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CN-121995299-A - Self-adaptive calibration method, device and system applied to intelligent ammeter

CN121995299ACN 121995299 ACN121995299 ACN 121995299ACN-121995299-A

Abstract

The invention discloses a self-adaptive calibration method applied to a smart electric meter, which is characterized in that environmental magnetic field data of the electric meter are collected, a magnetic field interference level is determined based on the environmental magnetic field data, and a calibration mode corresponding to the magnetic field level is switched based on the magnetic field interference level, so that the self-adaptive calibration method is suitable for changeable application environments, the influence of an external magnetic field on the metering of the electric meter is reduced, the metering precision and the operation efficiency are simultaneously considered, and the calibration by adopting a complex algorithm under the condition of small influence of the external magnetic field is avoided. The method comprises the steps of initializing a smart electric meter, collecting metering data, storing a standard waveform sequence, initial metering parameters, standard power and preset fitting coefficients, collecting and storing magnetic field data through a three-dimensional magnetic field sensor, determining a magnetic field interference level based on the magnetic field data, switching to a corresponding calibration mode according to the determined magnetic field interference level, and collecting data and calculating electric energy according to the switched calibration mode, wherein the step S1 is used for collecting metering data and storing the metering data, and the step S2 is used for collecting and storing the magnetic field data through the three-dimensional magnetic field sensor and determining the magnetic field interference level based on the magnetic field data.

Inventors

  • WANG XI
  • YE LAN

Assignees

  • 国网黑龙江省电力有限公司营销服务中心

Dates

Publication Date
20260508
Application Date
20260212

Claims (10)

