Optical storage direct flexible building power distribution and utilization system broadband data detection method

Abstract

The invention, which relates to the technical field of the electric power system, discloses a broadband data detection method for a power distribution and utilization system of an optical storage direct-flexible building, comprising the following steps: S1, acquiring signal data; the signal data is a current signal of the output end of the power distribution and utilization system of the optical storage direct flexible building; s2, performing windowing processing on the signal data to obtain a windowing signal; s3, performing discrete Fourier transform processing on the windowed signal to obtain a frequency spectrum function; s4, performing frequency spectrum calculation based on the frequency spectrum function by adopting a three-spectral-line interpolation algorithm to obtain a measurement parameter corresponding to the broadband current of the power distribution and utilization system; the measurement parameters comprise frequency, amplitude and phase. In order to reduce frequency spectrum leakage and a fence effect caused by Fourier transform, a frequency spectrum function is calculated by using a three-spectral-line interpolation algorithm, and broadband current measurement parameters of a power distribution and utilization system are obtained. Therefore, accurate identification of broadband current detection of the power distribution and utilization system can be realized.

Description

Technical Field

[0001] The present invention belongs to the technical field of power systems, and specifically relates to a broadband data detection method for a photovoltaic storage direct-current flexible building power distribution system. Background Art

[0002] "PV-storage-direct-flexible" buildings refer to new building distribution systems that meet the needs of carbon neutrality goals through photovoltaic power generation, energy storage, DC distribution and flexible energy use. PV-storage-direct-flexible buildings provide a solution for the sustainable development of the construction industry to efficiently utilize renewable energy and optimize energy consumption. The current involved is one of the most important state parameters in the power system. With the construction of new power systems, large-scale wind power, photovoltaics and other new energy sources will be quickly connected to the grid. The power grid has introduced a large number of harmonic components and DC components, and traditional power grid current sensing measurement technology faces challenges. The power grid morphology presents new features such as wide dynamics in the time and frequency domain and multiple parameters. The various current signals to be measured show characteristics such as wide frequency bandwidth, wide dynamic range of quantity value, and large amount of data. Higher requirements are put forward for the monitoring of various state quantities of the power system and its equipment, which brings challenges to the accurate perception of current in the power system.

[0003] Nowadays, synchronous measurement technologies including wide area measurement systems (WAMS) and phasor measurement units (PMUs) have covered most transmission networks and power plants, and have been widely used in the dynamic monitoring of broadband data of distribution and utilization systems of photovoltaic storage and direct flexible buildings, making it a promising platform for monitoring broadband data of distribution and utilization systems. In actual electricity, the signals measured by PMUs usually contain certain noise, which requires the analysis method to have high pattern resolution and noise resistance to perform broadband current detection in distribution and utilization systems. The Super Resolution Perception (SRP) technology of load data of distribution and utilization systems is used to improve its comprehensive perception capability, perform super-resolution perception of the power consumption data of distribution and utilization systems and the current data of transmission lines, and perform load identification on the power consumption data.

[0004] The existing broadband data detection methods for power distribution systems mainly include discrete Fourier transform (DFT), Prony algorithm, wavelet algorithm, artificial neural network algorithm, time-frequency domain method, etc. The Prony algorithm has a strong estimation ability for related parameters and can accurately identify broadband current parameters of power distribution systems, but it has the problem of large amount of calculation and requires prior knowledge of the model. The harmonic detection method based on wavelet analysis can effectively detect harmonic signals, but the amount of calculation is large, the real-time application is poor, and the calculation accuracy is affected by the wavelet basis function. The artificial neural network algorithm is difficult to construct training samples and the amount of calculation is also too large. Its accuracy is highly dependent on samples, and there is no standardized method for determining the number of samples, which is not in line with engineering practice. Time-frequency domain methods such as Ibrahim time-domain modal identification method have large amount of calculation, and serious edge trend effects will cause inaccurate decomposition. The most widely used method is the DFT algorithm, but the DFT algorithm has spectrum leakage and fence effect when the signal is non-periodicly sampled, which will make the measured parameters inaccurate. Summary of the invention

[0005] The purpose of the present invention is to address the above-mentioned problems and propose a method for detecting broadband data of a photovoltaic-storage-direct-flexible building power distribution system, which can realize accurate identification of broadband current detection of the power distribution system.

