Low-Carbon Optimal Scheduling of Multi-Microgrid Stackelberg Game Considering Uncertainty
To improve the low-carbon economic operation of multi-microgrid with different stakeholders in the same region,a multi-microgrid Stackelberg game low-carbon optimization method considering wind and solar uncertainty is proposed.Firstly,based on multi-agent technology,an energy interaction model for a multi-microgrid system with multi-microgrid operators as leaders and each microgrid as followers is established.Then,Stackelberg game model based on conditional risk value is established to address the uncertainty of wind and solar energy,considering the operating costs and carbon trading costs of each entity.Finally,the genetic algorithm and CPLEX solver are combined to solve the problem.The results show that this optimization strategy can effectively improve the economic efficiency of each entity,promote the consumption of renewable energy,and reduce carbon emissions.