Transitions to electric vehicles (EV) are expected to increase electricity use in residences, where most tend to recharge. We develop a mathematical programming framework for shifting residential EV charging during low electricity pricing hours to minimize the additional electricity costs that a household incurs from charging their vehicle. The model also aims to meet additional household and their community preferences by adopting four secondary objectives: charging as soon as possible when the user arrives at home, charging as late as possible before the user leaves home, charging for valley filling and peak shaving of the residential load, and charging in a shared community hub by using a fast charging station. We analyze granular residential energy data from a sample of Austin households in 2018. We conduct an empirical analysis to compare households’ electricity bills under four electricity pricing schemes, including flat rates and time-of-use rates, both with and without a separate meter for EV charging. Our findings indicate that if charging behaviors remain unchanged, installing a separate meter for EVs is more expensive than treating EVs as another residential plug load. However, under time-of-use EV charging tariffs, households should adjust their charging behaviors, as validated by our optimization model. Implementing all four secondary charging objectives successfully avoids the on-peak periods of the EV charging rate and reduces households’ overall daily electricity costs by 38.87 % during the summer and by 44.3 % during the winter. Charging as soon as possible, charging as late as possible, and charging at a shared station provide drivers with increased flexibility. Charging as soon as possible and charging as late as possible lead to the lowest charger utilization, with the former having the longest charging stop time before home departure and the latter allowing for the longest charging start time upon home arrival. Charging at a shared station gives rise to the lowest share of charging time over dwell time. Charging for valley filling and peak shaving of the residential load offers less flexibility but has the advantage of flattening the load curve and mitigating high peak loads. This proves crucial in safeguarding the community’s energy distribution infrastructure.

中文翻译：

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托管住宅电动汽车充电可最大限度地减少电费，同时满足驾驶员和社区的偏好

向电动汽车（EV）的过渡预计将增加住宅用电量，而大多数住宅都倾向于充电。我们开发了一个数学编程框架，用于在低电价时段转移住宅电动汽车充电，以最大限度地减少家庭因车辆充电而产生的额外电力成本。该模型还旨在通过采用四个次要目标来满足更多家庭及其社区的偏好：用户到家时尽快充电、用户离开家前尽可能晚充电、填谷调峰充电。住宅负载，并使用快速充电站在共享社区中心充电。我们分析了 2018 年奥斯汀家庭样本的详细住宅能源数据。我们进行了实证分析，比较了四种电价方案下的家庭电费，包括统一电价和分时电价，无论是否有单独的电表用于电动汽车充电。我们的研究结果表明，如果充电行为保持不变，为电动汽车安装单独的电表比将电动汽车视为另一种住宅插头负载更昂贵。然而，根据我们的优化模型的验证，在电动汽车分时充电费率下，家庭应该调整其充电行为。四个二次充电目标的全部实现，成功避开了电动汽车充电高峰期，使家庭日常用电成本在夏季降低了 38.87%，在冬季降低了 44.3%。尽快充电、尽可能晚充电以及在共享充电站充电为驾驶员提供了更大的灵活性。尽快充电和尽可能晚充电会导致充电器利用率最低，前者在出发前的充电停止时间最长，后者在到家时​​的充电开始时间最长。在共享充电站充电时，充电时间占停留时间的比例最低。对住宅负荷进行填谷和调峰收费的灵活性较差，但具有拉平负荷曲线和缓解高峰值负荷的优点。事实证明，这对于保护社区的能源分配基础设施至关重要。