Power grid side electric energy metering method and device considering inter-harmonic component

Abstract

The invention relates to the technical field of electric energy measurement, and provides a power grid side electric energy metering method and device considering inter-harmonic components, and the method comprises the following steps: obtaining voltage data and current data of a power grid side, and extracting a voltage waveform signal and a current waveform signal through constructing a steady-state signal model; based on the obtained waveform signals, fundamental component extraction is carried out, based on a unary linear regression method, the amplitudes and phases of harmonic signals and inter-harmonic signals are compensated, and harmonic components and inter-harmonic components are extracted; based on the obtained fundamental component, each harmonic component and inter-harmonic component of each signal, calculating to obtain fundamental electric energy, harmonic electric energy and inter-harmonic electric energy; and based on the fundamental wave electric energy, the harmonic electric energy and the inter-harmonic electric energy, correcting the measured electric energy of the power grid side. And through steady-state model fitting and a unary linear regression compensation mechanism, the response and adaptability to high-frequency disturbance components are improved.

Description

Technical Field

[0001] The present invention relates to the technical field related to electric energy measurement, and in particular to a grid-side electric energy metering method and device taking into account interharmonic components. Background Art

[0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] In order to ensure the stable operation of the power system and the accuracy of energy management, accurate measurement of power on the grid side is particularly important. Especially in the scenario where wind farms and photovoltaic power plants are connected to the grid, real-time acquisition of available power data on the grid side not only helps to optimize energy dispatch and frequency control, but also has important significance for power quality analysis, electricity bill settlement and evaluation of new energy power generation efficiency.

[0004] However, since photovoltaic power generation and wind power generation are significantly affected by weather, environmental and other factors during operation, the output power is volatile and unstable. Especially in the process of connecting new energy power sources to the power grid, harmonics or interharmonics are often introduced on the grid side due to a variety of complex factors. These power disturbance signals will not only cause grid pollution, but may also lead to a decrease in the effective transmission efficiency of power. More importantly, when faced with high-frequency harmonic and interharmonic interference, traditional power grid power measurement methods often have problems such as insufficient response capability, low filtering accuracy, and low frequency domain resolution, resulting in large measurement errors, which makes the acquired power data deviate from the actual value, affecting the system's scheduling and analysis decisions.

[0005] Among the existing methods, an energy metering method based on Kaiser window FFT single peak interpolation is proposed. Its core idea is to perform FFT transformation after applying Kaiser window function to the measured voltage and current signals, and to perform interpolation correction on frequency, amplitude and phase through spectrum line amplitude ratio fitting correction formula, so as to improve the accuracy of energy metering in the presence of harmonic and interharmonic interference. Although this method improves the accuracy of harmonic parameter extraction to a certain extent, it still relies on the spectrum characteristics and empirical formula of fixed window function. The spectrum characteristics of fixed window function (such as Kaiser window) are set at the time of design, and cannot dynamically adapt to the actual grid frequency fluctuation, signal characteristic changes or complex harmonic components. It is difficult to deal with the errors caused by spectrum leakage and non-integer period sampling under different working conditions; interpolation correction formulas are mostly empirical fitting formulas based on the response characteristics of window functions, and lack of interpretable mathematical model support for the relationship between frequency offset and error. When the frequency offset exceeds a specific range or the interference component is complex, the compensation accuracy decreases significantly. Summary of the invention

[0006] In order to solve the above problems, the present invention proposes a grid-side electric energy metering method and device taking into account interharmonic components, which realizes the sampling of waveform signals by constructing a steady-state signal model of grid voltage and current, and further constructs an error compensation model based on univariate linear regression, and establishes a statistical mapping relationship with frequency offset as the independent variable and error as the dependent variable, which fundamentally enhances the system's perception and correction capabilities of measurement errors caused by frequency disturbances, thereby improving the accuracy and robustness of the overall electric energy metering.

[0007] In order to achieve the above object, the present invention adopts the following technical solution: One or more embodiments provide a grid-side electric energy metering method taking into account interharmonic components, comprising the following steps: Obtain voltage data and current data on the grid side, and extract voltage waveform signals and current waveform signals by building a steady-state signal model; Based on the obtained waveform signals, the fundamental component is extracted, and based on the univariate linear regression method, the amplitude and phase of the harmonic signal and the interharmonic signal are compensated to extract the harmonic component and the interharmonic component; Based on the fundamental wave component, each harmonic component and interharmonic component of each signal obtained, the fundamental wave electric energy, harmonic electric energy and interharmonic electric energy are calculated respectively; The measured electric energy on the grid side is corrected based on the fundamental electric energy, harmonic electric energy and interharmonic electric energy.

