Optimal Allocation of Public Charging Stations based on Traffic Density in Smart Cities

Miguel Campaña, Esteban Inga

Research output: Contribution to conferencePaper

Abstract

Plug-in electric vehicle (PEV) massive introduction will contribute to improve the air quality, however, the limited driving range might cause few interests for the potential consumers of this new alternative mobility. Therefore, it's essential that public charging stations (PCS) are planning through optimal deployments, this guarantee that PEV operators lay out PCS that contemplate maxim reach distance. Thus, Article contributes for PCS optimal deployment with traffic flow restrictions, driving maxim distance, load density and relation of PEV with infrastructure environment of load public station (IPCS); besides, PCS in need of multiple connections (slow, fast and ultra-fast charging). Finally, proposed heuristic considers a theoretical model with spatial approach. Study region data was obtained by means of osm file, courtesy of OpenStreetMap platform. Hence, the model knows areas and cartography reality, hereafter cartography reality displaces PCS for PEV.

Original languageEnglish
Pages1-6
Number of pages6
DOIs
StatePublished - 1 Jun 2019
Event2019 IEEE Colombian Conference on Applications in Computational Intelligence, ColCACI 2019 - Proceedings -
Duration: 1 Jun 2019 → …

Conference

Conference2019 IEEE Colombian Conference on Applications in Computational Intelligence, ColCACI 2019 - Proceedings
Period1/06/19 → …

Keywords

  • georeferenced system
  • graph theory
  • heuristic
  • multiple connections
  • Plug-in electric vehicle
  • vehicular traffic

Fingerprint

Dive into the research topics of 'Optimal Allocation of Public Charging Stations based on Traffic Density in Smart Cities'. Together they form a unique fingerprint.

Cite this