A power quality analysis method, system

Abstract

The application discloses a power quality analysis method and system, and relates to the field of power monitoring. The method comprises the following steps: receiving power monitoring message data through a DMA mode by using an SPI interface, and temporarily storing the received message data in a RAM; performing wavelet transform and FFT algorithm processing on voltage and current signals of the power monitoring message data; analyzing power quality parameters of a power grid, including voltage, frequency, voltage temporary rise / fall, short-time interruption frequency, short-time and long-time flicker, harmonics, inter-harmonics, and displaying the parameters in a visual mode. The method has smaller parameter error, and improves the accuracy of power quality analysis.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of power monitoring, more particularly, to a power quality analysis method and system. BACKGROUND

[0002] As one of the most widely used energy forms in today's society, the development and utilization level of electric energy is directly related to the development strength of a country. In order to improve the efficiency of electric energy and better serve the public life and meet the needs of social production, it is particularly important to conduct in-depth analysis on the quality of electric energy.

[0003] With the rapid development of renewable energy such as wind energy, water energy and solar energy, although these new energy sources have brought diversification to energy supply, their inherent randomness, intermittency, volatility and non-dispatchability have affected the quality of the converted electric energy. Therefore, it is very important to analyze the quality of the electric energy converted from these new energy sources to ensure its safe and controllable use.

[0004] In addition, with the increasing demand for electric energy and the rapid development of new energy generation and grid-connected technology, the structure of the power grid and the characteristics of the load have undergone significant changes. The coexistence of alternating current and direct current in the electrical environment, as well as the existence of special loads, may cause problems such as harmonic interference, voltage fluctuation, three-phase voltage imbalance, etc. These problems make it difficult to accurately measure the electric energy quality parameters in the power grid. SUMMARY

[0005] The purpose of the present application is to solve the problem of inaccurate measurement of electric energy quality parameters in the power grid, and to provide a power quality analysis method, comprising the following steps:

[0006] S1, using the SPI interface, receiving electric energy monitoring message data through the DMA mode, and temporarily storing the received message data in the RAM;

[0007] S2, wavelet transform and FFT algorithm processing are performed on the voltage and current signals of the electric energy monitoring message data;

[0008] S3, analyzing the electric energy quality parameters of the power grid, including voltage, frequency, voltage temporary rise / fall, short interruption frequency, short and long time flicker, harmonic, interharmonic, and displaying through a visual method.

[0009] Further, S1 specifically comprises:

[0010] S11, initializing the SPI interface and configuring it in data receiving mode;

[0011] S12, waiting for the DMA interrupt trigger and completing data reception;

[0012] S13, verifying the received data;

[0013] S14, temporarily storing the verified message data into RAM.

[0014] Further, 16 frames of data are stored in an array, and after storing 16 frames of data, 4096-point FFT is performed.

[0015] Further, S2 is specifically:

[0016] S21, analyzing the message data to obtain the required voltage sampling value;

[0017] S22, wavelet transforming the collected voltage and current signals;

[0018] S23, performing FFT algorithm processing on the data after wavelet transform processing, and converting time domain data into frequency domain.

[0019] Further, the sampled voltage or current signal is decomposed into high-frequency and low-frequency components by wavelet transform to improve the frequency domain resolution, which is expressed as:

[0020]

[0021] wherein ψ j,k (x) represents a wavelet function related to parameters j and k, s j is a scale variable, j is a frequency domain parameter, k is a translation variable, j, k∈Z represents the wavelet after j, k transformation belongs to the wavelet function set, Z represents the parameter change set in the wavelet function set, j0 is an arbitrary starting point in the wavelet function set, c j0 (k) represents an approximation coefficient, d j (k) represents a fine coefficient, represents a scale function, f(x) represents a sampled voltage or current signal, and x represents a time variable.

