LAPSE:2023.30786
Published Article
LAPSE:2023.30786
Operational Parameter Analysis and Performance Optimization of Zinc−Bromine Redox Flow Battery
Ye-Qi Zhang, Guang-Xu Wang, Ru-Yi Liu, Tian-Hu Wang
April 17, 2023
Zinc−bromine redox flow battery (ZBFB) is one of the most promising candidates for large-scale energy storage due to its high energy density, low cost, and long cycle life. However, numerical simulation studies on ZBFB are limited. The effects of operational parameters on battery performance and battery design strategy remain unclear. Herein, a 2D transient model of ZBFB is developed to reveal the effects of electrolyte flow rate, electrode thickness, and electrode porosity on battery performance. The results show that higher positive electrolyte flow rates can improve battery performance; however, increasing electrode thickness or porosity causes a larger overpotential, thus deteriorating battery performance. On the basis of these findings, a genetic algorithm was performed to optimize the batter performance considering all the operational parameters. It is found that the battery energy efficiency can reach 79.42% at a current density of 20 mA cm−2. This work is helpful to understand the energy storage characteristics and high-performance design of ZBFB operating at various conditions.
Keywords
2D transient model, Genetic Algorithm, large-scale energy storage, operational parameters, Optimization, zinc–bromine redox flow battery
Suggested Citation
Zhang YQ, Wang GX, Liu RY, Wang TH. Operational Parameter Analysis and Performance Optimization of Zinc−Bromine Redox Flow Battery. (2023). LAPSE:2023.30786
Author Affiliations
Zhang YQ: Department of Mathematics and Physics, North China Electric Power University, Beijing 102206, China
Wang GX: Department of Mathematics and Physics, North China Electric Power University, Beijing 102206, China [ORCID]
Liu RY: Key Laboratory of Power Station Energy Transfer Conversion and System, Ministry of Education, North China Electric Power University, Beijing 102206, China; School of Energy Power and Mechanical Engineering, North China Electric Power University, Beijing 1
Wang TH: Key Laboratory of Power Station Energy Transfer Conversion and System, Ministry of Education, North China Electric Power University, Beijing 102206, China; School of Energy Power and Mechanical Engineering, North China Electric Power University, Beijing 1
Journal Name
Energies
Volume
16
Issue
7
First Page
3043
Year
2023
Publication Date
2023-03-27
Published Version
ISSN
1996-1073
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PII: en16073043, Publication Type: Journal Article
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doi:10.3390/en16073043
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