Voltage flicker parameter detection method and module based on high-order symmetric derivative and fractional Kaiser window

Abstract

The invention discloses a voltage flicker parameter detection method and module based on a high-order symmetric derivative and a fractional Kaiser window. The voltage flicker parameter detection method and module are used for electric energy quality monitoring. The method comprises the steps that first-order symmetric difference is popularized to high-order symmetric difference on the basis of first-order symmetric difference, a multi-resolution concept is introduced to obtain a multi-resolution high-order symmetric envelope derivative operator with high precision and high robustness, and flicker envelope signals are extracted more rapidly and accurately through the energy operator; then, fractional Kaiser window three-spectral-line improved FFT (Fast Fourier Transform) spectrum correction with two adjustable parameters is adopted for the extracted envelope signal; the method can effectively adapt to single-frequency modulation and multi-frequency modulation environments, can suppress interference of harmonic waves, inter-harmonic waves, fundamental wave frequency fluctuation, phase jump and noise, and is wider in application range in the field of electric energy quality monitoring compared with modules obtained by other energy operators.

Description

Technical Field

[0001] This invention relates to the field of power quality analysis technology, and more specifically to a method and module for detecting voltage flicker parameters based on higher-order symmetric derivatives and fractional Kaiser windows. Background Technology

[0002] With the transformation of the energy structure, a high proportion of distributed power sources are widely connected to the distribution network, resulting in a "weak grid" characteristic with low reactance-to-resistivity ratio (X / R) and low short-circuit capacity, making voltage flicker an increasingly prominent problem. Meanwhile, fluctuating loads such as welding machines and electric arc furnaces are also major causes of voltage flicker. Voltage flicker seriously affects the normal operation of power equipment and the quality of power supply for users. Therefore, developing accurate and efficient flicker parameter detection technology is crucial to ensuring grid security.

[0003] Currently, the methods for detecting voltage flicker parameters are mainly divided into the following categories, but all of them have limitations to varying degrees:

[0004] Methods based on standards and filtering include the IEC-recommended square detection method and its improved versions (half-wave RMS method, full-wave rectification method). The detection accuracy of these methods heavily depends on the accuracy of the filter parameters, and the square detection method generates interfering harmonic components when processing multi-frequency flicker signals, thus limiting its applicability.

[0005] Time-frequency analysis-based methods, such as the Hilbert transform, can directly extract the signal envelope, but they suffer from the endpoint flying wing phenomenon and have poor noise resistance. Wavelet transform and its improved algorithms (such as the moving invariant wavelet) have time-frequency localization capabilities, but they face the challenge of selecting wavelet basis functions and have large errors when sampling asynchronously.

[0006] In addition, the classic FFT method, although fast in computation, suffers from low detection accuracy due to inherent spectral leakage and picket fence effects; improved spectral correction methods, such as Chirp-Z transform and six-term cosine window interpolation, improve frequency resolution, but their accuracy is still limited by frequency resolution and the algorithm complexity increases; high-precision algorithms, such as matrix pencil method and S-transform, can achieve high time-frequency analysis accuracy, but the computational load is huge, making it difficult to implement real-time detection in embedded devices.

[0007] Energy operator-based methods, such as the Teager-Kaiser energy operator (TKEO) and its improved algorithms, are simple and fast to calculate, but they have significant errors at high modulation frequencies, and their detection performance is sensitive to the sampling frequency and has poor adaptability.

[0008] To effectively address the need for accurate measurement and rapid estimation of flicker parameters in complex power grid environments and diverse detection scenarios, this invention proposes a detection method with multiple adjustable parameters. Summary of the Invention

[0009] In view of this, the present invention provides a voltage flicker parameter detection method and module based on high-order symmetric derivatives and fractional Kaiser windows for power quality monitoring. The detection method uses the multi-resolution high-order symmetric envelope derivative operator (MHOS-EDO) to extract weak flicker envelopes, which can adapt to different sampling frequencies. At the same time, it adopts three-line interpolation FFT spectrum analysis and correction based on fractional Kaiser windows to accelerate the calculation speed of the algorithm and reduce the square root calculation when extracting flicker envelopes.

