An adaptive broadband measurement method and system suitable for distribution automation terminals

Abstract

An adaptive broadband measurement method and system for distribution automation terminals includes a windowed FFT calculation, followed by coarse frequency determination and dense spectrum judgment based on spectrum amplitude, followed by a windowed ZoomFFT calculation under dense spectrum conditions, followed by multi-spectral line interpolation, and finally, spectrum sorting to extract the broadband frequency components of the electrical quantity to be measured, along with their corresponding amplitudes and phases. The method adaptively changes the frequency resolution based on the spectral characteristics of the electrical quantity to achieve detection of dense harmonics and interharmonics while reducing computational overhead and providing excellent engineering value.

Description

Technical Field

[0001] The present invention relates to the technical field of measurement methods, and more particularly to an adaptive broadband measurement method and system applicable to a distribution automation terminal. Background Art

[0002] With the increasing maturity of renewable energy technologies and the accelerating intelligence of power grids, power systems are facing a series of challenges brought about by the "dual highs" of both renewable energy and power electronic devices. While the proliferation of power electronic devices enhances the control and maintenance capabilities of the power grid, it also introduces a significant number of harmonics and interharmonics, leading to broadband signals in the grid. These numerous broadband components not only impact power quality but also significantly impact traditional relay protection. The short-circuit current provided by the power supply through the converter covers a wider frequency band, potentially causing the transformer's longitudinal differential protection, which relies on low-order harmonic braking, to fail.

[0003] Accurately measuring broadband signal components is crucial to the safety and stability of power systems, benefiting subsequent applications such as broadband operating status tracking and oscillation monitoring, broadband parameter identification, broadband disturbance location, high-precision power quality assessment, and arc high-resistance fault identification. Currently, most measurement devices measure only the power frequency and harmonics up to the 20th order, with a frequency resolution of 5Hz or higher, which falls short of broadband measurement requirements. Currently, broadband measurement typically requires measuring signals in the 0-2500Hz range with a frequency resolution of 1Hz.

[0004] The Fast Fourier Transform (FFT) is widely used in power system measurements due to its low computational complexity and ease of embedded code implementation. Combining various windowed FFTs with spectral line interpolation correction algorithms can achieve measurement accuracies generally exceeding 10⁻⁵. However, due to the inherent mainlobe width of the window function, signals with similar frequencies can affect each other. According to the sampling theorem, increasing frequency resolution requires more data points. Longer sequences increase computational complexity, even making them impractical for engineering applications. To meet the high-precision, high-resolution, and relatively low-computation requirements of distribution automation terminals for broadband measurements, research on relevant algorithms is essential. Summary of the Invention

[0005] To address the deficiencies in the prior art, the present invention provides a method and system for adaptive broadband measurement of distribution automation terminals, providing an effective algorithm solution for broadband measurement with high measurement accuracy, high frequency resolution and low computational complexity.

[0006] The present invention adopts the following technical solutions. A first aspect of the present invention provides an adaptive broadband measurement method applicable to a distribution automation terminal, comprising the following steps:

[0007] Perform windowed FFT calculation on the collected electrical quantities to obtain the frequency spectrum of the windowed FFT of the electrical quantities;

[0008] Based on the maximum amplitude spectrum line position of the electrical quantity windowed FFT spectrum, the coarse frequency is determined, and whether there is a dense spectrum near the coarse frequency is judged;

[0009] If there is a dense spectrum, based on the spectral line position of the dense spectrum, the starting frequency and cutoff frequency of the bandpass filter are refined, and the collected electrical quantity is calculated by windowing ZoomFFT to obtain the spectrum of the electrical quantity windowing ZoomFFT, and multi-spectral line interpolation calculation is performed;

[0010] If there is no dense spectrum, perform multi-spectral line interpolation calculation on the spectrum of the windowed FFT of the electrical quantity;

[0011] Spectrum sorting extracts the broadband frequency components of the electrical quantity to be measured and their corresponding amplitudes and phases.

[0012] Preferably, performing windowed FFT calculation on the collected electrical quantity to obtain a frequency spectrum of the windowed FFT of the electrical quantity specifically includes:

[0013] At the set sampling frequency Discrete sampling of electrical quantities is performed to obtain Sampling data points are cached to form the first cache sequence ;

[0014] The first buffer sequence is processed by window function The cached data points in the buffer are windowed and truncated to obtain the windowed discrete sampling data, which is cached to form the second buffer sequence ;

[0015] The second buffer sequence containing the windowed discrete sampling data After performing FFT transformation, the influence of the side lobes at the negative frequency points is ignored, and the spectrum of the electrical quantity windowed FFT is obtained.

