Online Scheduling for Hierarchical Vehicle-to-Grid System: Design, Formulation, and Algorithm

Abstract

Due to the increasing popularity of electric vehicles (EVs) and technological advancements of EV electronics, the vehicle-to-grid (V2G) technique, which utilizes EVs to provide ancillary services for power grid, stimulates new ideas in current smart grid research. When coordinating a large number of EVs distributed in different geographical locations, a single aggregator is not sufficient to oversee the whole system and a hierarchical V2G system is required. Therefore, how to design a hierarchical V2G system and how to coordinate large-scale EVs to provide ancillary services become critical issues. In this paper, a generic hierarchical framework for a V2G system, which aims to provide frequency regulation services, is proposed to address the issues. Smart V2G aggregators (SVAs) are designed and employed to control the V2G system in a tree-like manner. A multi-level online V2G (MLOV) algorithm is devised for hierarchical V2G scheduling and it requires no forecasting information on regulation signals. It can also deal with the scalability issue encountered by the centralized algorithms and incast issue arising in the distributed algorithms. The simulation results show that the proposed algorithm outperforms the existing methods for the tradeoff between the quality of frequency regulation services and computational time. Through the computational study of the proposed algorithm, we also find that the computational time of the MLOV algorithm can be reduced exponentially by employing more SVAs and distributing the computational burden to the SVAs, with slight sacrifice on the smoothing quality.