Demand side management to reduce Peak-to-Average Ratio using game theory in smart grid

In this paper, we propose a novel demand side management technique to reduce the peak load of the system. We consider a smart power system with distributed users that request their energy demands to an energy provider and the energy provider dynamically updates the energy prices based on the load profiles of the users. The users try to minimize the Peak-to-Average Ratio (PAR) of the power system by charging for their batteries at low-demand periods and discharging the energy at high-demand periods. We also propose a distributed demand side management algorithm using a game theoretical approach in which each user tries to minimize its total energy cost. In simulation results, we show that the proposed algorithm will simultaneously minimize the PAR and the total energy cost.