[0016] Preferably, determining the coarse frequency based on the maximum amplitude line position of the spectrum of the electrical quantity windowed FFT and judging whether there is a dense spectrum near the coarse frequency specifically includes:

[0017] The frequency corresponding to the maximum amplitude spectral line position in the frequency spectrum of the electrical quantity windowed FFT is determined as the coarse frequency, and the amplitudes of the maximum amplitude spectral line position and the preceding and succeeding spectral line positions are obtained;

[0018] The amplitude ratio of adjacent spectral line positions is compared with the pre-stored value, and whether there is a dense spectrum is determined based on whether the difference is less than the threshold value.

[0019] Preferably, comparing the amplitude ratio of adjacent spectral line positions with a pre-stored value and determining whether a dense spectrum exists based on whether the difference is less than a threshold value specifically includes:

[0020] by Indicates the position of the spectrum line Spectral line position with the real spectrum The deviation between them is the ratio of the spectrum response of the Hanning window at different frequencies stored in advance: 、 , , and pre-stored in the global array, the criterion of whether it contains a dense spectrum is constructed by comparing the amplitude ratio, which is expressed as the following formula (1):

[0021]

[0022] Where:

[0023] The position of the spectral line before the maximum amplitude spectral line position The amplitude of The maximum amplitude line The amplitude of the position, The position of the next spectral line after the maximum amplitude spectral line The amplitude of The threshold value to be set.

[0024] Preferably, the refining of the starting frequency and the cutoff frequency of the bandpass filter based on the position of the spectral line where the dense spectrum exists specifically includes:

[0025] The spectral line position of the spectrum amplitude maximum is taken, the first spectrum amplitude maximum is used to refine the start frequency, and the last spectrum amplitude maximum is used to refine the cutoff frequency.

[0026] Preferably, the starting frequency of the refinement and cutoff frequency The value is expressed as follows:

[0027]

[0028] Where:

[0029] 、 are the maximum and minimum spectral line positions where there is a dense spectrum, To refine the passband frequency offset, The length of the sequence calculated for the FFT transform.

[0030] Preferably, performing a windowed ZoomFFT calculation on the collected electrical quantity to obtain a frequency spectrum of the windowed ZoomFFT of the electrical quantity specifically includes:

[0031] At the set sampling frequency Discrete sampling of electrical quantities is performed to obtain Sampling data points are cached to form the third cache sequence , and perform complex modulation frequency shift on it to form the fourth cache sequence , which is expressed as follows:

[0032]

[0033] Where: represents the fourth cache sequence; Indicates the fourth cache sequence The cached data points, which are discrete data points after complex modulation frequency shift; 、 are the determined refinement starting frequency and cutoff frequency respectively; represents the frequency zero point of the signal represented by the fourth cache sequence;

[0034] For discrete data points containing complex modulation frequency shift The fourth cache sequence Perform FFT transformation, filter in the frequency domain, and retain The spectrum within the range, other spectral lines are set to zero, and the filtered spectrum is obtained ;

[0035] For length The filtered spectrum of Perform IFFT and get the length The first time domain signal is sampled by a fifth buffer sequence representing the first time domain signal. Take one point, so that the length can be The resampled second time domain signal is subjected to a windowed FFT transform to obtain a resampled spectrum. , the frequency resolution corresponding to the frequency domain is / .

[0036] Preferably, the performing of multi-spectral line interpolation calculation specifically includes:

[0037] The amplitudes of three spectral lines with large information content near the maximum value in the spectrum of the electrical quantity windowed FFT or the spectrum of the electrical quantity windowed ZoomFFT are selected for interpolation correction, which can be expressed as the following formulas (5) and (6):

[0038]

[0039] Where:

[0040] The position of the spectral line before the maximum amplitude spectral line position The amplitude of The maximum amplitude line The amplitude of the position, The position of the next spectral line after the maximum amplitude spectral line The amplitude of Indicates the true spectral line position and the position of the maximum amplitude line Deviation between Indicates the ratio relationship between the maximum amplitude spectral line and its previous and next spectral lines;

[0041] Fitting to polynomial The coefficients of are used to obtain the correction formulas for amplitude, frequency and phase, which are expressed as follows:

[0042]

[0043] Where:

[0044] is the spectral line position of the true frequency, is the frequency resolution, is the calculated frequency of dense spectrum signal and non-dense spectrum signal after frequency shift, is the amplitude of the dense spectrum signal and the non-dense spectrum signal after the calculated frequency shift, is the phase of the calculated dense spectrum signal and non-dense spectrum signal after frequency shift.

[0045] Preferably, the spectrum sorting and extraction of the broadband frequency components of the electrical quantity to be measured and their corresponding amplitudes and phases specifically include:

[0046] The frequency adjustment is performed as shown in the following formula (10):

[0047]

[0048] Where:

[0049] is the actual dense spectrum signal frequency, is the frequency shift of the dense spectrum, is the frequency of the frequency-shifted dense spectrum calculation, is the sampling frequency.

