Learning EV Placement Factors with Social Welfare and Economic Variation Modeling

Jingyi Yuan, Qiushi Cui, Zhihao Ma, Yang Weng

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations


The past few years have witnessed significant growth on the possession rate of electric vehicles (EV). Such growth urgently requires well-designed plans on charging station placement for sustainable EV growth. Existing solutions ignore many practical factors and lack a systematic method prioritizing them. Through constructive learning, we propose an urban EV charging station planning method with the deployment of levelized cost. This method incorporates four practical costs, considering the convexification of the constraints, economic parameter variation, and the interconnected electric and transportation networks. To better quantify the charging demand, the nested logit model is deployed. Meanwhile, we relate the public information of house prices with EV growth when assigning the weights. Furthermore, we also design the software that enables EV charging station placement. Numerical results reveal the trade-off in EV charger planning, as well as a promising system-level optimization performance.

Original languageEnglish (US)
Title of host publication51st North American Power Symposium, NAPS 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728104072
StatePublished - Oct 2019
Event51st North American Power Symposium, NAPS 2019 - Wichita, United States
Duration: Oct 13 2019Oct 15 2019

Publication series

Name51st North American Power Symposium, NAPS 2019


Conference51st North American Power Symposium, NAPS 2019
Country/TerritoryUnited States

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture
  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Safety, Risk, Reliability and Quality


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