Method and device for correcting error of electric energy meter in electromagnetic environment

Abstract

The invention provides a method and device for correcting errors of an electric energy meter in an electromagnetic environment, and belongs to the field of electric energy meters. The method comprises the following steps: acquiring a signal source frequency of an electric energy meter in an electromagnetic environment, a signal source amplitude of the electric energy meter and an electromagnetic radio frequency signal parameter, and judging whether the signal source frequency, the signal source amplitude and the electromagnetic radio frequency signal parameter exceed a preset error range or not according to the signal source frequency, the signal source amplitude and the electromagnetic radio frequency signal parameter; when the judgment result is that the preset error range is exceeded, determining an electromagnetic radio frequency signal parameter correction value according to the signal source frequency and the signal source amplitude; and adjusting an error correction module of the electric energy meter by using the electromagnetic radio frequency signal parameter correction value so as to realize the error correction of the electric energy meter. The influence of the randomness of the electromagnetic signal on the metering error of the intelligent electric energy meter is considered, the metering error of the electric energy meter is corrected, and the metering accuracy is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of electric energy meters, and in particular to a method and a device for correcting errors of electric energy meters in an electromagnetic environment. Background Art

[0002] With the rapid development of smart grids and user information collection systems, a modern power grid that integrates advanced sensor measurement technology, communication technology and control technology has taken shape. However, the sharp increase in the number of smart energy meters has also brought challenges to the reliability assessment of energy meters. At present, many achievements have been made in the study of the impact of environmental factors such as temperature and humidity on energy meter measurement. However, since smart energy meters are all electronic energy meters, the large number of electronic components they contain are extremely susceptible to interference from the complex electromagnetic fields around them.

[0003] At present, scholars at home and abroad have conducted extensive research on the impact of smart energy meters in electromagnetic environments. They found that in complex electromagnetic environments, due to the wide variety of electromagnetic interference signals and different modulation methods, the performance of surrounding electronic equipment systems has been reduced. Therefore, the accuracy of error correction for energy meters in electromagnetic environments needs to be improved urgently. Summary of the invention

[0004] The embodiments of the present invention provide a method and a device for error correction of an electric energy meter in an electromagnetic environment, so as to solve the problem that the accuracy of error correction of an electric energy meter in an electromagnetic environment needs to be improved.

[0005] In a first aspect, an embodiment of the present invention provides a method for error correction of an electric energy meter in an electromagnetic environment, comprising:

[0006] Acquire the signal source frequency, signal source amplitude and electromagnetic radio frequency signal parameters of the electric energy meter in the electromagnetic environment, and determine whether the signal source frequency, signal source amplitude and electromagnetic radio frequency signal parameters exceed a preset error range according to the signal source frequency, signal source amplitude and electromagnetic radio frequency signal parameters;

[0007] When the judgment result is beyond the preset error range, determining the electromagnetic radio frequency signal parameter correction value according to the signal source frequency and the signal source amplitude;

[0008] The error correction module of the electric energy meter is adjusted by utilizing the electromagnetic radio frequency signal parameter correction value to realize the error correction of the electric energy meter.

[0009] In a possible implementation, judging whether the signal source frequency, the signal source amplitude, and the electromagnetic radio frequency signal parameter exceed a preset error range includes:

[0010] Determining a frequency threshold and an amplitude threshold according to the electromagnetic radio frequency signal parameters;

[0011] When the signal source frequency exceeds the frequency threshold, or the signal source amplitude exceeds the amplitude threshold, it is determined that the preset error range is exceeded.

[0012] In a possible implementation manner, before obtaining the signal source frequency of the electric energy meter in the electromagnetic environment, the signal source amplitude of the electric energy meter, and the electromagnetic radio frequency signal parameters, the method further includes:

[0013] Under different electromagnetic radio frequency signal parameter conditions, the signal source frequency and signal source amplitude are changed respectively, and the corresponding electric energy meter measurement error values ​​are collected;

[0014] Perform cluster analysis on the collected data to determine the error variation rules under different electromagnetic RF signal parameter conditions and different combinations of signal source frequencies and signal source amplitudes;

[0015] The error variation rule is stored according to the set data structure.

[0016] In a possible implementation manner, determining a frequency threshold and an amplitude threshold according to the electromagnetic radio frequency signal parameter includes:

[0017] When the error variation law is stored according to a relationship comparison table, a table lookup is performed based on the electromagnetic radio frequency signal parameters and the error variation law to determine the frequency threshold and the amplitude threshold.

[0018] In a possible implementation manner, determining a frequency threshold and an amplitude threshold according to the electromagnetic radio frequency signal parameter includes:

[0019] Inputting the electromagnetic radio frequency signal parameters into a frequency threshold determination model and an amplitude threshold determination model respectively, and outputting corresponding frequency thresholds and amplitude thresholds;

[0020] Wherein, the frequency threshold determination model and the amplitude threshold determination model are obtained through training based on the error variation law.

[0021] In a possible implementation, the electromagnetic radio frequency signal parameters include:

[0022] The electromagnetic radio frequency signal amplitude, the electromagnetic radio frequency signal frequency and the electromagnetic radio frequency signal phase.

[0023] In a possible implementation, a spectrum analyzer is used to monitor electromagnetic radio frequency signal parameters in an electromagnetic environment in real time.

[0024] In a possible implementation, determining the electromagnetic radio frequency signal parameter correction value according to the signal source frequency and the signal source amplitude includes:

[0025] When the signal source frequency is constant, if the signal source power is within the first setting range, the greater the signal source power, the greater the electromagnetic radio frequency signal parameter correction value; if the signal source power exceeds the first setting range, the greater the signal source power, the smaller the electromagnetic radio frequency signal parameter correction value;

[0026] When the signal source power is constant, if the signal source frequency is within the second setting range, the greater the signal source frequency, the greater the electromagnetic RF signal parameter correction value; if the signal source power exceeds the second setting range, the greater the signal source frequency, the smaller the electromagnetic RF signal parameter correction value.