[0050] The second aspect of the present invention provides an adaptive broadband measurement system suitable for distribution automation terminals, which runs the adaptive broadband measurement method suitable for distribution automation terminals described in the first aspect, including: a windowed FFT calculation module, a dense spectrum judgment module, a windowed ZoomFFT calculation module, a multi-spectral line interpolation calculation module, and an electrical quantity broadband component extraction module; the windowed FFT calculation module is used to perform windowed FFT calculations on the collected electrical quantities; the dense spectrum judgment module is used to determine the dense spectrum based on the spectrum amplitude to determine the coarse frequency; the windowed ZoomFFT calculation module is used for windowed ZoomFFT calculations under dense spectrum conditions; the multi-spectral line interpolation calculation module is used for multi-spectral line interpolation fitting to calculate the electrical quantity amplitude, frequency and phase; the electrical quantity broadband component extraction module is used to sort the spectrum to extract the broadband frequency components of the electrical quantities to be measured and their corresponding amplitudes and phases.

[0051] The third aspect of the present invention provides an electronic device, comprising: a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus; the memory is used to store computer programs; the processor is used to execute the computer programs stored in the memory, and when the computer program is loaded into the processor, it implements the adaptive broadband measurement method applicable to distribution automation terminals according to the first aspect.

[0052] A fourth aspect of the present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the adaptive broadband measurement method applicable to distribution automation terminals described in the first aspect.

[0053] Compared with the prior art, the beneficial effects of the present invention include at least the following: the present invention provides a method and system for adaptive broadband measurement applicable to distribution automation terminals, which adaptively switches whether frequency refinement is required based on the signal contained in the electrical quantity, thereby reducing the amount of computation; when a dense spectrum exists, high-frequency resolution recognition is achieved through the ZoomFFT algorithm; and the ZoomFFT and windowed FFT spectrum lines are corrected separately using a multi-spectral line interpolation correction algorithm, thereby improving the accuracy of broadband measurement. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 It is a flow chart of an adaptive broadband measurement method applicable to distribution automation terminals;

[0055] Figure 2 This is a schematic diagram of an adaptive broadband measurement system applicable to distribution automation terminals of the present invention;

[0056] Figure 3 It is the Hanning window FFT spectrum and local magnification;

[0057] Figure 4Spectral distribution diagram of different algorithms under dense spectrum. DETAILED DESCRIPTION

[0058] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. The described embodiments are only part of the embodiments of the present invention, not all of them. Based on the spirit of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts are within the scope of protection of the present invention.

[0059] Embodiment 1 of the present invention provides an adaptive broadband measurement method applicable to a distribution automation terminal, such as Figure 1 As shown, the following steps are included:

[0060] Step 1: Perform windowed FFT calculation on the collected electrical quantity to obtain the frequency spectrum of the windowed FFT of the electrical quantity.

[0061] Step 1 specifically includes:

[0062] Step 1.1: Set the sampling frequency Discrete sampling of electrical quantities is performed to obtain Sampling data points are cached to form the first cache sequence , which is expressed as the following formula (11):

[0063]

[0064] Where:

[0065] Represents the first cache sequence;

[0066] Indicates the first cache sequence cached data points;

[0067] Indicates the length of the cached data in the first cache sequence.

[0068] Step 1.2: Window the first buffer sequence The cached data points in the buffer are windowed and truncated to obtain the windowed discrete sampling data, which is cached to form the second buffer sequence The window function is preferably but not limited to the Hanning window; specifically, it is expressed as follows (12) and (13):

[0069]

[0070] Where:

[0071] represents the second cache sequence;

[0072] is the Hanning window function;

[0073] is the discrete sampling data after windowing.

[0074] Step 1.3: Contains the discrete sampling data after windowing The second cache sequence After performing FFT transformation, ignoring the influence of the side lobes at the negative frequency points, the spectrum of the electrical quantity windowed FFT is obtained, which is expressed as the following formula (14):

[0075]

[0076] Where:

[0077] The spectrum of the windowed FFT of the electrical quantity,

[0078] Indicates the subharmonics, is the spectral line position of the real spectrum;

[0079] Indicates the position of the spectrum line Spectral line position with the real spectrum Deviation between

[0080] For the The amplitude of the subharmonics, For the Phase of subharmonics;

[0081] is the imaginary unit, is the base of natural logarithms;

[0082] W (·) is the spectral response of the Hanning window.

[0083] Step 2: Spectrum of electrical quantity windowed FFT The maximum amplitude spectrum line position is used to determine the coarse frequency and determine whether a dense spectrum exists. If a dense spectrum exists, proceed to step 3; if not, proceed to step 4.

[0084] Step 2 specifically includes:

[0085] Step 2.1: Window the FFT spectrum of the electrical quantity The maximum amplitude line position The corresponding frequency is determined as the coarse frequency , and obtain the amplitudes of the maximum amplitude spectral line position and its previous and next spectral line positions.

