Optimized Support Vector Machine & Wavelet Transform for Distribution Grid Fault Location

被引：22

作者：

Shafiullah, Md ^{[1
]}

Ijaz, Muhammad ^{[1
]}

Abido, M. A. ^{[1
]}

Al-Hamouz, Z. ^{[1
]}

机构：

[1] King Fahd Univ Petr & Minerals, Dept Elect Engn, Dhahran, Saudi Arabia

来源：

2017 11TH IEEE INTERNATIONAL CONFERENCE ON COMPATIBILITY, POWER ELECTRONICS AND POWER ENGINEERING (CPE-POWERENG) | 2017年

关键词：

Backtracking Search Algorithm; Distribution Grid; Fault Location; Support Vector Machine; Wavelet Transform; Statistical Measures;

D O I：

10.1109/CPE.2017.7915148

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

The precise knowledge of fault locations is very important as longer period interruption caused by faults are responsible for most of the customer minute losses in the distribution grid. The objective of this paper is to locate different types of faults in a distribution grid by extracting the features of three phase fault currents employing wavelet transform (WT) and feeding the statistical measures of the extracted features as inputs of optimized support vector machine (SVM). Backtracking search algorithm is employed to optimize the parameters of the SVM. Finally, the results of the proposed model are compared with the results of a general/non-optimized support vector machine to validate the efficacy of the proposed model.

引用

页码：77 / 82

页数：6

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