TY - JOUR
T1 - Exploring the potential of rental electric vehicles for vehicle-to-grid
T2 - A data-driven approach
AU - Sun, Mingdong
AU - Shao, Chunfu
AU - Zhuge, Chengxiang
AU - Wang, Pinxi
AU - Yang, Xiong
AU - Wang, Shiqi
N1 - Funding Information:
This work was supported by the Hong Kong Polytechnic University [1-BE2J; PB2B], and the National Natural Science Foundation of China (52002345; 52072025).
Publisher Copyright:
© 2021 Elsevier B.V.
PY - 2021/12
Y1 - 2021/12
N2 - 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.
AB - 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.
KW - Car rental
KW - Data-driven approach
KW - Electric vehicle
KW - GPS trajectory data
KW - Vehicle-to-grid(V2G)
UR - http://www.scopus.com/inward/record.url?scp=85113300958&partnerID=8YFLogxK
U2 - 10.1016/j.resconrec.2021.105841
DO - 10.1016/j.resconrec.2021.105841
M3 - Journal article
AN - SCOPUS:85113300958
SN - 0921-3449
VL - 175
JO - Resources, Conservation and Recycling
JF - Resources, Conservation and Recycling
M1 - 105841
ER -