[0022] Further, S3 is specifically:

[0023] S31, extracting frequency domain amplitude information from the FFT calculation result, the integer multiple position of the fundamental frequency is the harmonic, and the rest is the interharmonic; for the harmonic, the harmonic voltage and harmonic current content rate 2-50 times, the harmonic current effective value 2-50 times, and the voltage and current harmonic total harmonic distortion rate are calculated; for the interharmonic, the interharmonic voltage and harmonic current contain 0.5-49.5 times, the harmonic current effective value 0.5-49.5 times;

[0024] S32, square root operation is carried out to the voltage value, and the effective value of the voltage is obtained;The average value is calculated once every 16 frames of data received, and the voltage effective average value is obtained;The absolute value of the difference between the voltage effective value and 220V is divided by 220V, and the deviation value of the voltage is obtained;

[0025] S33, the signal frequency is obtained, and the frequency average value is calculated every 16 frames of data received;

[0026] S34, the voltage anomaly is monitored, if the abnormal condition is restored within 10ms to 1min, it is recorded as an abnormality;Otherwise, it is not regarded as an abnormality;

[0027] S35, flicker monitoring, according to the requirements of IEC-61000-4-15, the instantaneous flicker value with half cycle as the time interval is calculated, and the short-time flicker value is obtained every 10 minutes, and the flicker value is obtained every two hours;Specifically, the root mean square value of each frame of data is calculated twice in half cycle, and 512-point FFT is stored;The instantaneous flicker value is calculated according to the FFT result, the short-time flicker value is calculated by accumulating 120 times, and the long-time flicker value is calculated by accumulating 12 times;

[0028] S36, after data processing and calculation, the data is packaged, sent through UART protocol, the packaged data is analyzed, and graphical display is carried out.

[0029] Further, the calculation formula of the harmonic voltage content rate is as follows:

[0030]

[0031] Wherein, HRuh represents the harmonic voltage content rate, v n represents the n-order harmonic voltage value, and v1 represents the fundamental wave voltage value.

[0032] The application also provides an electric energy quality analysis system, comprising:

[0033] The data receiving unit is used for receiving the electric energy monitoring message data through the DMA mode by using the SPI interface, and temporarily storing the received message data in the RAM;

[0034] The signal processing unit is used for wavelet transform and FFT algorithm processing of the voltage and current signals of the electric energy monitoring message data;

[0035] The parameter analysis unit is used for analyzing the electric energy quality parameters of the power grid, including: voltage, frequency, voltage temporary rise / fall, short-time interruption times, short-time and long-time flicker, harmonic, and interharmonic, and displaying through a visual mode.

[0036] The technical scheme provided by the application has the beneficial effects that:

[0037] The present invention analyzes the data of the power grid using an algorithm that combines wavelet transform and FFT, which can accurately capture the transient characteristics and non-stationary characteristics of the signal, making the measured parameter errors smaller and improving the accuracy of power quality analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 is a flow chart of a power quality analysis method according to an embodiment of the present invention;

[0039] Figure 2 This is a flow chart of wavelet transform and FFT calculation according to an embodiment of the present invention;

[0040] Figure 3 This is a flow chart of harmonic analysis calculations according to an embodiment of the present invention;

[0041] Figure 4 is a flow chart of frequency and frequency deviation calculation according to an embodiment of the present invention;

[0042] Figure 5 This is a flow chart of short-time flicker calculation according to an embodiment of the present invention. DETAILED DESCRIPTION

[0043] To make the objectives, technical solutions and advantages of the present invention more clear, the embodiments of the present invention will be further described below with reference to the accompanying drawings.

[0044] The flow chart of the power quality analysis method according to the embodiment of the present invention is as follows: Figure 1 , specifically including the following steps:

[0045] S1. Use the SPI interface to receive the power monitoring message data through DMA mode, and temporarily store the received message data in RAM.

[0046] Specifically:

[0047] S11. Initialize the SPI interface and configure it to data receiving mode.

[0048] S12, waiting for DMA interrupt to be triggered. When 1546 data are received, the interrupt is triggered and the data reception is completed.

[0049] S13. Verify the frame header, check bit, frame tail, etc. of the received data. If the data packet information does not meet expectations, it means that the data packet may be damaged or a communication error occurs.

