Optimal Planning of Electric Vehicle Charging Stations Considering Traffic Load for Smart Cities

Abstract

The massive introduction of electric vehicles as a mobility alternative requires deploying an infrastructure of charging stations for electric cars (ICSEC). This new mobility concept will mitigate the environmental harm caused by the emission of CO2 generated by conventional internal combustion mobility methods. The sustainability of the ICSEC depends not only on the capacity to meet the demand for charging batteries for electric vehicles (EV) but also on an adequate number of public/private charging stations (CS) distributed in a geolocalized area. It is noted that the distribution of CS must respond to a set of real mobility constraints, such as vehicular flow capacity, road capacity, and trajectories. The planning, intelligent location of public charging stations (PCS), and contingency analysis will enable us to study the increase in demand for electrical distribution substations (EDS). Therefore, the present model explains the need to plan the massive introduction of EVs by observing the user’s conditions at the trajectory level through finite resource allocation processes, segmentation, and minimum spanning trees, by observing heterogeneous vehicular flow criteria through microscopic analysis, to understand the space–time relationship of vehicular flow in georeferenced scenarios. Consequently, the computational complexity of the model is of the combinatorial type, and it is defined as NP-Hard given the multiple variables and constraints within the transportation problem.