A hybrid demand response mechanism based on real-time incentive and real-time pricing

Bo Xu, Jiexin Wang, Mengyuan Guo, Jiayu Lu, Gehui Li and Liang Han

Energy, 2021, vol. 231, issue C

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.

Keywords: Demand response; Real-time pricing; Real-time incentive; Stackelberg game; Smart grid (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (22)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:231:y:2021:i:c:s0360544221011889

DOI: 10.1016/j.energy.2021.120940

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