Skip to main content

Research Repository

Advanced Search

Historical data based energy management in a microgrid with a hybrid energy storage system

Jia, Ke; Chen, Yiru; Bi, Tianshu; Lin, Yaoqi; Thomas, David W.P.; Sumner, M.

Historical data based energy management in a microgrid with a hybrid energy storage system Thumbnail


Authors

JIE KE JIE.KE@NOTTINGHAM.AC.UK
Research Fellow

Yiru Chen

Tianshu Bi

Yaoqi Lin

David W.P. Thomas

MARK SUMNER MARK.SUMNER@NOTTINGHAM.AC.UK
Professor of Electrical Energy Systems



Abstract

In a micro-grid, due to potential reverse output profiles of the Renewable Energy Source (RES) and the load, energy storage devices are employed to achieve high self-consumption of RES and to minimize power surplus flowing back into the main grid. This paper proposes a variable charging/discharging threshold method to manage energy storage system. And an Adaptive Intelligence Technique (AIT) is put forward to raise the power management efficiency. A battery-ultra-capacitor hybrid energy storage system (HESS) with merits of high energy and power density is used to evaluate the proposed method with onsite measured RES output data. Compared with the PSO algorithm based on the precise predicted data of the load and the RES, the results show that the proposed method can achieve better load smoothing and maximum self-consumption of the RES without the requirement of precise load and RES forecasting.

Citation

Jia, K., Chen, Y., Bi, T., Lin, Y., Thomas, D. W., & Sumner, M. (2017). Historical data based energy management in a microgrid with a hybrid energy storage system. IEEE Transactions on Industrial Informatics, 13(5), 2597-2605. https://doi.org/10.1109/TII.2017.2700463

Journal Article Type Article
Acceptance Date Apr 25, 2017
Online Publication Date May 3, 2017
Publication Date Oct 31, 2017
Deposit Date Mar 6, 2018
Publicly Available Date Mar 6, 2018
Journal IEEE Transactions on Industrial Informatics
Print ISSN 1551-3203
Electronic ISSN 1941-0050
Publisher Institute of Electrical and Electronics Engineers
Peer Reviewed Peer Reviewed
Volume 13
Issue 5
Pages 2597-2605
DOI https://doi.org/10.1109/TII.2017.2700463
Keywords Adaptive intelligent technique (AIT); Energy management; Hybrid energy storage system (HESS); Variable threshold
Public URL https://nottingham-repository.worktribe.com/output/890557
Publisher URL http://ieeexplore.ieee.org/document/7918619/
Additional Information c2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including
reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Files





You might also like



Downloadable Citations