, N0 is the data length after zero padding, N0 is greater than N and is an integer power of 2.

[0078] Step 4: Fill the data signal x with zeros w0 (n) Perform radix-2 FFT calculation to obtain the frequency spectrum and amplitude spectrum of the data signal.

[0079] Fill the data signal x with zeros w0 (n) Perform a radix 2 FFT calculation to obtain the FFT result of the kth frequency point as follows:

[0080]

[0081] Where, X w0 (k) is the FFT result of the kth frequency point, j is the imaginary unit, is the basis function of FFT, and k represents the frequency index calculated by FFT;

[0082] The resulting frequency spectrum is:

[0083]

[0084] The amplitude spectrum is:

[0085]

[0086] Among them, f k is the frequency spectrum, A kis the amplitude spectrum.

[0087] This embodiment solves the problems of insufficient number of sampling points, limited sampling frequency resolution, high host computer storage pressure, spectrum leakage, etc. by selecting appropriate window functions and zero-padding, providing the prerequisite for achieving accurate measurement of harmonic frequency and amplitude.

[0088] Step 5: Based on the amplitude spectrum, search for amplitude information greater than a set threshold, and combine the amplitude peak and the amplitude of its adjacent spectrum lines to obtain the frequency compensation coefficient of each index point.

[0089] Taking the mth harmonic as an example, we select the spectrum line k m and its left and right spectral lines k m-1 、k m+1 , where k m The amplitude is the largest, k m-1 =k m -1,k m+1 =k m +1;

[0090] The amplitudes of the corresponding spectral lines are A m-1 、A m 、A m+1 , the relationship among the three is A m-1 m >A m+1 , A m-1 and A m+1 The size of the relationship depends on the position of the spectrum line of the real spectrum in k m On the left or right side, if k0 is in k m On the left, then A m-1 >A m+1 , whereas A m-1 m+1 ;

[0091] The frequency compensation coefficient α is obtained by performing secondary interpolation on the amplitude information. The specific formula is as follows:

[0092]

[0093] Step 6: Perform fitting calculation based on the frequency compensation coefficient of each index point obtained in step 5 to obtain the amplitude compensation coefficient of each index point.

[0094] According to the frequency compensation coefficient, the corrected frequency f0 is obtained, and then the spectrum line k is obtained. m Frequency correction δf0=f0-f m After calculating the hth harmonic, the amplitude compensation coefficient is obtained by fitting. The calculation formula of the amplitude compensation coefficient β is as follows:

[0095] β=g(δf0) ​​

[0096] Where g(δf0) is the polynomial fitting formula, δf0 is the spectrum line k m Frequency correction amount.

[0097] Step 7: Based on the frequency compensation coefficient of each index point obtained in step 5 and the amplitude compensation coefficient of each index point obtained in step 6, calculate the precise frequency and amplitude of each index point after compensation.

[0098] Taking the mth harmonic as an example, the calculation formula for the precise frequency and amplitude of each index point after compensation is as follows:

[0099]

[0100] A0=βA m

[0101]

[0102] Where k is the corrected spectral line, A0 is the corrected amplitude, and Δf is the relative frequency resolution after zero padding.

[0103] Example 2

[0104] like Figure 2 As shown, this embodiment provides a harmonic measurement system based on self-compensating FFT, including:

[0105] The data acquisition and preprocessing module is used to discretely collect the current and voltage data signals of the power system and filter the collected data signals.

[0106] Let the sampling frequency be f s , then the frequency resolution is f s / N, the sampled data signal after filtering is expressed as follows:

[0107]

[0108] Where x(n) is the current and voltage discrete sampling data signal after filtering, n = 0, 1, 2..., N-1, h is the highest order of the added harmonic, A m is the amplitude of the mth harmonic, f m is the frequency of the mth harmonic, φ m is the phase of the mth harmonic.

[0109] The data windowing module is used to perform windowing processing on the filtered data signal to obtain a windowed discrete sampling data signal.

[0110] The formula for the windowed discrete sampling data signal is as follows:

[0111]

[0112] x w (n) = x(n)·w b-h (n)

[0113] Where w b-h (n) is the four-term Blackman-Harris window function.

[0114] The data zero-filling module is used to fill the windowed discrete sampling data signal with zeros to obtain a zero-filled data signal.

[0115] Zero-fill data signal x w0 The formula for (n) is as follows:

[0116]

[0117] Wherein, N0 is the data length after zero padding, N0 is greater than N and is an integer power of 2.

[0118] The self-compensation module is used to perform radix-2 FFT calculation on the zero-filled data signal and calculate the frequency compensation coefficient and amplitude compensation coefficient of each index point.