[0006] In a first aspect, the present application provides a method for detecting broadband data of a photovoltaic storage direct-flexible building power distribution system, comprising:

[0007] Acquire signal data; the signal data is a current signal at the output end of the photovoltaic storage direct-flexible building power distribution system;

[0008] Performing windowing processing on the signal data to obtain a windowed signal;

[0009] Performing discrete Fourier transform processing on the windowed signal to obtain a spectrum function;

[0010] A three-spectral line interpolation algorithm is used to perform spectrum calculation based on the spectrum function to obtain measurement parameters corresponding to the broadband current of the power distribution system; the measurement parameters include: frequency, amplitude and phase.

[0011] Optionally, performing windowing processing on the signal data to obtain a windowed signal specifically includes:

[0012] Performing mathematical modeling on the signal data by using a difference algorithm to obtain a signal mathematical model;

[0013] Performing discrete sampling processing on the signal data model based on a fixed sampling frequency to obtain discrete sampling signal data;

[0014] The discrete sampling signal data is subjected to windowing processing using an RV(1)-4 window function to obtain a windowed signal.

[0015] Optionally, the mathematical expression of the windowed signal is:

[0016] s w (n) = s(n)p(n);

[0017]

[0018] Among them, s w (n) is the mathematical expression of the windowed signal; s(n) is the discrete sampling signal data; A1 is the amplitude of the fundamental frequency component of the signal; f1 is the frequency of the fundamental frequency component of the signal; f c is a fixed sampling frequency; θ1 is the phase of the fundamental frequency component of the signal; A s f is the amplitude of the broadband current component of the power distribution system in the signal; s is the frequency of the broadband current component of the power distribution system in the signal; θ s is the phase of the broadband current component of the power distribution system in the signal; p(n) is the RV(1)-4 window function; N is the number of sampling points; n is the sampling point sequence number.

[0019] Optionally, performing discrete Fourier transform processing on the windowed signal to obtain a spectrum function specifically includes:

[0020] The windowed signal is subjected to discrete Fourier transform processing to obtain a transformed spectrum function; the expression of the transformed spectrum function is:

[0021]

[0022] Based on the transformed spectrum function, the negative spectrum is filtered out to obtain the spectrum function; the spectrum function is expressed as:

[0023]

[0024] Where S1(m) is the transformed spectrum function; A1 is the amplitude of the fundamental frequency component of the signal; j is the imaginary unit; θ1 is the phase of the fundamental frequency component of the signal; N is the number of sampling points; f1 is the frequency of the fundamental frequency component of the signal; f c is a fixed sampling frequency; A s is the amplitude of the broadband current component of the power distribution system in the signal; θ s f is the phase of the broadband current component of the power distribution system in the signal; s is the frequency of the broadband current component of the power distribution system in the signal; S(m) is the spectrum function; m is the sampling point number for discrete Fourier transform processing.

[0025] Optionally, a three-spectrum interpolation algorithm is used to perform spectrum calculation based on the spectrum function to obtain measurement parameters corresponding to the broadband current of the power distribution system, specifically including:

[0026] Determine a spectrum maximum point based on the spectrum function;

[0027] Based on the maximum value point of the spectrum, according to the maximum value solving method, a spectrum point set is determined within a set range;

[0028] Using a polynomial fitting method, based on the RV(1)-4 window function after Fourier transformation, the fitting coefficients are determined according to the spectrum point set;

[0029] Determining the measurement parameters according to the spectrum point set and the fitting coefficients;

[0030] The expression corresponding to the frequency is:

[0031]

[0032] The expression corresponding to the amplitude is:

[0033]

[0034] The expression corresponding to the phase is:

[0035] θ s =angle[S(m2)]-aπ;

[0036] Among them, m2 is the maximum spectrum point, m3 is the second largest spectrum point, m1 is the third largest spectrum point, S(m2) is the spectrum function corresponding to the maximum spectrum point m2; a is the first fitting coefficient, V(a) is the function of the first fitting coefficient a, angle is the operation of obtaining the phase angle to calculate the phase angle of the complex number, and N is a variable.

[0037] Optionally, the broadband data detection method of the photovoltaic storage direct-flexible building power distribution system further includes:

[0038] A three-spectrum interpolation algorithm is adopted to calculate the measurement parameters corresponding to the broadband currents of multiple power distribution systems based on the spectrum function.

