A multi-period optimization model for the deployment of public electric vehicle charging stations on network

A multi-period multipath refueling location model is developed to expand public electric vehicle (EV) charging network to dynamically satisfy origin–destination (O–D) trips with the growth of EV market. The model captures the dynamics in the topological structure of network and determines the cost-effective station rollout scheme on both spatial and temporal dimensions. The multi-period location problem is formulated as a mixed integer linear program and solved by a heuristic based on genetic algorithm. The model and heuristic are justified using the benchmark Sioux Falls road network and implemented in a case study of South Carolina. The results indicate that the charging station rollout scheme is subject to a number of major factors, including geographic distributions of cities, vehicle range, and deviation choice, and is sensitive to the types of charging station sites.

• Record URL:
  https://doi.org/10.1016/j.trc.2016.01.008
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S0968090X16000267
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/0968090X
• Supplemental Notes:
  • Abstract reprinted with permission of Elsevier.
• Authors:
  • Li, Shengyin
  • Huang, Yongxi
  • Mason, Scott J
• Publication Date: 2016-4

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References; Tables;
• Pagination: pp 128-143
• Serial:
  • Transportation Research Part C: Emerging Technologies
  • Volume: 65
  • Publisher: Elsevier
  • ISSN: 0968-090X
  • Serial URL: http://www.sciencedirect.com/science/journal/0968090X

Subject/Index Terms

• TRT Terms: Case studies; Deployment; Electric vehicle charging; Electric vehicles; Genetic algorithms; Location; Mixed integer programming; Networks; Optimization; Origin and destination; Service stations
• Uncontrolled Terms: Battery charging stations (Electric vehicles)
• Geographic Terms: South Carolina
• Subject Areas: Energy; Highways; Planning and Forecasting; Vehicles and Equipment;

Filing Info

• Accession Number: 01597496
• Record Type: Publication
• Files: TRIS
• Created Date: Apr 28 2016 2:42PM