Title
A Novel Charging Scheme for Electric Vehicles With Smart Communities in Vehicular Networks
Abstract
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 in the vehicular networks. 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 using a game theoretical approach. First, a three-party energy network is proposed to model the interactions among the main grid, EVs, and aggregators in the smart grid. Second, the trust model is presented to improve the safety of energy trading by evaluating the reliability of aggregators based on direct trust and indirect trust. Third, based on the four-stage Stackelberg game, the optimal strategies of three energy entities are analyzed. The Stackelberg equilibrium can be obtained by the proposed accelerated gradient descent based iteration algorithm. Furthermore, a weighted max–min fairness based energy allocation algorithm is proposed to allocate the limited renewable energy for EVs in a fair and efficient manner. Finally, extensive simulations are carried out to evaluate and demonstrate the effectiveness of the proposed scheme through comparison with conventional schemes.
Year
DOI
Venue
2019
10.1109/TVT.2019.2923851
IEEE Transactions on Vehicular Technology
Keywords
Field
DocType
Microgrids,Games,Electric vehicle charging,Renewable energy sources,Smart cities
Gradient descent,Renewable energy,Smart grid,Computer science,Computer network,Provisioning,Stackelberg competition,Energy allocation,Vehicular ad hoc network,Grid,Distributed computing
Journal
Volume
Issue
ISSN
68
9
0018-9545
Citations 
PageRank 
References 
4
0.41
0
Authors
5
Name
Order
Citations
PageRank
Yuntao Wang110523.69
Zhou Su255346.81
Qichao Xu331821.08
Tingting Yang44917.12
Ning Zhang529917.82