Electric energy measurement method under grid waveform distortion

Abstract

The present invention discloses an electric energy metering method under grid waveform distortion, and specifically relates to the technical field of electric energy metering. In view of the problem that the existing technology is prone to generate zero-sequence current or false phase drift in multi-point grounding or grounding fault power systems, which leads to false triggering of energy compensation mechanisms, metering deviations and electricity price settlement risks, an abnormality identification and control method that integrates zero-sequence current frequency domain feature analysis and three-phase phase offset trend consistency judgment is proposed. Through synchronous sampling, frequency domain analysis and trend consistency evaluation of three-phase voltage, current and neutral line current, the false phase offset state is accurately identified, the erroneous compensation behavior is shielded in real time and switched to the fundamental power metering mode. After recovery, the error backtracking correction mechanism is used to ensure the accuracy of electric energy metering, effectively improving the anti-interference ability and metering credibility of the meter under complex working conditions.

Description

Technical Field

[0001] The present invention relates to the technical field of electric energy metering, and in particular to an electric energy metering method under grid waveform distortion. Background Art

[0002] Energy metering under grid waveform distortion refers to the process of accurately measuring energy when the grid voltage or current waveform is distorted (i.e., deviates from an ideal sine waveform) due to factors such as nonlinear loads. Because waveform distortion can cause harmonics and voltage flicker, traditional energy meters can suffer from measurement errors. Therefore, energy metering technology with interference immunity and harmonic recognition capabilities is required to ensure high-precision energy metering in complex grid environments.

[0003] The existing technology has the following shortcomings:

[0004] In power systems with multiple grounding points or ground faults (such as subway traction systems and long-distance transmission lines), zero-sequence currents or false phase shifts may appear in the current loop, which can be misinterpreted by phase-shift identification algorithms as real load phase shifts. Furthermore, this misinterpretation can trigger erroneous energy compensation mechanisms, leading to an improper decomposition of active and reactive power. This can significantly overestimate apparent power metering and distort power factor calculations, potentially leading to contract execution errors or punitive electricity price settlement issues. Summary of the Invention

[0005] The purpose of the present invention is to provide a method for measuring electric energy under grid waveform distortion to solve the shortcomings of the background technology.

[0006] To achieve the above-mentioned object, the present invention provides the following technical solution: a method for measuring electric energy under grid waveform distortion, comprising:

[0007] Collect three-phase voltage and three-phase current signals, and obtain synchronous sampling data including voltage signals, current signals and neutral current signals;

[0008] Performing frequency domain analysis on the sampled data to obtain the total harmonic distortion rate of each phase and the phase angle between the voltage and current;

[0009] Based on the phase angle calculation result, identifying whether there is a phase offset and triggering a compensation algorithm;

[0010] Simultaneously calculating the three-phase zero-sequence current, and judging whether there is a ground fault or nonlinear loop interference based on the amplitude and spectrum characteristics of the zero-sequence current;

[0011] In the case of a ground fault or nonlinear loop interference, the consistency of the phase offset trend of each phase is further analyzed to identify the false phase offset state;

[0012] When a false phase offset state is identified, the current phase compensation operation is shielded and an alternative metering algorithm based on fundamental wave power calculation is adopted;

[0013] The zero-sequence current and phase changes are continuously monitored. If the detection results return to the normal range, the phase compensation mechanism is restored and the error is corrected.

[0014] Preferably, the frequency domain analysis includes:

[0015] Apply window function processing to the sampled signal;

[0016] Perform fast Fourier transform on each phase signal;

[0017] The fundamental and higher harmonic frequency components are extracted to calculate the total harmonic distortion and fundamental phase angle.

[0018] Preferably, determining whether the phase offset is abnormal includes:

[0019] Compare the phase angle of each phase in the current cycle with the set normal range of phase angle;

[0020] If any phase angle deviates from the interval and exceeds the tolerance threshold within a number of consecutive cycles, it is determined that a phase offset anomaly exists.

[0021] Preferably, the frequency domain anomaly index of the zero-sequence current is generated after analyzing the frequency spectrum characteristics, and the generation method is:

[0022] Extracting time domain signals through zero-sequence current calculation formula , perform FFT spectrum analysis on zero sequence current, Apply the window function and perform a fast Fourier transform over one complete cycle to obtain the spectrum: ;in, is the amplitude component of the nth harmonic, Indicates the amplitude of the fundamental wave (50Hz), Indicates the highest harmonic component; sets the weighting coefficient , calculate the zero-sequence current frequency domain anomaly index, the expression is: ; is the frequency domain anomaly index of zero-sequence current.

