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

fYear

2012

fDate

17-20 June 2012

Firstpage

9

Lastpage

12

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Sensor Array and Multichannel Signal Processing Workshop (SAM), 2012 IEEE 7th

Conference_Location

Hoboken, NJ

ISSN

1551-2282

Print_ISBN

978-1-4673-1070-3

Type

conf

DOI

10.1109/SAM.2012.6250572

Filename

6250572