Electric power metering signal filtering method and equipment

Abstract

The invention discloses an electric power metering signal filtering method and equipment, relates to the technical field of electric power metering, and solves the technical problems that the filtering effect of a traditional filtering method for filtering strong electromagnetic signal interference is not ideal and the filtering requirement of electric power metering is difficult to meet on the premise that fundamental waves and effective harmonic waves are reserved. The method comprises the following steps: acquiring a metering signal, and acquiring the power frequency of the metering signal through a frequency calculation model; performing orthogonal modulation on the metering signal according to the power frequency to obtain an amplitude and a phase of a fundamental wave of the metering signal; according to the power frequency, the amplitude and the phase, fitting to generate a fundamental wave of the metering signal; and on the basis of the fundamental wave, filtering the metering signal through a time domain filtering model to obtain the harmonic wave of the metering signal. According to the invention, the interference of strong electromagnetic signals can be effectively filtered on the premise of keeping fundamental waves and harmonic waves, and the healthy operation of a power grid and the accuracy of electric energy metering are ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of electric power metering, and in particular to a method and device for filtering electric power metering signals. Background Art

[0002] In the field of power metering, accurate measurement of power consumption is crucial, not only involving the calculation of power, but also related to the operation efficiency and energy management of the power grid. In order to ensure the accuracy of power metering, it is necessary to retain the fundamental wave (45Hz~55Hz) of the metering signal as well as the effective harmonics (below 20th order). The fundamental wave is the main frequency component of the voltage or current in the power system, which is usually the same as the frequency of the power grid and represents the main part of the power. Therefore, it is necessary to accurately measure the fundamental wave to determine the actual power consumption. Harmonics are distorted components of the voltage or current waveform generated by nonlinear loads, and the frequencies of these distortion components are integer multiples of the fundamental frequency. Although harmonics only account for a small part of the power, they can cause damage to power grid equipment, such as transformers, generators, and cables. Therefore, in order to ensure the healthy operation of the power grid and the accuracy of power metering, it is very necessary to monitor and control harmonics.

[0003] like Figure 1 As shown in the figure, it is the waveform 1 of the standard fundamental wave in power frequency metering, and its fundamental wave frequency is 50Hz. It can be seen from the figure that the waveform 1 is very smooth. In the actual power grid, the metering signal will be affected by a variety of electrical equipment, and the signal will contain various harmonic signals. In the standard power metering system, it is considered that harmonics below the 20th order are valid metering signals and need to be retained. Figure 2 As shown, waveform 2 is a fundamental wave plus harmonics. It can be seen from the figure that waveform 2 is sawtooth-shaped and is affected by harmonics and is no longer a smooth sine waveform. Figure 1 and Figure 2 The waveforms in the figure are all waveforms that need to be retained during the electric energy metering process.

[0004] In addition, when analog signals are converted into digital signals, background noise (also called random noise or white noise) will be generated. Its waveform is as follows: Figure 3 As shown in the figure, it can be seen that its waveform is Figure 2 The middle waveform 2 is more densely jagged. Background noise is usually a high-frequency signal, which is relatively easy to remove. It can usually be basically filtered out by filtering it with a FIR (Finite Impulse Response) low-pass filter.

[0005] However, in the process of electric energy metering, normal metering signals are more susceptible to interference from high-intensity electromagnetic signals, such as Figure 4As shown in the figure, it is the waveform 4 of the metering signal interfered by the electromagnetic signal. It can be seen from the figure that there are several abnormally prominent peaks, which are caused by strong interference and are signals that need to be filtered out. Figure 4 Waveform 4 in the figure is currently filtered using a traditional digital filter, such as Figure 5-Figure 7 As shown, waveform 4 is filtered by FIR filter, IIR filter (recursive filter) and wavelet transform while retaining the fundamental wave and harmonic wave. It can be seen from the figure that there are still abnormally prominent peaks, the strong electromagnetic interference is not effectively filtered out, and the filtering effect is not ideal.

