Electrical automation quality detection method and system

Abstract

The invention belongs to the technical field of quality detection, and discloses an electrical automation quality detection method and system. The method comprises the steps of collecting original voltage and current signals of a PCC point of a power grid and performing FFT to obtain a background harmonic frequency set and a background harmonic amplitude set; generating an initial frequency grid based on a preset target frequency band, and generating a sparse frequency grid in combination with the background harmonic waves; calculating the estimated signal-to-noise ratio of each candidate frequency, performing ascending sorting to obtain an injection sequence, injecting sinusoidal signals, collecting PCC point voltage response and total current, and calculating a frequency impedance data pair; performing rational function fitting based on the frequency impedance data to obtain a broadband impedance curve; analyzing the curve, extracting quality characteristic parameters, and performing quality judgment according to the parameters; according to the method, the technical problem that the grid-connected stability quality of a single new energy converter cannot be quickly and automatically qualified in a production line offline detection scene in the prior art is effectively solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of quality detection, more particularly, to an electrical automation quality detection method and system. BACKGROUND

[0002] With large-scale grid-connected access of new energy, the interaction between new energy and power grid causes sub-synchronous and super-synchronous oscillation problems, and the wideband impedance characteristic is a key index for analyzing the grid-connected stability of new energy stations and converters. The wideband impedance characteristic is crucial for evaluating the anti-disturbance ability of grid-connected systems and avoiding oscillation risks. The traditional methods for measuring wideband impedance in the current industry mainly include the sweep frequency method and the random signal injection method. The sweep frequency method requires injecting disturbance signals at different frequency points and measuring responses one by one, which not only takes a long time, but also may excite potential oscillation of the system due to long-time and large-amplitude disturbance signals, thereby threatening the safety of power grid operation. Although the random signal injection method can achieve fast frequency response, the low signal-to-noise ratio caused by the dispersion of injected signal energy makes it difficult to effectively guarantee the measurement accuracy, especially in the field environment of the public connection point (PCC point) of new energy stations, where the background harmonics are rich. The core contradiction of the prior art is that it is difficult to balance the speed of impedance measurement, the safety of disturbance injection, and the accuracy of measurement results. In addition, in the scene of detecting the grid-connected stability quality of a single new energy converter offline, the traditional method still relies on manual analysis and judgment of impedance data, lacks a standardized and automated judgment process, and is difficult to meet the needs of the production line for fast, accurate, and batch qualification judgment of a single converter. Therefore, it is difficult to adapt to the efficient scene characteristics of offline detection of the production line.

[0003] A Chinese patent with publication number CN119315514A discloses a wind farm grid-connected stability rapid evaluation method and system based on impedance model: S1, establish the physical model of the wind farm grid-connected system Collect data of the wind farm grid-connected system, analyze the overall structure and parameters of the wind farm grid-connected system, and build a physical model of the wind farm grid-connected system. The physical model shows the interaction between each component in the system, providing a framework for subsequent impedance modeling; S2, establish the impedance model of the wind farm and the grid The impedance model of the wind farm includes the impedance of the wind turbine system, the impedance of the converter, and the total impedance of the wind farm; The impedance model of the grid includes the impedance of the transmission line, the impedance of the transformer, and the load impedance of the grid. By calculating the impedance of the wind farm and the grid, the complex impedance matrix of the wind farm grid-connected system is obtained; S3, select appropriate evaluation indicators to determine the evaluation indicators to measure the stability evaluation of the wind farm grid-connected system. The evaluation indicators include voltage stability, frequency stability, and power factor. When selecting evaluation indicators, consider the characteristics of the wind farm and the requirements of the grid, such as selecting voltage transient response, frequency response, and power fluctuation indicators for analysis; S4, impedance matching analysis By comparing the impedance of the wind farm and the grid, the stability of the system is determined. Impedance matching analysis is used to identify potential stability problems to ensure that the system remains stable within all operating frequency ranges; S5, evaluate dynamic response characteristics Evaluate the response capability of the wind farm to disturbances during the grid connection process. By simulating the actual operation of the wind farm and the grid, the response behavior of the system under disturbance is observed; S6, steady-state analysis Power balance, power factor, and voltage and frequency stability of the wind farm grid-connected system are evaluated. This is done by calculating the power flow, load distribution, and voltage and frequency stability of the system to determine the stability of the system under steady-state conditions; S7, evaluate the impact of grid connection on the grid Evaluate the impact of wind farm grid connection on the grid and determine whether it will have a negative impact on the stability of the grid. Analyze the grid voltage fluctuation, frequency change, and system harmonics. Use power system simulation tools to simulate and analyze the grid after grid connection; S8, design control strategy Control strategy includes power control of wind turbine, current control of converter, and voltage and frequency regulation of system. By designing control algorithms such as PID control and fuzzy control, the stability and performance of the system are improved, and multiple simulation tests are performed to determine the optimal control parameters and strategies.

[0004] Although the above method can meet most scenarios, research and practical application of the above method and prior art have found that the above method and prior art at least have the following defects:

[0005] The above method cannot quickly and automatically determine the grid-connected stability quality of a single new energy converter in an offline detection scenario on a production line.

[0006] In view of this, the present application proposes an electrical automation quality detection method and system to solve the above problems. SUMMARY

[0007] In order to overcome the above-mentioned defects of the prior art, in order to achieve the above-mentioned purpose, the present application provides the following technical scheme: an electrical automation quality detection method, comprising:

[0008] Collecting the original voltage signal and the original current signal of the PCC point and performing fast Fourier transform to obtain a background harmonic frequency set and a background harmonic amplitude set;

[0009] A preset target scanning frequency band is generated according to a fixed interval to generate an initial frequency grid; a sparse frequency grid is generated according to the background harmonic frequency set and the initial frequency grid;

[0010] The estimated signal-to-noise ratio of each candidate frequency in the sparse frequency grid is calculated and sorted in ascending order to obtain an injection sequence, the injection sequence is input into a control power amplifier to obtain a sinusoidal injection signal, and the sinusoidal injection signal is injected into the PCC point through a current coupler;

[0011] At the same time of injecting the sinusoidal injection signal, the voltage response and the total current of the PCC point are collected; the signal parameters corresponding to the sinusoidal injection signal are extracted, the complex impedance is calculated according to the signal parameters, and the frequency impedance data pair is obtained;

[0012] The frequency impedance data pair is fitted according to the rational function, and the coefficients are solved based on the least square method to obtain a wideband impedance curve;

[0013] The wideband impedance curve is analyzed to extract the quality characteristic parameters, and the quality is determined according to the quality characteristic parameters.

