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电动汽车代理商参与需求响应的多层博弈竞标模型 被引量:9

Multi-layer game bidding model for electric vehicle aggregators participating in demand response
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摘要 随着电力市场的发展和电动汽车保有量的增加,为电动汽车(EV)用户提供充放电引导服务的电动汽车代理商(EVA)将成为电力市场需求侧的重要组成部分,电网、EVA、EV之间形成比较复杂的利益关联关系。本文提出了一种基于需求侧充放电竞标的EV调度多层博弈模型,以EVA需求响应为核心,构建EV用户自主选择EVA的演化博弈模型、EVA与EV之间的主从博弈模型以及不同EVA在日前市场竞争的非合作博弈模型,分析了各自之间的效用函数及条件约束,结合各自特点设计了相应的均衡解求解算法。算例分析表明该方法能有效协调电网、EVA及EV之间的互动收益,降低调度成本。 With the development of the power market and the increase in the number of electric vehicles,EVAs( electric vehicle aggregators),which provide charging and discharging guidance services for EV( electric vehicle) users,will become an important part of the demand side of the power market,including the power grid,EVA,and EV. A more complex relationship of interests is formed. This paper proposes a multi-layer game model of EV scheduling based on demand side charging and discharging competitive bid. The EVA demand response is taken as the core. With EVA demand response as the core,the evolutionary game model of EVA self-selected EVA,the leaderfollower game model between EVA and EV,and the non-cooperative game model of different EVA competition in the market are established. The utility function and conditional constraints between them are analyzed,and the corresponding equilibrium solution algorithm is designed according to their respective characteristics. The example analysis shows that the method can effectively coordinate the interaction income between grid,EVA and EV,and reduce the scheduling cost.
作者 程宏波 罗通 康琛 田旭 郭源曦 王勋 CHENG Hong-bo;LUO Tong;KANG Chen;TIAN Xu;GUO Yuan-xi;WANG Xun(School of Electrical and Automation Engineering,East China Jiaotong University,Nanchang 330013,China;State Grid Jiangxi Electric Power Co.,Ltd.Electric Power Research Institute,Nanchang 330096,China)
出处 《电工电能新技术》 CSCD 北大核心 2020年第2期46-56,共11页 Advanced Technology of Electrical Engineering and Energy
基金 国家自然科学基金项目(51667008) 江西省杰出青年人才培养项目(20162BCB23046)
关键词 电动汽车 电动汽车代理商 需求响应 主从博弈 非合作博弈 演化博弈 electric vehicle electric vehicle aggregators demand response leader-follower game non-cooperative game evolutionary game
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