A power quality monitoring method and apparatus

Abstract

The application relates to the technical field of power system analysis, and particularly provides a power quality monitoring method and device, which comprises the following steps: sampling power quality parameters by using a three-cycle sampling method; adopting a discrete-time Fourier transform method to analyze the amplitude of each frequency point of a sampling signal; and performing aggregate analysis on the power quality parameters based on the amplitude of each frequency point of the sampling signal to obtain an aggregate spectrum diagram corresponding to the power quality parameters. The technical scheme provided by the application can collect and analyze power quality parameters in a power grid in real time, and accurately judge the power quality state.

Description

Technical Field

[0001] This invention relates to the field of power system analysis technology, specifically to a power quality monitoring method and device. Background Technology

[0002] Power quality is a crucial indicator for evaluating the operational quality of a power system and directly impacts the safe and stable operation of power equipment. With the widespread application of numerous power electronic devices, nonlinear loads, and distributed generation units in modern power systems, power quality issues in the power grid are becoming increasingly serious. Common power quality problems include voltage fluctuations and flicker, harmonics, frequency deviations, and voltage imbalances. These problems not only affect the normal operation of power equipment but can also lead to equipment damage, reduced efficiency, and grid failures.

[0003] Currently, power quality monitoring typically relies on traditional power quality monitoring equipment, which generally suffers from the following problems: First, most traditional power quality monitoring equipment can only monitor basic power parameters (such as voltage, frequency, and power), lacking the ability to accurately detect more complex power quality issues (such as harmonics and voltage flicker). Second, existing monitoring systems mostly collect data periodically, making it difficult to achieve real-time online monitoring of power quality, especially when power fluctuations are frequent, thus failing to detect problems in a timely manner. Moreover, while some high-precision power quality monitoring equipment can capture more complex power parameters, these devices are usually expensive, with high installation and maintenance costs, hindering large-scale application.

[0004] Therefore, how to design a system that can monitor power quality in real time, accurately, and at low cost, and analyze and judge complex power quality parameters has become an urgent problem to be solved in the current technology field. Summary of the Invention

[0005] To overcome the above-mentioned defects, the present invention proposes a power quality monitoring method and device.

[0006] Firstly, a power quality monitoring method is provided, the power quality monitoring method comprising:

[0007] Power quality parameters are sampled using the three-cycle sampling method;

[0008] The amplitude of the sampled signal at each frequency point is analyzed using the discrete-time Fourier transform method;

[0009] Based on the amplitude of each frequency point of the sampled signal, the power quality parameters are aggregated and analyzed to obtain the aggregated spectrum diagram corresponding to the power quality parameters.

[0010] Preferably, the power quality parameters include at least one of the following: voltage, current, frequency, and harmonics.

[0011] Preferably, before sampling the power quality parameters using the three-cycle sampling method, the process includes: preprocessing the original power quality parameters.

[0012] Furthermore, the preprocessing of the raw power quality parameters includes: performing low-pass filtering or band-pass filtering on the raw power quality parameters, filling in missing values ​​on the raw power quality parameters, removing outliers from the raw power quality parameters, and / or detecting and deleting duplicate data on the raw power quality parameters.

[0013] Preferably, the amplitude of the sampled signal at each frequency point is as follows:

[0014]

[0015] In the above formula, A k Let y1 be the amplitude of the sampled signal at frequency point k, W be the window function, α be the auxiliary parameter, α = k0 - k1 - 0.5, k0 be the spectral line index of the sampled signal at frequency point k, k1 be the spectral line index to the left of frequency point k, N be the data truncation length, y1 be the amplitude of the spectral line to the left of frequency point k, and y2 be the amplitude of the spectral line to the right of frequency point k.

[0016] Preferably, the step of performing aggregated analysis on the power quality parameters based on the amplitude of each frequency point of the sampled signal to obtain the aggregated spectrum diagram corresponding to the power quality parameters includes:

[0017] Set the aggregation bandwidth, and starting from the initial frequency, analyze the aggregation amplitude of each unit in the frequency band corresponding to one aggregation bandwidth;

[0018] Obtain the frequency band and aggregate amplitude corresponding to each unit, and construct an aggregated spectrum diagram.

