An archetypal routing network model to help identify potential charging locations for long-haul electric vehicles in Ontario, Canada

被引:5
|
作者
Dimatulac, Terence [1 ]
Maoh, Hanna [1 ]
Carriveau, Rupp [1 ]
机构
[1] Univ Windsor, Cross Border Inst, 401 Sunset Ave, Windsor, ON N9B 3P4, Canada
关键词
Archetypal Routing Network; Long-Haul Electric Trucks; Truck GPS Data; Charging Locations; Electricity Demand; IMPACT;
D O I
10.1016/j.trip.2023.100825
中图分类号
U [交通运输];
学科分类号
08 ; 0823 ;
摘要
Some estimates show long-haul transport trucks contribute as much as 10% of all Canada's greenhouse gas emissions. Long-haul electric vehicles (LHEVs) or "electric big rigs" offer a potentially compelling option to mitigate these emissions. However, LHEV charging is expected to burden the power grid significantly more than charging smaller passenger electric vehicles. To date, there is very little research on the impact of charging such vehicles on power grids. The following study leverages conventional long-haul truck GPS data to develop an archetypal routing network (ARN) model that can help identify candidate charging infrastructure locations in Ontario, Canada. Results suggest that based on historical LHEV travel patterns, most candidate charging station locations fall along critical road links in Ontario like Highway 401 and Highway 400. Subsequently, the addi-tional electricity demand of these stations is estimated and compared with Ontario's current electricity demand. Though the charging stations' aggregate daily demand is smaller than Ontario's overall demand, some of these stations' hourly electricity demand during peak hours are great enough to put significant pressure on local infrastructures.
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页数:13
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