Empirical grid impact of in-home electric vehicle charging differs from predictions

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Yueming Lucy Qiu , Yi David Wang , Hiroyuki Iseki , Xingchi Shen , Bo Xing , Huiming Zhang
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引用次数: 12

Abstract

Accurate assessment of the impact of electric vehicle (EV) charging on the electric grid is critical for energy policymakers to design efficient EV subsidy programs as well as to provide reliable electricity infrastructure. Despite the fact that 80 % of EV charging is conducted with residential in-home chargers, very few empirical studies have examined the load and environmental impact of residential EV charging based on actual electricity consumption data. Our paper fills this critical gap in the literature, applying a difference-in-differences approach to high frequency smart meter data of about 1600 EV homes from 2014 to 2019 in Arizona, United States. First, we find that the electricity demand during the system peak hours from 6 to 8 pm in summer can increase by 7–14 % at an average household with in-home EV charging. Second, EV households respond to electricity pricing signals by increasing their charging in lower-priced off-peak hours within the EV-specific time-of-use (TOU) pricing. Third, we find evidence of rebound effects in driving that lead to a reduction in home-electricity consumption in certain hours of the day. Lastly, we show that our empirical estimation of the grid impact due to in-home EV charging is different from that predicted by existing simulation models due to factors such as consumer behaviors. Such deviations between predicted and actual behaviors imply potential adjustment of relevant policy interventions.

家用电动汽车充电对电网的实证影响与预测不同
准确评估电动汽车充电对电网的影响对于能源政策制定者设计有效的电动汽车补贴计划以及提供可靠的电力基础设施至关重要。尽管80%的电动汽车充电是通过家用充电器进行的,但很少有实证研究基于实际用电量数据来检验家用电动汽车充电的负荷和环境影响。我们的论文填补了文献中的这一关键空白,对美国亚利桑那州2014年至2019年约1600个电动汽车家庭的高频智能电表数据采用了差异中的差异方法。首先,我们发现,在夏季6点至8点的系统高峰时段,使用家庭电动汽车充电的普通家庭的电力需求可以增加7 - 14%。其次,电动汽车家庭通过在电动汽车特定使用时间(TOU)定价范围内的低电价非高峰时段增加充电来响应电价信号。第三,我们发现了驾驶反弹效应的证据,这导致一天中某些时间的家庭用电量减少。最后,我们表明,由于消费者行为等因素,我们对家庭电动汽车充电对电网影响的经验估计与现有仿真模型的预测存在差异。这种预测行为与实际行为之间的偏差意味着相关政策干预的潜在调整。
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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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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