[0019] Furthermore, the aggregation bandwidth is 2kHz, and the initial frequency is 2kHz.

[0020] Furthermore, the aggregation amplitude of each unit is as follows:

[0021]

[0022] In the above formula, G b Let f be the aggregated amplitude per unit b, f be the current frequency, fb be the starting frequency of the frequency band corresponding to unit b, k be the aggregated bandwidth, r be the spectral analysis resolution, and C be the aggregated amplitude per unit b. f This represents the amplitude of the sampled signal at the current frequency point.

[0023] Secondly, a power quality monitoring device is provided, the power quality monitoring device comprising:

[0024] The sampling module is used to sample power quality parameters using the three-cycle sampling method;

[0025] The first analysis module is used to analyze the amplitude of the sampled signal at each frequency point using a discrete-time Fourier transform device;

[0026] The second analysis module is used to perform aggregate analysis on the power quality parameters based on the amplitude of each frequency point of the sampled signal, and obtain the aggregated spectrum diagram corresponding to the power quality parameters.

[0027] Preferably, the power quality parameters include at least one of the following: voltage, current, frequency, and harmonics.

[0028] Preferably, the device includes a preprocessing module for preprocessing the raw power quality parameters.

[0029] Furthermore, the preprocessing of the raw power quality parameters includes: performing low-pass filtering or band-pass filtering on the raw power quality parameters, filling in missing values ​​on the raw power quality parameters, removing outliers from the raw power quality parameters, and / or detecting and deleting duplicate data on the raw power quality parameters.

[0030] Preferably, the amplitude of the sampled signal at each frequency point is as follows:

[0031]

[0032] In the above formula, A k Let y1 be the amplitude of the sampled signal at frequency point k, W be the window function, α be the auxiliary parameter, α = k0 - k1 - 0.5, k0 be the spectral line index of the sampled signal at frequency point k, k1 be the spectral line index to the left of frequency point k, N be the data truncation length, y1 be the amplitude of the spectral line to the left of frequency point k, and y2 be the amplitude of the spectral line to the right of frequency point k.

[0033] Preferably, the second analysis module is specifically used for:

[0034] Set the aggregation bandwidth, and starting from the initial frequency, analyze the aggregation amplitude of each unit in the frequency band corresponding to one aggregation bandwidth;

[0035] Obtain the frequency band and aggregate amplitude corresponding to each unit, and construct an aggregated spectrum diagram.

[0036] Furthermore, the aggregation bandwidth is 2kHz, and the initial frequency is 2kHz.

[0037] Furthermore, the aggregation amplitude of each unit is as follows:

[0038]

[0039] In the above formula, Gb Let f be the aggregated amplitude per unit b, f be the current frequency, fb be the starting frequency of the frequency band corresponding to unit b, k be the aggregated bandwidth, r be the spectral analysis resolution, and C be the aggregated amplitude per unit b. f This represents the amplitude of the sampled signal at the current frequency point.

[0040] Thirdly, a computer device is provided, comprising: one or more processors;

[0041] The processor is used to execute one or more programs;

[0042] When the one or more programs are executed by the one or more processors, the power quality monitoring method is implemented.

[0043] Fourthly, a computer-readable storage device is provided, on which a computer program is stored, wherein when the computer program is executed, the power quality monitoring method is implemented.

[0044] The above-described technical solutions of the present invention have at least one or more of the following beneficial effects:

[0045] This invention provides a power quality monitoring method and apparatus, comprising: sampling power quality parameters using a three-cycle sampling method; analyzing the amplitude of the sampled signal at each frequency point using a discrete-time Fourier transform method; and performing aggregated analysis on the power quality parameters based on the amplitude of the sampled signal at each frequency point to obtain an aggregated spectrum diagram corresponding to the power quality parameters. The technical solution provided by this invention can collect and analyze power quality parameters in the power grid in real time and accurately determine the power quality status. Attached Figure Description

[0046] Figure 1 This is a schematic diagram of the main steps of the power quality monitoring method according to an embodiment of the present invention. Detailed Implementation

[0047] The specific embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0048] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0049] As disclosed in the background section, power quality is a crucial indicator for measuring the operational quality of a power system and is directly related to the safe and stable operation of power equipment. With the widespread application of numerous power electronic devices, nonlinear loads, and distributed generation devices in modern power systems, power quality problems in the power grid are becoming increasingly serious. Common power quality issues include voltage fluctuations and flicker, harmonics, frequency deviations, and voltage imbalances. These problems not only affect the normal operation of power equipment but may even lead to equipment damage, reduced efficiency, and grid failures.