[0006] In the process of implementing the present invention, the inventors found that there are at least the following problems in the prior art:

[0007] Under the premise of retaining the fundamental wave and effective harmonics, the traditional filtering method has an unsatisfactory filtering effect in filtering out strong electromagnetic signal interference and is difficult to meet the filtering requirements of power metering. Summary of the invention

[0008] The purpose of the present invention is to provide a method and device for filtering electric power metering signals, so as to solve the technical problem that the traditional filtering method has an unsatisfactory filtering effect of filtering out strong electromagnetic signal interference under the premise of retaining fundamental wave and effective harmonics, and it is difficult to meet the filtering requirements of electric power metering. The preferred technical solutions among the many technical solutions provided by the present invention can produce many technical effects as described below.

[0009] To achieve the above object, the present invention provides the following technical solutions:

[0010] The present invention provides a filtering method for an electric power metering signal, comprising the following steps: obtaining a metering signal, and obtaining the power frequency of the metering signal through a frequency calculation model; performing orthogonal modulation on the metering signal according to the power frequency to obtain the amplitude and phase of the fundamental wave of the metering signal; fitting and generating the fundamental wave of the metering signal according to the power frequency, amplitude and phase; based on the fundamental wave, filtering the metering signal through a time domain filtering model to obtain the fundamental wave plus harmonics of the metering signal.

[0011] Optionally, obtaining the power frequency of the metering signal through a frequency calculation model includes: constructing a right triangle at the starting point and the ending point of the power frequency cycle with two sampling points before and after the zero crossing point as the hypotenuse; wherein the sampling points are sampling values ​​of the metering signal, and the sampling points of each power frequency cycle together form the waveform of the metering signal; according to the right triangle, calculating the time interval t1 from the zero crossing point at the starting point to the next sampling point, and the time interval t2 from the last sampling point at the ending point to the zero crossing point; according to the time interval t1 and the time interval t2, the power frequency is calculated.

[0012] Optionally, the calculation formula for obtaining the power frequency f is:

[0013] Wherein, n is the sampling rate of sampling the metering signal; N is the number of sampling points actually collected in one power frequency cycle.

[0014] Optionally, the method of filtering the metering signal through a time domain filtering model based on the fundamental wave to obtain harmonics of the metering signal includes: adding a waveform y1 with an amplitude greater than a% of the fundamental wave and a waveform y2 with an amplitude less than a% of the fundamental wave to the waveform diagram of the metering signal; comparing each sampling point on the metering signal with the waveform y1 and the waveform y2; and replacing the sampling points that are beyond the range of the waveform y1 and the waveform y2 by a recovery strategy to obtain the harmonics of the metering signal.

[0015] Optionally, the sampling points exceeding the range of the waveform y1 and the waveform y2 are replaced by a recovery strategy, including: replacing the sampling points exceeding the range of the waveform y1 and the waveform y2 with sampling points at corresponding positions in the first n periods or the last n periods.

[0016] Optionally, the sampling points exceeding the range of the waveform y1 and the waveform y2 are replaced by a recovery strategy, including: the sampling points exceeding the range of the waveform y1 and the waveform y2 are replaced by the values ​​of the corresponding positions of the fundamental wave.

[0017] Optionally, obtaining the fundamental wave plus harmonics of the metering signal includes: after obtaining the fundamental wave plus harmonics of the metering signal, filtering the metering signal through a digital filter to obtain a final fundamental wave plus harmonics.

[0018] Optionally, the orthogonal modulation of the metering signal according to the power frequency to obtain the amplitude and phase of the fundamental wave of the metering signal includes: generating a cosine wave with the same frequency as the power frequency, and a sine wave with the same frequency as the power frequency; multiplying the metering signal with the cosine wave and the sine wave, respectively, to obtain an I component signal and a Q component signal after modulation; filtering the I component signal and the Q component signal, and superimposing them to obtain a modulated signal of the metering signal; and using the amplitude and phase of the modulated signal as the amplitude and phase of the fundamental wave of the metering signal.

[0019] Optionally, the obtaining of the metering signal and obtaining the power frequency of the metering signal through a frequency calculation model include: obtaining an initial power frequency through the frequency calculation model, and performing Kalman filtering on the initial power frequency to obtain the power frequency of the metering signal.

[0020] A filtering device for electric power metering signals, comprising:

[0021] one or more processors;

[0022] The memory is used to store one or more computer programs, and the one or more processors are used to execute the one or more computer programs stored in the memory, so that the one or more processors perform a filtering method for an electric power metering signal as described in any one of the above items.

