CIESC Journal ›› 2023, Vol. 74 ›› Issue (3): 1260-1274.DOI: 10.11949/0438-1157.20221595

• Energy and environmental engineering • Previous Articles     Next Articles

Multi-objective optimization of high-efficiency solar water electrolysis hydrogen production system and its performance

Sheng’an ZHANG(), Guilian LIU()   

  1. School of Chemical Engineering and Technology, Xi’an Jiaotong University, Xi’an 710049, Shaanxi, China
  • Received:2022-12-10 Revised:2023-01-04 Online:2023-04-19 Published:2023-03-05
  • Contact: Guilian LIU


张生安(), 刘桂莲()   

  1. 西安交通大学化学工程与技术学院,陕西 西安 710049
  • 通讯作者: 刘桂莲
  • 作者简介:张生安(1995—),男,博士研究生,
  • 基金资助:


Given the growing demand for clean and sustainable production technologies of green hydrogen, an efficient solar-based system with power and hydrogen production integrated has been developed. The system consists of a tower solar power generation and thermal energy storage system, a proton exchange membrane (PEM) electrolysis water system, a reheated steam Rankine cycle with a regenerator and an organic Rankine cycle waste heat recovery subsystem with a regenerator. Energy cascade utilization can be realized. The integrated system is simulated in Aspen Plus software, and the mathematical models of the solar heliostat field and PEM electrolyzer are written in Fortran language and embedded. Based on the non-dominated sorting genetic algorithm-Ⅱ (NSGA-Ⅱ) and the interaction between Aspen Plus and MATLAB software, the trade-off between maximum exergy efficiency, maximum output electrical energy per day, and minimum levelized cost of hydrogen (LCOH) is performed through multi-objective optimization. The Pareto frontier shows that the optimal exergy efficiency and output electrical energy per day are 52.19% and 247.352 MWh/d, increased by 3.00% and 31.14%, respectively; the LCOH is 6.05 USD/kg, decreased by 4.87%, and the optimal hydrogen production capacity is 4.796 t/d. This study has specific guiding significance for large-scale solar power generation and hydrogen production.

Key words: solar power tower, electrolysis, hydrogen production, integration, algorithm, multi-objective optimization


针对日益重要的清洁可持续绿氢生产技术需求,开发了一种基于太阳能,集发电和制氢于一体的高效系统。该系统由塔式太阳能发电和热能存储系统、质子交换膜(PEM)电解水系统和含有回热器的再热式蒸汽朗肯循环及含有回热器的有机朗肯循环余热回收子系统组成,可实现能量梯级利用。在Aspen Plus中建立了各子系统的模拟模型,并用Fortran语言编写太阳能定日镜场和PEM电解槽数学模型,基于非支配排序遗传算法-Ⅱ (NSGA-Ⅱ)和Aspen Plus与MATLAB软件的交互和多目标优化权衡最大㶲效率、最大日净输电量、最小氢气的平准化成本(LCOH),实现该系统的优化。所建立的模型可以高效准确地模拟、分析和优化该集成系统。帕累托前沿表明,该系统最优的㶲效率、日净输电量和LCOH分别为52.19%、247.352 MWh/d和6.05 USD/kg;优化后,最佳氢气产能为4.796 t/d,㶲效率提高3.00%,日净输电量增加31.14%,LCOH降低4.87%。该研究对于大规模太阳能耦合发电和制氢工艺的开发具有重要的指导意义。

关键词: 塔式太阳能发电, 电解, 制氢, 集成, 算法, 多目标优化

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