TY - GEN
T1 - A stochastic flow capturing location and allocation model for siting electric vehicle charging stations
AU - Tan, Jingzi
AU - Lin, Wei Hua
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/11/14
Y1 - 2014/11/14
N2 - With the move of electric vehicle (EV) initiatives in many countries, there is a growing demand for fast-charging stations for recharging EVs. In this paper, we consider the problem of siting these EV charging stations in a transportation network with demand uncertainty. The demand for service considered is the passing flows in the network, i.e., the drive-by customers. We started with formulating the problem as a deterministic flow capturing location-allocation problem and then extended it into a stochastic model. Our results show that the stochastic model more realistically capture the actual coverage of the demand. We also developed a backup flow capturing model for providing secondary or multiple facilities coverage to ensure stability in service coverage and reduce the 'range anxiety.' Test cases with different flow composition and cost parameters are examined.
AB - With the move of electric vehicle (EV) initiatives in many countries, there is a growing demand for fast-charging stations for recharging EVs. In this paper, we consider the problem of siting these EV charging stations in a transportation network with demand uncertainty. The demand for service considered is the passing flows in the network, i.e., the drive-by customers. We started with formulating the problem as a deterministic flow capturing location-allocation problem and then extended it into a stochastic model. Our results show that the stochastic model more realistically capture the actual coverage of the demand. We also developed a backup flow capturing model for providing secondary or multiple facilities coverage to ensure stability in service coverage and reduce the 'range anxiety.' Test cases with different flow composition and cost parameters are examined.
UR - http://www.scopus.com/inward/record.url?scp=84937139516&partnerID=8YFLogxK
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U2 - 10.1109/ITSC.2014.6958140
DO - 10.1109/ITSC.2014.6958140
M3 - Conference contribution
AN - SCOPUS:84937139516
T3 - 2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014
SP - 2811
EP - 2816
BT - 2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014
Y2 - 8 October 2014 through 11 October 2014
ER -