Dynamic electric vehicle charging load modeling: From perspective of transportation

This paper proposes a methodology to model and analyze the impact of large scale adoption of electric vehicles (EVs) as movable charging loads in power system and transportation network based on driving pattern. A driving pattern model is introduced to emulate the spatial and temporal randomness of EVs. Several important variables can be obtained, including parking locations, trip distances, driving times, parking durations and charging durations. The aggregated EV charging loads at each bus of power system are determined by Monte Carlo simulation (MCS) based on the number of charging EVs at the corresponding charging station of transportation network. The simulation result shows that the number of parking EVs and EV charging loads profile vary among different locations and nodes. Driving pattern plays a key role in EV charging load modeling.