[0014] Further, the method for obtaining the background harmonic frequency and the background harmonic amplitude comprises:

[0015] The original voltage signal and the original current signal are preprocessed to obtain the preprocessed voltage signal and the current signal;

[0016] The preprocessed voltage signal and the current signal are respectively subjected to N-point fast Fourier transform to obtain the voltage frequency domain signal and the current frequency domain signal in complex form;

[0017] The voltage amplitude spectrum and the current amplitude spectrum are calculated according to the voltage frequency domain signal and the current frequency domain signal combined with the signal gain and the energy dispersion coefficient;

[0018] The actual frequency corresponding to the mth index is calculated according to the sampling rate and the sampling point number N, and the frequency axis is obtained by counting all the actual frequencies;

[0019] The frequency corresponding to the spectral peak with the largest amplitude in the frequency axis is statistically extracted as the fundamental frequency; the voltage amplitude spectrum and current amplitude spectrum corresponding to the fundamental frequency are obtained as the fundamental voltage amplitude and fundamental current amplitude.

[0020] Traverse the frequency axis to obtain all frequency points whose actual frequency is greater than twice the fundamental frequency as the frequencies to be sorted. Sort the frequencies to be sorted in ascending order that meet the screening conditions, and extract the corresponding frequencies and amplitudes to obtain the background harmonic frequency set and the corresponding harmonic amplitude set.

[0021] Furthermore, the screening conditions include condition 1 and condition 2, wherein condition 1: the voltage amplitude of the frequency to be sorted is not lower than the harmonic voltage identification threshold or the current amplitude of the candidate frequency is not lower than the harmonic current identification threshold.

[0022] Condition 2: Within the allowable deviation range, the frequency to be sorted is n times the fundamental frequency, where n is an integer not less than 2.

[0023] Furthermore, methods for generating sparse frequency grids include:

[0024] The target scanning frequency band is divided according to a fixed interval to obtain an initial grid frequency set. The number of grid points is calculated based on the upper and lower limits of the target scanning frequency band and the fixed interval.

[0025] Set an interference avoidance bandwidth. For each initial frequency in the initial grid frequency set, if the initial frequency point is within the interference avoidance bandwidth of the background harmonic frequency, then remove the corresponding initial frequency and construct a sparse frequency grid based on the remaining frequency points.

[0026] Furthermore, methods for obtaining the injection sequence include:

[0027] The background noise amplitude is obtained by performing cubic spline interpolation on the harmonic spectrum of each candidate frequency in the sparse frequency grid.

[0028] The estimated signal-to-noise ratio is calculated based on the preset effective value of the injected signal, the system calibration coefficient, and the background noise amplitude. The estimated signal-to-noise ratios are then sorted in ascending order to obtain the injection sequence.

[0029] Furthermore, methods for obtaining the background noise amplitude include:

[0030] Within each segmented interval, define a cubic spline interpolation function that satisfies the interpolation conditions;

[0031] Construct the cubic interpolation function expression for each segmented interval;

[0032] Establish a system of equations based on the interpolation conditions, solve for the coefficients of all segmented intervals, obtain the interpolation function for all segmented intervals, and obtain the continuous interpolation function.

[0033] Traverse the frequency points of the sparse frequency grid, determine the sub-interval where the candidate frequency is located; extract the corresponding sub-interval and the corresponding interpolation coefficient;

[0034] Substitute the candidate frequency into the cubic interpolation function of the corresponding sub-interval to calculate the background noise amplitude.

[0035] Further, the interpolation conditions include:

[0036] At the endpoints of the sub-interval, the value of the interpolation is equal to the original amplitude;

[0037] The first and second derivatives at the connection of the sub-interval are continuous;

[0038] The natural boundary is adopted, that is, the second derivative values of the two endpoints of the sub-interval are 0.

[0039] Further, the method for obtaining the frequency impedance data pair includes:

[0040] According to the injection sequence, a sinusoidal injection signal is calculated and obtained, the sinusoidal injection signal is injected into the PCC point through a current coupler, and the voltage response and total current of the PCC point are collected while the sinusoidal injection signal is injected; signal parameters corresponding to the sinusoidal injection signal are extracted, the signal parameters include voltage response effective value, voltage phase, total current effective value and current phase; impedance phase is calculated and obtained according to the voltage phase and the current phase, complex impedance is calculated and obtained in combination with the voltage response effective value, the total current effective value and the impedance phase, and the frequency is combined to splice, and the frequency impedance data pair is obtained.

[0041] Further, the quality characteristic parameters include phase margin, amplitude margin, Nyquist distance and specific frequency band impedance maximum value;

[0042] The method for obtaining the phase margin includes:

[0043] Traverse the wideband impedance curve, obtain the frequency corresponding to the impedance value of 1 as the amplitude cross frequency, calculate the difference between the impedance phase of the amplitude cross frequency and -180°, and obtain the phase margin;

[0044] The method for obtaining the amplitude margin includes:

[0045] Traverse the wideband impedance curve, obtain the frequency corresponding to the impedance phase of -180° as the phase cross frequency, calculate the negative logarithm of the impedance amplitude corresponding to the phase cross frequency, and obtain the amplitude margin;

[0046] The method for obtaining the specific frequency band impedance maximum value includes:

[0047] The impedance curve of the target frequency band in the continuous impedance curve is intercepted, a discrete frequency sequence is obtained based on a sampling step, each frequency point in the discrete frequency sequence is substituted into the continuous impedance function, the corresponding real part and imaginary part of the complex impedance are calculated, for each discrete frequency point, the corresponding amplitude is calculated according to the corresponding real part and imaginary part of the complex impedance, all NL discrete frequency points are traversed, NL is the number of discrete frequency points, the amplitude of each point is calculated, and an impedance amplitude array of a specific frequency band is generated; and the maximum impedance amplitude in the impedance amplitude array is extracted as the maximum impedance of the specific frequency band.

[0048] Further, the method for obtaining the Nyquist distance comprises:

[0049] The rated reference impedance is calculated, and the normalized complex impedance is calculated based on the continuous impedance function;

[0050] The normalized complex impedance is discretely sampled in a preset frequency range with a sampling frequency step of to generate a discrete frequency sequence; each frequency point in the discrete frequency sequence is substituted into the calculation to obtain the corresponding normalized complex impedance, a discrete complex impedance array is obtained, and the real part array and the imaginary part array are obtained by splitting;

[0051] A complex plane coordinate system with the real axis as the horizontal axis and the imaginary axis as the vertical axis is built, and the Nyquist curve is drawn based on the real part array and the imaginary part array;

[0052] For the gth point in the discrete complex impedance array, the Euclidean distance between the point and the point (-1, j0) is calculated, the Euclidean distance of each point is calculated by traversing all the discrete complex impedance points, a distance array is generated, and the minimum value in the distance array is obtained as the Nyquist distance.

