A subband MUSIC/ESPRIT technique for estimating harmonics in power signals

This paper proposes a subband filtering technique to the MUSIC and the ESPRIT algorithm for the harmonic parameters estimation of power signals. In proposed method, the input power signals are decomposed to the odd harmonics and the even harmonics respectively by designing the filter bank system. The amplitude and the frequency estimation of the decomposed harmonics are carried out using the MUSIC and the ESPRIT method. Subband filtering can reduce the autocorrelation matrix size of input data, and the effect of fundamental component in estimating the parameters. Therefore, this subband technique has advantage in computational cost and estimation accuracy compared to fullband MUSIC and ESPRIT. To demonstrate the performance of the method, computer simulations are performed to the synthesized input signal, and experiment results are compared in subband and fullband cases.

[1]  P.A. Crossley,et al.  Bridging the gap between signal and power , 2009, IEEE Signal Processing Magazine.

[2]  J.J. Tomic,et al.  A New Power System Digital Harmonic Analyzer , 2007, IEEE Transactions on Power Delivery.

[3]  Hun Choi,et al.  Time varying harmonics estimation of power signal based on filter banks and adaptive filtering , 2010, 2010 IEEE Instrumentation & Measurement Technology Conference Proceedings.

[4]  Irene Yu-Hua Gu,et al.  Signal processing of power quality disturbances , 2006 .

[5]  Y. Z. Liu A wavelet based model for on-line tracking of power system harmonics using Kalman filtering , 2001, 2001 Power Engineering Society Summer Meeting. Conference Proceedings (Cat. No.01CH37262).

[6]  S. Chen A Wavelet Based Model for On-line Tracking of Power System Harmonics using Kalman Filtering , 2001 .