[0050] Currently, power quality monitoring typically relies on traditional power quality monitoring equipment, which generally suffers from the following problems: First, most traditional power quality monitoring equipment can only monitor basic power parameters (such as voltage, frequency, and power), lacking the ability to accurately detect more complex power quality issues (such as harmonics and voltage flicker). Second, existing monitoring systems mostly collect data periodically, making it difficult to achieve real-time online monitoring of power quality, especially when power fluctuations are frequent, thus failing to detect problems in a timely manner. Moreover, while some high-precision power quality monitoring equipment can capture more complex power parameters, these devices are usually expensive, with high installation and maintenance costs, hindering large-scale application.

[0051] Therefore, how to design a system that can monitor power quality in real time, accurately, and at low cost, and analyze and judge complex power quality parameters has become an urgent problem to be solved in the current technology field.

[0052] To address the aforementioned problems, this invention provides a power quality monitoring method and apparatus, comprising: sampling power quality parameters using a three-cycle sampling method; analyzing the amplitude of the sampled signal at each frequency point using a discrete-time Fourier transform method; and performing aggregated analysis on the power quality parameters based on the amplitude of the sampled signal at each frequency point to obtain an aggregated spectrum diagram corresponding to the power quality parameters. The technical solution provided by this invention can collect and analyze power quality parameters in the power grid in real time, accurately determining the power quality status.

[0053] The above plan will be explained in detail below.

[0054] Example 1

[0055] See appendix Figure 1 , Figure 1 This is a schematic flowchart of the main steps of a power quality monitoring method according to an embodiment of the present invention.

[0056] like Figure 1 As shown, the power quality monitoring method in this embodiment of the invention mainly includes the following steps:

[0057] Step S101: Sample the power quality parameters using the three-cycle sampling method;

[0058] Step S102: Analyze the amplitude of the sampled signal at each frequency point using the discrete-time Fourier transform method;

[0059] Step S103: Based on the amplitude of each frequency point of the sampled signal, perform aggregate analysis on the power quality parameters to obtain the aggregated spectrum diagram corresponding to the power quality parameters.

[0060] The power quality parameters include at least one of the following: voltage, current, frequency, and harmonics.

[0061] In this embodiment, a three-cycle sampling method is used to collect data from distribution network nodes in real time, including power quality parameters such as voltage, current, frequency, and harmonics. The three-cycle sampling method is a key step in this power quality monitoring system, its core being the sampling of the power frequency signal for three complete cycles. The power frequency is typically 50Hz or 60Hz, corresponding to a cycle of 20ms or 16.67ms respectively. The working principle of the three-cycle sampling method is to continuously record the signal for three complete cycles during each data acquisition, continuously acquiring the instantaneous values ​​of voltage and current. The advantage of this method is that it can more accurately capture harmonic components, frequency shifts, and voltage fluctuations in periodic signals, while reducing errors caused by single-cycle fluctuations. The sampling frequency is usually much higher than the power frequency of the signal, ensuring accurate capture of high-frequency harmonics. For example, if the sampling frequency is 10kHz, 500 data points can be collected in each power frequency cycle, thus enabling a very detailed characterization of the power signal waveform. This high-precision sampling ensures the real-time nature and accuracy of the data.

[0062] In this embodiment, before sampling the power quality parameters using the three-cycle sampling method, the process includes: preprocessing the original power quality parameters.