[0053] Further, the method for determining the quality comprises:

[0054] If all the quality characteristic parameters satisfy that the phase margin is not lower than the phase threshold value, the amplitude margin is not lower than the amplitude threshold value, the Nyquist distance is not lower than the distance threshold value, and the maximum impedance of the specific frequency band is not higher than the impedance threshold value, it is determined that the quality is qualified, otherwise it is determined that the quality is unqualified, and the corresponding unqualified parameters and deviation values are output.

[0055] An electrical automation quality detection system, which implements the electrical automation quality detection method, comprises:

[0056] The passive monitoring module: collects original voltage signals and original current signals of a point of common coupling (PCC) of a power grid and performs fast Fourier transform to analyze and obtain a background harmonic frequency set and a background harmonic amplitude set;

[0057] The grid generation module: generates an initial frequency grid according to the background harmonic frequency set and the initial frequency grid; and generates a sparse frequency grid according to the background harmonic frequency set and the initial frequency grid;

[0058] The intelligent injection module: calculate the estimated signal-to-noise ratio of each candidate frequency in the sparse frequency grid and sort it in ascending order, obtain the injection sequence, input the injection sequence into the control power amplifier, obtain the sinusoidal injection signal, and inject the sinusoidal injection signal into the PCC point through the current coupler;

[0059] The data acquisition module: while injecting the sinusoidal injection signal, collect the voltage response and total current of the PCC point; extract the signal parameters corresponding to the sinusoidal injection signal, calculate the complex impedance according to the signal parameters, and obtain the frequency impedance data pair;

[0060] The impedance calculation module: perform rational function fitting according to the frequency impedance data pair, and solve the coefficients based on the least square method to obtain the wideband impedance curve;

[0061] The quality detection module: analyze the wideband impedance curve, extract the quality characteristic parameters, and make quality judgment according to the quality characteristic parameters.

[0062] The technical effects and advantages of the electrical automation quality detection method and system of the present application are as follows:

[0063] The present application generates a sparse frequency grid that avoids interference by passively monitoring the background harmonics of the PCC point, optimizes the sinusoidal signal injection strategy by sorting in ascending order according to the estimated signal-to-noise ratio, synchronously collects the response signal to calculate the discrete frequency impedance data pair, reconstructs the wideband impedance curve based on rational function fitting and least square method, automatically extracts four core quality characteristic parameters: phase margin, amplitude margin, Nyquist distance and maximum impedance in a specific frequency band, and finally automatically compares all parameters with the preset threshold values derived from international standards, grid guidelines and enterprise internal controls. This method effectively solves the technical problems of low detection accuracy, excessive manual intervention, low determination efficiency and poor consistency of results caused by relying on manual analysis of impedance curves and non-targeted signal injection in the prior art when detecting the grid stability quality of a single new energy converter offline. Through background harmonic avoidance, rational function fitting and standardized parameter calculation, the error of impedance measurement and characteristic parameter extraction is controlled at a low level, providing reliable data support for determination. From frequency grid generation, signal injection, impedance calculation, parameter extraction to threshold comparison, the whole process does not require manual intervention, eliminating subjective errors. By reducing the number of invalid injections through sparse frequency grid, the automatic process significantly shortens the detection time of a single converter, and the automatic output of unqualified parameters and deviation values can guide rapid rectification, perfectly adapting to the core needs of rapid, automatic and accurate qualification determination of the grid stability quality of a single new energy converter in the offline scene of the production line, significantly improving the detection efficiency and determination reliability of the production line. BRIEF DESCRIPTION OF DRAWINGS

[0064] Figure 1A flowchart of an electrical automation quality detection method according to the present application is shown in the figure;

[0065] Figure 2 A data flow diagram according to the present application is shown in the figure;

[0066] Figure 3 A flowchart of a method for obtaining background noise amplitude according to the present application is shown in the figure;

[0067] Figure 4 A structural diagram of an electrical automation quality detection system according to the present application is shown in the figure. DETAILED DESCRIPTION

[0068] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of the present application.

[0069] Embodiment 1

[0070] Referring to FIGS. Figure 1 , Figure 2 The electrical automation quality detection method according to the present application includes the following steps:

[0071] The original voltage signal and the original current signal of the power grid public connection point (PCC) are collected and subjected to fast Fourier transform to obtain the background harmonic frequency and the background harmonic amplitude;

[0072] The method for obtaining the background harmonic frequency and the background harmonic amplitude includes the following steps:

[0073] The original voltage signal and the original current signal are preprocessed to obtain the preprocessed voltage signal and the preprocessed current signal;

[0074] The preprocessed voltage signal and the preprocessed current signal are subjected to N-point fast Fourier transform respectively to obtain the voltage frequency domain signal and the current frequency domain signal in complex form; for example, , wherein, m is the frequency point index, N is the number of sampling points, is the fast Fourier transform; wherein the real part of the complex number corresponds to the in-phase component of the signal, and the imaginary part corresponds to the quadrature component;

[0075] The voltage amplitude spectrum and the current amplitude spectrum are calculated according to the voltage frequency domain signal and the current frequency domain signal in combination with the signal gain and the energy dispersion coefficient; for example, the voltage amplitude spectrum and the current amplitude spectrum wherein, a voltage modulus value of the fast Fourier transform of the mth frequency point; a current modulus value of the fast Fourier transform of the mth frequency point; a voltage signal gain; a current signal gain; an energy dispersion coefficient;

[0076] The actual frequency corresponding to the mth index is calculated according to the sampling rate and the number N of sampling points, such as the actual frequency corresponding to the mth index , and the frequency axis is obtained by counting all the actual frequencies, a sampling rate;

[0077] The frequency corresponding to the spectral peak with the maximum amplitude in the extracted frequency axis is counted as the fundamental frequency; the voltage amplitude spectrum value and the current amplitude spectrum value corresponding to the fundamental frequency are obtained as the fundamental voltage amplitude and the fundamental current amplitude;

[0078] All frequency points greater than twice the fundamental frequency in the frequency axis are obtained as the to-be-sorted frequencies by traversing, the to-be-sorted frequencies meeting the screening condition are sorted in ascending order, and the corresponding frequencies and amplitudes are extracted to obtain a background harmonic frequency set and a corresponding harmonic amplitude set.

[0079] The screening condition includes condition 1 and condition 2, wherein condition 1: the voltage amplitude of the to-be-sorted frequency is not lower than the harmonic voltage recognition threshold or the current amplitude of the candidate frequency is not lower than the harmonic current recognition threshold;

[0080] Condition 2: within an allowable deviation range, the to-be-sorted frequency is n times of the fundamental frequency, and n is an integer not lower than 2.