[0027] In a possible implementation, a filter is connected to the signal input end of the electric energy meter;

[0028] The method of adjusting the error correction module of the electric energy meter by using the electromagnetic radio frequency signal parameter correction value includes:

[0029] A filter adjustment parameter is determined according to the electromagnetic radio frequency signal parameter correction value, and the filter is adjusted according to the filter adjustment parameter.

[0030] In a second aspect, an embodiment of the present invention provides an error correction device for an electric energy meter in an electromagnetic environment, comprising:

[0031] An acquisition module, used to acquire the signal source frequency, signal source amplitude and electromagnetic radio frequency signal parameters of the electric energy meter in an electromagnetic environment;

[0032] A determination module, used to determine whether the signal source frequency, the signal source amplitude and the electromagnetic radio frequency signal parameter exceed a preset error range according to the signal source frequency, the signal source amplitude and the electromagnetic radio frequency signal parameter, and when the judgment result is that the signal source frequency, the signal source amplitude and the electromagnetic radio frequency signal parameter exceed the preset error range, determine a correction value of the electromagnetic radio frequency signal parameter according to the signal source frequency and the signal source amplitude;

[0033] The adjustment module is used to adjust the error correction module of the electric energy meter by using the electromagnetic radio frequency signal parameter correction value to realize the error correction of the electric energy meter.

[0034] The embodiment of the present invention provides a method and device for error correction of an electric energy meter in an electromagnetic environment, by obtaining the signal source frequency, signal source amplitude and electromagnetic radio frequency signal parameters of the electric energy meter in the electromagnetic environment, and then judging whether these parameters exceed the preset error range. In this way, it is possible to instantly identify whether the electric energy meter is subject to significant electromagnetic interference, and decide whether correction measures need to be taken. When the detection result shows that the parameter exceeds the preset error range, the correction value of the electromagnetic radio frequency signal parameter is further determined according to the signal source frequency and the signal source amplitude. Using these correction values, the error correction module of the electric energy meter is adjusted to accurately offset the influence of electromagnetic interference on the metering accuracy of the electric energy meter, realize the correction of the electric energy meter error, and ensure the accuracy of the metering result. The present invention takes into account the influence of the randomness of electromagnetic signals on the metering error of the intelligent electric energy meter, and copes with the potential influence of the complex and changeable electromagnetic environment on the metering error of the intelligent electric energy meter through dynamic monitoring and instant correction. By correcting the metering error of the electric energy meter, the accuracy of electric energy metering is improved, thereby reducing the economic losses caused by the metering error. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0036] Figure 1 It is a schematic diagram of the interference path of radio frequency signals on the measurement of electric energy meters;

[0037] Figure 2 It is a flow chart of the implementation of the method and device for error correction of electric energy meters in electromagnetic environment provided by the embodiment of the present invention;

[0038] Figure 3 is a general structure diagram of an m-sequence provided in an embodiment of the present invention;

[0039] Figure 4 It is the schematic diagram of a 4-stage feedback shift register;

[0040] Figure 5 It is a schematic diagram of the generation of a 4-level m-sequence;

[0041] Figure 6 It is the m-sequence test current signal model;

[0042] Figure 7 This is a schematic diagram of the effect of m-sequence modulation on the measurement error of the electric energy meter;

[0043] Figure 8 It is a schematic diagram of the effect of m-sequence series on the measurement error of electric energy meter;

[0044] Fig. 9 It is a schematic diagram of the influence of input current amplitude on measurement error;

[0045] Fig.10 This is a picture of the experimental site;

[0046] Fig.11 It is a three sigma criterion chart;

[0047] Fig.12 This is the error analysis diagram of 3 types of electric energy meters;

[0048] Fig.13 It is a structural schematic diagram of an error correction device for an electric energy meter in an electromagnetic environment provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0049] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present invention. However, it should be clear to those skilled in the art that the present invention may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present invention.

[0050] Before explaining this application solution, the electromagnetic interference coupling mechanism and its impact on the electric energy meter are introduced:

[0051] The impact of RF signals on smart energy meters is mainly reflected in two aspects: on the one hand, RF signals can penetrate the outer shell of the energy meter and directly enter its internal structure; on the other hand, RF signals can also enter the interior of the energy meter through various wiring ports, thereby generating interference effects. The interference pathways of RF signals on energy meter measurement are as follows: Figure 1 shown.

[0052] The electric energy meter obtains voltage and current signals through voltage sampling and current sampling, and converts the collected analog signals into digital signals for processing. Since the external analog interface of the high-precision metering chip inside the electric energy meter is directly connected to the external PCB circuit board wiring, when these analog signal lines and reference voltage and current signal lines are coupled with high-frequency interference signals, the low-pass filter in the subsequent digital circuit may not be able to effectively filter and process. If the intensity of the interference signal exceeds the noise threshold of the internal circuit of the electric energy meter, it may have a significant impact on the metering accuracy of the electric energy meter.

[0053] Therefore, the embodiments of the present application are intended to solve the problem of correcting the metering error of the electric energy meter when the metering accuracy of the electric energy meter exceeds a specific error range.

[0054] In order to make the purpose, technical solutions and advantages of the present invention more clear, specific embodiments will be described below in conjunction with the accompanying drawings.

[0055] Figure 2 The implementation flow chart of the method and device for error correction of electric energy meters in electromagnetic environment provided by the embodiment of the present invention is described in detail as follows:

[0056] S201, obtaining a signal source frequency, a signal source amplitude and electromagnetic radio frequency signal parameters of an electric energy meter in an electromagnetic environment, and determining whether the signal source frequency, the signal source amplitude and the electromagnetic radio frequency signal parameters exceed a preset error range.

[0057] The execution subject of the method for error correction of an electric energy meter under an electromagnetic environment provided in the embodiment of the present application is a controller or a control terminal connected to the electric energy meter. These execution subjects can be built into the electric energy meter or can be independent devices connected to the outside of the electric energy meter. In this embodiment, the controller is used as the execution subject for description.

[0058] In the actual implementation process, the signal source frequency and the signal source amplitude of the electric energy meter are obtained by connecting the signal output port of the electric energy meter to a dedicated test device (such as a spectrum analyzer or a digital oscilloscope).