[0010] To achieve the above objectives, the present invention adopts the following technical solution:

[0011] In a first aspect, this application discloses a method for detecting voltage flicker parameters based on higher-order symmetric derivatives and fractional Kaiser windows, including;

[0012] A mathematical model of voltage flicker is constructed, and the grid voltage is sampled discretely.

[0013] Based on the collected discrete voltages, a higher-order symmetric envelope derivative operator is obtained, and the flicker envelope in the grid voltage is extracted using the operator.

[0014] The flicker envelope is weighted using a fractional Kaiser window, and then a Fourier transform is performed to obtain the discrete spectrum.

[0015] Calculate the amplitude ratio corresponding to the peak spectral line index, and obtain the offset of the actual peak relative to the peak spectral line index according to the predefined offset mapping function; determine the flicker frequency according to the offset; and determine the flicker amplitude based on the predefined amplitude correction function of the offset.

[0016] Preferably, the mathematical model expression for voltage flicker is:

[0017]

[0018] in, Let n be the grid voltage corresponding to any sampling point n, where n is any sampling point. The magnitude of the grid voltage. The amplitude modulation function represents the flicker voltage, used to describe the variation of the voltage amplitude at sampling point n relative to the rated value. The digital angular frequency representing the fundamental frequency of the grid voltage. , The angular frequency of the grid voltage. , For power grid frequency, Sampling frequency, This represents the relative voltage fluctuation component. This represents the digital angular frequency of the k-th flicker signal. , The angular frequency of the flicker signal. , The frequency of the flicker signal modulation wave.

[0019] Preferably, the higher-order symmetric envelope derivative operator is obtained, including:

[0020] Determine the order of the symmetric difference and sampling point spacing ,

[0021] For the power grid voltage waveform, the sampling point spacing is calculated as follows: of Order-symmetric difference;

[0022] Based on the above By applying the energy operator FWEO and HT properties, we can obtain higher-order symmetric envelope derivative operators.

[0023] Preferably, the expression for the higher-order symmetric envelope derivative operator is:

[0024]

[0025] In the formula, This represents a multiresolution higher-order symmetric envelope derivative operator. Let n be the grid voltage corresponding to any sampling point n. Let A represent the amplitude of the grid voltage. Indicates the order, This represents the digital angular frequency of the fundamental frequency of the grid voltage, where n is an arbitrary sampling point. This indicates the spacing between sampling points.

[0026] Preferably, the extraction method for the flicker envelope in the grid voltage waveform using the operator is as follows:

[0027]

[0028] In the formula, This represents a multiresolution higher-order symmetric envelope derivative operator. Let n be the grid voltage corresponding to any sampling point n. The magnitude of the grid voltage. Indicates the order, The digital angular frequency representing the fundamental frequency of the grid voltage. This indicates the spacing between sampling points.

[0029] Preferably, calculating the amplitude ratio corresponding to the peak spectral line index includes: identifying the index and amplitude of the peak spectral line and its left and right adjacent lines in the discrete spectrum, and calculating the amplitude ratio according to the following formula:

[0030]

[0031] In the formula, The peak spectral line amplitude in the discrete spectrum. and These represent the amplitudes of the lines adjacent to the peak spectral line on the left and right, respectively.

[0032] Preferably, the fitting process of the offset mapping function is as follows:

[0033] The range of values ​​for the predefined offset is substituted into the following formula to calculate the corresponding amplitude ratio;

[0034]

[0035] In the formula, This is the offset. For the fractional Kaiser's spectral function;

[0036] Generate offset-amplitude ratio data pairs, and perform polynomial fitting with amplitude ratio as the independent variable and offset as the dependent variable.

[0037] Preferably, determining the flicker frequency based on the offset includes:

[0038]

[0039] In the formula, This is an index of the actual peak spectral lines. This is the offset. Indicates frequency resolution;

[0040] Combined with the amplitude correction function Determining the flicker amplitude includes:

[0041]

[0042] In the formula, The peak spectral line amplitude in the discrete spectrum. and These represent the amplitudes of the lines adjacent to the peak spectral line on the left and right, respectively.

[0043] Preferably, the predefined amplitude correction function based on the offset includes:

[0044] The flicker amplitude is calculated based on the amplitude correction function and the window function spectrum, respectively.