[0081] The original voltage signal and the original current signal of the grid connection point, i.e. the PCC point, are collected during the grid connection detection of the new energy converter, and are preprocessed to eliminate the DC component and suppress interference, and then N-point fast Fourier transform is performed to obtain complex voltage frequency domain signals and current frequency domain signals, the voltage amplitude spectrum and the current amplitude spectrum are calculated in combination with the voltage signal gain, the current signal gain and the energy dispersion coefficient, the actual frequency corresponding to each FFT index is determined according to the sampling rate and the sampling point number N, and the frequency axis is formed, the fundamental frequency corresponding to the amplitude maximum spectrum peak in the frequency axis and the fundamental voltage and current amplitude are further identified, and finally the background harmonic frequency set and the corresponding harmonic amplitude set are obtained by screening the to-be-sorted frequencies which are greater than twice the fundamental frequency, meet the voltage amplitude threshold or the current amplitude threshold, and are within the allowable deviation range of the fundamental frequency n times, n being an integer not less than 2, the core role of the process lies in: in the scene of detecting a single new energy converter offline, the interference frequency and intensity of the grid background harmonic can be accurately identified, which provides a key basis for subsequent adaptive avoidance of these interference frequency points and optimization of the test signal injection strategy, effectively avoids the interference of the background harmonic on the impedance measurement of the converter, greatly reduces the number of invalid signal injections to improve the impedance measurement speed, while ensuring the impedance measurement accuracy, and accurate wideband impedance data is the basis for subsequent automatic extraction of stability characteristic parameters such as phase margin and Nyquist distance, and automatic comparison with the qualified threshold, finally realizing rapid and automatic qualified judgment of the grid connection stability quality of a single new energy converter, and solving the technical problems that the existing technology cannot effectively exclude the background harmonic interference, resulting in long detection time, low precision and dependence on manual intervention, and being difficult to adapt to the offline efficient detection demand of the production line.

[0082] A preset target scanning frequency band is generated according to a fixed interval to generate an initial frequency grid; a sparse frequency grid is generated according to the background harmonic frequency set and the initial frequency grid;

[0083] The method for generating the sparse frequency grid comprises:

[0084] The target scanning frequency band is divided according to a fixed interval to obtain an initial grid frequency set, and the number of grid points is calculated according to the upper limit, the lower limit and the fixed interval of the target scanning frequency band; if the number of grid points is greater than a preset threshold, the initial grid frequency set is pruned to obtain a pruned grid frequency set, and the number of grid points in the pruned grid frequency set is less than the preset threshold. Wherein, and are the upper limit and the lower limit of the target scanning frequency band, respectively; is the fixed interval;

[0085] A disturbance avoidance bandwidth is set, for each initial frequency in the initial grid frequency set, if the initial frequency point is within the disturbance avoidance bandwidth of the background harmonic frequency, the corresponding initial frequency is removed, and a sparse frequency grid is formed based on the remaining frequency points.

[0086] By eliminating the background harmonic interference frequency points, the measurement error caused by background interference when injecting test signals into the converter PCC point is avoided, the accuracy of grid impedance measurement is ensured from the source, and reliable data basis is provided for subsequent extraction of phase margin, Nyquist distance and other stability characteristic parameters; the sparse frequency grid significantly reduces the number of invalid frequency points, significantly shortens the detection time of a single converter, and adapts to the rhythm of efficient off-line detection of the production line; at the same time, the standardized frequency grid generation and interference elimination process does not require manual intervention and can be directly embedded into the automatic detection system, providing standardized frequency dimension support for subsequent extraction of stability characteristic parameters based on impedance data, automatic comparison with qualified threshold and final qualified judgment, effectively solving the technical problems of the prior art that the measurement accuracy is low, the detection time is long, and manual adjustment of frequency points is difficult to realize automatic judgment and cannot adapt to the off-line detection requirements of the production line.

[0087] The estimated signal-to-noise ratio of each candidate frequency in the sparse frequency grid is calculated and sorted in ascending order to obtain an injection sequence, the injection sequence is input into a control power amplifier to obtain a sinusoidal injection signal, and the sinusoidal injection signal is injected into the PCC point through a current coupler;

[0088] The method for obtaining the injection sequence comprises:

[0089] The harmonic spectrum of each candidate frequency in the sparse frequency grid is subjected to cubic spline interpolation to obtain a background noise amplitude;

[0090] Referring to Figure 3 , the method for obtaining the background noise amplitude comprises:

[0091] The sparse frequency grid is divided into K-1 segmented intervals, and in each segmented interval of the sparse frequency grid, a cubic spline interpolation function satisfying an interpolation condition is defined ;

[0092] The interpolation condition comprises:

[0093] At the endpoints of the segmented intervals, the interpolated values are equal to the original amplitudes; that is , , wherein is the corresponding cubic spline interpolation function value at the first frequency point in the segmented interval; wherein is the first frequency point; is the cubic spline interpolation function value corresponding to the first frequency point; is the original amplitude corresponding to the first frequency point; is the original amplitude corresponding to the first frequency point; a frequency point; for the segmented interval the first derivative of the corresponding cubic spline interpolation function at a frequency point the function value at; for the first a frequency point corresponding to the original amplitude;

[0094] The first and second derivatives at the connection of the segmented interval are continuous; that is , ; wherein the first derivative of the cubic spline interpolation function at the first a frequency point the first derivative of the cubic spline interpolation function at the first a frequency point the first derivative of the cubic spline interpolation function at the first the second derivative of the cubic spline interpolation function at the first a frequency point the second derivative of the cubic spline interpolation function at the first a frequency point the second derivative of the cubic spline interpolation function at the first

[0095] The second derivatives of the natural boundary, that is, the two endpoints of the segmented interval, are 0; ; ; the second derivative of the first frequency point; the second derivative of the first a frequency point

[0096] The cubic interpolation function expression in each segmented interval is constructed; such as the cubic interpolation function wherein , , , the interpolation coefficient of the first segmented interval; the local variable in the segmented interval, the cubic interpolation function variable;

[0097] According to the interpolation conditions, the equation group is established, the coefficients of all segmented intervals are solved, the interpolation functions of all segmented intervals are obtained, and the continuous interpolation function is obtained; such as:

[0098] By substituting the interpolation conditions , ;

[0099] to First derivative : , we have : ; where, is the length of the segment interval;

[0100] Second derivative : , we have : , we have ; ;

[0101] Substitute into the first derivative equation, combined with the first derivative continuity condition , to establish a three-moment equation about : ;

[0102] Substitute into the natural boundary condition , , solve the above linear equations, get all ;

[0103] To solve and : , .

[0104] Through the above steps, we can solve all the interpolation coefficients of the segment interval, so as to determine the complete continuous interpolation function , in , when , .

[0105] Traverse the frequency points of the sparse frequency grid, judge the segment interval where the candidate frequency is located; extract the corresponding segment interval and the corresponding interpolation coefficient;

[0106] Substitute the candidate frequency into the corresponding segment cubic interpolation function to calculate the background noise amplitude; if the background noise amplitude , where, is the candidate frequency, , , and are all interpolation coefficients.