[0008] One or more embodiments provide a grid-side electric energy metering device taking into account interharmonic components, including: A sampling module is configured to obtain voltage data and current data on the grid side, and extract voltage waveform signals and current waveform signals by constructing a steady-state signal model; The component extraction module is configured to extract the fundamental component based on each waveform signal obtained, and to compensate the amplitude and phase of the harmonic signal and the interharmonic signal based on a univariate linear regression method to extract the harmonic component and the interharmonic component; The electric energy calculation module is configured to calculate the fundamental electric energy, the harmonic electric energy and the interharmonic electric energy respectively based on the fundamental wave component, each harmonic component and the interharmonic component of each signal obtained; The correction module is configured to correct the measured electric energy on the grid side based on the fundamental electric energy, the harmonic electric energy and the interharmonic electric energy.

[0009] An electronic device comprises a memory and a processor and computer instructions stored in the memory and executed on the processor. When the computer instructions are executed by the processor, the steps of the above-mentioned grid-side electric energy metering method taking into account interharmonic components are completed.

[0010] Compared with the prior art, the present invention has the following beneficial effects: The electric energy metering method of the present invention can realize accurate metering of electric energy on the grid side in a complex electric energy disturbance environment. Through steady-state model fitting and univariate linear regression compensation mechanism, the response and adaptability to high-frequency disturbance components are improved. Compared with the fixed window function method, this method has higher spectrum adaptability and modeling flexibility, and can effectively reduce energy errors caused by factors such as spectrum leakage, frequency drift and non-integer cycle sampling. This strategy significantly improves the frequency domain resolution and the dynamic range of energy measurement, enabling the system to accurately obtain the actual distribution of electric energy in fundamental, harmonic and interharmonic, providing reliable support for electric energy data analysis and scheduling decisions.

[0011] The advantages of the present invention and additional advantages will be described in detail in the following specific embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] The accompanying drawings constituting a part of the present invention are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their description are used to explain the present invention but do not constitute a limitation of the present invention.

[0013] Figure 1 is a flow chart of a grid-side electric energy metering method according to Embodiment 1 of the present invention; Figure 2 is a system block diagram of a grid-side electric energy metering method according to Embodiment 2 of the present invention; Figure 3 It is a schematic diagram of the structure of the electronic device according to the third embodiment of the present invention. DETAILED DESCRIPTION

[0014] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0015] It should be noted that the following detailed descriptions are exemplary and are intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present invention belongs.

[0016] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprising" and / or "including" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof. It should be noted that, in the absence of conflict, the various embodiments of the present invention and the features in the embodiments can be combined with each other. The embodiments will be described in detail below in conjunction with the accompanying drawings.

[0017] Example 1 In the technical solutions disclosed in one or more embodiments, Figure 1 As shown, a grid-side electric energy metering method taking into account interharmonic components comprises the following steps: Step S1, obtaining voltage data and current data on the grid side, and extracting voltage waveform signals and current waveform signals through the constructed steady-state signal model; Step S2: extracting the fundamental component based on each waveform signal obtained, and compensating the amplitude and phase of the harmonic signal and the interharmonic signal based on a univariate linear regression method to extract the harmonic component and the interharmonic component; Step S3, based on the fundamental wave component, each harmonic component and interharmonic component of each signal obtained, respectively calculate and obtain the fundamental wave electric energy, harmonic electric energy and interharmonic electric energy; Step S4, correcting the measured electric energy on the grid side based on the fundamental electric energy, harmonic electric energy and interharmonic electric energy; In this embodiment, by constructing a steady-state signal model of voltage and current, using the voltage and current time series signals obtained by continuous sampling, the time domain fitting method is first used to extract the steady-state waveform, and the fundamental component is separated therefrom. Then, the harmonics and interharmonics of the known frequency components are subjected to residual fitting with the original waveform by applying a univariate linear regression strategy, and the amplitude and phase of each frequency component are obtained by the fitting coefficient to achieve accurate compensation for the non-fundamental frequency components. Subsequently, the extracted frequency component signals are used to calculate the respective electric energy components, which are the fundamental electric energy, harmonic electric energy and interharmonic electric energy, respectively, and the integral method is used to sum the power signals per unit time to achieve energy quantification. Finally, the original measurement data is corrected for electric energy in combination with the three types of electric energy results, which significantly improves the overall measurement accuracy.

[0018] This implementation method can achieve accurate measurement of grid-side electric energy in a complex electric energy disturbance environment. Through steady-state model fitting and linear regression compensation mechanism, the response and adaptability to high-frequency disturbance components are improved. Compared with the fixed window function method, this method has higher spectrum adaptability and modeling flexibility, and can effectively reduce energy errors caused by factors such as spectrum leakage, frequency drift and non-integer cycle sampling. This strategy significantly improves the frequency domain resolution and the dynamic range of energy measurement, enabling the system to accurately obtain the actual distribution of electric energy in fundamental, harmonic and interharmonic, providing reliable support for electric energy data analysis and scheduling decisions.

