Nagabhushana, BS and Chandrasekharaiah, HS (1996) Analysis of SSR Using Artificial Neural Networks. In: International Conference on Intelligent Systems Applications to Power Systems, 1996. ISAP '96, 28 January-2 February, Orlando, 416 -420.
Artificial neural networks (ANNs) are being advantageously applied to power system analysis problems. They possess the ability to establish complicated input-output mappings through a learning process, without any explicit programming. In this paper, an ANN based method for subsynchronous resonance (SSR) analysis is presented. The designed ANN outputs a measure of the possibility of the occurrence of SSR and is fully trained to accommodate the variations of power system parameters over the entire operating range. The effectiveness of this approach is tested by experimenting on the first bench mark model proposed by IEEE Task Force on SSR.
|Item Type:||Conference Paper|
|Additional Information:||Copyright 1990 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.|
|Keywords:||Subsynchronous resonance;Eigen value analysis;Artificial Neural Networks;Natural frequencies|
|Department/Centre:||Division of Electrical Sciences > High Voltage Engineering (merged with EE)|
|Date Deposited:||06 May 2006|
|Last Modified:||19 Sep 2010 04:26|
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