Understanding the linkage between electric vehicle charging network coverage and charging opportunity using GPS travel data
- National Renewable Energy Lab. (NREL), Golden, CO (United States)
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
- Lamar Univ., Beaumont, TX (United States). Dept. of Civil and Environmental Engineering
Using GPS travel survey data from three metropolitan areas, this paper estimates the relationship between plug-in electric vehicle (PEV) public charging infrastructure coverage and charging opportunity. The former is defined as the percentage of public areas with charging stations installed and the latter represents the drivers probability of accessing a public charger at their trip stops (stop-based) or during at least one stop of their travel day (trip chain-based). Understanding this relationship is important to PEV manufacturers and electric vehicle supply equipment (EVSE) providers, as well as government agencies, for evaluating different levels of EVSE deployment and estimating the impact of its availability on PEV adoption. Heuristic procedures are developed to estimate stop- and trip chain-based charging opportunities. Charging opportunity reflects the visibility of EVSE as the incremental security that charging stations enable, while evaluating the potential of a driver to access EVSE at travel stops or during the day, for different levels of EVSE deployment on the transportation network. The metrics proposed do not assess the probability of completing trips with electric vehicles of a given range. The analysis results indicate that drivers’ trip destinations concentrate in a few popular places and EVSE deployment in these areas could achieve relatively high levels of charging opportunity. This finding is also robust to regional variations.
- Research Organization:
- Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
- Sponsoring Organization:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE); USDOE
- Grant/Contract Number:
- AC05-00OR22725
- OSTI ID:
- 1567006
- Alternate ID(s):
- OSTI ID: 1636916
- Journal Information:
- Transportation Research Part C: Emerging Technologies, Vol. 98, Issue C; ISSN 0968-090X
- Publisher:
- ElsevierCopyright Statement
- Country of Publication:
- United States
- Language:
- English
Web of Science
Charging Station and Power Network Planning for Integrated Electric Vehicles (EVs)
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journal | July 2019 |
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