[0019] In step S1, the voltage data and current data on the grid side are obtained, and a method for extracting a voltage waveform signal and a current waveform signal by constructing a sampling model includes the following steps: S11: When multiple new energy generating units are connected to the grid and operated, the voltage data and current data on the grid side are synchronously collected and processed to obtain the collected voltage data and the collected current data on the grid side; In the specific implementation process, the voltage data and current data on the grid side are synchronously collected and processed to obtain the collected voltage data and collected current data on the grid side. Specifically: A voltage acquisition device and a current acquisition device are arranged on the grid side, and the voltage acquisition device and the current acquisition device are controlled to synchronously perform the acquisition of voltage data and current data on the grid side, so as to obtain the collected voltage data and current data on the grid side.

[0020] The power grid of this embodiment is composed of multiple new energy units connected to the grid. The new energy generator sets may include but are not limited to photovoltaic battery components in photovoltaic power plants and wind generator sets in wind power plants. When the new energy units are generating electricity, the discharge of the new energy units fluctuates due to environmental reasons. When the new energy units are connected to the grid, the power generation of the new energy units fluctuates, resulting in the grid being subject to more serious harmonic or interharmonic impacts, which may cause large errors in the calculation of electric energy on the grid side. After multiple new energy units are connected to the grid and put into operation, voltage and current collection on the grid side is realized through the voltage collection equipment and current collection equipment set up on the grid side, that is, the voltage collection equipment and the current collection equipment are controlled to synchronously execute the collection and processing of the voltage data and the current data on the grid side, so as to obtain the collected voltage data and the collected current data on the grid side.

[0021] S12: For the voltage data and the current data, data sampling and processing are respectively performed through the constructed steady-state signal model to extract the voltage waveform signal and the current waveform signal; the steady-state signal model includes a steady-state grid voltage signal model and a steady-state grid current signal model. Based on the steady-state grid voltage signal model and the steady-state grid current signal model, real-time data sampling and processing are performed on the voltage data and the current data on the grid side to obtain the voltage waveform signal and the current waveform signal.

[0022] In a specific implementation method, first, a steady-state grid voltage signal model and a steady-state grid current signal model are constructed, as follows: The steady-state grid voltage signal model is: ; The steady-state grid current signal model is: ; in, , Respectively represent the number of different frequency components in the voltage data and current data; , Respectively represent the frequency value of the nth frequency component in the voltage data and the current data; , Respectively represent the initial phase angle of the nth frequency component in the voltage data and the current data; , Represents the collected voltage data and current data under the nth frequency component of the input.

[0023] Then set the number of frequency components n, the initial phase angle of each frequency component and , and the frequency value of each frequency component, the steady-state grid voltage signal model and the steady-state grid current signal model constructed above are respectively configured to perform real-time data sampling and processing on the voltage data and the current data on the grid side to obtain a voltage waveform signal and a current waveform signal; In the above implementation, the voltage and current signals on the grid side are fitted into steady-state waveform functions composed of multiple frequency components by mathematical modeling. The voltage signal model constructs a voltage time domain signal composed of fundamental wave, harmonics and interharmonics by setting the corresponding amplitude, frequency and initial phase angle for each frequency component; the current signal model also uses the same method to model the multi-frequency components. After obtaining the actual measurement signal, by fitting the above model parameters, the separation and identification of each frequency component in the voltage and current can be achieved, providing basic support for the subsequent calculation of the electric energy component. This signal modeling method establishes an accurate mapping between the measurement data and the spectral characteristics, so that the contribution of different frequency components in the time domain can be clearly reflected.

[0024] The above modeling method can characterize the steady-state spectrum structure of voltage and current in the power grid in a clear mathematical form, which not only improves the recognition accuracy of each frequency component, but also enhances the interpretability of the modeling results. The model has a high degree of structural flexibility and can adapt to power interference components of different quantities, frequency ranges and phase relationships. Through the parameter fitting process, the amplitude and phase errors in the actual signal can be accurately estimated, providing effective input for the subsequent compensation mechanism based on regression analysis, thereby significantly improving the spectrum resolution and energy calculation accuracy of the entire power metering system.

[0025] In the above scheme, a steady-state grid voltage signal model and a steady-state grid current signal model are first constructed, and then the collected voltage data and current data are input into the steady-state model, and the voltage and current waveform signals are output through the steady-state grid voltage signal model and the steady-state grid current signal model.

[0026] In step S2, based on each waveform signal obtained, the fundamental component, harmonic component and interharmonic component are extracted, including the following steps: S21: performing fundamental wave orthogonal component extraction processing based on the voltage waveform signal and the current waveform signal to obtain voltage fundamental wave orthogonal components and current fundamental wave orthogonal components; In a specific implementation process, fundamental wave orthogonal component extraction processing is performed based on the voltage waveform signal and the current waveform signal to obtain the voltage fundamental wave orthogonal component and the current fundamental wave orthogonal component, including: S211: Obtaining the fundamental frequency of each waveform signal on the grid side, and filtering the voltage waveform signal and the current waveform signal in sequence based on the fundamental frequency to obtain a voltage fundamental wave signal and a current fundamental wave signal; S212: Perform fundamental wave orthogonal component extraction processing on the voltage fundamental wave signal and the current fundamental wave signal to obtain the voltage fundamental wave orthogonal component and the current fundamental wave orthogonal component.

