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Multi-objective optimization of water electrolysis based on coupling model of electrochemistry and multiphase flow.
- Source :
- Journal of Environmental Chemical Engineering; Dec2023, Vol. 11 Issue 6, pN.PAG-N.PAG, 1p
- Publication Year :
- 2023
-
Abstract
- In this paper, a coupling model of electrochemistry and multiphase flow is established, which considers the interaction between electrochemical reactions and the flow regime of gas and liquid. Based on the ANOVA analysis, response surface methodology, and multi-objective optimization, the effects of electrolyte temperature, electrolyte concentration, and inlet velocity on the performance of water electrolysis are further studied. The calculation results show that with the increase of temperature and concentration of electrolyte, the average value of current density gradually increases, but the uniformity of current density and the specific energy consumption will deteriorate. Increasing the inlet velocity can simultaneously improve the average value and the uniformity of current density and specific energy consumption. And the intelligent optimization algorithm is introduced into the field of water electrolysis to obtain the local sensitivity and the Pareto front. Three groups of optimized parameters are determined. Compared with the original parameters, the average value of the current density of the optimized parameters increases by 7.04 % on average, the variance of the current density of that decreases by 28.14 % on average, and the specific energy consumption of the optimized parameters reduces by 45.90 % on average. The empirical correlation between operating parameters and electrolyzer performance is obtained. The research results provide guidance for the design of electrolyzer. [Display omitted] • Establish a coupling model of electrochemistry and multiphase flow. • Develop response surface and genetic algorithm to optimize. • Electrolyte concentration has great impact on water electrolysis performance. • Average value and variance of current density are improved by 7.46 % and 28.48 %. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 22133437
- Volume :
- 11
- Issue :
- 6
- Database :
- Supplemental Index
- Journal :
- Journal of Environmental Chemical Engineering
- Publication Type :
- Academic Journal
- Accession number :
- 174295792
- Full Text :
- https://doi.org/10.1016/j.jece.2023.110985