Optimization Approaches for the Optimal Placement of Electrical Charging Stations

Transportation electrification is among the vital solutions for green transport environments. Since the number of electric cars has been increasing, a fast deployment of electric charging stations is needed. However, charging infrastructure costs can be very high, especially if super-fast chargers (level 3) need to be deployed. Moreover, charging stations cannot be installed everywhere due to their high energy consumption. In this context, we herein propose two optimization solutions to solve an assignment problem for a fleet of battery-electric cars and existing points of interest (or stations). The first solution is based on the greedy algorithm (GA) approach, while the second solution is based on linear programming (LP). Different constraints were considered, such as the number of charging stations, maximum capacity of charging stations, final battery state, waiting time, driving style, distance to each station, and charging cost. An illustrative example was used to demonstrate how using a cost function of level 3 chargers coupled with charging costs seriously affects the deployment cost and charging location. The chargers’ installation cost, charging stations’ cost, the maximum number of charging points, the number of charging stations, the final state of charge, and drivers’ different road behaviors were considered in the design of both models. Moreover, a new cost function was injected into the models to determine each battery-electric (BE) car assignment. Using the proposed algorithm, we considered high charging demands for BE cars when reaching their destinations without violating their energy needs.