Game and Contract Theory-Based Energy Transaction Management for Internet of Electric Vehicle

• Main Authors: Adugna Gebrie Jember, Wenhe Xu, Chao Pan, Xiongwen Zhao, Xin-Cheng Ren
• Format: Article
• Language: English
• Published: IEEE 2020-01-01
• Series: IEEE Access
• Subjects: Smart grid; V2G energy management optimization; Stackelberg game; contract theory; edge computing
• Online Access: https://ieeexplore.ieee.org/document/9250528/

With the development and expansion of smart grid systems, vehicle-to-grid (V2G) has become a new type of energy interaction based on Internet of Electric Vehicles (IoEVs). By leveraging the charging/discharging capabilities of EVs, V2G can be implemented in smart grid to enable intelligent energy transactions and reduce the unbalance of supply and demand. However, the implementation of interaction between the existing V2G technology and IoEVs faces the problems of high-complexity energy transaction management, insufficient computing capability, poor scalability, and lack of incentive mechanisms. The three-tier bi-directional energy transaction management strategies based on game and contract theory have been proposed. Firstly, the optimal pricing and EV discharging strategy is obtained based on the non-cooperative Stackelberg game and the energy-price equilibrium. Secondly, in order to optimize the utility of EAG, the information asymmetry incentive mechanism based on contract theory is proposed. This mechanism can effectively stimulate EVs to contribute to V2G energy transaction and further improve social benefits considering the energy transmission loss and battery life cycle degradation. To reduce the communication as well as processing latency and improve the efficiency of energy transaction management, edge computing has been incorporated. Simulation results show that the performance of the proposed scheme significantly outperforms other existing schemes under various scenarios.