[0023] Implementing one of the above technical solutions of the present invention has the following advantages or beneficial effects:

[0024] Since there may be some tiny time deviations or synchronization deviations in the actual sampling process of the metering signal, the actual number of sampling points in each cycle may not be the number of sampling points of the standard industrial frequency. Therefore, the present invention first calculates the actual and accurate industrial frequency through a frequency calculation model, and obtains the amplitude and phase of the fundamental wave through accurate industrial frequency orthogonal modulation. According to the industrial frequency, amplitude and phase, the fundamental wave of the metering signal can be fitted and generated, and an accurate fundamental wave signal can be obtained; based on the fundamental wave, the metering signal is filtered through a time domain filtering model to obtain accurate harmonics; the method of the present invention can effectively filter out the interference of strong electromagnetic signals while retaining the fundamental wave and harmonics, thereby ensuring the healthy operation of the power grid and the accuracy of electric energy metering. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. It is obvious that the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work. In the drawings:

[0026] Figure 1 It is a waveform diagram of the fundamental wave of the metering signal of the prior art of the present invention;

[0027] Figure 2 is a waveform diagram of harmonics of a metering signal of the prior art of the present invention;

[0028] Figure 3 It is a waveform diagram of a metering signal interfered by background noise in the prior art of the present invention;

[0029] Figure 4 It is a waveform diagram of a metering signal interfered by strong electromagnetic noise in the prior art of the present invention;

[0030] Figure 5 is a flow chart of a method for filtering electric power metering signals according to an embodiment of the present invention;

[0031] Figure 6 is a discrete graph of sampling points of a metering signal according to an embodiment of the present invention;

[0032] Figure 7 is a flow chart of step S1 of a method for filtering electric power metering signals according to an embodiment of the present invention;

[0033] Figure 8 It is a local enlarged diagram of the sampling point of the metering signal at the zero crossing of the metering signal of the first embodiment of the present invention;

[0034] Fig. 9 is a flow chart of step S2 of a method for filtering electric power metering signals according to an embodiment of the present invention;

[0035] Fig.10 is a waveform diagram of a fundamental wave generated by fitting in the first embodiment of the present invention;

[0036] Fig.11 This is an overlapping waveform diagram of a measurement signal waveform and a fitting generated fundamental wave in the first embodiment of the present invention;

[0037] Fig.12 is a flow chart of step S4 of a method for filtering electric power metering signals according to an embodiment of the present invention;

[0038] Fig.13 is a waveform diagram of a time domain filtering model according to a first embodiment of the present invention;

[0039] Fig.14 is a partially enlarged waveform diagram of the time domain filtering model of the first embodiment of the present invention;

[0040] Fig.15 It is a waveform diagram of harmonics after filtering according to the first embodiment of the present invention. DETAILED DESCRIPTION

[0041] In order to make the purpose, technical solutions and advantages of the present invention clearer, the various exemplary embodiments to be described below will refer to the corresponding drawings, which constitute a part of the exemplary embodiments, wherein various exemplary embodiments that may be used to implement the present invention are described. Unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementation methods described in the following exemplary embodiments do not represent all implementation methods consistent with the present disclosure. It should be understood that they are only examples of processes, methods, devices, etc. that are consistent with some aspects of the present disclosure as detailed in the attached claims, and other embodiments may also be used, or the embodiments listed herein may be modified in structure and function without departing from the scope and essence of the present invention.

[0042] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", etc. indicate the orientation or positional relationship based on the drawings, which is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the elements referred to must have a specific orientation, be constructed and operated in a specific orientation. The terms "first", "second", etc. are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. The term "multiple" means two or more. The terms "connected" and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, an integral connection, a mechanical connection, an electrical connection, a communication connection, a direct connection, an indirect connection through an intermediate medium, and can be the internal connection of two elements or the interaction relationship between two elements. The term "and / or" includes any and all combinations of one or more related listed items. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to the specific circumstances.

[0043] In order to illustrate the technical solution of the present invention, a specific embodiment is used below for description, and only the parts related to the embodiment of the present invention are shown.