[0023] Preferably, after analyzing the consistency of the phase shift trends of each phase, a phase shift trend consistency index is generated, and the generation method is:

[0024] Set a sliding time window T and record the phase difference between the three-phase voltage and current in each sampling period: ;in: ; n is the number of sampling points in the time window; is the phase drift time series of phase X, is the phase drift time series of phase Y, is the phase drift time series of phase Z;

[0025] Calculate the cosine similarity for each pair of phase shift vectors , the expression is: ; For the drift angle trend angle between phases X and Y, calculate the three sets of cosine similarities: ; Calculate the phase shift trend consistency index PDCI, that is, average and normalize the three-phase cosine similarity, the expression is: .

[0026] Preferably, the zero-sequence current frequency domain anomaly index and the phase shift trend consistency index are normalized so that they are both between [0, 1], and the normalized zero-sequence current frequency domain anomaly index and the phase shift trend consistency index are weighted averaged to obtain the phase shift state anomaly score value.

[0027] Preferably, a preset judgment threshold Sth∈[0,1] is set. If the phase offset state abnormality score value is greater than or equal to the preset judgment threshold, it is determined to be a false phase offset state, and the compensation algorithm should be prevented from triggering or switching to the fundamental-dominant model; otherwise, it is regarded as a real load change and power compensation processing can be performed normally.

[0028] Preferably, the error correction includes: recording the start and end time of the compensation shielding period and the alternative metering electric energy; after the abnormal state is lifted, estimating the real electric energy based on the historical power factor or load characteristic model; compensating the error of the accumulated electric energy value by interpolation or unified correction factor, and marking the correction section.

[0029] In the above technical solution, the technical effects and advantages provided by the present invention are:

[0030] 1. The proposed method for energy metering under grid waveform distortion effectively addresses the existing problem of phase drift misjudgment caused by ground faults or nonlinear interference. By collecting synchronized data on three-phase voltage, current, and neutral current, and performing frequency domain analysis and trend consistency calculation on the signals, it accurately identifies false phase offset states, avoiding power decomposition distortion and energy metering deviations caused by false triggering compensation mechanisms. This effectively improves the system's anti-interference capability and robustness in multi-point grounding and complex load scenarios.

[0031] 2. By introducing a fundamental power alternative metering mechanism and an error correction mechanism, this invention ensures the continuity and reliability of metering data even in the presence of misjudgments. Once the anomaly is resolved, the system automatically switches to normal compensation mode and retroactively corrects errors, establishing a complete adaptive closed-loop metering system. This method is particularly suitable for complex power quality scenarios, such as subway traction power supply systems, long-distance transmission lines, and industrial distribution networks, demonstrating broad engineering applicability and significant economic value. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments described in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0033] Figure 1 This is a mind map of the method of the present invention. DETAILED DESCRIPTION

[0034] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0035] For examples, see Figure 1 As shown, the electric energy metering method under grid waveform distortion described in this embodiment includes:

[0036] Collect three-phase voltage and three-phase current signals, and obtain synchronous sampling data including voltage signals, current signals and neutral current signals;

[0037] Performing frequency domain analysis on the sampled data to obtain the total harmonic distortion rate of each phase and the phase angle between the voltage and current;

[0038] Based on the phase angle calculation result, identifying whether there is a phase offset and triggering a compensation algorithm;

[0039] Simultaneously calculating the three-phase zero-sequence current, and judging whether there is a ground fault or nonlinear loop interference based on the amplitude and spectrum characteristics of the zero-sequence current;

[0040] In the case of a ground fault or nonlinear loop interference, the consistency of the phase offset trend of each phase is further analyzed to identify the false phase offset state;

[0041] When a false phase offset state is identified, the current phase compensation operation is shielded and an alternative metering algorithm based on fundamental wave power calculation is adopted;

[0042] The zero-sequence current and phase changes are continuously monitored. If the detection results return to the normal range, the phase compensation mechanism is restored and the error is corrected.

[0043] In an embodiment of the present invention, to meet the demand for electric energy metering under conditions of grid waveform distortion, a synchronous sampling module is first designed and implemented to collect multi-channel electrical signals including three-phase voltages (Ua, Ub, Uc), three-phase currents (Ia, Ib, Ic), and neutral current (In), which serve as the input data basis for subsequent distortion identification and metering calculations.

