Energy Trading in the Smart Grid: A Distributed Game-Theoretic Approach

In this paper, we propose both a centralized solution and a distributed game-theoretic approach to solve the problem of energy trading in the smart grid. In particular, we consider a number of geographically distributed consumers that need to buy energy from the neighboring users who have a surplus stored energy to meet their local demands. While buyers minimize their energy bill by buying energy at prices lower than that of the grid, sellers can make pro?t by selling the extra stored energy, which could have been acquired from affordable renewable resources. Buying energy from neighboring users also helps in reducing the stress on the main grid, which decreases electricity prices and protects the environment. We ?rst formulate the energy trading problem as a centralized optimization problem. Then, we propose a distributed solution based on the game theory that requires each user to merely apply its best response strategy to the current state of the system. Buyers play the game by deciding how much energy to be bought from each seller in order to minimize their energy bill taking into account different constraints tied to the grid infrastructure. Extensive simulations con?rm the effectiveness of the proposed approach in terms of energy bill savings, convergence in acceptable times, and fairness to its users.