Agent-Based Modelling Approach to Support Strategic Planning for EV Charging Stations in A University Campus

The future of transportation is rapidly transforming with the increasing adoption of electric vehicles (EVs), signifying a global commitment to sustainability. This expansion introduces significant challenges, particularly in the construction and maintenance of EV charging infrastructure. As EV numbers rise, user dissatisfaction due to inadequate charging facilities threatens the adoption of electric mobility. Additionally, the strain on financial and power resources necessitates strategic planning to avoid misallocation. This paper focuses on addressing these challenges within the context of charging stations inside a university campus where these challenges are significantly emerging due to the synchrony of EV users (arrival time, charging time,...) as well as electrical uses with different purposes (charging and other activities) at the same time. To tackle these issues, we propose a Simulation Environment using an Agent-Based Modelling Approach (ABM). We simulate the charging behaviours of EV users, optimize infrastructure deployment, and enhance decision-making for charging station operations thanks to simulations based on real data. The results showed that increasing active charging ports in targeted areas, combined with strict rules banning gasoline vehicles from EV spots, achieved over 90% satisfaction for charged electric vehicles. The performance analysis assessed how parameters like charging port numbers, locations, and policies influenced infrastructure efficiency, helping define an optimal configuration that balances cost while aligning electricity use with the universitys overall consumption.