[0107] According to the preset injection signal effective value, the system calibration coefficient and the background noise amplitude, the estimated signal-to-noise ratio is calculated, the estimated signal-to-noise ratio is sorted in ascending order, and the injection sequence is obtained. If the estimated signal-to-noise ratio , where, is the preset injection signal effective value, which is set according to the capacity of the station, such as 100MW station ; The system calibration coefficient is determined by the acquisition unit gain and the coupling device efficiency, and is calibrated in advance by a 100Ω standard resistor. Usually = 1.05-1.2.

[0108] The cubic spline interpolation can accurately fit the background noise amplitude, ensuring the accuracy of the estimated signal-to-noise ratio. By prioritizing the injection of low signal-to-noise ratio frequency points in ascending order, the high signal-to-noise ratio of full-band impedance measurement can be ensured with the minimum injection energy, avoiding the measurement precision deficiency caused by unreasonable signal injection strategy. This provides reliable data support for subsequent accurate calculation of wideband impedance and extraction of phase margin and other stability characteristic parameters. The whole process from background noise amplitude calculation to injection sequence generation is automatically executed through standardized algorithms, without the need for manual adjustment of injection frequency or judgment of interference strength, significantly reducing the manual intervention link. At the same time, the injection demand of key frequency points is prioritized, avoiding the waste of time caused by invalid signal injection, significantly improving the detection efficiency of a single converter, and perfectly adapting to the core demand of production line offline detection for speed and automation. It provides efficient and accurate pre-signal injection protection for subsequent stability characteristic parameter extraction based on impedance data, automatic comparison with qualified threshold, and final qualified judgment, effectively solving the technical problems of existing technologies, such as the dependence of signal injection strategy on manual intervention, the interference of background noise on measurement precision, and the low detection efficiency, which makes it difficult to realize the rapid and automatic qualified judgment of single converter grid stability in the production line offline scene.

[0109] The control power amplifier generates a sinusoidal injection signal according to the injection sequence, and injects the sinusoidal injection signal into the PCC point. At the same time of injecting the sinusoidal injection signal, the voltage response and total current of the PCC point are collected. The signal parameters corresponding to the sinusoidal injection signal are extracted, and the complex impedance is calculated according to the signal parameters to obtain the frequency impedance data pair.

[0110] The method for obtaining the frequency impedance data pair comprises:

[0111] The sinusoidal injection signal is calculated according to the injection sequence, and the sinusoidal injection signal is injected into the PCC point through the current coupler. At the same time of injecting the sinusoidal injection signal, the voltage response and total current of the PCC point are collected. The signal parameters corresponding to the sinusoidal injection signal are extracted, including the voltage response effective value, the voltage phase, the total current effective value, and the current phase. The impedance phase is calculated according to the voltage phase and the current phase, and the complex impedance is calculated by combining the voltage response effective value, the total current effective value, and the impedance phase. The frequency impedance data pair is obtained by combining the frequency. For example, the sinusoidal injection signal is generated as wherein, is the initial phase, is the th frequency point in the injection sequence; is the time; the complex impedance of a frequency point wherein, is an impedance amplitude, is a voltage response effective value, is a total current effective value; is an impedance phase, is a voltage phase, is a current phase; is an imaginary number; is a mathematical constant; is an effective value of the current.

[0112] The automatic calculation of the complex impedance is realized through the standardized signal injection and parameter extraction process, the errors and low efficiency caused by manual reading and calculation of data are avoided, and the accuracy and consistency of the frequency impedance data pair are ensured. The generated frequency impedance data pair is the direct basis for subsequent rational function fitting to obtain a wideband impedance curve and extract phase margin and other stability characteristic parameters, and the accuracy directly determines the reliability of the stability determination. At the same time, combined with the sparse frequency grid and the optimized injection sequence in the early stage, this process only performs signal injection and impedance calculation on key effective frequency points, greatly reduces redundant operations, significantly improves the detection speed of a single converter, perfectly adapts to the demand for rapid and automation of the production line offline scene, and provides core data support for automatic qualified determination of the grid-connected stability quality of a single new energy converter by comparing the stability characteristic parameters and the qualified threshold, effectively solving the technical problems of the prior art, such as dependence on manual impedance measurement process, insufficient data accuracy, low detection efficiency, and difficulty in completing rapid and automatic qualified determination in the production line offline scene.

[0113] The wideband impedance curve is obtained by rational function fitting according to the frequency impedance data pair and solving the coefficients based on the least square method; for example, a fitting model is obtained as follows: wherein, , is a polynomial order, which is set according to the number of data points; , is a coefficient to be solved; the error sum of squares of the fitting value and the measured value is minimized as the target, and the coefficients are solved by the least square method: wherein, is a fitting phase of the impedance, M is the number of frequency points in the injection sequence, is the fitting model value of the th frequency point in the injection sequence, is the measured impedance amplitude of the th frequency point in the injection sequence, is the measured impedance phase of the th frequency point in the injection sequence.

[0114] The rational function model fits the physical characteristics of the grid-connected impedance of the new energy converter, and combines the optimal error control of the least square method, so as to control the fitting error of discrete data at a low level, and ensure that the wideband impedance curve accurately reflects the impedance characteristics of the converter in the full frequency band, thereby providing a continuous and reliable data carrier for subsequent extraction of stability key characteristic parameters such as phase margin and Nyquist distance. The discrete frequency impedance data cannot directly support full-band stability analysis, while the continuous curve can completely cover the key oscillation frequency band such as subsynchronous and supersynchronous, thereby avoiding omission or deviation of the characteristic parameter extraction. The entire fitting process can be embedded in an automatic detection system through a standardized algorithm, without the need for manual adjustment of model parameters or intervention in the calculation process, so as to fully adapt to the production line "automation" detection requirements. At the same time, the least square method has high solving efficiency and will not increase the detection time, and cooperates with the signal injection and impedance calculation process optimized in the early stage, so as to further guarantee the "fast" detection rhythm, and effectively solve the technical problems in the prior art, such as difficulty in extracting stability characteristic parameters due to the lack of accurate continuous impedance curve, dependence on manual experience to complete the data, poor consistency of detection results, and difficulty in realizing rapid and automatic qualification judgment of single converter grid-connected stability in the production line offline scene.

[0115] The quality characteristic parameters are obtained by analyzing the wideband impedance curve.

[0116] The method for obtaining the quality characteristic parameters comprises:

[0117] The quality characteristic parameters comprise a phase margin, an amplitude margin, a Nyquist distance, and a maximum impedance value in a specific frequency band.

