微电网
电池(电)
功率(物理)
汽车工程
计算机科学
荷电状态
灵活性(工程)
能源管理
储能
网格
工程类
电气工程
能量(信号处理)
电压
物理
统计
量子力学
数学
几何学
作者
Qingqing Yang,Jianwei Li,Ruixin Yang,Jin Zhu,Xuechao Wang,Hongwen He
出处
期刊:eTransportation
[Elsevier]
日期:2022-02-01
卷期号:11: 100151-100151
被引量:19
标识
DOI:10.1016/j.etran.2021.100151
摘要
This paper proposes a new hybrid scheme using the EV battery and the local battery as a unit, taking an active part in the grid services. Both electric vehicles and grid-scale battery energy storage have been growing fast in recent years. The active combination of these two kinds of energy sectors is challenging but will unlock extra flexibility at the distribution level. Therefore, the EV battery (EVB) and local battery (LB) are studied in a hybrid scheme for the first time. The scheme delivers an improved optimal power schedule for the fast frequency regulation (FFR) in the microgrid. A hybrid power management strategy based on an improved model predictive control (IMPC) in a microgrid is developed. The IMPC is advanced by adding the battery degradation prediction and EV capacity prediction in the loop and designed for optimal power-sharing with the minimum effect on battery lifetime. The EV battery status, which is critical for both the IMPC and the battery degradation quantification, is predicted by the deep learning approach. The proposed hybrid power management with IMPC is verified to be very effective with optimal power-sharing and battery anti-aging control in the microgrid application.
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