Multi-layer Real-time Control Strategy for Electric Vehicle Aggregators for Peak Regulation of Power Grid

被引:0
作者
Hu, Junjie [1 ]
Lu, Jiayue [1 ]
Ma, Wenshuai [1 ]
Li, Gengyin [1 ]
Wang, Wen [2 ]
Yang, Ye [2 ]
机构
[1] State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources (North China Electric Power University), Beijing
[2] State Grid Smart Internet of Vehicles Co., Ltd., Beijing
来源
Dianli Xitong Zidonghua/Automation of Electric Power Systems | 2024年 / 48卷 / 22期
基金
中国国家自然科学基金;
关键词
electric vehicle aggregator; model predictive control; multi-layer control system; multi-timescale control;
D O I
10.7500/AEPS20231215003
中图分类号
学科分类号
摘要
The participation of large-scale electric vehicles (EVs) in grid interaction will provide important flexibility resources for new power systems, and currently dispersed EVs have participated in auxiliary services such as peak regulation of power grids through aggregation. Aiming at the problems of low precision and long solving time of the control strategy for peak regulation, a multi-layer real-time control method for large-scale EVs for the peak regulation of power grids is proposed. First, the characteristic quantities are extracted from the historical data of charging stations for cluster analysis. Secondly, the power robust upper and lower boundary model of EVs under different charging requirements is established. Then, based on the model predictive control algorithm, a dual-layer multi-timescale rolling optimization control model is established, and the total power is decomposed and quickly corrected according to the cluster-EV level. Finally, a case is given to verify that the total control accuracy of the proposed control algorithm can reach more than 97%, and the whole period can meet the market assessment demand, and the calculation time of a single period is less than 5 s, which meets the real-time requirement. © 2024 Automation of Electric Power Systems Press. All rights reserved.
引用
收藏
页码:84 / 95
页数:11
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