Low-Complexity Nonlinear Analysis of Synchrophasor Measurements for Events Detection and Localization

被引:12
|
作者
Liu, Guohong [1 ,2 ]
Chen, Hong [1 ,2 ]
Sun, Xiaoying [2 ]
Quan, Nan [3 ]
Wan, Lei [4 ]
Chen, Rounan [2 ]
机构
[1] Jilin Univ, State Key Lab Automot Simulat & Control, Changchun 130025, Jilin, Peoples R China
[2] Jilin Univ, Coll Commun Engn, Changchun 130025, Jilin, Peoples R China
[3] State Power Econ Res Inst, Beijing 102209, Peoples R China
[4] China Elect Power Res Inst, Beijing 100192, Peoples R China
来源
IEEE ACCESS | 2018年 / 6卷
关键词
Power system; wide-area monitoring; phasor measurement unit; events detection; events localization; Nystrom approximation; kernel principal components analysis; COMPONENT ANALYSIS; TRANSMISSION-LINES; FAULT-DETECTION; PCA; IMPLEMENTATION; ALGORITHMS; REDUCTION; SYSTEMS;
D O I
10.1109/ACCESS.2017.2772287
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper is concerned with the computational efficient nonlinear analysis of phasor measurement unit data and presents a Nystrom principal components analysis-based algorithm for events detection and localization in an electrical power system. Based on the properly chosen sample subset of every moving window data, the Nystrom approximation is carried out to obtain the principal eigenvalues and related eigenvectors of a mapped kernel matrix. Then, the T-2 statistic is constructed to detect the abnormal states of an electrical power system. In addition, the contribution of each variable to the T-2 statistic is derived to determine the location of the fault bus. Compared with the previous works, the novel version proposed in this paper efficiently reduces the computational burden, and accurately locates the fault bus. Computer simulations using both realistic data, collected from the China power system, and simulated voltage and phase-angle data, validate the reliability of the proposed algorithm.
引用
收藏
页码:4982 / 4993
页数:12
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