[0086] It is worth noting that according to the principle that time domain point multiplication is equivalent to frequency domain convolution, the spectrum lines obtained by FFT calculation represent frequencies. Generally, integers are used to represent frequency positions. Multiplying by the frequency resolution can convert the frequency corresponding to the spectrum line. If the spectrum of the electrical quantity windowed FFT is The real spectrum contained in There must be a maximum amplitude spectral line position , the deviation between the two is Between, as shown in the following formula (15):

[0087]

[0088] Where:

[0089] Indicates the deviation between the spectral line position of the true spectrum and the spectral line position of the maximum amplitude;

[0090] is the position of the maximum amplitude spectral line;

[0091] is the spectral line position of the real spectrum.

[0092] Spectrum distribution after FFT transformation It must be the maximum value position, so we can first locate the coarse frequency components contained in the electrical quantity based on this characteristic, that is, That is, the steps of determining the coarse frequency include: obtaining the frequency spectrum of the electrical quantity windowed FFT Maximum amplitude line position , the maximum amplitude line position The corresponding frequency is determined as the coarse frequency .

[0093] The position of the spectrum line before and after the maximum amplitude spectrum line after FFT transformation is expressed by the following formula (16):

[0094]

[0095] Where:

[0096] Indicates the position of the previous spectral line with the maximum amplitude;

[0097] Indicates the position of the maximum amplitude spectral line;

[0098] Indicates the position of the spectral line following the position of the spectral line with the maximum amplitude.

[0099] The previous spectral line position of the maximum amplitude spectral line position is obtained The amplitude at , the position of the maximum amplitude spectral line The amplitude at and the next spectral line position after the maximum amplitude spectral line position The amplitude at .

[0100] Step 2.2: Compare the amplitude ratio of adjacent spectral line positions with the pre-stored value, and determine whether there is a dense spectrum based on whether the difference is less than the threshold value.

[0101] According to the spectrum of windowed FFT Hanning window spectrum term in the expression , pre-store the ratio of the Hanning window's spectrum response at different frequencies: 、 , On the basis of determining the coarse frequency, it is judged whether the ratio of the maximum spectral line amplitude to the amplitudes of the spectral lines before and after it meets the ratio of the spectrum response of the pre-stored Hanning window at different frequencies. If so, it is determined that the electrical quantity does not contain a dense spectrum, otherwise the electrical quantity contains a dense spectrum.

[0102] It is understandable that Represents the meaning of the spectral line position Spectral line position with the real spectrum The deviation between This means that by refining Ask for multiple groups 、 , , and pre-stored in the global array, the criterion of whether it contains a dense spectrum is constructed by comparing the amplitude ratio, which is expressed as the following formula (17):

[0103]

[0104] Where:

[0105] for The amplitude of the position spectrum line, for The amplitude of the position spectrum line, for The amplitude of the position spectrum line;

[0106] The threshold value to be set.

[0107] Step 2.3: If there is a dense spectrum, proceed to step 3. If there is no dense spectrum, proceed to step 4. That is, if / Approximately equal to / and / Approximately equal to / If there is no dense spectrum, proceed to step 4; otherwise, if there is a dense spectrum, proceed to step 3.

[0108] It is understandable that only the maximum amplitude line position This is an example explanation. After FFT transformation, there may be multiple maxima in the spectrum distribution. For the spectral line position of each maximum value, the above-mentioned dense spectrum criterion is used to determine whether there is a dense spectrum, and the spectral line position where the dense spectrum exists is obtained.

[0109] Step 3: Under the dense spectrum condition, based on the spectral line position of the dense spectrum, refine the starting frequency and cutoff frequency of the bandpass filter, perform windowed ZoomFFT calculation on the collected electrical quantity, and obtain the frequency spectrum of the windowed ZoomFFT of the electrical quantity.

[0110] Step 3 specifically includes:

[0111] Step 3.1: Refine the starting frequency based on the first and last two spectral line positions with dense spectra and cutoff frequency , for example but not limited to, in step 2, determine 、 、 ( < < ) There are dense spectra at these three places, so use To determine the starting frequency of the bandpass filter, To determine the cutoff frequency of the bandpass filter, and then determine the spectrum range that needs to be refined, the starting frequency of the refinement and cutoff frequency The value is expressed as follows:

[0112]

[0113] Where:

[0114] 、 are the maximum and minimum spectral line positions where there is a dense spectrum,

[0115] To refine the bandpass frequency offset, according to The size of is appropriately selected, preferably but not limited to, , is the sampling frequency,

[0116] The length of the sequence calculated for the FFT transform.

[0117] It is worth noting that the bandpass filtering in step 3.1 adopts time-complex modulation analysis, and the starting frequency Not less than 0, if f 2 is less than 5Hz, the bandpass filter becomes a low-pass filter.