[0050] S14. Temporarily store the verified message data in RAM.

[0051] Specifically, the data receiving and detecting device of the embodiment of the present application is designed based on an ARM Cortex-M4 core and is used for efficiently monitoring power quality parameters in a power grid. The device is suitable for receiving power grid cycle data provided by a single-phase intelligent internet-of-things electric energy meter through an SPI communication mode and realizing real-time monitoring of key parameters such as voltage deviation, frequency deviation and harmonics.

[0052] S2, wavelet transform and FFT algorithm processing are performed on the voltage and current signals of the electric energy monitoring message data. The wavelet transform is used for accurately capturing transient characteristics of the signals, and the FFT is used for converting time domain data into a frequency domain so as to analyze parameters such as harmonics and interharmonics. In the embodiment of the present application, every 16 frames of data are stored in an array, and after 16 frames of data are stored, 4096-point FFT is performed.

[0053] Specifically,

[0054] S21, the message data is parsed to obtain required voltage sampling values;

[0055] S22, wavelet transform is performed on the collected voltage and current signals to extract detailed characteristics of the signals, including transient signals and non-stationary characteristics. A wavelet transform algorithm is designed using MATLAB, and then a MATLAB Coder tool is used to convert the M file of MATLAB into a C code form and import it into an engineering file, and a main program calls a wavelet transform function to process the sampling signals. The wavelet transform repeatedly decomposes the sampled voltage or current signals into high-frequency and low-frequency components to gradually improve the frequency domain resolution. Initially, the signals are divided into details (high frequency) and approximations (low frequency) by an orthogonal wavelet base. Then, the approximation part is decomposed again to generate more detailed decomposition levels. With each level of decomposition, more detailed details in the frequency domain can be obtained. Wavelet packet decomposition is a further development on the basis of discrete wavelet transform, and the wavelet transform is nested for each layer. The wavelet function is as follows:

[0056]

[0057] The original signal is recovered, that is:

[0058]

[0059] wherein ψ j,k (x) represents a wavelet function related to parameters j and k, s j is a scale variable, j is a frequency domain parameter, and Z represents a parameter variation set in the wavelet function set, and Z represents a parameter variation set in the wavelet function set,

[0060] S23, the data processed by wavelet transform is processed by FFT algorithm, time domain data is converted into frequency domain, in order to analyze harmonic and interharmonic parameters.

[0061] Reference Figure 2 , Figure 2 is the wavelet transform and FFT calculation flowchart of the embodiment of the application, during data processing, the collected signal is first decomposed by wavelet packet transform method, first, system initialization and wavelet packet transform base function selection are performed, then the analysis scale is determined and the sample signal characteristic value is extracted. Next, the system will check whether the waveform changes, if changes, the change time is recorded and the stable signals before and after the change are extracted for FFT processing, finally, the whole processing flow is ended.

[0062] Reference Figure 3 , Figure 3 is the harmonic analysis calculation flowchart of the embodiment of the application. The system accumulates and stores every 16 frames of data in an array, and whenever the array is full, the system performs 4096-point fast Fourier transform (FFT) on the data. Through the results of FFT, the system can extract the amplitude information in the frequency domain, wherein the amplitudes located at the integer multiple positions of the fundamental frequency are identified as harmonics, and the amplitudes at other positions are interharmonics.

[0063] S3, the power quality parameters of the power grid are analyzed, including: voltage, frequency, voltage temporary rise / fall, short interruption times and short-time and long-time flicker, harmonics, interharmonics, and are displayed through a visual mode.

[0064] Specifically,

[0065] S31, the frequency domain amplitude information is extracted from the FFT calculation results, the integer multiple positions of the fundamental frequency are harmonics, and the rest are interharmonics; for harmonics, the harmonic voltage and harmonic current content rate 2-50 times, the harmonic current effective value 2-50 times are monitored, and the voltage and current harmonic total harmonic distortion rate are calculated; for interharmonics, the interharmonic voltage and harmonic current content 0.5-49.5 times, the harmonic current effective value 0.5-49.5 times are monitored.