[0063] In one implementation, this step can significantly improve transmission efficiency and reduce potential errors during transmission. Common preprocessing techniques include low-pass filtering and band-pass filtering to remove high-frequency noise while retaining key low-frequency information in power quality monitoring, such as harmonics and voltage fluctuations. Interpolation, mean imputation, or other algorithms are used to fill in missing values; statistical methods or machine learning algorithms are used to detect and remove outliers, such as sudden current changes and invalid readings; and duplicate data records are detected and deleted to ensure the uniqueness of each record.

[0064] In this embodiment, the acquired power signal is discretely sampled, and the resulting discrete signal is input to the data analysis module. The Discrete-Time Fourier Transform (DTFT) algorithm is used to perform frequency domain transformation on the signal. This step allows the extraction of frequency components of the power signal, obtaining the amplitude and phase information of each frequency component. Especially for key power quality parameters such as harmonics, frequency shifts, and voltage fluctuations, DTFT has high frequency resolution. By converting the acquired voltage, current, and other signal data into frequency domain signals, the system can identify abnormalities at different frequencies, such as higher harmonics and frequency drift. This step provides the basis for real-time frequency response analysis, enabling the terminal to comprehensively monitor the power quality in the grid and provide real-time frequency response analysis results, ensuring the stability of grid operation and improving power quality. The amplitudes of the sampled signal at each frequency point are as follows:

[0065]

[0066] In the above formula, A k Let y1 be the amplitude of the sampled signal at frequency point k, W be the window function, α be the auxiliary parameter, α = k0 - k1 - 0.5, k0 be the spectral line index of the sampled signal at frequency point k, k1 be the spectral line index to the left of frequency point k, N be the data truncation length, y1 be the amplitude of the spectral line to the left of frequency point k, and y2 be the amplitude of the spectral line to the right of frequency point k.

[0067] In this embodiment, frequency sampling and aggregation analysis of power quality monitoring data are performed using a frequency band aggregation method. By acquiring power signals at a sampling rate of 2kHz, high-frequency components and transient changes in the power system are captured. The acquired 2kHz signal data is input to an aggregation module, which aggregates the sampled data within multiple time windows. Through aggregation analysis of this data, features of short-time harmonics, rapid voltage fluctuations, and other high-frequency power quality problems in the power signal can be extracted. The 2kHz sampling rate not only ensures high frequency resolution of the signal but also improves the accuracy of aggregation analysis, making it suitable for detecting complex power quality problems and identifying faults. The aggregation analysis of power quality parameters based on the amplitude of each frequency point of the sampled signal to obtain the aggregated spectrum diagram corresponding to the power quality parameters includes:

[0068] Set the aggregation bandwidth, and starting from the initial frequency, analyze the aggregation amplitude of each unit in the frequency band corresponding to one aggregation bandwidth;

[0069] Obtain the frequency band and aggregate amplitude corresponding to each unit, and construct an aggregated spectrum diagram.

[0070] In one embodiment, the aggregation bandwidth is 2kHz and the initial frequency is 2kHz.

[0071] In one implementation, the aggregate amplitude of each unit is as follows:

[0072]

[0073] In the above formula, G b Let f be the aggregated amplitude per unit b, f be the current frequency, fb be the starting frequency of the frequency band corresponding to unit b, k be the aggregated bandwidth, r be the spectral analysis resolution, and C be the aggregated amplitude per unit b. f This represents the amplitude of the sampled signal at the current frequency point.

[0074] Example 2

[0075] Based on the same inventive concept, the present invention also provides a power quality monitoring device, the power quality monitoring device comprising:

[0076] The sampling module is used to sample power quality parameters using the three-cycle sampling method;

[0077] The first analysis module is used to analyze the amplitude of the sampled signal at each frequency point using a discrete-time Fourier transform device;

[0078] The second analysis module is used to perform aggregate analysis on the power quality parameters based on the amplitude of each frequency point of the sampled signal, and obtain the aggregated spectrum diagram corresponding to the power quality parameters.

[0079] Preferably, the power quality parameters include at least one of the following: voltage, current, frequency, and harmonics.

[0080] Preferably, the device includes a preprocessing module for preprocessing the raw power quality parameters.

