Optimized support vector machine & wavelet transform for distribution grid fault location

Md Shafiullah; Muhammad Ijaz; M. A. Abido; Z. Al-Hamouz

doi:10.1109/CPE.2017.7915148

Optimized support vector machine & wavelet transform for distribution grid fault location

Md Shafiullah
, Muhammad Ijaz
, M. A. Abido
, Z. Al-Hamouz

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

31 Scopus citations

Abstract

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.

Original language	English
Title of host publication	2017 11th IEEE International Conference on Compatibility, Power Electronics and Power Engineering, CPE-POWERENG 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	77-82
Number of pages	6
ISBN (Electronic)	9781509049639
DOIs	https://doi.org/10.1109/CPE.2017.7915148
State	Published - 28 Apr 2017

Publication series

Name	2017 11th IEEE International Conference on Compatibility, Power Electronics and Power Engineering, CPE-POWERENG 2017

Bibliographical note

Publisher Copyright:
© 2017 IEEE.

Keywords

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

ASJC Scopus subject areas

Electrical and Electronic Engineering
Energy Engineering and Power Technology

Access to Document

10.1109/CPE.2017.7915148

Cite this

Shafiullah, M., Ijaz, M., Abido, M. A., & Al-Hamouz, Z. (2017). Optimized support vector machine & wavelet transform for distribution grid fault location. In 2017 11th IEEE International Conference on Compatibility, Power Electronics and Power Engineering, CPE-POWERENG 2017 (pp. 77-82). Article 7915148 (2017 11th IEEE International Conference on Compatibility, Power Electronics and Power Engineering, CPE-POWERENG 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CPE.2017.7915148

Shafiullah, Md ; Ijaz, Muhammad ; Abido, M. A. et al. / Optimized support vector machine & wavelet transform for distribution grid fault location. 2017 11th IEEE International Conference on Compatibility, Power Electronics and Power Engineering, CPE-POWERENG 2017. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 77-82 (2017 11th IEEE International Conference on Compatibility, Power Electronics and Power Engineering, CPE-POWERENG 2017).

@inproceedings{0f1e88707478478883d933be6db2ddd7,

title = "Optimized support vector machine \& wavelet transform for distribution grid fault location",

abstract = "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.",

keywords = "Backtracking Search Algorithm, Distribution Grid, Fault Location, Statistical Measures, Support Vector Machine, Wavelet Transform",

author = "Md Shafiullah and Muhammad Ijaz and Abido, \{M. A.\} and Z. Al-Hamouz",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.",

year = "2017",

month = apr,

day = "28",

doi = "10.1109/CPE.2017.7915148",

language = "English",

series = "2017 11th IEEE International Conference on Compatibility, Power Electronics and Power Engineering, CPE-POWERENG 2017",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "77--82",

booktitle = "2017 11th IEEE International Conference on Compatibility, Power Electronics and Power Engineering, CPE-POWERENG 2017",

address = "United States",

}

Shafiullah, M, Ijaz, M, Abido, MA & Al-Hamouz, Z 2017, Optimized support vector machine & wavelet transform for distribution grid fault location. in 2017 11th IEEE International Conference on Compatibility, Power Electronics and Power Engineering, CPE-POWERENG 2017., 7915148, 2017 11th IEEE International Conference on Compatibility, Power Electronics and Power Engineering, CPE-POWERENG 2017, Institute of Electrical and Electronics Engineers Inc., pp. 77-82. https://doi.org/10.1109/CPE.2017.7915148

Optimized support vector machine & wavelet transform for distribution grid fault location. / Shafiullah, Md; Ijaz, Muhammad; Abido, M. A. et al.
2017 11th IEEE International Conference on Compatibility, Power Electronics and Power Engineering, CPE-POWERENG 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 77-82 7915148 (2017 11th IEEE International Conference on Compatibility, Power Electronics and Power Engineering, CPE-POWERENG 2017).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Optimized support vector machine & wavelet transform for distribution grid fault location

AU - Shafiullah, Md

AU - Ijaz, Muhammad

AU - Abido, M. A.

AU - Al-Hamouz, Z.

PY - 2017/4/28

Y1 - 2017/4/28

N2 - 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.

AB - 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.

KW - Backtracking Search Algorithm

KW - Distribution Grid

KW - Fault Location

KW - Statistical Measures

KW - Support Vector Machine

KW - Wavelet Transform

UR - https://www.scopus.com/pages/publications/85019601713

U2 - 10.1109/CPE.2017.7915148

DO - 10.1109/CPE.2017.7915148

M3 - Conference contribution

AN - SCOPUS:85019601713

T3 - 2017 11th IEEE International Conference on Compatibility, Power Electronics and Power Engineering, CPE-POWERENG 2017

SP - 77

EP - 82

BT - 2017 11th IEEE International Conference on Compatibility, Power Electronics and Power Engineering, CPE-POWERENG 2017

PB - Institute of Electrical and Electronics Engineers Inc.

ER -

Shafiullah M, Ijaz M, Abido MA, Al-Hamouz Z. Optimized support vector machine & wavelet transform for distribution grid fault location. In 2017 11th IEEE International Conference on Compatibility, Power Electronics and Power Engineering, CPE-POWERENG 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 77-82. 7915148. (2017 11th IEEE International Conference on Compatibility, Power Electronics and Power Engineering, CPE-POWERENG 2017). doi: 10.1109/CPE.2017.7915148

Optimized support vector machine & wavelet transform for distribution grid fault location

Abstract

Publication series

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

Fingerprint

Cite this