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Orderly charging strategy of battery electric vehicle driven by real-world driving data

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  • Tao, Ye
  • Huang, Miaohua
  • Chen, Yupu
  • Yang, Lan

Abstract

The work preprocessed the real-world driving data of 1000 battery electric vehicles (BEVs) in Zhengzhou, China. Then a scheduling model of electric vehicles on time dimension was established based on the processed data. The mathematical model could meet the operation requirements of grid side and user side. The grid-side optimization minimized the system’s equivalent load fluctuation, and the user-side was optimized to maximize the charging capacity of electric vehicles. The mathematical model was solved by the genetic algorithm toolbox in Matlab software. Besides, we obtained the quantity distribution of BEV access to the power grid, parking time distribution, parking duration distribution and initial state of charge (SOC) distribution at the beginning of charging by analyzing the real-world driving data. These distribution curves were used to obtain the driving and charging habits of BEV drivers. By comparing the optimized orderly charging strategy with the random charging, in the case of meeting the user’s demand for charging power, the peak and valley difference and the equivalent load fluctuation of the power grid were significantly reduced by 22 and 22.7%, respectively. It greatly improves the security and economy of the grid.

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  • 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).
    • Handle: RePEc:eee:energy:v:193:y:2020:i:c:s0360544219325010
    DOI: 10.1016/j.energy.2019.116806
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    5. Ye Tao & Yupu Chen & Miaohua Huang & Lan Yang, 2023. "Data-Based Orderly Charging Strategy Considering Users’ Charging Choices," Energies, MDPI, vol. 16(19), pages 1-16, October.
    6. Hui Hwang Goh & Lian Zong & Dongdong Zhang & Wei Dai & Chee Shen Lim & Tonni Agustiono Kurniawan & Kai Chen Goh, 2022. "Orderly Charging Strategy Based on Optimal Time of Use Price Demand Response of Electric Vehicles in Distribution Network," Energies, MDPI, vol. 15(5), pages 1-25, March.
    7. Zhang, Yuanjian & Huang, Yanjun & Chen, Haibo & Na, Xiaoxiang & Chen, Zheng & Liu, Yonggang, 2021. "Driving behavior oriented torque demand regulation for electric vehicles with single pedal driving," Energy, Elsevier, vol. 228(C).
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    9. Calearo, Lisa & Marinelli, Mattia & Ziras, Charalampos, 2021. "A review of data sources for electric vehicle integration studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
    10. Yin, Wanjun & Ji, Jianbo & Wen, Tao & Zhang, Chao, 2023. "Study on orderly charging strategy of EV with load forecasting," Energy, Elsevier, vol. 278(C).
    11. Lai, Xin & Huang, Yunfeng & Deng, Cong & Gu, Huanghui & Han, Xuebing & Zheng, Yuejiu & Ouyang, Minggao, 2021. "Sorting, regrouping, and echelon utilization of the large-scale retired lithium batteries: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 146(C).
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