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Computational intelligence applications to crisis management in power systems

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Negnevitsky, M (2008) Computational intelligence applications to crisis management in power systems. In: 8th International Conference on Intelligent Technologies, 12-14 December 2007, Sydney, Australia.

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Abstract

In emergency conditions, power system operators deal with large amounts of data. Due to psychological stress, operators may not be able to adequately respond to critical conditions and make correct decisions. Mistakes can damage expensive power system equipment or worse lead to major emergencies. Intelligent systems can play an advisory role suggesting the necessary actions to be taken to deal with a given emergency as well as identifying failures of protection systems and circuit breakers. This paper outlines some experience obtained at the University of Tasmania in developing intelligent systems for power systems security. An expert system for clearing overloads applies the network sensitivity factors to reschedule power generation, reconfigure networks and shed loads. An expert system for voltage control is developed for detecting voltage violations and providing a set of control actions to solve voltage problems. Neural networks are used to identify multiple failures of protection and circuit breakers.

Item Type: Conference or Workshop Item (Paper)
Keywords: computational intelligence; power systems; emergency conditions; crisis management; emergency management; psychological stress; decision making; protection systems; circuit breakers; protection system failure; circuit breaker failure; expert systems; network sensitivity; power generation rescheduling; network reconfiguration; load shedding; voltage control; neural networks; intelligent control; intelligent support.
Journal or Publication Title: International Journal of Automation and Control
Page Range: pp. 247-273
ISSN: 1740-7516
Identification Number - DOI: 10.1504/IJAAC.2008.022180
Additional Information: Copyright © 2007, Eighth International Conference on Intelligent Technologies (InTech 2007). All Rights Reserved
Date Deposited: 07 Apr 2008 14:59
Last Modified: 18 Nov 2014 03:36
URI: http://eprints.utas.edu.au/id/eprint/4819
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