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Research on strategic interactions and evolution mechanisms of multi-agents in power systems from a policy mix perspective

Author

Listed:
  • An, Binghui
  • Wang, Jingyi
  • Xu, Hua
  • Wang, Minggang

Abstract

Driven by the "double carbon" goal, the energy transformation of the power industry confronts the dual challenges of inadequate coordination of policy tools and an absence of a subject game mechanism. This paper constructs a tripartite evolutionary game model involving the government, the traditional energy power generation system (TPG), and the hybrid energy power generation system (HPG). It innovatively introduces the tradable green certificate (TGC) and a carbon tax mechanism within the framework of the renewable energy quota policy (REQ) and the renewable energy subsidy policy (RES). By establishing a multi-dimensional policy integration mechanism, the synergistic driving effect of different policy combinations on energy transformation is revealed. The theoretical analysis deduces the income function of each game subject under eight strategy combinations and obtains the replication dynamics equation of three participants. Based on Lyapunov's first law, the stability of the equilibrium point is analyzed, and two stable equilibrium points are obtained. Numerical simulation verifies the evolution path of strategy implementation in different scenarios. The influence of the initial quota obligation, the penalty coefficient of TPG, the reward and punishment coefficient of HPG, the unit subsidy, the TGC price, and the carbon price, etc. single policy implementations on the stable state of system evolution is systematically analyzed. The change of system evolution stable state under the synergistic effect of multiple policy combinations is analyzed. The study finds that the dual policy integration of TGC and a carbon tax can effectively enhance the regulatory effectiveness of REQ, and the revenue from the carbon tax can help offset the fiscal gap caused by RES. The net income of government policy has a significant threshold effect on supervision, and the dynamic punishment mechanism based on TGC price linkage can effectively curb the opportunistic behavior of HPG.

Suggested Citation

  • An, Binghui & Wang, Jingyi & Xu, Hua & Wang, Minggang, 2025. "Research on strategic interactions and evolution mechanisms of multi-agents in power systems from a policy mix perspective," Energy, Elsevier, vol. 335(C).
    • Handle: RePEc:eee:energy:v:335:y:2025:i:c:s0360544225036394
    DOI: 10.1016/j.energy.2025.137997
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