1.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),吉林省吉林市 132012
2.智能电网教育部重点实验室(天津大学),天津市 300072
姜涛(1983—),男,通信作者,博士,教授,博士生导师,主要研究方向:电力系统安全性与稳定性、可再生能源集成、综合能源系统。E-mail:electricpowersys@163.com
迟大硕(2000—),男,硕士研究生,主要研究方向:电力系统优化运行与灵活性提升。E-mail:2202200143@neepu.edu.cn
吴成昊(1996—),男,博士研究生,主要研究方向:电力系统灵活性、电力市场。E-mail:1202100019@neepu.edu.cn
收稿:2025-02-18,
修回:2025-08-15,
网络首发:2025-11-26,
纸质出版:2026-02-10
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姜涛,迟大硕,吴成昊等.城市交通网-快速充电站-配电网分层协同优化方法[J].电力系统自动化,2026,50(3):36-47.
JIANG Tao,CHI Dashuo,WU Chenghao,et al.Hierarchical Coordinated Optimization Method for Urban Transportation Network- Fast Charging Station-Distribution Network[J].Automation of Electric Power Systems,2026,50(3):36-47.
姜涛,迟大硕,吴成昊等.城市交通网-快速充电站-配电网分层协同优化方法[J].电力系统自动化,2026,50(3):36-47. DOI: 10.7500/AEPS20250218002.
JIANG Tao,CHI Dashuo,WU Chenghao,et al.Hierarchical Coordinated Optimization Method for Urban Transportation Network- Fast Charging Station-Distribution Network[J].Automation of Electric Power Systems,2026,50(3):36-47. DOI: 10.7500/AEPS20250218002.
随着交通电气化持续推进,城市交通网与配电网耦合程度逐步增强,使得交通流与电力潮流的计算更加复杂。为全面描述电动汽车对城市交通网与配电网的影响,提出一种基于动态交通流和电力潮流的城市交通网-快速充电站-配电网分层协同优化调度策略,实现交通网、快速充电站、配电网的经济、灵活运行。首先,在配电网优化层以最小化运行成本为目标进行电力潮流优化,交通网优化层基于混合用户均衡进行交通流分配,快速充电站优化层以最大化运营商收益为目标调度电动汽车。然后,为简化模型,将交通流分配问题转化为快速充电站收益模型的约束条件并进行线性化处理,进而采用交替方向乘子法求解,以保护不同主体的信息隐私。最后,通过IEEE 33节点配电网与Nguyen-Dupuis交通网耦合系统验证了所提方法的有效性。
With the continuous advancement of transportation electrification
the coupling degree between the urban transportation network (UTN) and the distribution network (DN) is gradually increasing
which makes the calculation of traffic flow and power flow more complex. In order to comprehensively describe the impact of electric vehicles on UTN and DN
this paper proposes a dispatching strategy of hierarchical coordinated optimization for UTN-fast charging station (FCS)-DN based on dynamic traffic flow and power flow to realize the economical and flexible operation of UTN
FCS and DN. First
the power flow optimization is carried out in the DN optimization layer with the goal of minimizing the operation cost
the traffic flow assignment is carried out based on the mixed user balance in the UTN optimization layer
and the electric vehicles are dispatched with the goal of maximizing the operator’s revenue in the FCS optimization layer. Then
in order to simplify the model
the traffic flow allocation problem is transformed into the constraints of the FCS revenue model and linearized
and then the alternating direction method of multipliers is used to solve the above problem to protect the information privacy of various subjects. Finally
the effectiveness of the proposed model is verified by the system coupled with the IEEE 33-bus distribution network and the Nguyen-Dupuis transportation network.
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