Optimal Location of Charging Stations in Road Networks: A Coverage Approach with Electrical Relief and Infrastructure

This paper presents a methodology for optimal location of electric stations in road networks, combining open geospatial data, relief and existing electrical infrastructure. The road network is represented as a primal graph, in which intersections and connection points are treated as demand nodes and road stretches as weighted edges. The altitude of the nodes is extracted from a mosaic of the MDE Topodata/INPE and incorporated into the cost of autonomy through a linear penalty associated with the elevation gain. Candidates for electric stations are generated from the electrical infrastructure near the highways and evaluated by minimum network paths. The problem is formulated as a model of covering sets, solved exactly by means of the Gurobi solver. The results indicate optimal solutions between 22 and 36 electric stations in the analyzed scenarios, with total coverage conditioned to the spatial availability of the candidates.