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Optimization models for placement of an energy-aware electric vehicle charging infrastructure |
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| Affiliation: | 1. Abengoa Hidrógeno, S.A., Spain;2. Department of Economics, Pablo de Olavide University, Spain;3. Física Teórica, University of Seville, Spain;4. Department of Geography, History and Philosophy, Pablo de Olavide University, Spain;1. DeGroote School of Business, McMaster University, Hamilton, ON, Canada;2. School of Geography and Earth Sciences, McMaster University, Hamilton, ON, Canada;3. School of Computational Science and Engineering, McMaster University, Hamilton, ON, Canada;1. Department of Civil, Construction and Environmental Engineering, Iowa State University, 350 Town Engineering Building, Ames, IA 50011, USA;2. Oak Ridge National Laboratory, National Transportation Research Center, 2360 Cherahala Boulevard, Knoxville, TN 37932, USA |
| 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. |
| Keywords: | Charging infrastructure placement Electric vehicles Energy-aware optimization models Multi-objective optimization |
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