Harmonic detection method, system and device for large-scale charging and discharging station and medium

Abstract

The application discloses a kind of large-scale charging and discharging station-oriented harmonic detection method, system, equipment and medium, method includes: according to the sampling signal of large-scale charging and discharging station, obtain its discretization signal;The windowing processing is carried out to the discretization signal, and obtains windowed signal;Wherein, for low-order harmonic signal in discretization signal, using window function carries out windowing processing;For high-order harmonic signal in discretization signal, using convolution window carries out windowing processing;The discrete Fourier transform is carried out to the windowed signal, and obtains discrete frequency spectrum;According to the discrete frequency spectrum at fundamental wave, the amplitude, frequency and phase of signal are obtained.The present application improves the traditional harmonic detection technology using window function theory, solves the influence of spectral leakage on harmonic detection accuracy, improves the accuracy of harmonic detection in large-scale charging and discharging station.

Description

Technical Field

[0001] This invention belongs to the field of power system power quality analysis, and specifically relates to a harmonic detection method, system, equipment and medium for large-scale charging and discharging stations. Background Technology

[0002] With the rapid development of the electric vehicle industry, the construction of large-scale charging and discharging stations, a crucial means of achieving efficient power consumption and bidirectional interaction between power sources and loads for large-scale electric vehicles, will become more widespread and intensive. The ultra-fast charging piles and high-power battery stacks centrally deployed in these large stations are prone to a series of harmonic problems, such as increased harmonic content and harmonic distortion, under high-frequency charging and discharging operations. Furthermore, existing harmonic research mainly focuses on the simulation analysis of the harmonic characteristics of charging facilities. However, the results of simulation analysis differ significantly from actual results and cannot accurately reflect the actual situation of charging stations; research based on actual measurement data is still needed. Therefore, selecting appropriate window functions based on measured data from large stations to accurately detect different types of harmonics is a crucial foundation for studying their propagation characteristics and effective mitigation, which will help accelerate the construction and development of electric vehicle charging infrastructure and improve the power supply quality of charging and discharging stations.

[0003] There are currently some reports on harmonic detection. One approach involves combining a Gaussian random measurement matrix with a window function at the sampling end to construct a sparse window measurement matrix for windowed compression sampling of the harmonic signal. However, due to the wide main lobe width of the window function, its resolution for ultra-high-order harmonics is insufficient, easily leading to spectral aliasing and an inability to accurately distinguish the frequency and amplitude of adjacent harmonics. Simultaneously, sidelobe leakage can mask the spectral peaks of low-amplitude high-order harmonics, further increasing the detection error of harmonic amplitude and phase. Another approach involves sampling dynamic harmonic signals to obtain the required time-domain sequence; then using a convolutional window to truncate the sampled discrete sequence to obtain the required windowed signal; finally, performing a Fast Fourier Transform on the windowed truncated signal to obtain the signal's spectral information. This processing scheme increases the computation time for low-order harmonic signal analysis, which is not conducive to applications in real-time harmonic monitoring scenarios in power distribution networks.

[0004] Therefore, there is a need to find a window function harmonic detection method for large-scale charging and discharging stations, which led to this case. Summary of the Invention

[0005] The purpose of this invention is to provide a harmonic detection method, system, equipment, and medium for large-scale charging and discharging stations. It improves traditional harmonic detection technology by utilizing window function theory, solves the impact of spectrum leakage on harmonic detection accuracy, and improves the accuracy of harmonic detection in large-scale charging and discharging stations.

[0006] To achieve the above objectives, the solution of the present invention is:

[0007] A harmonic detection method for large-scale charging and discharging stations includes:

[0008] Based on the sampled signals of the large-scale charging and discharging station, its discretized signal is obtained;

[0009] The discretized signal is windowed to obtain a windowed signal; wherein, for low-order harmonic signals in the discretized signal, a window function is used for windowing; and for high-order harmonic signals in the discretized signal, a convolution window is used for windowing.

[0010] Perform a discrete Fourier transform on the windowed signal to obtain the discrete spectrum;

[0011] The amplitude, frequency, and phase of the signal are obtained from the discrete spectrum at the fundamental frequency.

[0012] The discrete signal is windowed to obtain a windowed signal, including:

[0013] For the discretized signal Add a rectangular window Receive windowing signal .

