计及WCVaR评估的微电网供需协同两阶段日前优化调度

Two-stage Day-ahead Optimal Microgrid Scheduling with Coordination Between Supply and Demand Considering WCVaR Assessment

针对微电网自治程度较高且存在新能源出力不确定的问题,从并网型微电网运营商的角度提出一种供需协同两阶段日前优化调度框架。首先建立供需协同调度的主从Stackelberg博弈双层优化模型,其中上层运营商问题包含日前调度和实时调控2个阶段,并在实时调控阶段引入最差条件风险价值评估新能源不确定性造成的最恶劣调控成本风险;下层用户综合考虑电费支出和用电满意度问题。然后采用KKT(Karush-Kuhn-Tucker)条件、Big-M法以及线性规划强对偶理论将模型转化为混合整数线性规划问题。算例分析表明,所提模型可以决策新能源出力最恶劣概率分布下的最优日前调度方案,同时协同优化电价政策和负荷曲线,降低系统运营成本和风险。

In view of the high degree of autonomy of the microgrid and the uncertainty of renewable energy output,this paper proposes a two-stage day-ahead optimal scheduling framework of coordination between supply and demand from the perspective of grid-connected microgrid operators.First of all,a bi-level optimization model of supply and demand collaborative scheduling is established based on the master-slave Stackelberg game.The upper operator’s problem includes two stages:day-ahead scheduling and real-time control.In the real-time control stage,the worst-case conditional value at risk(WCVaR)is utilized to assess the cost risk caused by the uncertainty of renewable energy resources in the worst-case scenario.Then the Karush-Kuhn-Tucker condition,the Big-M method and strong duality theory of linear programming are used to transform the bi-level optimization problem into a mixed-integer linear programming problem.Case analysis indicates that the proposed model can decide the optimal day-ahead scheduling scheme under the worst-case probability distribution of renewable energy output,simultaneously optimize the electricity price and load curve,and reduce the system operation cost and risk.