Planning for Deregulation of the Illinois Electric Power Market Using Agent-Based Modeling   . . . Abstract and Biography Charles Macal, Argonne National Laboratory     2:00 PM, Grier Room, Room 34-401B LIDS Colloquium -   There will be a short reception at 1:30PM on the 6th floor of the Dreyfoos tower in the Stata Center

Abstract and Biography

Abstract: A novel agent-based modeling approach is used to simulate the Illinois electric power grid and restructured power market under conditions of deregulation. The agent-based approach can capture the complex interactions between the physical infrastructure, that is, generation, transmission, and distribution infrastructure, and the economic behavior of market participants. The elements of the transmission grid (generators, buses, load centers, etc.) are represented in detail and power market operations are simulated on an hourly basis. A DC optimal power flow model is calibrated with an AC representation and directly interacts with the agent-based economic model. Market participants or “agents” are individually represented with unique business and bidding strategies, risk preferences, objectives, and decision rules. The success of an agent is a function not only of its own decisions and actions, but also of the decisions and actions of the other market participants. Since market rules restrict the local information shared among participants, agent decisions are made without perfect knowledge or certainty. Market agents learn from past experience and adapt their behaviors, such as bidding into pool markets, to improve their positions. At the request of regulators in preparing for deregulation of the Illinois electric power market, the model was used to investigate the potential for individual agents to exercise market power in terms of unilaterally raising electricity prices. The application of the model demonstrated the need for market monitors and making real-time information available to consumers.

Biography: Charles Macal is Senior Systems Engineer and Director of the Complex Adaptive Systems Group at Argonne National Laboratory. He applies computational modeling and simulation tools to complex systems in a variety of fields, including energy, national security and defense. He is a principal investigator for the development of the widely used Repast agent-based modeling tookit. Dr. Macal serves on the editorial boards of the ACM Transactions on Modeling and Simulation and the journal Simulation, and he has co-authored a book, Managing Business Complexity: Discovering Strategic Solutions with Agent-Based Modeling and Simulation, published in 2007 by Oxford Press. He is Adjunct Professor at The University of Chicago, where he teaches courses on complex adaptive systems for threat management and emergency preparedness. Dr. Macal received a Ph.D. in Industrial Engineering & Management Sciences from Northwestern University and holds an M.S. in Industrial Engineering and a B.S. in Engineering Sciences from Purdue University. He is a registered professional engineer in the State of Illinois and is a member of the Association for Computing Machinery (ACM), Institute of Electrical and Electronics Engineers (IEEE), Society for Computer Simulation International (SCSI), the Institute for Operations Research and the Management Sciences (INFORMS), and Systems Dynamics Society (SDS).