Nonlinear load monitoring method and device
By using the zero-crossing method and orthogonal basis calculation of Fourier transform to calculate the fundamental frequency and harmonics of the power grid, the accuracy problem of measuring non-integer multiple harmonics in the power grid is solved, and high frequency resolution and high accuracy harmonic measurement are achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- PETROCHINA CO LTD
- Filing Date
- 2024-11-04
- Publication Date
- 2026-05-08
AI Technical Summary
Existing technologies struggle to accurately and quickly measure non-integer harmonics, especially interharmonics, in power grids, resulting in low frequency resolution and large calculation errors.
The fundamental frequency of the power grid is calculated using the zero-crossing method. Based on the fundamental frequency, the number of sampling points for the Fourier transform is determined, and an orthogonal basis for the Fourier forward transform is established. The amplitude and phase of the fundamental frequency and each integer harmonic are determined through the Fourier forward transform, and then the amplitude and phase of the interharmonics are calculated.
It improves the frequency resolution of non-integer harmonics, reduces frequency leakage and picket fence effect caused by asynchronous algorithms, and improves the accuracy by more than 10 times compared with traditional DFT at a frequency offset of 0.5%, with only an increase in computational cost of one orthogonal basis calculation.
Smart Images
Figure CN121995152A_ABST
Abstract
Description
Technical Field
[0001] This disclosure belongs to the field of monitoring instrument technology, and specifically relates to a nonlinear load monitoring method and device. Background Technology
[0002] With the widespread application of nonlinear devices such as power electronic components in power systems, harmonic pollution in power grids is becoming increasingly serious. For example, controllable or uncontrollable rectifiers, especially rectifiers with capacitive filters, generate interharmonics that are non-integer multiples due to the randomness of the control signals in static frequency converters, welding machines, and electric arc furnaces.
[0003] The frequency converter used in oil extraction is an electrical device that uses power electronic components, and its front end uses a capacitive filter rectifier. Although it has a significant energy-saving effect during operation, it will bring serious harmonic pollution to the power grid. This invention can achieve accurate and rapid measurement of fundamental, harmonic, and interharmonic waves with relatively low resource consumption, providing a basis for further harmonic control or evaluating the control effect.
[0004] Fourier transform (DFT) is generally used for harmonics that are integer multiples of each other. For harmonics that are not integer multiples of each other, N fundamental frequency periods are sampled and extended into a periodic function, which can improve the frequency resolution by N times. This is equivalent to being able to measure the signal of the 1 / Nth harmonic. However, when the harmonic order is an infinite repeating decimal m, since N / m cannot be a periodic function, the Fourier transform of the sampling period extension will introduce asynchronous error. Summary of the Invention
[0005] To address the above problems, this disclosure provides a nonlinear load monitoring method, the method comprising:
[0006] Obtain the preprocessed sampled signal parameters;
[0007] The fundamental frequency of the power grid is obtained by calculating the parameters of the sampled signal using the zero-crossing method.
[0008] The number of sampling points for the Fourier transform is determined based on the fundamental frequency of the power grid, and an orthogonal basis for the Fourier forward transform is established based on the number of sampling points for the Fourier transform and the fundamental frequency of the power grid.
[0009] The amplitude and phase of the fundamental wave and each integer harmonic are determined by the orthogonal basis of the Fourier transform.
[0010] The amplitude and phase of the interharmonics are determined based on the amplitude and phase of the fundamental wave and each integer harmonic, thus enabling nonlinear load monitoring.
[0011] Preferably, obtaining the preprocessed sampled signal parameters includes:
[0012] Acquire three-phase AC voltage signals and three-phase AC current signals;
[0013] The three-phase AC voltage signal and the three-phase AC current signal are reduced in size to obtain the pre-processed three-phase AC voltage signal parameters;
[0014] The three-phase AC current signal is amplified and reduced by transconductance to obtain the preprocessed three-phase AC current signal parameters.
[0015] Preferably, the sampled value signal parameters include: sampled values before different positive zero crossings, sampled values after different positive zero crossings, and sampling period.
[0016] Preferably, the fundamental frequency of the power grid is obtained by calculating the sampled signal parameters using the zero-crossing method, including:
[0017] The parameters of the sampled signal are calculated using the zero-crossing calculation method, and the time interval between multiple zero-crossing non-integer samples is obtained.
[0018] The fundamental frequency of the power grid is obtained by weighting the sampling period with the number of sampling points between integers at zero crossings and combining the time intervals of multiple non-integer samplings at zero crossings.
[0019] Preferably, the amplitude and phase of the fundamental wave are determined using orthogonal bases of the Fourier transform, including:
[0020] The Fourier coefficients of the 50-cycle fundamental wave are obtained by using the orthogonal basis of the Fourier forward transform and the number of sampling points of the Fourier transform.