[0045] By combining the equations, we obtain the expression for the amplitude correction function;

[0046] The range of values ​​for the predefined offset is substituted into the amplitude correction function expression to obtain offset-amplitude correction data pairs. The offset is used as the independent variable and the value is used as the dependent variable for polynomial fitting.

[0047] Secondly, this application also provides a voltage flicker parameter detection module based on higher-order symmetric derivatives and fractional Kaiser windows. This device applies the voltage flicker parameter detection method based on higher-order symmetric derivatives and fractional Kaiser windows as described above, including:

[0048] The voltage sampling unit is used to construct a mathematical model of voltage flicker and to perform discrete sampling of the grid voltage.

[0049] The envelope extraction unit is used to obtain a high-order symmetric envelope derivative operator based on the collected discrete voltage, and to use the operator to extract the flicker envelope in the grid voltage waveform.

[0050] The discrete spectrum acquisition unit is used to weight the flicker envelope using a fractional Kaiser window, and then perform a Fourier transform to obtain the discrete spectrum.

[0051] The flicker parameter detection unit is used to calculate the amplitude ratio corresponding to the peak spectral line index, obtain the offset of the actual peak relative to the peak spectral line index according to a predefined offset mapping function, determine the flicker frequency according to the offset, and determine the flicker amplitude based on the predefined amplitude correction function of the offset.

[0052] This invention discloses a voltage flicker parameter detection method and module based on high-order symmetric derivatives and fractional Kaiser windows, suitable for power quality monitoring. It effectively adapts to both single-frequency and multi-frequency modulation environments and suppresses interference from harmonics, interharmonics, fundamental frequency fluctuations, phase jumps, and noise. Compared to other energy operators, it has a wider range of applications. The specific beneficial effects of this application include:

[0053] 1) Introducing a higher-order symmetric envelope derivative operator can achieve higher-precision flicker envelope extraction by leveraging more accurate signal demodulation capabilities and the robustness of symmetric differential design. On the other hand, by simplifying the envelope extraction formula and avoiding square root operations, the computational load can be effectively reduced and the computational speed can be improved.

[0054] 2) Based on the fractional Kaiser window, the desired main lobe width and side lobe attenuation characteristics can be obtained by adjusting two adjustable parameters. The corresponding three-spectral-line interpolation algorithm can effectively suppress the spectral leakage and picket fence effect of the flicker envelope signal extracted by MHOS-EDO. Attached Figure Description

[0055] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0056] Figure 1 The flowchart shows a voltage flicker parameter detection method based on higher-order symmetric derivatives and fractional Kaiser windows.

[0057] Figure 2 A comparison and verification graph showing the effect of the fractional Kaiser window function;

[0058] Figure 3 An example diagram of a voltage flicker parameter detection module based on high-order symmetric derivatives and fractional Kaiser windows is shown.

[0059] Figure 4 A comparison chart of measurement errors for flicker amplitude modulation coefficient;

[0060] Figure 5 This is a comparison chart of flicker frequency measurement errors. Detailed Implementation

[0061] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0062] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0063] This invention addresses the problems of poor accuracy in voltage flicker parameter estimation and insufficient adaptability to complex power grid conditions by proposing a multi-resolution high-order symmetric envelope derivative operator (MHOS-EDO) and a three-spectral interpolation method based on a fractional Kaiser window. First, it extends the first-order symmetric difference to a higher-order symmetric difference and introduces the concept of multi-resolution to obtain the high-accuracy and robust MHOS-EDO. This energy operator extracts the flicker envelope signal faster and more accurately. Second, the extracted envelope signal is subjected to FFT spectral correction using a three-spectral-line improved FFT with two adjustable parameters based on a fractional Kaiser window.

[0064] In one embodiment, the voltage flicker parameter detection method based on higher-order symmetric derivatives and fractional Kaiser windows includes the following steps:

[0065] A mathematical model of voltage flicker is constructed, and the grid voltage is sampled discretely.

[0066] Based on the collected discrete voltages, a higher-order symmetric envelope derivative operator is obtained, and the flicker envelope in the grid voltage waveform is extracted using the operator.

[0067] The flicker envelope is weighted using a fractional Kaiser window, and then a Fourier transform is performed to obtain the discrete spectrum.

