TY - GEN
T1 - A game theoretical charging scheme for electric vehicles in smart community
AU - Wang, Yuntao
AU - Su, Zhou
AU - Xu, Qichao
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/27
Y1 - 2018/7/27
N2 - In a smart community (SC) with renewable energy sources (RES), flexible charging service can be provisioned to electric vehicles (EVs), where EVs can choose clean energy, traditional energy, or the mixture of them on demand. Considering the existence of various entities in the SC and the limited generation capacity of RES, it becomes of significance yet very challenging to optimally schedule the charging service for EVs with different consumption preferences. In this paper, we propose a charging scheme for EVs in a SC integrated with RES by using a game theoretical approach. Firstly, a three-party energy network is proposed to model the interactions among the power grid, EVs, and aggregators in the smart grid. Secondly, the trust model is presented to improve safety of power trading by evaluating the reliability of aggregators. Thirdly, based on the four-stage stackelberg game, the optimal strategies of three energy entities are analyzed by solving the stackelberg equilibrium (SE). Furthermore, a weighted max-min fairness (WMMF) based algorithm is proposed to fairly allocate the limited renewable power for EVs. Finally, extensive simulations are carried out to evaluate and demonstrate the effectiveness of the proposed scheme through comparison with conventional schemes.
AB - In a smart community (SC) with renewable energy sources (RES), flexible charging service can be provisioned to electric vehicles (EVs), where EVs can choose clean energy, traditional energy, or the mixture of them on demand. Considering the existence of various entities in the SC and the limited generation capacity of RES, it becomes of significance yet very challenging to optimally schedule the charging service for EVs with different consumption preferences. In this paper, we propose a charging scheme for EVs in a SC integrated with RES by using a game theoretical approach. Firstly, a three-party energy network is proposed to model the interactions among the power grid, EVs, and aggregators in the smart grid. Secondly, the trust model is presented to improve safety of power trading by evaluating the reliability of aggregators. Thirdly, based on the four-stage stackelberg game, the optimal strategies of three energy entities are analyzed by solving the stackelberg equilibrium (SE). Furthermore, a weighted max-min fairness (WMMF) based algorithm is proposed to fairly allocate the limited renewable power for EVs. Finally, extensive simulations are carried out to evaluate and demonstrate the effectiveness of the proposed scheme through comparison with conventional schemes.
KW - EV charging
KW - Game theory
KW - Smart community
UR - https://www.scopus.com/pages/publications/85051440018
U2 - 10.1109/ICC.2018.8422235
DO - 10.1109/ICC.2018.8422235
M3 - 会议稿件
AN - SCOPUS:85051440018
SN - 9781538631805
T3 - IEEE International Conference on Communications
BT - 2018 IEEE International Conference on Communications, ICC 2018 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE International Conference on Communications, ICC 2018
Y2 - 20 May 2018 through 24 May 2018
ER -
