Energy meter and wideband metering compensation method of energy meter adaptive to harmonic environment of power grid

Abstract

The present application relates to the field of measuring electric variables, and specifically discloses an electric energy meter wideband metering compensation method and an electric energy meter that are adaptive to a power grid harmonic environment, the method comprising: an electric energy meter obtaining analog signals corresponding to voltage and current in a power grid harmonic environment, and comprehensively calculating a complexity value of an original power grid signal; discretizing different numbers of signal sampling points according to three levels of the complexity value, and obtaining a frequency domain spectrum through Fourier transform; identifying peak values of each wave type based on the frequency domain spectrum, dividing each frequency band corresponding to each wave type component and setting a transition zone on both sides of the frequency band, and corresponding voltage and current signals in the same frequency band; extracting core parameters of each frequency band, calculating electric energy of each wave type, and performing metering compensation corresponding to each frequency band; detecting the metering compensation effect, and if the electric energy meter passes the effect test, performing actual metering of the power grid, and if the electric energy meter fails the effect test, optimizing a preset process and completing an adaptive process of metering compensation.

Description

Technical Field

[0001] This invention relates to the field of measuring electrical variables, specifically to a broadband metering compensation method for electricity meters adapted to power grid harmonic environments, and an electricity meter. Background Technology

[0002] An electricity meter is a core device used to accurately measure electricity consumption. The key to its metering technology is to accurately capture voltage and current signals and calculate power and energy, which revolves around three major aspects: voltage and current signal acquisition, power calculation, and energy accumulation.

[0003] Currently, existing technologies for broadband metering compensation in electricity meters mainly include signal processing-based compensation techniques, magnetic ring compensation structure techniques, and multi-mode error dynamic compensation techniques. Among these, Fourier transform is the fundamental tool for broadband metering. Its core principle is to decompose the time-domain signals of the grid output voltage and current into sine or cosine components of different frequencies within the grid construction environment, thereby specifically compensating for errors at each frequency. In actual metering, the harmonic components of the grid signal are decomposed in real time using Fourier transform. Based on the decomposition results, the power of each frequency component is corrected for errors, and finally, the total compensated power is obtained by summing them up.

[0004] For example, the invention patent with announcement number CN113030835B relates to a method for measuring electricity, including the following steps: Before the electricity meter leaves the factory, its internal MCU stores a first calibration coefficient for adjusting the measurement data of full-wave current and a second calibration coefficient for adjusting the measurement data of half-wave current; the MCU reads and stores the current waveform sampling data in the metering chip, performs a discrete Fourier transform on the current waveform sampling data, and calculates the even-order harmonic content and the odd-order harmonic content; then it is determined whether the above-mentioned even-order harmonic content is within a set threshold range and the odd-order harmonic content is 0 or close to 0; if so, it is determined that this is a half-wave current, and the second calibration coefficient is called to adjust the electricity measured by the electricity meter; if not, the first calibration coefficient is called to adjust the electricity measured by the electricity meter.

[0005] For example, the invention patent with announcement number CN114089263B discloses an automatic DC harmonic compensation method suitable for mass production without manual correction, including: step 1, reading the current signal of the current channel of the metering chip of the energy meter and identifying the DC harmonic operating condition of the current signal; step 2, locating the current signal segment where the current signal is located; step 3, calculating the compensation data of the current signal; and step 4, compensating for the active power sampling error of the current signal.

[0006] Currently, the above technical solutions still have some shortcomings, specifically in the following aspects:

[0007] (1) In practical applications, signal samples of limited length are often collected and processed. The signal spectrum in the frequency domain will have side lobes. When the signal frequency is not at the frequency sampling point of the Fourier transform, the energy will be dispersed to other frequencies and cause spectral leakage, which will cause the position of the peak value of the spectrum to shift. This will cause a large error in the measurement of harmonics and lead to incorrect calculation of the harmonic content.

[0008] (2) Current electricity meters have obvious frequency band coverage gaps in the measurement of high-order harmonics, interharmonics and superharmonics. The existing bandpass filter coefficients have poor adaptability. New power systems usually generate a large number of superharmonics. The bandpass filter cannot adapt to the filtering requirements of different harmonics in a wide frequency domain, which can easily lead to misjudgment and omission of electricity by the electricity meter, affecting the accounting of new energy power generation, resulting in electricity metering errors, and directly affecting the revenue of power generation companies. Summary of the Invention

[0009] To address the shortcomings of existing technologies, this invention provides a broadband metering compensation method and an energy meter for adaptive power grid harmonic environments, which can effectively solve the problems mentioned in the background technology.

[0010] To achieve the above objectives, the present invention provides the following technical solution: The first aspect of the present invention provides a broadband metering compensation method for an adaptive power grid harmonic environment, comprising: the power meter acquiring analog signals corresponding to voltage and current in the power grid harmonic environment; comprehensively calculating the complexity value of the original power grid signal based on the characteristics of the analog signal within the metering period; classifying the original power grid signal into three levels according to the complexity value, obtaining different discrete-time signal samples by corresponding to different numbers of signal sampling points according to the level, and obtaining the frequency domain spectrum through Fourier transform; identifying the peak values ​​of each waveform based on the frequency domain spectrum and recording them into various datasets; dividing each frequency band corresponding to each waveform component and setting transition zones on both sides of the frequency band to correspond the voltage and current signals of the same frequency band; extracting the core parameters of each frequency band, calculating the energy of each waveform respectively, and performing metering compensation for each frequency band during the energy calculation process; inputting a known standard mixed signal to test the metering compensation effect; if the power meter passes the effect test, the actual power grid metering process is performed; if it fails the effect test, the preset process is optimized to complete the adaptive metering compensation process.

[0011] The second aspect of this invention provides an energy meter for a broadband metering compensation method for an adaptive power grid harmonic environment, comprising: a synchronous clock for controlling the acquisition process of voltage and current signals, unifying the time delay of voltage signal processing in a voltage sensor and current signal processing in a current transformer, and synchronizing the frequency bands corresponding to the divided voltage and current; a voltage sensor for acquiring analog signals of voltage connected to the power grid; a current transformer for acquiring analog signals of current connected to the power grid; a spectrum analyzer for sampling and processing each original power grid signal into discrete-time signals, performing Fourier transform on the discrete-time signals to obtain the frequency domain spectrum corresponding to each original power grid signal; and a filter for extracting the corresponding waveform components separately from the mixed signals.

