引用本文:戚佳金,尹淑淙,张 良,等.虚拟电厂与电动汽车运营商的主从-演化混合博弈调度方法[J].电力系统保护与控制,2025,53(18):131-141.
QI Jiajin,YIN Shucong,ZHANG Liang,et al.A master-slave evolutionary hybrid game-based scheduling method for virtual power plants and electric vehicle operators[J].Power System Protection and Control,2025,53(18):131-141
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虚拟电厂与电动汽车运营商的主从-演化混合博弈调度方法
戚佳金,尹淑淙,张 良,等
1.杭州电力设备制造有限公司,浙江 杭州 310016;2.现代电力系统仿真控制与绿色电能新技术教育部 重点实验室(东北电力大学),吉林 吉林 132012
摘要:
针对电动汽车需求响应机制下电动汽车多主体的复杂博弈问题,提出一种考虑低碳目标的虚拟电厂与电动汽车运营商的主从-演化混合博弈的调度方法。首先,基于logit协议构建电动汽车充放电调度演化博弈模型。其次,建立虚拟电厂与电动汽车的主从-演化混合博弈模型。虚拟电厂作为领导者制定电价,电动汽车聚合商作为跟随者根据电价确定充放电策略。最后,联合求解纳什均衡和演化均衡,得到各主体最优策略。通过仿真实验,验证所提方法能够在考虑电动汽车用户利益的同时,有效减少电网的碳排放量,降低负荷的峰谷差,实现多主体的合作共赢。
关键词:  电动汽车  低碳  主从博弈  演化博弈
DOI:10.19783/j.cnki.pspc.247007
分类号:
基金项目:吉林省重大科技专项课题资助(20240204001SF)
A master-slave evolutionary hybrid game-based scheduling method for virtual power plants and electric vehicle operators
QI Jiajin1, YIN Shucong2, ZHANG Liang2, WANG Dianbin2, LONG Yanliang2, ZHANG Chaorui2
1. Hangzhou Electric Power Equipment Manufacturing Company Limited, Hangzhou 310016, China; 2. Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology, Ministry of Education (Northeast Electric Power University), Jilin 132012, China
Abstract:
To address the complex multi-agent game problem of electric vehicles under demand response mechanisms, a scheduling method is proposed for virtual power plants and electric vehicle operators based on a master-slave evolutionary hybrid game, considering low-carbon objectives. First, an evolutionary game model for electric vehicle charging and discharging scheduling is constructed based on the logit protocol. Second, a master-slave evolutionary hybrid game model is established between the virtual power plants and electric vehicles, where the virtual power plants act as leaders to set electricity prices, and electric vehicle aggregators act as followers to determine charging and discharging strategies based on the prices. Finally, the Nash equilibrium and evolutionary equilibrium are jointly solved to obtain the optimal strategies for each agent. Simulation results verify that the proposed method can effectively reduce grid carbon emissions and mitigate load peak-valley differences while considering the interests of electric vehicle users, thereby achieving win-win outcomes among multiple parties.
Key words:  electric vehicle  low carbon  master-slave game  evolutionary game
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