Optimal deployment of fast-charging stations for electric vehicles considering the sizing of the electrical distribution network and traffic condition

The conventional vehicle fleet worldwide has contributed to the degradation of air quality due to CO₂ emissions. Consequently, it has migrated from internal combustion to electric vehicles (EVs). However, it is essential to ensure the deployment of electric vehicle charging station infrastructures (EVCSI) to guarantee their interoperability for the development of electric mobility. Moreover, the sustainability of EVCSI depends not only on the capacity to meet demand but also on the adequate number of terminals in the different public charging stations (CS) to reduce waiting times for battery recharging. Then to achieve an optimal sizing of charging stations, it is crucial to foresee the maximum number of vehicles that could use the different CS during a time interval. The sizing of CS must respond to real mobility constraints and technical conditions, such as the capacity of vehicular flow, the capacity of the roads according to their geometry, the trajectories marked by the users, and the possible exit of operation of some CS. Therefore, this paper addresses the problem considering four fundamental axes, which are: stochastic analysis of heterogeneous vehicular flow, a solution to the transportation problem with the capacitated multicommodity flow problem and Hungarian algorithm, analysis of the optimal number of terminals considering loading times, and finally the proposed EVCSI will be validated using the CymDist software for electrical engineering. Consequently, the computational complexity of the model is of a combinatorial type and is defined as NP-hard given the multiple variables and constraints within the transportation problem.