1.山东大学核科学与能源动力学院,山东 济南 250061
2.烟台东德实业有限公司,山东 烟台 264000
张志伟(2002—),男,硕士研究生,研究方向为氢能储运,E-mail:202434580@mail.sdu.edu.cn;
陈常念,副教授,研究方向为综合能源系统及氢能储运,E-mail:chen.cn@sdu.edu.cn。
收稿:2026-05-01,
修回:2026-06-25,
网络首发:2026-08-26,
纸质出版:2026-08-28
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张志伟, 闫闯, 陈常念, 等. 计及多能流耦合的离网型氢能站综合能源能效分析与多目标优化[J]. 储能科学与技术, 2026, 15(8): 3189-3202.
ZHANG Zhiwei, YAN Chuang, CHEN Changnian, et al. Comprehensive energy efficiency analysis and multi-objective optimization of off-grid liquid hydrogen refueling stations with multi-energy flow coupling[J]. Energy Storage Science and Technology, 2026, 15(8): 3189-3202.
张志伟, 闫闯, 陈常念, 等. 计及多能流耦合的离网型氢能站综合能源能效分析与多目标优化[J]. 储能科学与技术, 2026, 15(8): 3189-3202. DOI: 10.19799/j.cnki.2095-4239.2026.0369.
ZHANG Zhiwei, YAN Chuang, CHEN Changnian, et al. Comprehensive energy efficiency analysis and multi-objective optimization of off-grid liquid hydrogen refueling stations with multi-energy flow coupling[J]. Energy Storage Science and Technology, 2026, 15(8): 3189-3202. DOI: 10.19799/j.cnki.2095-4239.2026.0369.
针对传统液氢加氢站气化过程存在的冷能浪费严重、热力学效率低等问题,提出液氢加氢站与质子交换膜燃料电池耦合的离网能量综合利用系统。该系统以多能流梯级利用为核心,通过匹配储冷工质相变温度,构建了深冷、中冷与低温三级梯级回收架构。在保障液氢气化及稳定供应的基础上,利用有机朗肯循环实现发电,并通过蓄冷工艺达成液氮与干冰的高价值联产。采用Aspen HYSYS对上述系统进行了建模与仿真验证,并结合人工神经网络与非支配排序遗传算法进行了多目标优化,结果表明,在全局最优决策点下日处理量为1 t的液氢加氢站系统㶲效率、能量效率、净输出功率分别为59.63%、88.97%、154.87 kW,不仅实现了179.97 kg/h液氮与89.69 kg/h干冰的高效联产,还输出了约132 kW的有效电能。经济性分析进一步显示,当液氢到站价为39.89 CNY/kg,氢气售价为61 CNY/kg时,系统投资回收期为6年,最高可使加氢价格降低21.77%,与传统加氢站和现有冷能回收方案相比,实现了能量效率、联产效益及运行安全性的提升。
To address cold energy waste and low thermodynamic efficiency in traditional liquid hydrogen (LH
2
) refueling stations
this study proposes an off-grid integrated energy utilization system that couples an LH
2
refueling station with a proton exchange membrane fuel cell (PEMFC). With multi-energy flow cascade utilization as the core and by matching the phase-change temperatures of cold storage media
a three-stage cascade recovery architecture consisting of cryogenic
medium-cold
and low-temperature levels is constructed. On the basis of ensuring stable LH
2
vaporization and hydrogen supply
the system utilizes the organic Rankine cycle (ORC) for power generation and achieves high-value coproduction of liquid nitrogen (LN
2
) and dry ice through a cold storage process. The system
scaled for a 1 t/d LH
2
throughput
was modeled using Aspen HYSYS and optimized via a collaborative framework integrating artificial neural networks (ANN)
the non-dominated sorting genetic algorithm Ⅱ (NSGA-Ⅱ)
SHAP
and TOPSIS. At the global optimal decision point
the system achieves an exergy efficiency of 59.63%
an energy efficiency of 88.97%
and a net output power of 154.87 kW
with the net recovery work reaching 379.7 W/kg H
2
. Concurrently
it coproduces 179.97 kg/h of LN
2
89.69 kg/h of dry ice
and approximately 132 kW of effective electricity. Economically
under an LH
2
feed price of 39.89 CNY/kg and a hydrogen sales price of 61 CNY/kg
the payback period is 6 years
reducing the terminal refueling cost by up to 21.77%. Ultimately
this approach realizes comprehensive improvements in system energy efficiency
multi-generation economic benefits
and operational safety.
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