[0021] The amplitude of the fundamental wave is obtained by weighting the Fourier coefficients of the 50-cycle fundamental wave.
[0022] The phase of the fundamental wave is obtained from its amplitude.
[0023] Preferably, the amplitude and phase of each integer harmonic are determined using orthogonal bases of the Fourier transform, including:
[0024] The Fourier coefficients of the 50m periodic fundamental wave are obtained by using the orthogonal basis of the Fourier forward transform and the number of sampling points of the Fourier transform.
[0025] The amplitude of each integer harmonic is obtained by weighting the Fourier coefficients of the 50m period fundamental wave;
[0026] The phase of each integer harmonic is obtained based on the amplitude of each integer harmonic.
[0027] Preferably, determining the amplitude and phase of the interharmonic based on the amplitude and phase of the fundamental wave and each integer harmonic includes:
[0028] The harmonic amplitude of the interharmonic at each frequency point is calculated based on the number of sampling points in the Fourier transform.
[0029] The harmonic amplitudes of all interharmonics excluding integer harmonics;
[0030] Integrate all interharmonics greater than the harmonic threshold to generate an interharmonic group set;
[0031] For the interharmonics in the interharmonic group set, 10 interharmonic orthogonal bases are established at a frequency interval of 1 / 10 of 1Hz;
[0032] The set of interharmonic subgroups is obtained by calculating the orthogonal basis of interharmonics.
[0033] For the interharmonics in the interharmonic subgroup set, 10 interharmonic orthogonal bases are established at a frequency interval of 1 / 10 of 0.1 Hz;
[0034] Calculate the harmonic amplitude of the interharmonic subgroup based on the interharmonic orthogonal basis;
[0035] The amplitude and phase of the largest element are selected as the amplitude and phase of the interharmonic.
[0036] This disclosure also proposes a nonlinear load monitoring device, the device including an AD conversion circuit, the AD conversion circuit being connected to a current-to-voltage conversion module and a voltage tracking module, the current-to-voltage conversion module being connected to a current transformer, and the voltage tracking module being connected to a voltage divider resistor network;
[0037] The AD conversion circuit is used to acquire waveform values of voltage and current channels, and to calculate the amplitude and phase of harmonics and interharmonics;
[0038] The voltage divider resistor network is used to reduce the three-phase AC voltage signal;
[0039] The current-to-voltage conversion module is used to amplify the three-phase current.
[0040] Preferably, the AD conversion circuit is also connected to a reference voltage and a chip.
[0041] Preferably, the chip is connected to the display screen and the keyboard.
[0042] This disclosure also proposes an electronic device, comprising:
[0043] Processor and memory;
[0044] The processor invokes the computer program stored in the memory to execute any of the nonlinear load monitoring methods described above.
[0045] This disclosure also proposes a computer-readable storage medium.
[0046] The computer-readable storage medium stores a computer program that, when executed by a processor, enables the processor to perform any of the nonlinear load monitoring methods described above.
[0047] This disclosure has the following beneficial effects:
[0048] (1) This disclosure targets integer harmonic components and fundamental frequency, and establishes fundamental orthogonal basis based on fundamental frequency adjustment. It can automatically adjust the frequency difference caused by asynchronous sampling, reduce frequency leakage and picket fence effect caused by asynchronous algorithm. Compared with traditional DFT, the accuracy is improved by more than 10 times when the frequency deviation is 0.5%, and the computational workload only increases by one calculation of orthogonal basis.
[0049] (2) This disclosure uses a double 10-fold frequency division method for inter-harmonics, and only calculates the amplitude exceeding the harmonic threshold, which can greatly reduce the amount of calculation. At the same time, the harmonic calculation uses an independent orthogonal basis and double 10-fold frequency division, which increases the frequency resolution of inter-harmonics by 100 times in the same calculation time.
[0050] Other features and advantages of this disclosure will be set forth in the following description and will be apparent in part from the description or may be learned by practicing the disclosure. The objects and other advantages of this disclosure may be realized and obtained by means of the structures pointed out in the description and the accompanying drawings. Attached Figure Description
[0051] To more clearly illustrate the technical solutions in the embodiments of this disclosure or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0052] Figure 1 A diagram illustrating a nonlinear load monitoring method in an embodiment of this disclosure is shown.
[0053] Figure 2 This diagram illustrates the time interval curves for zero-crossing non-integer sampling in embodiments of this disclosure.