[0014] For low-order harmonic signals in the discretized signal, windowing is performed using a window function, including:

[0015] For low-order harmonic signals in discretized signals, the Nuttall window function is used. Windowing is applied, and the time-domain representation of the Nuttall window function is as follows:

[0016] ,

[0017] in, The number of terms in the window function; , This represents the total number of sampling points; Satisfy constraints and .

[0018] For higher harmonic signals in the discretized signal, a convolution window is used for windowing processing, including:

[0019] Nuttall window function Perform temporal convolution operations to obtain the convolution window. ,in, This represents the number of Nuttall windows participating in the convolution.

[0020] A harmonic detection system for large-scale charging and discharging stations includes:

[0021] The signal discretization module is configured to obtain the discretized signal based on the sampled signal of the large charging and discharging station;

[0022] The signal windowing module is configured to perform windowing processing on the discretized signal to obtain a windowed signal; wherein, for low-order harmonic signals in the discretized signal, a window function is used for windowing processing; and for high-order harmonic signals in the discretized signal, a convolution window is used for windowing processing.

[0023] The discrete transform module is configured to perform a discrete Fourier transform on the windowed signal to obtain a discrete spectrum; and,

[0024] The harmonic parameter acquisition module is configured to obtain the amplitude, frequency, and phase of the signal based on the discrete spectrum at the fundamental frequency.

[0025] The signal windowing module performs windowing processing on the discretized signal to obtain a windowed signal, including:

[0026] For the discretized signal Add a rectangular window Receive windowing signal .

[0027] The signal windowing module uses a window function to window low-order harmonic signals in the discretized signal, including:

[0028] For low-order harmonic signals in discretized signals, the Nuttall window function is used. Windowing is applied, and the time-domain representation of the Nuttall window function is as follows:

[0029] ,

[0030] in, The number of terms in the window function; , This represents the total number of sampling points; Satisfy constraints and .

[0031] The signal windowing module uses a convolution window to window higher harmonic signals in the discretized signal, including:

[0032] Nuttall window function Perform temporal convolution operations to obtain the convolution window. ,in, This represents the number of Nuttall windows participating in the convolution.

[0033] A 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, it implements the steps of the harmonic detection method for large-scale charging and discharging stations as described above.

[0034] A computer-readable storage medium storing a computer program; when executed by a processor, the computer program implements the steps of the harmonic detection method for large-scale charging and discharging stations as described above.

[0035] After adopting the above scheme, this invention, based on the principle of harmonic detection method according to window function theory, analyzes the performance and spectral characteristics of various window functions, and selects the Nuttall window function with small sidelobe peak level and large sidelobe asymptotic decay rate to optimize the spectral characteristics. For higher harmonics, by performing time-domain self-convolution operation on the original Nuttall window function, a convolution window is established on the basis of the original window function, further improving the performance of the window function and greatly improving the detection effect of harmonics in large charging and discharging stations.

[0036] Compared to existing technologies, the beneficial effects of this invention are as follows: the four-term 3rd-order Nuttall windows have ideal sidelobe characteristics, effectively reducing spectral leakage of low-order harmonics. The spectral characteristics of the Nuttall self-convolution window are even better than those of the Nuttall window. As the convolution order increases, the sidelobe peak value of the Nuttall self-convolution window decreases rapidly, and the sidelobe attenuation rate increases rapidly, which can more effectively suppress spectral leakage of high-order harmonics. Attached Figure Description

[0037] Figure 1 This is a flowchart of the harmonic detection method of the present invention;

[0038] Figure 2 This is a measured current signal diagram from a power station in Wuxi. Detailed Implementation

[0039] This invention provides a harmonic detection method for large-scale charging and discharging stations, comprising:

[0040] Based on the sampled signals of the large-scale charging and discharging station, its discretized signal is obtained;

[0041] The discretized signal is windowed to obtain a windowed signal; wherein, for low-order harmonic signals in the discretized signal, a window function is used for windowing; and for high-order harmonic signals in the discretized signal, a convolution window is used for windowing.

[0042] Perform a discrete Fourier transform on the windowed signal to obtain the discrete spectrum;

[0043] The amplitude, frequency, and phase of the signal are obtained from the discrete spectrum at the fundamental frequency.

