Estimating the electric vehicle charging demand of multi-unit dwelling residents in the United States

Xiaobin Cheng, Eleftheria Kontou
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Abstract

Early battery electric vehicle (EV) adopters can access home chargers for reliable charging. As the EV market grows, residents of multi-unit dwellings (MUDs) may face barriers in owning EVs and charging them without garage or parking availability. To investigate the mechanisms that can bridge existing disparities in home charging and station deployment, we characterized the travel behavior of MUD residents and estimated their EV residential charging demand. This study classifies the travel patterns of MUD residents by fusing trip diary data from the National Household Travel Survey and housing features from the American Housing Survey. A hierarchical agglomerative clustering method was used to cluster apartment complex residents’ travel profiles, considering attributes such as dwell time, daily vehicle miles traveled (VMT), income, and their residences’ US census division. We propose a charging decision model to determine the charging station placement demand in MUDs and the charging energy volume expected to be consumed, assuming that MUD drivers universally operate EVs in urban communities. Numerical experiments were conducted to gain insight into the charging demand of MUD residents in the US. We found that charging availability is indispensable for households that set out to meet 80% state of charge by the end of the day. When maintaining a 20% comfortable state of charge the entire day, the higher the VMT are, the greater the share of charging demand and the greater the energy use in MUD chargers. The upper-income group requires a greater share of MUD charging and greater daily kWh charged because of more VMT.
估算美国多单元住宅居民的电动汽车充电需求
早期的纯电动汽车(EV)用户可以使用家用充电器进行可靠充电。随着电动汽车市场的增长,多单元住宅(mud)的居民在没有车库或停车场的情况下,可能会面临拥有电动汽车和充电的障碍。为了探讨弥合家庭充电和充电站部署差距的机制,我们对MUD居民的出行行为进行了表征,并估计了他们的电动汽车住宅充电需求。本研究通过融合全国家庭旅行调查的旅行日记数据和美国住房调查的住房特征,对MUD居民的旅行模式进行分类。考虑居住时间、每日车辆行驶里程(VMT)、收入和居住地的美国人口普查区划等属性,采用分层聚类方法对公寓楼居民的出行概况进行聚类。在城市社区中,假设MUD司机普遍驾驶电动汽车,我们提出了一个充电决策模型来确定MUD中充电站的放置需求和期望消耗的充电能量量。通过数值实验了解美国MUD居民的充电需求。我们发现,对于那些打算在一天结束时达到80%电量的家庭来说,充电的可用性是必不可少的。当全天保持20%舒适充电状态时,VMT越高,充电需求份额越大,MUD充电器的能耗越大。高收入群体需要更大的MUD充电份额和更大的日充电千瓦时,因为他们有更多的行驶里程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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