Estimation of Electric Vehicle Schedulable Capacity Considering Vehicle-road-station Interaction and Users’ Bounded Rationality

Electric vehicles (EVs) have a fast response capability, so the accurate estimation of EVs’ schedulable capacity is a premise for exerting its value of flexibility. A schedulable capacity estimation model, with users’ bounded rationality taken into account, is proposed based on the practical background of information interaction among EVs, charging stations and traffic network. The temporal-spatial distribution and charging demand of EVs in traffic network is forecasted according to trip chain simulation. Secondly, a vehicle-road-station interaction model incorporating queuing factors is established to forecast the time and location at which EV connects to power grid. Subsequently, the mutual adjustment relationship between the cost of energy consumption and charging or discharging time is analyzed, aiming to characterize users’ bounded rational energy consumption behaviors for estimating EVs’ schedulable capacity. Finally, the schedulable capacity of EVs is estimated through simulation on a certain traffic network, and the results demonstrate the advantages of the proposed method in accurately estimating EVs’ schedulable capacity.