JACIII Vol.18 No.5 pp. 714-727
doi: 10.20965/jaciii.2014.p0714


Preventing Large-Scale Emergencies in Modern Power Systems: AI Approach

Michael Negnevitsky*, Nikita V. Tomin**, and Christian Rehtanz***

*School of Engineering, University of Tasmania, Private Bag 65, Hobart, Australia

**Department of Electric Power System, Melentiev Energy Systems Institute, 130 Lermontov Str., Irkutsk 664033, Russia

***Energy Systems, Energy Efficiency and Energy Economics, TU Dortmund University, Emil-Figge-Strasse 70, Dortmund 44221, Germany

October 3, 2013
March 13, 2014
September 20, 2014
power system, emergency condition, computational intelligence, disaster management
In recent years, due to liberalization, power systems are being operated closer and closer to their limits. At the same time, they have increased in size and complexity. Both factors increase the risk of major power outages and blackouts. In emergency and abnormal conditions, a power system operator has to deal with large amounts of data. However, due to emotional and psychological stress, an operatormay not be able to respond to critical conditions adequately and make correct decisions promptly. Mistakes can damage very expensive power system equipment or worse lead to major emergencies and catastrophic situations. Intelligent systems can play an important role by alarming the operator and suggesting the necessary actions to be taken to deal with a given emergency. This paper outlines some experience obtained at the University of Tasmania, Australia, Energy Systems Institute, Russia and TU-Dortmund University, Germany in developing intelligent systems for preventing large-scale emergencies and blackouts in modern power systems.
Cite this article as:
M. Negnevitsky, N. Tomin, and C. Rehtanz, “Preventing Large-Scale Emergencies in Modern Power Systems: AI Approach,” J. Adv. Comput. Intell. Intell. Inform., Vol.18 No.5, pp. 714-727, 2014.
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