Optimum Scenarios of EV Charging Infrastructure: A Case Study for the Saudi Arabia Market

Abstract

The lack of an EV charging infrastructure is of the top five barriers preventing the adoption of EVs on a large scale. A long charging time is also one of the five barriers, according to the latest survey published by the IEA in 2021. The estimated increase in demand for EVs is a big challenge in many countries all around the world. This challenge exists in many EU and Middle East countries. The main reason for this problem is the requirement of huge funds to install enough public charging points that result in satisfactory charging services. Hence, the phase-out plans of internal combustion engine (ICE) vehicles can be carried out successfully and smoothly. Unfortunately, there is a trade-off between the cost of installing charging points and EV charging time. Therefore, it is important to optimize both factors simultaneously. This way, the charging services can be provided at the minimum possible cost and at a satisfactory level of quality. This study determines the optimum ratio of the number of chargers to the number of EVs in a certain province. The optimal number of chargers that are necessary to optimally serve a certain number of EVs has been determined. Two well-known evolutionary search techniques have solved the optimization problem: particle swarm optimization (PSO) and genetic algorithms (GA). Both algorithms have succeeded in providing many optimal charging infrastructure scenarios. Hence, the decision maker can select the most convenient scenario from several alternatives based on the available budgets and the most convenient charging time.

Keywords

• EV
• electric vehicle
• fast chargers
• public charging points
• residential charger
• optimization techniques