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

• An energy-aware optimization framework is proposed for charging station placement.
• Multi-objective optimization model with two energy-aware criteria is introduced.
• A detailed EV energy cost model is employed to construct optimization models.
• Mesh adaptive direct search method for solving proposed models is utilized.
• Real world datasets are investigated to perform the case studies.

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.