Demand response management of smart grid based on Stackelberg-evolutionary joint game

Jun Li, Tao Li, Daoyi Dong

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

We investigated the real-time pricing demand response management system of multiple microgrids and multiple power users. Accordingly, we have proposed a Stackelberg-evolutionary joint game framework to examine the real-time pricing scheme of multiple microgrids and multiple power users so as to establish equilibrium strategies. Both a non-cooperative game among multiple microgrids and a multi-population evolutionary game among multiple power users were considered. Furthermore, we constructed a Stackelberg game between microgrids and power users to reflect their sequential interaction, wherein the microgrids are leaders, and the power users are followers. We also proved the existence and uniqueness of the Stackelberg equilibrium. Furthermore, we proposed an iterative algorithm to compute the equilibrium strategy and demonstrate the convergence and effectiveness through numerical simulations, which demonstrated that the algorithm could achieve a balance between power supply and demand balance.

Original languageEnglish
Article number182201
JournalScience China Information Sciences
Volume66
Issue number8
DOIs
StatePublished - Aug 2023

Keywords

  • Stackelberg game
  • demand response management
  • multi-population evolutionary game
  • real-time pricing
  • smart grid

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