[0012] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects:

[0013] (1) This invention provides a broadband metering compensation method for an adaptive power grid harmonic environment. The power meter acquires the analog signals corresponding to voltage and current in the power grid harmonic environment. Based on the characteristics of the analog signals within the metering period, the complexity value of the original power grid signal is calculated. The complexity value of the original power grid signal is divided into three levels, and different numbers of signal sampling points are corresponding to the levels. This enables the digital signal processing algorithm to track the dynamic changes of the power system and obtain different discrete-time signal samples. The frequency domain spectrum is obtained through Fourier transform. Based on the frequency domain spectrum, the peak values ​​of each waveform are identified and recorded as various datasets. Each frequency band corresponding to each waveform component is divided and a transition zone is set on both sides of the frequency band to eliminate the interference of harmonics and noise on metering in a wide frequency range, thereby achieving accurate metering of broadband power. The voltage and current signals in the same frequency band are matched. The core parameters of each frequency band are extracted, and the power of each waveform is calculated. Metering compensation is performed for each frequency band during the power calculation process. A known standard mixed signal is input to test the metering compensation effect. If the power meter passes the effect test, the actual power grid metering process is performed. If the effect test fails, the preset process is optimized to complete the adaptive metering compensation process.

[0014] (2) The present invention preclassifies the original power grid signal by the complexity value of the original power grid signal, and the complexity value of the original power grid signal corresponds to the complexity of the power grid environment waveform. Based on the complexity value of the original power grid signal, different numbers of signal sampling points are corresponding to the complexity value of the original power grid signal, so that the digital signal processing algorithm can track the dynamic changes of the power system and obtain different discrete time signal samples, prevent the side lobes of the signal in the frequency domain spectrum, and make the signal frequency correspond to the frequency sampling points of the Fourier transform, thereby improving the accuracy of harmonic measurement.

[0015] (3) Compared with the existing technology, this solution fills the gap in frequency band coverage for the metering of high-order harmonics, interharmonics and superharmonics. It prioritizes the differentiation of the frequency distribution of each waveform component in the frequency domain spectrum, and accurately measures the corresponding electrical energy of each waveform component according to the detailed frequency band division. This avoids the omission and miscalculation of the corresponding component's electrical energy due to frequency band mixing. At the same time, it dynamically adapts to the filtering requirements of different harmonics in the wide frequency domain, ensuring the accurate measurement of electrical energy by the meter, adapting to the current accounting of new energy power generation, avoiding the electrical energy metering error in the harmonic environment of the power grid, and protecting the revenue of power generation companies and the rights and interests of users. Attached Figure Description

[0016] The present invention will be further described with reference to the accompanying drawings, but the embodiments in the drawings do not constitute any limitation on the present invention. For those skilled in the art, other drawings can be obtained based on the following drawings without creative effort.

[0017] Figure 1 This is a schematic diagram of the method flow of the present invention.

[0018] Figure 2 This is a schematic diagram of the connection of the electricity meter device of the present invention.

[0019] Figure 3 This is a flowchart of the broadband metering compensation process for the electricity meter according to the present invention.

[0020] Figure 4 This is a schematic diagram of the harmonic frequency range of the electricity meter metering process of the present invention. Detailed Implementation

[0021] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0022] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0023] In the embodiments of this invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning. Similarly, the terms "of," "corresponding (relevant)," and "corresponding" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning.

[0024] In this embodiment of the invention, sometimes a subscript such as W1 may be written in a non-subscript form such as W1. When the difference is not emphasized, the meaning they express is the same.

[0025] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0026] Reference Figure 1 As shown, this invention provides a broadband metering compensation method for electricity meters in an adaptive power grid harmonic environment, comprising:

[0027] The overall process of electricity metering is as follows: analog signals proportional to the grid voltage and current are obtained through voltage divider resistors, shunts, or current transformers and sent to the sampling end of the metering chip. The chip's built-in high-precision analog-to-digital converter converts the collected analog voltage and current signals into digital signals at a fixed sampling rate. The sampling frequency is synchronized with the grid frequency to ensure that the number of sampling points is fixed within one grid cycle. The sampling signal is decomposed into the fundamental wave and each harmonic through a digital signal processing algorithm to obtain independent voltage and current data for each frequency component. The fundamental wave energy and each harmonic energy are calculated separately. The harmonic energy is summed to obtain the harmonic energy. The energy is accumulated in the total energy register and the accumulated result is written to the memory in real time.

[0028] In this embodiment of the invention, Figure 4 It reflects the possible distribution of harmonics and their corresponding amplitudes in the frequency domain spectrum, and can more intuitively show the grouping of each harmonic frequency, and identify the nonlinear interference of the electricity meter in the harmonic range. Figure 4 This is a schematic diagram of the harmonic frequency range of the electricity meter metering process of the present invention.

[0029] In this embodiment of the invention, the above-mentioned power grid harmonic environment includes a situation where there is only the fundamental wave in the power grid, which is an ideal power grid environment for the operation of the electricity meter.

[0030] The electricity meter acquires analog signals corresponding to voltage and current in the grid harmonic environment, and calculates the complexity value of the original grid signal based on the characteristics of the analog signals within the metering period.

[0031] In this embodiment of the invention, the above-mentioned simulated signal is the real signal corresponding to the voltage and current in the actual operation of the power grid, and the core is the signal that changes continuously with time.

[0032] Specifically, the complexity value of the original power grid signal is calculated based on the characteristics of the analog signal within the metering period. The process is as follows:

[0033] The electricity meter is installed in the harmonic environment of the power grid. The synchronous clock built into the metering chip controls the acquisition of voltage and current, unifies the time delay of voltage in voltage sensor and current in current transformer signal processing, and synchronously acquires the analog signals corresponding to voltage and current respectively.

[0034] The analog signals corresponding to voltage and current within the metering cycle are extracted and recorded as the original power grid signals.

[0035] The ideal fundamental peak value of each original power grid signal is coupled with a preset value ratio. Specifically, the ideal fundamental peak value is multiplied by the preset value ratio to obtain the value threshold of each original power grid signal.

