Frequency and harmonic detection method based on unscented Kalman filtering

Abstract

The invention discloses a frequency and harmonic detection method based on unscented Kalman filtering. A fundamental wave frequency part is defined in an observation state variable, the fundamental wave frequency can be directly measured, an independent frequency measurement algorithm is not needed any more, and the problems that according to an existing frequency measurement method such as a zerocrossing point method, zero crossing point detection is inaccurate when harmonic waves are serious, and linearization errors are caused by asynchronous sampling of an interpolation period method aresolved. According to the method, the amplitude and the phase of each harmonic wave are directly selected as parts of the state variable, the amplitude and the phase information of each harmonic wave can be directly measured, and further calculation is not needed; by using the unscented Kalman filter, the problems of spectrum leakage and fence effect caused by asynchronous sampling during frequencymeasurement or harmonic measurement of a Fourier transform method are avoided.

Description

technical field [0001] The invention relates to the field of power quality detection in power systems, in particular to a frequency and harmonic detection method based on unscented Kalman filtering. Background technique [0002] The measurement of frequency in the power system is the basis for the measurement of other power quality parameters. Taking harmonic measurement as an example, the frequency of each harmonic is in multiples of the fundamental frequency. If you want to accurately measure the amplitude and phase of each harmonic, the fundamental frequency must be known, that is, it needs to be measured in advance. [0003] The frequency measurement method has the zero-crossing method, which detects the time interval between two zero-crossing points of the waveform to calculate the frequency, but when the harmonics are severe, the zero-crossing detection is inaccurate and the frequency measurement is inaccurate. come error. The interpolation cycle method performs inte...

AI Technical Summary

Problems solved by technology

[0003] The frequency measurement method has the zero-crossing method, which detects the time interval between two zero-crossing points of the waveform to calculate the frequency, but when the harmonics are severe, the zero-crossing detection is inaccurate and the frequency measurement is inaccurate. come error

The interpolation period method performs interpolation processing near the zero-crossing point, which reduces the difficulty of zero-crossing point detection, but the sampling out of sync will lead to linearization errors

The Fourier transform method can be used to measure both frequency and harmonics, but this method needs to obtain a period of data before calculation, the real-time performance is not good, and there are problems caused by the sampling period and the waveform period are not strictly synchronized. The Problem of Spectrum Leakage and Fence Effects

In the traditional Kalman filter harmonic measurement algorithm, most of the state variables are selected as The magnitude and phase cannot be directly obtained from the state variables, and further calculations are required

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