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

Author

Listed:
  • 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)

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.

Suggested Citation

  • Jun Yang & Jiejun Chen & Lei Chen & Feng Wang & Peiyuan Xie & Cilin Zeng, 2016. "A Regional Time-of-Use Electricity Price Based Optimal Charging Strategy for Electrical Vehicles," Energies, MDPI, vol. 9(9), pages 1-18, August.
    • Handle: RePEc:gam:jeners:v:9:y:2016:i:9:p:670-:d:76564
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    References listed on IDEAS

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    3. He, Lifu & Yang, Jun & Yan, Jun & Tang, Yufei & He, Haibo, 2016. "A bi-layer optimization based temporal and spatial scheduling for large-scale electric vehicles," Applied Energy, Elsevier, vol. 168(C), pages 179-192.
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    5. Foley, Aoife & Tyther, Barry & Calnan, Patrick & Ó Gallachóir, Brian, 2013. "Impacts of Electric Vehicle charging under electricity market operations," Applied Energy, Elsevier, vol. 101(C), pages 93-102.
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    Cited by:

    1. Junjie Hu & Hugo Morais & Tiago Sousa & Shi You & Reinhilde D’hulst, 2017. "Integration of Electric Vehicles into the Power Distribution Network with a Modified Capacity Allocation Mechanism," Energies, MDPI, vol. 10(2), pages 1-20, February.
    2. Su Su & Hao Li & David Wenzhong Gao, 2017. "Optimal Planning of Charging for Plug-In Electric Vehicles Focusing on Users’ Benefits," Energies, MDPI, vol. 10(7), pages 1-15, July.

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