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Computational intelligence applications to crisis management in power systems


Negnevitsky, M, Computational intelligence applications to crisis management in power systems, Proceedings of the SAI Intelligent Systems Conference 2016, 21-22 Spetember 2016, London, UK, pp. 1-2. ISBN 978-1-5090-1121-6 (2016) [Refereed Conference Paper]


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Copyright 2016 IEEE


In emergency and abnormal conditions, a power system operator has to deal with a large amount of data and apply most appropriate remedial actions. However, due to emotional and psychological stress, an operator may not be able to adequately respond to critical conditions and make correct decisions. Mistakes can damage very expensive power system equipment or worse lead to major emergencies and catastrophic situations. Intelligent systems can play an advisory role suggesting the necessary actions, which should be taken to deal with a given emergency or abnormal condition as well as identifying failures of protection systems and circuit breakers. This paper outlines some experience obtained at the School of Engineering of the University of Tasmania in developing intelligent systems for power systems security. An expert system for clearing overloads applies the network sensitivity factors to determine appropriate actions, which include generation rescheduling, network reconfiguration and load shedding. An expert system for voltage control is developed and used for detecting voltage violations and providing a set of effective control actions to solve voltage problems in real-time. An artificial neural network is used to identify multiple failures of protection relays and circuit breakers. This system uses information received from protection systems in the form of alarms and is able to deal with incomplete and distorted data.

Item Details

Item Type:Refereed Conference Paper
Keywords:computational intelligence, power system, emergency condition, crisis management
Research Division:Engineering
Research Group:Electrical engineering
Research Field:Electrical energy generation (incl. renewables, excl. photovoltaics)
Objective Division:Energy
Objective Group:Energy storage, distribution and supply
Objective Field:Energy services and utilities
UTAS Author:Negnevitsky, M (Professor Michael Negnevitsky)
ID Code:114458
Year Published:2016
Deposited By:Engineering
Deposited On:2017-02-15
Last Modified:2017-11-02
Downloads:169 View Download Statistics

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