1.College of Electrical Engineering and Control Science, Nanjing Tech University, Nanjing 211816, China;2.Nantong Power Supply Company of State Grid Jiangsu Electric Power Co., Ltd., Nantong 226006, China
In order to avoid the impact of disordered charging of numerous electric vehicles (EVs) on secure and economic operation of power system, a day-ahead scheduling strategy of distribution network considering vehicle-to-grid (V2G) auxiliary service is proposed. Firstly, based on the history and real-time information of the smart grid and Internet of Things, the charging and discharging model of EVs is established, and the selection and classification of EV auxiliary service participants are carried out. Secondly, a bi-level optimal economic scheduling model of distribution network considering V2G auxiliary services is built. The upper level aims at minimizing grid loss cost, EV power cost and system load variance, and optimizes the charging and discharging power of the charging stations and the operating state of the voltage regulating equipment. The lower one is devoted to minimizing the switch time of EV charging and discharging state and the deviation between the charging station power and the upper optimization result, and figures out the charging and discharging power of each EV participant. Finally, the results of the example system verify the effectiveness of the proposed method.
This work is supported by Six Talent Peaks Project in Jiangsu Province (No. XNY-020).
|||HAO Lili, WANG Guodong, WANG Hui, et al. Day-ahead Scheduling Strategy of Distribution Network Considering Electric Vehicle-to-Grid Auxiliary Service[J]. Automation of Electric Power Systems,2020,44(14):35-43. DOI:10.7500/AEPS20190911002|