[0068] Calculate the amplitude ratio corresponding to the peak spectral line index. Based on the predefined offset mapping function This yields the offset of the actual peak value relative to the peak spectral line index. According to the offset Determine the flicker frequency;

[0069] Based on offset Predefined amplitude correction function Combined with the amplitude correction function Determine the flicker amplitude value.

[0070] The voltage flicker parameter detection method based on higher-order symmetric derivatives and fractional Kaiser windows in this application follows the flowchart. Figure 1 .

[0071] In some implementations, the first step includes constructing a mathematical model of voltage flicker to simulate the acquired voltage waveform and obtain the sampled signal. ;

[0072] In this embodiment, the mathematical model of voltage flicker is generally expressed as the result of modulation of a voltage fluctuation component of 0.05-35Hz and the root mean square (RMS) value of the rated power frequency voltage. Its time-domain mathematical expression is as follows:

[0073] (1)

[0074] in, The magnitude of the grid voltage. The angular frequency of the grid voltage. The initial phase angle of the grid voltage. It is a time-varying amplitude signal. For the voltage fluctuation component, its time-domain mathematical expression is:

[0075] (2)

[0076] in, The amplitude of voltage flicker. Let k be the number of terms in the voltage fluctuation signal that contain flicker components, and k be the term index. This is the flicker amplitude value. and These are the angular frequency and initial phase of the flicker component, respectively.

[0077] Furthermore, by performing discrete sampling on equation (1), a discrete expression for the mathematical model of voltage flicker can be obtained, which is in the form of:

[0078] (3)

[0079] in, Let n be the grid voltage corresponding to any sampling point n, where n is any sampling point. The magnitude of the grid voltage. The amplitude modulation function represents the flicker voltage, used to describe the variation of the voltage amplitude at sampling point n relative to the rated value. The digital angular frequency representing the fundamental frequency of the grid voltage. , The angular frequency of the grid voltage. , For power grid frequency, Sampling frequency, This represents the relative voltage fluctuation component. This represents the digital angular frequency of the k-th flicker signal. , The angular frequency of the flicker signal. , The frequency of the flicker signal modulation wave.

[0080] In some implementation schemes, the second step is: voltage flicker envelope extraction. ;

[0081] That is, based on the simulated voltage waveform, a higher-order symmetric envelope derivative operator is obtained, and the flicker envelope in the grid voltage waveform is extracted using the operator;

[0082] In this embodiment, obtaining the higher-order symmetric envelope derivative operator includes:

[0083] Determine the order of the symmetric difference and sampling point spacing ,

[0084] For the power grid voltage waveform, the sampling point spacing is calculated as follows: of Order-symmetric difference;

[0085] Based on the above By applying the energy operator FWEO and HT properties, we can obtain higher-order symmetric envelope derivative operators.

[0086] In one exemplary embodiment, the discrete form of the conventional TKEO is shown in equation (4);

[0087] (4)

[0088] In the formula, This represents the discrete representation of the traditional TKEO energy operator. It represents any discrete signal, meaning that any discrete-time tracking of transient energy can be achieved with only three adjacent sampling points.

[0089] However, calculating transient energy from adjacent sampling points makes the results susceptible to noise, amplitude fluctuations at some endpoints and abrupt changes, and interference from the smoothness of the sampling signal. To address these challenges, symmetrical differencing is used to improve noise robustness through data smoothing. The sampling interval is... Symmetric differences are divided into:

[0090] (5)

[0091] By recursively applying equation (5), we can obtain its... Order-symmetric difference expression

[0092] (6)

[0093] Furthermore, to address the issue of insufficient signal demodulation accuracy caused by noise in traditional TKEO, a sampling point spacing of [missing information] is adopted. of Order-symmetric difference:

[0094] (7)

[0095] Substitute equation (7) into the expression for the energy operator FWEO as follows:

[0096] (8)

[0097] In the formula, This represents the frequency-weighted energy operator. Represents a continuous real-domain signal. Represents the imaginary unit. This represents the Hilbert transform.

[0098] The form of MHOS-EDO is obtained:

[0099] (9)

[0100] In the formula, This represents the multiresolution high-order symmetric envelope derivative operator MHOS-EDO.

