Flow battery energy storage system for microgrid peak shaving based on predictive control algorithm
Tiancheng Ouyang,
Mingliang Zhang,
Peijia Qin and
Xianlin Tan
Applied Energy, 2024, vol. 356, issue C, No S0306261923018123
Abstract:
Energy storage system is an important component of the microgrid for peak shaving, and vanadium redox flow battery is suitable for small-scale microgrid owing to its high flexibility, fast response and long service time. Therefore, a microgrid based on vanadium redox flow battery is studied for rural applications in this paper, in which biomass gasification and solid oxide fuel cell are integrated as power generation units to provide stable electricity. A predictive control method is presented to improve the efficiency of flow battery and the economic feasibility of this system is evaluated. The mathematical model is validated with the experimental data of published literature. The results indicate that controlling the electrolyte flow rate according to the current and the state of battery can reduce the energy loss of flow battery. The optimal electrolyte flow rate is determined by predictive control method, which can significantly improve the performance of flow battery compared with previous method. The overall efficiency of battery for peak shaving is achieved by 84% and the pay back period of this microgrid system is 7.33 year.
Keywords: Microgrid; Biomass energy; Vanadium redox flow battery; Support vector machine; Peak shaving (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0306261923018123
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:356:y:2024:i:c:s0306261923018123
Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/bibliographic
http://www.elsevier. ... 405891/bibliographic
DOI: 10.1016/j.apenergy.2023.122448
Access Statistics for this article
Applied Energy is currently edited by J. Yan
More articles in Applied Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().