New algorithm for EHV transmission line faulted-phase selection based on wavelet transforms and artificial intelligence

Jianyi Chen; Raj Aggarwal; Y Lu

doi:10.1109/APAP.2011.6180825

New algorithm for EHV transmission line faulted-phase selection based on wavelet transforms and artificial intelligence

Jianyi Chen, Raj Aggarwal, Y Lu

Department of Electronic & Electrical Engineering

Research output: Chapter or section in a book/report/conference proceeding › Chapter or section

6 Citations (SciVal)

Abstract

This paper proposes a novel algorithm for EHV transmission line faulted phase selection based on current transients by employing the wavelet transform (WT) and the artificial neural network (ANN) techniques. The WT technique and spectral energy calculation offer an efficient method for feature extraction and the ANN plays an important role for decision making. The system is simulated using EMTP and the proposed faulted phase selection scheme is developed based on MATLAB. All the test results show that the designed algorithm is very suitable for identifying the faulted phase(s) under a wide variety of different system and fault conditions in EHV-transmission lines.

Original language	English
Title of host publication	2011 International Conference on Advanced Power System Automation and Protection (APAP), 16-20 October 2011
Publisher	IEEE
Pages	2374-2379
Number of pages	6
Volume	3
ISBN (Print)	9781424496198
DOIs	https://doi.org/10.1109/APAP.2011.6180825
Publication status	Published - Oct 2011

Keywords

wavelet transform
neural networks
phase selection

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10.1109/APAP.2011.6180825

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New algorithm for EHV transmission line faulted-phase selection based on wavelet transforms and artificial intelligence. / Chen, Jianyi; Aggarwal, Raj; Lu, Y.
2011 International Conference on Advanced Power System Automation and Protection (APAP), 16-20 October 2011. Vol. 3 IEEE, 2011. p. 2374-2379.

Research output: Chapter or section in a book/report/conference proceeding › Chapter or section

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AB - This paper proposes a novel algorithm for EHV transmission line faulted phase selection based on current transients by employing the wavelet transform (WT) and the artificial neural network (ANN) techniques. The WT technique and spectral energy calculation offer an efficient method for feature extraction and the ANN plays an important role for decision making. The system is simulated using EMTP and the proposed faulted phase selection scheme is developed based on MATLAB. All the test results show that the designed algorithm is very suitable for identifying the faulted phase(s) under a wide variety of different system and fault conditions in EHV-transmission lines.

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KW - neural networks

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BT - 2011 International Conference on Advanced Power System Automation and Protection (APAP), 16-20 October 2011

PB - IEEE

ER -

New algorithm for EHV transmission line faulted-phase selection based on wavelet transforms and artificial intelligence

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Keywords

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