[0101] For discrete signals By trigonometric identities The sum (6) yields its Order-symmetric difference:

[0102] (10)

[0103] In the formula, Represents discrete signals amplitude, Indicates digital frequency.

[0104] Based on the properties of HT ,have

[0105] (11)

[0106] Substituting equations (10) and (11) into equation (9) yields...

[0107] (12)

[0108] flicker modulation coefficient Usually in the range The frequency of the flicker signal modulated wave is between these values. The range of values ​​is The number of terms in the flicker component Smaller, Equation (3) The fluctuation range is very small, so it can be approximated as a constant. Equation (3) becomes .so The MHOS-EDO is:

[0109] (13)

[0110] Furthermore, when extracting the flicker envelope, use Substitute;

[0111] (14)

[0112] Ignore and Two smaller components, only retain The flicker envelope component can then be obtained:

[0113] (15)

[0114] Compared to the traditional TKEO algorithm for extracting the flicker envelope, Equation (15) does not involve the square root operation, which helps to speed up the calculation and facilitates the detection of meeting the real-time requirements.

[0115] When estimating voltage flicker parameters, directly relying on the flicker envelope signal extracted through MHOS-EDO can lead to issues such as ambiguity in flicker frequency components and amplitude calculation errors due to spectral leakage and the picket fence effect. Therefore, this invention introduces a fractional Kaiser window function with a specific time-domain distribution.

[0116] To verify the effect of this function, select , The fractional Kaiser window, and its comparison with the Kaiser window ( A comparative analysis of the normalized logarithmic spectra of the Hanning window, Blackman-Harris window, and Nuttall window was conducted, and the results are as follows: Figure 2 As shown in Table 1, the peak sidelobe levels and the asymptotic sidelobe decay rates for the fractional Kaiser window and other windows are compared.

[0117] Table 1

[0118]

[0119] It is evident that the Kaiser window is in While a single-window window may have a low sidelobe peak value, it cannot guarantee a sufficiently high sidelobe decay rate. Using a fractional Kaiser window, however, ensures a sufficiently low sidelobe peak value while maintaining a relatively high sidelobe decay rate. Therefore, compared to other commonly used window functions, the fractional Kaiser window can more effectively suppress the interference of spectral leakage on measurement accuracy.

[0120] In this embodiment, the Kaiser window is a special case of the fractional Kaiser window. The two adjustable parameters of the fractional Kaiser window can more finely adjust the main lobe width and side lobe attenuation, and its form is as follows:

[0121] (16)

[0122] in, This represents the discrete expression of the fractional Kaiser window function, specifically the value of the nth fractional Kaiser window. It is a fractional modified Bessel function of the first kind of zero order. For fractional parameters, , m represents the summation index, For the Euler gamma function; For shape parameters, is the window length, and n represents the nth sampling point.

[0123] The spectral function of the fractional Kaiser is as follows:

[0124] (17)

[0125] In some implementations, the third step involves windowing the extracted envelope using a fractional Kaiser window. Then, Fast Fourier Transform was used for analysis. Specifically:

[0126] 1. Suppress spectral leakage and picket fence effect of flicker envelope signal by using fractional Kaiser window, i.e., for conduct Weighted:

[0127] (18)

[0128] 2. After windowing the discrete flicker envelope signal, a Fourier transform is performed to analyze the k-th flicker fluctuation component in the signal.

[0129] (19)

[0130] In the formula, This represents the frequency resolution, specifically the frequency spacing between adjacent discrete frequency points after the FFT. . Indicates the amplitude of the spectral line. This represents the index of a discrete frequency point, and N is the window length, which is the number of sampling points.

[0131] In one implementation, given that the FFT signal will have a picket fence effect under asynchronous sampling conditions, making it difficult to accurately obtain frequency components, this application uses three-spectral-line interpolation for envelope spectrum analysis, which is more accurate.

