论文标题
使用手机数据和基于兴趣的分段来估算电动汽车公共充电需求
Estimation of Electric Vehicle Public Charging Demand using Cellphone Data and Points of Interest-based Segmentation
论文作者
论文摘要
公路电气化的竞赛已经开始，说服驾驶员从燃油动力车辆转换为电动汽车需要强大的电动汽车（EV）充电基础设施。本文提出了一种创新的EV充电需求估计和细分方法。首先，我们使用细胞信号数据来估计邻域粒度的充电需求。其次，我们提出了一个分割模型，以分配不同充电技术之间的总充电需求：正常，半比例和快速充电。细分模型是一种基于城市感兴趣的方法，是一种最先进的方法，它推导了适用于城市规划的有用趋势。提出了布鲁塞尔市的一个案例研究。
The race for road electrification has started, and convincing drivers to switch from fuel-powered vehicles to electric vehicles requires robust Electric Vehicle (EV) charging infrastructure. This article proposes an innovative EV charging demand estimation and segmentation method. First, we estimate the charging demand at a neighborhood granularity using cellular signaling data. Second, we propose a segmentation model to partition the total charging needs among different charging technology: normal, semi-rapid, and fast charging. The segmentation model, an approach based on the city's points of interest, is a state-of-the-art method that derives useful trends applicable to city planning. A case study for the city of Brussels is proposed.