[0059] Electromagnetic radio frequency signal parameters include the frequency, intensity and possible modulation mode of electromagnetic interference, etc. These parameters are crucial for evaluating the impact of electromagnetic environment on electric energy meters.

[0060] In one possible implementation, a spectrum analyzer is used to monitor the electromagnetic radio frequency signal parameters in the electromagnetic environment in real time. In other possible implementations, an electromagnetic field strength meter is used to perform real-time measurements at the location of the electric energy meter to obtain the electromagnetic radio frequency signal parameters.

[0061] After obtaining the signal source frequency, signal source amplitude and electromagnetic radio frequency signal parameters, these data are compared with the preset standard values ​​to determine whether there is a measurement error exceeding the maximum allowable interference level.

[0062] If the analysis results of the signal source frequency, signal source amplitude and electromagnetic RF signal parameters are within the preset error range, it can be considered that the performance of the electric energy meter is normal and is not significantly affected by the electromagnetic environment. On the contrary, if the judgment result exceeds the preset error range, it indicates that the electric energy meter is significantly affected by the electromagnetic environment, and the measurement error needs to be corrected accordingly.

[0063] S202: When the judgment result is that the error exceeds the preset error range, a correction value of the electromagnetic radio frequency signal parameter is determined according to the signal source frequency and the signal source amplitude.

[0064] In the specific implementation process, it was found through simulation that when the signal source frequency is constant, the electric energy metering error increases with the increase of the signal source power. When it increases to a certain extent, the error variation range decreases. When the signal source power is constant, the electric energy metering error will slowly increase with the increase of the signal source frequency. When it reaches a certain extent, it will show a decreasing trend, and under different transmission powers, its turning frequency is similar. Therefore, to adapt to different working conditions, the influence of electromagnetic signals on the metering error of the electric energy meter is different. It is necessary to determine the electromagnetic radio frequency signal parameter correction value according to different working conditions to improve the metering accuracy of the electric energy meter.

[0065] S203, using the electromagnetic radio frequency signal parameter correction value, adjusting the error correction module of the electric energy meter to achieve error correction of the electric energy meter.

[0066] The electromagnetic radio frequency signal parameter correction value is applied to the error correction module of the electric energy meter through a software program or hardware adjustment, thereby realizing the correction of the electric energy meter error.

[0067] In a possible implementation, a filter is connected to a signal input terminal of the electric energy meter;

[0068] The error correction module of the electric energy meter is adjusted by using the electromagnetic radio frequency signal parameter correction value, including:

[0069] The filter adjustment parameters are determined according to the electromagnetic radio frequency signal parameter correction values, and the filter is adjusted according to the filter adjustment parameters.

[0070] A filter is connected to the signal input end of the electric energy meter to filter out the interference of the electromagnetic radio frequency signal on the electric energy meter signal through the filter.

[0071] In the specific implementation process, the electromagnetic radio frequency signal parameter correction value is obtained by accurately calculating the signal source frequency and the signal source amplitude, which reflects the specific impact of the electromagnetic radio frequency signal on the error of the electric energy meter. According to the electromagnetic radio frequency signal parameter correction value, the parameters that need to be adjusted by the filter are calculated. Optionally, the filter cutoff frequency, bandwidth, phase response, etc. are included. According to the determined filter adjustment parameters, the filter is adjusted by adjusting the internal circuit elements of the filter (such as inductance, capacitance, resistance, etc.) to filter out the interference of the electromagnetic radio frequency signal, thereby reducing the error of the electric energy meter.

[0072] In other possible implementations, there is no need to connect a filter, and the capacitors at the adjacent ports inside the energy meter are directly used to change the current direction and voltage phase difference, thereby achieving the purpose of adjusting the error. This implementation requires the components of the energy meter to be improved. For those energy meters that have been installed and do not have adjustable capacitors, new energy meters must be replaced, which limits their application scope.

[0073] In this embodiment, the signal source frequency, signal source amplitude and electromagnetic radio frequency signal parameters of the electric energy meter in the electromagnetic environment are obtained, and then it is determined whether these parameters exceed the preset error range. In this way, it is possible to instantly identify whether the electric energy meter is subject to significant electromagnetic interference and decide whether corrective measures need to be taken. When the detection result shows that the parameter exceeds the preset error range, the correction value of the electromagnetic radio frequency signal parameter is further determined according to the signal source frequency and the signal source amplitude. Using these correction values, the error correction module of the electric energy meter is adjusted to accurately offset the influence of electromagnetic interference on the metering accuracy of the electric energy meter, realize the correction of the electric energy meter error, and ensure the accuracy of the metering result. The present invention takes into account the influence of the randomness of electromagnetic signals on the metering error of the smart electric energy meter, and through dynamic monitoring and instant correction, it copes with the potential influence of the complex and changeable electromagnetic environment on the metering error of the smart electric energy meter. By correcting the metering error of the electric energy meter, the accuracy of electric energy metering is improved, thereby reducing the economic losses caused by metering errors.

[0074] In a possible implementation, judging whether the preset error range is exceeded according to the signal source frequency, the signal source amplitude and the electromagnetic radio frequency signal parameters includes:

[0075] determining a frequency threshold and an amplitude threshold according to electromagnetic radio frequency signal parameters;

[0076] When the frequency of the signal source exceeds the frequency threshold, or the amplitude of the signal source exceeds the amplitude threshold, it is determined that the preset error range is exceeded.

[0077] Among them, the frequency threshold and amplitude threshold represent the critical value of the electromagnetic radio frequency signal affecting the metering accuracy of the electric energy meter. When either the signal source frequency or the signal source amplitude corresponds to the threshold, it is judged that the metering error exceeds the maximum allowable interference level, and the metering error correction is performed to improve the metering accuracy.

[0078] This embodiment sets a frequency threshold and an amplitude threshold, and monitors and determines in real time whether the metering error of the electric energy meter exceeds a preset range, and promptly starts an error correction program, thereby effectively improving the metering accuracy of the electric energy meter.

