A distributed week-ahead scheduling method for the charging / discharging of plug-in electric vehicles integrated into the grid

Abstract

With the proliferation of electric vehicles (EVs) around the world, the large-scale grid-vehicle interaction (GVI) has become more and more promising recently. However, the existing research works on GVI are mainly limited to day-ahead or intra-day schedules which may not fully utilize the EVs' potential in charging/discharging arrangements for the power grid. Besides, the commonly-adopted practice of the central organization by the electric vehicle aggregator (EVA) may induce EV owners' privacy concerns. To solve these problems and furtherly strengthen the GVI willingness of EV users, a distributed week-ahead framework for the charging / discharging schedules of plug-in EVs interacting with the grid under the organization of an EVA is proposed in this paper. To describe the available dispatchable capacity of one single EV on a weekly time scale, the trip-chain based EV charging and travelling behavior model is formulated. For the EVA, it utilizes aggregate EV power and energy boundaries to model its feasible operation region which is crucial for the determination of the guidance tracking power profile in the distribution energy market clearing process. To protect the EVs' privacies and reduce the computational burden, a distributed algorithm is proposed to help the EVA allocate the guidance power profile among EVs. Case studies are conducted to demonstrate the validness and effectiveness of the proposed methods.

Keywords

• vehicle-to-grid interaction
• electric vehicles
• electric vehicle aggregator
• renewable energy sources
• distributed optimization