203 / 2021-10-31 22:34:22
Research on Temporal and Spatial Distribution of Electric Vehicle (EV) Charging Load Based on Real Data & Simulation
electric vehicle,charging load forecasting,data mining,simulation
终稿
Zezhao Chen / UESTC
Jierui Zhang / UESTC
Yalong Guo / UESTC
Jialin Du / UESTC
Zongxing Xin / UESTC
Qianyu Li / Xi'an Jiaotong University
Changhua Zhang / UESTC
Xiaohao Xu / UESTC
To solve the problems of over-theorization and lack of real data in the current research, this paper proposes a data-driven EV charging load demand forecasting model. The model is based on analysis of residents’ travel patterns hided in EV travel data and single EV charging & discharging model considering its related characteristics. The results of a calculation example in Chengdu show that the proposed model can effectively predict the temporal and spatial distribution characteristics of EV charging load in different urban functional areas and in different time ranges. This provides a basis for the construction of charging stations and charging load management after EV have been applied in large scale.

 
重要日期
  • 会议日期

    07月11日

    2023

    08月18日

    2023

  • 11月10日 2021

    初稿截稿日期

  • 12月10日 2021

    注册截止日期

  • 12月11日 2021

    报告提交截止日期

主办单位
IEEE IAS
承办单位
IEEE IAS Student Chapter of Southwest Jiaotong University (SWJTU)
IEEE IAS Student Chapter of Huazhong University of Science and Technology (HUST)
IEEE PELS (Power Electronics Society) Student Chapter of HUST
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