Power quality interharmonic detection method and device based on power meter

By combining improved IEC grouping and adaptive threshold filtering with linear Kalman filtering, the problem of insufficient accuracy and adaptability in existing interharmonic detection is solved, realizing high-precision and adaptive power quality interharmonic detection, which is suitable for micro-synchronous phasor measurement units in smart energy meters.

CN121955505BActive Publication Date: 2026-05-29NINGXIA LGG INSTR CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
NINGXIA LGG INSTR CO LTD
Filing Date
2026-04-01
Publication Date
2026-05-29

AI Technical Summary

Technical Problem

Existing interharmonic detection schemes suffer from low detection accuracy and poor adaptability. Traditional methods cannot accurately identify the frequency, amplitude, and phase of independent spectral components in a signal, and lack online adaptive adjustment capabilities when the harmonic/interharmonic components of the power grid change dynamically.

Method used

A power quality interharmonic detection method based on electricity meters is adopted. A list of spectral components is generated by improving IEC grouping and adaptive threshold filtering. The optimal estimation of spectral components is performed by combining linear Kalman filter. The state-space model and dynamic maximum allowable error are used to judge the power grid spectrum change, so as to achieve adaptive detection.

Benefits of technology

It improves the accuracy and adaptability of interharmonic detection, can adapt to changes in the power grid spectrum composition online, overcomes the mismatch defects of fixed model algorithms in dynamic power grids, and has high accuracy and anti-interference capabilities.

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Abstract

The application provides a power quality interharmonic detection method and device based on an electric energy meter, and relates to the technical field of power quality monitoring. The method comprises the following steps: acquiring continuous sampling data of a power grid signal, and preprocessing to obtain a complex frequency spectrum; adopting improved IEC grouping and adaptive threshold filtering to filter out false spectral lines, and generating a spectral component list; constructing a state space model and initializing a linear Kalman filter; using the linear Kalman filter to output optimal estimates of instantaneous amplitude, instantaneous phase and instantaneous frequency through prediction and update, and reconstructing the estimated value of the power grid signal; calculating the instantaneous estimation error according to the current sampling point data and the estimated value of the power grid signal; judging whether the power grid spectrum has a mutation according to the instantaneous estimation error and the maximum allowable error, and returning to step S1 to detect again based on the latest continuous sampling data when the mutation occurs. The scheme can improve the accuracy and adaptability of interharmonic detection.
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Citation Information

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