[0054] Figure 3 A flowchart illustrating the calculation of the amplitude and phase of the fundamental wave and each integer harmonic is shown in an embodiment of this disclosure;
[0055] Figure 4 A flowchart illustrating the calculation of the amplitude and phase of interharmonics in an embodiment of this disclosure is shown;
[0056] Figure 5 A diagram of a nonlinear load monitoring device is shown in an embodiment of this disclosure;
[0057] Figure 6 This diagram shows the internal structure of the current-to-voltage conversion module in an embodiment of the present disclosure.
[0058] Figure 7 This diagram illustrates the internal structure of the voltage tracking module in an embodiment of the present disclosure.
[0059] Figure 8 A diagram of a nonlinear load monitoring device is shown in an embodiment of this disclosure;
[0060] In the diagram: 1. Reference voltage; 2. Power supply module; 3. Current-to-voltage conversion module; 4. Voltage divider resistor network; 5. Current transformer; 6. Display LCD; 7. Voltage tracking module; 8. BF609 chip and its peripherals; 9. AD conversion circuit; 10. Keyboard. Detailed Implementation
[0061] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided to make this disclosure more comprehensive and complete, and to fully convey the concept of the example embodiments to those skilled in the art. The described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a full understanding of embodiments of this disclosure. However, those skilled in the art will recognize that the technical solutions of this disclosure can be practiced with one or more of the specific details omitted, or other methods, components, apparatus, steps, etc., can be employed. In other instances, well-known technical solutions are not shown or described in detail to avoid obscuring various aspects of this disclosure.
[0062] Furthermore, the accompanying drawings are merely illustrative of this disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and therefore repeated descriptions of them will be omitted. Some block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities may be implemented in software, in one or more hardware units or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.
[0063] The flowchart shown in the attached diagram is merely an illustrative example and does not necessarily include all steps. For example, some steps may be broken down, while others may be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.
[0064] The terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented, for example, in orders other than those illustrated or described herein.
[0065] Furthermore, the terms “comprising” and “having”, and any variations thereof, are intended to cover non-exclusive inclusion, such that a process, method, system, product, or device that includes a series of steps or sub-modules is not necessarily limited to those steps or sub-modules that are explicitly listed, but may include other steps or sub-modules that are not explicitly listed or that are inherent to such process, method, product, or device.
[0066] This disclosure targets integer harmonic components and the fundamental frequency. It establishes a fundamental orthogonal basis based on the fundamental frequency adjustment, automatically adjusting for frequency differences caused by non-sampling and reducing frequency leakage and picket fence effects caused by asynchronous algorithms. Compared to traditional DFT, it improves accuracy by more than 10 times at a frequency deviation of 0.5%, with only one additional orthogonal basis calculation. Furthermore, the interharmonic calculation uses an independent orthogonal basis and two 10-fold frequency division searches, increasing the frequency resolution of interharmonics by 100 times within the same computation time. This is of great significance for the rapid and accurate measurement of fundamental, harmonic, and interharmonic frequencies in power grids.
[0067] like Figure 1 As shown, this disclosure proposes a nonlinear load monitoring method, the method comprising:
[0068] Obtain the preprocessed sampled signal parameters;
[0069] The fundamental frequency of the power grid is obtained by calculating the parameters of the sampled signal using the zero-crossing method.
[0070] The number of sampling points for the Fourier transform is determined based on the fundamental frequency of the power grid, and an orthogonal basis for the Fourier forward transform is established based on the number of sampling points for the Fourier transform and the fundamental frequency of the power grid.
[0071] The amplitude and phase of the fundamental wave and each integer harmonic are determined by the orthogonal basis of the Fourier transform.
[0072] The amplitude and phase of the interharmonics are determined based on the amplitude and phase of the fundamental wave and each integer harmonic, thus enabling nonlinear load monitoring.
[0073] Specifically, the parameters of the preprocessed sampled signal are obtained, including:
[0074] Acquire three-phase AC voltage signals and three-phase AC current signals;
[0075] The three-phase AC voltage signal and the three-phase AC current signal are reduced in size to obtain the pre-processed three-phase AC voltage signal parameters;
[0076] The three-phase AC current signal is amplified and reduced by transconductance to obtain the preprocessed three-phase AC current signal parameters.
[0077] Specifically, the sampled signal parameters include: sampled values before different positive zero crossings, sampled values after different positive zero crossings, and the sampling period.
[0078] Specifically, the zero-crossing method is used to calculate the sampled signal parameters to obtain the fundamental frequency of the power grid, including:
[0079] The parameters of the sampled signal are calculated using the zero-crossing calculation method, and the time interval between multiple zero-crossing non-integer samples is obtained.
[0080] The fundamental frequency of the power grid is obtained by weighting the sampling period with the number of sampling points between integers at zero crossings and combining the time intervals of multiple non-integer samplings at zero crossings.