[0039] In a second aspect, the present application provides a broadband data detection device for a photovoltaic storage direct-flexible building power distribution system, comprising:

[0040] A signal data acquisition module is used to acquire signal data; the signal data is a current signal at the output end of the photovoltaic storage direct-flexible building power distribution system;

[0041] A windowing processing module, used for performing windowing processing on the signal data to obtain a windowed signal;

[0042] A transform processing module, used for performing discrete Fourier transform processing on the windowed signal to obtain a spectrum function;

[0043] The spectrum calculation module is used to use a three-line interpolation algorithm to perform spectrum calculation based on the spectrum function to obtain measurement parameters corresponding to the broadband current of the power distribution system; the measurement parameters include: frequency, amplitude and phase.

[0044] In the third aspect, the present application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-mentioned method for detecting broadband data of a photovoltaic-storage-direct-flexible building power distribution system.

[0045] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-mentioned method for detecting broadband data of a photovoltaic-storage-direct-flexible building power distribution system.

[0046] In a fifth aspect, the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the above-mentioned method for detecting broadband data of a photovoltaic-storage-direct-flexible building power distribution system.

[0047] Compared with the prior art, the present invention has the following beneficial effects:

[0048] The present application provides a method for detecting broadband data of a photovoltaic storage direct-flexible building power distribution system. The method first collects the current signal at the output end of the photovoltaic storage direct-flexible building power distribution system, and then adds a Rife-Vincent (1)-4 window function, that is, an RV (1)-4 window function, to the signal for discrete Fourier transform to obtain a spectrum function. In order to reduce the spectrum leakage and fence effect caused by the Fourier transform, the spectrum function is calculated using a three-spectral line interpolation algorithm to obtain broadband current measurement parameters of the power distribution system. Therefore, the present application can realize accurate identification of broadband current detection of the power distribution system. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 This is a flow chart of a method for detecting broadband data in a photovoltaic-storage-direct-flexible building power distribution system;

[0050] Figure 2 It is a schematic diagram of the operation steps of the broadband data detection method of the photovoltaic storage direct flexible building power distribution system in practical application;

[0051] Figure 3 It is a schematic diagram of the time domain waveform of the signal;

[0052] Figure 4 is the spectrum diagram of the signal;

[0053] Figure 5This is a schematic diagram of the data comparison results of amplitude identification under noise-free conditions;

[0054] Figure 6 This is a schematic diagram of the data comparison results of frequency identification under noise-free conditions;

[0055] Figure 7 This is a schematic diagram of the data comparison results of phase identification under noise-free conditions;

[0056] Figure 8 This is a schematic diagram of the data comparison results of amplitude identification under 40dB noise conditions;

[0057] Fig. 9 This is a diagram showing the data comparison results of frequency identification under 40dB noise conditions;

[0058] Fig.10 This is a schematic diagram of the data comparison results of phase identification under 40dB noise conditions;

[0059] Fig.11 A schematic diagram of the structure of a computer device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0060] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific implementation method described herein is only an optimal embodiment of the present invention, which is only used to explain the present invention and does not limit the scope of protection of the present invention. All other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0061] Embodiment 1: Scholars around the world have studied a series of window functions and interpolation algorithms with superior performance. Commonly used window functions include Hanning window, Blackman window, Nuttall window, Rife-vincent window, etc. When selecting a window function, its main lobe and side lobe characteristics should be fully considered. Among them, Rife-vincent window has better main lobe and side lobe characteristics than other window functions, and has better effect in suppressing spectrum leakage. Commonly used interpolation algorithms mainly include dual-line interpolation algorithm and three-line interpolation algorithm, among which the three-line interpolation algorithm has higher accuracy than the dual-line interpolation algorithm.

[0062] like Figure 1 As shown, the present application provides a method for detecting broadband data of a photovoltaic storage direct-flexible building power distribution system, the method comprising:

[0063] Step 100: Acquire signal data. The signal data is a current signal at the output end of the photovoltaic storage direct-flexible building power distribution system.

[0064] Step 200: Perform windowing processing on signal data to obtain a windowed signal.

[0065] Step 300: Perform discrete Fourier transform processing on the windowed signal to obtain a spectrum function.