[0118] Step 3.2: Set the sampling frequency Discrete sampling of electrical quantities is performed to obtain The sampling data points are cached to form a third cache sequence, which is expressed as the following formula (19):

[0119]

[0120] Where:

[0121] represents the third cache sequence;

[0122] Indicates the third cache sequence The cached data points;

[0123] Indicates the refinement factor;

[0124] Indicates the third cache sequence The length of the cached data in .

[0125] Step 3.3: The length of the cached data is The third cache sequence Perform complex modulation frequency shift to form the fourth cache sequence , which is expressed as follows:

[0126]

[0127] Where:

[0128] represents the fourth cache sequence;

[0129] Indicates the fourth cache sequence The cached data points, i.e., discrete data points after complex modulation frequency shift;

[0130] 、 They correspond to the determined refined starting frequency and cutoff frequency respectively;

[0131] Indicates the frequency zero point of the signal represented by the fourth cache sequence.

[0132] Step 3.4: Contains the discrete data points after complex modulation frequency shift The fourth cache sequence Perform FFT transformation, filter in the frequency domain, and retain The spectrum within the range, other spectral lines are set to zero, and the filtered spectrum is obtained , which can remove frequencies outside the frequency band to be refined and avoid spectrum aliasing caused by subsequent resampling;

[0133] Step 3.5: For length The filtered spectrum of Perform IFFT (Inverse Fast Fourier Transform) to obtain a length of The first time domain signal is expressed as follows:

[0134]

[0135] Where:

[0136] Represents the fifth cache sequence, representing the length The first time domain signal;

[0137] represents the cached data points of the fifth cache sequence, i.e., the discrete data points after complex modulation frequency shift;

[0138] Indicates IFFT operation.

[0139] Step 3.6: Sample the fifth buffer sequence representing the first time domain signal. Take one point, so that the length can be The second time domain signal is expressed as follows:

[0140]

[0141] Where:

[0142] Represents the sixth cache sequence, representing the length A second time domain signal;

[0143] represents a cached data point of a sixth cache sequence, i.e., a discrete data point after sampling;

[0144] Indicates the fifth cache sequence Every Take a sample from each point;

[0145] It can be understood that the sampling frequency of the second time domain signal is equivalent to / .

[0146] Step 3.7: Perform windowed FFT transformation on the resampled second time domain signal to obtain the resampled spectrum , the frequency resolution corresponding to the frequency domain is / , the frequency resolution is improved times.

[0147] It is worth noting that the resampling of the electrical quantity in step 3 does not require interpolation, but is a point-to-point frequency reduction, which reduces the sampling frequency. Here, it is necessary to consider that after reducing the sampling frequency, the signal in the original signal that is higher than 1 / 2 of the resampling frequency cannot interfere with the resampling.

[0148] Step 4: If there is no dense spectrum, perform multi-spectral line interpolation calculation on the spectrum of the electrical quantity windowed FFT; if there is a dense spectrum, perform multi-spectral line interpolation calculation on the spectrum of the electrical quantity windowed ZoomFFT obtained in step 3; sort the spectrum to extract the broadband frequency components of the electrical quantity to be measured and their corresponding amplitudes and phases.

[0149] Step 4 specifically includes:

[0150] Since the main lobe width of the Hanning window is narrow, the amplitudes of three spectral lines with large information content near the maximum value in the spectrum of the electrical quantity windowed FFT or the spectrum of the electrical quantity windowed ZoomFFT are used for interpolation correction, including Amplitude of the position spectrum line , Amplitude of the position spectrum line and Amplitude of the position spectrum line , which is expressed as follows:

[0151]

[0152] Where:

[0153] Indicates the true spectral line position and the position of the maximum amplitude line Deviation between

[0154] It represents the ratio of the maximum amplitude spectral line and its previous and next spectral lines.

[0155] It is worth noting that both dense spectrum and non-dense spectrum are processed by windowed FFT. For windowed FFT, the input data length is configurable, and the output only needs to know the sampling frequency and data length in advance. The sampling frequency of the present invention is unchanged, but the sampling length of the dense spectrum signal will be expanded after the dense spectrum is identified. This is also the explanation for using complex modulation analysis (corresponding to bandpass filtering + frequency shifting) to extract the dense spectrum. Therefore, in step 4, the spectrum of the electrical quantity windowed ZoomFFT is Spectrum of the windowed FFT of the sum electrical quantity They are all inputs, and the corresponding modules are the same.

