MEMS Seminar: Iterative Mechanisms for Electricity Markets
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Wednesday, September 14, 2016 - 12:00pm to 1:00pm
Professor Alfredo Garcia, University of Florida
We consider the problem of designing the rules by which dispatch and payment to electricity market participants are gradually adjusted while taking into account network and reliability constraints so as to ensure the market clears with an efficient outcome. Small adjustments (which require minimal information from market participants at each iteration) facilitate the identification of incentives for ensuring truthful reporting of private information. We propose a class of iterative mechanisms and show this class exhibits many desirable properties: incentive compatibility, efficiency, individual rationality and (weak) budget balance. We also analyze an iterative mechanism for stochastic market clearing, a pressing need given the increasing penetration of highly intermittent renewable generation technologies. In this case, the marginal cost of adjustments may only be estimated with some error. We show that truthful reporting is a Nash equilibrium and the resulting dispatch converges almost surely to the efficient dispatch.
Alfredo Garcia is Professor with the Department of Industrial and Systems Engineering at the University of Florida. He received an undergraduate
degree in Electrical Engineering from the Universidad de los Andes, Colombia, in 1991, the Diplome d'Etudes Approfondies D.E.A. in Control
Systems from the Université Paul Sabatier, Toulouse, France, in 1992, and the Ph.D. degree in Operations Research from the University of Michigan, Ann
Arbor, in 1997. During 1998-2000 he served as Commissioner in the Colombian Energy Regulatory Commission. From 2001-2015 he was a member of the faculty at the University of Virginia. His research interests include game theory and dynamic optimization with applications in power and communication networks. He currently manages the program in "Control of Networked Multi-agent Systems" for ARO.
Lunch will be available at 11:30 am.