TY - GEN
T1 - Electric vehicle charging station placement
AU - LAM, Yun Sang Albert
AU - LEUNG, Yiu Wing
AU - CHU, Xiaowen
N1 - Copyright:
Copyright 2014 Elsevier B.V., All rights reserved.
PY - 2013
Y1 - 2013
N2 - Transportation electrification is one of the essential components in the future smart city planning and electric vehicles (EVs) will be integrated into the transportation system seamlessly. Charging stations are the main source of energy for EVs and their locations are critical to the accessibility of EVs in a city. They should be carefully situated so that an EV can access a charging station within its driving range and cruise around anywhere in the city upon being recharged. In this paper, we formulate the Electric Vehicle Charging Station Placement Problem, in which we minimize the total construction cost subject to the constraints for the charging station coverage and the convenience of the drivers for EV charging. We study the properties of the problem, especially its NP-hardness, and propose an efficient greedy algorithm to tackle the problem. We perform a series of simulation whose results show that the greedy algorithm can result in solutions comparable to the mixed-integer programming approach and its computation time is much shorter.
AB - Transportation electrification is one of the essential components in the future smart city planning and electric vehicles (EVs) will be integrated into the transportation system seamlessly. Charging stations are the main source of energy for EVs and their locations are critical to the accessibility of EVs in a city. They should be carefully situated so that an EV can access a charging station within its driving range and cruise around anywhere in the city upon being recharged. In this paper, we formulate the Electric Vehicle Charging Station Placement Problem, in which we minimize the total construction cost subject to the constraints for the charging station coverage and the convenience of the drivers for EV charging. We study the properties of the problem, especially its NP-hardness, and propose an efficient greedy algorithm to tackle the problem. We perform a series of simulation whose results show that the greedy algorithm can result in solutions comparable to the mixed-integer programming approach and its computation time is much shorter.
UR - http://www.scopus.com/inward/record.url?scp=84893629162&partnerID=8YFLogxK
U2 - 10.1109/SmartGridComm.2013.6688009
DO - 10.1109/SmartGridComm.2013.6688009
M3 - Conference proceeding
AN - SCOPUS:84893629162
SN - 9781479915262
T3 - 2013 IEEE International Conference on Smart Grid Communications, SmartGridComm 2013
SP - 510
EP - 515
BT - 2013 IEEE International Conference on Smart Grid Communications, SmartGridComm 2013
T2 - 2013 IEEE International Conference on Smart Grid Communications, SmartGridComm 2013
Y2 - 21 October 2013 through 24 October 2013
ER -