[0079] In a possible implementation manner, before obtaining the signal source frequency of the electric energy meter in the electromagnetic environment, the signal source amplitude of the electric energy meter, and the electromagnetic radio frequency signal parameters, the method further includes:

[0080] Under different electromagnetic radio frequency signal parameter conditions, the signal source frequency and signal source amplitude are changed respectively, and the corresponding electric energy meter measurement error values ​​are collected;

[0081] Perform cluster analysis on the collected data to determine the error variation rules under different electromagnetic RF signal parameter conditions and different combinations of signal source frequencies and signal source amplitudes;

[0082] The error variation rule is stored according to the set data structure.

[0083] Among them, cluster analysis is performed on the collected data to identify the error variation rules under different electromagnetic RF signal parameter conditions and different signal source frequency and signal source amplitude combinations. Cluster analysis can use algorithms such as K-means and hierarchical clustering to divide the data into different groups according to the similarity of the error values.

[0084] Through cluster analysis, we can find out which combinations of electromagnetic RF signal parameters, signal source frequency and signal source amplitude will lead to large errors, as well as the trend of errors changing with these parameters.

[0085] In a possible implementation, the electromagnetic radio frequency signal parameters include:

[0086] The electromagnetic radio frequency signal amplitude, the electromagnetic radio frequency signal frequency and the electromagnetic radio frequency signal phase.

[0087] Among them, the amplitude of the electromagnetic radio frequency signal reflects the strength of the signal; the frequency of the electromagnetic radio frequency signal determines the wavelength and periodicity of the signal; and the phase of the electromagnetic radio frequency signal describes the starting point of the signal waveform.

[0088] In addition, the error variation law obtained by cluster analysis is stored according to a set data structure. Optionally, it is a database table, which at least contains fields such as electromagnetic RF signal parameters, signal source frequency, signal source amplitude, and corresponding error variation law. The stored data can be used for subsequent error correction and prediction, helping to quickly locate and solve potential error problems and improve the accuracy and reliability of the entire system.

[0089] In other possible implementations, further training is performed based on the clustering results to determine the corresponding relationship model, and the resulting training model is stored to reduce data storage pressure.

[0090] This embodiment uses the steps of pre-collecting data, clustering analysis, and data storage to more accurately understand the error variation law of the electric energy meter and optimize the error correction process.

[0091] Based on the above-mentioned embodiments, the error variation law is stored in a different manner, and the frequency threshold and the amplitude threshold are determined in a different manner according to the electromagnetic radio frequency signal parameters.

[0092] In a possible implementation, determining a frequency threshold and an amplitude threshold according to electromagnetic radio frequency signal parameters includes:

[0093] When the error variation law is stored according to the relationship comparison table, the frequency threshold and the amplitude threshold are determined by looking up the table according to the electromagnetic radio frequency signal parameters and the error variation law.

[0094] Among them, when the error change law is stored according to the relationship comparison table, when it is necessary to determine the frequency threshold and amplitude threshold under specific electromagnetic radio frequency signal parameters, the corresponding row or column is found in the relationship comparison table according to the current electromagnetic radio frequency signal parameters (such as frequency range, amplitude range, etc.).

[0095] According to the search result, the upper or lower limit of the frequency and amplitude that will not cause significant errors under the electromagnetic radio frequency signal parameter conditions, that is, the frequency threshold and the amplitude threshold, are determined.

[0096] In this embodiment, the frequency threshold and the amplitude threshold can be quickly determined by table lookup without complicated calculation or reasoning.

[0097] In a possible implementation, determining a frequency threshold and an amplitude threshold according to electromagnetic radio frequency signal parameters includes:

[0098] Inputting electromagnetic radio frequency signal parameters into a frequency threshold determination model and an amplitude threshold determination model respectively, and outputting corresponding frequency thresholds and amplitude thresholds;

[0099] Among them, the frequency threshold determination model and the amplitude threshold determination model are trained based on the error variation law.

[0100] During the training process, the electromagnetic radio frequency signal parameters are used as input features, and the upper or lower limits of the frequency and amplitude that will not cause significant errors (ie, the frequency threshold and the amplitude threshold) are used as output targets.

[0101] When it is necessary to determine the frequency threshold and amplitude threshold under specific electromagnetic radio frequency signal parameters, the current electromagnetic radio frequency signal parameters are input into the trained frequency threshold determination model and amplitude threshold determination model. The model calculates according to the input parameters and outputs the corresponding frequency threshold and amplitude threshold.

[0102] In this embodiment, the machine learning model can adaptively determine the frequency threshold and amplitude threshold according to the input electromagnetic radio frequency signal parameters without manual intervention. By training a large amount of data, the model can learn the general law of error change and make reasonable predictions for electromagnetic radio frequency signal parameters that have not been seen.

[0103] In a possible implementation, determining the electromagnetic radio frequency signal parameter correction value according to the signal source frequency and the signal source amplitude includes:

[0104] When the signal source frequency is constant, if the signal source power is within the first setting range, the greater the signal source power, the greater the electromagnetic radio frequency signal parameter correction value; if the signal source power exceeds the first setting range, the greater the signal source power, the smaller the electromagnetic radio frequency signal parameter correction value;

[0105] When the signal source power is constant, if the signal source frequency is within the second setting range, the greater the signal source frequency, the greater the electromagnetic RF signal parameter correction value; if the signal source power exceeds the second setting range, the greater the signal source frequency, the smaller the electromagnetic RF signal parameter correction value.

[0106] Based on the relationship between the signal source frequency, signal source power and metering error of the electric energy meter, when the signal source frequency is constant, the electric energy metering error increases with the increase of the signal source power. When it increases to a certain extent, the error variation range decreases. When the signal source power is constant, the electric energy metering error will slowly increase with the increase of the signal source frequency. When it reaches a certain extent, it will show a decreasing trend. In order to adapt to various working conditions, we need to determine the correction value of the electromagnetic RF signal parameters to improve the accuracy of the error correction, thereby enhancing the metering accuracy of the electric energy meter.