[0044] Specifically, this embodiment configures the energy metering device with a high-precision analog-to-digital converter (ADC). This ADC has at least seven synchronous sampling channels, one for each of the three-phase voltage, three-phase current, and neutral current signals. The sampling frequency of the ADC is preferably set to no less than 10 kHz to ensure accurate capture of common high-order harmonic components (e.g., 15th to 40th harmonics) and non-periodic interference characteristics.

[0045] To achieve amplitude and phase consistency sampling of voltage and current signals, this embodiment uses a unified reference clock source to trigger ADC channel sampling and uniformly controls the sampling starting point through a synchronous controller to maintain a strict time correspondence between the voltage and current waveforms, ensuring the accuracy of subsequent phase angle analysis.

[0046] To enhance detection of zero-sequence components, the sampling channel for the neutral current In is isolated and coupled using a dedicated current transformer with a sensitivity of 0.1 A / bit, ensuring that even weak zero-sequence current fluctuations can be captured and identified. The collected neutral current signal is combined with the individual phase currents for analysis to determine whether the system has multiple grounding points, ground faults, or three-phase imbalance.

[0047] All sampled voltage and current signals will be temporarily stored in the cache unit of the FIFO structure and read by the embedded processor according to the set cycle and perform preliminary signal preprocessing, including low-pass filtering, amplitude normalization, abnormal peak removal and other operations, which will be further used in steps such as spectrum analysis, phase recognition and distortion determination.

[0048] Through the above-mentioned implementation structure and method, the present invention can realize the precise synchronous collection and subsequent analysis of various power parameters in a severely distorted or non-ideal power supply environment, and provide accurate and reliable basic data support for subsequent phase offset correction and compensation strategies.

[0049] After completing the synchronous sampling of the three-phase voltage, current, and neutral current, the present invention further performs frequency domain analysis on the acquired sampled data to extract the main frequency characteristic parameters required for energy metering, including the total harmonic distortion (THD) of each phase voltage and current signal and the phase angle between the voltage and current.

[0050] Specifically, this embodiment uses a Fast Fourier Transform (FFT) algorithm to perform discrete spectrum analysis on each phase voltage and current signal within a fixed time window. The time window is preferably set to an integer multiple of a complete power frequency cycle, such as 20ms, 40ms, or 80ms, to ensure frequency resolution while avoiding spectral leakage caused by boundary truncation.

[0051] During the frequency domain transformation process, this embodiment first applies a window function to the input signal, preferably using a Hanning window, to reduce the interference of sidelobe leakage on the calculation of higher-order harmonics. Then, an FFT is performed on each phase voltage Ua, Ub, and Uc and current Ia, Ib, and Ic to extract the fundamental frequency (typically 50 Hz or 60 Hz) and its several subharmonic amplitude components.

[0052] The calculation formula of the total harmonic distortion THD is: ;in, represents the fundamental amplitude, represents the amplitude of the nth harmonic component, where N is the upper limit of the harmonic order for analysis, preferably 25 or higher.

[0053] At the same time, in order to obtain the phase angle relationship between the voltage and current of each phase, the present invention extracts the phase angle θ of the fundamental component in the corresponding spectrum and calculates the phase difference by the formula: ;in, is the fundamental voltage phase angle, is the fundamental current phase angle, and ϕ represents the phase offset between the voltage and current of the phase.

[0054] In actual implementation, all frequency domain analysis operations are performed by an embedded processor or a supporting digital signal processor (DSP) to ensure real-time performance on the embedded platform. The frequency domain analysis results are temporarily stored and fed into the subsequent distortion determination and compensation logic.

[0055] Through this implementation, the present invention can not only comprehensively identify and quantify the harmonic distortion level of each phase, but also accurately calculate the phase angle change trend, thereby providing data support for whether to enable the phase compensation mechanism in the future, and effectively avoiding the power misdecomposition problem caused by inaccurate frequency component identification.

[0056] After completing the phase angle calculation between the voltage and current of each phase, the present invention further implements a phase offset identification and compensation algorithm triggering mechanism to determine whether there is a risk of electric energy metering error under the current operating conditions, and accordingly decide whether to adjust and compensate the power calculation model.

