考虑充电不确定性的EVs集群参与削峰服务控制策略研究OA

In the"source-grid-load-storage"system with new energy integration,electric vehicles(EVs)clusters face challenges such as differences in users'charging behaviors and dynamic changes in system demands when participating in peak-shaving auxiliary services.An optimized charging strategy model was proposed integrated with state of charge(SOC)fuzzy control,while considering the degree of peak-shaving demand in different time periods.Taking the maximization of the total expected benefits of both load aggregators and EVs users as the objective,the optimization model was solved by combining genetic algorithm with CPLEX.Case studies show that the proposed SOC fuzzy charging control strategy can balance the charging and discharging willingness of EV users,reserve adjustable capacity for EVs to support peak-shaving services,and maximize the total expected benefits of load aggregators and EV users.This provides a more optimal solution for EV cluster peak-shaving services in the"source-grid-load-storage"system.