ON-LINE ESTIMATION OF SYNCHRONIZING AND DAMPING TORQUE COEFFICIENTS USING AN ARTIFICIAL NEURAL NETWORK BASED APPROACH

E. A. ABU-AL-FEILAT; E. M. Aggoune; M. Bettayeb; H. N. AL-DUWAISH

doi:10.1080/07313569708955792

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ON-LINE ESTIMATION OF SYNCHRONIZING AND DAMPING TORQUE COEFFICIENTS USING AN ARTIFICIAL NEURAL NETWORK BASED APPROACH

Journal article

Peer reviewed

ON-LINE ESTIMATION OF SYNCHRONIZING AND DAMPING TORQUE COEFFICIENTS USING AN ARTIFICIAL NEURAL NETWORK BASED APPROACH

E. A. ABU-AL-FEILAT, E. M. Aggoune, M. Bettayeb and H. N. AL-DUWAISH

Electric machines and power systems, Vol.25(9), pp.993-1007

01/10/1997

DOI: https://doi.org/10.1080/07313569708955792

Abstract

dynamic stability

neural networks

synchronizing and damping torques

This paper presents an artificial neural network based on-line approach to assess the dynamic stability of a single machine connected to an infinite bus system. The proposed approach is based on estimating the synchronizing and damping torque coefficients of the synchronous machine from voltage and power on-line measurements. Test results show that the proposed approach is very encouraging for fast evaluation of the dynamic stability.

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Title: ON-LINE ESTIMATION OF SYNCHRONIZING AND DAMPING TORQUE COEFFICIENTS USING AN ARTIFICIAL NEURAL NETWORK BASED APPROACH
Creators - without role: E. A. ABU-AL-FEILAT - King Fahd University of Petroleum and Minerals
E. M. Aggoune - King Fahd University of Petroleum and Minerals
M. Bettayeb - King Fahd University of Petroleum and Minerals
H. N. AL-DUWAISH - King Fahd University of Petroleum and Minerals
Publication Details: Electric machines and power systems, Vol.25(9), pp.993-1007
Publisher: Taylor & Francis Group
Identifiers: 9933829808331
Academic Unit: University of Tabuk; King Fahd University of Petroleum & Minerals
Language: English
Resource Type: Journal article