This paper proposes a game-theoretic approach to design a distributed real-time electricity pricing mechanism. Our approach is novel in that it guarantees individual rationality, meaning that it provides suppliers and consumers with a guaranteed incentive to participate in the real-time pricing market. Such an incentive is devised by offering a time-varying, situation-dependent subsidy that guarantees that a supplier/consumer profits by switching from a fixed-price contract to the real-time pricing contract. Although we assume that suppliers and consumers decide supply and demand quantities in a fully distributed manner to maximize their own profit, the proposed mechanism guarantees under moderate conditions that the market converges through an iterative process to a Nash equilibrium that maximizes social welfare. Furthermore, in order to guarantee safe operation of an electrical grid, our pricing mechanism increases stability of load frequency control, and at the same time, achieves supply-demand equilibrium by explicitly taking into account an equality constraint through dual decomposition method. We empirically demonstrate by simulations the individual rationality of the proposed mechanism as well as the convergence to supply-demand equilibrium.

This paper deals with game theoretic real-time pricing method based on dual decomposition and its application to load frequency control of power networks. The proposed pricing method in this study aims to solve the constrained optimization problem consist of each player's utility and social welfare under selfish players. Selfish player's decision is a Nash equilibrium solution considering their own cost functions. We show this method can lead their own decision to social welfare maximization. Finally we show the effectiveness of the proposed methodology for load frequency control by several simulation results.