[0066] Step 400: Using a three-spectrum interpolation algorithm, spectrum calculation is performed based on a spectrum function to obtain measurement parameters corresponding to the broadband current of the power distribution system. The measurement parameters include: frequency, amplitude and phase.

[0067] In one embodiment, performing windowing processing on the signal data to obtain a windowed signal specifically includes:

[0068] The signal data is mathematically modeled using a difference algorithm to obtain a signal mathematical model.

[0069] The signal data model is discretely sampled based on a fixed sampling frequency to obtain discrete sampled signal data.

[0070] The discrete sampling signal data is windowed using the RV(1)-4 window function to obtain a windowed signal.

[0071] Specifically, the mathematical expression of the windowed signal is:

[0072] s w (n) = s(n)p(n);

[0073]

[0074] Among them, s w (n) is the mathematical expression of the windowed signal; s(n) is the discrete sampling signal data; A1 is the amplitude of the fundamental frequency component of the signal; f1 is the frequency of the fundamental frequency component of the signal; f c is a fixed sampling frequency; θ1 is the phase of the fundamental frequency component of the signal; A s f is the amplitude of the broadband current component of the power distribution system in the signal; s is the frequency of the broadband current component of the power distribution system in the signal; θ s is the phase of the broadband current component of the power distribution system in the signal; p(n) is the RV(1)-4 window function; N is the number of sampling points; n is the sampling point sequence number.

[0075] In one embodiment, the windowed signal is subjected to discrete Fourier transform processing to obtain a spectrum function, which specifically includes:

[0076] The windowed signal is processed by discrete Fourier transform to obtain the transformed spectrum function; the expression of the transformed spectrum function is:

[0077]

[0078] Based on the transformed frequency spectrum function, filter out the negative frequency spectrum to obtain the frequency spectrum function. The expression of the frequency spectrum function is as follows:

[0079]

[0080] where S1(m) is the transformed frequency spectrum function; A1 is the amplitude of the fundamental frequency component of the signal; j is the imaginary unit; θ1 is the phase of the fundamental frequency component of the signal; N is the number of sampling points; f1 is the frequency of the fundamental frequency component of the signal; f c is the fixed sampling frequency; A s is the amplitude of the broadband current component in the power distribution and utilization system of the signal; θ s is the phase of the broadband current component in the power distribution and utilization system of the signal; f s is the frequency of the broadband current component in the power distribution and utilization system of the signal; S(m) is the frequency spectrum function; m is the sampling point sequence number for discrete Fourier transform processing.

[0081] In one embodiment, the three-spectrum line interpolation algorithm is adopted to perform spectrum calculation based on the frequency spectrum function to obtain the measurement parameters corresponding to the broadband current of the power distribution and utilization system, specifically including:

[0082] Determine the frequency spectrum maximum point m' based on the frequency spectrum function; based on the frequency spectrum maximum point, determine the frequency spectrum point set within a set range according to the maximum value solving method; the frequency spectrum point set includes the maximum frequency spectrum point m2, the second largest frequency spectrum point m3, and the third largest frequency spectrum point m1; where m3 = m2 + 1; m1 = m2 - 1.

[0083] Adopt the method of polynomial fitting. Based on the RV(1)-4 window function after Fourier transform, determine the fitting coefficients according to the frequency spectrum point set; the fitting coefficients include: the first fitting coefficient a and the second fitting coefficient b; a = m' - m2; -0.5 < b < 0.5; let y1 = |S(m2 - 1)|, y2 = |S(m2)|, y3 = |S(m2 + 1)|, then The essence of the formula is that b is a function of a, denoted as b = x(a). Obtain its inverse function a = x -1 (b) by the method of polynomial fitting. When the coefficient of the window function p(n) is a real number, its Fourier transform P(2πf) is an even function, so the above inverse function and its function are both odd functions. Therefore, a = x -1 (b) only has odd-order terms. Obtain the coefficients of the inverse function by the polyfit(b, a, k) function in the MATLAB software, and then the expression of the inverse function a = x -1 (b) can be obtained, that is, the method of polynomial approximation, where k is the number of terms of the fitting polynomial; let Similarly, a and V(a) can be obtained. S(m2-1) is the spectrum function corresponding to the third largest spectrum point; S(m2) is the spectrum function corresponding to the maximum spectrum point; S(m2+1) is the spectrum function corresponding to the second largest spectrum point; y1 is the function value corresponding to S(m2-1); y2 is the function value corresponding to S(m2); y3 is the function value corresponding to S(m2+1). P(m3-m), P(m1-m), P(m2-m), P(1-a), P(-1-a) and P(-a) are all window functions after the variable n is replaced accordingly.

