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Siting public charge stations for taxis in Beijing based on Monte Carlo simulation

机译:基于蒙特卡洛模拟的北京出租车选址公共收费站

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With the rapid increase of electric vehicle number, lacking of charge stations has been the most obvious problem. Although there exist some charge stations in Beijing now and more will be built, it will take a long time due to technological and social constraints. This paper studies the travel behavior of the customer and electric taxi. Based on the density functions of travel distance, departure time and state of charge, Monte Carlo simulation is applied to generate two randomly sequences, which including the departure events with travel distances and the state of charge value. Comparing the value of two sequences, and if the state of charge cannot ensure the travel distance at a certain time point, there's a charge demand. We get the charge demand function by this way, and the peak demand value at a certain time can also be found. Finally, we propose some park-lot-based siting locations and make a sensitivity analysis. The innovation of this paper is using travel behavior to simulate travel events in order to recognize charge demand, and the paper has proposed a model to site charge facilities that can satisfy the current demand of electric taxis.
机译:随着电动汽车数量的迅速增加,缺少充电站已成为最明显的问题。尽管北京现在有一些充电站,并且还会建造更多的充电站,但是由于技术和社会限制,这将花费很长时间。本文研究了客户和电动出租车的行驶行为。基于行进距离,出发时间和荷电状态的密度函数,应用蒙特卡洛模拟生成两个随机序列,其中包括具有行进距离的荷电事件和荷电状态值。比较两个序列的值,如果充电状态不能确保在特定时间点的行驶距离,则存在充电需求。通过这种方式我们可以得到充电需求函数,并且还可以找到特定时间的峰值需求值。最后,我们提出了一些基于公园的选址位置并进行了敏感性分析。本文的创新之处在于使用出行行为来模拟出行事件以识别充电需求,并且本文提出了一种模型来对能够满足当前电动出租车需求的充电设施进行定位。

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