Visible to the public Game-Theoretic Methods for Distributed Management of Energy Resources in the Smart GridConflict Detection Enabled

TitleGame-Theoretic Methods for Distributed Management of Energy Resources in the Smart Grid
Publication TypePresentation
Year of Publication2012
AuthorsQuanyan Zhu, University of Illinois at Urbana-Champaign, Tamer Başar, University of Illinois at Urbana-Champaign
KeywordsNSA SoS Lablets Materials, science of security, Toward a Theory of Resilience in Systems: A Game-Theoretic Approach, UIUC

The smart grid is an ever-growing complex dynamic system with multiple interleaved layers and a large number of interacting components. In this talk, we discuss how game-theoretic tools can be used as an analytical tool to understand strategic interactions at different layers of the system and between different decision-making entities for distributed management of energy resources. We first investigate the issue of integration of renewable energy resources into the power grid. We establish a game-theoretic framework for modeling the strategic behavior of buses that are connected to renewable energy resources, and study the Nash equilibrium solution of distributed power generation at each bus. Our framework uses a cross-layer approach, taking into account the economic factors as well as system stability issues at the physical layer. In the second part of the talk, we discuss the issue of integration of plug-in electric vehicles (PHEVs) for vehicle-to-grid (V2G) transactions on the smart grid. Electric vehicles will be capable of buying and selling energy from smart parking lots in the future. We propose a multi-resolution and multi-layer stochastic differential game framework to study the dynamic decision-making process among PHEVs. We analyze the stochastic game in a large-population regime and account for the multiple types of interactions in the grid. Using these two settings, we demonstrate that game theory is a versatile tool to address many fundamental and emerging issues in the smart grid.


Presented at the Eighth Annual Carnegie Mellon Conference on the Electricity Industry Data-Driven Sustainable Engergy Systems in Pittsburgh, PA, March 12-14, 2012.

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