Site selection optimization of charging station based on rapid clustering of electric vehicle driving data
CSTR:
Author:
Affiliation:

(1. School of Electrical Engineering, Southeast University, Nanjing 210096, China;2. Key Laboratory of Smart Grid Technology and Equipment of Jiangsu Province, Nanjing 210096, China)

Clc Number:

Fund Project:

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    Abstract:

    With the scaled development of electric vehicle, it is urgent to make reasonable site selection planning for charging stations to meet the actual needs. Electric vehicle traffic trajectory data are modeled and analyzed, and spectral clustering method is adopted to realize rapid clustering of electric vehicle driving data. According to the results of rapid clustering, the optimal location planning of charging stations is realized with the goal of minimizing the cost of construction economic operation and maintenance after the location of charging stations. The result of the calculation example shows that the charging station established can satisfy the user’s convenience and minimize the annual economic cost.

    Reference
    Related
    Cited by
Get Citation

王妍,吴传申,高山.基于电动汽车行驶数据快速聚类的充电站选址优化[J].电力需求侧管理英文版,2021,23(3):08-12.

Copy
Related Videos

Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:March 02,2021
  • Revised:March 21,2021
  • Adopted:
  • Online: May 24,2021
  • Published:
Article QR Code