A novel implementation for generator rotor angle stability prediction using an adaptive artificial neural network application for dynamic security assessment

Citation

Al-Masri, Ahmed Naufal A. and Ab Kadir, Mohd Zainal Abidin and Hizam, Hashim and Mariun, Norman (2013) A novel implementation for generator rotor angle stability prediction using an adaptive artificial neural network application for dynamic security assessment. IEEE Transactions on Power Systems, 28 (3). pp. 2516-2525. ISSN 0885-8950

Abstract

This paper addresses a new approach for predicting the generator rotor angle using an adaptive artificial neural network (AANN) for power system stability. The aim of this work is to predict the stability status for each generator when the system is under a contingency. This is based on the initial condition of an operating point, which is represented by the generator rotor angle at a certain load level. An automatic data generation algorithm is developed for the training and testing process. The proposed method has been successfully tested on the IEEE 9-bus test system and the 87-bus system for Peninsular Malaysia.

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Additional Metadata

Item Type:	Article
Divisions:	Faculty of Engineering
DOI Number:	https://doi.org/10.1109/TPWRS.2013.2247069
Publisher:	IEEE
Keywords:	Artificial neural network (ANN); Contingency analysis; Dynamic security assessment (DSA); Rotor angle stability
Depositing User:	Muizzudin Kaspol
Date Deposited:	23 May 2014 07:30
Last Modified:	06 Jun 2016 07:22
Altmetrics:	http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1109/TPWRS.2013.2247069
URI:	http://psasir.upm.edu.my/id/eprint/28635
Statistic Details:	View Download Statistic

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