[0044] This invention also provides a harmonic detection system for large-scale charging and discharging stations, comprising:

[0045] The signal discretization module is configured to obtain the discretized signal based on the sampled signal of the large charging and discharging station;

[0046] The signal windowing module is configured to perform windowing processing on the discretized signal to obtain a windowed signal; wherein, for low-order harmonic signals in the discretized signal, a window function is used for windowing processing; and for high-order harmonic signals in the discretized signal, a convolution window is used for windowing processing.

[0047] The discrete transform module is configured to perform a discrete Fourier transform on the windowed signal to obtain a discrete spectrum; and,

[0048] The harmonic parameter acquisition module is configured to obtain the amplitude, frequency, and phase of the signal based on the discrete spectrum at the fundamental frequency.

[0049] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0050] like Figure 1 As shown, this invention proposes a harmonic detection method for large-scale charging and discharging power stations, comprising: acquiring measured voltage and current signals from the large power station; analyzing the principle of the harmonic detection method based on window function theory; for low-order harmonics in the power station, optimizing the spectral characteristics by selecting a Nuttall window function with small sidelobe peak levels and large sidelobe asymptotic decay rates; for high-order harmonics, establishing a convolution window based on the original Nuttall window function through time-domain convolution operations for detection.

[0051] Harmonic detection methods based on window function theory, in the traditional harmonic detection process, are equivalent to adding a rectangular window during signal truncation, as follows:

[0052] (1) Given signal Discretization yields:

[0053]

[0054] In the formula, For amplitude, . For the frequency of the signal, The initial phase of the signal. The sampling period of the signal; , This represents the total number of sampling points.

[0055] (2) Window the signal by adding a rectangular window. The windowed signal then becomes:

[0056]

[0057] In the formula, This is the discrete expression for a rectangular window.

[0058] (3) Perform a discrete Fourier transform to obtain the discrete spectrum:

[0059]

[0060] In the formula, Here is the spectral expression for the rectangular window function; ω is the angular frequency of the signal.

[0061] (4) Calculate the harmonic parameters. If If it is an integer, then That is, the sequence spectrum A spectral value, and has Therefore, by The amplitude, frequency, and phase of a signal can be obtained using the following formulas:

[0062]

[0063]

[0064]

[0065] In low-order harmonic detection, the sidelobe level and asymptotic decay rate of the window function directly affect the harmonic analysis results. Larger sidelobes indicate greater leakage, while faster sidelobe decay strengthens leakage suppression. Traditional FFT harmonic detection methods, during signal truncation, are equivalent to applying a rectangular window with a sidelobe peak level of -13dB and an asymptotic decay rate of 6dB / oct. In large power stations, the amplitude of low-order harmonics below the 11th order is generally less than 1% of the fundamental frequency, meaning the amplitude attenuation is less than -40dB. If traditional harmonic detection methods are used directly for spectral analysis, the -13dB sidelobes will overwhelm the actual -40dB harmonic signal, affecting the accuracy of low-order harmonic analysis. To reduce spectral leakage, a Nuttall window function with a small sidelobe peak level and a large asymptotic decay rate should be selected for signal processing.

[0066] The Nuttall window, which exhibits good sidelobe performance, is a cosine combination window, and its time-domain representation is as follows:

[0067]

[0068] In the formula, The number of terms in the window function; ; The constraints should be met. , .

[0069] The discrete Fourier transform (DFT) of the Nuttall window is:

[0070]

[0071] In the formula, Angular frequency; This is the spectral expression for the rectangular window function.

[0072] In general, N >> 1, and the discrete Fourier transform expression of the Nuttall window can be simplified to:

[0073]

[0074] Among different cosine combination windows, the four-term third-order Nuttall window exhibits the most ideal sidelobe characteristics, with a sidelobe asymptotic decay rate of 30 dB / oct and a sidelobe peak level reaching −83 dB. Therefore, the four-term third-order Nuttall window is used to detect the low-order harmonics of the input signal.

[0075] For high-order harmonic detection, the four 3rd-order Nuttall windows used in low-order harmonic detection are subjected to p-order self-convolution operations to obtain the Nuttall self-convolution window, and then high-order harmonic analysis is performed.

