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Optimal Planning of Charging for Plug-In Electric Vehicles Focusing on Users’ Benefits

Author

Listed:
  • Su Su

    (National Active Distribution Network Technology Research Center, Beijing Jiaotong University, Beijing 100044, China)

  • Hao Li

    (National Active Distribution Network Technology Research Center, Beijing Jiaotong University, Beijing 100044, China)

  • David Wenzhong Gao

    (Department of Electrical and Computer Engineering, University of Denver, Denver, CO 80210, USA)

Abstract

Many electric vehicles’ (EVs) charging strategies were proposed to optimize the operations of the power grid, while few focus on users’ benefits from the viewpoint of EV users. However, low participation is always a problem of those strategies since EV users also need a charging strategy to serve their needs and interests. This paper proposes a method focusing on EV users’ benefits that reduce the cost of battery capacity degradation, electricity cost, and waiting time for different situations. A cost model of battery capacity degradation under different state of charge ( SOC ) ranges is developed based on experimental data to estimate the cost of battery degradation. The simulation results show that the appropriate planning of the SOC range reduces 80% of the cost of battery degradation, and the queuing theory also reduces over 60% of the waiting time in the busy situations. Those works can also become a premise of charging management to increase the participation. The proposed strategy focusing on EV users’ benefits would not give negative impacts on the power grid, and the grid load is also optimized by an artificial fish swarm algorithm (AFSA) in the solution space of the charging time restricted by EV users’ benefits.

Suggested Citation

  • 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.
  • Handle: RePEc:gam:jeners:v:10:y:2017:i:7:p:952-:d:104123
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    References listed on IDEAS

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    Cited by:

    1. Jie Song & Xin Pan & Chao Lu & Hanchen Xu, 2017. "A Simulation-Based Optimization Method for Hybrid Frequency Regulation System Configuration," Energies, MDPI, vol. 10(9), pages 1-14, August.
    2. Yuttana Kongjeen & Krischonme Bhumkittipich, 2018. "Impact of Plug-in Electric Vehicles Integrated into Power Distribution System Based on Voltage-Dependent Power Flow Analysis," Energies, MDPI, vol. 11(6), pages 1-16, June.
    3. Chunlin Guo & Jingjing Yang & Lin Yang, 2018. "Planning of Electric Vehicle Charging Infrastructure for Urban Areas with Tight Land Supply," Energies, MDPI, vol. 11(9), pages 1-17, September.
    4. Kakillioglu, Emre Anıl & Yıldız Aktaş, Melike & Fescioglu-Unver, Nilgun, 2022. "Self-controlling resource management model for electric vehicle fast charging stations with priority service," Energy, Elsevier, vol. 239(PC).
    5. Ouyang, Quan & Fang, Ruyi & Xu, Guotuan & Liu, Yonggang, 2022. "User-involved charging control for lithium-ion batteries with economic cost optimization," Applied Energy, Elsevier, vol. 314(C).

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