张学军, 韩鹏. “车−站−路−网”系统中时空分布充电电价的优化[J]. 现代电力, 2021, 38(6): 628-635. DOI: 10.19725/j.cnki.1007-2322.2020.0427
引用本文: 张学军, 韩鹏. “车−站−路−网”系统中时空分布充电电价的优化[J]. 现代电力, 2021, 38(6): 628-635. DOI: 10.19725/j.cnki.1007-2322.2020.0427
ZHANG Xuejun, HAN Peng. Optimization of Spatial-Temporal Charging Price in the System Composed of Electric Vehicle, Charging Station, Traffic Network and Power Network[J]. Modern Electric Power, 2021, 38(6): 628-635. DOI: 10.19725/j.cnki.1007-2322.2020.0427
Citation: ZHANG Xuejun, HAN Peng. Optimization of Spatial-Temporal Charging Price in the System Composed of Electric Vehicle, Charging Station, Traffic Network and Power Network[J]. Modern Electric Power, 2021, 38(6): 628-635. DOI: 10.19725/j.cnki.1007-2322.2020.0427

“车−站−路−网”系统中时空分布充电电价的优化

Optimization of Spatial-Temporal Charging Price in the System Composed of Electric Vehicle, Charging Station, Traffic Network and Power Network

  • 摘要: 以电动汽车(electric vehicles,EV)和充电站(charging stations,CS)为纽带,城市电力网(power network,PN)和交通网(traffic network,TN)之间发生了复杂的耦合关联,形成了“车−站−路−网”系统。考虑到系统的运行状况与EV充电负荷和交通出行在时间和空间2个维度上的分布都有关系,提出了采用时空分布充电价格引导EV充电和出行行为,来改善“车−站−路−网”系统运行的方法。为此,建立了组成系统的各类实体的数学模型;采用层次分析法(analytic hierarchy process,AHP)描述了驾驶员行为决策过程的个体差异性。在此基础上,以PN网损最小和TN拥挤程度最小为目标,构建了时空分布充电电价优化模型。仿真结果表明,采用时空分布充电电价能减小PN损耗和电压偏移、缓解TN拥堵状况和均衡CS间的充电负荷,达到了优化“车−站−路−网”系统运行的目标。

     

    Abstract: Taking electric vehicles (EV) and charging stations (CS) as the link, a complex coupling correction between urban power network (PN) and traffic network (TN) has been occurred, and an EV-CS-TN-PN system is formed. Considering the fact that the operating condition of this system was related to the distribution of EV charging load and transportation and trip in space dimension and time dimension, so a method was proposed to adopt the spatial and temporal distributed electricity price to lead the EV charging as well as the behavior of transportation and trip to improve the operation of EV-CS-TN-PN system. For this purpose, the mathematical models of various kinds of entities constituting this system were established. The analytic hierarchy process (AHP) algorithm was utilized to describe the individual difference in the behavior decision-making process of drivers. On this basis, taking the minimum PN network loss and the minimum degree of crowdedness of TN as objectives, an optimization model of spatial and temporal distributed charging price was constructed. Simulation results show that adopting spatial and temporal distributed charging price can decrease the loss and voltage excursion of PN, mitigate the degree of crowdedness of TN and balancing the charging load among CS, thus the goal of optimizing the operation of EV-CS-TN-PN system can be achieved.

     

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