[0044] Embodiment 1:

[0045] like Figure 5 As shown, the present invention provides a filtering method for an electric power metering signal, comprising the following steps: S1, obtaining a metering signal, and obtaining the power frequency of the metering signal through a frequency calculation model; S2, performing orthogonal modulation on the metering signal according to the power frequency to obtain the amplitude and phase of the fundamental wave of the metering signal; S3, fitting and generating the fundamental wave of the metering signal according to the power frequency, amplitude and phase; S4, filtering the metering signal based on the fundamental wave through a time domain filtering model to obtain the fundamental wave plus harmonics of the metering signal.

[0046] Since there may be some slight time deviations or synchronization deviations in the actual sampling process of the metering signal, the actual number of sampling points in each cycle may not be the number of sampling points of the standard power frequency. Therefore, this embodiment first calculates the actual and accurate power frequency through the frequency calculation model, and obtains the amplitude and phase of the fundamental wave through accurate power frequency orthogonal modulation. According to the power frequency, amplitude and phase, the fundamental wave of the metering signal can be fitted and generated, and an accurate fundamental wave signal can be obtained; then, based on the fundamental wave, the metering signal is filtered through a time domain filtering model to obtain accurate harmonics; the method of the present invention can effectively filter out the interference of strong electromagnetic signals while retaining the fundamental wave and harmonics, thereby ensuring the healthy operation of the power grid and the accuracy of electric energy metering.

[0047] Next, combine Figure 5-15 The specific implementation steps of the filtering method for the power metering signal provided in this embodiment are described in detail:

[0048] First, execute step S1 to obtain a metering signal, and obtain the power frequency of the metering signal through a frequency calculation model. Figure 4 As shown in the figure, the obtained metering signal is subjected to IIR low-pass filtering and the power frequency signal is retained to filter the zero point burrs and improve the accuracy of frequency calculation. The frequency calculation model calculates the power frequency of the metering signal based on the filtered power frequency signal.

[0049] In the power system, in order to accurately measure and analyze the frequency and waveform of the power grid, a high-speed sampling rate analog-to-digital converter is usually used to capture the metering signal. For example, using a 6.4kHz analog-to-digital converter for sampling, 6400 data points (i.e., sampling points) of the metering signal can be collected per second. In general, the basic power frequency of the power grid is 50Hz, which means that the metering signal of the power grid completes 50 cycles per second. Since one cycle is 1 / 50 second, i.e., 20 milliseconds, and the sampling rate is 6.4kHz, 128 sampling points can be sampled per power frequency cycle, and the time interval between each two sampling points is 156.25us. Ideally, 128 sampling points can be sampled in one power frequency cycle. However, in the actual sampling process, there is a slight time deviation or synchronization error, so that the first sampling point at the beginning of a power frequency cycle is not a zero crossing point, resulting in the number of points sampled in each power frequency cycle not being exactly 128. This deviation may cause some errors in the analysis of power grid signals, especially in the harmonic analysis or frequency measurement, resulting in inaccurate measurement results.

[0050] like Figure 6 As shown in FIG. 1 , it is a discrete diagram of the sampling points of the metering signal. In the diagram, the zero crossing before the sampling point M is the starting point of a power frequency cycle, and the zero crossing after the sampling point N is the end point of a power frequency cycle. Due to the discreteness of the sampling of the digital-to-analog converter, the first sampling point M and the last sampling point N under the power frequency cycle are not zero crossing points. This error has a great impact on the accuracy and stability of the calculated frequency. Therefore, this embodiment reduces this error through a frequency calculation model.

[0051] Specifically, Figure 7As shown, the power frequency of the metering signal is obtained through the frequency calculation model, including: S11, at the starting point and the end point of the power frequency cycle, a right triangle is constructed with two sampling points before and after the zero crossing point as the hypotenuse; wherein the sampling point is the sampling value of the metering signal, and the sampling points of each power frequency cycle together form the waveform of the metering signal; S12, according to the right triangle, the time interval t1 from the zero crossing point at the starting point to the next sampling point, and the time interval t2 from the last sampling point at the end point to the zero crossing point are calculated; S3, according to the time interval t1 and the time interval t2, the power frequency is calculated. Through the frequency calculation model, the time from the zero crossing point to the next sampling point can be accurately obtained, so as to accurately calculate the actual power frequency in a power frequency cycle.