[0084] The measurement parameters are determined based on the spectrum point set and the fitting coefficients.

[0085] The expression corresponding to the frequency is:

[0086]

[0087] The expression corresponding to the amplitude is:

[0088]

[0089] The expression corresponding to the phase is:

[0090] θ s =angle[S(m2)]-aπ;

[0091] Among them, f s f is the frequency of the broadband current component of the power distribution system in the signal; c is a fixed sampling frequency; N is the number of sampling points; A s is the amplitude of the broadband current component of the power distribution system in the signal; θ s is the phase of the broadband current component of the power distribution system in the signal; S(m2) is the spectrum function corresponding to the maximum spectrum point m2; angle is the operation for obtaining the phase angle, to calculate the phase angle of the complex number.

[0092] As an optional implementation method, the broadband data detection method of the photovoltaic storage direct-flexible building power distribution system also includes:

[0093] The three-spectrum interpolation algorithm is adopted to calculate the measurement parameters corresponding to the broadband current of multiple power distribution systems based on the spectrum function.

[0094] In practical applications, such as Figure 2 As shown, the specific operation steps of the method mentioned in this application are as follows:

[0095] Step 1: Collect the current signal at the output end of the solar-storage direct-flexible building power distribution system.

[0096] Step 2: Perform windowing processing on the current signal to obtain a windowed signal.

[0097] 2.1. Model the broadband current signal of the power distribution system, derive the interpolation algorithm formula of the current signal, and the modeled signal, that is, the corresponding signal mathematical model is:

[0098] s(t)=A1 cos(2πf1t+θ1)+A s cos(2πf s t+θ s )(1)

[0099] Using PMU with fixed sampling frequency f c Sampling is performed, and the discretely sampled current signal is:

[0100]

[0101] Among them, A1 is the amplitude of the fundamental frequency component of the signal; f1 is the frequency of the fundamental frequency component of the signal; θ1 is the phase of the fundamental frequency component of the signal; A s f is the amplitude of the broadband current component of the power distribution system in the signal; s is the frequency of the broadband current component of the power distribution system in the signal; θ s It is the phase of the broadband current component of the power distribution system in the signal.

[0102] 2.2. Let p(n) be the RV(1)-4 window function, and add window to the sampled signal to obtain s w (n) = s(n)p(n), s w (n) is the windowed function, that is, the mathematical expression of the windowed signal.

[0103] Step 3: Based on the windowed signal in step 2, perform discrete Fourier transform on the windowed signal and ignore the influence of the negative spectrum to obtain the spectrum function.

[0104] 3.1. Perform discrete Fourier transform on the windowed signal to obtain the spectrum function:

[0105]

[0106] Where m = 0, 1, N-1, N is the number of sampling points; j is the imaginary unit;

[0107] 3.2. Ignore the influence of negative spectrum:

[0108]

[0109] Step 4: Calculate the spectrum of the spectrum function in step 3 using a three-line interpolation algorithm.

[0110] 4.1. Assume that the maximum spectral point sampled near the maximum spectral point m' is point m2, which can be located by solving for the maximum value. The second largest spectral point on the right is point m3 = m2 + 1, and the third largest spectral point on the left is m1 = m2 - 1. Obviously, m2 - 1 < m2 < m2 + 1. Let a = m' - m2, and b satisfies -0.5 < b < 0.5. Let y1 = |S(m2 - 1)|, y2 = |S(m2)|, y3 = |S(m2 + 1)|. Let:

[0111]

[0112] Calculate the value of b as:

[0113]

[0114] The essence of formula (6) is that b is a function of a, denoted as b = x(a). The inverse function a = x -1 (b) is obtained by the method of polynomial fitting. When the coefficients of the window function p(n) are real numbers, its Fourier transform P(2πf) is an even function. Therefore, both the above inverse function and its function are odd functions. So a = x -1 (b) only has odd-order terms. The coefficients of the inverse function can be obtained by the polyfit(b, a, k) function in the MATLAB software, and then the expression of the inverse function a = x -1 (b) can be obtained, which is the method of polynomial approximation, where k is the number of terms of the fitting polynomial.

