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

Ju Eon Bae, Supaporn Wilailak, Jae Hyeon Yang, Dong Yeol Yun, Umer Zahid*, Chul Jin Lee

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

54 Scopus citations

Abstract

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/kg-LH2 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.

Original languageEnglish
Article number113835
JournalEnergy Conversion and Management
Volume231
DOIs
StatePublished - 1 Mar 2021

Bibliographical note

Publisher Copyright:
© 2021 Elsevier Ltd

Keywords

  • Genetic Algorithm
  • Hydrogen Liquefaction
  • Multi-objective Optimization

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment
  • Nuclear Energy and Engineering
  • Fuel Technology
  • Energy Engineering and Power Technology

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