Optimal carbon quota allocation for power system decarbonization: a two-stage peer-to-peer market framework

Amid the global pursuit of deep decarbonization, effectively harnessing demand-side resources has emerged as a crucial strategy, particularly as end-user consumption is a primary driver of carbon emissions. However, existing demand-side carbon policies often impose a significant financial burden on consumers and struggle to utilize carbon quota resources to achieve effective emission reductions. To address these limitations, this paper proposes a novel two-stage framework for carbon quota allocation to advance the decarbonization of power systems. The first stage introduces an allocation strategy that accounts for the heterogeneous low-carbon potential among different consumers, thereby regulating the supply-demand dynamics of the secondary carbon market. The second stage establishes a peer-to-peer carbon market based on a double-auction mechanism to support efficient and transparent rule-based trading. Within this market, an optimal bidding model is formulated to capture the strategic interactions among participants. To solve this complex optimization problem, an enhanced multi-agent deep deterministic policy gradient algorithm is developed, which incorporates a centralized reward mechanism to improve computational tractability. Finally, case studies validate the effectiveness and superiority of the proposed framework.