[0115] 4.2. Calculate the frequency of the broadband current signal of the power distribution and utilization system.

[0116]

[0117] 4.3. Calculate the amplitude of the broadband current signal of the power distribution and utilization system.

[0118] m2 is the spectral line with the largest amplitude. Therefore, when calculating the weighted average of the three spectral lines, it is given the largest weighting ratio of 2. From formula (4) and by transposing, we can get:

[0119]

[0120] Let:

[0121]

[0122] Obtain V(a) that only contains even-order terms by the method of polynomial fitting, and calculate the amplitude of the current signal as:

[0123]

[0124] 4.4. Calculate the phase of the broadband current signal of the power distribution and utilization system.

[0125] θ s =angle[S(m2)]-aπ(11)

[0126] 4.5. Calculate the interpolation fitting formula based on the RV(1)-4 window.

[0127] The expression of RV(1)-4 window is:

[0128]

[0129] Its Fourier transform is:

[0130]

[0131] In the formula, A0 represents the average value component, A 1、 A2 and A3 represent the complex amplitudes of harmonic components of different frequencies.

[0132] The polynomial fitting method can be used to derive the polynomial coefficients of a and V(a), and then the fitting formula of the RV(1)-4 window is obtained as follows:

[0133] a=0.666287b-0.07398320b 3 +0.01587358b 5 -0.00311639b 7 (14)

[0134] V(a)=1.333333327+0.5265879a 2 +0.00699742a 4 +0.02103885a 6 (15)

[0135] 4.6. Correction formula for calculating broadband current components in multi-distribution power systems.

[0136] When the signal contains broadband current components of multiple power distribution systems, equation (1) can be expanded to:

[0137]

[0138] A si , f si ,θ si are the amplitude, frequency and phase of the broadband current component of the i-th power distribution system. The principle of three-point interpolation is to find the three maximum spectral lines near the target frequency, of which the maximum value can be obtained by locating the maximum value. Therefore, when the signal contains broadband current components of multiple power distribution systems, the three-point interpolation method uses formula (5)-formula (15) to calculate the frequency, amplitude and phase of the broadband current components of multiple power distribution systems, which are expressed as follows:

[0139]

[0140] θ si =angle[S(m 2i )]-a i π(19)

[0141]

[0142] Where m 2i is the position of the maximum spectral line of the broadband current component of the ith power distribution system in the spectrum, m 1i is the position of the spectrum line to the left of the i-th maximum spectrum line, m 3i is the position of the spectrum line to the right of the i-th maximum spectrum line; b i Can be b i =(|S(m 2i -1)|-|S(m 2i +1)|) / |S(m 2i )| is obtained. Finally, the frequency, amplitude and phase angle of the broadband current of the power distribution system are obtained.

[0143] This application first collects the current signal at the output end of the photovoltaic storage direct-flexible building power distribution system, then adds the Rife-Vincent (1)-4 window function to the signal for discrete Fourier transform to obtain the spectrum function. In order to reduce the spectrum leakage and fence effect caused by the Fourier transform, the three-spectral line interpolation algorithm is used to calculate the spectrum function to obtain the broadband current measurement parameters of the power distribution system. This application has the following beneficial effects:

[0144] (1) It can accurately detect the broadband current of the power distribution system, and increase the identification range of the broadband current component of the power distribution system to signals above 50 Hz. The identification frequency band obtained by this method is wide and the measurement accuracy is high.

[0145] (2) Taking the influence of noise into consideration, the algorithm still has high accuracy in identifying broadband current components in multi-distribution power systems.

[0146] (3) It provides a good data basis for studying the generation mechanism of broadband current components in new photovoltaic storage and direct-flexible building power distribution systems, and is also of reference value for the study of control strategies.

[0147] In practical applications, parameter identification of broadband current detection in a power distribution system is performed on an example signal whose operating frequency is a non-nominal frequency of 49.7 Hz as shown in Table 1.

[0148] Table 1: Example signal parameter table for non-nominal frequency 49.7 Hz operating frequency

[0149]

[0150]

[0151] The time domain waveform of the signal is Figure 3 As shown, it is similar to the collection of broadband current components of the power distribution system. Figure 4 It is the spectrum diagram of the signal, and the raised part of the graph is the broadband current oscillation component of the power distribution system.

