Iteratively Reweighted Linear Least Squares for Frequency Estimation in Unbalanced Three-phase Power System
Yuan Chen, Weize Sun, Long-Ting Huang, Hing Cheung So
Abstract
Smart grid has attracted increasing attention in the past decade, and one of its common problems is the variation of the nominal frequency (50 or 60 Hz) introduced by harmonics. In this paper, a batch-mode frequency estimator that can accurately obtain the deviation from the nominal frequency is proposed. The signal model, which includes not only the fundamental frequency but also the harmonics, is first defined, and its characteristic is then studied. Employing the linear prediction (LP) property of the model, the deviated frequency is iteratively updated according to the weighted LP errors, to achieve accurate fundamental frequency estimation. Computer simulations indicate that our proposed method is more accurate and reliable than the conventional estimators in the presence of harmonics and amplitude oscillation.
BibTeX
@inproceedings{icassp2019_iterativelyrewei,
title = {Iteratively Reweighted Linear Least Squares for Frequency Estimation in Unbalanced Three-phase Power System},
author = {Yuan Chen and Weize Sun and Long-Ting Huang and Hing Cheung So},
booktitle = {ICASSP 2019},
year = {2019}
}