부산대학교 도서관

In the day-ahead market, load aggregators can participate in market-based trading through rational scheduling of EV charging and discharging. This paper investigates the method to predict the dispatchable potential of electrical vehicle (EV) clusters under the vehicle network interaction. Firstly, a Monte Carlo method was used to simulate the charging and discharging load characteristics of EV clusters; secondly, based on the Minkowski summation Virtual Battery (VB) model, a large-scale single EV storage model is converted into a virtual storage cluster to obtain the maximum charging and discharging power and electric energy boundaries of EV clusters at a time, which can be applied by load aggregators to implement different vehicle-grid interaction strategies and to participate in day-ahead market transactions.