[0066] The calculation formula of the harmonic voltage content rate is as follows:

[0067]

[0068] Among them, HRuh represents the harmonic voltage content rate, v n represents the n-order harmonic voltage value, and v1 represents the fundamental voltage value.

[0069] S32, calculate the voltage effective value, effective average and deviation: square root operation is carried out on the voltage value, and the effective value of the voltage is obtained; the average value is calculated once every 16 frames of data, and the voltage effective average value is obtained; the absolute value of the difference between the voltage effective value and 220V is divided by 220V, and the voltage deviation value is obtained.

[0070] S33, the signal frequency is obtained, and the frequency average value is calculated every 16 frames of data. Figure 4 , Figure 4 The frequency and frequency deviation calculation flowchart of the embodiment of the application is shown in FIG. 4. The system obtains the signal frequency by input capture through the falling edge interrupt, and calculates the average value of the frequency after receiving 16 frames of data to ensure the accuracy of the measurement result.

[0071] S34, monitor the voltage anomaly, if the abnormal condition recovers within 10ms to 1min, it is recorded as an abnormality; otherwise, it is not regarded as an abnormality.

[0072] S35, flicker monitoring, according to the requirements of IEC-61000-4-15, the instantaneous flicker value with a half cycle as the time interval is calculated, and a short-time flicker value is obtained every 10 minutes, and a flicker value is obtained every two hours; the root mean square value of each frame of data is calculated twice in a half cycle, and 512-point FFT is performed after storage; the instantaneous flicker value is calculated according to the FFT result, the short-time flicker value is calculated after 120 times of accumulation, and the long-time flicker value is calculated after 12 times of accumulation.

[0073] Reference Figure 5 , Figure 5 The short-time flicker calculation flowchart of the embodiment of the application is shown in FIG. 5. When the system processes each frame of data, the root mean square value of two half cycles is calculated first, and these values are stored. Then, 512-point FFT is performed using the stored data. Based on the result of FFT, the system further calculates the instantaneous flicker value. When 120 times of data are accumulated, the system calculates the short-time flicker value; and when 12 times of data are accumulated, the long-time flicker value is calculated.

[0074] S36, after data processing and calculation, the data is packaged, sent through the UART protocol, analyzed and displayed graphically.

[0075] The embodiment of the application also includes: an electric energy quality analysis system, characterized in that it comprises:

[0076] The data receiving unit is used for receiving the electric energy monitoring message data through the DMA mode by using the SPI interface, and temporarily storing the received message data in the RAM.

[0077] The signal processing unit is used for wavelet transform and FFT algorithm processing of the voltage and current signals of the electric energy monitoring message data.

[0078] The parameter analysis unit is used to analyze the power quality parameters of the power grid, including: voltage, frequency, voltage swell / sag, number of short interruptions, short and long flicker, harmonics, and interharmonics, and display them in a visual way.

[0079] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not limited to the embodiments shown herein but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A power quality analysis method, characterized in that: The following steps are involved: S1. Use the SPI interface to receive the power monitoring message data through DMA mode and temporarily store the received message data in RAM; S2. Perform wavelet transform and FFT algorithm processing on the voltage and current signals of the power monitoring message data; S3. Analyze the power quality parameters of the power grid, including voltage, frequency, voltage swell / sag, number of short interruptions, short and long flicker, harmonics, and interharmonics, and display them in a visual manner; S2 is specifically: S21, parsing the message data to obtain the required voltage sampling value; S22, performing wavelet transform on the collected voltage and current signals; S23, performing FFT algorithm processing on the data processed by wavelet transform to convert the time domain data into frequency domain; Wavelet transform is used to decompose the sampled voltage or current signal into high-frequency and low-frequency components to improve the frequency domain resolution, which can be expressed as: in, represents the wavelet function associated with parameters j and k, 、 is a scale variable, j is a frequency domain parameter, is the translation variable, j, k∈Z means that the wavelet after transformation according to j, k belongs to the wavelet function set, Z represents the parameter change set in the wavelet function set, j0 is an arbitrary starting point in the wavelet function set, represents the approximate coefficient, represents the fine coefficient, represents the scaling function, represents the sampled voltage or current signal, and x represents the time variable.