[0052] by Figure 8 Let's take an example: Figure 8 This is a partial enlarged diagram of the measurement signal sampling point at the zero crossing. In the figure, the horizontal axis represents time, and the vertical axis represents the sampling value of the measurement signal. The right triangle △ADC is constructed with the line connecting the two sampling points A and C before and after the zero crossing point as the hypotenuse. The intersection points of the right triangle △ADC and the horizontal axis time are B and E respectively. Point B is the zero crossing point. BE represents the time interval t1 from the zero crossing point to the next sampling point. In the right triangle △ADC, there are: Right now

[0053] Among them, AE is the sampling value of sampling point A; DE is the absolute value of the sampling value of sampling point C; AD is the sampling value of sampling point A plus the absolute value of the sampling value of sampling point C; CD is the time interval from sampling point C to sampling point A, which is 156.25us. Therefore, the length of line segment BE can be calculated, which is the time interval t1 from zero-crossing point B to the next sampling point A. Similarly, the time interval t2 from the last sampling point to the zero-crossing point at the end of the power frequency cycle is calculated. Further, the calculation formula of the power frequency f can be obtained as follows:

[0054] Wherein, n is the sampling rate of the analog-to-digital converter sampling the metering signal; N is the number of sampling points actually collected in one power frequency cycle.

[0055] In this way, an industrial frequency f will be calculated and output for each industrial frequency cycle, but the value of f will change frequently and quickly. In order to improve the accuracy and stability of the industrial frequency, the industrial frequency f can also be filtered. Specifically, the initial industrial frequency (i.e., the industrial frequency f mentioned above) is obtained through the frequency calculation model, and the initial industrial frequency is Kalman filtered to obtain the final industrial frequency of the metering signal. The industrial frequency f after Kalman filtering can quickly follow the frequency response and ensure the stability of the industrial frequency f.

[0056] Then, execute step S2, perform orthogonal modulation on the metering signal according to the power frequency, and obtain the amplitude and phase of the fundamental wave of the metering signal. In order to obtain the accurate fundamental wave of the metering signal, it is also necessary to perform orthogonal modulation on the metering signal to obtain the amplitude and phase of the fundamental wave. In signal processing, if the inner product of two signals is zero, it can be said that the two signals are orthogonal. Orthogonality prevents the signals from interfering with each other, thereby facilitating demodulation and separation. Orthogonal demodulation is to multiply the received signal with two orthogonal reference signals (generally sine signals and cosine signals) with a phase difference of 90 degrees, and then filter the product result to separate the target frequency component in the original signal.

[0057] Specifically, Fig. 9 As shown, the metering signal is orthogonally modulated according to the power frequency to obtain the amplitude and phase of the fundamental wave of the metering signal, including: S21, generating a cosine wave with the same frequency as the power frequency, and a sine wave with the same frequency as the power frequency; S22, multiplying the metering signal with the cosine wave and the sine wave respectively, and obtaining the I component signal and the Q component signal after modulation; S23, filtering the I component signal and the Q component signal, and superimposing them to obtain the modulation signal of the metering signal; S24, using the amplitude and phase of the modulated signal as the amplitude and phase of the fundamental wave of the metering signal. By filtering the I component signal and the Q component signal, noise and interference can be removed, thereby restoring the original baseband signal of the metering signal, and then obtaining the parameters required for fitting the fundamental wave.

[0058] Next, step S3 is executed to fit and generate the fundamental wave of the metering signal according to the power frequency, amplitude and phase. The fitting output is as follows: Among them, AD[n] represents the discrete sequence of the fundamental wave; n is an integer greater than or equal to 0, representing the sequence number of the discrete sequence; A is the amplitude of the fundamental wave calculated by orthogonal demodulation, is the phase of the fundamental wave, and f is the power frequency. Fig.10 As shown in the figure, waveform 5 is the fundamental wave generated by fitting. Overlap waveform 4 and waveform 5 on the same coordinate axis to obtain the following Fig.11 As shown in the waveform diagram, the blue waveform in the figure represents the waveform 4 of the metering signal, and the orange waveform represents the fundamental wave generated by fitting (i.e., waveform 5). It can be seen from the figure that waveform 5 is the fundamental wave of waveform 4, and the two have the same phase. Through the above method, the fundamental wave of the metering signal with high precision can be obtained.