[0027] Optionally, continuous Fourier transform can be used to extract fundamental orthogonal components. The voltage fundamental signal and the current fundamental signal are transformed by continuous Fourier transform, and the fundamental orthogonal components are extracted based on the transformation results, thereby obtaining the voltage fundamental orthogonal components and the current fundamental orthogonal components.

[0028] In the above scheme, it is first necessary to determine the fundamental frequency of each waveform signal, that is, the AC signal, and obtain the fundamental frequency (such as 50Hz) of the AC signal on the grid side of the power grid according to relevant settings. After obtaining the fundamental frequency, the voltage waveform signal and the current waveform signal are filtered in turn by the fundamental frequency, so that the voltage fundamental signal and the current fundamental signal can be effectively extracted; then the orthogonal components of the voltage fundamental signal and the current fundamental signal are extracted.

[0029] S22: extracting harmonics and interharmonics from the voltage waveform signal and the current waveform signal to obtain voltage harmonic components, current harmonic components, voltage interharmonic components, and current interharmonic components, including: S221: Based on the voltage fundamental wave signal and the current fundamental wave signal, separate the voltage harmonic signal, the voltage interharmonic signal, the current harmonic signal and the current interharmonic signal from the voltage waveform signal and the current waveform signal; Specifically, after obtaining the voltage fundamental signal and the current fundamental signal, it is necessary to separate the harmonic signals and interharmonic signals of the voltage waveform signal and the current waveform signal; the voltage waveform signal is subjected to difference processing with the voltage fundamental signal, and the current waveform signal is subjected to difference processing with the current fundamental signal, and the obtained signals can be separated into harmonic signals or interharmonic signals, wherein the harmonic signal is an integer multiple signal greater than 1 of the fundamental signal, and the interharmonic signal is a non-integer multiple signal; in this way, the voltage harmonic signal, the voltage interharmonic signal, the current harmonic signal and the current interharmonic signal can be separated.

[0030] S222: extracting the amplitude and phase values ​​corresponding to the voltage harmonic signal, the voltage interharmonic signal, the current harmonic signal, and the current interharmonic signal respectively; S223: performing error compensation processing on the corresponding amplitude and phase value of each signal to obtain a voltage harmonic signal, a voltage interharmonic signal, a current harmonic signal and a current interharmonic signal after error compensation; Since amplitude or phase errors may occur when the harmonic signal and the interharmonic signal are separated, it is necessary to perform error compensation processing on the amplitude and phase values, that is, error compensation processing is performed on the amplitude and phase values ​​corresponding to the voltage harmonic signal, the voltage interharmonic signal, the current harmonic signal, and the current interharmonic signal respectively; In a feasible implementation method, the error compensation method can adopt a curve fitting method to compensate for the amplitude error, establish an amplitude compensation model based on univariate linear regression, and compensate the error value of the amplitude of the separated harmonic signal and interharmonic signal accordingly. The amplitude compensation model based on univariate linear regression is specifically: Frequency offset is the independent variable, the amplitude error value of the harmonic signal or interharmonic signal As the dependent variable, the frequency offset is the offset between the actual frequency and the fundamental frequency (50Hz); multiple corresponding offset variables and error values ​​are used as independent observation samples , and perform univariate linear regression analysis to obtain the regression parameters best estimate; The amplitude compensation model based on univariate linear regression is as follows: ; ; ; ; in, is the number of samples, is the average value of the amplitude error, is the average value of frequency offset; are the coefficients of the amplitude compensation model, is the bias of the amplitude compensation model; Perform curve fitting calculation based on the best estimated values ​​of regression parameters, calculate the theoretical errors of each harmonic and interharmonic, and make corresponding error compensation for the observed values; Similarly, the phase value is also compensated in the same way, and a phase compensation model based on univariate linear regression is established: is the independent variable, the phase error value of the harmonic signal or interharmonic signal As the dependent variable, the frequency offset is the offset between the actual frequency and the fundamental frequency (50Hz); multiple corresponding offset variables and error values ​​are used as independent observation samples , and perform univariate linear regression analysis to obtain the regression parameters The best estimate of ; The phase compensation model based on univariate linear regression is as follows: ; ; ; ; in, is the number of samples, is the average value of the phase error, is the average value of frequency offset; are the coefficients of the phase compensation model, is the bias of the phase compensation model; Through the above model, we can get and Best estimate of and ; Thus, the optimal regression parameters are obtained That is, error estimation; then the amplitude and phase values ​​are compensated for errors through regression error estimation.

