An electric vehicle charging station access equilibrium model with M/D/C
queueing
- URL: http://arxiv.org/abs/2102.05851v2
- Date: Fri, 3 Sep 2021 19:41:03 GMT
- Title: An electric vehicle charging station access equilibrium model with M/D/C
queueing
- Authors: Bingqing Liu, Theodoros P. Pantelidis, Stephanie Tam, Joseph Y. J.
Chow
- Abstract summary: We propose an EV-to-charging station user equilibrium (UE) assignment model with a M/D/C queue approximation as a nondifferentiable nonlinear program.
The model is applied to the large-scale case study of New York City Department of Citywide Administrative Services (NYC DCAS) fleet and EV charging station configuration as of July 8, 2020.
Results suggest a policy based on selecting locations with high utilization ratio instead of with high queue delay.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Despite the dependency of electric vehicle (EV) fleets on charging station
availability, charging infrastructure remains limited in many cities. Three
contributions are made. First, we propose an EV-to-charging station user
equilibrium (UE) assignment model with a M/D/C queue approximation as a
nondifferentiable nonlinear program. Second, to address the
non-differentiability of the queue delay function, we propose an original
solution algorithm based on the derivative-free Method of Successive Averages.
Computational tests with a toy network show that the model converges to a UE. A
working code in Python is provided free on Github with detailed test cases.
Third, the model is applied to the large-scale case study of New York City
Department of Citywide Administrative Services (NYC DCAS) fleet and EV charging
station configuration as of July 8, 2020, which includes unique, real data for
563 Level 2 chargers and 4 Direct Current Fast Chargers (DCFCs) and 1484 EVs
distributed over 512 Traffic Analysis Zones. The arrival rates of the
assignment model are calibrated in the base scenario to fit an observed average
utilization ratio of 7.6% in NYC. The model is then applied to compare charging
station investment policies of DCFCs to Level 2 charging stations based on two
alternative criteria. Results suggest a policy based on selecting locations
with high utilization ratio instead of with high queue delay.
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