双碳目标下基于Stackelberg和合作博弈的虚拟电厂双层优化调度

A Two-level Optimization Scheduling of a Virtual Power PlantBased on Stackelberg and Cooperative Game TheoryUnder the Dual Carbon Goals

在中国的双碳目标下,大规模新能源发电接入虚拟电厂时,将导致电力市场交易中的高额惩罚成本。为此,设计了虚拟电厂参与日前市场竞标的双层博弈模型,以双层收益最大化为目标对虚拟电厂进行调度优化。首先,利用场景生成与削减技术考虑风力发电商和电动汽车聚合商的不确定性,设计了由风力发电商、电动汽车聚合商和燃气轮机合作组成的虚拟电厂下层电量竞标模型,以及虚拟电厂控制中心的上层电价竞标模型。其次,基于两个子模型之间的主从递阶关系,利用卡罗需库-恩塔-克(KKT)条件将双层模型转化为一个混合互补问题,通过求解获得优化方案,并基于Shapley值法对合作方进行利润分配。数值算例表明,设计的模型能有效减少碳排放和降低风电惩罚成本,同时增加参与者的收益。

Under the dual carbon goals in China,the large-scale integration of new energy power generation into the virtual power plant(VPP)will lead to high penalty costs in electricity market transactions.A two-level game model for VPP participating in day-ahead market bidding was designed,with the objective of maximizing two-level benefits through scheduling optimization of VPP.Firstly,considering the uncertainty of wind power plants(WPP)and electric vehicle aggregator(EVA)using scenario generation and reduction techniques,a lower-level electricity bidding model composed of WPP,EVA,and gas turbine(GT)cooperation was designed,along with an upper-level electricity price bidding model for the VPP operator.Secondly,based on the hierarchical relationship between the two sub-models,the two-level model was transformed into a mixed complementarity problem(MCP)using the Karush-Kuhn-Tucker(KKT)conditions,and an optimal solution was obtained.Profit allocation for the cooperative parties was conducted using the Shapley value method.Numerical examples show that the designed model can effectively reduce carbon emissions and wind power penalty costs,while increasing participant benefits.