TY - GEN
T1 - A contract based approach for electric vehicles charging in heterogeneous networks
AU - Chen, Huwei
AU - Su, Zhou
AU - Hui, Yilong
AU - Hui, Hui
AU - Fang, Dongfeng
N1 - Publisher Copyright:
© 2017, Springer Nature Singapore Pte Ltd.
PY - 2017
Y1 - 2017
N2 - With the help of mobile charging stations (MCSs), the charging service of electric vehicles (EVs) can be provided more easily with higher payoff and lower consumption, compared with the fixed charging stations (FCSs). Although many traditional approaches have been used to decide the pricing plans for FCSs, it can not be efficient to design the optimal pricing strategy for MCSs. In this paper, we propose a contract-based scheme to solve the problem of supplying power service to EV users. Firstly, considering quality of service (QoS) and mobility of MCS in the heterogeneous networks, we study and develop the utility function based on the relationship for MCS and EV users. Then, the charging problem for EV users is formulated as an optimization problem through the contract theory. Thirdly, we present the iterative algorithm to achieve the optimal solution. Our simulation results show the effectiveness of the proposed strategy.
AB - With the help of mobile charging stations (MCSs), the charging service of electric vehicles (EVs) can be provided more easily with higher payoff and lower consumption, compared with the fixed charging stations (FCSs). Although many traditional approaches have been used to decide the pricing plans for FCSs, it can not be efficient to design the optimal pricing strategy for MCSs. In this paper, we propose a contract-based scheme to solve the problem of supplying power service to EV users. Firstly, considering quality of service (QoS) and mobility of MCS in the heterogeneous networks, we study and develop the utility function based on the relationship for MCS and EV users. Then, the charging problem for EV users is formulated as an optimization problem through the contract theory. Thirdly, we present the iterative algorithm to achieve the optimal solution. Our simulation results show the effectiveness of the proposed strategy.
UR - https://www.scopus.com/pages/publications/85029385297
U2 - 10.1007/978-981-10-6364-0_32
DO - 10.1007/978-981-10-6364-0_32
M3 - 会议稿件
AN - SCOPUS:85029385297
SN - 9789811063633
T3 - Communications in Computer and Information Science
SP - 319
EP - 328
BT - Advanced Computational Methods in Energy, Power, Electric Vehicles, and Their Integration - International Conference on Life System Modeling and Simulation, LSMS 2017 and International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2017, Proceedings
A2 - Luk, Patrick
A2 - Li, Kang
A2 - Yang, Zhile
A2 - Xue, Yusheng
A2 - Cui, Shumei
A2 - Niu, Qun
PB - Springer Verlag
T2 - International Conference on Life System Modeling and Simulation, LSMS 2017 and International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2017
Y2 - 22 September 2017 through 24 September 2017
ER -