[0081] In this embodiment, as Figure 2 As shown, the time interval between two zero-crossing non-integer samples can be calculated using the following formula:
[0082]
[0083] In the formula: t Δ t represents the time interval between two zero-crossing non-integer samples; Δ1 t represents the time from the first positive zero crossing to the first sampled data; Δ2 y represents the time from the second positive zero crossing to the nth sampled data; y0 represents the sampled value before the first positive zero crossing; y1 represents the sampled value after the first positive zero crossing; y n This represents the sampled value before the second positive zero crossing; y n+1 The sampled value after the second positive zero crossing; T represents the sampling period, which is 78.125us in this embodiment (corresponding to a sampling rate of 12.8kSPS).
[0084] Assuming the number of sampling points for integers between two zero crossings is n, since n×T s +t Δ = 1 / f, so the frequency can be expressed as:
[0085]
[0086] In this embodiment, as Figure 3 As shown, the number of sampling points for the Fourier transform is determined based on the fundamental frequency of the power grid, and an orthogonal basis for the Fourier forward transform is established based on the number of sampling points and the fundamental frequency of the power grid. The specific details are as follows:
[0087] 1) Calculate the number of sampling points for the DFT.
[0088] The sampling data in this disclosure is saved for 2 seconds, with a total of 25,600 sampling data points, and the refresh time is 1 second.
[0089] The purpose of this design is that the fundamental frequency of the power grid is 50Hz most of the time, and 12,800 data points are sampled per second for calculation. When the power grid frequency is below 50Hz, this invention requires more than 12,800 data points. Holding data for 2 seconds prevents insufficient sampling data when the power grid frequency is below 50Hz; that is, data is saved for 2 seconds, and the data refresh rate is 1 second. In reality, each data saving process involves nearly 1 second of repeating the data from the previous second.
[0090]
[0091] Where: N W1 This represents the approximate value of the sampling points participating in the DFT calculation within a 50-cycle time window; ROUND represents the rounding function; f represents the fundamental frequency.
[0092] 2) Construct orthogonal bases for the fundamental wave
[0093]
[0094] In the formula: i represents the sampling value number; 50 represents 50 periods; A1 represents the set of arrays of orthogonal bases.
[0095] Specifically, the amplitude and phase of the fundamental wave are determined through the orthogonal basis of the Fourier transform, including:
[0096] The Fourier coefficients of the 50-cycle fundamental wave are obtained by using the orthogonal basis of the Fourier forward transform and the number of sampling points of the Fourier transform.
[0097] The amplitude of the fundamental wave is obtained by weighting the Fourier coefficients of the 50-cycle fundamental wave.
[0098] The phase of the fundamental wave is obtained from its amplitude.
[0099] In this embodiment, the formulas for calculating the amplitude and phase of the fundamental wave are as follows:
[0100]
[0101] In the formula: C1 represents the Fourier system of the fundamental wave; A1 represents the amplitude of the fundamental wave; φ1 represents the phase of the fundamental wave; im represents the imaginary part; re represents the real part; F 50 This represents the Fourier coefficients of the fundamental wave over 50 periods.
[0102] It should be noted that the impact of self-built orthogonal basis on frequency error is very small (49.5-50.5Hz) and can be almost ignored.
[0103] As can be seen from Equation 4, the asynchronous error of DFT is:
[0104]
[0105] If the default DFT orthogonal basis is used, the measurement result is proportional to the frequency deviation. If the frequency is 50.5Hz, the frequency deviation is 1%, resulting in a measurement error of approximately 0.5%.
[0106] When the grid frequency deviation reaches 1%, the normal DFT amplitude error has an impact of 0.5%.
[0107] The influence of amplitude error in this invention It increased by about 128 times.
[0108] Specifically, the amplitude and phase of each integer harmonic are determined using the orthogonal basis of the Fourier transform, including:
[0109] The Fourier coefficients of the 50m periodic fundamental wave are obtained by using the orthogonal basis of the Fourier forward transform and the number of sampling points of the Fourier transform.
[0110] The amplitude of each integer harmonic is obtained by weighting the Fourier coefficients of the 50m period fundamental wave;
[0111] The phase of each integer harmonic is obtained based on the amplitude of each integer harmonic.
[0112] In this embodiment, the formulas for calculating the amplitude and phase of integer harmonics are as follows:
[0113]
[0114] In the formula: C m A Fourier system representing the m-th harmonic; A m φ represents the amplitude of the m-th harmonic; m The m-th harmonic represents the phase; im represents the imaginary part; re represents the real part; F 50m This represents the Fourier coefficients of a fundamental wave with 50m periods.