2. A power quality analysis method according to claim 1, characterized in that: S1 is specifically: S11, initialize the SPI interface and configure it to data receiving mode; S12, wait for DMA interrupt to trigger and data reception to complete; S13, verifying the received data; S14. Temporarily store the verified message data in RAM.

3. The power quality analysis method according to claim 1, characterized in that: Store every 16 frames of data in an array, and perform a 4096-point FFT after all 16 frames of data are stored.

4. The power quality analysis method according to claim 1, characterized in that: S3 specifically: S31. Extract frequency domain amplitude information from the FFT calculation results. Integer multiples of the fundamental frequency are harmonics, and the rest are interharmonics. For harmonics, monitor the harmonic voltage and harmonic current content rates of 2 to 50 times, the effective value of the harmonic current of 2 to 50 times, and calculate the voltage and current total harmonic distortion rate. For interharmonics, monitor the interharmonic voltage and harmonic current content rate of 0.5~49.5 times, and the effective value of harmonic current of 0.5~49.5 times; S32. Perform a square root operation on the voltage value to obtain the effective value of the voltage; calculate the average value every time 16 frames of data are received to obtain the effective average value of the voltage; calculate the absolute value of the difference between the effective value of the voltage and 220V and divide it by 220V to obtain the voltage deviation value; S33, obtaining the signal frequency, and calculating the average frequency every 16 frames of received data; S34: Monitor voltage abnormalities. If the abnormal condition is restored within 10ms to 1min, it is recorded as an abnormality; otherwise, it is not considered an abnormality. S35, flicker monitoring, calculated according to the requirements of IEC-61000-4-15, obtains the instantaneous flicker value at half-cycle intervals, a short-term flicker value is obtained every 10 minutes, and a flicker value is obtained every two hours. Specifically, the RMS value of each frame of data is calculated twice for half a cycle, stored and then a 512-point FFT is performed. The instantaneous flicker value is calculated based on the FFT results, and the short-term flicker value is calculated by accumulating 120 times and the long-term flicker value by accumulating 12 times. S36. After the data processing and calculation are completed, the data is packaged and sent through the UART protocol. The packaged data is parsed and displayed graphically.

5. The power quality analysis method according to claim 1, characterized in that: The calculation formula for harmonic voltage content is as follows: in, Indicates the harmonic voltage content rate, Indicates the n-order harmonic voltage value, Indicates the fundamental voltage value.

6. The ARM-based power quality analysis system is characterized by: include: The data receiving unit is used to receive the power monitoring message data by DMA using the SPI interface and temporarily store the received message data in the RAM; A signal processing unit is used to perform wavelet transform and FFT algorithm processing on the voltage and current signals of the power monitoring message data; Parameter parsing unit, used to analyze the power quality parameters of the power grid, including voltage, frequency, voltage swell / sag, number of short interruptions, short and long flicker, harmonics, and interharmonics, and display them in a visual way; The voltage and current signals of the power monitoring message data are processed by wavelet transform and FFT algorithm as follows: Analyze the message data to obtain the required voltage sampling value; Perform wavelet transform on the collected voltage and current signals; Perform FFT algorithm on the data processed by wavelet transform to convert the time domain data into frequency domain; Wavelet transform is used to decompose the sampled voltage or current signal into high-frequency and low-frequency components to improve the frequency domain resolution, which can be expressed as: in, represents the wavelet function associated with parameters j and k, 、 is a scale variable, j is a frequency domain parameter, is the translation variable, j, k∈Z means that the wavelet after transformation according to j, k belongs to the wavelet function set, Z represents the parameter change set in the wavelet function set, j0 is an arbitrary starting point in the wavelet function set, represents the approximate coefficient, represents the fine coefficient, represents the scaling function, represents the sampled voltage or current signal, and x represents the time variable.

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