Robust principal component analysis-based coherency identification of generators with missing PMU measurements

被引：2

作者：

Qing, Xiangyun ^{[1
]}

Wang, Shaobo ^{[2
]}

Jia, Tinggang ^{[3
]}

Niu, Yugang ^{[1
]}

机构：

[1] E China Univ Sci & Technol, Sch Informat Sci & Engn, 130 Meilong Rd, Shanghai 200237, Peoples R China

[2] Shanghai Elect Grp Co Ltd, Shanghai 200081, Peoples R China

[3] Shanghai Elect Grp Co Ltd, Cent Acad, Shanghai 200081, Peoples R China

来源：

IEEJ TRANSACTIONS ON ELECTRICAL AND ELECTRONIC ENGINEERING | 2016年 / 11卷 / 01期

关键词：

coherency identification; robust principal component analysis; hierarchical clustering; power system; data-driven;

D O I：

10.1002/tee.22186

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：

This study provides a new algorithm for grouping coherent generators in power systems using robust principal component analysis. In coherency identification of generators based on measurements by a phasor measurement unit (PMU), PMU measurements can become unavailable because of unexpected failure of data acquisition or communication links. However, the proposed algorithm is robust to missing PMU measurements and is demonstrated on an IEEE 16-generator 68-bus system. This effective identification of coherent clusters with missing PMU measurements is validated and compared with results obtained using the principal component analysis and independent component analysis methods. (c) 2015 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

引用

页码：36 / 42

页数：7

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