[0057] Specifically, this embodiment sets a set of reference phase angle intervals to represent the normal phase angle range corresponding to typical load types (such as resistive, inductive, and capacitive) in an ideal sinusoidal power grid environment. The reference intervals can be preset based on the system type or established through self-learning. Typically, the following intervals are set for a fundamental frequency of 50Hz:

[0058] Resistive load: ų≈ 0°±5°;

[0059] Inductive load: ų∈ [+10°, +45°];

[0060] Capacitive load: ų∈ [−10°, −45°];

[0061] In actual operation, the system compares the phase angles ų calculated in real time with the above-mentioned reference interval. If the phase angle of any phase deviates from its typical interval threshold within a number of consecutive cycles (such as 3 to 5 cycles), and the deviation exceeds the set error tolerance (for example, ±10°), an abnormal phase deviation is identified.

[0062] Once a phase shift anomaly is identified, the present invention initiates a compensation algorithm. The compensation algorithm switches to a "phase compensation enhancement mode" based on the current distortion level and phase change trend. In this mode:

[0063] The phase correction factor Δų is introduced to adjust the calculation expressions of active power P and reactive power Q;

[0064] Perform phase synchronization correction on the original voltage and current signals to calibrate the calculation of the power factor cosų;

[0065] Depending on the specific scenario, the fundamental-dominant model or the harmonic rejection model is enabled to ensure that the compensation result is based only on the effective energy component.

[0066] In addition, to avoid false triggering caused by short-term disturbances, this embodiment adopts a time window consistency judgment method. Only when the phase offset anomaly exists continuously and is consistent with the trend of zero-sequence current change, the compensation trigger is finally confirmed, ensuring that the system has good anti-interference ability and false judgment suppression ability.

[0067] Through this implementation, the electric energy metering system can effectively sense abnormal phase drift, dynamically adjust the power calculation path under waveform distortion or system abnormality, and ensure the accuracy and reliability of the metering results.

[0068] In order to improve the ability to identify abnormal grid conditions, especially the accuracy of identifying ground faults and nonlinear loop interference, the present invention further introduces the steps of calculating the zero-sequence current and analyzing the spectrum characteristics after completing the frequency domain analysis of the three-phase voltage and current.

[0069] Specifically, the zero-sequence current It is calculated in real time using the following formula: ;in, 、 、 The calculation can be performed in an embedded processor or digital signal processor (DSP), and is updated once every sampling cycle to maintain dynamic monitoring of the system's neutral imbalance state.

[0070] In order to further identify the abnormal source of zero-sequence current, the present invention Perform frequency domain analysis to extract its spectrum characteristics. After analyzing the spectrum characteristics, generate the zero-sequence current frequency domain anomaly index. The generation method is:

[0071] Extracting time domain signals through zero-sequence current calculation formula , perform FFT spectrum analysis on zero sequence current, Apply a window function (such as a Hanning window) and perform a fast Fourier transform (FFT) within a complete period (such as 40ms) to obtain the spectrum: ;in, is the amplitude component of the nth harmonic, Indicates the amplitude of the fundamental wave (50Hz), Indicates the highest harmonic component (such as the 25th, which is 1250Hz).

[0072] Set weighting coefficient To emphasize the importance of high-frequency components. Commonly used weighting methods are linear increment or exponential weighting. The zero-sequence current frequency domain anomaly index is calculated as follows: ; is the frequency domain anomaly index of zero-sequence current.

[0073] FDAI < 0.05: The spectrum energy is mainly concentrated in the fundamental wave, and the zero-sequence current is normally unbalanced;

[0074] FDAI≈0.1~0.3: There is a certain nonlinear disturbance, which may be ground stray current;

[0075] FDAI > 0.3: The spectrum energy is significantly biased toward high frequencies, suggesting the presence of a ground fault, harmonic injection, or high-frequency coupling interference.

[0076] When a ground fault or nonlinear loop interference is detected, the consistency of the phase shift trends of each phase is analyzed to generate a phase shift trend consistency index. The generation method is:

[0077] Set a sliding time window T (for example, 200ms, corresponding to 10 20ms power frequency cycles), and record the phase difference between the three-phase voltage and current in each sampling period: ;in: ; n is the number of sampling points in the time window (for example, n = 10); is the phase drift time series of phase X, is the phase drift time series of phase Y, is the phase drift time series of phase Z;

[0078] Calculate the cosine similarity for each pair of phase shift vectors , the expression is: ; For the drift angle trend angle between phases X and Y, calculate the three sets of cosine similarities: ; Calculate the phase shift trend consistency index PDCI, that is, average and normalize the three-phase cosine similarity, the expression is: .

