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Transactions: WSEAS TRANSACTIONS ON POWER SYSTEMS
Transactions ID Number: 32-685
Full Name: Ahmed Haidar
Position: Doctor (Researcher)
Age: ON
Sex: Male
Address: UMP - Lebuhraya Tun Razak, 26300 Kuantan, Pahang, Malaysia
Country: MALAYSIA
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E-mail address: ahaidar67@yahoo.com
Other E-mails: ahmedm@ump.edu.my
Title of the Paper: An Application of Generalized Regression Neural Networks To Transient Stability Evaluation
Authors as they appear in the Paper: Ahmed M. A. Haidar, M.W. Mustafa, Norazila Jaalam, R. Abdullah, M. R. Ahmad, N. M. Saad
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Number of paper pages: 10
Abstract: Transient Stability Analysis is part of dynamic security assessment of power systems which involves the evaluation of the ability of a power system to remain in equilibrium under severe but credible contingencies. A transient stability index is described for the dynamic security evaluation of electric power systems by providing a measure for their level of security. In this paper, transient stability analysis aims to assess the dynamic behaviour of a power system in a fast and accurate way. In the proposed method transient stability of a power system is first determined based on the generator relative rotor angles index obtained from the time domain simulation outputs. A technique for constructing this index is developed applying the principles of generalized regression neural network while the stability determination is based on the initial fault-on accelerations of machine rotors. For illustrative purposes, the technique developed is applied to a 9-bus IEEE test !
system. Some numerical results are presented
Keywords: Power system, Transient stability, Neural network & Generalized regression
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