[0152] Figure 5 , Figure 6 and Figure 7 The data comparison results of the identification of broadband current components of multi-distribution power system under noise-free conditions using RV(1)-4 window, Hanning window, RV(1)-3 window, Blackman-Harris window and Nuttall(1)-4 are shown in Figure 2. It can be seen that the parameter identification error using RV(1)-4 window is the smallest, and the amplitude identification error can reach 10 -7 %, the frequency identification error can reach 10 -13 %, the phase identification error can reach 10 -10 %.

[0153]

[0154] h' is the calculated value of the parameter, h is the theoretical value of the parameter, and η is the relative error of parameter identification. Table 2 shows the relative error values ​​of RV(1)-4 window identification.

[0155] Table 2 Relative error value table

[0156]

[0157] In order to verify the recognition accuracy of the algorithm under noisy conditions, the signal-to-noise ratio SNR is introduced:

[0158]

[0159] where σ 2 is the variance of Gaussian white noise. Figure 8 , Fig. 9 and Fig.10 The data comparison results of the identification of broadband current components of multi-distribution power system under 40dB noise conditions using RV(1)-4 window, Hanning window, RV(1)-3 window, Blackman-Harris window and Nuttall(1)-4 are shown in Figure 2. It can be seen that the parameter identification error using RV(1)-4 window is the smallest, and the amplitude identification error can reach 10 -4 %, the frequency identification error can reach 10 -6 %, the phase identification error can reach 10 -4 %.

[0160] Table 3 Relative identification error of the algorithm for the signal under 40dB noise

[0161]

[0162]

[0163] Based on the same inventive concept, the embodiment of the present application also provides a photovoltaic storage direct flexible building power distribution system broadband data detection device for implementing the photovoltaic storage direct flexible building power distribution system broadband data detection method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more photovoltaic storage direct flexible building power distribution system broadband data detection device embodiments provided below can refer to the limitations of the photovoltaic storage direct flexible building power distribution system broadband data detection method above, and will not be repeated here.

[0164] In an exemplary embodiment, a broadband data detection device for a photovoltaic storage direct-flexible building power distribution system is provided, comprising:

[0165] A signal data acquisition module is used to acquire signal data; the signal data is a current signal at the output end of the photovoltaic storage direct-flexible building power distribution system;

[0166] A windowing processing module, used for performing windowing processing on the signal data to obtain a windowed signal;

[0167] A transform processing module, used for performing discrete Fourier transform processing on the windowed signal to obtain a spectrum function;

[0168] The spectrum calculation module is used to use a three-line interpolation algorithm to perform spectrum calculation based on the spectrum function to obtain measurement parameters corresponding to the broadband current of the power distribution system; the measurement parameters include: frequency, amplitude and phase.

[0169] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Fig.11As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a broadband data detection method for a photovoltaic storage direct-flexible building power distribution system is implemented.

[0170] Those skilled in the art will understand that Fig.11 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0171] In an exemplary embodiment, a computer device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

[0172] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0173] In an exemplary embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0174] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0175] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0176] The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on blockchain, etc., but is not limited thereto. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but is not limited thereto.

Claims

1. A broadband data detection method for a photovoltaic storage direct-flexible building power distribution system, characterized in that: The steps include: S1. Acquire signal data; the signal data is a current signal at the output end of the photovoltaic storage direct-flexible building power distribution system; S2, performing windowing processing on the signal data to obtain a windowed signal; S3, performing discrete Fourier transform processing on the windowed signal to obtain a spectrum function; S4. Using a three-spectral line interpolation algorithm, perform spectrum calculation based on the spectrum function to obtain measurement parameters corresponding to the broadband current of the power distribution system; the measurement parameters include frequency, amplitude and phase.

2. According to claim 1, a broadband data detection method for a photovoltaic storage and direct-flexible building power distribution system is characterized in that: The S2 comprises the following steps: S21, using a difference algorithm to perform mathematical modeling on the signal data to obtain a signal mathematical model; S22, performing discrete sampling processing on the signal data model based on a fixed sampling frequency to obtain discrete sampling signal data; S23, using RV(1)-4 window function to perform windowing processing on the discrete sampling signal data to obtain a windowed signal.