[0036] It should be explained that the aforementioned ideal fundamental peak values ​​refer to the fixed voltage and current peak values ​​corresponding to the fundamental wave in the ideal power grid environment in which the electricity meter operates. These are all ideal preset parameters.

[0037] Extract each peak value of each original power grid signal, compare each peak value of each original power grid signal with the threshold value of each original power grid signal, and count the number of original power grid signal peak values ​​that are greater than or equal to the threshold value of the original power grid signal. This number is recorded as the number of local peak values ​​of the original power grid signal.

[0038] In this embodiment of the invention, the variance of the zero-crossing rate of change of the original power grid signal is obtained by calculating the slope change rate of the original power grid signal at each zero point position, then averaging the slope change rates, and calculating the variance based on the average. The mean of the zero-crossing time interval deviation of the original power grid signal is obtained by calculating the time interval of the original power grid signal at each adjacent zero point position and then averaging the difference between the time intervals.

[0039] The number of local peaks, the variance of the zero-crossing rate of change, and the mean of the zero-crossing time interval deviation of the original power grid signal within the metering period are obtained and normalized respectively. Characteristic influence parameters corresponding one-to-one with the number of local peaks, the variance of the zero-crossing rate of change, and the mean of the zero-crossing time interval deviation are introduced. These parameters are used to quantify the influence weight of each parameter on the final result. The normalized results of each parameter are weighted and aggregated with the corresponding characteristic influence parameters to obtain the complexity value of the original power grid signal as a comprehensive parameter.

[0040] The specific analysis process is as follows:

[0041]

[0042] In the formula, CPX is the complexity value of the original power grid signal, num is the number of local peaks in the original power grid signal, D is the variance of the zero-crossing rate of change of the original power grid signal, E is the mean of the zero-crossing time interval deviation of the original power grid signal, q1 is the characteristic influence parameter corresponding to the number of local peaks preset in the energy meter compensation database, q2 is the characteristic influence parameter corresponding to the variance of the zero-crossing rate of change preset in the energy meter compensation database, and q3 is the characteristic influence parameter corresponding to the mean of the zero-crossing time interval deviation preset in the energy meter compensation database.

[0043] Based on historical data, the influence of the number of local peaks, the variance of the zero-crossing rate of change, and the mean of the zero-crossing time interval deviation on the original power grid signal complexity is determined. Each influence level is assigned a weight with a total percentage of 1. Using the number of local peaks, the variance of the zero-crossing rate of change, and the mean of the zero-crossing time interval deviation of the original power grid signal within the metering period as model inputs, the LSTM algorithm updates the influence weights of all parameters in reverse, gradually reducing the error. The corresponding feature influence parameters are used as output targets. After the weighted model stabilizes, the corresponding influence parameters are output. For example, using the number of local peaks in the original power grid signal as input to construct training data, combined with the time-series feature input of the metering period, the cumulative influence of the number of local peaks is captured, and the feature influence parameters corresponding to the number of local peaks are output. These parameters are then organized into a mapping table, stored in the energy meter compensation database, and the corresponding mapping relationship is retrieved through the energy meter.

[0044] In this embodiment of the invention, multivariate analysis is performed on the number of local peaks in the original power grid signal, the variance of the zero-crossing rate of change of the original power grid signal, and the mean of the zero-crossing time interval deviation of the original power grid signal. Specifically, the correlation between these parameters is considered. The variance of the zero-crossing rate of change of the original power grid signal is positively correlated with the mean of the zero-crossing time interval deviation of the original power grid signal. The number of local peaks in the original power grid signal and the mean of the zero-crossing time interval deviation of the original power grid signal jointly affect the variance of the zero-crossing rate of change of the original power grid signal.

[0045] Based on the complexity of the original power grid signal, it is divided into three levels. Different numbers of signal sampling points are corresponding to the levels to obtain different discrete-time signal samples, and the frequency domain spectrum is obtained through Fourier transform.

[0046] Specifically, the number of signal sampling points corresponds to different levels, and the process is as follows:

[0047] The complexity value of the original power grid signal is mapped to a preset power grid signal complexity level, which includes the fundamental frequency ordinary level, the mixed harmonics complexity level, and the mixed superharmonics complexity level.

[0048] The built-in spectrum analyzer in the electricity meter samples and processes the original power grid signals into discrete-time signals, with different numbers of sampling points corresponding to different levels of power grid signal complexity.

[0049] The original power grid signal corresponding to the fundamental frequency ordinary level is sampled and processed using a preset number of fundamental frequency sampling points, while the original power grid signal corresponding to the mixed superharmonic complex level is sampled and processed using a preset number of high-precision sampling points.

[0050] The number of local peak values ​​of the original power grid signal corresponding to the complexity level of mixed harmonics is first extracted. The equivalent mixed harmonic number is obtained by substituting the equivalent mixed harmonic number into a preset power function relationship with the number of sampling points of the fundamental wave, and then the number of mixed harmonic sampling points is obtained for sampling processing.

[0051] After sampling and processing, each original power grid signal is converted into a discrete-time signal. The discrete-time signal is then subjected to a Fourier transform to obtain the frequency domain spectrum corresponding to each original power grid signal.

[0052] The peak values ​​of each waveform are identified based on the frequency domain spectrum and recorded into various datasets. Each frequency band corresponding to each waveform component is divided and a transition zone is set on both sides of the frequency band. The voltage and current signals in the same frequency band are then mapped.

[0053] Specifically, the process involves dividing each frequency band corresponding to each waveform component and setting transition regions on both sides of the frequency band.

[0054] Various datasets are obtained based on frequency domain spectrum identification, including fundamental wave datasets, harmonic datasets, and superharmonic datasets.

[0055] The amplitude values ​​at corresponding positions in the fundamental wave dataset, harmonic dataset, and superharmonic dataset are coupled with a preset frequency band retention ratio. Specifically, the amplitude values ​​at corresponding positions in each dataset are multiplied by the preset frequency band retention ratio to obtain the frequency band retention threshold for each waveform. The frequency band retention threshold for each waveform is the basis for filtering out noise interference introduced by the Fourier transform based on the generation characteristics of the frequency domain spectrum.

[0056] It should be explained that the corresponding position mentioned above refers to the location point in the frequency domain spectrum that contains spectral information. The corresponding amplitude, phase and frequency data can be obtained by finding the location point in the frequency domain spectrum.

