Multi-time Scale Low-Carbon Optimal Scheduling of Virtual Power Plants Considering Stepped Carbon Trading

In order to improve energy utilization efficiency and achieve low-carbon emissions, a multi-time scale optimal scheduling method for virtual power plants in a low-carbon environment has been proposed. Firstly, this paper constructs a virtual power plant containing CCPP-P2G-HFC (Carbon capture power plant, power to gas and hydrogen fuel cell), establishes the mathematical model of CCPP-P2G-HFC, and introduces the stepped carbon trading mechanism. Then, based on the multi-time scale regulation and control architecture of virtual power plants, a multi-time scale scheduling method with the objective functions of minimizing the operating cost and carbon trading cost is put forward. The analysis results show that the method proposed in this paper can effectively reduce the operating cost of virtual power plants while cutting down carbon emissions, thus realizing the coordinated optimization of economy and low-carbon.