卢慧, 谢开贵, 邵常政, 胡博, 潘聪聪, 黄博. 考虑燃油车和电动汽车动态混合交通流的电动汽车充电站规划[J]. 高电压技术, 2023, 49(3): 1150-1160. DOI: 10.13336/j.1003-6520.hve.202213562023
引用本文: 卢慧, 谢开贵, 邵常政, 胡博, 潘聪聪, 黄博. 考虑燃油车和电动汽车动态混合交通流的电动汽车充电站规划[J]. 高电压技术, 2023, 49(3): 1150-1160. DOI: 10.13336/j.1003-6520.hve.202213562023
LU Hui, XIE Kaigui, SHAO Changzheng, HU Bo, PAN Congcong, HUANG Bo. Charging Station Planning with the Dynamic and Mixed Traffic Flow of Gasoline and Electric Vehicles[J]. High Voltage Engineering, 2023, 49(3): 1150-1160. DOI: 10.13336/j.1003-6520.hve.202213562023
Citation: LU Hui, XIE Kaigui, SHAO Changzheng, HU Bo, PAN Congcong, HUANG Bo. Charging Station Planning with the Dynamic and Mixed Traffic Flow of Gasoline and Electric Vehicles[J]. High Voltage Engineering, 2023, 49(3): 1150-1160. DOI: 10.13336/j.1003-6520.hve.202213562023

考虑燃油车和电动汽车动态混合交通流的电动汽车充电站规划

Charging Station Planning with the Dynamic and Mixed Traffic Flow of Gasoline and Electric Vehicles

  • 摘要: 充电站的规划对缓解用户里程焦虑和电动汽车的规模化应用具有重要意义。随着电动汽车渗透率的提高,交通流的形态愈发复杂,导致充电站规划面临严峻挑战。针对已有研究忽略燃油车的路径选择对电动汽车出行以及充电站规划的影响,基于燃油车和电动汽车实时能耗的区别,提出了考虑燃油车和电动汽车动态混合交通流的交通分配模型,基于此进行了交通和配电网耦合网络的充电站规划,以满足电动汽车的充电需求。以耦合网络的规划和运行总成本最小为目标,考虑不同规划阶段燃油车和电动汽车的增长速度,结合耦合网络运行约束来确定电动汽车充电站的位置和容量。为得到全局最优解,应用Benders分解算法将模型分解成主–子问题进行迭代求解。以Sioux Falls交通网和IEEE 69节点配电网的耦合网络为测试系统,仿真算例表明考虑动态混合交通分配后可以减少车流量峰值,改善交通流分布,得到了最优的充电站规划结果。

     

    Abstract: Charging station planning (CSP) is vital to alleviating users' driving range anxiety and promoting the integration of electric vehicles (EVs). The increase in the market penetration of EVs will impact the traffic stream, leading to severe challenges in CSP. In most existing works, the traffic behavior of gasoline vehicles (GVs) and EVs, especially the interactions of route selection between the vehicles are neglected in the CSP. This paper proposes a novel traffic assignment model in which the dynamic and mixed traffic flows of GVs and EVs are taken into consideration and the characteristics of the vehicles' energy consumption are captured. Moreover, the CSP is carried out to meet the charging demands of EVs. The total cost of planning and operation of the coupling network is taken as a goal, and the growth rate of the vehicles in different planning stages, transportation and distribution operation constraints are all considered. Besides, the model is decomposed into main-sub-problems by the Benders decomposition algorithm for the global optimal solution. The simulation is carried out in the coupling network of Sioux Falls transportation network and IEEE 69-node distribution network. The results verify that the traffic flow can be improved with the dynamic mixed traffic distribution, and the charging station planning results can also be obtained optimally.

     

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