[0057] The amplitude of the frequency domain spectrum corresponding to the original power grid signal is compared with the frequency band retention threshold at the corresponding position. If the amplitude of the spectrum is greater than or equal to the frequency band retention threshold at the corresponding position, the spectrum at that position is marked as the waveform at the corresponding position. If the amplitude of the spectrum is less than the frequency band retention threshold at the corresponding position, the position is not marked.

[0058] The frequency spectrum corresponding to the band retention threshold of the fundamental wave is denoted as the fundamental wave band boundary, and the frequency spectrum corresponding to the band retention threshold of the harmonic wave is denoted as the harmonic band boundary, thus dividing the band components of the fundamental wave and the band components of the harmonic wave.

[0059] Extract the peak data corresponding to the superharmonic dataset, obtain the midpoint frequency of the frequency corresponding to the adjacent real peak, and denot it as the frequency band boundary frequency of each superharmonic. This yields the sub-band components that separate each component of the superharmonic.

[0060] It should be explained that the aforementioned true peak values ​​refer to the peak data contained in the location points collected after noise removal and stored in various datasets.

[0061] Transition zones are set at both sides of the harmonic frequency band components and at both sides of the sub-frequency band components of the superharmonic wave.

[0062] The proportions of harmonic frequency band components in the total frequency domain spectrum and the proportions of each sub-band component of superharmonic waves in the total frequency domain spectrum are calculated, and the results are denoted as harmonic proportions and sub-proportions of superharmonic waves.

[0063] The actual peak value corresponding to the harmonic frequency band component is coupled with the harmonic proportion. Specifically, the actual peak value corresponding to the harmonic frequency band component is multiplied by the harmonic proportion to obtain the transition width of the harmonic frequency band.

[0064] The actual peak values ​​corresponding to each sub-band component of the superharmonic wave are coupled with the corresponding sub-proportions of the superharmonic wave. Specifically, the actual peak values ​​corresponding to each sub-band component of the superharmonic wave are multiplied by the sub-proportions of the superharmonic wave to obtain the transition width of each sub-band of the superharmonic wave.

[0065] In this embodiment of the invention, the reason for extending the transition zone in the frequency band division of harmonics and superharmonics is that the spectral range of harmonics and superharmonics of different frequencies is wider than the fixed position of the fundamental wave. Adding a transition zone to the frequency bands of harmonics and superharmonics can prevent omissions of harmonic and superharmonic frequency bands caused by the determination of threshold division, thereby improving the accuracy of power metering.

[0066] The synchronization clock synchronizes the divided voltage and current with the corresponding frequency band, compares the frequency axis corresponding to the voltage and current in the same frequency band, and fills in the missing frequency spectrum parameters.

[0067] It should be explained that the above-mentioned supplementing the missing frequency corresponding to the frequency means that if only one frequency corresponding to the voltage or current exists, the other frequency corresponding to the missing current or voltage needs to be obtained in the frequency domain spectrum and classified as a frequency within the frequency band.

[0068] In this embodiment of the invention, the calculation of electrical energy is essentially the accumulation of grid power over time. Therefore, it is necessary to align voltage and current in the same frequency band to ensure that the frequency axes corresponding to voltage and current both have spectral parameters corresponding to the frequency of voltage and current.

[0069] Furthermore, the process of obtaining various datasets based on frequency domain spectrum identification is as follows:

[0070] Obtain the frequency domain spectrum corresponding to each original power grid signal, count the amplitude and distribution of each peak in the frequency domain spectrum, and calculate the effective value of the signal in the frequency domain spectrum;

[0071] It should be explained that the above process of calculating the effective value of the signal in the frequency domain spectrum involves obtaining the amplitude corresponding to each frequency point in the spectrum, calculating the effective value of each individual component for each original power grid signal, and then superimposing them according to Passevar's theorem to obtain the effective value of the signal in the frequency domain spectrum.

[0072] In this embodiment of the invention, distribution refers to the phase difference between each location point, reflecting the positional relationship of each location point in the frequency domain spectrum.

[0073] The amplitude corresponding to each peak is compared with the effective value of the signal in the frequency domain spectrum. If there is a peak in the frequency domain spectrum whose amplitude is less than the effective value of the signal in the frequency domain spectrum, and the frequency distribution corresponding to the peak is only a single point, then the peak is identified as noise interference, the peak is removed, and the true peaks corresponding to the original power grid signal in the frequency domain spectrum are highlighted.

[0074] The maximum threshold of the fundamental frequency range is obtained by superimposing the ideal fundamental frequency with the preset position discrimination error value, and the minimum threshold of the fundamental frequency range is obtained by performing difference processing on the ideal fundamental frequency with the preset position discrimination error value.

[0075] It should be explained that the aforementioned ideal fundamental frequency refers to the fixed voltage and current spectrum frequencies corresponding to the fundamental frequency in the ideal power grid environment in which the electricity meter operates. These are all ideal preset parameters.

[0076] Extract the frequency corresponding to each true peak and compare it with the threshold of the fundamental frequency range. If a true peak belongs to the fundamental frequency range, then the data of the location point corresponding to the true peak is included in the dataset and denoted as the fundamental frequency dataset.

[0077] Identify the location corresponding to each true peak in the spectrum, and denote the region where the frequency distribution corresponding to each true peak in the frequency domain spectrum is not equal to 1 as a broadband region. Include the data of the location points corresponding to each true peak in the broadband region into the dataset, which is called the superharmonic dataset.

[0078] In this embodiment of the invention, the peak shape of the fundamental wave and harmonics in the frequency domain spectrum is either the fundamental wave or each harmonic corresponds to only one independently distributed peak. The distribution of the peak values ​​of the superharmonic is a broadband cluster rather than a single peak. Therefore, the superharmonic can be distinguished from the fundamental wave and harmonics based on the distribution of the peak values.

[0079] The maximum and minimum thresholds of the fundamental frequency range are both multiplied by a preset positive integer to obtain each positive harmonic range. The frequencies corresponding to the independent true peaks are extracted and compared with the thresholds of each positive harmonic range. If the frequency of an independent position belongs to a certain positive harmonic range, the data corresponding to this frequency position is included in the dataset and recorded as the positive integer harmonic dataset corresponding to that positive harmonic range.

