计及需求响应的虚拟电厂日前市场交易策略研究

Day-ahead Market Trading Strategy of Virtual Power Plant Considering Demand Response

虚拟电厂作为分布式资源的聚合体,可以参与电能量市场与调峰市场交易。提出一种虚拟电厂参与能量与调峰市场的交易策略。首先,构建虚拟电厂参与能量与调峰市场的交易框架。然后,构建了柔性负荷的能量-调峰响应模型,并针对柔性负荷中的可转移负荷提出一种计及峰谷转移偏差的阶梯型补偿需求响应机制,目的在于引导可转移负荷参与需求响应的同时提高虚拟电厂在调峰市场中的收益。最后,构建虚拟电厂与柔性负荷之间的主从博弈模型,采用粒子群算法与Gurobi相结合的方法求解虚拟电厂利润与柔性负荷用电成本的纳什均衡。算例表明,所提需求响应机制能够充分挖掘可转移负荷的响应潜力,并增加虚拟电厂在日前市场中的利润。

Virtual power plant which is the aggregation of distributed energy resources,is capable of engaging in transactions within the energy and peak regulation markets.A trading strategy that enables virtual power plants to actively participate in these markets is proposed.Fiestly,a transaction framework is developed for the virtual power plant participatimg in the energy and peak regulation markets.Then,the energy and peak regulation response model of flexible load is constructed,and a stepped compensation demand response mechanism considering peak-valley transfer deviation is proposed for the transferable load,with the aim of guiding transferable load to participate in demand response while improving the revenue of the virtual power plant in the peak regulation market.Finally,the master-slave game model between the virtual power plant and the flexible load is constructed,and the Nash equilibrium between the profit of the virtual power plant and the electricity cost of the flexible load is solved by the combination of particle swarm optimization and Gurobi.The case study shows that the proposed demand response mechanism can fully tap the response potential of transferable load and increase the profit of virtual power plants in the day-ahead market.