Heuristic Method for Optimal Deployment of Electric Vehicle Charge Stations Using Linear Programming
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.
KeywordsGeoreference system Trajectory analysis Multiple connections Plug-in electric vehicle Vehicular density
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.
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