[0156] The polynomial fitting function polyfit can be used to obtain the polynomial The coefficients of , from which the correction formulas for amplitude, frequency and phase can be obtained, expressed as the following formulas (26) to (28):

[0157]

[0158] Where:

[0159] is the spectral line position of the true frequency;

[0160] is the frequency resolution;

[0161] The frequencies of the dense spectrum signal and the non-dense spectrum signal after the calculated frequency shift;

[0162] is the amplitude of the dense spectrum signal and the non-dense spectrum signal after the calculated frequency shift;

[0163] is the phase of the calculated dense spectrum signal and non-dense spectrum signal after frequency shift.

[0164] Further in a preferred but non-limiting embodiment, when When it is greater than 1000, function A is expressed as follows:

[0165]

[0166] Where:

[0167] The fitting function between the spectral line position and amplitude after the window function is fixed;

[0168] It is the reciprocal of the data window length after zero padding.

[0169] In a preferred but non-limiting embodiment, since ZoomFFT performs complex modulation frequency shift, the final calculated frequency needs to be frequency adjusted, as expressed by the following formula (30):

[0170]

[0171] Where:

[0172] is the actual dense spectrum signal frequency;

[0173] is the frequency shift of the dense spectrum;

[0174] The frequencies calculated for the frequency-shifted dense spectrum;

[0175] is the sampling frequency.

[0176] After adjusting the frequency in the presence of a dense spectrum, the frequency data calculated in the non-dense spectrum segment is sorted and the broadband frequency components of the electrical quantity to be measured and their corresponding amplitudes and phases are extracted.

[0177] Embodiment 2 of the present invention provides an adaptive broadband measurement system applicable to a distribution automation terminal, based on the adaptive broadband measurement method applicable to a distribution automation terminal, such as Figure 2 Shown, including:

[0178] Windowed FFT calculation module, dense spectrum judgment module, windowed ZoomFFT calculation module, multi-spectral line interpolation calculation module, electrical quantity wide-band component extraction module;

[0179] The windowed FFT calculation module is used to perform windowed FFT calculations on the collected electrical quantities; the dense spectrum judgment module is used to determine the coarse frequency judgment of the dense spectrum based on the spectrum amplitude; the windowed ZoomFFT calculation module is used for windowed ZoomFFT calculations under dense spectrum conditions; the multi-spectral line interpolation calculation module is used for multi-spectral line interpolation fitting to calculate the electrical quantity amplitude, frequency and phase; the electrical quantity wide-band component extraction module is used for spectrum sorting to extract the wide-band frequency components of the electrical quantities to be measured and their corresponding amplitude and phase.

[0180] Embodiment 3 of the present invention provides an electronic device for an adaptive broadband measurement method applicable to a distribution automation terminal, and runs the adaptive broadband measurement method applicable to a distribution automation terminal:

[0181] It includes a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus;

[0182] Memory for storing computer programs;

[0183] The processor is configured to execute a program stored in the memory to implement the steps of the adaptive broadband measurement method applicable to a distribution automation terminal.

[0184] Embodiment 4 of the present invention provides a computer-readable storage medium having a computer program stored thereon. When the program is executed by a processor, the adaptive broadband measurement method applicable to a distribution automation terminal is implemented.

[0185] In order to more clearly introduce the outstanding essential features of the present invention and the significant progress it brings to the existing technology, a simulation comparison method is adopted to process the same simulation signal using the existing technology method and the method of the present invention respectively, thereby verifying the beneficial technical effect of the present invention in improving the broadband measurement accuracy.

[0186] Specifically, the simulation comparison method and the power system harmonic signal are used for analysis, and the applied simulation harmonic model is expressed as follows:

[0187]

[0188] Perform windowed FFT calculation on the above simulation, taking 4096 points, Figure 3 The calculated spectrum distribution diagram shows that the frequencies are mainly distributed at 21.875Hz, 51.5625Hz, 192.1875Hz, and 2500Hz. After multi-spectral line interpolation correction calculation, the corresponding frequencies and amplitudes are shown in Table 1:

[0189] Table 1 Frequencies and amplitudes obtained by multi-spectral interpolation correction using existing technology

[0190]

[0191] from Figure 3 The local magnified image shows that the spectrum line near 192.1875Hz is abnormal. By comparing the ratio of the spectrum response of the pre-stored Hanning window at different frequencies, it can be determined that there is a dense spectrum near 192.1875Hz. ZoomFFT is used to refine the spectrum, and windowing and multi-spectral line interpolation correction are performed. The distribution of the spectrum lines is shown in the following figure when the Hanning window FFT and single ZoomFFT algorithms are added without refinement. Figure 4 As shown in Table 2, the final calculation results of the algorithm proposed in this invention are as follows:

[0192] Table 2 Frequency and amplitude calculated using the algorithm provided by the present invention

[0193]

[0194] The beneficial effects of the present invention are that, compared with the prior art, the present invention provides a method and system for adaptive broadband measurement applicable to distribution automation terminals, which adaptively switches whether frequency refinement is required according to the signal contained in the electrical quantity, thereby reducing the amount of computation; when a dense spectrum exists, high-frequency resolution recognition is achieved through the ZoomFFT algorithm; and the ZoomFFT and windowed FFT spectrum lines are corrected separately using a multi-spectral line interpolation correction algorithm, thereby improving the accuracy of broadband measurement.