[0081] Furthermore, the preprocessing of the raw power quality parameters includes: performing low-pass filtering or band-pass filtering on the raw power quality parameters, filling in missing values ​​on the raw power quality parameters, removing outliers from the raw power quality parameters, and / or detecting and deleting duplicate data on the raw power quality parameters.

[0082] Preferably, the amplitude of the sampled signal at each frequency point is as follows:

[0083]

[0084] In the above formula, A k Let y1 be the amplitude of the sampled signal at frequency point k, W be the window function, α be the auxiliary parameter, α = k0 - k1 - 0.5, k0 be the spectral line index of the sampled signal at frequency point k, k1 be the spectral line index to the left of frequency point k, N be the data truncation length, y1 be the amplitude of the spectral line to the left of frequency point k, and y2 be the amplitude of the spectral line to the right of frequency point k.

[0085] Preferably, the second analysis module is specifically used for:

[0086] Set the aggregation bandwidth, and starting from the initial frequency, analyze the aggregation amplitude of each unit in the frequency band corresponding to one aggregation bandwidth;

[0087] Obtain the frequency band and aggregate amplitude corresponding to each unit, and construct an aggregated spectrum diagram.

[0088] Furthermore, the aggregation bandwidth is 2kHz, and the initial frequency is 2kHz.

[0089] Furthermore, the aggregation amplitude of each unit is as follows:

[0090]

[0091] In the above formula, G b Let f be the aggregated amplitude per unit b, f be the current frequency, fb be the starting frequency of the frequency band corresponding to unit b, k be the aggregated bandwidth, r be the spectral analysis resolution, and C be the aggregated amplitude per unit b. f This represents the amplitude of the sampled signal at the current frequency point.

[0092] Example 3

[0093] Based on the same inventive concept, this invention also provides a computer device, which includes a processor and a memory. The memory stores a computer program, which includes program instructions. The processor executes the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, and is suitable for implementing one or more instructions. Specifically, it is suitable for loading and executing one or more instructions from the computer storage medium to implement the corresponding method flow or corresponding function, thereby realizing the steps of the power quality monitoring method in the above embodiments.

[0094] Example 4

[0095] Based on the same inventive concept, this invention also provides a storage medium, specifically a computer-readable storage device (Memory), which is a memory device in a computer device used to store programs and data. It is understood that the computer-readable storage device here can include both the built-in storage medium in the computer device and extended storage media supported by the computer device. The computer-readable storage device provides storage space that stores the terminal's operating system. Furthermore, this storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more computer programs (including program code). It should be noted that the computer-readable storage device here can be a high-speed RAM memory or a non-volatile memory, such as at least one disk storage device. The processor can load and execute one or more instructions stored in the computer-readable storage device to implement the steps of the power quality monitoring method in the above embodiments.

[0096] 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 embodied 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.

[0097] 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.

[0098] 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 1The function specified in one or more boxes.

[0099] 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.

[0100] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for monitoring power quality, characterized in that, The method includes: Power quality parameters are sampled using the three-cycle sampling method; The amplitude of the sampled signal at each frequency point is analyzed using the discrete-time Fourier transform method; Based on the amplitude of each frequency point of the sampled signal, the power quality parameters are aggregated and analyzed to obtain the aggregated spectrum diagram corresponding to the power quality parameters.

2. The method as described in claim 1, characterized in that, The power quality parameters include at least one of the following: voltage, current, frequency, and harmonics.

3. The method as described in claim 1, characterized in that, Before sampling power quality parameters using the three-cycle sampling method, the process includes preprocessing the original power quality parameters.

4. The method as described in claim 3, characterized in that, The preprocessing of the raw power quality parameters includes: performing low-pass filtering or band-pass filtering on the raw power quality parameters, filling in missing values ​​on the raw power quality parameters, removing outliers from the raw power quality parameters, and / or detecting and deleting duplicate data on the raw power quality parameters.

5. The method as described in claim 1, characterized in that, The amplitudes of the sampled signal at each frequency point are as follows: In the above formula, A k Let y1 be the amplitude of the sampled signal at frequency point k, W be the window function, α be the auxiliary parameter, α = k0 - k1 - 0.5, k0 be the spectral line index of the sampled signal at frequency point k, k1 be the spectral line index to the left of frequency point k, N be the data truncation length, y1 be the amplitude of the spectral line to the left of frequency point k, and y2 be the amplitude of the spectral line to the right of frequency point k.

