Predicting popularity of EV charging infrastructure from GIS data

@article{Straka2019PredictingPO,
  title={Predicting popularity of EV charging infrastructure from GIS data},
  author={M. Straka and P. D. Falco and Gabriella Ferruzzi and D. Proto and G. V. D. Poel and Shahab Khormali and Lubo{\vs} Buzna},
  journal={ArXiv},
  year={2019},
  volume={abs/1910.02498}
}
  • M. Straka, P. D. Falco, +4 authors Luboš Buzna
  • Published 2019
  • Computer Science, Mathematics, Economics
  • ArXiv
  • The availability of charging infrastructure is essential for large-scale adoption of electric vehicles (EV). Charging patterns and the utilization of infrastructure have consequences not only for the energy demand, loading local power grids but influence the economic returns, parking policies and further adoption of EVs. We develop a data-driven approach that is exploiting predictors compiled from GIS data describing the urban context and urban activities near charging infrastructure to explore… CONTINUE READING
    1 Citations

    Figures and Tables from this paper

    References

    SHOWING 1-10 OF 55 REFERENCES
    Data analysis on the public charge infrastructure in the city of Amsterdam
    • 24
    • PDF
    Indicator-based methodology for assessing EV charging infrastructure using exploratory data analysis
    • 17
    • Highly Influential
    • PDF
    Optimal fast charging station placing and sizing
    • 206
    Optimal Planning of Electric-Vehicle Charging Stations in Distribution Systems
    • 358