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

Jianyi Chen, Raj Aggarwal, Y Lu

Research output: Chapter in Book/Report/Conference proceedingChapter

6 Citations (Scopus)

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 languageEnglish
Title of host publication2011 International Conference on Advanced Power System Automation and Protection (APAP), 16-20 October 2011
PublisherIEEE
Pages2374-2379
Number of pages6
Volume3
ISBN (Print)9781424496198
DOIs
Publication statusPublished - Oct 2011

Keywords

  • wavelet transform
  • neural networks
  • phase selection

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    Chen, J., Aggarwal, R., & Lu, Y. (2011). New algorithm for EHV transmission line faulted-phase selection based on wavelet transforms and artificial intelligence. In 2011 International Conference on Advanced Power System Automation and Protection (APAP), 16-20 October 2011 (Vol. 3, pp. 2374-2379). IEEE. https://doi.org/10.1109/APAP.2011.6180825