Modeling the impact of vehicle-to-grid discharge technology on transport and power systems. (April 2022)

• Record Type: Journal Article
• Authors: Ding, Yanyan; Li, Xinwei; Jian, Sisi
• Is Part Of: Transportation research. Volume 105(2022)
• Publication Date: 2022-04
• Subjects: Electric vehicles -- V2G -- Commute congestion -- Bottleneck; Transportation -- Research -- Periodicals; Transportation -- Environmental aspects -- Periodicals; 354.76
• DOI: 10.1016/j.trd.2022.103220
• Languages: English
• ISSNs: 1361-9209

Abstract

Highlights: Bi-modal bottleneck model to capture impact of EV discharge on traffic congestion. Traffic congestion is reduced if discharge and non-discharge EVs do not interact. Prove the occurrence condition that ensures transport and power systems are better off. Develop a decision tree for DNO to determine the optimal discharge reward. Use real data of a pilot V2G project to demonstrate key findings. Abstract: Vehicle-to-grid (V2G) technology enables electric vehicles (EVs) to discharge unused power to the power grid, allowing EVs to serve as flexible energy resources. Although this technology promises benefits to power systems, its impact on transport systems is unknown. We investigate the interaction between transport and power systems with V2G during co-existing peak periods. Commuters choosing to discharge earn rewards while encountering additional delay costs and altering departure time. A bottleneck model is used to characterize drivers' departure time and discharge choices. Possible queue patterns and occurrence conditions are derived. Traffic congestion is proved to be reduced compared to the without V2G case when commuters choosing to discharge arrive at the bottleneck earlier than those choosing not to discharge. We also derive the sufficient condition of the "win–win–win" situation for EV drivers, power and transport systems and develop a decision tree for the power system to set the discharge reward optimally.