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A Multi-Period Framework for Coordinated Dispatch of Plug-in Electric Vehicles

Author

Listed:
  • Yinuo Huang

    (College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China)

  • Chuangxin Guo

    (College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China)

  • Yi Ding

    (College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China)

  • Licheng Wang

    (School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane 4067, Australia)

  • Bingquan Zhu

    (State Grid Zhejiang Electric Power Company, Hangzhou 310007, China)

  • Lizhong Xu

    (State Grid Zhejiang Electric Power Company, Hangzhou 310007, China)

Abstract

Coordinated dispatch of plug-in electric vehicles (PEVs) with renewable energies has been proposed in recent years. However, it is difficult to achieve effective PEV dispatch with a win-win result, which not only optimizes power system operation, but also satisfies the requirements of PEV owners. In this paper, a multi-period PEV dispatch framework, combining day-ahead dispatch with real-time dispatch, is proposed. On the one hand, the day-ahead dispatch is used to make full use of wind power and minimize the fluctuation of total power in the distribution system, and schedule the charging/discharging power of PEV stations for each period. On the other hand, the real-time dispatch arranges individual PEVs to meet the charging/discharging power demands of PEV stations given by the day-ahead dispatch. To reduce the dimensions of the resulting large-scale, non-convex problem, PEVs are clustered according to their travel information. An interval optimization model is introduced to obtain the problem solution of the day-ahead dispatch. For the real-time dispatch, a priority-ordering method is developed to satisfy the requirements of PEV owners with fast response. Numerical studies demonstrate the effectiveness of the presented framework.

Suggested Citation

  • Yinuo Huang & Chuangxin Guo & Yi Ding & Licheng Wang & Bingquan Zhu & Lizhong Xu, 2016. "A Multi-Period Framework for Coordinated Dispatch of Plug-in Electric Vehicles," Energies, MDPI, vol. 9(5), pages 1-16, May.
    • Handle: RePEc:gam:jeners:v:9:y:2016:i:5:p:370-:d:70134
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    References listed on IDEAS

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    1. Gruber, J.K. & Huerta, F. & Matatagui, P. & Prodanović, M., 2015. "Advanced building energy management based on a two-stage receding horizon optimization," Applied Energy, Elsevier, vol. 160(C), pages 194-205.
    2. Liu, Yangyang & Jiang, Chuanwen & Shen, Jingshuang & Hu, Jiakai & Luo, Yifan, 2015. "Coordination of hydro units with wind power generation based on RAROC," Renewable Energy, Elsevier, vol. 80(C), pages 783-792.
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    Citations

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    Cited by:

    1. Samy Faddel & Ali T. Al-Awami & Osama A. Mohammed, 2018. "Charge Control and Operation of Electric Vehicles in Power Grids: A Review," Energies, MDPI, vol. 11(4), pages 1-21, March.
    2. Jun Yang & Wanmeng Hao & Lei Chen & Jiejun Chen & Jing Jin & Feng Wang, 2016. "Risk Assessment of Distribution Networks Considering the Charging-Discharging Behaviors of Electric Vehicles," Energies, MDPI, vol. 9(7), pages 1-20, July.
    3. Zhang, Xizheng & Wang, Zeyu & Lu, Zhangyu, 2022. "Multi-objective load dispatch for microgrid with electric vehicles using modified gravitational search and particle swarm optimization algorithm," Applied Energy, Elsevier, vol. 306(PA).
    4. Haque, A.N.M.M. & Ibn Saif, A.U.N. & Nguyen, P.H. & Torbaghan, S.S., 2016. "Exploration of dispatch model integrating wind generators and electric vehicles," Applied Energy, Elsevier, vol. 183(C), pages 1441-1451.
    5. Ivana Semanjski & Sidharta Gautama, 2016. "Forecasting the State of Health of Electric Vehicle Batteries to Evaluate the Viability of Car Sharing Practices," Energies, MDPI, vol. 9(12), pages 1-17, December.
    6. Yining Zhang & Yubin He & Mingyu Yan & Chuangxin Guo & Yi Ding, 2018. "Linearized Stochastic Scheduling of Interconnected Energy Hubs Considering Integrated Demand Response and Wind Uncertainty," Energies, MDPI, vol. 11(9), pages 1-23, September.

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