[0107] In the aforementioned embodiment, the relationship between the signal source frequency, signal source power and metering error of the electric energy meter is determined through the following simulation process.

[0108] First, construct a dynamic test current signal and a dynamic test voltage signal. Specifically include:

[0109] Acquire a sinusoidal steady-state current signal and a sinusoidal steady-state voltage signal, and generate an m-sequence based on a shift register with linear feedback;

[0110] The steady-state current signal and the sinusoidal steady-state voltage signal are modulated respectively according to the m-sequence to obtain a dynamic test current signal and a dynamic test voltage signal.

[0111] The m-sequence generation principle is as follows:

[0112] The m sequence is also called the linear feedback shift register sequence. Its general structure is shown in the figure below. Figure 3 As shown, it is the longest period sequence generated by a shift register with linear feedback.

[0113] Assume that the initial state of the m sequence is (a0, a1, ..., a n-2 , a n-1 ), after one shift linear feedback, the input of the first stage of the shift register is:

[0114]

[0115] Among them, c i is the feedback coefficient. After k shifts, the input of the first stage is:

[0116]

[0117] Among them, l = n + k - 1, (n, k = 1, 2, 3 ...), it can be seen that the input of the first stage of the shift register is determined by the feedback logic and the original state of the shift register. Take a 4-stage linear feedback shift register as an example, Figure 4 As shown, its period is p = 2 4 -1=15, its characteristic polynomial is a 4th-order primitive polynomial, which can divide (x 15 +1). First, (x 15 +1) Factorize the factors so that each factor is a reduced polynomial (a polynomial that cannot be decomposed into the product of two non-constant polynomials within the domain of definition), and then find f(x), as follows:

[0118] x 15 +1=(x+1)(x 15 +x+1)(x 4 +x+1)×(x 4 +x 3 +1)(x 4 +x 3 +x+1)

[0119] Among them, there are three 4th-order polynomials, but only two of them can generate m-sequences. 4 +x+1 constitutes an m sequence such as Figure 5 shown.

[0120] Its initial state is (a3, a2, a1, a0) = (1, 0, 0, 0). When shifted once, a3 and a0 modulo 2 are added to generate a new input and placed in register a. 3， Register a2 is updated to the original value of a3, a1 is updated to the original value of a2, and a0 is updated to the original value of a1. Therefore, the state becomes (1, 1, 0, 0). After shifting 15 times in this way, it returns to the initial state. From the above shifting method, it can be seen that if the initial state is (0, 0, 0, 0), it is still all 0 after shifting. Therefore, this feedback shift register should avoid the all-zero state.

[0121] Based on the above analysis of the principle of m-sequence, it is not difficult to see that within one cycle, it can effectively reflect the random changes of dynamic signals and has a strong autocorrelation, but after exceeding the length of the cycle, it will enter the next cycle. Therefore, the pseudo-randomness of the m-sequence can be used to simulate the RF electromagnetic signal model in a complex electromagnetic environment.

[0122] Secondly, construct electromagnetic radio frequency signals for interference testing. Specifically include:

[0123] Acquire an input voltage signal of an electric energy meter, an input current signal of an electric energy meter, a radio frequency current signal, and a radio frequency voltage signal;

[0124] Modulating the radio frequency current signal according to the m-sequence to obtain an interference test current signal;

[0125] The interference test current signal and the input current signal of the electric energy meter are added to obtain a metering error current test signal, and the radio frequency voltage signal and the input voltage signal of the electric energy meter are added to obtain a metering error voltage test signal;

[0126] Multiply the metering error current test signal by the gain factor k i , multiply the measurement error voltage test signal by the gain factor k u ;

[0127] Discretize the calculation results and multiply them to get the instantaneous power signal p containing radio frequency interference i (n);

[0128] The instantaneous power signal p containing radio frequency interference i (n) is decomposed into the active power of the input signal p0(n) and the active power of the RF signal p(n):

[0129] The active power is accumulated respectively to obtain the corresponding input signal energy E0 and the energy containing the radio frequency signal E;

[0130] The measurement error containing radio frequency electromagnetic signals is determined as:

[0131]

[0132] Based on the above m-sequence modulation principle, the steady-state signal can be converted into a dynamic signal, and the m-sequence test current signal model can be constructed as follows: Figure 6 shown.

[0133] The sinusoidal steady-state current signal i0(t) is modulated by using the m-sequence binary waveform to establish a current signal i1(t) with random dynamic characteristics. The sinusoidal steady-state voltage signal and the sinusoidal steady-state current signal are assumed to be:

[0134]

[0135] Where, I is the amplitude of the sinusoidal steady-state current; is the phase of the sinusoidal steady-state current; U is the amplitude of the sinusoidal steady-state voltage; is the phase of the sinusoidal steady-state voltage; ω is the angular frequency.

[0136] The binary waveform function m(t) is expressed as the multiplication of a matrix window function and a numerical m sequence:

[0137]

[0138] Where N is 2 l-1, l is the series of m sequence; g(t) function is the window function, T is the period of sinusoidal steady-state current, k=1, 2, 3..., N.

[0139] By multiplying the m(t) function with the sinusoidal steady-state current i0(t) for amplitude modulation, we can obtain:

[0140]

[0141] Where I is the modulated current i d (t), |m(t)|≤1.

[0142] According to the aforementioned m-sequence generation principle, the m(k) sequence can be obtained as:

[0143]

[0144] Substituting the above into the above we get:

[0145]

[0146] In summary, the parameter model of the test current signal modulated by the m sequence can be given by the above formula, where the model parameters of i1(t) are given by C i (i=1, 2, 3..., n), I, U, The value of ω determines the

[0147] Since radio frequency interference is a kind of approximately uniformly distributed noise, this noise is independent of the input current and voltage of the electric energy meter and can be superimposed on the input current and voltage, thereby affecting the metering accuracy of the electric energy meter [18-19]. Based on this, this application will establish a mathematical model of the influence of radio frequency electromagnetic signals on the metering error of smart electric energy meters based on m-sequence modulation.

