Agent-based modelling of electric vehicle behaviour in a university environment

Abstract

As the number of electric vehicles (EVs) increases, the strategic planning of charging infrastructure becomes a crucial matter. Vehicle parking time takes the longest at home and work. The residential is responsible for 75% of EV charging time, while the workplace is for 14%. The combination of EVs with intermittent energy sources has attracted considerable attention in recent years. It has several advantages, including significantly greening the entire EV usage cycle and attaining financial viability by lowering the direct peak demand on the grid. This study has described the agent-based infrastructure of the EV charging station model on university premises. It lets us obtain the best possible energy supply from solar PV, external batteries, and grid agents. Three charging scenarios (uncontrolled, vehicle-to-grid (V2G), and grid-to-vehicle (G2V)) are constructed and simulated with varying percentages of EV resemblance. Slow charging is included in the G2V scenario to improve the PV benefits in the EV charging model. The simulation result shows that slow charging in the workplace infrastructure increases the PV benefits of EV charging while reducing grid dependency.