Title :
Widely linear state space models for frequency estimation in unbalanced three-phase systems
Author :
Dini, Dahir H. ; Xia, Yili ; Douglas, Scott C. ; Mandic, Danilo P.
Author_Institution :
Dept. of Electr. & Electron. Eng., Imperial Coll. London, London, UK
Abstract :
A novel technique for the online frequency estimation of three-phase power systems using the widely linear (augmented) complex least mean square (ACLMS) algorithm has recently been proposed, and was shown to achieve significantly better estimates than conventional complex least mean square (CLMS) algorithm based frequency estimation under unbalanced system conditions. In this paper, we consider the frequency estimation problem from the state space point of view, and show that the augmented complex Kalman filter (ACKF) offers significantly better performance than ACLMS.
Keywords :
Kalman filters; frequency estimation; least mean squares methods; ACKF; ACLMS; augmented complex Kalman filter; augmented complex least mean square algorithm; online frequency estimation; unbalanced three-phase systems; widely linear state space models; Algorithm design and analysis; Covariance matrix; Frequency estimation; Kalman filters; Power systems; Time frequency analysis; Vectors; Complex Kalman filter; complex circularity; frequency estimation; smart grid; widely linear model;
Conference_Titel :
Sensor Array and Multichannel Signal Processing Workshop (SAM), 2012 IEEE 7th
Conference_Location :
Hoboken, NJ
Print_ISBN :
978-1-4673-1070-3
DOI :
10.1109/SAM.2012.6250572