[0119] Fill the data signal x with zeros w0 (n) Perform a radix 2 FFT calculation to obtain the FFT result of the kth frequency point as follows:

[0120]

[0121] Where, X w0 (k) is the FFT result of the kth frequency point, j is the imaginary unit, is the basis function of FFT, and k represents the frequency index calculated by FFT;

[0122] The resulting frequency spectrum is:

[0123]

[0124] The amplitude spectrum is:

[0125]

[0126] Among them, f k is the frequency spectrum, A k is the amplitude spectrum.

[0127] The method for calculating the frequency compensation coefficient of each index point is as follows:

[0128] Taking the mth harmonic as an example, we select the spectrum line k m and its left and right spectral lines k m-1 、k m+1 , where spectral line k mThe amplitude is the largest, k m-1 =k m -1,k m+1 =k m +1;

[0129] The amplitudes of the corresponding spectral lines are A m-1 、A m 、A m+1 , the relationship among the three is A m-1 m >A m+1 , A m-1 and A m+1 The size relationship depends on the position of the spectrum line k0 of the real spectrum. m On the left or right side, if k0 is on the spectrum line k m On the left, then A m-1 >A m+1 , whereas A m-1 m+1 ;

[0130] The frequency compensation coefficient α is obtained by performing secondary interpolation on the amplitude information. The specific formula is as follows:

[0131]

[0132] The method for calculating the amplitude compensation coefficient of each index point is as follows:

[0133] According to the frequency compensation coefficient, the corrected frequency f0 is obtained, and then the spectrum line k is obtained. m Frequency correction δf0=f0-f m After calculating the hth harmonic, the amplitude compensation coefficient is obtained by fitting. The calculation formula of the amplitude compensation coefficient β is as follows:

[0134] β=g(δf0)

[0135] Where g(δf0) is the polynomial fitting formula, δf0 is the spectrum line k m Frequency correction amount.

[0136] The output module is used to output the precise frequency and amplitude of each index point after compensation.

[0137] Taking the mth harmonic as an example, the calculation formula for the precise frequency and amplitude of each index point after compensation is as follows:

[0138]

[0139] A0=βA m

[0140]

[0141] ​​Where k is the corrected spectral line, A0 is the corrected amplitude, and Δf is the relative frequency resolution after zero padding.

[0142] Experimental verification

[0143] Analyze the input power system harmonic signal, the input harmonic signal is:

[0144]

[0145] The test parameters are set as follows: fundamental frequency f1 is 50.2Hz, sampling frequency f s is 10000Hz, A m is the amplitude of each harmonic, φ m is the phase of each harmonic; the frequency and amplitude of each harmonic should be: f1=50.1Hz, A1=1V; f2=100.2Hz, A2=0.1V; f3=150.3Hz, A3=0.15V; f4=200.4Hz, A4=0.2V; f5=250.5Hz, A5=0.25V; f6=300.6Hz, A6=0.3V; f7=350.7Hz, A7=0.35V; f8=400.8Hz, A8=0.4V.

[0146] like Figure 3 and Figure 4 As shown in the figure, the frequency error and amplitude error comparison diagram of the method of the present invention and the FFT, windowed FFT and windowed zero-filled FFT methods are shown respectively; Figure 3 and Figure 4 The following results can be obtained: the method of the present invention can effectively and significantly improve the accuracy of harmonic frequency and amplitude measurement. While improving the measurement accuracy, the present invention does not make further requirements on the number of data sampling points and sampling frequency, so it has high applicability in engineering.

[0147] Compared with existing technologies, this invention achieves a reasonable allocation of sampling points and reduces storage pressure while achieving highly accurate output results. Windowing and zero-padding processes provide reliable solutions for insufficient sampling points, limited sampling frequency resolution, high host computer storage pressure, and spectrum leakage. Furthermore, a self-compensating correlation calculation between frequency and amplitude is performed on the processed data to obtain corrected frequency and amplitude values. This provides a high-precision algorithm with low operating cost and strong applicability for harmonic calculation in engineering applications.

[0148] Example 3

[0149] A device includes a memory and a processor, wherein the memory is used to store a program that supports the processor to execute the harmonic measurement method based on self-compensating FFT in embodiment 1, and the processor is configured to execute the program stored in the memory.

[0150] Example 4

[0151] A storage medium stores a computer program, which, when executed by a processor, executes the steps of the harmonic measurement method based on self-compensating FFT in embodiment 1.

[0152] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A harmonic measurement method based on self-compensating FFT, characterized in that: The following steps are involved: S1 selects the sampling frequency and number of sampling points, and discretely collects the current and voltage data signals of the N-point power system, which are recorded as , and collect N point data signals Perform filtering processing; S2 N-point data signal obtained based on filtering , select the window function to perform windowing processing, and obtain the N-point discrete sampling data signal after windowing (n); S3 is the N-point discrete sampling data signal after windowing (n) is padded with zeros, and we get Zero-fill data signal (n); S4 fills the data signal with zeros (n) performing radix-2 FFT calculation to obtain the frequency spectrum and amplitude spectrum of the data signal; S5 searches for amplitude information greater than a set threshold based on the amplitude spectrum, and obtains the frequency compensation coefficient of each index point by combining the amplitude peak and the amplitude of its adjacent spectrum lines; S6 performs fitting calculation based on the obtained frequency compensation coefficient of each index point to obtain the amplitude compensation coefficient of each index point; S7 calculates the precise frequency and amplitude of each index point after compensation based on the obtained frequency compensation coefficient and amplitude compensation coefficient of each index point.

