In this paper, an optimization model for the Charging Station Location Problem of Electric Vehicles for Freight Transportation CSLP-EVFT is presented. This model aims to determine an optimal location strategy of Electric Vehicle Charging Stations EVCSs and the routing plan of a fleet of electric vehicles under battery driving range limitation, in conjunction with the impact on the power distribution system. Freight transportation is modeled under the mobility patterns followed by the Capacitated Vehicle Routing Problem CVRP for contracted fleet, and Shortest Path SP problem for subcontracted fleet. A linear formulation of the power flow is used in order to consider the impact on the electric grid. Several costs are examined, i.e., EVs routing, installation and energy consumption of EVCSs, and energy losses. Although uncertainties related to temporal variation of some aspects (number of customers and their demands, fleet size, power network nodes and routes) are not addressed, the proposed model represents a useful approach to evaluate multiple scenarios or to be introduced within stochastic optimization. Instead, the mathematical model is studied under the variation of EVs travel range that accounts for the advance of battery technology and sensitivity analysis. Additionally, the problem is reduced to a mixed integer non-linear mathematical model, which is linearized by using multivariable Taylor’s series.

Electric Vehicles (EVs) represent a significant option that contributes to improve the mobility and reduce the pollution, leaving a future expectation in the merchandise transportation sector, which has been demonstrated with pilot projects of companies operating EVs for products delivering. In this work a new approach of EVs for merchandise transportation considering the location of Electric Vehicle Charging Stations (EVCSs) and the impact on the Power Distribution System (PDS) is addressed. This integrated planning is formulated through a mixed integer non-linear mathematical model. Test systems of different sizes are designed to evaluate the model performance, considering the transportation network and PDS. The results show a trade-off between EVs routing, PDS energy losses and EVCSs location.

In this paper, the Multi-Depot Electric Vehicle Location Routing Problem with Time Windows (MDVLRP) is addressed. This problem is an extension of the MDVLRP, where electric vehicles are used instead of internal combustion engine vehicles. The recent development of this model is explained by the advantages of this technology, such as the diminution of carbon dioxide emissions, and the support that they can provide to the design of the logistic and energy-support structure of electric vehicle fleets. There are many models that extend the classical VRP model to take electric vehicles into consideration, but the multi-depot case for location-routing models has not been worked out yet. Moreover, we consider the availability of two energy supply technologies: the “Plug-in” Conventional Charge technology, and Battery Swapping Stations; options in which the recharging time is a function of the amount of energy to charge and a fixed time, respectively. Three models are proposed: one for each of the technologies mentioned above, and another in which both options are taken in consideration. The models were solved for small scale instances using C++ and Cplex 12.5. The results show that the models can be used to design logistic and energy-support structures, and compare the performance of the different options of energy supply, as well as measure the impact of these decisions on the overall distance traveled or other optimization objectives that could be worked on in the future.