Real-time pricing for smart grid with distributed energy and storage: A noncooperative game method considering spatially and temporally coupled constraints

With increasing distributed energy (DE) and storage devices integrated into power market, energy provision is becoming more complicated. The real-time pricing (RTP) is an ideal method for smart grid to balance real-time demand and shift peak-hour load. In this paper, we focus on the smart grid with integration of DE and storage devices and formulate the related RTP as a noncooperative game. In this model, both spatially and temporally coupled constraints, which couple the energy demand of all users and over all time slots, are taken into account. In addition, satisfaction maximization and cost minimization are equally considered, and DE is assumed to be kept for the user's own use or to be sold to the smart grid. The existence of the optimal strategies in the non-cooperative game are analyzed and an online distributed algorithm is further proposed to obtain the Nash equilibrium by dual decomposition. With this approach, each user can schedule the optimal energy consumption, generation and/or storage strategies while preserving the privacies of the users and the provider. Numerical results illustrate that the RTP strategy can effectively reduce peak load, balance supply and demand and enhance the welfare of each user.