考虑备用服务的电动汽车代理商竞价与定价联合优化  

Joint optimization of bidding and pricing strategy for electric vehicle aggregators considering reserve service

作　　者：杨思渊 姜子卿 艾芊[1] YANG Siyuan;JIANG Ziqing;AI Qian(School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China)

机构地区：[1]上海交通大学电子信息与电气工程学院,上海200240

出　　处：《电力自动化设备》2018年第12期25-32,共8页Electric Power Automation Equipment

基　　金：国家自然科学基金-国家电网联合基金资助项目(U1766207)~~

摘　　要：电动汽车代理商(EVA)的出现有望改善电网与大规模电动汽车的互动用电问题。以EVA为研究对象,分析其运营过程中的购、售电市场行为,提出其参与备用服务市场后的竞价与定价联合优化方法,以提高代理商在参与电网能量交易中的经济收益并降低电动汽车的充电成本。在建立日前能量市场和备用服务市场的统一出清模型的基础上,考虑EVA与车主的主从博弈,建立EVA的竞价与定价策略的双层优化模型,得到EVA在日前市场的最优竞价策略和充电费用的制定策略。通过算例分析表明所提模型的有效性,验证所提策略的经济性和灵活性。The emergence of EVAs(Electric Vehicle Aggregators)is expected to improve the problems on interactive power supply between the power grid and large-scale electric vehicles. The EVAs are taken as the research objects to analyze their market behaviors of electricity purchasing and selling in the operation process. Then the joint optimization method of bidding and pricing strategy considering the participation in the reserve service market is proposed to enhance the economic benefits of the aggregators and reduce the cost of charging fees for electric vehicles. Based on the unified clearing model of the day-ahead energy market and reserve service market and considering the Stackelberg game between the EVAs and the electric vehicle owners, a bi-level optimization model of EVA bidding and pricing strategy is proposed. Consequently, the optimal bidding strategy of EVAs in the day-ahead energy market and the setting strategy of charging fees are obtained. The validity of the proposed model and the economy and flexibility of the proposed strategy are verified by the analysis of an example.

关 键 词：电动汽车 电动汽车代理商 竞价策略 定价策略 双层优化 备用服务 联合优化 

分 类 号：TM761[电气工程—电力系统及自动化] U469.72[机械工程—车辆工程]