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

Miguel Campaña; Esteban Inga

doi:10.1007/978-3-030-36211-9_20

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

Miguel Campaña, Esteban Inga

Research Group on Smart Electrical Grids (GIREI)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

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 language	English
Title of host publication	Applications of Computational Intelligence - 2nd IEEE Colombian Conference, ColCACI 2019, Revised Selected Papers
Editors	Alvaro David Orjuela-Cañón, Juan Carlos Figueroa-García, Julián David Arias-Londoño
Publisher	Springer
Pages	247-258
Number of pages	12
ISBN (Print)	9783030362102
DOIs	https://doi.org/10.1007/978-3-030-36211-9_20
State	Published - 1 Jan 2019
Event	2nd IEEE Colombian Conference on Applications in Computational Intelligence, ColCACI 2019 - Barranquilla, Colombia Duration: 5 Jun 2019 → 7 Jun 2019

Publication series

Name	Communications in Computer and Information Science
Volume	1096 CCIS
ISSN (Print)	1865-0929
ISSN (Electronic)	1865-0937

Conference

Conference	2nd IEEE Colombian Conference on Applications in Computational Intelligence, ColCACI 2019
Country/Territory	Colombia
City	Barranquilla
Period	5/06/19 → 7/06/19

Bibliographical note

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.

Publisher Copyright:
© Springer Nature Switzerland AG 2019.

Keywords

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

Access to Document

10.1007/978-3-030-36211-9_20

Cite this

Campaña, M., & Inga, E. (2019). Heuristic Method for Optimal Deployment of Electric Vehicle Charge Stations Using Linear Programming. In A. D. Orjuela-Cañón, J. C. Figueroa-García, & J. D. Arias-Londoño (Eds.), Applications of Computational Intelligence - 2nd IEEE Colombian Conference, ColCACI 2019, Revised Selected Papers (pp. 247-258). (Communications in Computer and Information Science; Vol. 1096 CCIS). Springer. https://doi.org/10.1007/978-3-030-36211-9_20

Campaña, Miguel ; Inga, Esteban. / Heuristic Method for Optimal Deployment of Electric Vehicle Charge Stations Using Linear Programming. Applications of Computational Intelligence - 2nd IEEE Colombian Conference, ColCACI 2019, Revised Selected Papers. editor / Alvaro David Orjuela-Cañón ; Juan Carlos Figueroa-García ; Julián David Arias-Londoño. Springer, 2019. pp. 247-258 (Communications in Computer and Information Science).

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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.",

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author = "Miguel Campa{\~n}a and Esteban Inga",

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Campaña, M & Inga, E 2019, Heuristic Method for Optimal Deployment of Electric Vehicle Charge Stations Using Linear Programming. in AD Orjuela-Cañón, JC Figueroa-García & JD Arias-Londoño (eds), Applications of Computational Intelligence - 2nd IEEE Colombian Conference, ColCACI 2019, Revised Selected Papers. Communications in Computer and Information Science, vol. 1096 CCIS, Springer, pp. 247-258, 2nd IEEE Colombian Conference on Applications in Computational Intelligence, ColCACI 2019, Barranquilla, Colombia, 5/06/19. https://doi.org/10.1007/978-3-030-36211-9_20

Heuristic Method for Optimal Deployment of Electric Vehicle Charge Stations Using Linear Programming. / Campaña, Miguel; Inga, Esteban.
Applications of Computational Intelligence - 2nd IEEE Colombian Conference, ColCACI 2019, Revised Selected Papers. ed. / Alvaro David Orjuela-Cañón; Juan Carlos Figueroa-García; Julián David Arias-Londoño. Springer, 2019. p. 247-258 (Communications in Computer and Information Science; Vol. 1096 CCIS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Inga, Esteban

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Y1 - 2019/1/1

N2 - 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.

AB - 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.

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Campaña M, Inga E. Heuristic Method for Optimal Deployment of Electric Vehicle Charge Stations Using Linear Programming. In Orjuela-Cañón AD, Figueroa-García JC, Arias-Londoño JD, editors, Applications of Computational Intelligence - 2nd IEEE Colombian Conference, ColCACI 2019, Revised Selected Papers. Springer. 2019. p. 247-258. (Communications in Computer and Information Science). doi: 10.1007/978-3-030-36211-9_20

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

Abstract

Publication series

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Bibliographical note

Keywords

Access to Document

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