Title :
Recursive total least-squares estimation of frequency in three-phase power systems
Author :
Arablouei, Reza ; Dogancay, Kutluyil ; Werner, Stefan
Author_Institution :
Inst. for Telecommun. Res., Univ. of South Australia, Mawson Lakes, SA, Australia
Abstract :
We propose an adaptive algorithm for estimating the frequency of a three-phase power system from its noisy voltage readings. We consider a second-order autoregressive linear predictive model for the noiseless complex-valued αβ signal of the system to relate the system frequency to the phase voltages. We use this model and the noisy voltage data to calculate a total least-square (TLS) estimate of the system frequency by employing the inverse power method in a recursive manner. Simulation results show that the proposed algorithm, called recursive TLS (RTLS), outperforms the recursive least-squares (RLS) and the bias-compensated RLS (BCRLS) algorithms in estimating the frequency of both balanced and unbalanced three-phase power systems. Unlike BCRLS, RTLS does not require the prior knowledge of the noise variance.
Keywords :
adaptive signal processing; autoregressive processes; frequency estimation; inverse problems; power grids; regression analysis; adaptive algorithm; adaptive signal processing; balanced three-phase power systems; electric power grids; inverse power method; noiseless complex-valued αβ signal; noisy voltage readings; phase voltages; recursive TLS; recursive total least-squares frequency estimation; second-order autoregressive linear predictive model; unbalanced three-phase power systems; Estimation; Frequency estimation; Noise measurement; Power systems; Signal to noise ratio; Steady-state; Adaptive signal processing; frequency estimation; inverse power method; linear predictive modeling; total least-squares;
Conference_Titel :
Signal Processing Conference (EUSIPCO), 2014 Proceedings of the 22nd European
Conference_Location :
Lisbon