波动工况下碱性水电解制氢运行操作参数可行域分析与多目标优化

doi:10.19595/j.cnki.1000-6753.tces.251693

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Abstract

Alkaline water electrolysis (AWE) powered by renewable energy is a primary pathway for large-scale hydrogen production. However, the intermittency and volatility of renewable energy impose operational challenges. Input power fluctuations cause temperature changes and elevated HTO concentrations, which compromise system safety. Existing control strategies, which adopt either constant operating parameters or linear adjustments based on input power, are insufficient under fluctuating conditions. To address these issues, this study proposes a coordinated control method for AWE based on feasible domain analysis and multi-objective optimization of operating parameters.
First, an accurate multi-physics dynamic model is established, coupling heat transfer, gas crossover, mass transport, and system efficiency. This model analyzes how power fluctuations and parameter adjustments affect temperature, gas crossover, mass transport, and efficiency. The results show that reducing pressure and circulation flow rate suppresses gas crossover and lowers HTO concentration, but at the expense of system efficiency. Moreover, the mass transport process within the separator is identified as the primary factor leading to the slow response of HTO concentration, reducing pressure or increasing current density can effectively shorten the mass transport time.
Then, strict safety constraints are introduced based on the multi-physics model to investigate how temperature variations affect the operational safety boundaries. These safety constraints are then reformulated as boundaries of temperature, current density, pressure, and circulation flow rate. By combining these safety boundaries, the feasible domain of operational parameters is determined, and its variation under fluctuating operating conditions is analyzed. The results show that moderately reducing the pressure can improve the lower power limit, and adjusting the circulating flow rate according to the input power can enhance the adaptability of AWE to power fluctuations.
On this basis, coordinated regulation of pressure and circulation flow rate is implemented using the electrolyzer temperature and input power sequence as references. With energy utilization, HTO concentration, and system efficiency as objectives, the feasible domain constraints are incorporated into a penalty-function-based optimization framework. A multi-objective evolutionary algorithm based on decomposition (MOEA/D) is employed to obtain the Pareto-optimal set, and receding-horizon optimization is further applied to ensure smooth adjustment of operational parameters and generate the optimal control sequence.
Finally, the model is validated using real AWE data, and the method is evaluated in a photovoltaic hydrogen production scenario. The results demonstrate that the proposed strategy effectively extends the lower operating power limit of AWE, maintains HTO concentration within the safety threshold, improves system efficiency by 2.05%, increases total hydrogen production by 30.7%, and reduces hydrogen production cost by 18.07%. Overall, the study shows that temperature fluctuations under renewable power supply reshape the feasible domain, and coordinated adjustment of operational parameters according to temperature and input power can reduce HTO concentration and enhance system efficiency, thereby strengthening the adaptability of AWE to fluctuating renewable energy conditions.

Key words： Alkaline water electrolysis fluctuating conditions strict safety constraints operating parameters feasible domain multi-objective optimization

Received: 30 September 2025

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TK91

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	Yang Fuquan
	Yan Rongge
	Sun Hexu
	Lei Zhaoming
	Liu Bin

Cite this article:

Yang Fuquan,Yan Rongge,Sun Hexu等. Feasible Domain Analysis and Multi-Objective Optimization of Operating Parameters for Alkaline Water Electrolysis Hydrogen Production under Fluctuating Operating Conditions[J]. Transactions of China Electrotechnical Society, 0, (): 20251693-.

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