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Intelligent Agent Approach to the Control of Critical Infrastructure Networks

Authors: James D. Gadze, Niki Pissinou, Kia Makki


In this paper we propose an intelligent agent approach to control the electric power grid at a smaller granularity in order to give it self-healing capabilities. We develop a method using the influence model to transform transmission substations into information processing, analyzing and decision making (intelligent behavior) units. We also develop a wireless communication method to deliver real-time uncorrupted information to an intelligent controller in a power system environment. A combined networking and information theoretic approach is adopted in meeting both the delay and error probability requirements. We use a mobile agent approach in optimizing the achievable information rate vector and in the distribution of rates to users (sensors). We developed the concept and the quantitative tools require in the creation of cooperating semiautonomous subsystems which puts the electric grid on the path towards intelligent and self-healing system.

Keywords: Mobile agent, power system operation and control, real time, wireless communication.

Digital Object Identifier (DOI):

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[1] US - Canada Power System Outage Task Force, "Final Report on the August 14, Blackout in the United States and Canada: Causes and Recommendations," April 5, 2004.
[2] C. Rehtanz, "Autonomous Systems and Intelligent Agents in Power System Control and Operation," Springer - Verlag, NY 2003.
[3] Massoud Amin, "Towards Self-Healing Energy Infrastructure Systems," IEEE Computer Application in Power, January 2001, pp. 20-28.
[4] Massoud Amin, "National Infrastructure as Complex Interactive Networks," In Automation, Control and Complexity: An Integrated Approach. John Wiley & Sons, New York 2000, pp. 263-286.
[5] A.M Wildberger, "Autonomous Adaptive Agents for Distributed Control of the Electric Power Grid in a Competitive Electric Power Industry," Proc. of Knowledge-Based Intelligent Electronic Systems, May 21 - 23, 1997, pp. 2 - 11.
[6] K. Moslehi, A.B. Ranjit Kumar, et al, "Control Approach for Self- Healing Power Systems: A Conceptual Overview," Presented at the Electricity Transmission in Deregulated Markets: Challenges, Opportunities, and Necessary Research and Development, Carnegie Mellon University, Dec 15 - 16 2004.
[7] P. Hines, H. Liao, D. Jia, and S. Talukdar:, "Autonomous Agents and Cooperation for the Control of Cascading Failures in Electric Grids," Proc. of the IEEE Conference on Networking, Sensing and Control, 2005.
[8] C. Asavathiratham, "The Influence Model: A Tractable Representation for the Dynamics of Networked Markov Chains," Ph.D. Thesis, EECS department, MIT, October 2000.
[9] Jie Chen, J.S Thorp, and Ian Dobson, "Cascading Dynamics and Mitigation Assessment in Power System Disturbances via a Hidden Failure Model," International Journal of Electrical Power and Energy Systems, 2003.
[10] S. Tamronglak, A.G Phadke, S.H Horowitz and J.S Thorp, "Anatomy of Power System Blackouts: Preventive Relaying Strategies," IEEE Transactions on Power Delivery 1996, 11(2), pp. 708 - 715.
[11] I.V Basawa, and B.L.S Prakasa, "Probability and Mathematical Statistics: Statistical Inference for Stochastic Processes," Academic Press, NY 1980.
[12] Sheldon M. Ross, "Introduction to Probability Models," Academic Press San Diego, 2004.