Power quality disturbance identification using wavelet packet energy entropy and weighted support vector machines

被引：81

作者：

Hu, Guo-Sheng ^{[1
,3
]}

Zhu, Feng-Feng ^{[2
]}

Ren, Zhen ^{[1
]}

机构：

[1] Anqing Teachers Coll, Sch Comp & Informat, Anqing 246011, Peoples R China

[2] S China Univ Technol, Sch Math Sci, Guangzhou 51060, Guangdong, Peoples R China

[3] S China Univ Technol, Sch Elect Power, Guangzhou 510640, Guangdong, Peoples R China

来源：

EXPERT SYSTEMS WITH APPLICATIONS | 2008年 / 35卷 / 1-2期

关键词：

weighted support vector machines (WSVMs); power quality; disturbances; classification; wavelet packet energy entropy;

D O I：

10.1016/j.eswa.2007.06.005

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, wavelet packet energy entropy and weighted support vector machines are used to automatically detect and classify power quality (PQ) disturbances. Electric power quality is an aspect of power engineering that has been with Lis since the inception of power systems. The types of concerned disturbances include voltage sags, swells, interruptions. Wavelet packet are utilized to denoise the digital signals, to decompose the signals and then to obtain five common features for the sampling PQ disturbance signals. A weighted support vector machine is designed and trained by 5-dimension feature space points for making it decision regarding the type of the disturbance. Simulation cases illustrate the effectiveness. (C) 2007 Elsevier Ltd. All rights reserved.

引用

页码：143 / 149

页数：7

共 19 条

[1]

BI DQ, 2003, CHINESE J AUTOMATIO, V27, P50

[2]

GEN YL, 2006, CHINESE J SCI INSTRU, V27, P180

[3]

GEN YL, 2006, CHINESE J SCI INSTRU, V27, P217

[4] Electric power quality: Types and measurements [J].

Golkar, MA .

PROCEEDINGS OF THE 2004 IEEE INTERNATIONAL CONFERENCE ON ELECTRIC UTILITY DEREGULATION, RESTRUCTURING AND POWER TECHNOLOGIES, VOLS 1 AND 2, 2004, :317-321

[5]

GUI ZH, 2004, CHINESE J CHINESE AU, V28, P62

[6]

HE YZ, 2001, CHINESE J J VIBRATIO, V14, P72

[7]

He Zheng-you, 2005, Proceedings of the CSEE, V25, P38

[8]

HE ZY, 2004, J CHINESE POWER SYST, V28, P17

[9] Automated classification of power-quality disturbances using SVM and RBF networks [J].

Janik, P ;

Lobos, T .

IEEE TRANSACTIONS ON POWER DELIVERY, 2006, 21 (03) :1663-1669

[10]

Li Shi-ling, 2003, Journal of System Simulation, V15, P76

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