Location Selection of Fast-Charging Station for Heavy-Duty EVs Using GIS and Grid Analysis: Preprint

Xiangqi Zhu, Mingzhi Zhang, Barry Mather, Pranav Kulkarni, Andrew Meintz

Research output: Contribution to conferencePaper

Abstract

This work presents a systematic methodology for the location selection of fast-charging stations for heavy-duty Electric Vehicles (EVs) based on both geospatial and electrical grid analysis. The geo-spatial analysis is based on real-world geographic information system (GIS) data of road networks and existing supportive infrastructures. The grid analysis is implemented based on node level analysis of potential impacts on voltages and power losses in distribution system. A case study using realistic three-phase unbalanced distribution feeder from California and extracted real-world GIS data is used to demonstrate the intuitiveness and effectiveness of the proposed methodology for the location selection of fast charging station for heavy duty EVs.
Original languageAmerican English
Number of pages8
StatePublished - 2021
Event2021 IEEE Innovative Smart Grid Technologies - North America (ISGT NA)
Duration: 15 Feb 202118 Feb 2021

Conference

Conference2021 IEEE Innovative Smart Grid Technologies
CityNorth America (ISGT NA)
Period15/02/2118/02/21

Bibliographical note

See NREL/CP-5D00-79800 for paper as published in proceedings

NREL Publication Number

  • NREL/CP-5D00-77823

Keywords

  • fast charging stations
  • GIS
  • grid analysis
  • heavy duty EVs
  • location selection
  • transportation

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