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A Deployment Model of Charging Pile Based on Random Forest for Shared Electric Vehicle in Smart Cities

机译:基于随机森林的智能城市共享电动汽车充电桩部署模型

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In the smart cities, sharing electric vehicles have many advantages such as environmental protection, low carbon emission, and high efficiency, which will greatly facilitate human life. However, whether the shared electric vehicle can be charged in time directly affects the users' experience. Based on this fact, we study that how to deploy the charging piles in the parking station of the shared electric vehicle, and propose a charging pile deployment model. First, the number of shared electric vehicles that check out from parking stations is predicted based on the random forest algorithm. Then, a mobile model of the shared electric vehicle is established. Based on the mobile model, the number of shared electric vehicles that check in within the target period is calculated and whether they reach the starvation state are determined. After that, the number of charging piles to be deployed is determined. Finally, the effects of hunger rate, battery capacity and the distance between parking stations on the number of charging piles were simulated by experiments. The experimental results verify the validity and feasibility of the proposed model. The prediction model proposed in this paper can provide a certain decision basis for the sharing of electric vehicle charging pile planning.
机译:在智慧城市中,共享电动汽车具有环保,低碳排放,高效率等诸多优势,将极大地促进人们的生活。然而,共享电动车辆是否能够及时充电直接影响用户的体验。基于这一事实,我们研究了如何在共享电动汽车的停车场中部署充电桩,并提出了一种充电桩部署模型。首先,基于随机森林算法预测从停车场退房的共享电动汽车的数量。然后,建立共享电动车辆的移动模型。基于移动模型,计算在目标时段内登记的共享电动车辆的数量,并确定它们是否达到饥饿状态。之后,确定要部署的充电桩的数量。最后,通过实验模拟了饥饿率,电池容量和停车站之间的距离对充电桩数量的影响。实验结果验证了该模型的有效性和可行性。本文提出的预测模型可以为电动汽车充电桩规划的共享提供一定的决策依据。

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