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An Assessment Method for the Impact of Electric Vehicle Participation in V2G on the Voltage Quality of the Distribution Network

Author

Listed:
  • Wei Chen

    (College of Electrical Engineering and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China)

  • Lei Zheng

    (College of Electrical Engineering and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China)

  • Hengjie Li

    (College of Electrical Engineering and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China)

  • Xiping Pei

    (College of Electrical Engineering and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China)

Abstract

In order to further evaluate the impact of vehicle-to-grid (V2G) on the distribution network, this paper studies a method to assess the influence of electric vehicles participating in charge and discharge on the voltage quality of the distribution network. First, considering the state of charge of the EV, the participation of the owner and other factors, the charging and discharging model is built. Then, the probabilistic power flow calculation based on Latin hypercube sampling is used to obtain the probability distribution of the voltage amplitude of the charge and discharge load connected to the distribution network, and finally the evaluation index is established to quantify and calculate the voltage quality of the distribution network participating in the V2G process of electric vehicles. Simulation results show that the evaluation method has the advantage of fast calculation speed while ensuring known accuracy, introduces the probability distribution of expected value and variance quantification of voltage amplitude, more intuitively understands the degree of influence on voltage quality before and after V2G, and can effectively assess the impact of electric vehicles accessing the distribution network in V2G mode on the power quality of low-voltage residential areas and industrial and commercial areas, and this evaluation method can provide useful reference for the formulation of future V2G control strategies and the planning of future urban power grids.

Suggested Citation

  • Wei Chen & Lei Zheng & Hengjie Li & Xiping Pei, 2022. "An Assessment Method for the Impact of Electric Vehicle Participation in V2G on the Voltage Quality of the Distribution Network," Energies, MDPI, vol. 15(11), pages 1-14, June.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:11:p:4170-:d:832672
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    References listed on IDEAS

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    1. Tao, Ye & Huang, Miaohua & Chen, Yupu & Yang, Lan, 2020. "Orderly charging strategy of battery electric vehicle driven by real-world driving data," Energy, Elsevier, vol. 193(C).
    2. Du, Jiuyu & Li, Feiqiang & Li, Jianqiu & Wu, Xiaogang & Song, Ziyou & Zou, Yunfei & Ouyang, Minggao, 2019. "Evaluating the technological evolution of battery electric buses: China as a case," Energy, Elsevier, vol. 176(C), pages 309-319.
    3. Lyu, Lin & Yang, Xinran & Xiang, Yue & Liu, Junyong & Jawad, Shafqat & Deng, Runqi, 2020. "Exploring high-penetration electric vehicles impact on urban power grid based on voltage stability analysis," Energy, Elsevier, vol. 198(C).
    4. Sanchari Deb & Kari Tammi & Karuna Kalita & Pinakeshwar Mahanta, 2018. "Impact of Electric Vehicle Charging Station Load on Distribution Network," Energies, MDPI, vol. 11(1), pages 1-25, January.
    5. Rabiee, Abdorreza & Sadeghi, Mohammad & Aghaeic, Jamshid & Heidari, Alireza, 2016. "Optimal operation of microgrids through simultaneous scheduling of electrical vehicles and responsive loads considering wind and PV units uncertainties," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 721-739.
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    Cited by:

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