A hybrid demand response mechanism based on real-time incentive and real-time pricing. (15th September 2021) - Xu, Bo; Wang, Jiexin; Guo, Mengyuan; Lu, Jiayu; Li, Gehui; Han, Liang
Abstract: This paper proposes a hybrid demand response (DR) mechanism considering three types of participants: power grid operator (PGO), retailers and end users. Different from the traditional price-based or incentive-based methods, this hybrid mechanism combines real-time pricing and real-time incentive together to implement demand response programs dispatched by PGO, i.e., the PGO provides incentives to retailers and the retailers set optimal real-time prices to users every 5 min. This hybrid DR mechanism can better motivate retailers to participate by providing them with monetary incentives from PGO for load shifting. We use a three-level Stackelberg game to model the proposed mechanism. The PGO first determines the optimal incentive rate to minimize its cost, then the retailers decide the optimal electricity price to maximize their profits, and the users finally choose the optimal power demand to maximize their welfare. The analytical solutions of the optimal decisions for every participant are given. We also propose a distributed algorithm to implement this mechanism in a practical application by considering information asymmetry. The simulation results verify its advantages over traditional demand response mechanisms. Highlights: A novel hybrid demand response (DR) mechanism combining real-time pricing and real-time incentive is proposed. The hybrid DR mechanism is modeled by a three-level Stackelberg game. The existence and uniqueness of the solution at game equilibrium is proved and analyzed. A distributed algorithm is proposed to implement hybrid DR under information asymmetry. The benefits of the power grid, retailers and users are improved under hybrid DR.