[0031] The compensation model is established by using univariate linear regression, which simplifies the complex window response estimation process in the traditional spectrum interpolation method. This method has strong mathematical interpretability and model versatility, and can accurately correct amplitude deviations within a variety of disturbance frequency ranges. At the same time, the model has low dependence on input data and can achieve stable modeling through a small number of sampling points, which is convenient for rapid deployment in the field system and significantly improves the accuracy of amplitude recognition and measurement.

[0032] This compensation model provides a low-complexity, highly versatile phase correction method that can significantly improve the accuracy of amplitude and phase angle in power measurement, and is particularly effective for complex signals with multiple frequency components. Compared with the interpolation method that relies on the characteristics of the window function, this method can more flexibly deal with different types of spectrum disturbances, while supporting phase tracking under high-frequency components, and improving the accuracy of reactive power and power factor in power calculation.

[0033] In another achievable implementation manner, the error compensation method may adopt a locally weighted regression (LWR) amplitude and phase compensation method to solve the amplitude and phase recognition error problem of harmonics and interharmonics in the power signal under frequency disturbance.

[0034] Compared with the univariate linear model, the Locally Weighted Regression (LWR) method focuses more on local fitting characteristics while retaining the global trend modeling capability. It can handle nonlinear error behavior more finely, especially showing higher responsiveness and compensation accuracy under high-frequency disturbances or short-term mutations.

[0035] The amplitude and phase compensation method using Locally Weighted Regression (LWR) includes the following steps: S223-1, collecting multiple frequency offsets and corresponding error values ​​(amplitude errors or phase errors) to form observation samples; S223-2. For each data point to be compensated, select a group of sample points in its neighborhood, use the Gaussian kernel function as the weight function to calculate the weight of the sample points, and obtain a weighted matrix: In local weighted regression, instead of using the entire sample set to uniformly model all points, a separate fit is performed for each point to be estimated. In this fitting, each training sample is assigned a weight W based on its "closeness" to the current estimated point. These weights form a diagonal matrix, namely a weighted matrix; S223-3, fitting is performed using the weighted least square method according to the obtained weighted matrix to obtain the compensation amount for each observation data; Furthermore, the compensation amount calculated by the univariate regression compensation model and the compensation amount calculated by the local weighted regression method are averaged to obtain the final supplementary amount.

[0036] S224: Perform component extraction processing of harmonics and interharmonics on each signal after error compensation to obtain each harmonic component of voltage, each harmonic component of current, interharmonic components of voltage, and interharmonic components of current.

[0037] In step S3, the fundamental wave components of each signal include voltage fundamental wave orthogonal components and current fundamental wave orthogonal components; each harmonic component of each signal includes voltage harmonic components and current harmonic components; and the interharmonic components of each signal include voltage interharmonic components and current interharmonic components. Based on the voltage fundamental wave orthogonal component, the current fundamental wave orthogonal component, the voltage harmonic components, the current harmonic components, the voltage interharmonic components and the current interharmonic components, the fundamental wave electric energy, the harmonic electric energy and the interharmonic electric energy are calculated respectively, including: The fundamental wave electric energy is calculated and processed by using the voltage fundamental wave orthogonal component and the current fundamental wave orthogonal component to obtain the fundamental wave electric energy; Harmonic electric energy is calculated and processed in sequence using each harmonic component of voltage and each harmonic component of current, and each harmonic electric energy is accumulated to form harmonic electric energy; The interharmonic electric energy is calculated and processed using the voltage interharmonic components and the current interharmonic components to obtain the interharmonic electric energy.

[0038] Step S4, correcting the measured electric energy on the grid side based on the fundamental electric energy, the harmonic electric energy and the interharmonic electric energy, including: Step S41: Detect and measure the electric energy on the grid side by using an electric energy meter to obtain measured electric energy; Step S42: subtract the fundamental wave power, harmonic power and interharmonic power in sequence from the measured power; In this step, there may be other forms of usable electric energy in the grid, such as direct current electric energy. By subtracting them, other forms of electric energy data in the grid can be calculated. When making corrections, only the unusable harmonic electric energy and interharmonic electric energy need to be corrected. Step S43: based on the subtraction result, correct the measured electric energy to obtain a corrected measured value of the electric energy; 1) If the subtraction result is greater than 0 after the fundamental wave energy, harmonic energy and interharmonic energy are subtracted from the measured energy, the subtraction result is added to the fundamental wave energy as the corrected energy measurement value; Specifically, when the subtraction result is greater than 0, it can be confirmed that there is still DC power on the grid side, and the subtraction result is used as the DC power. At this time, the corrected power measurement value is the sum of the DC power and the fundamental power; as the available power, and as the final corrected power displayed on the grid side of the grid end; 2) If the fundamental wave power, harmonic power and interharmonic power are subtracted from the measured power in sequence and the subtraction result is equal to 0, it is confirmed that there is no DC power at the grid end, and the fundamental wave power is used as the corrected power measurement value; 3) If the fundamental wave energy, harmonic energy and interharmonic energy are subtracted from the measured energy in sequence, and the subtraction result is less than 0, it is determined that the measurement error is large, an early warning is issued, and the measurement result is not output; feedback can be given to the management user that the energy meter has a large measurement error and needs to be repaired.

