Research on the Optimal Scheduling of Multi-Microgrid Double-Layer Game Considering Fair Carbon Trading Strategy in the Green Certificate Trading Market

Various micro-grid systems participating in the green certificate trading market have uneven returns due to differences in unit size and carbon emission modes. In order to balance the interests of participants in the green certificate market and reduce market transaction risks, this paper adopts the per unit principle to analyze the substantial variation in carbon emissions of each unit in the power-vehicle-heat-supply network coupling system. It establishes a stepped reward and punishment mechanism based on the deviation between the carbon emissions of different units and the average carbon emissions. Simultaneously, the allocation of China Certified Emission Reduction (CCER) and the volume of green certificate transactions in various micronetworks are dynamically modified based on the carbon quota assigned during equitable carbon trading. The proposed method involves the development of a two-layer optimal scheduling model using the Mixed Integer Chaotic Particle Swarm Optimization algorithm (MICPSO). The upper layer engages in a hybrid strategy that combines the energy price and carbon pricing tactics with the output of the lower unit. The calculation findings indicate that the green certificate trading costs for the power grid and vehicle network are lowered by 3426.32 yuan and 293.41 yuan, respectively, as compared to the traditional stepped carbon trading system. However, the cost of the heat supply network increases by 4318 yuan. This study proposes a fair carbon trading method that can alter the amount of green certificate trading in micro-grid groups based on varying volumes. To enhance the microgrid in accordance with the increased number of new energy units, it is necessary to provide a fair distribution of the environmental advantages of green electricity across microgrids.