Modeling Electric Vehicle Charging Load on Power Grid Considering Travel Behavior

Electric vehicle (EV) usage increases every year, yet there is no accurate model to predict traveling or charging behavior. Current working models present inaccurate data as well as showing the same daily demand at different locations. These models do not consider the variations of human behavior and differences in geographic areas. However, an agent-based modeling (ABM) system is able to track individuals in a simulation to predict their behavior. NetLogo is an ABM platform implemented to show the behavior of EVs. Through the ABM simulation, travelers were simulated and recorded to predict their future load demand realistically and accurately on the grid. This simulation showed different peak times and load amounts between locations and slight differences in each iteration as expected. These results show a more accurate prediction of future EV load demand based on the input data such as vehicle type ratio, number of vehicles, and average range of city.