[0080] In this embodiment of the invention, the frequency position of the harmonic is usually a positive integer multiple of the fundamental frequency, and the positive integer is greater than or equal to 3. The multiple by which the harmonic is greater than the fundamental frequency is recorded as the harmonic order. For example, if the frequency position of the fundamental frequency is 50Hz, the frequency position of the 3rd harmonic is approximately 150Hz, and the frequency position of the 3rd harmonic is usually 3 times that of the fundamental frequency.

[0081] Extract the core parameters of each frequency band, calculate the electrical energy of each waveform, and perform metering compensation for each frequency band during the electrical energy calculation process.

[0082] Specifically, the metering compensation process for each frequency band is as follows:

[0083] Based on the predefined frequency bands of the fundamental, harmonic, and superharmonic components, the corresponding fundamental, harmonic, and superharmonic components are extracted separately from the frequency domain spectrum through the built-in filter of the energy meter.

[0084] In this embodiment of the invention, the filter built into the energy meter can configure the filter coefficients according to the frequency data of the frequency band, and filter out the corresponding frequency band from the frequency domain spectrum of the mixed signal.

[0085] Calculate the electrical energy components of the fundamental, harmonic, and superharmonic frequencies separately, and perform metering compensation for each frequency band:

[0086] The core parameters of each waveform component of the original power grid signal corresponding to each frequency band are extracted. The core parameters include the amplitude, frequency and phase of each voltage waveform component corresponding to each frequency band, and the amplitude, frequency and phase of each current waveform component corresponding to each frequency band.

[0087] The fundamental phase difference between voltage and current is obtained by performing phase difference processing on the frequency band corresponding to the fundamental voltage component and the frequency band corresponding to the fundamental current component.

[0088] The voltage amplitude and current amplitude of the fundamental frequency band are coupled. Specifically, the voltage amplitude and current amplitude of the fundamental frequency band are multiplied, the coupling result is multiplied with the fundamental phase difference between voltage and current, and the product is integrated within the measurement period to obtain the electrical energy component of the fundamental frequency band.

[0089] Obtain the ratio difference of the current transformer as indicated on the electricity meter, and couple the ratio difference of the current transformer with the energy component of the fundamental frequency band. Specifically, multiply the ratio difference of the current transformer with the energy component of the fundamental frequency band to obtain the compensation component of the fundamental frequency band. Superimpose the energy component of the fundamental frequency band with the compensation component of the fundamental frequency band to obtain the actual energy component of the fundamental frequency band.

[0090] The voltage amplitude and current amplitude of the harmonic frequency band are coupled together. Specifically, the voltage amplitude and current amplitude of the harmonic frequency band are multiplied together, and the coupling result is multiplied with the harmonic phase difference corresponding to the voltage and current. The product result is then integrated within the metering period to obtain the electrical energy component of the harmonic frequency band.

[0091] The calibration synthesis error of the FIR filter corresponding to the harmonic frequency band is extracted. The difference between the electrical energy component of the harmonic frequency band and the calibration synthesis error is processed to obtain the actual electrical energy component of the harmonic frequency band.

[0092] In this embodiment of the invention, in wideband metering of electricity, the comprehensive error of the FIR filter includes amplitude, phase and frequency response, and is usually controlled between 0.5% and 5%. The specific value depends on the filter order, window function selection and hardware quantization bit depth.

[0093] Furthermore, the metrological compensation for each frequency band also includes:

[0094] The voltage amplitude and current amplitude of the superharmonic sub-band are coupled together. Specifically, the voltage amplitude and current amplitude of the superharmonic sub-band are multiplied together, and the coupling result is multiplied with the superharmonic phase difference corresponding to the voltage and current. The product is then integrated within the measurement period to obtain the electrical energy component of the superharmonic sub-band.

[0095] Superharmonic band compensation uses short-time Fourier transform to obtain the time-frequency matrix, identifies the dominant frequency of the current superharmonic, and generates a correlation coefficient that matches the dominant frequency for each dominant frequency.

[0096] It should be explained that the correlation coefficient mentioned above refers to the quantification of the correlation between the narrowband Fourier basis function matched for each dominant frequency and the corresponding superharmonic, judging the degree of fit between the superharmonic signal and the narrowband Fourier basis function.

[0097] The correlation coefficients of each frequency in the superharmonic band are compared with the preset correlation coefficient threshold. If the correlation coefficient is greater than or equal to the preset correlation coefficient threshold, the corresponding dominant frequency is retained. If the correlation coefficient is less than the preset correlation coefficient threshold, the dominant frequency is considered to be interference from superharmonic doping and is screened out.

[0098] The total electrical energy of the superharmonic frequency band components is obtained by summing the electrical energy components of each superharmonic sub-band.

[0099] The metering compensation effect is tested by inputting a known standard mixed signal. If the meter passes the effect test, the actual metering process of the power grid is carried out. If the meter fails the effect test, the preset process is optimized to complete the adaptive process of metering compensation.

[0100] Specifically, the process of detecting the metrological compensation effect by inputting a known standard spurious signal is as follows:

[0101] Different standard hybrid signals are continuously input into the electricity meter. The standard hybrid signals are pre-constructed grid harmonic hybrid signals that contain known harmonics and superharmonics of specific electrical energy.

[0102] Based on the operation of the electricity meter in the harmonic environment of the power grid, the frequency band division results and the corresponding metering errors of the frequency bands are obtained. The ratio of the metering error corresponding to the frequency band of each waveform division to the electrical energy of the waveform component corresponding to the standard result is calculated to obtain the metering error of each broadband frequency band.

[0103] The metering compensation effect is tested based on the metering error of each broadband frequency. Each broadband frequency metering error is compared with the preset error safety threshold. If each broadband frequency metering error is less than or equal to the error safety threshold, the electricity meter is considered to meet the compensation effect test and the electricity meter is put into actual operation of the power grid.

[0104] In this embodiment of the invention, electricity meters that meet the compensation effect verification are put into actual operation of the power grid. Based on the actual frequency band division during the operation of the electricity meters, the metering is compensated in real time according to the preset compensation measures. If the electricity meter identifies the actual peak value corresponding to a different frequency superharmonic in the superharmonic data set, it automatically includes it in the superharmonic frequency band, recalculates the correlation coefficient corresponding to the frequency band, and completes the adaptive process of metering compensation.

