Abstract
Alkaline water electrolysis (AWE) is the most mature electrochemical technology for hydrogen production from renewable electricity. Thus, its mathematical modeling is an important tool to provide new perspectives for the design and optimization of energy storage and decarbonization systems. However, current models rely on numerous empirical parameters and neglect variations of temperature and concentration alongside the electrolysis cell, which can impact the application and reliability of the simulation results. Thus, this study proposes a simple four-parameter semi-empirical model for AWE system analysis, which relies on minimal fitting data, while providing reliable extrapolation results. In addition, the effect of model dimensionality (i.e., 0D, 1/2D and 1D) are carefully assessed in the optimization of an AWE system. The results indicate that the
proposed model can accurately reproduce literature data from four previous works (R2 ≥ 0.98), as well as new experimental data. In the system optimization, the trade-offs existing in the lye cooling sizing highlight that maintaining a low temperature difference in AWE stacks (76–80 ◦C) leads to higher efficiencies and lower hydrogen costs.
proposed model can accurately reproduce literature data from four previous works (R2 ≥ 0.98), as well as new experimental data. In the system optimization, the trade-offs existing in the lye cooling sizing highlight that maintaining a low temperature difference in AWE stacks (76–80 ◦C) leads to higher efficiencies and lower hydrogen costs.
Original language | English |
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Article number | 125154 |
Number of pages | 15 |
Journal | Applied Thermal Engineering |
Volume | 262 |
DOIs | |
Publication status | Published - 1 Mar 2025 |