[0079] PDCI ≈ 1: The three-phase trends are highly consistent, which may be due to system load changes;

[0080] PDCI∈[0.5, 0.9]: Some phase shifts are different and need to be judged in combination with zero-sequence current;

[0081] PDCI < 0.5: The three-phase trends are seriously inconsistent, suggesting a ground fault, local interference, or sampling anomaly. The compensation mechanism needs to be blocked.

[0082] The zero-sequence current frequency domain anomaly index and the phase shift trend consistency index are normalized so that they are both between [0, 1]. The phase shift state anomaly score is obtained by performing weighted average calculation on the normalized zero-sequence current frequency domain anomaly index and phase shift trend consistency index.

[0083] A preset judgment threshold Sth∈[0,1] (e.g., 0.5-0.7) is set to distinguish between true load phase shift and false phase shift caused by non-power anomalies. If the phase shift state abnormality score is greater than or equal to the preset judgment threshold, it is determined to be a false phase shift state, and the compensation algorithm should be prevented from triggering or switching to the fundamental-dominant model. Otherwise, it is considered a true load change, and power compensation can proceed normally.

[0084] After determining it is in an abnormal state, the system automatically prohibits the execution of the phase compensation logic in the current cycle, including:

[0085] Suspend the calculation path for correcting the active power and reactive power decomposition based on the phase angle;

[0086] Does not update the compensation control registers or power correction factors;

[0087] The period is marked as a compensation shielding period and written into the event record buffer for later tracing and statistics.

[0088] This measure can effectively prevent the system from incorrectly adjusting power components under non-power distortion conditions, avoiding miscalculations or over-corrections in electricity bill settlement.

[0089] While compensating for the operation shielding, the present invention adopts a simplified power metering method based on the fundamental component as an alternative path to ensure that a stable and reliable electric energy metering value can be provided under the false phase drift state.

[0090] The specific implementation of the fundamental wave power measurement method includes the following steps:

[0091] The fundamental wave (50Hz or 60Hz) is extracted from the voltage and current signals using Fourier transform or bandpass filter, which are respectively recorded as 、 .

[0092] Calculate the instantaneous fundamental active power , the expression is: ;in, It is the phase angle between the fundamental voltage and current. If the phase information cannot be obtained stably, a default power factor (such as 0.95) can be set for estimation.

[0093] The fundamental active power obtained is integrated over time to obtain the periodic electric energy. , the expression is: ; 、 Indicates a time period, which is used to identify the data in the final electric energy data as coming from the fundamental wave alternative metering mode, so that the back-end billing system can independently identify it or apply the subsidy mechanism.

[0094] The system continuously monitors the abnormal phase offset score. Once the score falls below the threshold for a certain number of cycles (e.g., 3 consecutive cycles), the system automatically switches back to normal phase compensation mode.

[0095] If switching occurs, the system performs error compensation or interpolation correction to maintain the continuity and accuracy of long-term power statistics results.

[0096] Continuously monitor the zero-sequence current and phase changes. If the detection results return to the normal range, the phase compensation mechanism is restored and the error is corrected. Specifically:

[0097] Read all compensation mask cycle data from the event record buffer to obtain the start and end time , the fundamental wave replacement measurement mode is adopted during this period.

[0098] Extract the integral value of fundamental power during this period ; Compensate for system conditions during the shielding period (temperature, load type, THD level, etc.);

[0099] After the system is freed from the anomaly, the phase compensation model is restored. At this time, the actual power value that should have been generated during the shielding period is estimated based on the restored grid phase state and harmonic level. .

[0100] Common methods include: comparing the current load power factor, harmonic power rate and other characteristics with the historical database; finding the most similar power mode and predicting the true value ;

[0101] Calculate the total error value , the expression is: ;

[0102] Execution error compensation strategy:

[0103] Adjust the accumulated energy value: add ΔE to the distributed interpolation value. The segmented energy can be added back in subsequent settlements: the total energy value is adjusted directly using the correction factor. The segment is marked as corrected; the original and corrected values are archived for audit and verification. If the system supports remote communication, the energy data correction event can be reported to the backend platform.

[0104] The above formulas are all dimensionless and numerical calculations. The formulas are obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formulas are set by technicians in this field according to actual conditions.

