Development of a DC Fast Charging Station Model for Use with EV Infrastructure Projection Tool

Conference · Thu Aug 30 04:00:00 EDT 2018

DOI:https://doi.org/10.1109/ITEC.2018.8450158· OSTI ID:1487315

Ucer, Emin Y. ^[1]; Kisacikoglu, Mithat C. ^[1]; Erden, Fatih ^[2]; Meintz, Andrew L ^[3]; Rames, Clement L ^[3]

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1. University of Alabama
2. Bilkent University
3. National Renewable Energy Laboratory (NREL), Golden, CO (United States)

The deployment of public charging infrastructure networks has been a major factor in enabling electric vehicle (EV) technology transition, and must continue to support the adoption of this technology. DC fast charging (DCFC) increases customer convenience by lowering charging time, enables long-distance EV travel, and could allow the electrification of high-mileage fleets. Yet, high capital costs and uneven power demand have been major challenges to the widespread deployment of DCFC stations. There is a need to better understand DCFC stations' loading, utilization, and customer service quality (i.e. queuing time, charging duration, and queue length). This study aims to analyze these aspects using one million vehicle-days of travel data within the Columbus, OH, region. Monte Carlo analysis is carried out in three types of areas - urban, suburban, and rural- to quantify the effect of uncertain parameters on DCFC station loading and service quality.

• Research Organization: National Renewable Energy Laboratory (NREL), Golden, CO (United States)
• Sponsoring Organization: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Vehicle Technologies Office (EE-3V)
• DOE Contract Number: AC36-08GO28308
• OSTI ID: 1487315
• Report Number(s): NREL/CP-5400-71245
• Country of Publication: United States
• Language: English

Related Subjects

25 ENERGY STORAGE
33 ADVANCED PROPULSION SYSTEMS
batteries
charging stations
data models
load modeling
power demand
state of charge
tools