A Regional Time-of-Use Electricity Price Based Optimal Charging Strategy for Electrical Vehicles

Jun Yang, Jiejun Chen, Lei Chen, Feng Wang, Peiyuan Xie and Cilin Zeng
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Jun Yang: School of Electrical Engineering, Wuhan University, Wuhan 430072, China
Jiejun Chen: School of Electrical Engineering, Wuhan University, Wuhan 430072, China
Lei Chen: School of Electrical Engineering, Wuhan University, Wuhan 430072, China
Feng Wang: Computer School of Wuhan University, Wuhan 430072, China
Peiyuan Xie: State Grid Hunan Power Supply Company, Changsha 410007, China
Cilin Zeng: State Grid Hunan Power Supply Company, Changsha 410007, China

Energies, 2016, vol. 9, issue 9, 1-18

Abstract: With the popularization of electric vehicles (EVs), the out-of-order charging behaviors of large numbers of EVs will bring new challenges to the safe and economic operation of power systems. This paper studies an optimal charging strategy for EVs. For that a typical urban zone is divided into four regions, a regional time-of-use (RTOU) electricity price model is proposed to guide EVs when and where to charge considering spatial and temporal characteristics. In light of the elastic coefficient, the user response to the RTOU electricity price is analyzed, and also a bilayer optimization charging strategy including regional-layer and node-layer models is suggested to schedule the EVs. On the one hand, the regional layer model is designed to coordinate the EVs located in different time and space. On the other hand, the node layer model is built to schedule the EVs to charge in certain nodes. According to the simulations of an IEEE 33-bus distribution network, the performance of the proposed optimal charging strategy is verified. The results demonstrate that the proposed bilayer optimization strategy can effectively decrease the charging cost of users, mitigate the peak-valley load difference and the network loss. Besides, the RTOU electricity price shows better performance than the time-of-use (TOU) electricity price.

Keywords: electric vehicles; user responsivity; optimization scheduling; RTOU electricity price model; regional layer model; node layer model (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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