[0076] Nuttall self-convolution windows, obtained by performing self-convolution operations on several Nuttall windows, can be represented as:

[0077]

[0078] In the formula, The number of Nuttall windows participating in the convolution is called the order of the Nuttall self-convolution window.

[0079] If the Nuttall window length is ,but The order of the Nuttall self-convolution window is According to the convolution theorem, convolution of functions in the time domain is equivalent to multiplication in the frequency domain. Therefore... Nuttall self-convolution window The frequency response is: .

[0080] With the main lobe width remaining constant, the convolution order increases. As the number of sidelobes increases, the peak level of the Nuttall self-convolution window also increases. The sidelobe attenuation rate decreases rapidly with the increase of [missing information], and the sidelobe attenuation It increases rapidly with the increase of [something]. Its sidelobe peak level ([something]) ), sidelobe decay rate ( ) and convolution order The following approximate relationship exists: ; .

[0081] Among them, the sidelobe level of the second-order Nuttall self-convolution window is −121.9dB and the sidelobe attenuation rate is 84dB / oct. The spectral characteristics of the Nuttall self-convolution window are better than those of the Nuttall window, and it can more effectively suppress the spectral leakage of higher harmonics.

[0082] For higher harmonic analysis, the formulas for calculating the frequency, amplitude, and phase of the m-th harmonic are:

[0083]

[0084] In the formula, This refers to the harmonic frequency.

[0085] In one embodiment, Figure 2 This is a current signal diagram measured at a power station in Wuxi, used in this invention. An example analysis is conducted on the detection results of harmonics in the measured signal from a large power station using different window functions. Tables 1 and 2 show the relative errors of low-order harmonic parameters, and Tables 3 and 4 show the relative errors of high-order harmonic parameters, demonstrating the superiority of the method proposed in this invention.

[0086]

[0087]

[0088] The accuracy of the above window functions for detecting low-order harmonics in measured signals from large-scale data stations, from highest to lowest, is as follows: Nuttall window, Blackman-Harris window, Blackman window, Hanning window, and Hamming window. Among them, the Nuttall window function achieves a relative error of at least 10 for amplitude and phase detection. -7 %, 10 -7 %, indicating high measurement accuracy.

[0089]

[0090]

[0091] For high-order harmonic detection of measured signals in large-scale data centers, the relative error is 10 when a first-order Nuttall convolution window is added.-7 %~10 -9 %, 10 -6 %~10 -8 % with a second-order convolution window of 10 -8 %~10 -10 %, 10 -7 %~10 -9 % Adding a third-order convolution window makes it 10 -8 %~10 -10 %, 10 -8 %~10 -10 In summary, this indicates that the detection accuracy of the Nuttall convolution window increases with the convolution order. However, if the convolution order is too large, the main lobe becomes wider, and the side lobes significantly interfere with the main lobe, making accurate measurement impossible. Generally, the order should not exceed four.

[0092] First, this invention is based on the principle of harmonic detection based on window function theory. For low-order harmonics in power plants, the Nuttall window function with small sidelobe peak levels and large asymptotic decay rates is selected to optimize the spectral characteristics. For high-order harmonics in power plants, a convolution window is established based on the original Nuttall window function through time-domain convolution, forming a method for harmonic detection applied to large power plants. Second, a case study is conducted using measured voltage and current signals from large power plants. By comparing the relative errors of different window functions on the harmonic parameters of measured signals from large power plants, it is shown that the window function detection method proposed in this invention can effectively detect harmonics in large power plants.

[0093] The four-term 3rd-order Nuttall window exhibits ideal sidelobe characteristics, effectively reducing spectral leakage of low-order harmonics in the field. The Nuttall self-convolution window has even better spectral characteristics than the Nuttall window. As the convolution order increases, the sidelobe peak value of the Nuttall self-convolution window decreases rapidly, while the sidelobe attenuation rate increases rapidly, which can more effectively suppress spectral leakage of high-order harmonics in the field.

[0094] This invention also provides another computer device, including a processor and a memory configured to store a computer program capable of running on the processor; wherein, when the processor is configured to run the computer program, it performs the method steps described in the foregoing embodiments.

[0095] In practical applications, the aforementioned processor includes a Field-Programmable Gate Array (FPGA), and the processor can be a Central Processing Unit (CPU) or a Digital Signal Processor (DSP). It is understood that for different devices, the electronic devices used to implement the above-mentioned processor functions can also be other types, and this embodiment of the invention does not impose specific limitations.