[0039] The above implementation method uses an energy meter as the original measurement method, and obtains a comprehensive measurement value as the starting point. Then, the extracted fundamental power, harmonic power and interharmonic power are subtracted step by step to strip out the possible redundant energy or noise interference. Branch processing is performed based on the positive and negative judgment of the subtraction result: if the remaining energy is still a positive value, it is considered that there is a missing component, and it is superimposed with the fundamental energy to reconstruct the correction value; if it is zero, it is considered that the measurement is accurate and no correction is required, and the fundamental value is retained as the final data; if a negative value appears, it reflects that the measurement is overshoot or abnormal, triggering the abnormal alarm module to remind the user or system to intervene. The entire processing flow combines physical characteristics and logical judgments to effectively improve the controllability and accuracy of the measurement results.

[0040] The implementation method realizes multi-dimensional calibration of the traditional measurement values ​​of the energy meter, especially in scenarios with severe harmonic and interharmonic interference, which can effectively eliminate the measurement deviation caused by non-power components. The calibration process is set by the "subtraction + conditional judgment" method to avoid false correction or over-compensation caused by simple linear correction, and improve the accuracy and fault tolerance of the correction mechanism. The introduction of the early warning mechanism further improves the system's intelligent perception capability and operational reliability, and can promptly identify and respond to abnormal measurement conditions, which is suitable for application environments in smart grids that are highly sensitive to power quality.

[0041] Example 2 Based on Example 1, this embodiment provides a grid-side electric energy metering device taking into account interharmonic components, such as Figure 2 As shown, including: A sampling module is configured to obtain voltage data and current data on the grid side, and extract voltage waveform signals and current waveform signals by constructing a steady-state signal model; The component extraction module is configured to extract the fundamental component based on each waveform signal obtained, and to compensate the amplitude and phase of the harmonic signal and the interharmonic signal based on a univariate linear regression method to extract the harmonic component and the interharmonic component; The electric energy calculation module is configured to calculate the fundamental electric energy, the harmonic electric energy and the interharmonic electric energy respectively based on the fundamental wave component, each harmonic component and the interharmonic component of each signal obtained; The correction module is configured to correct the measured electric energy on the grid side based on the fundamental electric energy, the harmonic electric energy and the interharmonic electric energy.

[0042] Based on the univariate linear regression method, the amplitude and phase of the harmonic signal and the interharmonic signal are compensated, and the error compensation method adopts the curve fitting method; To compensate for the amplitude error, an amplitude compensation model based on univariate linear regression is established. Specifically: Taking the frequency offset as the independent variable and the amplitude error value of the harmonic signal or inter-harmonic signal as the dependent variable, multiple corresponding offset variables and error values are used as independent observation samples for univariate linear regression analysis to obtain the best estimated values of the regression parameters; The amplitude compensation model based on univariate linear regression is specifically: ; ; ; ; wherein, is the number of samples, is the average value of the amplitude error value, is the average value of the frequency offset; is the coefficient of the amplitude compensation model, is the offset of the amplitude compensation model; Perform curve fitting calculation according to the best estimated values of the regression parameters, calculate the theoretical errors of each harmonic and inter-harmonic, and perform corresponding error compensation on the observed values; For error compensation of the phase value, an amplitude compensation model based on univariate linear regression is established. Specifically: Taking the frequency offset as the independent variable and the phase error value of the harmonic signal or inter-harmonic signal as the dependent variable; using multiple corresponding offset variables and phase error values as independent observation samples, and performing univariate linear regression analysis to obtain the best estimated values of the regression parameters; The phase compensation model based on univariate linear regression is as follows: ; ; ; ; wherein, is the number of samples, is the average value of the phase error value, is the average value of the frequency offset; is the coefficient of the phase compensation model, is the offset of the phase compensation model; Through the above model, the best estimates and in univariate linear regression are obtained and ; thus obtaining the best regression error estimate ; then perform error compensation processing on the amplitude and phase values through the regression error estimate.

[0043] It should be noted here that the various modules in this embodiment correspond one-to-one to the various steps in Example 1, and the specific implementation process is the same, which will not be repeated here.

[0044] Example 3 Based on Embodiment 1, this embodiment provides an electronic device such as Figure 3 As shown, it includes a memory and a processor and computer instructions stored in the memory and running on the processor. When the computer instructions are executed by the processor, the steps of a grid-side electric energy metering method taking into account interharmonic components described in Example 1 are completed.

[0045] Figure 3 The structural components of the electronic device shown do not constitute a limitation on all devices, and may include more or fewer components than shown, or combine certain components. The memory can be used to store the application 401 and various functional modules, and the processor runs the application stored in the memory, thereby executing various functional applications and data processing of the device.