[0105] Furthermore, if the effect test fails, the preset process will be optimized as follows:

[0106] If a broadband metering error exceeds the error safety threshold, the electricity meter is considered to fail the compensation effect test, and the compensation process is optimized.

[0107] The broadband metering error is coupled with the ratio difference of the current transformer marked on the energy meter. Specifically, the broadband metering error is multiplied by the ratio difference of the current transformer marked on the energy meter to obtain the ratio difference compensation value. The ratio difference compensation value is then superimposed on the marked value to obtain the feedback compensation ratio difference.

[0108] The feedback compensation ratio difference is used as the updated value of the ratio difference of the current transformer. The feedback compensation ratio difference is coupled with the actual power component of the fundamental frequency band. Specifically, the feedback compensation ratio difference is multiplied by the actual power component of the fundamental frequency band to obtain the feedback component of the fundamental frequency band. The actual power component of the fundamental frequency band is superimposed with the feedback component of the fundamental frequency band to obtain the power correction component of the fundamental frequency band.

[0109] At the same time, the difference between the broadband measurement error and the error safety threshold is processed to obtain the compensation error.

[0110] The sampling process for the corresponding waveform of the broadband measurement error is set according to the compensation error. The compensation error is coupled with the preset number of sampling points of the corresponding waveform. Specifically, the compensation error is multiplied by the preset number of sampling points of the corresponding waveform, and the result is added to the preset number of sampling points to obtain the number of sampling point corrections.

[0111] Based on the corrected number of sampling points, the original power grid signals are sampled and processed again, and Fourier transform is performed again to obtain the corrected frequency domain spectrum corresponding to each original power grid signal.

[0112] By repeating the operation of the energy meter with the corrected parameters, the corrected frequency band division results and the corresponding metering error data are obtained, and the optimization effect is re-verified.

[0113] Reference Figure 2 As shown, the second aspect of the present invention provides an energy meter for an adaptive power grid harmonic environment broadband metering compensation method, comprising: a synchronous clock, a voltage sensor, a current transformer, a spectrum analyzer, and a filter.

[0114] The aforementioned synchronization clock is used to control the acquisition process of voltage and current signals, unify the signal processing delay of voltage in voltage sensors and current in current transformers, and synchronize the frequency bands corresponding to the divided voltage and current signals.

[0115] The voltage sensor described above is used to acquire analog signals of the voltage connected to the power grid.

[0116] The aforementioned current transformer is used to acquire analog signals of the current connected to the power grid.

[0117] The aforementioned spectrum analyzer is used to sample and process each original power grid signal into a discrete-time signal, and then perform a Fourier transform on the discrete-time signal to obtain the frequency domain spectrum corresponding to each original power grid signal.

[0118] The filter described above is used to extract the corresponding waveform components from the mixed signal individually.

[0119] According to the embodiments of the present invention Figure 3 The process described provides a method for electricity meter compensation: the electricity meter acquires analog signals corresponding to voltage and current in the harmonic environment of the power grid, and calculates the complexity value of the original power grid signal; based on the three levels of complexity, different numbers of signal sampling points are discretized, and the frequency domain spectrum is obtained through Fourier transform; based on the frequency domain spectrum, the peak values ​​of each waveform are identified, each waveform component is divided into a frequency band, and transition zones are set on both sides of the frequency band to correspond the voltage and current signals in the same frequency band; the core parameters of each frequency band are extracted, the energy of each waveform is calculated, and metering compensation is performed for each frequency band; the metering compensation effect is tested, and if the electricity meter passes the effect test, the actual metering process of the power grid is carried out; if it fails the effect test, the preset process is optimized to complete the adaptive process of metering compensation. Figure 3 This is a flowchart of the broadband metering compensation process for the electricity meter according to the present invention.

[0120] The above description is merely an example and illustration of the structure of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, or use similar methods to replace them, as long as they do not deviate from the structure of the invention or exceed the scope defined by the present invention, they should all fall within the protection scope of the present invention.

Claims

1. A broadband metering compensation method for electricity meters in an adaptive power grid harmonic environment, characterized in that, include: The electricity meter acquires analog signals corresponding to voltage and current in the grid harmonic environment, and calculates the complexity value of the original grid signal based on the characteristics of the analog signals within the metering period. Based on the complexity of the original power grid signal, it is divided into three levels. Different numbers of signal sampling points are corresponding to the levels to obtain different discrete-time signal samples. The frequency domain spectrum is obtained through Fourier transform. Based on frequency domain spectrum identification, the peak values ​​of each waveform are recorded into various datasets. Each frequency band corresponding to each waveform component is divided and a transition zone is set on both sides of the frequency band. The voltage and current signals in the same frequency band are matched. Extract the core parameters of each frequency band, calculate the electrical energy of each waveform, and perform metering compensation for each frequency band during the electrical energy calculation process; The metering compensation effect is tested by inputting a known standard mixed signal. If the meter passes the effect test, the actual metering process of the power grid is carried out. If the meter fails the effect test, the preset process is optimized to complete the adaptive process of metering compensation.

2. The broadband metering compensation method for adaptive power grid harmonic environment according to claim 1, characterized in that: The complexity value of the original power grid signal is calculated based on the characteristics of the analog signal within the metering period. The specific calculation process is as follows: The electricity meter is installed in the harmonic environment of the power grid. The synchronous clock built into the metering chip controls the acquisition of voltage and current, unifies the time delay of voltage in voltage sensor and current in current transformer signal processing, and synchronously acquires the analog signals corresponding to voltage and current respectively. The analog signals corresponding to voltage and current within the metering cycle are extracted and recorded as the original power grid signals; The ideal fundamental peak value of each original power grid signal is coupled with a preset value ratio to obtain the value threshold of each original power grid signal. Extract each peak value of each original power grid signal, compare each peak value of each original power grid signal with the threshold value of each original power grid signal, and count the number of original power grid signal peak values ​​that are greater than or equal to the threshold value of the original power grid signal, which is recorded as the number of local peak values ​​of the original power grid signal. The number of local peaks, the variance of the zero-crossing rate of change, and the mean of the zero-crossing time interval deviation of the original power grid signal within the metering period are obtained and normalized respectively. Characteristic influence parameters corresponding one-to-one with the number of local peaks, the variance of the zero-crossing rate of change, and the mean of the zero-crossing time interval deviation are introduced. These parameters are used to quantify the influence weight of each parameter on the final result. The normalized results of each parameter are weighted and aggregated with the corresponding characteristic influence parameters to obtain the complexity value of the original power grid signal as a comprehensive parameter.

