Widely Linear State Space Models for Frequency Estimation in Unbalanced Three-Phase Systems

被引：0

作者：

Dini, Dahir H. ^{[1
]}

Xia, Yili ^{[1
]}

Douglas, Scott C. ^{[2
]}

Mandic, Danilo P. ^{[1
]}

机构：

[1] Univ London Imperial Coll Sci Technol & Med, Dept Elect & Elect Engn, Exhibit Rd, London SW7 2BT, England

[2] So Methodist Univ, Dept Elect Engn, Dallas, TX 75275 USA

来源：

2012 IEEE 7TH SENSOR ARRAY AND MULTICHANNEL SIGNAL PROCESSING WORKSHOP (SAM) | 2012年

基金：

英国工程与自然科学研究理事会;

关键词：

Complex Kalman filter; widely linear model; complex circularity; frequency estimation; smart grid;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

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.

引用

页码：9 / 12

页数：4

共 8 条

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