3. According to claim 2, a broadband data detection method for a photovoltaic storage and direct-flexible building power distribution system is characterized in that: The mathematical expression of the windowed signal is specifically expressed as follows: s w (n)=s(n)p(n); Among them, s w (n) is the mathematical expression of the windowed signal; s(n) is the discrete sampling signal data; A1 is the amplitude of the fundamental frequency component of the signal; f1 is the frequency of the fundamental frequency component of the signal; f c is a fixed sampling frequency; θ1 is the phase of the fundamental frequency component of the signal; A s f is the amplitude of the broadband current component of the power distribution system in the signal; s is the frequency of the broadband current component of the power distribution system in the signal; θ s is the phase of the broadband current component of the power distribution system in the signal; p(n) is the RV(1)-4 window function; N is the number of sampling points; n is the sampling point sequence number.

4. According to claim 1, a method for detecting broadband data of a photovoltaic storage and direct-flexible building power distribution system, characterized in that: The S3 comprises the following steps: S31, performing discrete Fourier transform processing on the windowed signal to obtain a transformed spectrum function; Among them, the expression of the transformed spectrum function is: S32, based on the transformed spectrum function, filtering out the negative spectrum to obtain the spectrum function; Wherein, the expression of the spectrum function is: Where S1(m) is the transformed spectrum function; A1 is the amplitude of the fundamental frequency component of the signal; j is the imaginary unit; θ1 is the phase of the fundamental frequency component of the signal; N is the number of sampling points; f1 is the frequency of the fundamental frequency component of the signal; f c is a fixed sampling frequency; A s is the amplitude of the broadband current component of the power distribution system in the signal; θ s f is the phase of the broadband current component of the power distribution system in the signal; s is the frequency of the broadband current component of the power distribution system in the signal; S(m) is the spectrum function; m is the sampling point number for discrete Fourier transform processing.

5. According to claim 1, a method for detecting broadband data of a photovoltaic storage and direct-flexible building power distribution system, characterized in that: The S4 comprises the following steps: S41, determining a spectrum maximum point based on the spectrum function; S42, based on the maximum value point of the spectrum, according to the maximum value solving method, determine a spectrum point set within a set range; S43, using a polynomial fitting method, based on the RV(1)-4 window function after Fourier transformation, to determine fitting coefficients according to the spectrum point set; S44, determining the measurement parameters according to the spectrum point set and the fitting coefficient; The expression corresponding to the frequency is: The expression corresponding to the amplitude is: The expression corresponding to the phase is: i s =angle[S(m2)]-aπ; Among them, m2 is the maximum spectrum point, m3 is the second largest spectrum point, m1 is the third largest spectrum point, S(m2) is the spectrum function corresponding to the maximum spectrum point m2; a is the first fitting coefficient, V(a) is the function of the first fitting coefficient a, angle is the operation of obtaining the phase angle to calculate the phase angle of the complex number, and N is a variable.

6. According to claim 1, a method for detecting broadband data of a photovoltaic storage and direct-flexible building power distribution system, characterized in that: Also includes: A three-spectrum interpolation algorithm is adopted to calculate the measurement parameters corresponding to the broadband currents of multiple power distribution systems based on the spectrum function.

7. A broadband data detection device for a photovoltaic storage and direct-flexible building power distribution system, characterized in that: The device comprises: A signal data acquisition module is used to acquire signal data; the signal data is a current signal at the output end of the photovoltaic storage direct-flexible building power distribution system; A windowing processing module, used for performing windowing processing on the signal data to obtain a windowed signal; A transform processing module, used for performing discrete Fourier transform processing on the windowed signal to obtain a spectrum function; The spectrum calculation module is used to use a three-line interpolation algorithm to perform spectrum calculation based on the spectrum function to obtain measurement parameters corresponding to the broadband current of the power distribution system; the measurement parameters include: frequency, amplitude and phase.

8. A computer device, characterized in that: The computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the broadband data detection method for a photovoltaic-storage direct-flexible building power distribution system described in any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for detecting broadband data of a photovoltaic-storage-direct-flexible building power distribution system according to any one of claims 1 to 6 is implemented.

10. A computer program product, characterized in that The computer program product includes a computer program, and when the computer program is executed by a processor, it implements the broadband data detection method for the photovoltaic storage and direct-flexible building power distribution system according to any one of claims 1 to 6.

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