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Energy-Management Strategy of Battery Energy Storage Systems in DC Microgrids: A Distributed Dynamic Event-Triggered H ∞ Consensus Control.

Authors :
Wang, Rui
Sun, Qiuye
Han, Ji
Zhou, Jianguo
Hu, Wei
Zhang, Huaguang
Wang, Peng
Source :
IEEE Transactions on Systems, Man & Cybernetics. Systems. Sep2022, Vol. 52 Issue 9, p5692-5701. 10p.
Publication Year :
2022

Abstract

Distributed renewable energy source is an advisable solution for dc microgrids to reduce fuel consumption and CO2 emission. In such microgrids, the installation of two or more battery energy storage (BES) units is utilized to compensate the power imbalance between the sources and loads. Nevertheless, energy management with numerous BES units does not simultaneously consider the impacts of distributed generators (DGs) and constant power loads (CPLs). Since the inaccurate current sharing will shorten the lifetime of the batteries and cause instability problem, this article proposes a distributed secondary $H_{\infty }$ consensus approach based on the dynamic event-triggered communication method to realize accurate current sharing and efficient operation in the presence of numerous DGs and CPLs. First, the whole state-space function model of the dc microgrid consisting of DGs, batteries, resistive loads, and CPLs, is first built in detail. This model is further transformed into standard linear heterogeneous multiagent systems, which provides an indispensable preprocessing for advanced control strategy application. Then, the distributed secondary $H_{\infty }$ consensus approach based on the foresaid systems is designed to achieve accurate current sharing. For reducing the communication among batteries and the controller updating frequency, the dynamic event-triggered communication method is proposed. Compared with existing event-triggered methods, the communication and controller updating frequency of the proposed dynamic event-triggered method have been reduced a lot. Additionally, the proposed method can not only avoid the Zeno behavior, but also obtain the lowest bound of the sampled time interval. Finally, the numerical simulation results and experimental results verify the effectiveness of the proposed control strategy. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
21682216
Volume :
52
Issue :
9
Database :
Academic Search Index
Journal :
IEEE Transactions on Systems, Man & Cybernetics. Systems
Publication Type :
Academic Journal
Accession number :
158603859
Full Text :
https://doi.org/10.1109/TSMC.2021.3129184