A neural network-based approach for on-line dynamic stability assessment using synchronizing and damping torque coefficients

  • E. Abu-Al-Feilat*
  • , M. Bettayeb
  • , H. Al-Duwaish
  • , M. Abido
  • , A. Mantawy
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

26 Scopus citations

Abstract

This paper presents an artificial neural network (ANN)-based on-line approach to evaluate the dynamic stability of a single machine infinite bus system. The proposed on-line assessment scheme is based on estimating the synchronizing and damping torque coefficients as dynamic performance indices. The two performance indices are estimated from on-line measurements of the changes in the rotor angle, speed and electromagnetic torque using a three-layer feedforward neural network with back propagation. The results show that the proposed method is very promising and encouraging for fast real-time evaluation of the dynamic performance of power systems.

Original languageEnglish
Pages (from-to)103-110
Number of pages8
JournalElectric Power Systems Research
Volume39
Issue number2
DOIs
StatePublished - Nov 1996

Keywords

  • Dynamic stability
  • Low-frequency electromechanical oscillations
  • Neural networks
  • On-line assessment
  • Synchronizing and damping torques

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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