[0148] The input sinusoidal signals u0(t) and i0(t) are established as follows:

[0149]

[0150] Among them, U0 and I0 represent the input voltage signal and input current signal amplitude of the energy meter respectively. are the phase difference between the input voltage signal of the electric energy meter and the input current signal of the electric energy meter, and ω0 is the angular frequency of the input signal.

[0151] The mathematical model of the unmodulated RF current signal and RF voltage signal is established as follows:

[0152] e i (t) = I e cos(ω1t+ψ i )-I e sin(ω1t+ψi )+σ i

[0153] e u (t) = U e cos(ω1t+ψ u )-U e sin(ω1t+ψ u )+σ u

[0154] Among them, U e ,I e are the amplitudes of the RF voltage signal and the RF current signal respectively; ω1=2πf1 is the angular frequency of the RF signal; ψ i and ψ u are the phases of the RF current signal and the RF voltage signal respectively; σ i and σ u are the noise errors of the RF current signal and the RF voltage signal respectively; ψ i , u , σ i and σ u They all obey a Gaussian distribution with a mean of 0 and a variance of 1; f1=1.84GHz is the angular frequency of the RF signal.

[0155] In order to simulate the randomness of RF signals in complex electromagnetic environments, the RF current signal can be modulated by the m sequence to obtain e id (t):

[0156]

[0157] Where N is the period length of the m sequence, l is the number of levels of the m sequence, and N = 2 l -1.

[0158] Adding the input current to the modulated RF current gives i e (t):

[0159] i e (t) = i0(t) + e id (t)

[0160] Adding the input voltage to the RF voltage gives u e (t):

[0161] u e (t)=u0(t)+e u (t)

[0162] will i e (t) multiplied by the gain factor k i , and then perform analog-to-digital conversion, discretization can get i e (n), similarly, ue (t) multiplied by the gain factor k u Then discretize to get u e (n):

[0163]

[0164] Among them, t n is the symbol width of the m sequence, t s is the time interval of the sampling points, β is the zero-crossing radian of the first sampling point, l is the series number of m sequence.

[0165] Discrete signal i e (n),u e (n) can be multiplied to obtain the instantaneous power signal p containing radio frequency interference i (n):

[0166] p i (n) = u e (n)i e (n)

[0167] The instantaneous power signal can effectively filter out high-order harmonics after passing through a low-pass filter. The effective sampling response of the active power low-pass filter is {r(n)=1 / L:0≤n≤L-1}. The discretized instantaneous active power signal p i (n) can be decomposed into the active power of the input signal p0(n) and the active power of the signal containing RF electromagnetic interference p(n):

[0168]

[0169] By accumulating and summing the active power, the accumulated electric energy can be obtained. Therefore, the electric energy of the input signal is E 0， The electrical energy containing the radio frequency electromagnetic signal is E:

[0170]

[0171] The above electric energy calculation formula calculates the measurement error of radio frequency electromagnetic signals as follows:

[0172]

[0173] In order to better obtain the results of the influence of electromagnetic signals on the metering error of electric energy meters, firstly, based on the mathematical model of the influence of radio frequency electromagnetic signals on the metering error of smart electric energy meters established in the above embodiments, a program was written using MATLAB to analyze the error size. Secondly, by building an electric energy meter dynamic error test system, dynamic error experiments were conducted on three different brands of electric energy meters, and the experimental data were analyzed to determine the influence of the metering error.

[0174] Based on the mathematical model established in the above-mentioned embodiment, the influence of radio frequency electromagnetic signals on the measurement of electric energy meters is studied in the following three aspects.

[0175] (1) When phase noise and amplitude noise exist at the same time, the influence of the RF signal obtained by m-sequence modulation on the metering error of the electric energy meter is compared with the influence of the RF signal obtained by no m-sequence modulation on the metering error of the electric energy meter. The simulation results are as follows: Figure 7 shown.

[0176] (2) When ensuring that phase noise and amplitude noise exist at the same time, the number of m-sequences is increased from 1 to 12, and 20 simulation experiments are set for each level. The scatter plots of the metering error of the electric energy meter under different numbers of levels are analyzed and compared. The results are shown in the figure. Figure 8 shown.

[0177] (3) When the power factor is 0.5, 0.8, and 1.0 respectively, after m-sequence modulation, the influence of input current amplitude on the measurement error of the electric energy meter is analyzed and compared. The results are as follows: Fig. 9 shown.

[0178] Depend on Figure 7 It can be seen that under the condition that both phase noise and amplitude noise exist, the measurement error of the mathematical model obtained after m-sequence modulation is about 50% of that in the unmodulated case. Figure 8 It can be seen that with the increase of the m-sequence level, the measurement error does not change significantly. In general, the measurement error is less than 0.3%, and in the worst case it is 0.79%, which meets the measurement standard of electric energy meters; Fig. 9 It can be seen that with the increase of input current amplitude, the measurement error of the electric energy meter gradually decreases. When the input current is greater than 5A, the measurement error is less than 0.3%. When the input current is greater than 15A, the measurement error is less than 0.1%. This rule exists under different power factors.

[0179] Smart meters are divided into Fig.10 The 12 interference areas are shown. In the electromagnetic field frequency of 400MHz to 1GHz, a tuned dipole antenna is used (8 frequencies, including 400MHz, 450MHz, 500MHz, 600MHz, 700MHz, 800MHz, 900MHz, and 1GHz, and a horn antenna is used in the high frequency band of 1.1GHz to 2.5GHz (4 frequencies, including 1GHz, 1.5GHz, 2GHz, and 2.5GHz). Each frequency point, each position, and each polarization direction require about 20 minutes of testing), interfere for 60s, pause for 20s, and continue to interfere. Each frequency band is tested 100 times.

[0180] According to the above experimental design, dynamic error tests were carried out on three electric energy meters from different manufacturers.

