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1.北京科技大学计算机与通信工程学院,北京市 100083
2.国网四川省电力公司经济技术研究院,四川省成都市 610041
郑远硕(1994—),女,博士研究生,主要研究方向:智能电网优化、电力需求响应。E-mail:1248708457@qq.com
李峰(1999—),男,硕士研究生,主要研究方向:智能电网优化。E-mail:lf18776374773@163.com
董九玲(1986—),女,博士研究生,主要研究方向:智能电网连锁故障分析及优化。E-mail:hndongjiuling@126.com
张敏(1972—),女,通信作者,副教授,主要研究方向:新一代互联网技术、内容分发网络、智能电网CPS安全等。E-mai:zhangm@ustb.edu.cn
收稿日期:2022-01-31,
修回日期:2022-04-11,
网络出版日期:2022-05-11,
纸质出版日期:2022-06-25
移动端阅览
郑远硕,李峰,董九玲等.“车-路-网”模式下电动汽车充放电时空灵活性优化调度策略[J].电力系统自动化,2022,46(12):88-97.
ZHENG Yuanshuo,LI Feng,DONG Jiuling,et al.Optimal Dispatch Strategy of Spatio-Temporal Flexibility for Electric Vehicle Charging and Discharging in Vehicle-Road-Grid Mode[J].Automation of Electric Power Systems,2022,46(12):88-97.
郑远硕,李峰,董九玲等.“车-路-网”模式下电动汽车充放电时空灵活性优化调度策略[J].电力系统自动化,2022,46(12):88-97. DOI: 10.7500/AEPS20220131001.
ZHENG Yuanshuo,LI Feng,DONG Jiuling,et al.Optimal Dispatch Strategy of Spatio-Temporal Flexibility for Electric Vehicle Charging and Discharging in Vehicle-Road-Grid Mode[J].Automation of Electric Power Systems,2022,46(12):88-97. DOI: 10.7500/AEPS20220131001.
电动汽车(EV)是具有交通和移动负荷双重属性的跨域主体。EV大规模集中充电会给电网带来冲击,并加剧交通拥堵。为此,提出基于“车-路-网”交互的EV充电负荷时空优化调度策略,对EV的充电行为进行合理调控。首先,建立动态路网模型并结合改进的Floyd算法精确模拟EV行驶路径,预测EV充电负荷时空分布特性。其次,以预测结果为基础,结合电价响应度模型提出基于主从博弈的优化调度策略,对电网、路网和EV用户的收益进行多目标优化。最后,以中国北京市某区域路网及IEEE 33节点配电系统对所提模型的有效性进行仿真验证,结果显示,所提策略可以实现充电站间的负荷时空分布均衡,改善充电站周围路网的交通流量状况,并降低EV用户充电成本。
Electric vehicle (EV) is a cross-domain subject with dual properties of traffic tool and mobile load. Large-scale centralized charging of EV will impact the power grid and aggravate the traffic congestion. Thus
the spatio-temporal optimal dispatch strategy for the EV charging load based on the interaction of vehicle-road-grid is proposed to regulate the charging behavior of EVs. Firstly
the dynamic traffic network model and the modified Floyd algorithm are used to simulate the EV driving path for predicting the spatio-temporal distribution characteristics of EV charging load. Secondly
based on the prediction results
the optimal dispatch strategy based on the Stackelberg game is proposed combining with the electricity price response degree model for the multi-objective optimization of the benefits of power grid
traffic networks and EV owners. Finally
a regional traffic network in Beijing
China and the IEEE 33-bus distribution system are simulated to verify the effectiveness of the proposed model. The results demonstrate that the proposed optimal dispatch strategy can not only realize the balanced distribution of load in time and space among charging stations
but also can improve the traffic flow of the traffic network around the charging stations and reduce the charging cost of EV users.
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