摘要
电动汽车无序充电让新能源为主体的新型电力系统中的多元决策主体均处在高成本、低收益且不安全的运行状态，针对这一问题，本文提出了一种考虑多元决策主体成本最优的电动汽车有序充放电方法。首先，构建了电动汽车用户成本支付函数最优的多目标优化模型，考虑了电动汽车充放电电价的随机性，并引入了可以改变电价的随机变量，把电动汽车用户成本支付函数转化为成本期望和成本偏差，并利用二次综合合理度函数获得最优解策略。其次，构建了电动汽车聚合商放电竞价模型和配电网运营商调度计划策略模型，并应用到双方主从非合作博弈模型中，通过求解非合作博弈纳什均衡，得到多元主体经济性均最优的电动汽车充放电调度策略。最后，通过仿真算例，结果表明上述方法可有效降低用户成本，提高电动汽车聚合商、配电网运营商的经济收益，其中所提出的基于电动汽车聚合商放电竞价的主从非合作博弈方法在有着较好的削峰填谷的消纳功能的同时，也提高了配电网系统的安全性。
关键词： 电动汽车；充放电电价；主从非合作博弈；用户成本；多目标优化模型
Abstract
The disorderly charging of electric vehicle (EV) makes the multiple decision-makers in the new power system dominated by new energy all in the state of high cost, low income and unsafe operation, for this problem, an orderly charging and discharging method considering the optimal cost of multiple decision-makers is proposed. First of all, a multi-objective optimization model for EV user (EVU) cost payment function is formulated with considering the randomness of EV charging and discharging electricity price. By introducing the random variable which can change the electricity price, the EVU cost payment function is transformed into cost expectation and cost deviation, and the optimal solution strategy can be obtained according to the secondary comprehensive reasonable function. Secondly, the discharge bidding model of EV aggregator (EVA) and the dispatching plan strategy model of distribution network operators are constructed, and applied to the non-cooperative game model of both sides. By solving the Nash equilibrium of non-cooperative game, the EV charging and discharging dispatching strategy with the optimal economy of multiple subjects is obtained. Finally, through the simulation examples, the results show that the above method can effectively reduce the EVU cost, improve economic benefits of the EVA and distribution network operators, and the above-mentioned master-slave non-cooperation game based on discharge bidding has a good absorption effect of peak cutting and valley filling function at the same time, also improve the security of the distribution network system.
Key words： Electric vehicle; Charge-discharge electricity price; Master-slave non-cooperation game; User cost; Multi-objective optimization model
参考文献 References
[1] 魏一凡,韩雪冰,卢兰光等.面向碳中和的新能源汽车与车网互动技术展望[J]. 汽车工程, 2022, 44 (04): 449-464.
[2] 侯贸军,罗春辉,武学伟等.计及PEV聚合器的含可再生能源电力系统AGC调节功率的协调调度[J]. 电力系统保护与控制, 2018, 46 (01): 63-70.
[3] 杨镜司, 秦文萍, 史文龙, 等. 基于电动汽车参与调峰定价策略的区域电网两阶段优化调度[J]. 电工技术学 报, 2022, 37(1): 58-71.
[4] Yue Huanzhan, Zhang Qian, Zeng Xiaosong, et al. Optimal scheduling strategy of electric vehicle cluster based on index evaluation system[J]. IEEE Transactions on Industry Applications, 2023, 59(1): 1212-1221.
[5] 房宇轩,胡俊杰,马文帅.计及用户意愿的电动汽车聚合商主从博弈优化调度策略[J].电工技术学报, 1-13[2024-01-30].
[6] 戴朝华,杨帅,叶圣永等.供需双方博弈视角下的V2G优化策略[J].西南交通大学学报, 1-10[2024-01-30].
[7] 李怡然,张姝,肖先勇等. V2G模式下计及供需两侧需求的电动汽车充放电调度策略[J]. 电力自动化设备, 2021, 41 (03): 129-135.
[8] 马文帅,胡俊杰,房宇轩等.电动汽车用户参与调控意愿的多代理表征与可信容量量化[J].电力系统自动化,2023, 47(18):122-131.
[9] 黄瑞锦,顾高峰.基于混合Logit模型的电动汽车购买意愿影响因素研究[J].交通运输研究,2021,7(01):95-103 +114.7.
[10] 吴赋章,杨军,林洋佳等.考虑用户有限理性的电动汽车时空行为特性[J].电工技术学报,2020,35(07):1563-1574.
[11] 陈海瑞,米增强,贾雨龙等.计及电价不确定的电动汽车聚合商区间调度策略[J].电测与仪表,2021,58(12):24-30.
[12] WU Hongyu, SHAHIDEHPOUR, ALABDULWAHAB A, et al. A game theoretic approach to risk-based optimal bidding strategies for electric vehicle aggregators in electricity markets with variable wind energy resources[J]. IEEE Transactions on Sustainable Energy, 2016,7(1):374-385.
[13] CHEN Lvpeng, YU Tao, CHEN Yongxiang,et al. Real-time optimal scheduling of large-scale electric vehicles: a dynamic non-cooperative game approach[J]. IEEE Access, 2020,8:133633-133644.
[14] 王晛,张华君,张少华.风电和电动汽车组成虚拟电厂参与电力市场的博弈模型[J].电力系统自动化,2019, 43(3): 155-162.
[15] 詹祥澎,杨军,韩思宁,等.考虑电动汽车可调度潜力的充电站两阶段市场投标策略[J].电力系统自动化, 2021, 45(10): 86-96.
[16] 潘樟惠,高赐威,刘顺桂.基于需求侧放电竞价的电动汽车充放电调度研究[J].电网技术,2016,40(04):1140-1146.
[17] 李军,梁嘉诚,刘克天等.计及用户响应度的电动汽车充放电优化调度策略[J].南方电网技术,2023,17(08):123-132.
[18] 刘东奇,张曦,钱奕衡.电动汽车集群充放电演化博弈协同策略[J].电力系统保护与控制,2023,51(16):84-93.
[19] 蔡国伟,姜雨晴,黄南天等.电力需求响应机制下基于多主体双层博弈的规模化电动汽车充放电优化调度[J].中国电机工程学报,2023,43(01):85-99.
[20] 马永翔,马少洁,闫群民等. 虚拟电厂与电动汽车用户的主从博弈定价策略[J].华北电力大学学报(自然科学版), 1-10[2024-01-30].
[21] 刘卫亮,闫倩文,张启亮等. 基于虚拟电厂区间主从博弈的车网互动优化调度[J].系统仿真学报, 1-13[2024-01-30].
[22] 李强,朱丹丹,黄地等. 虚拟电厂运营商与电动汽车用户的主从博弈定价策略[J].电力工程技术, 2022, 41 (04): 183-191.
[23] CHAI Bo, CHEN Jiming, YANG Zaiyue, et al. Demand response management with multiple utility companies: a two-level game approach[J]. IEEE Transactions on Smart Grid, 2014, 5(2):722-731.
[24] 戴朝华.搜寻者优化算法及其应用研究[D].西南交通大学,2009.