Exploring the potential of rental electric vehicles for vehicle-to-grid: A data-driven approach

Mingdong Sun, Chunfu Shao, Chengxiang Zhuge, Pinxi Wang, Xiong Yang, Shiqi Wang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

6 Citations (Scopus)

Abstract

Vehicle-to-Grid (V2G) is a promising technology in electrification of transportation. Previous studies of V2G tended to be focused on private Electric Vehicles (EVs), paying little attention to rental EVs. In response, this paper proposed a data-driven approach to quantify the potential contribution of rental EVs to smart grid through V2G, using a one-month GPS trajectory dataset containing 967 rental EVs in Beijing in January 2019. The data-driven approach was tested within several “what-if” scenarios in Beijing, which considered availability of infrastructures with different charging/discharging speeds. The results suggested that the increased availability of infrastructure and charging/discharging speed could increase both charging and discharging demands. On overage, a 10% increase in the probability of getting EVs charged gives rise to a 13% increase in charging demand, and a 28% increase in discharging demand. Given that rental EV users can get access to infrastructure anytime and anywhere with a charging/discharging speed of 3.0 km/min (i.e., 3 km electric range per minute), it was estimated that the total daily charging and discharging demands, on average, were 1,860,234 kWh and 1,467,044 kWh, respectively, which were around 3.12% and 2.46% of the total daily residential electricity demand. Furthermore, the increased availability and charging/discharging speed can also lead to a smaller gap between the charging cost per vehicle per day and discharging reward per vehicle per day, bringing more economic benefits to rental EV users through V2G.

Original languageEnglish
Article number105841
JournalResources, Conservation and Recycling
Volume175
DOIs
Publication statusPublished - Dec 2021

Keywords

  • Car rental
  • Data-driven approach
  • Electric vehicle
  • GPS trajectory data
  • Vehicle-to-grid(V2G)

ASJC Scopus subject areas

  • Waste Management and Disposal
  • Economics and Econometrics

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