3. The broadband metering compensation method for adaptive power grid harmonic environment according to claim 1, characterized in that: The specific process of assigning different numbers of signal sampling points according to the level is as follows: The complexity value of the original power grid signal is mapped to a preset power grid signal complexity level, which includes the fundamental frequency ordinary level, the mixed harmonic wave complexity level, and the mixed superharmonic wave complexity level. The built-in spectrum analyzer in the electricity meter samples and processes the original power grid signals into discrete-time signals, with different numbers of sampling points corresponding to different levels of power grid signal complexity. The original power grid signal corresponding to the fundamental frequency ordinary level is sampled and processed using a preset number of fundamental frequency sampling points, while the original power grid signal corresponding to the mixed superharmonic complex level is sampled and processed using a preset number of high-precision sampling points. The number of local peak values ​​of the original power grid signal corresponding to the complexity level of mixed harmonics is first extracted. The equivalent mixed harmonic number is obtained by substituting the equivalent mixed harmonic number into a preset power function relationship with the number of sampling points of the fundamental wave, and then the number of mixed harmonic sampling points is obtained for sampling processing. After sampling and processing, each original power grid signal is converted into a discrete-time signal. The discrete-time signal is then subjected to a Fourier transform to obtain the frequency domain spectrum corresponding to each original power grid signal.

4. The broadband metering compensation method for adaptive power grid harmonic environment according to claim 1, characterized in that: The process of dividing each frequency band corresponding to each waveform component and setting transition regions on both sides of the frequency band is as follows: Various datasets are obtained based on frequency domain spectrum identification, including fundamental wave datasets, harmonic datasets, and superharmonic datasets; The amplitudes at corresponding positions in the fundamental wave dataset, harmonic dataset, and superharmonic dataset are coupled with a preset frequency band retention ratio to obtain the frequency band retention threshold for each waveform. The frequency band retention threshold for each waveform is the basis for filtering out noise interference introduced by the Fourier transform based on the generation characteristics of the frequency domain spectrum. The amplitude of the frequency domain spectrum corresponding to the original power grid signal is compared with the frequency band preservation threshold at the corresponding position. If the amplitude of the spectrum is greater than or equal to the frequency band preservation threshold at the corresponding position, the spectrum at that position is marked as the waveform at the corresponding position. If the amplitude of the spectrum is less than the frequency band preservation threshold at the corresponding position, the position is not marked. The frequency spectrum corresponding to the fundamental frequency band retention threshold is denoted as the fundamental frequency band boundary, and the frequency spectrum corresponding to the harmonic frequency band retention threshold is denoted as the harmonic frequency band boundary, thus dividing the frequency band components of the fundamental frequency and the harmonic frequency band components. Extract the peak data corresponding to the superharmonic dataset, obtain the midpoint frequency of the frequency corresponding to the adjacent real peaks, and denot it as the frequency band boundary frequency of each superharmonic. This will give us the sub-band components that separate each component of the superharmonic. Transition zones are set at both sides of the harmonic frequency band components and at both sides of the sub-frequency band components of the superharmonic wave. The proportions of harmonic frequency band components in the total frequency domain spectrum and the proportions of each sub-band component of superharmonic waves in the total frequency domain spectrum are calculated, and the results are denoted as harmonic proportions and sub-proportions of superharmonic waves. By coupling the actual peak value corresponding to the harmonic frequency band component with the harmonic proportion, the transition width of the harmonic frequency band can be obtained. By coupling the actual peak values ​​corresponding to each sub-band component of the superharmonic wave with the corresponding proportions of each sub-band of the superharmonic wave, the transition width of each sub-band of the superharmonic wave can be obtained. The synchronization clock synchronizes the divided voltage and current with the corresponding frequency band, compares the frequency axis corresponding to the voltage and current in the same frequency band, and fills in the missing frequency spectrum parameters.

5. The broadband metering compensation method for adaptive power grid harmonic environment according to claim 4, characterized in that: The various datasets obtained based on frequency domain spectrum recognition are as follows: Obtain the frequency domain spectrum corresponding to each original power grid signal, count the amplitude and distribution of each peak in the frequency domain spectrum, and calculate the effective value of the signal in the frequency domain spectrum; The amplitude corresponding to each peak is compared with the effective value of the signal in the frequency domain spectrum. If there is a peak in the frequency domain spectrum whose amplitude is less than the effective value of the signal in the frequency domain spectrum, and the frequency distribution corresponding to the peak is only a single point, then the peak is identified as noise interference, the peak is removed, and the true peaks corresponding to the original power grid signal in the frequency domain spectrum are highlighted. The maximum threshold of the fundamental frequency range is obtained by superimposing the ideal fundamental frequency with the preset position discrimination error value, and the minimum threshold of the fundamental frequency range is obtained by performing difference processing on the ideal fundamental frequency with the preset position discrimination error value. Extract the frequency corresponding to each true peak and compare it with the threshold of the fundamental frequency range. If a true peak belongs to the fundamental frequency range, then the data of the location point corresponding to the true peak is included in the dataset and recorded as the fundamental frequency dataset. Identify the location corresponding to each true peak in the spectrum, and record the region where the frequency distribution corresponding to each true peak in the frequency domain spectrum is not equal to 1 as a broadband region. Include the data of the location points corresponding to each true peak in the broadband region into the dataset, which is called the superharmonic dataset. The maximum and minimum thresholds of the fundamental frequency range are both multiplied by a preset positive integer to obtain each positive harmonic range. The frequencies corresponding to the independent true peaks are extracted and compared with the thresholds of each positive harmonic range. If the frequency of an independent position belongs to a certain positive harmonic range, the data corresponding to this frequency position is included in the dataset and recorded as the positive integer harmonic dataset corresponding to that positive harmonic range.