[0132] In this embodiment, the peak value is first found. and the amplitude of the lines on its left and right sides and To calculate the amplitude ratio corresponding to the peak spectral line index. ;

[0133] Assume the index of the peak spectral line is Its corresponding frequency is The index of the adjacent spectral line on the left is The index of the adjacent spectral line on the right is The actual peak spectral line index is... The corresponding frequency is Define the offset. The amplitudes of the three spectral lines are defined as follows: , , At the same time, parameters are introduced. The derivation relationship is as follows:

[0134] (20)

[0135] Secondly, by fitting a polynomial Calculate the offset, i.e., according to a predefined offset mapping function. This yields the offset of the actual peak value relative to the peak spectral line index. According to the offset The flicker frequency is calculated using the following formula;

[0136] (twenty one)

[0137] In this step, a predefined offset mapping function is used. It is the offset Substituting into the following equation (22), we get for The function, denoted as Specifically:

[0138] (twenty two)

[0139] Furthermore, the range of values ​​for the offset is predefined; in this embodiment, it is... A series of offset-amplitude ratio data pairs were obtained, and then the polyfit polynomial fitting algorithm on the MATLAB platform was used to... and In one embodiment, the fitted parameters are obtained by fitting the functional relationship. With flicker frequency The parsing expression is:

[0140] (twenty three)

[0141] Finally, based on the offset Predefined amplitude correction function Combined with the amplitude correction function The flicker amplitude value is calculated using the following formula:

[0142] (twenty four)

[0143] Among them, for the predefined amplitude correction function The fitting process includes:

[0144] A correction formula for flicker amplitude is constructed based on the spectrum of the window function;

[0145] (25)

[0146] By combining equations (24) and (25), the amplitude correction function can be obtained. expression;

[0147] Furthermore, a predefined range of offset values ​​is substituted into the amplitude correction function. The expression yields offset-amplitude correction data pairs, and the offset is... As the independent variable, As the dependent variable, a polynomial fitting is performed. In this embodiment, the obtained amplitude correction function is:

[0148] (26)

[0149] In another embodiment, the present invention provides a voltage flicker parameter detection module based on higher-order symmetric derivatives and fractional Kaiser windows, comprising:

[0150] The voltage sampling unit is used to construct a mathematical model of voltage flicker and to perform discrete sampling of the grid voltage.

[0151] The envelope extraction unit is used to obtain a high-order symmetric envelope derivative operator based on the collected discrete voltage, and to use the operator to extract the flicker envelope in the grid voltage waveform.

[0152] The discrete spectrum acquisition unit is used to weight the flicker envelope using a fractional Kaiser window, and then perform a Fourier transform to obtain the discrete spectrum.

[0153] The flicker parameter detection unit is used to calculate the amplitude ratio corresponding to the peak spectral line index, obtain the offset of the actual peak relative to the peak spectral line index according to a predefined offset mapping function, determine the flicker frequency according to the offset, and determine the flicker amplitude based on the predefined amplitude correction function of the offset.

[0154] Since each step is consistent with the steps in the voltage flicker parameter detection method based on higher-order symmetric derivatives and fractional Kaiser windows described above, they will not be repeated here.

[0155] In one specific embodiment, the module is embedded in a power quality monitoring device, as detailed below. Figure 3 The detailed settings of the device are as follows:

[0156] 1. Operating power supply range: 88~286VAC / DC, 47~440Hz. Power consumption: <13W.

[0157] 2. Bus Voltage 1 / Bus Voltage 2 ----- Converts high voltage (such as 10kV, 35kV, etc.) to low voltage (such as 100V or 220V) proportionally for use by measuring instruments or protection devices.

[0158] 3. Line Current 1 / Line Current 2 ----- This converts large currents (such as hundreds of amperes) into smaller currents (such as 5A or 1A) for easier measurement and protection.

[0159] 4. Digital Input (DI) – Used for signal reception.

[0160] 5. Digital Output (DO) ---- Used for signal output.

[0161] 6. High-precision voltage flicker parameter detection technology module: implementation of the controller and detection of power flicker accuracy.

[0162] 7. The RS-485 interface corresponds to ports P3 (RS-485) and P4 (RS-485), with terminals marked D+, D-, and SH. It employs a dedicated RS-485 isolation chip and includes protection circuitry to prevent damage to the communication port from common-mode and differential-mode voltage interference, lightning strikes, and incorrect wiring.

[0163] 8. GPS time synchronization cable – GPS communication function.

