Multi-objective optimization of hydrogen liquefaction process integrated with liquefied natural gas system

被引:46
|
作者
Bae, Ju-Eon [1 ]
Wilailak, Supaporn [2 ]
Yang, Jae-Hyeon [1 ]
Yun, Dong-Yeol [1 ]
Zahid, Umer [3 ]
Lee, Chul-Jin [1 ,2 ]
机构
[1] Chung Ang Univ, Sch Chem Engn & Mat Sci, 84 Heukseok Ro, Seoul, South Korea
[2] Chung Ang Univ, Dept Intelligent Energy & Ind, 84 Heukseok Ro, Seoul, South Korea
[3] King Fahd Univ Petr & Minerals, Dept Chem Engn, Dhahran, Saudi Arabia
关键词
Hydrogen Liquefaction; Genetic Algorithm; Multi-objective Optimization; RE-LIQUEFACTION; PERFORMANCE; EXERGY; ENERGY; CYCLE; GASIFICATION; DESIGN; COST;
D O I
10.1016/j.enconman.2021.113835
中图分类号
O414.1 [热力学];
学科分类号
摘要
Liquid hydrogen is gaining increasing attention owing to its high energy density as 10.1 MJ/L compared to gaseous hydrogen as 5.6 MJ/L at 700 bar. However, the energy required for its cryogenic processes is significant. To reduce this energy demand, liquefied natural gas (LNG) cooling was introduced in addition to a nitrogen refrigerant to the hydrogen liquefaction process. The resultant hydrogen production from the steam methane reforming process via LNG emits carbon dioxide. Therefore, it is necessary to consider both energy and CO2 emission when optimizing this system. To minimize these factors, single and multi-objective optimizations were performed, as well as a cost analysis in order to determine the optimal performance. The results of multi objective optimization reveal that the CO2 emissions decrease by 38%, whereas the total investment cost is increased by 45% compared to the base case. The specific energy consumption is increased from 10.76 kWh/kgLH(2) to 11.13 kWh/kg-LH2. Therefore, the compromise between the cost and the CO2 emissions is made in the proposed case. These results will provide valuable insights regarding the economic demand and CO2 emission for future decision-making processes.
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页数:9
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