Optimal charging scheduling for large-scale EV (electric vehicle) deployment based on the interaction of the smart-grid and intelligent-transport systems

Yugong Luo, Tao Zhu, Shuang Wan, Shuwei Zhang and Keqiang Li

Energy, 2016, vol. 97, issue C, 359-368

Abstract: The widespread use of electric vehicles (EVs) is becoming an imminent trend. Research has been done on the scheduling of EVs from the perspective of the charging characteristic, improvement in the safety and economy of the power grid, or the traffic jams in the transport system caused by a large number of EVs driven to charging stations. There is a lack of systematic studies considering EVs, the power grid, and the transport system all together. In this paper, a novel optimal charging scheduling strategy for different types of EVs is proposed based on not only transport system information, such as road length, vehicle velocity and waiting time, but also grid system information, such as load deviation and node voltage. In addition, a charging scheduling simulation platform suitable for large-scale EV deployment is developed based on actual charging scenarios. The simulation results show that the improvements in both the transport system efficiency and the grid system operation can be obtained by using the optimal strategy, such as the node voltage drop is decreased, the power loss is reduced, and the load curve is optimized.

Keywords: Battery-switch EV; Electric vehicles; Fast-charging EV; Intelligent-transport system; Optimal scheduling strategy; Smart-grid system (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (40)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:97:y:2016:i:c:p:359-368

DOI: 10.1016/j.energy.2015.12.140

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