[0164] In one embodiment, in order to analyze the superiority of the voltage flicker parameter estimation algorithm based on MHOS-EDO and fractional Kaiser window three-line interpolation of this application, the Teager-Kaiser energy operator (TEKO), the improved Teager-Kaiser energy operator (ITEKO), and the algorithm of this invention are compared.

[0165] Simulation conditions are set as follows: the number of sampling points is 4096, and the amplitude of the fundamental voltage of the power grid is [value missing]. The power grid frequency is 50Hz, and the sampling frequency is... flicker signal frequency The modulation coefficient varies continuously within the range of 1 to 35 Hz. The value range is 0.1 pu.

[0166] The measurement errors of flicker amplitude modulation coefficient and flicker frequency are as follows: Figure 4 and Figure 5 As shown;

[0167] Depend on Figure 4 and Figure 5It is known that the voltage flicker parameter estimation algorithm of the fractional Kaiser window three-line interpolation of the present invention, which uses the improved Teager-Kaiser energy operator, can achieve the best estimation accuracy. The MHOS-EDO of the present invention can maintain the same accuracy as the improved Teager-Kaiser energy operator over a wide range. The accuracy of the algorithm in this application is reduced only when the flicker frequency is 24.5~25.5 Hz.

[0168] Fix the flicker signal frequency at The detection accuracy of the energy operator was compared at different sampling frequencies, and the detection results are shown in Tables 2 and 3.

[0169] Table 2 Measurement error of flicker amplitude modulation coefficient at different sampling frequencies

[0170]

[0171] Table 3. Flicker frequency measurement error at different sampling frequencies

[0172]

[0173] As shown in Tables 2 and 3, the flicker frequency measurement error of the three energy operators is low at different sampling frequencies, while the improved Teager-Kaiser energy operator is not as accurate as the algorithm of this invention in estimating the flicker amplitude modulation coefficient.

[0174] As shown in Table 3, although the flicker frequency measurement errors of the three energy operators are consistent at different sampling frequencies, the measurement errors of the flicker amplitude modulation coefficient at different sampling frequencies, as shown in Table 2, differ significantly. TKEO and the improved TKEO... The measurement error of the time-flicker amplitude modulation coefficient is small, while and However, a small error cannot be guaranteed at that time. This invention... and At that time, it can be adjusted and The value of reduces the error and can adapt to different sampling frequencies. This invention is more adaptable to different sampling environments.

[0175] The adjustable parameters of the technical method used in this invention's device allow it to adapt to different sampling frequencies, ensuring low measurement errors. Clearly, the voltage flicker parameter estimation algorithm based on MHOS-EDO and fractional Kaiser window three-spectral-line interpolation exhibits superior performance.

[0176] The above simulations verify the effectiveness of the proposed method in voltage flicker parameter detection and show that it can adapt to different sampling frequencies. Compared with the Teager-Kaiser energy operator and the improved Teager-Kaiser energy operator, the algorithm of this application has superior performance.

[0177] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to the method section.

[0178] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for detecting voltage flicker parameters based on higher-order symmetric derivatives and fractional Kaiser windows, characterized in that, A mathematical model of voltage flicker is constructed, and the grid voltage is sampled discretely. Based on the collected discrete voltages, a higher-order symmetric envelope derivative operator is obtained, and the flicker envelope in the grid voltage is extracted using the operator. The flicker envelope is weighted using a fractional Kaiser window, and then a Fourier transform is performed to obtain the discrete spectrum. Calculate the amplitude ratio corresponding to the peak spectral line index, and obtain the offset of the actual peak relative to the peak spectral line index according to the predefined offset mapping function; determine the flicker frequency according to the offset; and determine the flicker amplitude based on the predefined amplitude correction function of the offset.

2. The voltage flicker parameter detection method according to claim 1, characterized in that, The mathematical model expression for voltage flicker is: ； in, Let n be the grid voltage corresponding to any sampling point n, where n is any sampling point. The magnitude of the grid voltage. The amplitude modulation function represents the flicker voltage, used to describe the variation of the voltage amplitude at sampling point n relative to the rated value. The digital angular frequency representing the fundamental frequency of the grid voltage. , The angular frequency of the grid voltage. , For power grid frequency, Sampling frequency, This represents the relative voltage fluctuation component. This represents the digital angular frequency of the k-th flicker signal. , The angular frequency of the flicker signal. , The frequency of the flicker signal modulation wave.