[0118] The wideband impedance curve is traversed, a frequency corresponding to an impedance value of 1 is obtained as an amplitude cross frequency, a difference between an impedance phase of the amplitude cross frequency and -180° is calculated, and a phase margin is obtained; if the phase margin is less than 0, the amplitude cross frequency is taken as a phase cross frequency, and an amplitude margin is calculated according to the following formula: wherein, is the amplitude cross frequency; is the amplitude cross frequency The phase margin is a grid-connected stability quantitative index specified by international standards, and the numerical size directly reflects the disturbance resistance capability of the converter, replaces the subjective determination mode of analyzing the impedance curve relying on artificial experience in the prior art, eliminates the error and inconsistency of artificial judgment, and provides a standardized and quantifiable core basis for stability determination. From the traversal positioning of the amplitude cross frequency in the wideband impedance curve to the calculation of the phase margin, the whole process can be automatically executed through the algorithm, can be seamlessly embedded into the production line automatic detection process, greatly shortens the time consumption of index extraction, and adapts to the fast rhythm of offline detection. At the same time, the accurate phase margin data is the key input for subsequent automatic comparison with the preset qualified threshold and final determination of whether the grid-connected stability of the converter is qualified. If the index is lacking, the quantitative qualified determination cannot be completed, effectively solving the technical problems in the prior art that the lack of a standardized and automatically extracted stability quantitative index leads to low determination efficiency and inconsistent results, and it is difficult to realize the fast and automatic qualified determination of the grid-connected stability of a single converter in the production line offline scene.

[0119] The impedance phase of-180° is obtained as the phase cross frequency by traversing the wideband impedance curve, the negative logarithm of the impedance amplitude corresponding to the phase cross frequency is calculated, and the amplitude margin is obtained. If the amplitude margin , wherein, is the phase cross frequency. is the impedance of the phase cross frequency , and is a logarithmic function. The amplitude margin is a key stability quantitative index specified by international standards and grid guidelines, and the standardized calculation replaces the subjective mode of observing the impedance curve and judging the stability relying on experience in the prior art, completely eliminates the error and inconsistency of artificial judgment, and provides an objective and unified quantitative basis for stability evaluation. From the automatic positioning of the phase cross frequency in the wideband impedance curve to the accurate calculation of the amplitude margin according to the formula, the whole process can be completed through the algorithm embedded in the automatic detection system, without manual searching for the frequency point or calculating the logarithm, which greatly shortens the index extraction time and perfectly adapts to the fast and efficient rhythm of production line offline detection. At the same time, the accurate amplitude margin data is the core input for subsequent automatic comparison with the preset qualified threshold, and if the index is lacking, the quantitative qualified determination of the stability cannot be realized, effectively solving the technical problems in the prior art that the lack of an automatically extracted standardized amplitude margin index leads to low determination efficiency and poor reliability of the results, and it is difficult to realize the fast and automatic qualified determination of the grid-connected stability of a single converter in the production line offline scene.

[0120] The method for obtaining the Nyquist distance includes:

[0121] The rated reference impedance is calculated, and the normalized complex impedance is obtained by combining the continuous impedance function. If the rated reference impedance Per-unit complex impedance ,in, The rated voltage at the PCC point; Rated capacity for PCC point; for The real part, ; for The imaginary part, ; The impedance of the cubic interpolation function variable f;

[0122] The perimetric complex impedance is sampled within a preset frequency range with a frequency step size of [missing information]. Discrete sampling is performed to generate a discrete frequency sequence; each frequency point in the discrete frequency sequence is... Substitute the values ​​into the calculation to obtain the corresponding per-unit complex impedance, obtain the discrete complex impedance array, and split it to obtain the real part array and the imaginary part array;

[0123] Construct a complex plane coordinate system with the real axis as the horizontal axis and the imaginary axis as the vertical axis, and draw the Nyquist curve by combining the real part array and the imaginary part array;

[0124] For the g-th point in the discrete complex impedance array, calculate its relationship with... The Euclidean distance of a point is calculated by iterating through all discrete complex impedance points, calculating the Euclidean distance for each point, generating a distance array, and then taking the minimum value in the array as the Nyquist distance. (Euclidean distance example follows.) ,in, Let g be the real part corresponding to the g-th point; Let g be the imaginary part corresponding to the g-th point. This represents the g-th complex impedance element in the discrete complex impedance array. Perimeter normalization eliminates the impedance differences between converters with different rated parameters, providing a unified and comparable quantitative standard for the Nyquist distance, thus meeting the needs of batch testing converters of different specifications on production lines. The entire process, from perimeter calculation and discrete sampling to distance traversal solution, is automatically executed through standardized algorithms, eliminating the need for manual drawing of the Nyquist curve and subjective judgment of the distance to the (-1,j0) point, completely avoiding human error and significantly improving testing efficiency. Furthermore, as an internationally recognized core stability indicator, the precise value of the Nyquist distance can be directly and automatically compared with a preset pass threshold, serving as a key quantitative basis for determining whether the grid-connected stability of a converter is qualified. This effectively solves the technical problem of existing technologies relying on manual analysis of the Nyquist curve, resulting in low efficiency and poor consistency of results, making it difficult to achieve rapid and automated qualification determination of the grid-connected stability of a single converter in production line scenarios.

[0125] The impedance curve in the target frequency band in the continuous impedance curve is intercepted, a discrete frequency sequence is obtained based on a sampling step, each frequency point in the discrete frequency sequence is substituted into the continuous impedance function, the corresponding real part and imaginary part of the complex impedance are calculated, for each discrete frequency point, the corresponding amplitude is calculated according to the corresponding real part and imaginary part of the complex impedance, all NL discrete frequency points are traversed, NL is the number of discrete frequency points, the amplitude of each point is calculated, and an impedance amplitude array of a specific frequency band is generated; the maximum impedance amplitude in the impedance amplitude array is extracted as the maximum impedance in the specific frequency band. The accurate interception of the target frequency band focuses on the key risk range of grid-connected stability analysis, avoids irrelevant frequency band data interference, ensures that the extracted maximum value can directly reflect the impedance characteristics of the converter in the high oscillation risk frequency band, and provides targeted basis for quantitative evaluation of specific types of oscillation risks such as subsynchronous and supersynchronous; the whole process from frequency band interception, discrete sampling to amplitude calculation and maximum value extraction is automatically executed through standardized algorithms, without the need for manual selection of key frequency bands, manual calculation of amplitudes or judgment of peak values, completely eliminating the errors and efficiency bottlenecks of manual operations, greatly shortening the time consumption of index extraction of a single converter, and perfectly adapting to the rapid demand of production line batch off-line detection; at the same time, the maximum impedance in the specific frequency band is an oscillation risk quantitative index recognized by international standards and grid guidelines, which can be directly compared with the pre-stored qualified threshold in an automatic manner, and is the core risk evaluation input for subsequent completion of the grid-connected stability qualification of the converter, effectively solving the technical problems of low detection efficiency and poor result consistency caused by the dependence on manual data processing, subjective judgment of oscillation risk and non-automatic process in the prior art, and realizing the rapid and automatic qualification of the grid-connected stability of a single converter in the production line off-line scene.

