Implementation and laboratory test of a fully integrated neural network based protection relay for high voltage transmission lines

R K Aggarwal, J I Lorenzo, A L Orille

Research output: Contribution to conferencePaper

Abstract

This paper presents a novel approach to fault detection, faulted phase selection and direction estimation based on artificial neural networks (ANNs). The main target in this work is to find a relay design that is fast with a detection time independent of fault conditions (i.e. current transformer saturation, dynamic arcing faults, short circuit level and system topology) and that uses only unfiltered voltage and current samples, with the same structure and parameters for each relay location in a network. The neural relay is trained globally using training patterns from more than one relaying position in order to be as generic as possible. The CAD of the ANN-based relay is implemented into a hardware model (a DSP evaluation module plugged into a PC) and tested under laboratory conditions via the real-time digital simulation (RTDS) system.
Original languageEnglish
Pages72-75 Vol.1
Publication statusPublished - 2004
EventDevelopments in Power System Protection, 2004. Eighth IEE International Conference on -
Duration: 1 Jan 2004 → …

Conference

ConferenceDevelopments in Power System Protection, 2004. Eighth IEE International Conference on
Period1/01/04 → …

Keywords

  • real-time digital simulation
  • power transmission faults
  • faulted phase selection
  • neural relay
  • relay protection
  • unfiltered current samples
  • training patterns
  • high-voltage techniques
  • RTDS
  • ANN
  • CAD
  • direction estimation
  • artificial neural network
  • fault detection
  • protection relay
  • unfiltered voltage samples
  • neural nets
  • high voltage transmission lines

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