A novel real-time scheduling strategy with near-linear complexity for integrating large-scale electric vehicles into smart grid

Yanchong Zheng, Yitong Shang, Ziyun Shao and Linni Jian

Applied Energy, 2018, vol. 217, issue C, 13 pages

Abstract: Coordinated charging can utilize the properties of electric vehicles (EVs) to obtain various benefits. However, there are two major challenges, viz. the uncertainty of EV charging behaviors and the overlong solving time for the optimal solutions in the charging scheduling problem of large-scale EVs. It is almost infeasible to precisely predict the charging information of EVs due to the uncertainty of their mobility as transportation tools. In order to tackle this issue, the real-time charging scheduling method is employed in this paper. Even so, the computational complexity is crucially important in the real-time scheduling methods since the charging strategies of large-scale EVs must be acquired in a short time. Hence, a high efficient methodology is proposed for EV real-time scheduling based on the definition of capacity margin index and charging priority index. Finally, the simulation results show that the proposed scheduling method has a significant superiority over the uncoordinated charging in the regard of relieving the demand stress on the power system. Moreover, the complexity analysis demonstrates that the proposed method has near-linear complexity so that it can acquire the optimal real-time charging scheme in a rather shorter time than other methods.

Keywords: Electric vehicle; Coordinated charging; Real-time scheduling; Near-linear complexity; Smart grid (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (22)

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DOI: 10.1016/j.apenergy.2018.02.084

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