Hierarchical Scheduling and Carbon Trading of Multi-Microgrids Considering Dynamic Carbon Emission Factors

Current multi-microgrid scheduling faces dual challenges: static carbon accounting fails to reflect real-time emission intensity, and economic objectives often conflict with carbon reduction. To address this, this paper proposes a hierarchical scheduling framework integrating dynamic carbon emission factors and tiered carbon trading. The dynamic factors enable real-time carbon tracking, while the tiered mechanism imposes progressive penalties for excess emissions. A bi-level optimization model is developed: the upper-level system operator maximizes profit via price arbitrage, while lower-level microgrids minimize operational costs by optimizing dispatch (gas turbines, renewables, storage, demand response). The results demonstrate that the demand response (DR) mechanism effectively reduces microgrid operating costs. For instance, in Scenario 3 with DR implementation, the microgrid operating cost (118.38 × 103 CNY) shows a significant decrease compared to Scenario 2 (123.81 × 103 CNY) without this mechanism. However, while reducing microgrid costs, DR is accompanied by a reduction in operator revenue, which drops from 6.16 × 103 CNY in Scenario 1 to 2.91 × 103 CNY in Scenario 4. Furthermore, the carbon trading mechanism significantly impacts microgrid carbon emissions. Carbon pricing directly influences microgrid decision-making by altering resource dispatch priorities, thereby affecting carbon costs.