Simulation-Based Evaluation of EV Charging Configurations and Carbon Reduction Potential in a University Commuter System

This paper examines the performance and potential of CO2 reduction of different configurations of electric vehicle charging infrastructure within a university commuter model, incorporating a simulated population and a discrete event simulation model. A commuter population dataset is created from ZIP code-based population assignment, distance-band approach, and personalized driving pattern models. Various charging infrastructure setups involving level 2 charging and level 3 charging were simulated for 30-day periods, with performance metrics such as wait-time, peak demand, use factor, and infrastructure cost appropriately evaluated. It is seen that performance characteristics significantly enhance beyond a base infrastructure level of 45 level 2 charging stations, with wait times diminishing close to zero levels for most level 3 charging setups. A WCDM decision makers strategy shows the charging setups of (L2=5, L3=0), and (L2=6, L3=0) charging setups being most cost-effective charging options with charging setups involving one level 3 charging station being viable options with excellent performance matrices. Results from CO2 emission calculations reveal net emission a decent reduction potential every month with an eventual shift from internal-combustion engine vehicles to electric vehicles among the simulated commuter population dataset pool.