Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/15313
Title: Activity-Based Modeling to Predict Spatial and Temporal Power Demand of Electric Vehicles in Flanders, Belgium
Authors: KNAPEN, Luk 
KOCHAN, Bruno 
BELLEMANS, Tom 
JANSSENS, Davy 
WETS, Geert 
Issue Date: 2012
Publisher: NATL ACAD SCIENCES
Source: TRANSPORTATION RESEARCH RECORD (2287), p. 146-154
Abstract: Electric power demand for household-generated traffic was estimated as a function of time and space for the region of Flanders, Belgium. An activity-based model was used to predict traffic demand. Electric vehicle (EV) type and charger characteristics were determined on the basis of car ownership and on the assumption that the market shares of EV categories would be similar to the current ones for internal combustion engine vehicles published in government statistics. Charging opportunities at home and work locations were derived from the predicted schedules and the estimation of the possibility to charge at work. Simulations were run for several levels of EV market penetration and for specific ratios of battery-only electric vehicles (BEVs) to pluggable hybrid electric vehicles. A single car was used to drive all trips in a daily schedule. Most of the Flemish schedules could be driven entirely by a BEV even after the published range values were reduced to account for range anxiety and for the overestimated ranges resulting from tests in accordance with standards. The current overnight period for low-tariff electricity was found to be sufficiently long to allow for individual cost optimizing while minimizing the peaks for overall power demand.
Notes: Wets, G (reprint author), Hasselt Univ, Transportat Res Inst IMOB, Wetenschapspk 5,Bus 6, B-3590 Diepenbeek, Belgium. geert.wets@uhasselt.be
Keywords: Engineering, Civil; Transportation; Transportation Science & Technology
Document URI: http://hdl.handle.net/1942/15313
ISSN: 0361-1981
e-ISSN: 2169-4052
DOI: 10.3141/2287-18
ISI #: 000311918500019
Category: A1
Type: Journal Contribution
Validations: ecoom 2014
Appears in Collections:Research publications

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