[0115] Measuring m-integer harmonics does not require re-establishing an orthogonal basis. It is sufficient to multiply the vector array A1 of the orthogonal basis established by formula (4) by x(i) at m-intervals. Since the length of the orthogonal basis established by formula (4) is only N... W1 Since the m-th harmonic is counted at intervals of m, the required length is m × N. W1 An orthogonal basis is a basis of length N. W1The periodic function can be realized by taking the modulus of the orthogonal basis, which reduces the time required to calculate the orthogonal basis.
[0116] Specifically, the amplitude and phase of the interharmonics are determined based on the amplitude and phase of the fundamental wave and each integer harmonic, including:
[0117] The harmonic amplitude of the interharmonic at each frequency point is calculated based on the number of sampling points in the Fourier transform.
[0118] The harmonic amplitudes of all interharmonics excluding integer harmonics;
[0119] Integrate all interharmonics greater than the harmonic threshold to generate an interharmonic group set;
[0120] For the interharmonics in the interharmonic group set, 10 interharmonic orthogonal bases are established at a frequency interval of 1 / 10 of 1Hz;
[0121] The set of interharmonic subgroups is obtained by calculating the orthogonal basis of interharmonics.
[0122] For the interharmonics in the interharmonic subgroup set, 10 interharmonic orthogonal bases are established at a frequency interval of 1 / 10 of 0.1 Hz;
[0123] Calculate the harmonic amplitude of the interharmonic subgroup based on the interharmonic orthogonal basis;
[0124] The amplitude and phase of the largest element are selected as the amplitude and phase of the interharmonic.
[0125] In this embodiment, as Figure 4 As shown, the steps for calculating the amplitude and phase of interharmonics are as follows:
[0126] a) Step 1
[0127] As shown in formula (8), the amplitude of all interharmonics excluding integer harmonics is calculated in 1Hz intervals from 5Hz to 5kHz.
[0128] The amplitude A of the interharmonics at each frequency point m As shown in formula (8)
[0129]
[0130] In the formula: F k This represents the Fourier coefficients of the fundamental wave over k periods.
[0131] b) Step Two, Step Three
[0132] Perform a coarse screening of all subharmonics after removing integer harmonics;
[0133] The harmonic content threshold can be set: the default voltage is coarsely selected based on the harmonic content threshold of 0.015%Un (nominal voltage), and the threshold for current harmonic content is 0.05%In.
[0134] Note: According to the GB / T 14549-1993 standard for power quality and harmonics in public power grids, the measurement accuracy of Class A instruments is 0.05%Un (rated voltage) when the voltage content is <1%, and the measurement accuracy is 0.05%In (rated current) when the current harmonic content is <1%.
[0135] For A in formula (8) m Interharmonics exceeding the harmonic threshold are stored in the interharmonic group set SF. ih middle:
[0136] SF ih ={F k-1 ,F k ,F k+1 ...} / / List all values greater than the harmonic threshold (9)
[0137] For all elements in the interharmonic group set, establish 10 orthogonal bases of interharmonic groups according to Formula 10 at frequency intervals of 1 / 10 of 1Hz. Add 5 points before the m = k / 50th harmonic and 4 points after it.
[0138]
[0139]
[0140] In the formula: i represents the corresponding sampling point sequence; u = {-5, -4, -3, -1, 0, 1, 2, 3, 4}, 10 0.1Hz intervals; A u An array representing the set of orthogonal basis vectors; N Wu This represents the approximate value of the sampling points involved in the DFT calculation within a time window of 50u cycles.
[0141] Calculate the harmonic amplitude of the interharmonic group with an element harmonic interval frequency of 0.1 Hz using formula (11):
[0142]
[0143] In the formula: F k,u C represents the Fourier coefficients of the fundamental wave with (k+u / 10) / 50 periods; k,u Represents the (k+u / 10) / 50th harmonic coefficient; A m =|C k,u | represents the amplitude of (k+u / 10) / 50th harmonic; u represents -5, -4, ..., 4; 10th harmonics with an interval of 0.1Hz; k represents the corresponding kth harmonic.
[0144] All harmonic amplitudes A in step three m Interharmonics exceeding the harmonic threshold are stored in the interharmonic subgroup set SSF. ih Medium, SSF ih ={F k，u ,…,F k+1，u+1 ,…}.
[0145] For all elements within the interharmonic subgroup, establish 10 orthogonal bases for the interharmonic subgroups according to formula (12) at frequency intervals of 1 / 10 of 0.1Hz. Add 5 points before and 4 points after the m-th harmonic (500) as the center, and calculate 10 interval harmonics according to formula (13) to form a minimum harmonic subset SSSF. ih .
[0146]
[0147] Where: N Wuv This represents the approximate value of the sampling points participating in the DFT calculation within a time window of 50µs; i represents the corresponding sampling point sequence; v = {-5, -4, -3, -1, 0, 1, 2, 3, 4}, 10 intervals of 0.01Hz; A uv An array representing the set of orthogonal basis vectors.
