Highlights 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.
Abstract 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.
Optimization models for placement of an energy-aware electric vehicle charging infrastructure
2016-04-28
18 pages
Article (Journal)
Electronic Resource
English
Optimization models for placement of an energy-aware electric vehicle charging infrastructure
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