6. The broadband metering compensation method for adaptive power grid harmonic environment according to claim 1, characterized in that: The metering compensation for each frequency band is performed, and the specific compensation process is as follows: Based on the predefined frequency bands of the fundamental, harmonic, and superharmonic components, the corresponding fundamental, harmonic, and superharmonic components are extracted separately from the frequency domain spectrum through the built-in filter of the energy meter. Calculate the electrical energy components of the fundamental, harmonic, and superharmonic frequencies separately, and perform metering compensation for each frequency band: Extract the core parameters of each waveform component of the original power grid signal corresponding to each frequency band. The core parameters include the amplitude, frequency and phase of each voltage waveform component corresponding to each frequency band, and the amplitude, frequency and phase of each current waveform component corresponding to each frequency band. The fundamental phase difference between voltage and current is obtained by performing phase difference processing on the frequency band corresponding to the fundamental voltage component and the frequency band corresponding to the fundamental current component. The voltage amplitude and current amplitude in the fundamental frequency band are coupled together, and the coupling result is multiplied by the fundamental phase difference between voltage and current. The product is then integrated over the metering period to obtain the energy component of the fundamental frequency band. Obtain the ratio difference of the current transformer marked on the energy meter, couple the ratio difference of the current transformer with the energy component of the fundamental frequency band to obtain the compensation component of the fundamental frequency band, and superimpose the energy component of the fundamental frequency band with the compensation component of the fundamental frequency band to obtain the actual energy component of the fundamental frequency band. The voltage amplitude and current amplitude of the harmonic frequency band are coupled together, and the coupling result is multiplied by the harmonic phase difference corresponding to the voltage and current. The product is then integrated within the metering period to obtain the electrical energy component of the harmonic frequency band. The calibration synthesis error of the FIR filter corresponding to the harmonic frequency band is extracted. The difference between the electrical energy component of the harmonic frequency band and the calibration synthesis error is processed to obtain the actual electrical energy component of the harmonic frequency band.

7. The broadband metering compensation method for adaptive power grid harmonic environment according to claim 6, characterized in that: The step of performing metering compensation for each frequency band also includes: The voltage amplitude and current amplitude of the superharmonic sub-band are coupled together, and the coupling result is multiplied with the superharmonic phase difference corresponding to the voltage and current. The product is then integrated within the measurement period to obtain the electrical energy component of the superharmonic sub-band. Superharmonic band compensation uses short-time Fourier transform to obtain the time-frequency matrix, identifies the dominant frequency of the current superharmonic, and generates a correlation coefficient that matches the dominant frequency for each dominant frequency. The correlation coefficients of each frequency in the superharmonic band are compared with the preset correlation coefficient threshold. If the correlation coefficient is greater than or equal to the preset correlation coefficient threshold, the corresponding dominant frequency is retained. If the correlation coefficient is less than the preset correlation coefficient threshold, the dominant frequency is considered to be superharmonic interference and is screened out. The total electrical energy of the superharmonic frequency band components is obtained by summing the electrical energy components of each superharmonic sub-band.

8. The broadband metering compensation method for adaptive power grid harmonic environment according to claim 1, characterized in that: The measurement compensation effect is detected by inputting a known standard promiscuous signal. The specific detection process is as follows: Different standard hybrid signals are continuously input into the electricity meter. The standard hybrid signals are pre-constructed grid harmonic hybrid signals that contain known harmonics and superharmonics of specific electrical energy. Based on the operation of the electricity meter in the harmonic environment of the power grid, the frequency band division results and the corresponding metering errors of the frequency bands are obtained. The ratio of the metering error corresponding to the frequency band of each waveform division to the electrical energy of the waveform component corresponding to the standard result is calculated to obtain the metering error of each broadband frequency band. The metering compensation effect is tested based on the metering error of each broadband frequency. Each broadband frequency metering error is compared with the preset error safety threshold. If each broadband frequency metering error is less than or equal to the error safety threshold, the electricity meter is considered to meet the compensation effect test and the electricity meter is put into actual operation of the power grid.

9. The broadband metering compensation method for adaptive power grid harmonic environment according to claim 1, characterized in that: If the effect test fails, the preset process will be optimized. The specific optimization process is as follows: If a broadband metering error exceeds the error safety threshold, the electricity meter is considered to fail the compensation effect test, and the compensation process is optimized. The wideband metering error is coupled with the ratio difference of the current transformer marked on the energy meter to obtain the ratio difference compensation value. The ratio difference compensation value is then superimposed on the marked value to obtain the feedback compensation ratio difference. The feedback compensation ratio difference is used as the updated value of the ratio difference of the current transformer. The feedback compensation ratio difference is coupled with the actual power component of the fundamental frequency band to obtain the feedback component of the fundamental frequency band. The actual power component of the fundamental frequency band is superimposed with the feedback component of the fundamental frequency band to obtain the power correction component of the fundamental frequency band. Simultaneously, the difference between the broadband measurement error and the error safety threshold is processed to obtain the compensation error; The sampling process for the corresponding waveform of the broadband measurement error is set according to the compensation error. The compensation error is coupled with the preset number of sampling points for the corresponding waveform, and the result is added to the preset number of sampling points to obtain the number of sampling point corrections. Based on the number of corrected sampling points, the original power grid signals are sampled and processed again, and Fourier transform is performed again to obtain the corrected frequency domain spectrum of each original power grid signal. By repeating the operation of the energy meter with the corrected parameters, the corrected frequency band division results and the corresponding metering error data are obtained, and the optimization effect is re-verified.

10. An energy meter employing the adaptive power grid harmonic environment broadband metering compensation method as described in any one of claims 1-9, characterized in that: include: Synchronous clock, voltage sensor, current transformer, spectrum analyzer, and filter; The synchronization clock is used to control the acquisition process of voltage and current signals, unify the signal processing delay of voltage in voltage sensors and current in current transformers, and synchronize the frequency bands corresponding to the divided voltage and current. The voltage sensor is used to acquire an analog signal of the voltage connected to the power grid; The current transformer is used to acquire an analog signal of the current connected to the power grid; The spectrum analyzer is used to sample and process each original power grid signal into a discrete-time signal, perform a Fourier transform on the discrete-time signal, and obtain the frequency domain spectrum corresponding to each original power grid signal. The filter is used to extract the corresponding waveform components separately from the mixed signal.

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