| 引用本文: | 曹家乐,任永峰,薛宇,高博麟,祝荣.考虑用户偏好及动态定价的“车-站-能”优化调度策略[J].电力自动化设备,2026,46(2):148-155. |
| CAO Jiale,REN Yongfeng,XUE Yu,GAO Bolin,ZHU Rong.Optimal scheduling strategy of EV-charging station-energy considering user preference and dynamic pricing[J].Electric Power Automation Equipment,2026,46(2):148-155. |
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| 摘要: |
| 为了提高区域综合能源系统(RIES)的新能源利用率，协调各发电、储电、售电、用电主体利益，提出考虑用户偏好及动态定价的“车-站-能”优化调度策略。基于统计报告结果建立数学模型，对电动汽车的起始荷电状态、各时段电动汽车数量、各类型电动汽车充放电过程进行表征；建立以综合能源系统运营商为领导者，以能源供应商、充电站运营商、电动汽车聚合商为跟随者的RIES主从博弈模型，设计一种灵活调度RIES内部各主体的动态定价机制，引入Stevens定律描述电动汽车用户对不同充放电模式的偏好；通过遗传算法迭代求解最优值。算例结果表明，所提策略能有效提升新能源消纳率，平衡综合能源系统中各主体的利益，充分发挥电动汽车在电力市场中的调度潜力。 |
| 关键词: 电动汽车 区域综合能源系统 主从博弈 动态定价 用户偏好 |
| DOI：10.16081/j.epae.202503024 |
| 分类号: |
| 基金项目:国家自然科学基金资助项目(52367022,51967016)；国家重点研发计划项目(2021YFB2501000)；内蒙古自治区重点研发和成果转化项目(2023YFHH0077) |
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| Optimal scheduling strategy of EV-charging station-energy considering user preference and dynamic pricing |
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CAO Jiale1, REN Yongfeng1, XUE Yu2, GAO Bolin2, ZHU Rong1
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1.School of Energy and Power Engineering, Inner Mongolia University of Technology, Hohhot 010080, China;2.School of Vehicle and Mobility, Tsinghua University, Beijing 100084, China
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| Abstract: |
| In order to enhance the utilization rate of new energy in the regional integrated energy system(RIES),and coordinate the interests of power generation, power storage, power sales and power consumption entities, an optimal scheduling strategy of electric vehicle(EV)-charging station-energy considering user preference and dynamic pricing is proposed. Based on the results of statistical reports, a mathematical model is established to characterize the initial state of charge of EVs, the number of EVs in each time period and the charging and discharging processes of various types of EVs. A Stackelberg game model of RIES is established with the integrated energy system operator as the leader and the energy supplier, charging station operator and electric vehicle aggregator as the followers. A dynamic pricing mechanism for flexibly scheduling the various entities within RIES is designed, and Stevens’ law is introduced to describe the preferences of EV users for different charging and discharging modes. The optimal value is iteratively solved through genetic algorithm. The results of the case study show that the proposed strategy can effectively increase the consumption rate of new energy, balance the interests of all entities in the integrated energy system, and fully leverage the scheduling potential of EVs in the electricity market. |
| Key words: electric vehicles regional integrated energy system Stackelberg game dynamic pricing user preference |
