An improved real-time pricing algorithm based on utility maximization for smart grid

Real-time price is the most ideal pricing mechanism in power market. Therefore, study on real-time price algorithm has profound theoretical and practical significance in smart grid. In this paper, we propose an improved real-time pricing algorithm to solve the problems of bad convergence and applicable conditions of this existing optimal real-time pricing model based on utility maximization. First, we give analytically the system model in form of an improved utility function. Second, we utilize the gradient projection method to solve the optimization problem. This proposed algorithm can obtain the optimal price and energy consumption levels to maximize the aggregate utility of all subscribers and the energy provider in the system. The proposed algorithm is suitable for the case of large-scale users and has good convergence performance. The simulation results can demonstrate the feasibility and advantage of our proposed algorithm as compared with the traditional algorithm.