Electric Vehicles Charging Network Planning

Chapter
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 262)

Abstract

In this chapter we propose a method to plan the location of charging stations for electric vehicles (EV) in a city in which the objective is to maximize the number of satisfied vehicles under a fixed budget for building the stations. We take into consideration the maximum capacity of each possible site for installing a station, in terms of the number of plugs that each one can have, and the distance from that location and each demand point, which is measured in walking time. To be able to apply these models, we develop a charging demand model for based on parking data, considering that the higher the parking time, the greater the probability of charging. We also take in consideration the relation between the demand at different points, e.g., if a vehicle can charge at home, the probability of needing to charge at work will be significantly reduced. We test our mathematical models for the case of the city of Coimbra, where there is already a network of charging stations. We first use an existing mobility survey to extract parking data and establish a demand grid, and then we apply the models that gives us the optimal location for charging stations for the entire city allowing us to compare both.

Keywords

Electric vehicle Charging stations planning Mixed integer problem Charging demand 

Notes

Acknowledgments

Support for this work was provided by Project mobiOS—mobility Operating System, financed by COMPETE/QREN—Agência de Inovação. The authors would like to thank Metro Mondego for making available the data used in the case-study and Intergraph for providing the software Geomedia Professional 6. Gouveia was also supported by the Centre for Mathematics at the University of Coimbra and Fundação para a Ciência e a Tecnologia, through the European program COMPETE/FEDER.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Joana Cavadas
    • 1
  • Gonçalo Correia
    • 2
  • João Gouveia
    • 1
  1. 1.Department of MathematicsUniversity of CoimbraCoimbraPortugal
  2. 2.Department of Civil EngineeringUniversity of CoimbraCoimbraPortugal

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