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ChargeMap: An Electric Vehicle Charging Station Planning System

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Web and Big Data (APWeb-WAIM 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10367))

Abstract

The deployment optimization of charging stations is meaningful for the promotion of electric vehicles. The traditional approaches of charging station planning are mostly lack of comprehensive consideration. Some factors cannot be fully considered and effectively quantified in those approaches, such as the load of power grid, charging demand, transportation cost, construction cost, etc. This demo presents ChargeMap, a novel system of electric vehicle charging station planning which based on a multi-factor optimization model. ChargeMap could attain a balance among the factors that have great influence on charging station planning. What’s more, it delivers an apropos approach to quantify these factors. In this demo, we bring forth the application of ChargeMap on the real data sets of power grid, population, transportation and real estate of Beijing, which delivers an effective solution to the optimization of charging station planning.

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References

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Acknowledgments

This work was supported by State Grid Basic Research Program (DZ71-15-004).

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Authors and Affiliations

  1. Key Lab of High Confidence Software Technologies (MOE), School of EECS, Peking University, Beijing, 100871, China

    Longlong Xu, Wutao Lin, Zhenhui Xu, Wei Chen & Tengjiao Wang

  2. Technology and Strategy Research Center, China Electric Power Research Institute, Beijing, 100192, China

    Xiaorong Wang

Authors
  1. Longlong Xu
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  2. Wutao Lin
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  3. Xiaorong Wang
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  4. Zhenhui Xu
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  5. Wei Chen
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  6. Tengjiao Wang
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Corresponding author

Correspondence to Wei Chen .

Editor information

Editors and Affiliations

  1. Computer Science and Engineering, Hong Kong University of Science and Technology, Hong Kong, China

    Lei Chen

  2. Computer Science, Aarhus University, Aarhus N, Denmark

    Christian S. Jensen

  3. Computer Science, University of Southern California, Los Angeles, California, USA

    Cyrus Shahabi

  4. Northeastern University , Shenyang, China

    Xiaochun Yang

  5. Kent State University, Kent, Ohio, USA

    Xiang Lian

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© 2017 Springer International Publishing AG

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Cite this paper

Xu, L., Lin, W., Wang, X., Xu, Z., Chen, W., Wang, T. (2017). ChargeMap: An Electric Vehicle Charging Station Planning System. In: Chen, L., Jensen, C., Shahabi, C., Yang, X., Lian, X. (eds) Web and Big Data. APWeb-WAIM 2017. Lecture Notes in Computer Science(), vol 10367. Springer, Cham. https://doi.org/10.1007/978-3-319-63564-4_31

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  • DOI: https://doi.org/10.1007/978-3-319-63564-4_31

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-63563-7

  • Online ISBN: 978-3-319-63564-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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