中文摘要：

基于能源需求空间分布的既有新型燃料供应站布局模型解决了需求点与供应站之间的总距离最小、供应站服务客流最大、以及基于此两类目标的多目标优化问题。然而电动汽车充电时间较长的特性对充电站的空间布局问题提出了时间因素的限制。本文提出了充电站空间布局优化应该考虑充电的行为决策问题,即：何时需要充电,去何地充电,以及当因供电站的同时服务容量受到限制而产生排队时作何选择等。在研究充电行为和充电需求的基础上,建立了满足等待时间最短和服务最便利的时空间同时优化布局的动态模型,应用微观仿真方法进行了算例分析,并比较了该模型与传统截流选址模型在算例路网上的应用结果。结果证明时间限制下的行为决策对充电站布局存在较大影响,该动态模型对时间约束的考虑提高了优化结果的有效性。

英文摘要：

The conventional and popular alternative-fuel stations locating models that based on the the space dis- tribution of traffic demand have already managed to minimize total demand-weighted travel distance or to maxi- mize capturing, as well as to satisfy multiple purposes. While for the case of locating Elective Vehicles （EV） charging stations, the minimum requested charging time for EVs introduces a new factor for consideration, time constraints. The decision behaviors such as when and where to charge, and how to deal with the queuing prob- lem due to the simultaneous recharging capacity limitation are realized to have great impact on EV stations loca- tion optimization, therefore all those factors should be considered carefully for modeling. Based on the related research of refueling behaviors and refueling demands, this paper developed a new dynamic model, named as the Spatio-temporal Location Model, with dual purposes of achieving minimum waiting time and maximum ser- vice accessibility for a given number of EV charging stations. A micro simulation method has been employed on a 25-node network to figure out the optimal locations, and results of the model mentioned above are compared with the results of the traditional flow-capturing location model. Results suggest that time constraints do have great effects on the location of EV charging stations. The proposed model improves the optimization results by discarding some unreasonable hypotheses on charging behaviors and giving more attention to the time con- straints that exist in the real world.