  1. 1. An adaptive calibration method applied to a smart meter is characterized by comprising the following steps: step S1, initializing an intelligent ammeter, collecting metering data, and storing a standard waveform sequence, initial metering parameters, standard power and preset fitting coefficients; s2, acquiring and storing magnetic field data through a three-dimensional magnetic field sensor, and determining a magnetic field interference level based on the magnetic field data; Step S3, switching to a corresponding calibration mode according to the determined magnetic field interference level; And S4, collecting data and calculating electric energy according to the switched calibration mode.
  2. 2. The adaptive calibration method according to claim 1, wherein the step S1 comprises: s1.1, connecting the intelligent ammeter into a calibration system, wherein the calibration system is used for providing a non-magnetic environment and applying an external standard magnetic field environment; Step S1.2, under the environment without magnetic ring, collecting standard voltage U 0 , standard current I 0 , and voltage sampling value U_samp and current sampling value I_samp of the intelligent ammeter of a standard signal source output signal in a calibration system; s1.3, storing standard waveforms corresponding to the acquired standard signal source output signals; S1.4, taking a standard voltage U 0 and a standard current I 0 of the standard signal source output signal as references, taking a voltage sampling value U_samp and a current sampling value I_samp of the intelligent ammeter as measured values, fitting a voltage sampling coefficient K1 and a current sampling coefficient K2 by a least square method, and storing the voltage sampling coefficient K1 and the current sampling coefficient K2 in the intelligent ammeter; s1.5, calculating and storing an initial power error delta P0 and a standard power P2; And S1.6, testing the intelligent ammeter under the environment of applying an external standard magnetic field, recording an actual power error delta P1 by a high-precision error tester, performing third-order polynomial fitting on acquired data by adopting a least square method, obtaining preset fitting coefficients a0, a1, a2 and a3, and storing the preset fitting coefficients.
  3. 3. The adaptive calibration method according to claim 2, wherein the step S2 comprises: S2.1, acquiring magnetic field data through a three-dimensional magnetic field sensor according to a preset interval, wherein the magnetic field data comprise magnetic field intensities Bx, by and Bz of X, Y, Z triaxial components; S2.2, preprocessing the acquired magnetic field data, removing abnormal data, and calculating the triaxial component average magnetic field intensities Bx1, by1 and Bz1; And S2.3, calculating the magnetic occasion intensity B, the magnetic field azimuth angle theta and the magnetic field pitch angle phi, calculating and storing the weighted magnetic occasion intensity Bw, and respectively adopting the following formulas to calculate: ; ; ; ; Wherein Bx1 is the effective average magnetic field strength of the X-axis component, by1 is the effective average magnetic field strength of the Y-axis component, bz1 is the effective average magnetic field strength of the Z-axis component, B is the magnetic field combined strength, θ is the magnetic field azimuth angle, phi is the magnetic field pitch angle, and w1, w2, w3 are weight parameters; and S2.4, comparing the weighted magnetic occasion intensity Bw with an interference threshold value, and determining the magnetic field interference level as a no-magnetic field interference level, a low-magnetic field interference level or a high-magnetic field interference level.
  4. 4. The adaptive calibration method according to claim 2, wherein the step S1.4 comprises: Taking standard voltage U 0 and standard current I 0 of a standard signal as references, taking a voltage sampling value U_samp and a current sampling value I_samp of an ammeter to be calibrated as actual measurement values, adopting a least square method to fit a voltage sampling coefficient K1 and a current sampling coefficient K2, and enabling a fitting target to be the same as the actual measurement value Minimum (minimum), The fitting formula is as follows: n is the number of sampling points in the test duration, I is the serial number of the sampling points, U_samp (I) and I_samp (I) are the voltage sampling value and the current sampling value of the ith point of the ammeter, and U0 (I) and I0 (I) are the standard voltage value and the standard current value of the ith point of the standard signal.
  5. 5. The adaptive calibration method according to claim 2, wherein the step S1.5 comprises: The calculation formula of the initial power error Δp0 is as follows: ; Wherein P1 is the metering power of the ammeter, P2 is the standard power, and the calculation formulas of P1 and P2 are as follows: P1= ; ; Wherein cos phi 0 is a standard signal power factor, cos phi is a reference power factor, and cos phi is calculated by the following method: Collecting a voltage sampling value sequence U_samp (k) and a current sampling value sequence I_samp (k) in 1 frequency period, calculating a voltage sampling sequence average value U_samp_avg and a current sampling sequence average value I_samp_avg, and calculating covariance Cov (U_samp, I_samp) of the voltage sampling sequence standard deviation sigma U_samp and the current sampling sequence standard deviation sigma I_samp of the voltage sampling sequence average value U_samp_avg and the current sampling sequence average value I_samp, wherein the calculation formula is as follows: ; ; ; wherein n is the number of sampling points in 1 frequency period, and k is the serial number of the sampling points; The phase difference Δφ is calculated as follows: ; The reference power factor cos phi is calculated as follows:
  6. 6. the adaptive calibration method according to claim 3, wherein the step S3 is specifically: the calibration modes comprise a non-interference calibration mode, a low-interference calibration mode and a high-interference calibration mode; when the magnetic field interference level is a magnetic field interference-free level, switching a calibration mode to the interference-free calibration mode; When the magnetic field interference level is a low magnetic field interference level, switching a calibration mode to the low interference calibration mode; And when the magnetic field interference level is a high magnetic field interference level, switching a calibration mode to the high interference calibration mode.
  7. 7. The adaptive calibration method according to claim 6, wherein the step S4 comprises: When the calibration mode is the interference-free calibration mode, the sampling module collects real-time voltage and real-time current, calculates real-time power and calculates electric energy according to the real-time power; When the calibration mode is the low-interference calibration mode, collecting real-time voltage Ua and real-time current Ia, and calculating an uncalibrated power P0, wherein the calculation formula of the uncalibrated power P0 is as follows: wherein, K1 is a voltage sampling coefficient, K2 is a current sampling coefficient, cos phi 1 is a real-time power factor; collecting the real-time frequency f of the power grid, calculating the real-time angular frequency omega, and the real-time angular frequency omega has the following calculation formula: And calculating a fitting power error delta P1 based on the third-order fitting model, wherein the calculation formula is as follows: Wherein, the 、 、 、 The fitting coefficient is preset; the total power error Δp is calculated as follows: The calibrated real-time power P1 is calculated according to the following calculation formula: the electric energy E1 is calculated according to the following formula: when the calibration mode Is the high-interference calibration mode, the current sampling module collects real-time current signals at the frequency of 10kHz to obtain a sampling sequence Is (k) in 1 frequency period, extracts a waveform sequence of the standard waveform stored in the step S1.3, judges whether the waveform Is distorted, executes correction and calculates electric energy if the waveform Is distorted, and calculates the electric energy in the non-interference calibration mode if the waveform Is not distorted.
  8. 8. The adaptive calibration method of claim 7, wherein the performing correction if the waveform is distorted and calculating the power is specifically: with 1 frequency period as a window, is (k) Is divided into continuous windows, each window contains m points, and the current effective value I_rms and the standard waveform effective value I_st_rms of the current window are calculated according to the following calculation formula: wherein m is the number of sampling points, k is the serial number of the sampling points, Sampling a value of the current at the k point; The reference waveform is adjusted to obtain an adjusted reference waveform Iref (k), and the calculation formula is as follows: the difference delta I (k) between each sampling point and the reference waveform is calculated as follows: If Δi (k) > ε×in, then adjacent undistorted linear interpolation correction Is used to obtain corrected data Is' (k), and the correction calculation formula Is as follows: If delta I (k) Is less than or equal to epsilon multiplied by In, linear interpolation correction Is not carried out on adjacent non-distorted points, corrected data Is '(k) =is (k), a corrected waveform Is synthesized to obtain a corrected sequence Is' (k), and a corrected current effective value Ical Is calculated, wherein the calculation formula Is as follows: the voltage sampling sequence is acquired, the voltage effective value Ucal is calculated, and the calculation formula is as follows: calculating the real-time power factor cos phi 2, and calculating the calibrated power P2, wherein the calculation formula is as follows: wherein cos phi 2 is the real-time power factor; the electric energy E2 is calculated according to the following formula:
  9. 9. a smart meter device, comprising: the initialization module is used for initializing the intelligent ammeter, collecting metering data and storing a standard waveform sequence, initial metering parameters, standard power and preset fitting coefficients; The interference level evaluation module is used for acquiring and storing magnetic field data through the three-dimensional magnetic field sensor and determining a magnetic field interference level based on the magnetic field data; The calibration mode switching module is used for switching to a corresponding calibration mode according to the determined magnetic field interference level; and the electric energy calculation module is used for collecting data and calculating electric energy according to the switched calibration mode.
  10. 10. A smart meter system, comprising: A memory for storing a computer program; A processor for implementing the adaptive calibration method according to any one of claims 1-8 when executing said computer program.

