Rolling optimal scheduling considering electric vehicle users’ willingness

After the grid-connection of large-scale EVs（Electric Vehicles）, their disordered charging and discharging behaviors will bring extremely bad effects on the power system. Therefore, it is very important to aggregate and classify EVs and guide their ordered charging and discharging. However, the demands of different EV users are obviously personalized and diversified. In order to provide accurate services to different EV users, it is necessary to respond to EV users’ willingness. Firstly, the behavioral tendency function is proposed, which contains the information of EVs’ remaining capacity, future travel distance, charging and discharging status in the previous period, stop time, and so on, so as to evaluate the willingness of EV users to actively participate in scheduling. Then, EVs are classified according to the behavioral tendencies of EV users. Finally, the multi-objective optimization function considering the distribution network loss, the matching degree between wind power and load as well as load variance is established to carry out rolling scheduling for classified EVs, so as to determine the optimal scheduling strategy. The improved IEEE 33-bus system is taken as the example for simulation analysis, and the simulative results show that the proposed method can accurately response to EV users’ diversified demands, not only meets the transport needs of EVs, but also improves the whole efficiency of EV charging and discharging, and effectively reduces the distribution network loss and load variance, and improves the matching degree between wind power and load. © 2022 Electric Power Automation Equipment Press. All rights reserved.