6. The method as described in claim 1, characterized in that, The aggregation analysis of power quality parameters based on the amplitude of each frequency point of the sampled signal to obtain the aggregated spectrum diagram corresponding to the power quality parameters includes: Set the aggregation bandwidth, and starting from the initial frequency, analyze the aggregation amplitude of each unit in the frequency band corresponding to one aggregation bandwidth; Obtain the frequency band and aggregate amplitude corresponding to each unit, and construct an aggregated spectrum diagram.

7. The method as described in claim 6, characterized in that, The aggregated bandwidth is 2kHz, and the initial frequency is 2kHz.

8. The method as described in claim 6, characterized in that, The aggregation amplitude of each unit is as follows: In the above formula, G b Let f be the aggregated amplitude per unit b, f be the current frequency, fb be the starting frequency of the frequency band corresponding to unit b, k be the aggregated bandwidth, r be the spectral analysis resolution, and C be the aggregated amplitude per unit b. f This represents the amplitude of the sampled signal at the current frequency point.

9. A power quality monitoring device, characterized in that, The device includes: The sampling module is used to sample power quality parameters using the three-cycle sampling method; The first analysis module is used to analyze the amplitude of the sampled signal at each frequency point using a discrete-time Fourier transform device; The second analysis module is used to perform aggregate analysis on the power quality parameters based on the amplitude of each frequency point of the sampled signal, and obtain the aggregated spectrum diagram corresponding to the power quality parameters.

10. The apparatus as claimed in claim 9, characterized in that, The power quality parameters include at least one of the following: voltage, current, frequency, and harmonics.

11. The apparatus as claimed in claim 9, characterized in that, The device includes a preprocessing module for preprocessing the raw power quality parameters.

12. The apparatus as claimed in claim 11, characterized in that, The preprocessing of the raw power quality parameters includes: performing low-pass filtering or band-pass filtering on the raw power quality parameters, filling in missing values ​​on the raw power quality parameters, removing outliers from the raw power quality parameters, and / or detecting and deleting duplicate data on the raw power quality parameters.

13. The apparatus as claimed in claim 9, characterized in that, The amplitudes of the sampled signal at each frequency point are as follows: In the above formula, A k Let y1 be the amplitude of the sampled signal at frequency point k, W be the window function, α be the auxiliary parameter, α = k0 - k1 - 0.5, k0 be the spectral line index of the sampled signal at frequency point k, k1 be the spectral line index to the left of frequency point k, N be the data truncation length, y1 be the amplitude of the spectral line to the left of frequency point k, and y2 be the amplitude of the spectral line to the right of frequency point k.

14. The apparatus as claimed in claim 9, characterized in that, The second analysis module is specifically used for: Set the aggregation bandwidth, and starting from the initial frequency, analyze the aggregation amplitude of each unit in the frequency band corresponding to one aggregation bandwidth; Obtain the frequency band and aggregate amplitude corresponding to each unit, and construct an aggregated spectrum diagram.

15. The apparatus as claimed in claim 14, characterized in that, The aggregated bandwidth is 2kHz, and the initial frequency is 2kHz.

16. The apparatus as claimed in claim 14, characterized in that, The aggregation amplitude of each unit is as follows: In the above formula, G b Let f be the aggregated amplitude per unit b, f be the current frequency, fb be the starting frequency of the frequency band corresponding to unit b, k be the aggregated bandwidth, r be the spectral analysis resolution, and C be the aggregated amplitude per unit b. f This represents the amplitude of the sampled signal at the current frequency point.

17. A computer device, characterized in that, include: One or more processors; The processor is used to execute one or more programs; When the one or more programs are executed by the one or more processors, the power quality monitoring method as described in any one of claims 1 to 8 is implemented.

18. A computer-readable storage device, characterized in that, It contains a computer program, which, when executed, implements the power quality monitoring method as described in any one of claims 1 to 8.

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