[0148] Calculate the harmonic amplitude of the interharmonic subgroup with an element harmonic interval frequency of 0.01Hz using formula (13):
[0149]
[0150] In the formula: F k,u,v C represents the Fourier coefficients of the fundamental wave with (k+u / 10+v / 100) / 50 periods; k,u,v Represents the (k+u / 10+v / 100) / 50th harmonic coefficient; A m =|C k,u,v | represents the amplitude of the (k+u / 10+v / 100) / 50th harmonic; φ m Let (k+u / 10+v / 100) / 50 represent the phase of the harmonic; k represents the kth interharmonic; u represents the uth subharmonic of the kth interharmonic; v represents the vth harmonic of the uth subharmonic of the kth interharmonic.
[0151] The elements of all 10 harmonic subgroups form a harmonic minimum subset SSSF. ih :
[0152] SSSF ih ={F k,u,-5 ,F k,u,-4,……,F k,u,4}, 10 elements.
[0153] Since the frequency interval of interharmonics is generally more than 1 Hz, therefore, SSSF is taken. ih China A m The magnitude A of the element with the largest value m and phase φ m As a subset of interharmonics, the calculated order of the interharmonics is equal to (k + u / 10 + v). max / 100) / 50; where, v max For the minimum harmonic subset A m The index v of the element with the largest value.
[0154] like Figure 5 As shown, this disclosure also proposes a nonlinear load monitoring device, the device including an AD conversion circuit 9, the AD conversion circuit 9 being connected to a current-to-voltage conversion module 3 and a voltage tracking module 7, the current-to-voltage conversion module 3 being connected to a current transformer 5, and the voltage tracking module 7 being connected to a voltage divider resistor network 4;
[0155] The AD conversion circuit 9 is used to acquire waveform values of voltage and current channels, and to calculate the amplitude and phase of harmonics and interharmonics;
[0156] The voltage divider resistor network 4 is used to reduce the three-phase AC voltage signal;
[0157] The current-to-voltage conversion module 3 is used to amplify the three-phase current.
[0158] Specifically, the AD conversion circuit 9 is also connected to the reference voltage 1 and the chip 8.
[0159] Specifically, the chip 8 is connected to the display screen 6 and the keyboard 10.
[0160] In this device, reference voltage 1 is a 2.5V voltage value output by chip ADR441B;
[0161] Power module 2 uses a linear power supply with + / -15V, 5V, 1.8V, and 3.3V outputs, and a current output of 2A;
[0162] Current-to-voltage conversion module 3, such as Figure 6 As shown, it consists of an operational amplifier OPA2277U5 and an RF resistor with 0.01% accuracy (1ppm temperature drift). The RF resistor has a resistance of 100 ohms and converts a 10mA current output to a 1V voltage output.
[0163] The voltage divider resistor network 4 uses high-stability resistors with 1ppm temperature drift and 0.01% accuracy. The values of R1, R3, and R5 are 199K, and the values of R2, R4, and R6 are 1K. The voltage division ratio is 200:1, which means that with a voltage input of 200V, the secondary output is 1V.
[0164] The current transformer 5 is a 0.05 class zero flux current transformer with a transformation ratio of 8000:1, which means an 80A current input, a secondary output of 10mA, and a frequency range of 5Hz to 2.5kHz.
[0165] The LCD6 display module is directly driven by the BF609 chip and its peripherals through the AMC interface.
[0166] Voltage tracking module 7, such as Figure 7 As shown, the emitter follower circuit is composed of OPA2277 operational amplifier U7;
[0167] The BF609 chip and its peripherals 8 consist of the ADI BF609 chip and its peripherals. The chip has a large number of built-in peripherals, including one SPI interface, serial port, timer, 16 general-purpose I / O ports, AMC interface (asynchronous memory interface), etc., and 256MB YTE DRAM, which is used to complete the core algorithm, task scheduling, display and input of this invention.
[0168] The AD conversion circuit 9 uses an 8-channel strictly synchronous 24-bit sigma-delta AD converter ADS1278 with a typical integration error of ±0.0003% and a maximum sampling rate of 128KSPS.
[0169] Keyboard 10 is a simple keyboard with 6 key inputs connected to the 6 I / O pins of the BF609 processor chip and its peripherals. The secondary output of the current transformer 5 is connected to the input of the current-to-voltage conversion module 3. The output of the current-to-voltage conversion module 3 is connected to the three input channels of the AD conversion circuit 9. The output of the voltage divider resistor network 4 is connected to the input of the voltage tracking module 7. The output of the voltage tracking module 7 is connected to the three input channels of the AD conversion circuit 9. The conversion output of the AD conversion circuit 9 is connected to the BF609 chip and its peripherals 8 via the SPI port. The BF609 chip and its peripherals 8 are connected to the display LCD 6 via the AMC interface. The BF609 chip and its peripherals 8 are connected to the display keyboard 10 via the I / O interface.