[0126] The method for quality determination comprises:

[0127] If all quality characteristic parameters satisfy that the phase margin is not lower than the phase threshold value, the amplitude margin is not lower than the amplitude threshold value, the Nyquist distance is not lower than the distance threshold value, and the maximum impedance in the specific frequency band is not higher than the impedance threshold value, it is determined that the quality is qualified, otherwise it is determined that the quality is unqualified, and the corresponding unqualified parameters and deviation values are output.

[0128] In the scene of detecting the grid stability quality of a single new energy converter offline, by comparing the four core quality characteristic parameters of phase margin, amplitude margin, Nyquist distance and maximum impedance value in a specific frequency band extracted automatically in the early stage with the pre-stored phase threshold value, amplitude threshold value, distance threshold value and impedance threshold value derived from international standards, grid guidelines and enterprise internal control requirements, only when all parameters meet the conditions of phase margin not less than phase threshold value, amplitude margin not less than amplitude threshold value, Nyquist distance not less than distance threshold value and maximum impedance value in a specific frequency band not higher than impedance threshold value, the quality is determined to be qualified, otherwise it is determined to be unqualified and the specific unqualified parameters and deviation value are automatically output. The core role of this process is: completely replacing the mode of relying on manual experience to analyze impedance curve and subjectively judging stability in the prior art, eliminating the error and inconsistency of manual judgment through the standardized judgment logic of quantitative indicators, clear threshold values and automatic comparison; at the same time, the entire judgment process does not require human intervention, and can be completed within seconds from parameter input to result output, greatly improving the detection and judgment efficiency of a single converter, perfectly adapting to the demand for rapid batch offline detection of production line; in addition, the automatic output of unqualified parameters and deviation values can also provide accurate guidance for subsequent fault troubleshooting and parameter debugging of production line, forming a closed loop of detection, judgment and rectification, and effectively solving the technical problems that the prior art relies on manual judgment, is greatly affected by subjective factors, has low efficiency and is difficult to realize the rapid and automatic qualified judgment of the grid stability quality of a single new energy converter in the offline scene of production line.

[0129] Embodiment 2

[0130] Please refer to Figure 4 The electrical automation quality detection system described in the embodiment comprises:

[0131] The passive monitoring module acquires original voltage signals and original current signals of a point of common coupling (PCC) and performs fast Fourier transform to obtain a background harmonic frequency set and a background harmonic amplitude set;

[0132] The grid generation module: preset a target scanning frequency band and generates an initial frequency grid according to a fixed interval; generates a sparse frequency grid according to the background harmonic frequency set and the initial frequency grid;

[0133] The intelligent injection module: calculates the estimated signal-to-noise ratio of each candidate frequency in the sparse frequency grid and sorts them in ascending order to obtain an injection sequence, inputs the injection sequence into a control power amplifier to obtain a sinusoidal injection signal, and injects the sinusoidal injection signal into the PCC point through a current coupler;

[0134] Data acquisition module: collect the voltage response and total current of the PCC point while injecting the sinusoidal injection signal; extract the signal parameters corresponding to the sinusoidal injection signal, calculate the complex impedance according to the signal parameters, and obtain the frequency impedance data pair;

[0135] Impedance calculation module: perform rational function fitting according to the frequency impedance data pair, and solve the coefficients based on the least square method to obtain the wideband impedance curve;

[0136] Quality detection module: analyze the wideband impedance curve, extract the quality characteristic parameters, and perform quality determination according to the quality characteristic parameters.

[0137] The above is only a specific embodiment of the present application, but the protection scope of the present application is not limited thereto, any skilled person in the art can easily think of changes or replacements within the technical range disclosed by the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

[0138] Finally: the above is only a preferred embodiment of the present application and is not used to limit the present application, any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.

Claims

1. A method for quality inspection of electrical automation systems, characterized in that, include: The raw voltage and current signals of the power grid's point of common coupling (PCC) are collected and subjected to fast Fourier transform to analyze and obtain the set of background harmonic frequencies and the set of background harmonic amplitudes. Preset the target scanning frequency band and generate an initial frequency grid at fixed intervals; A sparse frequency grid is generated based on the background harmonic frequency set and the initial frequency grid. The estimated signal-to-noise ratio of each candidate frequency in the sparse frequency grid is calculated and sorted in ascending order to obtain the injection sequence. The injection sequence is input into the control power amplifier to obtain the sinusoidal injection signal. The sinusoidal injection signal is injected into the PCC point through the current coupler. Simultaneously with the injection of a sinusoidal signal, the voltage response and total current at the PCC point are collected; the signal parameters corresponding to the sinusoidal injection signal are extracted, and the complex impedance is calculated based on the signal parameters to obtain frequency impedance data pairs. Based on the frequency impedance data, a rational function is fitted, and the coefficients are solved using the least squares method to obtain the broadband impedance curve. The broadband impedance curve is analyzed to extract quality characteristic parameters, and the quality is judged based on the quality characteristic parameters.

2. The electrical automation quality inspection method according to claim 1, characterized in that, Methods for obtaining background harmonic frequencies and background harmonic amplitudes include: The original voltage and current signals are preprocessed to obtain preprocessed voltage and current signals. Perform N-point Fast Fourier Transform on the preprocessed voltage and current signals respectively to obtain complex voltage and current frequency domain signals; The voltage amplitude spectrum and current amplitude spectrum are calculated by combining the voltage frequency domain signal and the current frequency domain signal with the signal gain and energy dispersion coefficient; The actual frequency corresponding to the m-th index is calculated based on the sampling rate and the number of sampling points N, and the frequency axis is obtained by counting all actual frequencies. The frequency corresponding to the spectral peak with the largest amplitude in the frequency axis is statistically extracted as the fundamental frequency; the voltage amplitude spectrum and current amplitude spectrum corresponding to the fundamental frequency are obtained as the fundamental voltage amplitude and fundamental current amplitude. Traverse the frequency axis to obtain all frequency points whose actual frequency is greater than twice the fundamental frequency as the frequencies to be sorted. Sort the frequencies to be sorted in ascending order that meet the screening conditions, and extract the corresponding frequencies and amplitudes to obtain the background harmonic frequency set and the corresponding harmonic amplitude set.

3. The electrical automation quality inspection method according to claim 2, characterized in that, The screening conditions include condition 1 and condition 2, wherein condition 1: the voltage amplitude of the frequency to be sorted is not lower than the harmonic voltage identification threshold or the current amplitude of the candidate frequency is not lower than the harmonic current identification threshold. Condition 2: Within the allowable deviation range, the frequency to be sorted is n times the fundamental frequency, where n is an integer not less than 2.