3. The voltage flicker parameter detection method according to claim 1, characterized in that, Finding higher-order symmetric envelope derivative operators, including: Determine the order of the symmetric difference and sampling point spacing , For the power grid voltage waveform, the sampling point spacing is calculated as follows: of Order-symmetric difference; Based on the above By applying the energy operator FWEO and HT properties, we can obtain higher-order symmetric envelope derivative operators.

4. The voltage flicker parameter detection method according to claim 3, characterized in that, The expression for the higher-order symmetric envelope derivative operator is: ； In the formula, This represents a multiresolution higher-order symmetric envelope derivative operator. Let n be the grid voltage corresponding to any sampling point n. Let A represent the amplitude of the grid voltage. Indicates the order, This represents the digital angular frequency of the fundamental frequency of the grid voltage, where n is an arbitrary sampling point. This indicates the spacing between sampling points.

5. The voltage flicker parameter detection method according to claim 1, characterized in that, The operator is used to extract the flicker envelope from the grid voltage, and the extraction method is as follows: ； In the formula, This represents a multiresolution higher-order symmetric envelope derivative operator. Let n be the grid voltage corresponding to any sampling point n. The magnitude of the grid voltage. Indicates the order, The digital angular frequency representing the fundamental frequency of the grid voltage. This indicates the spacing between sampling points.

6. The voltage flicker parameter detection method according to claim 1, characterized in that, Calculate the amplitude ratio corresponding to the peak spectral line index, including: identifying the index and amplitude of the peak spectral line and its left and right adjacent lines in the discrete spectrum, and calculating the amplitude ratio according to the following formula: ； In the formula, The peak spectral line amplitude in the discrete spectrum. and These represent the amplitudes of the lines adjacent to the peak spectral line on the left and right, respectively.

7. The voltage flicker parameter detection method according to claim 1, characterized in that, The fitting process of the offset mapping function is as follows: The range of values ​​for the predefined offset is substituted into the following formula to calculate the corresponding amplitude ratio; ； In the formula, This is the offset. For the fractional Kaiser's spectral function; Generate offset-amplitude ratio data pairs, and perform polynomial fitting with amplitude ratio as the independent variable and offset as the dependent variable.

8. The voltage flicker parameter detection method according to claim 1, characterized in that, Determining the flicker frequency based on the offset includes: ； In the formula, This is an index of the actual peak spectral lines. This is the offset. Indicates frequency resolution; Combined with the amplitude correction function Determining the flicker amplitude includes: ； In the formula, The peak spectral line amplitude in the discrete spectrum. and These represent the amplitudes of the lines adjacent to the peak spectral line on the left and right, respectively.

9. The voltage flicker parameter detection method according to claim 1, characterized in that, Based on the offset predefined amplitude correction function, including: The flicker amplitude is calculated based on the amplitude correction function and the window function spectrum, respectively. By combining the equations, we obtain the expression for the amplitude correction function. The range of values ​​for the predefined offset is substituted into the amplitude correction function expression to obtain offset-amplitude correction data pairs. The offset is used as the independent variable and the value is used as the dependent variable for polynomial fitting.

10. A voltage flicker parameter detection module based on high-order symmetric derivatives and fractional Kaiser windows, characterized in that, The voltage flicker parameter detection method based on higher-order symmetric derivatives and fractional Kaiser windows according to any one of claims 1-9 includes: The voltage sampling unit is used to construct a mathematical model of voltage flicker and to perform discrete sampling of the grid voltage. The envelope extraction unit is used to obtain a high-order symmetric envelope derivative operator based on the collected discrete voltage, and to use the operator to extract the flicker envelope in the grid voltage. The discrete spectrum acquisition unit is used to weight the flicker envelope using a fractional Kaiser window, and then perform a Fourier transform to obtain the discrete spectrum. The flicker parameter detection unit is used to calculate the amplitude ratio corresponding to the peak spectral line index, obtain the offset of the actual peak relative to the peak spectral line index according to a predefined offset mapping function, determine the flicker frequency according to the offset, and determine the flicker amplitude based on the predefined amplitude correction function of the offset.

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