Description

Self-adaptive calibration method, device and system applied to intelligent ammeter Technical Field The invention relates to the technical field of intelligent electric meters, in particular to a self-adaptive calibration method, device and system applied to an intelligent electric meter. Background The electric meter is used as a core device for measuring the electric energy consumption, the measurement accuracy of the electric meter directly relates to the interests of both power supply and demand parties, and therefore the calibration work of the electric meter is very important. The existing ammeter calibration mode is concentrated in a factory stage, static calibration is carried out on the ammeter through a standard signal source, initialization is completed after fixed calibration parameters are determined, and dynamic calibration adjustment is not carried out after installation. However, the installation scene of the ammeter is complex and various, and strong magnetic devices such as a transformer, a motor, an electromagnetic oven and the like can be additionally arranged around the installation position, and the environmental magnetic field generated by the devices can cause interference to the current sampling link of the ammeter, so that the electric energy metering error is increased. Moreover, the interference degree of the environment magnetic fields with different intensities on the ammeter is different, and different magnetic field interference scenes cannot be adapted by adopting a single calibration mode, namely, if a calibration method aiming at low magnetic field intensity interference is adopted, measurement deviation exceeds standard due to insufficient calibration precision under the environment with high magnetic field intensity interference, if a complex calibration method aiming at high magnetic field intensity interference is adopted for a long time, the calculation load of the ammeter is increased under the environment without magnetic field interference or with low magnetic field intensity interference, the measurement response speed is reduced, and meanwhile, hardware resources are wasted. Therefore, there is a need for an ammeter calibration method capable of adaptively switching calibration modes according to the real-time environmental magnetic field intensity, so as to achieve both measurement accuracy and equipment operation efficiency under different interference scenarios. Disclosure of Invention The invention provides a self-adaptive calibration method, device and system applied to a smart electric meter, which are used for solving the technical problem that the electric meter in the prior art cannot be matched with an environment magnetic field adjustment calibration mode to accurately meter electric energy. The invention provides a self-adaptive calibration method applied to a smart meter, which comprises the following steps: step S1, initializing an intelligent ammeter, collecting metering data, and storing a standard waveform sequence, initial metering parameters, standard power and preset fitting coefficients; s2, acquiring and storing magnetic field data through a three-dimensional magnetic field sensor, and determining a magnetic field interference level based on the magnetic field data; Step S3, switching to a corresponding calibration mode according to the determined magnetic field interference level; And S4, collecting data and calculating electric energy according to the switched calibration mode. Optionally, the step S1 includes: s1.1, connecting the intelligent ammeter into a calibration system, wherein the calibration system is used for providing a non-magnetic environment and applying an external standard magnetic field environment; Step S1.2, under the environment without magnetic ring, collecting standard voltage U 0, standard current I 0, and voltage sampling value U_samp and current sampling value I_samp of the intelligent ammeter of a standard signal source output signal in a calibration system; s1.3, storing standard waveforms corresponding to the acquired standard signal source output signals; S1.4, taking a standard voltage U 0 and a standard current I 0 of the standard signal source output signal as references, taking a voltage sampling value U_samp and a current sampling value I_samp of the intelligent ammeter as measured values, fitting a voltage sampling coefficient K1 and a current sampling coefficient K2 by a least square method, and storing the voltage sampling coefficient K1 and the current sampling coefficient K2 in the intelligent ammeter; s1.5, calculating and storing an initial power error delta P0 and a standard power P2; And S1.6, testing the intelligent ammeter under the environment of applying an external standard magnetic field, recording an actual power error delta P1 by a high-precision error tester, performing third-order polynomial fitting on acquired data by adopting a least square method, obtaining preset fitting coefficients