[0195] Furthermore, compared with the prior art, the present invention provides a novel main lobe interference judgment method. The present invention uses the window function spectrum ratio relationship as the basis to identify the interference spectrum, which has better anti-interference ability than the prior art using phase difference. Based on this outstanding substantial feature, the significant progress brought by the present invention to the prior art includes at least strong anti-interference of dense spectrum recognition and low coupling with threshold setting.

[0196] In addition, compared with the existing technology, the present invention pre-stores the window function spectrum amplitude ratio for identifying dense spectra, then expands the sampling length after band-pass filtering, and finally performs windowed FFT again to calculate the frequency, amplitude, and phase angle; based on this outstanding substantial feature, the present invention brings significant improvements to the existing technology, including at least less calculation amount for dense spectrum identification, less interference in the low-frequency band of resampled data, and higher accuracy of signal frequency, amplitude, and phase angle obtained by re-windowing FFT calculation after refinement.

[0197] The present invention may be a system, a method and / or a computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for causing a processor to implement various aspects of the present disclosure.

[0198] It should be noted that, in the present invention, relational terms such as first and second, etc. are merely used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply the existence of any such actual relationship or order between these entities or operations. In addition, the terms "comprises," "comprising," or any other variations are intended to cover non-exclusive inclusion, so that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further restrictions, an element defined by the statement "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or device comprising the element.

[0199] Each embodiment in this specification is described in a related manner. Similar parts between the various embodiments can be referred to in conjunction with each other. Each embodiment focuses on the differences between the other embodiments. In particular, the system embodiment is generally similar to the method embodiment, so the description is relatively simple. For related parts, refer to the description of the method embodiment.

[0200] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered by the scope of protection of the claims of the present invention.

Claims

1. An adaptive broadband measurement method applicable to distribution automation terminals, characterized in that: The following steps are involved: Perform windowed FFT calculation on the collected electrical quantities to obtain the frequency spectrum of the windowed FFT of the electrical quantities; Based on the maximum amplitude line position of the spectrum of the electrical quantity windowed FFT, the coarse frequency is determined, and whether there is a dense spectrum near the coarse frequency is judged, including: determining the frequency corresponding to the maximum amplitude line position in the spectrum of the electrical quantity windowed FFT as the coarse frequency, and obtaining the amplitude of the maximum amplitude line position and the previous and next spectrum line positions; comparing the amplitude ratio of adjacent spectrum line positions with a pre-stored value, and judging whether there is a dense spectrum according to whether the difference is less than a threshold value; wherein, Indicates the position of the spectrum line Spectral line position with the real spectrum The deviation between them is the ratio of the spectrum response of the Hanning window at different frequencies stored in advance: 、 , , and pre-stored in the global array, the criterion of whether it contains a dense spectrum is constructed by comparing the amplitude ratio, which is expressed as the following formula (1): Where: The position of the spectral line before the maximum amplitude spectral line position The amplitude of The maximum amplitude line The amplitude of the position, The position of the next spectral line after the maximum amplitude spectral line The amplitude of is the threshold value set; W (·) is the spectral response of the Hanning window; If there is a dense spectrum, based on the spectral line position of the dense spectrum, the starting frequency and cutoff frequency of the bandpass filter are refined, and the collected electrical quantity is calculated by windowing ZoomFFT to obtain the spectrum of the electrical quantity windowing ZoomFFT, and multi-spectral line interpolation calculation is performed; If there is no dense spectrum, perform multi-spectral line interpolation calculation on the spectrum of the windowed FFT of the electrical quantity; Spectrum sorting extracts the broadband frequency components of the electrical quantity to be measured and their corresponding amplitudes and phases.

2. The adaptive broadband measurement method applicable to a distribution automation terminal according to claim 1, characterized in that: The windowed FFT calculation of the collected electrical quantity to obtain the frequency spectrum of the windowed FFT of the electrical quantity specifically includes: At the set sampling frequency Discrete sampling of electrical quantities is performed to obtain Sampling data points are cached to form the first cache sequence ; The first buffer sequence is processed by window function The cached data points in the buffer are windowed and truncated to obtain the windowed discrete sampling data, which is cached to form the second buffer sequence ; The second buffer sequence containing the windowed discrete sampling data After performing FFT transformation, the influence of the side lobes at the negative frequency points is ignored, and the spectrum of the electrical quantity windowed FFT is obtained.

