Ultra high speed deterministic algorithm for transmission lines disturbance identification based on principal component analysis and Euclidean norm

被引:9
作者
Morales, J. A. [1 ,2 ]
Orduna, E. [1 ]
Rehtanz, C. [3 ]
Cabral, R. J. [4 ]
Bretas, A. S. [4 ]
机构
[1] Univ Nacl San Juan, Inst Energia Elect, Av Lib Gral San Martin Oeste 1109 J5400ARL, San Juan, Argentina
[2] Univ Politecn Salesiana, Carrera Ingn Mecatron, Calle Vieja 12-30 & Elia Liut, Cuenca 010150, Ecuador
[3] TU Dortmund Univ, Inst Energy Syst Energy Efficiency & Energy Econ, Emil Figge Str 70, D-44227 Dortmund, Germany
[4] Univ Fed Rio Grande do Sul, Dept Elect Engn, Av Osvaldo Aranha,103 Room 116, BR-90035190 Porto Alegre, RS, Brazil
关键词
Deterministic algorithm; Undesirable conditions; Ellipsoidal pattern; Euclidean norm; POWER QUALITY EVENTS; OPTIMAL FEATURE-SELECTION; WAVELET TRANSFORM; CLASSIFICATION; TRANSIENTS; EUROPE;
D O I
10.1016/j.ijepes.2016.01.043
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
Protection devices are designed to provide high sensitivity to transients produced by undesirable conditions like lightning stroke, avoiding their operation under all tolerable events like switching operations. The problem of incorrect operation due to transient phenomena can be handled by two means, one is to allow the transients and provide additional logics in the relay, other means is to damp the oscillation from source side. Protection relays' not always must trip or send a trip signal and sometimes, only an alarm is necessary. In this context, this research presents a fast and reliable formulation for transmission lines (TLs) switching operations and lightning strokes detection and identification. The proposed methodology is based on Principal Component Analysis (PCA) and Euclidean Norm (EN); by using PCA it is possible to determine that normal operation signals describe a very well defined Ellipsoidal Pattern (EP). In this manner, by calculating the Euclidean Norm (EN) among Principal Components (PCs) for each sample and the origin of the reference Ellipsoidal Pattern, switching operations and lightning strokes are detected and identified. Test results show that the proposed algorithm presents high success on phenomena detection and identification, presenting a high potential for online applications. (c) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:312 / 324
页数:13
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