[0059] Finally, step S4 is executed to filter the metering signal based on the fundamental wave through the time domain filtering model to obtain the harmonic plus harmonic of the metering signal. After obtaining the fundamental wave, it is also necessary to obtain an accurate harmonic signal.

[0060] Specifically, Fig.12As shown, based on the fundamental wave, the metering signal is filtered through a time domain filtering model to obtain the harmonics of the metering signal, including: S41, adding a waveform y1 with an amplitude greater than a% of the fundamental wave and a waveform y2 with an amplitude less than a% of the fundamental wave to the waveform diagram of the metering signal; S42, comparing each sampling point on the metering signal with the waveform y1 and the waveform y2; S43, replacing the sampling points beyond the range of the waveform y1 and the waveform y2 through a recovery strategy to obtain the harmonics of the metering signal.

[0061] The amplitude of harmonics is generally less than 20% of the amplitude of fundamental wave. Therefore, it can be considered that signals with amplitudes too different from fundamental wave are interference waveforms. Based on the fundamental wave, the upper and lower limits of the fundamental wave are set, that is, a waveform y1 with an amplitude greater than a% of the fundamental wave is set as the upper limit, and a waveform with an amplitude less than a% of the fundamental wave is set as the lower limit. Signals exceeding the upper and lower limits are judged as interference signals and are filtered out. Next, the distance is explained with a=30, as shown in Fig.13 and Fig.14 As shown in the figure, the blue waveform represents the waveform 4 of the metering signal, the orange waveform represents the fundamental wave (ie, waveform 5); the yellow waveform represents the waveform y1 with an amplitude greater than 30% of the fundamental wave; and the purple waveform represents the waveform y2 with an amplitude less than 30% of the fundamental wave. Fig.14 For example, the amplitude of the section from point p1 to point p2 in the figure exceeds the range of waveform y1, and the amplitude of the section from point p3 to point p4 exceeds the range of waveform y2. Therefore, the sampling points between point p1 and point p2 and the sampling points between point p3 and point p4 are replaced through the recovery strategy.

[0062] The recovery strategy can be: replace the sampling points that are beyond the range of waveform y1 and waveform y2 with the sampling points at the corresponding positions of the first n cycles or the last n cycles. Fig.14 In the example, the sampling points between point p1 and point p2 can be replaced by the sampling points between point q1 and point q2 at the corresponding positions in the previous power frequency cycle, or by the sampling points at the corresponding positions in the next power frequency cycle. Similarly, the sampling points between point p3 and point p4 can also be replaced.

[0063] The recovery strategy may also be: the sampling points beyond the range of waveform y1 and waveform y2 are replaced by the values ​​at the corresponding positions of the fundamental wave. Fig.14 In the example, the sampling points between point p1 and point p2 can also be replaced by the sampling points at the corresponding positions of the fundamental waves. Different recovery strategies can be flexibly sampled according to actual conditions, and this embodiment does not limit this.

[0064] After time domain filtering, we can finally get Fig.15 Harmonics shown. Fig.15In the figure, the orange waveform is the final harmonic, and the blue part is the filtered interference signal. The signal with strong electromagnetic interference is basically perfectly filtered out, and the harmonics are also retained. Through the above method, it is possible to filter out strong electromagnetic interference in the metering signal while retaining the basic and harmonic waves.

[0065] In order to further improve the accuracy of harmonics, after obtaining the harmonics of the metering signal, the metering signal can be filtered in the frequency domain again through a digital filter to retain the harmonics within 20 times of the metering signal and obtain the final fundamental wave plus harmonics. Digital filters include: FIR filters, IIR filters, and wavelet transform filters.

[0066] The embodiment is only a specific example and does not represent only one implementation mode of the present invention.

[0067] Embodiment 2:

[0068] The present invention also provides an embodiment of a filtering device for electric power metering signals, comprising one or more processors and a memory; wherein the memory is used to store one or more computer programs, and the one or more processors are used to execute the one or more computer programs stored in the memory, so that the processor performs the features / steps of the above-mentioned electric power metering signal filtering method embodiment.

[0069] The above description is only the preferred embodiment of the present invention. It is known to those skilled in the art that various changes or equivalent substitutions may be made to these features and embodiments without departing from the spirit and scope of the present invention. In addition, under the teachings of the present invention, these features and embodiments may be modified to adapt to specific circumstances and materials without departing from the spirit and scope of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed herein, and all embodiments falling within the scope of the claims of this application belong to the protection scope of the present invention.

