Signal frequency and parameter estimation for power systems using the hierarchical identification principle

Yinni Cao,  and Zhanqiang Liu

[Abstract] Estimating the fundamental frequency and harmonic parameters is basic for signal modelling in a power supply system. This paper presents a gradient based algorithm and a least squares based algorithm to estimate the fundamental frequency, the amplitudes and the phases of harmonic waves according to the voltage/current samples of a power system. Differing from the existing parameter estimation algorithms either for power quality monitoring or for harmonic compensation, the proposed algorithms are based on the hierarchical identification principle and are able to estimate the fundamental frequency, the amplitudes and the phases of harmonic waves simultaneously. In addition, the proposed algorithms are in the recursive form, which is suitable for on-line implementation. The simulation results verify the effectiveness of the proposed algorithms.

Keywords: Signal modelling; Parameter estimation; Least squares; Stochastic gradient; Fundamental frequency estimation

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