引用本文:傅质馨,朱韦翰,朱俊澎,袁越.动态路-电耦合网络下电动出租车快速充电引导及其定价策略[J].电力自动化设备,2022,42(4):
FU Zhixin,ZHU Weihan,ZHU Junpeng,YUAN Yue.Fast charging guidance and pricing strategy for electric taxis based on dynamic traffic-grid coupling network[J].Electric Power Automation Equipment,2022,42(4):
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动态路-电耦合网络下电动出租车快速充电引导及其定价策略
傅质馨1,2, 朱韦翰1,2, 朱俊澎1,2, 袁越1,2
1.河海大学 能源与电气学院,江苏 南京 211100;2.河海大学 可再生能源发电技术教育部工程研究中心,江苏 南京 211100
摘要:
电动出租车作为快速充电及路-电耦合网络的主要参与者,其连续行驶-充电行为严重影响了路-电耦合网络的运行状态,为此提出了基于路-电耦合网络的电动出租车快速充电引导及其定价策略。首先,提出了电动出租车在路-电耦合网络下交通流-能量流-信息流的交互框架;然后,提出了交通网的信息动态更新策略,建立了单辆电动出租车模型用于模拟电动出租车的连续行驶-充电状态切换行为;在此基础上,提出了路径规划与交通网信息更新同周期的动态导航及考虑下一寻客点的选站决策方法;最后,根据站内负荷和选站负荷进行虚拟负荷预测,提出了基于虚拟负荷和利用率均衡的充电站定价策略。算例仿真结果表明,所提方法能够均衡充电站负荷,缓解交通网的拥堵状况,提高电动出租车的运营收入。
关键词:  路-电耦合网络  电动出租车  快速充电  动态导航  虚拟负荷  定价决策
DOI:10.16081/j.epae.202201013
分类号:U469.72
基金项目:国家自然科学基金青年基金资助项目(51807051);江苏省自然科学基金青年基金资助项目(BK20180507)
Fast charging guidance and pricing strategy for electric taxis based on dynamic traffic-grid coupling network
FU Zhixin1,2, ZHU Weihan1,2, ZHU Junpeng1,2, YUAN Yue1,2
1.School of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China;2.Research Center for Renewable Energy Generation Engineering of Ministry of Education, Hohai University, Nanjing 211100, China
Abstract:
As the main participants of fast charging and traffic-grid coupling network, the continuous driving-charging behavior of electric taxis seriously affects the operation state of traffic-grid coupling network. Therefore, the fast charging guidance and pricing strategy of electric taxis based on dynamic traffic-gird coupling network are proposed. Firstly, an interactive framework of traffic flow-energy flow-information flow for electric taxis in traffic-grid coupling network is proposed. Then, the dynamic updating strategy of traffic network information is proposed, and the model of a single electric taxi is built to simulate the continuous driving-charging state switching behavior of electric taxis. On this basis, the dynamic navigation of route planning and traffic network information updating in the same cycle and the station selection decision method considering the next passenger seeking point are proposed. Finally, the virtual load is predicted according to the station load and station selection load, and the pricing strategy of charging station based on virtual load and utilization ratio balance is proposed. The simulative results show that the proposed method can balance the load of charging station, alleviate traffic congestion and increase the operation income of electric taxis.
Key words:  traffic-grid coupling network  electric taxis  fast charging  dynamic navigation  virtual load  pricing decision

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