Despliegue óptimo georreferenciado de estaciones de carga vehicular pública considerando capacidad de flujo y distancias máximas habilitantes

Abstract

Modern challenges are aimed at the significant reduction of greenhouse gases, which deteriorate air quality. The automotive fleet, energy supplies (gas, steam, air conditioning, water for industrial use and electricity) are sources of 〖CO〗_2 that are released into the atmosphere. That is why; this article proposes a heuristic model aimed at significantly reducing dependence on internal combustion vehicles. The success or failure of the massive penetration of plug-in electric vehicles (PEV) will not only depend on the installed capacity in the electrical distribution systems, but also on the autonomy and comfort that the PEV can provide to the end user. Therefore, with the Geolocalised Minimum Station Staging Algorithm (GMSSA), a model capable of deploying infrastructure of public charging stations (IPCE) considering vehicular flow and maximum enabling distances is proposed. In such a way that, the minimum number of public charging stations (PCE) is selected, guaranteeing the possibility that a PEV can connect to a PCE, reducing to the maximum the anxiety of reach of the operator of the PEV.