[0096] The aforementioned memory can be volatile memory, such as random-access memory (RAM); or non-volatile memory, such as read-only memory (ROM), flash memory, hard disk drive (HDD), or solid-state drive (SSD); or a combination of the above types of memory, and provides instructions and data to the processor.

[0097] In an exemplary embodiment, the present invention also provides a computer-readable storage medium for storing a computer program.

[0098] Optionally, the computer-readable storage medium can be applied to any of the methods in the embodiments of the present invention, and the computer program causes the computer to execute the corresponding processes implemented by the processor in the various methods of the embodiments of the present invention. For the sake of brevity, these will not be described in detail here.

[0099] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The solutions in the embodiments of the present invention can be implemented using various computer languages, such as the object-oriented programming language Java and the interpreted scripting language JavaScript.

[0100] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0101] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0102] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0103] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0104] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A harmonic detection method for large-scale charging and discharging stations, characterized in that, include: Based on the sampled signals of the large-scale charging and discharging station, its discretized signal is obtained; The discretized signal is windowed to obtain a windowed signal; wherein, during the windowing process of the discretized signal, a window function is used for windowing the low-order harmonic signals in the discretized signal, and a convolution window is used for windowing the high-order harmonic signals in the discretized signal. Perform a discrete Fourier transform on the windowed signal to obtain the discrete spectrum; The amplitude, frequency, and phase of the signal are obtained from the discrete spectrum at the fundamental frequency.

2. The method as described in claim 1, characterized in that, The discretized signal is windowed to obtain a windowed signal, including: For the discretized signal Add a rectangular window Receive windowing signal .

3. The method as described in claim 1, characterized in that, For low-order harmonic signals in discretized signals, windowing is performed using a window function, including: For low-order harmonic signals in discretized signals, the Nuttall window function is used. Windowing is applied, and the time-domain representation of the Nuttall window function is as follows: ， in, The number of terms in the window function; , This represents the total number of sampling points; Satisfy constraints and .

4. The method as described in claim 3, characterized in that, For higher harmonic signals in discretized signals, a convolution window is used for windowing processing, including: Nuttall window function Perform temporal convolution operations to obtain the convolution window. ,in, This represents the number of Nuttall windows participating in the convolution.

5. A harmonic detection system for large-scale charging and discharging stations, characterized in that, include: The signal discretization module is configured to obtain the discretized signal based on the sampled signal of the large charging and discharging station; The signal windowing module is configured to perform windowing processing on the discretized signal to obtain a windowed signal; wherein, for low-order harmonic signals in the discretized signal, a window function is used for windowing processing; and for high-order harmonic signals in the discretized signal, a convolution window is used for windowing processing. The discrete transform module is configured to perform a discrete Fourier transform on the windowed signal to obtain a discrete spectrum; and, The harmonic parameter acquisition module is configured to obtain the amplitude, frequency, and phase of the signal based on the discrete spectrum at the fundamental frequency.

6. The system as described in claim 5, characterized in that, The signal windowing module performs windowing processing on the discretized signal to obtain a windowed signal, including: For the discretized signal Add a rectangular window Receive windowing signal .

7. The system as described in claim 5, characterized in that, The signal windowing module uses a window function to window low-order harmonic signals in the discretized signal, including: For low-order harmonic signals in discretized signals, the Nuttall window function is used. Windowing is applied, and the time-domain representation of the Nuttall window function is as follows: ， in, The number of terms in the window function; , This represents the total number of sampling points; Satisfy constraints and .

8. The system as described in claim 7, characterized in that, The signal windowing module uses a convolution window to process high-order harmonic signals in the discretized signal, including: Nuttall window function Perform temporal convolution operations to obtain the convolution window. ,in, This represents the number of Nuttall windows participating in the convolution.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor; characterized in that, When the processor executes the computer program, it implements the steps of the harmonic detection method for large-scale charging and discharging stations as described in any one of claims 1 to 4.

10. A computer-readable storage medium storing a computer program; characterized in that, When the computer program is executed by the processor, it implements the steps of the harmonic detection method for large-scale charging and discharging stations as described in any one of claims 1 to 4.

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