4. The electrical automation quality inspection method according to claim 1, characterized in that, Methods for generating sparse frequency grids include: The target scanning frequency band is divided according to a fixed interval to obtain an initial grid frequency set. The number of grid points is calculated based on the upper and lower limits of the target scanning frequency band and the fixed interval. Set an interference avoidance bandwidth. For each initial frequency in the initial grid frequency set, if the initial frequency point is within the interference avoidance bandwidth of the background harmonic frequency, then remove the corresponding initial frequency and construct a sparse frequency grid based on the remaining frequency points.

5. The electrical automation quality inspection method according to claim 1, characterized in that, Methods for obtaining the injection sequence include: The background noise amplitude is obtained by performing cubic spline interpolation on the harmonic spectrum of each candidate frequency in the sparse frequency grid. The estimated signal-to-noise ratio is calculated based on the preset effective value of the injected signal, the system calibration coefficient, and the background noise amplitude. The estimated signal-to-noise ratios are then sorted in ascending order to obtain the injection sequence.

6. The electrical automation quality inspection method according to claim 1, characterized in that, Methods for obtaining background noise amplitude include: Within each segmented interval, define a cubic spline interpolation function that satisfies the interpolation conditions; Construct the cubic interpolation function expression for each segmented interval; Establish a system of equations based on the interpolation conditions, solve for the coefficients of all segmented intervals, obtain the interpolation function for all segmented intervals, and obtain the continuous interpolation function. Traverse the frequency points of the sparse frequency grid to determine the segment interval where the candidate frequency is located; extract the corresponding segment interval and the corresponding interpolation coefficient; Substitute the candidate frequencies into the corresponding segmented cubic interpolation function to calculate the background noise amplitude.

7. The electrical automation quality inspection method according to claim 6, characterized in that, The interpolation conditions include: At the endpoints of the segmented interval, the interpolated value is equal to the original magnitude; The first and second derivatives are continuous at the junctions of piecewise intervals; Natural boundaries are used, meaning the second derivative values ​​at the two endpoints of the segmented interval are 0.

8. The electrical automation quality inspection method according to claim 1, characterized in that, Methods for obtaining frequency impedance data pairs include: A sinusoidal injection signal is calculated based on the injection sequence. This signal is then injected into the PCC point via a current coupler. Simultaneously, the voltage response and total current at the PCC point are acquired. The signal parameters corresponding to the sinusoidal injection signal are extracted, including the effective value of the voltage response, voltage phase, effective value of the total current, and current phase. The impedance phase is calculated based on the voltage and current phases. The complex impedance is then calculated by combining the effective value of the voltage response, the effective value of the total current, and the impedance phase. Finally, the data are spliced ​​together with the frequency to obtain frequency-impedance data pairs.

9. The electrical automation quality inspection method according to claim 1, characterized in that, The quality characteristic parameters include phase margin, gain margin, Nyquist distance, and maximum impedance at a specific frequency band; Methods for obtaining phase margin include: Traverse the wideband impedance curve to obtain the frequency corresponding to the impedance value of 1 as the amplitude crossover frequency, calculate the difference between the impedance phase at the amplitude crossover frequency and -180°, and obtain the phase margin. Methods for obtaining gain margin include: Traverse the wideband impedance curve to obtain the frequency corresponding to the impedance phase of -180° as the phase crossover frequency, calculate the negative logarithm of the impedance amplitude corresponding to the phase crossover frequency, and obtain the amplitude margin. Methods for obtaining the maximum impedance in a specific frequency band include: The impedance curve of the target frequency band is extracted from the continuous impedance curve. A discrete frequency sequence is obtained by sampling based on the sampling step size. Each frequency point in the discrete frequency sequence is substituted into the continuous impedance function to calculate the real and imaginary parts of the corresponding complex impedance. For each discrete frequency point, the corresponding amplitude is calculated based on the real and imaginary parts of the corresponding complex impedance. All NL discrete frequency points are traversed, where NL is the number of discrete frequency points, and the amplitude of each point is calculated to generate an impedance amplitude array for a specific frequency band. The maximum impedance amplitude is extracted from the impedance amplitude array as the maximum impedance value for the specific frequency band.

10. The electrical automation quality inspection method according to claim 1, characterized in that, Methods for obtaining the Nyquist distance include: Calculate the rated reference impedance, and then calculate the per-unit complex impedance using the continuous impedance function. The perimetric complex impedance is sampled within a preset frequency range with a frequency step size of [missing information]. Discrete sampling is performed to generate a discrete frequency sequence; each frequency point in the discrete frequency sequence is substituted into the calculation to obtain the corresponding per-unit complex impedance, and a discrete complex impedance array is obtained, which is then split to obtain the real part array and the imaginary part array. Construct a complex plane coordinate system with the real axis as the horizontal axis and the imaginary axis as the vertical axis, and draw the Nyquist curve by combining the real part array and the imaginary part array; For the g-th point in the discrete complex impedance array, calculate its Euclidean distance to the point (-1, j0). Iterate through all discrete complex impedance points, calculate the Euclidean distance for each point, generate a distance array, and take the minimum value in the distance array as the Nyquist distance.

11. The electrical automation quality inspection method according to claim 1, characterized in that, Methods for quality assessment include: If all quality characteristic parameters meet the following conditions: phase margin not lower than phase threshold, amplitude margin not lower than amplitude threshold, Nyquist distance not lower than distance threshold, and maximum impedance in a specific frequency band not higher than impedance threshold, then the quality is deemed qualified; otherwise, it is deemed unqualified, and the corresponding unqualified parameters and deviation values ​​are output.

12. An electrical automation quality inspection system, implementing the electrical automation quality inspection method according to any one of claims 1-11, characterized in that, include: Passive monitoring module: Collects raw voltage and current signals from the power grid's point of common coupling (PCC) and performs fast Fourier transform to analyze and obtain the set of background harmonic frequencies and the set of background harmonic amplitudes; Mesh generation module: Presets the target scanning frequency band and generates an initial frequency mesh at fixed intervals; A sparse frequency grid is generated based on the background harmonic frequency set and the initial frequency grid. Intelligent injection module: Calculates the estimated signal-to-noise ratio of each candidate frequency in the sparse frequency grid and sorts them in ascending order to obtain the injection sequence. The injection sequence is input into the control power amplifier to obtain a sinusoidal injection signal. The sinusoidal injection signal is injected into the PCC point through a current coupler. Data acquisition module: Simultaneously with the injection of a sinusoidal signal, it acquires the voltage response and total current at the PCC point; Extract the signal parameters corresponding to the sinusoidal injection signal, calculate the complex impedance based on the signal parameters, and obtain frequency impedance data pairs; Impedance calculation module: Fits rational functions to frequency impedance data and solves for coefficients using the least squares method to obtain wideband impedance curves; Quality Inspection Module: Analyzes wideband impedance curves, extracts quality characteristic parameters, and makes quality judgments based on these parameters.

Images