Intelligent Agent Approach to the Control of Critical Infrastructure Networks
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.
[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. www.nerc.com
[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.
[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. www.nerc.com
[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.
@article{"International Journal of Electrical, Electronic and Communication Sciences:59096", author = "James D. Gadze and Niki Pissinou and Kia Makki", title = "Intelligent Agent Approach to the Control of Critical Infrastructure Networks", abstract = "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.", volume = "2", number = "3", pages = "462-6", }