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Resident Plug-In Electric Vehicle Charging Modeling and Scheduling Mechanism in the Smart Grid

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  • Peng Han
  • Jinkuan Wang
  • Yinghua Han
  • Yan Li

Abstract

With the development of smart grid and the increase of global resident Plug-In Electric Vehicle (PEV) market in the near future, the interaction between limited distribution grid capacity and uncontrollable PEV charging loads can lead to violations of local grid restrictions. And the proper model charging scheduling mechanism is the key to assess and satisfy various resident charging requirements and help in optimizing utility utilization. In this paper, the distribution grid profile model with PEV charging power is firstly constructed for the purpose of studying resident PEV charging impact on the distribution grid. To better reflect the actual impact of PEVs, we use real data on driving behaviors, vehicle characteristics, and electricity loads to generate our model. Furthermore, an improved queuing-theory-based scheduling mechanism is proposed, the distribution grid communication structure and the algorithm are illustrated, and computer simulations are demonstrated to verify their performance. The results show that the proposed scheduling mechanism will enhance the distribution grid flexibility to meet various charging requirements while maximizing the grid capacity.

Suggested Citation

  • Peng Han & Jinkuan Wang & Yinghua Han & Yan Li, 2014. "Resident Plug-In Electric Vehicle Charging Modeling and Scheduling Mechanism in the Smart Grid," Mathematical Problems in Engineering, Hindawi, vol. 2014, pages 1-8, January.
    • Handle: RePEc:hin:jnlmpe:540624
    DOI: 10.1155/2014/540624
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    Cited by:

    1. Khalil Bachiri & Ali Yahyaouy & Hamid Gualous & Maria Malek & Younes Bennani & Philippe Makany & Nicoleta Rogovschi, 2023. "Multi-Agent DDPG Based Electric Vehicles Charging Station Recommendation," Energies, MDPI, vol. 16(16), pages 1-17, August.

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