Power System Analysis: Competitive Markets, Demand Management, and Security
In recent years, the power system has undergone unprecedented changes that have led to the rise of an interactive modern electric system typically known as the smart grid. In this interactive power system, various participants such as generation owners, utility companies, and active customers can compete, cooperate, and exchange information on various levels. Thus, instead of being centrally operated as in traditional power systems, the restructured operation is expected to rely on distributed decisions taken autonomously by its various interacting constituents. Due to their heterogeneous nature, these constituents can possess different objectives which can be at times conflicting and at other times aligned. Consequently, such a distributed operation has introduced various technical challenges at different levels of the power system ranging from energy management to control and security. To meet these challenges, game theory provides a plethora of useful analytical tools for the modeling and analysis of complex distributed decision making in smart power systems.
The goal of this chapter is to provide an overview of the application of game theory to various aspects of the power system including: i) strategic bidding in wholesale electric energy markets, ii) demand-side management mechanisms with special focus on demand response and energy management of electric vehicles, iii) energy exchange and coalition formation between microgrids, and iv) security of the power system as a cyber-physical system presenting a general cyber-physical security framework along with applications to the security of state estimation and automatic generation control. For each one of these applications, first an introduction to the key domain aspects and challenges is presented, followed by appropriate game-theoretic formulations as well as relevant solution concepts and main results.
KeywordsSmart grid Electric energy markets Demand-side management Power system security Energy management Distributed power system operation Dynamic game theory
This work was supported by the US National Science Foundation under Grants ECCS-1549894 and CNS-1446621.
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