[0046] The memory may be an internal memory or an external memory, or may include both internal and external memories. The internal memory may include a read-only memory (ROM), a programmable ROM (PROM), an electrically programmable ROM (EPROM), an electrically erasable programmable ROM (EEPROM), a flash memory, or a random access memory. The external memory may include a hard disk, a floppy disk, a ZIP disk, a USB disk, a magnetic tape, etc. The memory disclosed in the present invention includes but is not limited to these types of memories. The memory disclosed in the present invention is only used as an example and not as a limitation.

[0047] The input unit is used to receive input signals and keywords input by the user. The input unit may include a touch panel and other input devices. The touch panel may collect touch operations performed by the user on or near the touch panel (such as operations performed by the user using a finger, stylus, or any other suitable object or accessory on or near the touch panel) and drive the corresponding connection device according to a pre-set program; The input device may include, but is not limited to, one or more of a physical keyboard, function keys (such as playback control keys, switch keys, etc.), a trackball, a mouse, a joystick, etc.

[0048] The display unit can be used to display information input by the user or information provided to the user and various menus of the terminal device. The display unit can be in the form of a liquid crystal display, an organic light emitting diode, etc.

[0049] The processor is the control center of the terminal device. It uses various interfaces and lines to connect various parts of the entire device, and performs various functions and processes data by running or executing software programs and / or modules stored in the memory and calling data stored in the memory.

[0050] As an embodiment, the electronic device includes: one or more processors, a memory, and one or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the one or more processors, and the one or more applications are configured to execute the steps in the grid-side electric energy metering method taking into account interharmonic components described in the above-mentioned embodiment 1.

[0051] In an embodiment of the present invention, when multiple new energy units are connected to the grid and operated, the voltage data and current data on the grid side are synchronously collected and processed; the collected voltage data and the collected current data are sampled and processed respectively; the fundamental wave orthogonal component extraction processing is performed based on the voltage waveform signal and the current waveform signal; the harmonic and interharmonic component extraction processing is performed based on the voltage waveform signal and the current waveform signal; the fundamental wave electric energy, harmonic electric energy and interharmonic electric energy are calculated based on the voltage fundamental wave orthogonal component, the current fundamental wave orthogonal component, the voltage harmonic components, the current harmonic components, the voltage interharmonic components and the current interharmonic components respectively; the measured electric energy on the grid side is corrected based on the fundamental wave electric energy, the harmonic electric energy and the interharmonic electric energy; the available electric energy data on the grid side can be accurately measured, and the error of the measured electric energy on the grid side can be reduced, the electricity cost on the user side can be reduced, and the power supply company can be guided to suppress the harmonics and interharmonics on the grid side in time, thereby reducing the loss of electric energy.

[0052] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

[0053] Although the above describes the specific implementation mode of the present invention in conjunction with the accompanying drawings, it is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art on the basis of the technical solution of the present invention without creative work are still within the scope of protection of the present invention.

Claims

1. A grid-side electric energy metering method taking into account interharmonic components, characterized in that: The steps include: Obtain voltage data and current data on the grid side, and extract voltage waveform signals and current waveform signals by building a steady-state signal model; Based on the obtained waveform signals, the fundamental component is extracted, and based on the univariate linear regression method, the amplitude and phase of the harmonic signal and the interharmonic signal are compensated to extract the harmonic component and the interharmonic component; Based on the fundamental wave component, each harmonic component and interharmonic component of each signal obtained, the fundamental wave electric energy, harmonic electric energy and interharmonic electric energy are calculated respectively; The measured electric energy on the grid side is corrected based on the fundamental electric energy, harmonic electric energy and interharmonic electric energy.

2. A grid-side electric energy metering method taking into account interharmonic components as claimed in claim 1, characterized in that: The steady-state grid voltage signal model is: ； The steady-state grid current signal model is: ； in, , Respectively represent the number of different frequency components in the voltage data and current data; , Respectively represent the frequency value of the nth frequency component in the voltage data and the current data; , Respectively represent the initial phase angle of the nth frequency component in the voltage data and the current data; , Represents the collected voltage data and current data under the nth frequency component of the input.

3. A grid-side electric energy metering method taking into account interharmonic components as claimed in claim 1, characterized in that: The voltage data and current data on the grid side are obtained, and the voltage waveform signal and the current waveform signal are extracted by constructing a steady-state signal model, including the following steps: When multiple new energy units are connected to the grid, the voltage data and current data on the grid side are synchronously collected and processed to obtain the collected voltage data and current data on the grid side; For the collected voltage data and current data, data sampling processing is performed respectively through the constructed steady-state signal model to extract the voltage waveform signal and the current waveform signal.