Claims

1. A method for filtering an electric power metering signal, characterized in that: The following steps are involved: Acquire a metering signal, and acquire the power frequency of the metering signal through a frequency calculation model; Performing orthogonal modulation on the metering signal according to the power frequency to obtain the amplitude and phase of the fundamental wave of the metering signal; According to the power frequency, amplitude and phase, the fundamental wave of the metering signal is generated by fitting; Based on the fundamental wave, the metering signal is filtered through a time domain filtering model to obtain the fundamental wave plus harmonics of the metering signal.

2. A method for filtering electric power metering signals according to claim 1, characterized in that: The obtaining the power frequency of the metering signal through a frequency calculation model includes: At the starting point and the end point of the power frequency cycle, a right triangle is constructed with two sampling points before and after the zero crossing point as the hypotenuse; wherein the sampling points are the sampling values ​​of the metering signal, and the sampling points of each power frequency cycle together form the waveform of the metering signal; According to the right triangle, calculate the time interval t1 from the zero-crossing point at the starting point to the next sampling point, and the time interval t2 from the last sampling point at the ending point to the zero-crossing point; The power frequency is calculated according to the time interval t1 and the time interval t2.

3. The method for filtering an electric power metering signal according to claim 2, characterized in that: The calculation formula for obtaining the power frequency f is: Wherein, n is the sampling rate of sampling the metering signal; N is the number of sampling points actually collected in one power frequency cycle.

4. The method for filtering an electric power metering signal according to claim 1, characterized in that: The method of filtering the metering signal based on the fundamental wave through a time domain filtering model to obtain the harmonics of the metering signal includes: Adding a waveform y1 with an amplitude greater than a% of the fundamental wave and a waveform y2 with an amplitude less than a% of the fundamental wave to the waveform diagram of the metering signal; Comparing each sampling point on the metering signal with the waveform y1 and the waveform y2; The sampling points beyond the range of the waveform y1 and the waveform y2 are replaced by a restoration strategy to obtain harmonics of the metering signal.

5. The method for filtering an electric power metering signal according to claim 4, characterized in that: The sampling points exceeding the range of the waveform y1 and the waveform y2 are replaced by a recovery strategy, including: the sampling points exceeding the range of the waveform y1 and the waveform y2 are replaced by sampling points at corresponding positions of the first n cycles or the last n cycles.

6. The method for filtering an electric power metering signal according to claim 4, characterized in that: The replacing the sampling points beyond the range of the waveform y1 and the waveform y2 by a recovery strategy includes: replacing the sampling points beyond the range of the waveform y1 and the waveform y2 by the values ​​of the corresponding positions of the fundamental wave.

7. The method for filtering an electric power metering signal according to claim 1, characterized in that: The obtaining of the fundamental wave plus harmonics of the metering signal comprises: after obtaining the fundamental wave plus harmonics of the metering signal, filtering the metering signal through a digital filter to obtain the final fundamental wave plus harmonics.

8. The method for filtering an electric power metering signal according to claim 1, characterized in that: The orthogonal modulation of the metering signal according to the power frequency to obtain the amplitude and phase of the fundamental wave of the metering signal includes: generating a cosine wave having the same frequency as the power frequency and a sine wave having the same frequency as the power frequency; Multiplying the metering signal with the cosine wave and the sine wave respectively, and obtaining an I component signal and a Q component signal after modulation; Filtering the I component signal and the Q component signal, and superimposing them to obtain a modulation signal of the metering signal; The amplitude and phase of the modulated signal are used as the amplitude and phase of the fundamental wave of the metering signal.

9. The method for filtering an electric power metering signal according to claim 1, characterized in that: The method of obtaining the metering signal and obtaining the power frequency of the metering signal through a frequency calculation model includes: obtaining an initial power frequency through a frequency calculation model, and performing Kalman filtering on the initial power frequency to obtain the power frequency of the metering signal.

10. A filtering device for electric power metering signals, characterized in that: include: one or more processors; A memory is used to store one or more computer programs, and one or more of the processors are used to execute the one or more computer programs stored in the memory, so that one or more of the processors execute the filtering method for an electric power metering signal according to any one of claims 1 to 9.

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