[0170] The BF609 chip and its peripherals 8 read the AD conversion circuit 9 through the SPI interface. The current and voltage signals of the current transformers 5a / 5b / 5c and the voltage divider resistor network 4 are collected to form sampling data x[n]. After data calculation and storage of x[n], it is available for reading by a remote server through the serial port. It is also connected to the keyboard 10 through the IO interface and to the display LCD 6 through the AMC interface to realize local human-machine operation.
[0171] The working principle of this device is as follows:
[0172] The voltage divider resistor network 4 reduces the three-phase AC voltage signal by 200 times and inputs it to the voltage tracking module 7, which then inputs it to the three channels of the AD conversion module 9. The three-phase current is reduced by 8000 times through the current transformer 5 and input to the current-voltage conversion module 3. The current-voltage conversion module 3 amplifies the current through transconductance and outputs it to the three channels of the AD conversion module 9. The AD conversion module ADS1278 continuously acquires the waveform values of the voltage and current channels at a sampling rate of 12.8KSPS and calculates harmonics, interharmonics, and other electrical parameter values for viewing on the human-machine interface or uploading them to a remote server via serial port.
[0173] For voltage input: AC voltage input is U_L1, U_L2, U_L3, UN. Assume the output values of voltage tracking module 7 are Ua, Ub, Uc, and its transformation ratio is 200 times (voltage division ratio of voltage divider resistor network 4).
[0174]
[0175] For current input, the AC current input is I_L1, I_L2, I_L3, and the output voltage values of the current conversion module are assumed to be VIa, VIb, VIc.
[0176]
[0177] In the formula, 8000 is the current transformer ratio, and 100Ω is... Figure 6 The resistance value of RF.
[0178] After voltage and current input are converted to analog-to-digital (AD) signals, the AD converter continuously samples at a sampling rate of 12.8 kSPS, saving data once every second. Two seconds prior to the current time of each data point, after calibration, the sampled data corresponding to the first value is obtained.
[0179] x Ua (n), x Ub (n), x Uc (n) Floating-point storage, unit is V;
[0180] x Ia (n), x Ib(n), x Ic (n) Floating-point storage, unit is A;
[0181] Sampling data after Figure 1 The algorithm calculates the amplitudes of the fundamental wave, each harmonic, and interharmonic waves, as well as the signal A. m φ m .
[0182] It is worth noting that this disclosure only calculates up to the 50th harmonic. Since the properties of all six channels are the same, the analysis process in this invention uses x(n) to represent x. Ua (n), x Ub (n), x Uc (n), x Ia (n), x Ib (n), x Ic (n) Signal.
[0183] like Figure 8 As shown, corresponding to the nonlinear load monitoring method provided above, this disclosure also provides a nonlinear load monitoring device. Since the embodiment of this device is similar to the embodiment of the method described above, the description is relatively simple. For relevant details, please refer to the description in the method embodiment section above. The device described below is merely illustrative. This device may include: a processor 1, a memory 2, a communication bus (i.e., the aforementioned device bus), and a lookup engine. The processor 1 and the memory 2 communicate with each other through the communication bus and communicate with external systems through a communication interface. The processor 1 can call logical instructions in the memory 2 to execute the nonlinear load monitoring method.
[0184] Furthermore, the logical instructions in the aforementioned memory 2 can be implemented as software functional units and sold or used as independent products, and can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this disclosure, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this disclosure. The aforementioned storage medium includes various media capable of storing program code, such as memory chips, USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.
[0185] On the other hand, this disclosure also provides a processor-readable storage medium storing a computer program 3, which, when executed by a processor 1, is implemented to perform the nonlinear load monitoring method provided in the above embodiments.
[0186] The processor-readable storage medium can be any available medium or data storage device that the processor 1 can access, including but not limited to magnetic memory (e.g., floppy disk, hard disk, magnetic tape, magneto-optical disk (MO)), optical memory (e.g., CD, DVD, BD, HVD), and semiconductor memory (e.g., ROM, EPROM, EEPROM, non-volatile memory (NAND FLASH), solid-state drive (SSD)).
[0187] Those skilled in the art should understand that, despite the detailed description of this disclosure with reference to the foregoing embodiments, modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this disclosure.