2. The harmonic measurement method based on self-compensating FFT according to claim 1, characterized in that: The method for searching for amplitude information greater than a set threshold based on the amplitude spectrum is as follows: for the mth harmonic, select the spectrum line and its left and right spectral lines 、 , where the spectral line The amplitude is the largest, = -1, = +1; the amplitudes of the corresponding spectral lines are 、 、 The relationship among the three is , and The size relationship depends on the spectral lines of the real spectrum The position of the spectrum The left or right side, if On the spectrum On the left, > ,on the contrary .

3. The harmonic measurement method based on self-compensating FFT according to claim 2, characterized in that: The frequency compensation coefficient is obtained by performing secondary interpolation on the amplitude information, and its calculation formula is as follows: in, is the frequency compensation coefficient.

4. The harmonic measurement method based on self-compensating FFT according to claim 3, characterized in that: The calculation method of the amplitude compensation coefficient is as follows: the corrected frequency is obtained according to the frequency compensation coefficient, and then the spectrum line is obtained. The frequency correction amount is taken as the value, and after calculating the hth harmonic, the amplitude compensation coefficient is obtained by fitting.

5. The harmonic measurement method based on self-compensating FFT according to claim 4, characterized in that: The calculation formula of the amplitude compensation coefficient is as follows: Where, is the amplitude compensation coefficient, is the polynomial fitting formula, spectral lines Frequency correction amount.

6. The harmonic measurement method based on self-compensating FFT according to claim 5, characterized in that: The calculation formula for the exact frequency and amplitude of each index point after compensation is as follows: Where k is the corrected spectral line, is the corrected amplitude, is the relative frequency resolution after zero padding.

7. A harmonic measurement system based on the harmonic measurement method based on self-compensating FFT according to any one of claims 1 to 6, characterized in that: include: The data acquisition and preprocessing module is used to discretely collect the current and voltage data signals of the power system and filter the collected data signals; A data windowing module is used to perform windowing processing on the filtered data signal to obtain a windowed discrete sampling data signal; A data zero-filling module is used to fill the windowed discrete sampling data signal with zeros to obtain a zero-filled data signal; A self-compensation module is used to perform radix-2 FFT calculation on the zero-filled data signal and calculate the frequency compensation coefficient and amplitude compensation coefficient of each index point; The output module is used to output the precise frequency and amplitude of each index point after compensation.

8. The harmonic measurement system according to claim 7, characterized in that: The method for calculating the frequency compensation coefficient and amplitude compensation coefficient of each index point is as follows: 1) Search for amplitude information greater than a set threshold based on the amplitude spectrum; 2) Obtain the frequency compensation coefficient by performing secondary interpolation through the amplitude information; 3) Obtain the corrected frequency based on the frequency compensation coefficient, and then obtain the spectrum line The frequency correction amount is taken as the value, and after calculating the hth harmonic, the amplitude compensation coefficient is obtained by fitting.

9. The harmonic measurement system according to claim 8, characterized in that: The method for searching for amplitude information greater than a set threshold based on the amplitude spectrum is as follows: for the mth harmonic, select the spectrum line and its left and right spectral lines 、 , where the spectral line The amplitude is the largest, = -1, = +1; the amplitudes of the corresponding spectral lines are 、 、 The relationship among the three is , and The size relationship depends on the spectral lines of the real spectrum The position of the spectrum The left or right side, if On the spectrum On the left, > ,on the contrary .

10. The harmonic measurement system according to claim 9, characterized in that: The calculation formula of the frequency compensation coefficient is as follows: in, is the frequency compensation coefficient.

11. The harmonic measurement system according to claim 10, characterized in that: The calculation formula of the amplitude compensation coefficient is as follows: Where, is the amplitude compensation coefficient, is the polynomial fitting formula, spectral lines Frequency correction amount.

12. The harmonic measurement system according to claim 11, characterized in that: The calculation formula for the exact frequency and amplitude of each index point after compensation is as follows: Where k is the corrected spectral line, is the corrected amplitude, is the relative frequency resolution after zero padding.

13. A device comprising a memory and a processor, characterized in that: The memory is used to store a program that supports the processor to execute the harmonic measurement method based on self-compensating FFT according to any one of claims 1 to 6, and the processor is configured to execute the program stored in the memory.

14. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the harmonic measurement method based on self-compensating FFT according to any one of claims 1 to 6 are executed.

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