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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/17216

Title: Determining Electric Vehicle Charging Point Locations Considering Drivers’ Daily Activities
Authors: González, J.
Alvaro, Roberto
Garnallo, C.
Fuentes, M.
Fraile-Ardanuy, J.
Knapen, Luk
Janssens, Davy
Issue Date: 2014
Citation: Procedia Computer Science 32, p. 647-654
Series/Report: Procedia Computer Science
Series/Report no.: 32
Abstract: In this paper the daily temporal and spatial behavior of electric vehicles (EVs) is modelled using an activity-based (ActBM) micro-simulation model for Flanders region (Belgium). Assuming that all EVs are completely charged at the beginning of the day, this mobility model is used to determine the percentage of Flemish vehicles that cannot cover their programmed daily trips and need to be recharged during the day. Assuming a variable electricity price, an optimization algorithm determines when and where EVs can be recharged at minimum cost for their owners. This optimization takes into account the individual mobility constraint for each vehicle, as they can only be charged when the car is stopped and the owner is performing an activity. From this information, the aggregated electric demand for Flanders is obtained, identifying the most overloaded areas at the critical hours. Finally it is also analyzed what activities EV owners are underway during their recharging period. From this analysis, different actions for public charging point deployment in different areas and for different activities are proposed.
Notes: Fraile-Ardanuy, J (reprint author), ETSI Telecomunicac UPM, Madrid 28040, Spain. jesus.fraile.ardanuy@upm.es
URI: http://hdl.handle.net/1942/17216
Link to publication: http://www.sciencedirect.com/science/article/pii/S1877050914006723
DOI: 10.1016/j.procs.2014.05.472
ISI #: 000361562600079
ISSN: 1877-0509
Category: C1
Type: Proceedings Paper
Validation: ecoom, 2016
Appears in Collections: Research publications

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