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

Jia, Ke and Chen, Yiru and Bi, Tianshu and Lin, Yaoqi and Thomas, David W.P. and Sumner, M. (2017) Historical data based energy management in a microgrid with a hybrid energy storage system. IEEE Transactions on Industrial Informatics, 13 (5). pp. 2597-2605. ISSN 1941-0050

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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.

Item Type: Article
RIS ID: https://nottingham-repository.worktribe.com/output/890557
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.
Keywords: Adaptive intelligent technique (AIT); Energy management; Hybrid energy storage system (HESS); Variable threshold
Schools/Departments: University of Nottingham, UK > Faculty of Engineering > Department of Electrical and Electronic Engineering
Identification Number: https://doi.org/10.1109/TII.2017.2700463
Depositing User: Burns, Rebecca
Date Deposited: 06 Mar 2018 13:07
Last Modified: 04 May 2020 19:14
URI: https://eprints.nottingham.ac.uk/id/eprint/50205

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