[0181] Due to the huge amount of data, huge errors are inevitable during the test process. In order to reduce the impact of this phenomenon on the experimental conclusions, this application uses the three sigma criterion to clean the power values ​​of each interference group to ensure the reliability and accuracy of subsequent data analysis. The mean and standard deviation calculation formulas are as follows:

[0182]

[0183] Among them, μ is the mean value of the measurement error of each interference group; σ is the standard deviation of the measurement error of each interference group. Then use the following rules to eliminate outliers in the interference group error:

[0184]

[0185] After the above processing, Fig.11 It can be seen that the probability of the value distribution being within 3σ is as high as 99.73%. Values ​​outside this range can be considered as outliers and eliminated, which can effectively reduce the impact of gross errors on data analysis.

[0186] According to the measured experimental data, the measurement error of three different electric meters was analyzed by MATLAB software. The relationship between signal source power and dynamic error was studied when the signal source frequency was 400MHz, 450MHz, 500MHz, 600MHz, 700MHz, 800MHz, 900MHz, 1000MHz, 1500MHz, 2000MHz, and 2500MHz; the transmission source power was -30dB, -12dB, -10dB, -8dB, and -5dB. The test change curves of electric energy meters A, B, and C are shown in Figure 2. Fig.12 shown.

[0187] Depend on Fig.12 It can be seen that the data analysis results of the three different meters are similar. When the signal source frequency is constant, the energy measurement error increases with the increase of the signal source power. When it increases to a certain extent, the error variation range decreases. Since the size of the signal source power mainly depends on the amplitude of the RF signal, it can be considered that when the signal source frequency is constant, the energy measurement error increases with the increase of the signal source amplitude.

[0188] When the signal source power is constant, the energy metering error will slowly increase with the increase of the signal source frequency. When it reaches a certain level, it will show a decreasing trend, and its turning frequency is similar under different transmission powers.

[0189] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0190] The following is an embodiment of the device of the present invention. For details not described in detail therein, reference may be made to the corresponding method embodiment described above.

[0191] Fig.13 The structure diagram of the error correction device for an electric energy meter in an electromagnetic environment provided by an embodiment of the present invention is shown. For the convenience of description, only the part related to the embodiment of the present invention is shown, which is described in detail as follows:

[0192] like Fig.13 As shown, the error correction device 13 for an electric energy meter in an electromagnetic environment includes:

[0193] An acquisition module 1301 is used to acquire a signal source frequency, a signal source amplitude and electromagnetic radio frequency signal parameters of an electric energy meter in an electromagnetic environment;

[0194] A determination module 1302 is used to determine whether the signal source frequency, the signal source amplitude and the electromagnetic radio frequency signal parameters exceed a preset error range, and when the judgment result is that the signal source frequency, the signal source amplitude and the electromagnetic radio frequency signal parameters exceed the preset error range, determine a correction value of the electromagnetic radio frequency signal parameters according to the signal source frequency and the signal source amplitude;

[0195] The adjustment module 1303 is used to adjust the error correction module of the electric energy meter by using the electromagnetic radio frequency signal parameter correction value to achieve error correction of the electric energy meter.

[0196] In a possible implementation, the determining module 1302 is specifically configured to:

[0197] determining a frequency threshold and an amplitude threshold according to electromagnetic radio frequency signal parameters;

[0198] When the frequency of the signal source exceeds the frequency threshold, or the amplitude of the signal source exceeds the amplitude threshold, it is determined that the preset error range is exceeded.

[0199] In a possible implementation, the determining module 1302 is further configured to:

[0200] Under different electromagnetic radio frequency signal parameter conditions, the signal source frequency and signal source amplitude are changed respectively, and the corresponding electric energy meter measurement error values ​​are collected;

[0201] Perform cluster analysis on the collected data to determine the error variation rules under different electromagnetic RF signal parameter conditions and different combinations of signal source frequencies and signal source amplitudes;

[0202] The error variation rule is stored according to the set data structure.

[0203] In a possible implementation, the determining module 1302 is specifically configured to:

[0204] When the error variation law is stored according to the relationship comparison table, the frequency threshold and the amplitude threshold are determined by looking up the table according to the electromagnetic radio frequency signal parameters and the error variation law.

[0205] In a possible implementation, the determination module 1302 is specifically used to: input the electromagnetic radio frequency signal parameters into the frequency threshold determination model and the amplitude threshold determination model respectively, and output the corresponding frequency threshold and amplitude threshold;

[0206] Among them, the frequency threshold determination model and the amplitude threshold determination model are trained based on the error variation law.

[0207] In a possible implementation, the electromagnetic radio frequency signal parameters include:

[0208] The electromagnetic radio frequency signal amplitude, the electromagnetic radio frequency signal frequency and the electromagnetic radio frequency signal phase.

[0209] In a possible implementation, a spectrum analyzer is used to monitor electromagnetic radio frequency signal parameters in an electromagnetic environment in real time.

[0210] In a possible implementation, the determining module 1302 is specifically configured to:

[0211] When the signal source frequency is constant, if the signal source power is within the first setting range, the greater the signal source power, the greater the electromagnetic radio frequency signal parameter correction value; if the signal source power exceeds the first setting range, the greater the signal source power, the smaller the electromagnetic radio frequency signal parameter correction value;

[0212] When the signal source power is constant, if the signal source frequency is within the second setting range, the greater the signal source frequency, the greater the electromagnetic RF signal parameter correction value; if the signal source power exceeds the second setting range, the greater the signal source frequency, the smaller the electromagnetic RF signal parameter correction value.

[0213] In a possible implementation, a filter is connected to a signal input terminal of the electric energy meter;

[0214] The adjustment module 1303 is specifically configured to determine a filter adjustment parameter according to the electromagnetic radio frequency signal parameter correction value, and adjust the filter according to the filter adjustment parameter.