3. The adaptive broadband measurement method applicable to a distribution automation terminal according to claim 1, characterized in that: The refining of the start frequency and the cutoff frequency of the bandpass filter based on the position of the spectral line of the dense spectrum specifically includes: The spectral line position of the spectrum amplitude maximum is taken, the first spectrum amplitude maximum is used to refine the start frequency, and the last spectrum amplitude maximum is used to refine the cutoff frequency.

4. The adaptive broadband measurement method applicable to a distribution automation terminal according to claim 3, characterized in that: Refined starting frequency and cutoff frequency The value is expressed as follows: Where: 、 are the maximum and minimum spectral line positions where there is a dense spectrum, To refine the passband frequency offset, The length of the sequence calculated for the FFT transform.

5. The adaptive broadband measurement method applicable to distribution automation terminals according to claim 4, characterized in that: The windowed ZoomFFT calculation is performed on the collected electrical quantity to obtain the frequency spectrum of the windowed ZoomFFT of the electrical quantity, specifically including: At the set sampling frequency Discrete sampling of electrical quantities is performed to obtain Sampling data points are cached to form the third cache sequence , and perform complex modulation frequency shift on it to form the fourth cache sequence , which is expressed as follows: Where: represents the fourth cache sequence; Indicates the fourth cache sequence The cached data points, which are discrete data points after complex modulation frequency shift; 、 are the determined refinement start frequency and cutoff frequency respectively; represents the frequency zero point of the signal represented by the fourth cache sequence; For discrete data points containing complex modulation frequency shift The fourth cache sequence Perform FFT transformation, filter in the frequency domain, and retain The spectrum within the range, other spectral lines are set to zero, and the filtered spectrum is obtained ; For length The filtered spectrum of Perform IFFT and get the length The first time domain signal is sampled by a fifth buffer sequence representing the first time domain signal. Take one point, so the length is The resampled second time domain signal is subjected to a windowed FFT transform to obtain a resampled spectrum. , the frequency resolution corresponding to the frequency domain is / .

6. The adaptive broadband measurement method applicable to distribution automation terminals according to claim 1, characterized in that: The multi-spectral line interpolation calculation specifically includes: The amplitudes of three spectral lines with large information content near the maximum value in the spectrum of the electrical quantity windowed FFT or the spectrum of the electrical quantity windowed ZoomFFT are selected for interpolation correction, which can be expressed as the following formulas (5) and (6): Where: The position of the spectral line before the maximum amplitude spectral line position The amplitude of The maximum amplitude line The amplitude of the position, The position of the next spectral line after the maximum amplitude spectral line The amplitude of Indicates the true spectral line position and the position of the maximum amplitude line Deviation between Indicates the ratio relationship between the maximum amplitude spectral line and its previous and next spectral lines; Fitting to polynomial The coefficients of are used to obtain the correction formulas for amplitude, frequency and phase, which are expressed as follows: Where: is the spectral line position of the true frequency, is the frequency resolution, is the calculated frequency of dense spectrum signal and non-dense spectrum signal after frequency shift, is the amplitude of the dense spectrum signal and the non-dense spectrum signal after the calculated frequency shift, is the phase of the calculated dense spectrum signal and non-dense spectrum signal after frequency shift.

7. The adaptive broadband measurement method applicable to distribution automation terminals according to claim 1, characterized in that: The spectrum sorting and extraction of the broadband frequency components of the electrical quantity to be measured and their corresponding amplitudes and phases specifically include: The frequency adjustment is performed as shown in the following formula (10): Where: is the actual dense spectrum signal frequency, is the frequency shift of the dense spectrum, is the frequency of the frequency-shifted dense spectrum calculation, is the sampling frequency.

8. An adaptive broadband measurement system applicable to a distribution automation terminal, executing the adaptive broadband measurement method applicable to a distribution automation terminal according to any one of claims 1 to 7, comprising: Windowed FFT calculation module, dense spectrum judgment module, windowed ZoomFFT calculation module, multi-spectral line interpolation calculation module, electrical quantity wide-band component extraction module; characterized by: The windowed FFT calculation module is used to perform windowed FFT calculations on the collected electrical quantities; the dense spectrum judgment module is used to determine the coarse frequency judgment of the dense spectrum based on the spectrum amplitude; the windowed ZoomFFT calculation module is used for windowed ZoomFFT calculations under dense spectrum conditions; the multi-spectral line interpolation calculation module is used for multi-spectral line interpolation fitting to calculate the electrical quantity amplitude, frequency and phase; the electrical quantity wide-band component extraction module is used for spectrum sorting to extract the wide-band frequency components of the electrical quantities to be measured and their corresponding amplitude and phase.

9. An electronic device comprising: A processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus; the memory is used to store computer programs; the processor is used to execute the computer programs stored in the memory, characterized in that when the computer program is loaded into the processor, an adaptive broadband measurement method applicable to a distribution automation terminal according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the adaptive broadband measurement method applicable to a distribution automation terminal according to any one of claims 1 to 7 is implemented.

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