Optimization models for placement of an energy-aware electric vehicle charging infrastructure

This paper addresses the problem of optimally placing charging stations in urban areas. Two optimization criteria are used: maximizing the number of reachable households and minimizing overall e-transportation energy cost. The decision making models used for both cases are mixed integer programming with linear and nonlinear energy-aware constraints. A multi-objective optimization model that handles both criteria (number of reachable households and transportation energy) simultaneously is also presented. A number of simulation results are provided for two different cities in order to illustrate the proposed methods. Among other insights, these results show that the multi-objective optimization provides improved placement results.

• Record URL:
  https://doi.org/10.1016/j.tre.2016.04.013
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S1366554515302520
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/13665545
• Supplemental Notes:
  • Abstract reprinted with permission of Elsevier.
• Authors:
  • Yi, Zonggen
  • Bauer, Peter H
• Publication Date: 2016-7

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References; Tables;
• Pagination: pp 227-244
• Serial:
  • Transportation Research Part E: Logistics and Transportation Review
  • Volume: 91
  • Publisher: Elsevier
  • ISSN: 1366-5545
  • Serial URL: http://www.sciencedirect.com/science/journal/13665545

Subject/Index Terms

• TRT Terms: Electric vehicle charging; Energy; Infrastructure; Optimization; Urban areas
• Subject Areas: Energy; Highways; Planning and Forecasting;

Filing Info

• Accession Number: 01602106
• Record Type: Publication
• Files: TRIS
• Created Date: Jun 6 2016 4:20PM