[0105] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center via wired or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

[0106] It should be understood that the term "and / or" herein is merely a description of the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B may represent three situations: A exists alone, A and B exist at the same time, and B exists alone, where A and B may be singular or plural. In addition, the character " / " herein generally indicates that the objects associated with each other are in an "or" relationship, but it may also indicate an "and / or" relationship, which can be understood by referring to the context. A person of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0107] The above is only a specific implementation method of the present application, but the scope of protection of the present application is not limited thereto. Any technician familiar with this technical field can easily think of changes or replacements within the technical scope disclosed in this application, which should be covered by the scope of protection of the present application.

Claims

1. A method for measuring electric energy under grid waveform distortion, characterized by: include: Collect three-phase voltage and three-phase current signals, and obtain synchronous sampling data including voltage signals, current signals and neutral current signals; Performing frequency domain analysis on the sampled data to obtain the total harmonic distortion rate of each phase and the phase angle between the voltage and current; Based on the phase angle calculation result, identifying whether there is a phase offset and triggering a compensation algorithm; Simultaneously calculating the three-phase zero-sequence current, and judging whether there is a ground fault or nonlinear loop interference based on the amplitude and spectrum characteristics of the zero-sequence current; Specifically, the frequency domain anomaly index of zero-sequence current is generated after analyzing the spectrum characteristics. The generation method is: extracting the time domain signal through the zero-sequence current calculation formula , perform FFT spectrum analysis on zero sequence current, Apply the window function and perform a fast Fourier transform over one complete cycle to obtain the spectrum: ;in, is the amplitude component of the nth harmonic, Indicates the amplitude of the fundamental wave (50Hz), Indicates the highest harmonic component; sets the weighting coefficient , calculate the zero-sequence current frequency domain anomaly index, the expression is: ; is the frequency domain anomaly index of zero-sequence current; In the case of a ground fault or nonlinear loop interference, the consistency of the phase offset trend of each phase is further analyzed to identify the false phase offset state; Specifically, the consistency of the phase offset trends of each phase is analyzed to generate a phase offset trend consistency index. The generation method is: set a sliding time window T and record the phase difference between the three-phase voltage and current in each sampling period: ;in: ; n is the number of sampling points in the time window; is the phase drift time series of phase X, is the phase drift time series of phase Y, is the phase drift time series of phase Z; Calculate the cosine similarity for each pair of phase shift vectors , the expression is: ; For the drift angle trend angle between phases X and Y, calculate the three sets of cosine similarities: ; Calculate the phase shift trend consistency index PDCI, that is, average and normalize the three-phase cosine similarity, the expression is: ; When a false phase offset state is identified, the current phase compensation operation is shielded and an alternative metering algorithm based on fundamental wave power calculation is adopted; The zero-sequence current and phase changes are continuously monitored. If the detection results return to the normal range, the phase compensation mechanism is restored and the error is corrected.

2. The electric energy metering method under grid waveform distortion according to claim 1, characterized in that: The frequency domain analysis includes: Apply window function processing to the sampled signal; Perform fast Fourier transform on each phase signal; The fundamental and higher harmonic frequency components are extracted to calculate the total harmonic distortion and fundamental phase angle.

3. The electric energy metering method under grid waveform distortion according to claim 1, characterized in that: Determine whether the phase offset is abnormal, including: Compare the phase angle of each phase in the current cycle with the set normal range of phase angle; If any phase angle deviates from the interval and exceeds the tolerance threshold within a number of consecutive cycles, it is determined that a phase offset anomaly exists.

4. The electric energy metering method under grid waveform distortion according to claim 1, characterized in that: The zero-sequence current frequency domain anomaly index and the phase shift trend consistency index are normalized so that they are both between [0, 1]. The phase shift state anomaly score is obtained by performing weighted average calculation on the normalized zero-sequence current frequency domain anomaly index and phase shift trend consistency index.

5. The electric energy metering method under grid waveform distortion according to claim 4 is characterized in that: A preset judgment threshold Sth∈[0,1] is set. If the phase offset state abnormality score value is greater than or equal to the preset judgment threshold, it is determined to be a false phase offset state, and the compensation algorithm should be prevented from triggering or switching to the fundamental-dominant model; otherwise, it is regarded as a real load change and power compensation processing can be performed normally.

6. The electric energy metering method under grid waveform distortion according to claim 5, characterized in that: The error correction includes: recording the start and end time of the compensation shielding period and the alternative metered electric energy; after the abnormal state is released, estimating the real electric energy based on the historical power factor or load characteristic model; compensating the error of the accumulated electric energy value by interpolation or a unified correction factor, and marking the correction section.

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