4. A grid-side electric energy metering method taking into account interharmonic components as claimed in claim 1, characterized in that: Based on the univariate linear regression method, the amplitude and phase of the harmonic signal and the interharmonic signal are compensated, and the error compensation method adopts the curve fitting method; To compensate for the amplitude error, an amplitude compensation model based on univariate linear regression is established. Specifically: Taking the frequency offset as the independent variable and the amplitude error value of the harmonic signal or interharmonic signal as the dependent variable, a plurality of corresponding offset variables and error values ​​are used as independent observation samples to perform univariate linear regression analysis and obtain the best estimated value of the regression parameter.

5. A grid-side electric energy metering method taking into account interharmonic components as claimed in claim 4, characterized in that: To compensate for the error of the phase value, an amplitude compensation model based on univariate linear regression is established. Specifically: The frequency offset is used as the independent variable, and the phase error value of the harmonic signal or the interharmonic signal is used as the dependent variable; a plurality of corresponding offset variables and phase error values ​​are used as independent observation samples, and a univariate linear regression analysis is performed to obtain the best estimated value of the regression parameter.

6. A grid-side electric energy metering method taking into account interharmonic components as claimed in claim 1, characterized in that: Based on each waveform signal obtained, fundamental wave components are extracted, and based on a univariate linear regression method, amplitudes and phases of harmonic signals and interharmonic signals are compensated. The method for extracting harmonic components and interharmonic components includes the following steps: Performing fundamental wave orthogonal component extraction processing based on the voltage waveform signal and the current waveform signal to obtain the voltage fundamental wave orthogonal component and the current fundamental wave orthogonal component; The harmonic and interharmonic components are extracted from the voltage waveform signal and the current waveform signal to obtain the voltage harmonic components, the current harmonic components, the voltage interharmonic components and the current interharmonic components.

7. A grid-side electric energy metering method taking into account interharmonic components as claimed in claim 1, characterized in that: The measured power on the grid side is corrected based on fundamental power, harmonic power and interharmonic power, including: The electric energy on the grid side is detected and measured by an electric energy meter to obtain measured electric energy; Subtract the fundamental wave energy, harmonic energy and interharmonic energy in sequence from the measured energy; Based on the subtraction result, the measured electric energy is corrected to obtain a corrected measured value of the electric energy; If the subtraction result is greater than 0 after the fundamental wave electric energy, harmonic electric energy and interharmonic electric energy are subtracted from the measured electric energy in sequence, the subtraction result is added to the fundamental wave electric energy as the corrected electric energy measurement value; If the fundamental wave electric energy, harmonic electric energy and interharmonic electric energy are subtracted from the measured electric energy in sequence, and the subtraction result is equal to 0, the fundamental wave electric energy is taken as the corrected electric energy measurement value; If the fundamental wave electric energy, harmonic electric energy and interharmonic electric energy are subtracted in sequence from the measured electric energy, if the subtraction result is less than 0, it is determined that the measurement error is large and an early warning is issued.

8. A grid-side electric energy metering device taking into account interharmonic components, characterized in that: include: A sampling module is configured to obtain voltage data and current data on the grid side, and extract voltage waveform signals and current waveform signals by constructing a steady-state signal model; The component extraction module is configured to extract the fundamental component based on each waveform signal obtained, and to compensate the amplitude and phase of the harmonic signal and the interharmonic signal based on a univariate linear regression method to extract the harmonic component and the interharmonic component; The electric energy calculation module is configured to calculate the fundamental electric energy, the harmonic electric energy and the interharmonic electric energy respectively based on the fundamental wave component, each harmonic component and the interharmonic component of each signal obtained; The correction module is configured to correct the measured electric energy on the grid side based on the fundamental electric energy, the harmonic electric energy and the interharmonic electric energy.

9. A grid-side electric energy metering device taking into account interharmonic components as claimed in claim 8, characterized in that: Based on the univariate linear regression method, the amplitude and phase of the harmonic signal and the interharmonic signal are compensated, and the error compensation method adopts the curve fitting method; To compensate for the amplitude error, an amplitude compensation model based on univariate linear regression is established. Specifically: Taking the frequency offset as the independent variable and the amplitude error value of the harmonic signal or interharmonic signal as the dependent variable, a plurality of corresponding offset variables and error values ​​are used as independent observation samples to perform a univariate linear regression analysis and obtain the best estimated value of the regression parameter; To compensate for the error of the phase value, an amplitude compensation model based on univariate linear regression is established. Specifically: The frequency offset is used as the independent variable, and the phase error value of the harmonic signal or the interharmonic signal is used as the dependent variable; a plurality of corresponding offset variables and phase error values ​​are used as independent observation samples, and a univariate linear regression analysis is performed to obtain the best estimated value of the regression parameter.

10. An electronic device, characterized in that: The invention comprises a memory and a processor and computer instructions stored in the memory and executed on the processor. When the computer instructions are executed by the processor, the steps of a grid-side electric energy metering method taking into account interharmonic components as described in any one of claims 1 to 7 are completed.

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