TY - GEN
T1 - Using activity patterns to place electric vehicle charging stations in Urban regions
AU - Pal, Anamitra
AU - Rangudu, Pavan
AU - Ravi, S. S.
AU - Vullikanti, Anil K.
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/8/3
Y1 - 2018/8/3
N2 - There is growing interest in the adoption of electric vehicles (EVs) in urban regions. However, because of the limited battery range, the EV charging station infrastructure needs to be significantly expanded. We introduce EVChargingStation, the problem of optimizing charging stations so that each EV can be charged at a location within a certain service distance. Our formulation explicitly incorporates urban activity patterns, and considers multiple types of charging stations. We show that EVChargingStation is NP-hard, in general, and present approximation algorithms with provable performance guarantees. We evaluate one of our algorithms using a detailed urban activity model for the city of Portland, OR. Our results show a tradeoff between the number of charging stations and the maximum service distance, thus providing a systematic methodology for urban planners to evaluate policies for increasing EV deployment. We also show that considering such activity patterns is necessary, in the sense that deploying charging stations at 'high traffic' locations can lead to significantly worse solutions.
AB - There is growing interest in the adoption of electric vehicles (EVs) in urban regions. However, because of the limited battery range, the EV charging station infrastructure needs to be significantly expanded. We introduce EVChargingStation, the problem of optimizing charging stations so that each EV can be charged at a location within a certain service distance. Our formulation explicitly incorporates urban activity patterns, and considers multiple types of charging stations. We show that EVChargingStation is NP-hard, in general, and present approximation algorithms with provable performance guarantees. We evaluate one of our algorithms using a detailed urban activity model for the city of Portland, OR. Our results show a tradeoff between the number of charging stations and the maximum service distance, thus providing a systematic methodology for urban planners to evaluate policies for increasing EV deployment. We also show that considering such activity patterns is necessary, in the sense that deploying charging stations at 'high traffic' locations can lead to significantly worse solutions.
KW - Approximation algorithms
KW - Charging stations
KW - Electric vehicles
KW - Urban activity patterns
UR - http://www.scopus.com/inward/record.url?scp=85052249035&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85052249035&partnerID=8YFLogxK
U2 - 10.1109/IPDPSW.2018.00176
DO - 10.1109/IPDPSW.2018.00176
M3 - Conference contribution
AN - SCOPUS:85052249035
SN - 9781538655559
T3 - Proceedings - 2018 IEEE 32nd International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2018
SP - 1143
EP - 1152
BT - Proceedings - 2018 IEEE 32nd International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 32nd IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2018
Y2 - 21 May 2018 through 25 May 2018
ER -