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.
|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|
|Number of pages||12|
|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
|Name||Communications in Computer and Information Science|
|Conference||2nd IEEE Colombian Conference on Applications in Computational Intelligence, ColCACI 2019|
|Period||5/06/19 → 7/06/19|
Bibliographical noteFunding 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.
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.
- Georeference system
- Multiple connections
- Plug-in electric vehicle
- Trajectory analysis
- Vehicular density