基于信息间隙决策理论与动态分时电价的电动汽车接入虚拟电厂双层经济调度策略

Bi-level economic dispatch strategy for electric vehicles connecting to virtual power plant based on information gap decision theory and dynamic time-of-use price

针对虚拟电厂(VPP)因分布式电源出力的间隙性以及规模化电动汽车(EV)无序充电行为导致的功率波动问题,将信息间隙决策理论(IGDT)与动态分时电价(DTOUP)模型相结合,提出了一种EV接入VPP的双层经济调度策略,并综合考虑了柔性负荷的灵活性,以保证VPP能够经济、有效地运行。上层采用IGDT对分布式电源出力的间隙性进行鲁棒建模。为了灵活地引导EV聚合商(EVA)进行充放电规划,提出了基于“车-路”信息融合驱动的EV充电模型,并设计了基于模糊隶属度函数的DTOUP模型与整体最优指标,以提高EVA与VPP整体的经济效益。下层结合DTOUP与“车-路”信息,构建了以EVA与VPP交互成本和EV里程焦虑成本最小化为目标的EVA优化调度模型。算例仿真结果验证了所提策略的有效性。

In order to solve the power fluctuation problem of VPP(Virtual Power Plant) caused by the intermittency of distributed generation output and the disordered charging behavior of large-scale EVs(Electric Vehicles),by combining the IGDT(Information Gap Decision Theory) with the DTOUP(Dynamic Time-OfUse Price) model,a bi-level economic dispatch strategy for EVs connecting to VPP is proposed,and the flexibility of flexible load is taken into account to ensure that the VPP can operate economically and effectively. In the upper level,IGDT is used to robustly model the intermittency of distributed generation output.In order to flexibly guide EVA(Electric Vehicle Aggregator) in charging and discharging planning,the EV charging model driven by“EV-road”information fusion is proposed,and the DTOUP model based on fuzzy membership function and the overall optimal index are designed to improve the overall economic benefits of EVA and VPP. In the lower level,combining DTOUP and“EV-road”information,the EVA optimal dispatch model is constructed with the goal of minimizing the interaction cost between EVA and VPP and the EV range anxiety cost. Simulative results verify the effectiveness of the proposed strategy.