Claims
1. A nonlinear load monitoring method, characterized in that, The method includes: Obtain the preprocessed sampled signal parameters; The fundamental frequency of the power grid is obtained by calculating the parameters of the sampled signal using the zero-crossing method. The number of sampling points for the Fourier transform is determined based on the fundamental frequency of the power grid, and an orthogonal basis for the Fourier forward transform is established based on the number of sampling points for the Fourier transform and the fundamental frequency of the power grid. The amplitude and phase of the fundamental wave and each integer harmonic are determined by the orthogonal basis of the Fourier transform. The amplitude and phase of the interharmonics are determined based on the amplitude and phase of the fundamental wave and each integer harmonic, thus enabling nonlinear load monitoring.
2. The nonlinear load monitoring method according to claim 1, characterized in that, Obtain the parameters of the preprocessed sampled signal, including: Acquire three-phase AC voltage signals and three-phase AC current signals; The three-phase AC voltage signal and the three-phase AC current signal are reduced in size to obtain the pre-processed three-phase AC voltage signal parameters; The three-phase AC current signal is amplified and reduced by transconductance to obtain the preprocessed three-phase AC current signal parameters.
3. The nonlinear load monitoring method according to claim 2, characterized in that, The sampled signal parameters include: sampled values before different positive zero crossings, sampled values after different positive zero crossings, and the sampling period.
4. The nonlinear load monitoring method according to claim 3, characterized in that, The fundamental frequency of the power grid is obtained by calculating the sampled signal parameters using the zero-crossing method, including: The parameters of the sampled signal are calculated using the zero-crossing calculation method, and the time interval between multiple zero-crossing non-integer samples is obtained. The fundamental frequency of the power grid is obtained by weighting the sampling period with the number of sampling points between integers at zero crossings and combining the time intervals of multiple non-integer samplings at zero crossings.
5. The nonlinear load monitoring method according to claim 1, characterized in that, The amplitude and phase of the fundamental wave are determined using the orthogonal basis of the Fourier transform, including: The Fourier coefficients of the 50-cycle fundamental wave are obtained by using the orthogonal basis of the Fourier forward transform and the number of sampling points of the Fourier transform. The amplitude of the fundamental wave is obtained by weighting the Fourier coefficients of the 50-cycle fundamental wave. The phase of the fundamental wave is obtained from its amplitude.
6. The nonlinear load monitoring method according to claim 1, characterized in that, The amplitude and phase of each integer harmonic are determined using the orthogonal basis of the Fourier transform, including: The Fourier coefficients of the 50m periodic fundamental wave are obtained by using the orthogonal basis of the Fourier forward transform and the number of sampling points of the Fourier transform. The amplitude of each integer harmonic is obtained by weighting the Fourier coefficients of the 50m period fundamental wave; The phase of each integer harmonic is obtained based on the amplitude of each integer harmonic.
7. The nonlinear load monitoring method according to claim 1, characterized in that, Based on the amplitude and phase of the fundamental wave and each integer harmonic, determine the amplitude and phase of the interharmonic, including: The harmonic amplitude of the interharmonic at each frequency point is calculated based on the number of sampling points in the Fourier transform. The harmonic amplitudes of all interharmonics excluding integer harmonics; Integrate all interharmonics greater than the harmonic threshold to generate an interharmonic group set; For the interharmonics in the interharmonic group set, 10 interharmonic orthogonal bases are established at a frequency interval of 1 / 10 of 1Hz; The set of interharmonic subgroups is obtained by calculating the orthogonal basis of interharmonics. For the interharmonics in the interharmonic subgroup set, 10 interharmonic orthogonal bases are established at a frequency interval of 1 / 10 of 0.1 Hz; Calculate the harmonic amplitude of the interharmonic subgroup based on the interharmonic orthogonal basis; The amplitude and phase of the largest element are selected as the amplitude and phase of the interharmonic.
8. A nonlinear load monitoring device, characterized in that, The device includes an AD conversion circuit (9), which is connected to a current-to-voltage conversion module (3) and a voltage tracking module (7). The current-to-voltage conversion module (3) is connected to a current transformer (5), and the voltage tracking module (7) is connected to a voltage divider resistor network (4). The AD conversion circuit (9) is used to acquire the waveform values of the voltage and current channels, and to calculate the amplitude and phase of harmonics and interharmonics; The voltage divider resistor network (4) is used to reduce the three-phase AC voltage signal; The current-to-voltage conversion module (3) is used to amplify the three-phase current.
9. The nonlinear load monitoring device according to claim 8, characterized in that, The AD conversion circuit (9) is also connected to the reference voltage (1) and the chip (8).
10. The nonlinear load monitoring device according to claim 9, characterized in that, The chip (8) is connected to the display screen (6) and the keyboard (10).
11. An electronic device, characterized in that, include: Processor and memory; The processor invokes the computer program stored in the memory to execute the nonlinear load monitoring method according to any one of claims 1 to 7.
12. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, enables the processor to perform the nonlinear load monitoring method according to any one of claims 1 to 7.