[0215] In this embodiment, by obtaining real-time electromagnetic interference parameters and obtaining the metering error analysis model corresponding to the smart electric energy meter, the efficiency of metering error analysis is improved to adapt to different electromagnetic interference environments. The real-time electromagnetic interference parameters are input into the metering error analysis model, and the metering error value of the electric energy meter is output. When the metering error value of the electric energy meter is greater than the set threshold corresponding to the metering error analysis model, error warning information is generated. Among them, the metering error analysis model is obtained by training based on the test data after performing an error test on the smart electric energy meter based on the m-sequence dynamic test signal. Since in the actual working environment of the electric energy meter, the regional electromagnetic signal will undergo abnormal changes in time, frequency domain, energy, etc., and the surrounding electromagnetic signals have the characteristics of randomness and time-varying. The error test of the smart electric energy meter based on the m-sequence dynamic test signal can improve the efficiency of metering error analysis. The present invention takes into account the influence of the randomness of the electromagnetic signal on the metering error of the smart electric energy meter, and improves the accuracy of metering error monitoring.

[0216] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0217] Those of ordinary skill in the art will appreciate that the templates, units, and algorithm steps of each example described in conjunction with the embodiments disclosed in this application can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0218] If the module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, the steps of the above-mentioned methods and device embodiments for error correction of electric energy meters under electromagnetic environments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device that can carry the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory, random access memory, electric carrier signal, telecommunication signal and software distribution medium.

[0219] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A method for error correction of electric energy meters in an electromagnetic environment, characterized in that: include: Acquire the signal source frequency, signal source amplitude and electromagnetic radio frequency signal parameters of the electric energy meter in the electromagnetic environment, and determine whether the signal source frequency, signal source amplitude and electromagnetic radio frequency signal parameters exceed a preset error range according to the signal source frequency, signal source amplitude and electromagnetic radio frequency signal parameters; When the judgment result is beyond the preset error range, determining the electromagnetic radio frequency signal parameter correction value according to the signal source frequency and the signal source amplitude; The error correction module of the electric energy meter is adjusted by utilizing the electromagnetic radio frequency signal parameter correction value to realize the error correction of the electric energy meter.

2. The method for error correction of electric energy meters in electromagnetic environment according to claim 1, characterized in that: The determining whether the signal source frequency, the signal source amplitude and the electromagnetic radio frequency signal parameter exceed a preset error range includes: Determining a frequency threshold and an amplitude threshold according to the electromagnetic radio frequency signal parameters; When the signal source frequency exceeds the frequency threshold, or the signal source amplitude exceeds the amplitude threshold, it is determined that the preset error range is exceeded.

3. The method for error correction of electric energy meters in electromagnetic environment according to claim 2, characterized in that: Before obtaining the signal source frequency of the electric energy meter in the electromagnetic environment, the signal source amplitude of the electric energy meter and the electromagnetic radio frequency signal parameters, the method further includes: Under different electromagnetic radio frequency signal parameter conditions, the signal source frequency and signal source amplitude are changed respectively, and the corresponding electric energy meter measurement error values ​​are collected; Perform cluster analysis on the collected data to determine the error variation rules under different electromagnetic RF signal parameter conditions and different combinations of signal source frequencies and signal source amplitudes; The error variation rule is stored according to the set data structure.

4. The method for error correction of electric energy meters in electromagnetic environment according to claim 3, characterized in that: The determining of the frequency threshold and the amplitude threshold according to the electromagnetic radio frequency signal parameters comprises: When the error variation law is stored according to a relationship comparison table, a table lookup is performed based on the electromagnetic radio frequency signal parameters and the error variation law to determine the frequency threshold and the amplitude threshold.

5. The method for error correction of electric energy meters in electromagnetic environment according to claim 3, characterized in that: The determining of the frequency threshold and the amplitude threshold according to the electromagnetic radio frequency signal parameters comprises: Inputting the electromagnetic radio frequency signal parameters into a frequency threshold determination model and an amplitude threshold determination model respectively, and outputting corresponding frequency thresholds and amplitude thresholds; Wherein, the frequency threshold determination model and the amplitude threshold determination model are obtained through training based on the error variation law.

6. The method for error correction of electric energy meter in electromagnetic environment according to any one of claims 1 to 5, characterized in that: The electromagnetic radio frequency signal parameters include: The electromagnetic radio frequency signal amplitude, the electromagnetic radio frequency signal frequency and the electromagnetic radio frequency signal phase.

7. The method for error correction of electric energy meters in electromagnetic environment according to claim 1, characterized in that: Use spectrum analyzer to monitor electromagnetic RF signal parameters in electromagnetic environment in real time.

8. The method for error correction of electric energy meters in electromagnetic environment according to claim 1, characterized in that: The determining of the electromagnetic radio frequency signal parameter correction value according to the signal source frequency and the signal source amplitude includes: When the signal source frequency is constant, if the signal source power is within the first setting range, the greater the signal source power, the greater the electromagnetic radio frequency signal parameter correction value; if the signal source power exceeds the first setting range, the greater the signal source power, the smaller the electromagnetic radio frequency signal parameter correction value; When the signal source power is constant, if the signal source frequency is within the second setting range, the greater the signal source frequency, the greater the electromagnetic RF signal parameter correction value; if the signal source power exceeds the second setting range, the greater the signal source frequency, the smaller the electromagnetic RF signal parameter correction value.

9. The method for error correction of electric energy meters in electromagnetic environment according to claim 1, characterized in that: Connect a filter to the signal input end of the electric energy meter; The method of adjusting the error correction module of the electric energy meter by using the electromagnetic radio frequency signal parameter correction value includes: A filter adjustment parameter is determined according to the electromagnetic radio frequency signal parameter correction value, and the filter is adjusted according to the filter adjustment parameter.

10. A device for error correction of electric energy meters in electromagnetic environment, characterized in that: include: An acquisition module is used to acquire the signal source frequency, signal source amplitude and electromagnetic radio frequency signal parameters of the electric energy meter in the electromagnetic environment, and determine whether the signal source frequency, signal source amplitude and electromagnetic radio frequency signal parameters exceed a preset error range according to the signal source frequency, signal source amplitude and electromagnetic radio frequency signal parameters; A determination module, configured to determine a correction value of an electromagnetic radio frequency signal parameter according to the signal source frequency and the signal source amplitude when the judgment result exceeds a preset error range; The adjustment module is used to adjust the error correction module of the electric energy meter by using the electromagnetic radio frequency signal parameter correction value to realize the error correction of the electric energy meter.

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