Science & Technology Review >

2017 , Vol. 35 >Issue 21: 61 - 67

DOI: https://doi.org/10.3981/j.issn.1000-7857.2017.21.007

Articles

Recommendation method for electric vehicle charging based on collaborative filtering

  • BU Fanpeng ,
  • TIAN Shiming ,
  • GAO Jingjing ,
  • QI Linhai
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  • 1. China Electric Power Research Institute, Beijing 100192, China;
    2. School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China

Received date: 2017-09-01

  Revised date: 2017-10-15

  Online published: 2017-11-16

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Abstract

Based on a large number of charging behavior data, a charging interest model of electric vehicle users is established. The best charging options which users are interested in but have not found are recommended and charging behavior is orderly guided. In this paper, a recommended model based on a collaborative filtering algorithm is proposed for electric vehicle charging, and the best model parameter index is obtained through test and evaluation. New users with 10 times or less may use the user-based collaborative filtering algorithm while old users who have charged more than 10 times may adopt the collaborative filtering algorithm based on items. The optimal neighbor and recommended list length is 3 for the user-based collaborative filtering algorithm, and 4 for the algorithm based on items. The paper points out that the load aggregator can re-optimize the recommendation list in combination with the demand response plan and filter out the recommended information that conflicts with the demand response to realize the orderly charging control.

Key words： ordered charging; electric vehicles; collaborative filtering; intelligent recommend

Cite this article

BU Fanpeng , TIAN Shiming , GAO Jingjing , QI Linhai . Recommendation method for electric vehicle charging based on collaborative filtering[J]. Science & Technology Review, 2017 , 35(21) : 61 -67 . DOI: 10.3981/j.issn.1000-7857.2017.21.007

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