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MASEV: A MAS for the Analysis of Electric Vehicle Charging Stations Location

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Advances in Practical Applications of Agents, Multi-Agent Systems, and Complexity: The PAAMS Collection (PAAMS 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10978))

Abstract

Electric vehicles are already a reality in many cities around the world. However, the penetration of the electric vehicle depends on several factors, including the existence of an adequate network of charging stations. This article aims to address this problem by defining a multi-agent system (MAS) that collects information about the state of a city and proposes different configurations for the location of charging stations. More specifically, the proposed system integrates information from heterogeneous data sources and applies a genetic algorithm to characterize the areas where charging stations could potentially be located. The system has been tested with real information from the city of Valencia (Spain).

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Notes

  1. 1.

    General Urban Development Plan.

References

  1. Electromaps: Electromaps: Puntos de recarga en Valencia (2017). https://www.electromaps.com/puntos-de-recarga/espana/valencia

  2. Klabjan, D., Sweda, T.: The nascent industry of electric vehicles. In: Wiley Encyclopedia of Operations Research and Management Science (2011)

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  3. Wolfram, P., Lutsey, N.: Electric vehicles: literature review of technology costs and carbon emissions. Technical report, The International Council on Clean Transportation (2016)

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Acknowledgments

This work was partially supported by MINECO/FEDER TIN2015-65515-C4-1-R and MOVINDECI project of the Spanish government.

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Correspondence to J. Palanca .

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Jordán, J., Palanca, J., del Val, E., Julian, V., Botti, V. (2018). MASEV: A MAS for the Analysis of Electric Vehicle Charging Stations Location. In: Demazeau, Y., An, B., Bajo, J., Fernández-Caballero, A. (eds) Advances in Practical Applications of Agents, Multi-Agent Systems, and Complexity: The PAAMS Collection. PAAMS 2018. Lecture Notes in Computer Science(), vol 10978. Springer, Cham. https://doi.org/10.1007/978-3-319-94580-4_31

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  • DOI: https://doi.org/10.1007/978-3-319-94580-4_31

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-94579-8

  • Online ISBN: 978-3-319-94580-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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