Efficient Federated Connected Electric Vehicle Scheduling System: A Noncooperative Online Incentive Approach

Abstract

As one of the most promising elements in Intelligent Transportation Systems (ITSs), connected electric vehicles (CEVs) can be collectively utilized to improve the quality of essential transportation services. However, involving CEVs to provide vehicle-to-grid (V2G) services becomes a crucial problem since they are selfish and belong to different parties. To solve this problem, we propose an efficient federated CEV scheduling framework that implements noncooperative online incentive approach. In particular, the proposed system is designed for providing privacy-preserving power grid signals to each CEV aggregator (CEVA) within the citywide region. To motivate the CEVs to participate in V2G services, a noncooperative interaction scheme is designed between the selfish CEVs and each CEVA. The purpose of the game is to let the CEVA to determine the real-time electricity trading prices, while the CEVs decide their own real-time service schedules. Case studies assess the feasibility and effectiveness of proposed noncooperative incentive approach, in which the efficient motivation on the CEVs contribute to a high quality V2G services. Additionally, the use of sufficient online parking allocation method can further increase the quality of V2G services.