Heuristic Method for Optimal Deployment of Electric Vehicle Charge Stations Using Linear Programming

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The conventional automobile fleet has significantly increased the emission of toxic gases, thus reducing the quality of air. Therefore, this article proposes a heuristic planning model to promote the massive introduction of plug-in electric vehicles (PEV). Further, this article seeks to deploy electric vehicle charging stations (EVCS), such that the parking time to recharge a PEV are significantly reduced, according to the needs of the user. Besides, the trajectories (driving range) and vehicular flow (traffic) are considered as constraints to the planning problem, which are closely linked to the capacity of the road. On the other hand, clustering techniques are used taking into account real mobility restrictions as a function of minimum distances, and the relationship of the PEV with different charge supply subregions. At last, the model was developed in the Matlab and LpSolve environments. The former will enable the analysis of different trajectories and their relationship with its surroundings. On the other hand, the latter solves the optimization problem using the simplex method.

Original languageEnglish
Title of host publicationApplications of Computational Intelligence - 2nd IEEE Colombian Conference, ColCACI 2019, Revised Selected Papers
EditorsAlvaro David Orjuela-Cañón, Juan Carlos Figueroa-García, Julián David Arias-Londoño
PublisherSpringer
Pages247-258
Number of pages12
ISBN (Print)9783030362102
DOIs
StatePublished - 1 Jan 2019
Event2nd IEEE Colombian Conference on Applications in Computational Intelligence, ColCACI 2019 - Barranquilla, Colombia
Duration: 5 Jun 20197 Jun 2019

Publication series

NameCommunications in Computer and Information Science
Volume1096 CCIS
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference2nd IEEE Colombian Conference on Applications in Computational Intelligence, ColCACI 2019
Country/TerritoryColombia
CityBarranquilla
Period5/06/197/06/19

Bibliographical note

Funding Information:
This work has been conducted with the support of the GIREI (Grupo de Investigaci?n en Redes El?ctricas Inteligentes de la Universidad Polit?cnica Salesiana Ecuador), under the Project Optimal Deployment of Charge Stations required for Smart Cities based on Vehicular Flow.

Funding Information:
Acknowledgement. This work has been conducted with the support of the GIREI (Grupo de Investigación en Redes Eléctricas Inteligentes de la Universidad Politécnica Salesiana Ecuador), under the Project Optimal Deployment of Charge Stations required for Smart Cities based on Vehicular Flow.

Keywords

  • Georeference system
  • Multiple connections
  • Plug-in electric vehicle
  • Trajectory analysis
  • Vehicular density

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