Strategies for Process and Size Selection of Natural Gas Liquefaction Processes: Specific Profit Portfolio Approach by Economic Based Optimization

Inkyu Lee, Il Moon

Research output: Contribution to journalArticlepeer-review

19 Citations (Scopus)

Abstract

This study focuses on the strategies for process and size selection of various natural gas liquefaction processes by economic based optimization. As various types of liquefaction processes can be differentiated by their energy efficiency and equipment requirements, the energy requirement and cost of a liquefaction process have to be considered simultaneously to find the optimal process for a given plant size. Herein, we developed two mathematical models, i.e., the thermodynamic model and cost model, based on the unit equipment that were integrated into a profit optimization model that could be applied to various natural gas liquefaction processes and plant sizes. In this study, the profit optimization model was applied to three representative natural gas liquefaction processes: single mixed refrigerant (SMR), dual mixed refrigerant (DMR), and propane precooled mixed refrigerant (C3MR) processes. The capacity of the plants ranged from 1 to 7 million tons per annum (MTPA). As a result of profit optimization, specific profit portfolios were obtained and the economical plant size ranges were figured out: 1-2.2 MTPA for the SMR process, 2.2-4 MTPA for the DMR process, and 4-7 MTPA for the C3MR process.

Original languageEnglish
Pages (from-to)5845-5857
Number of pages13
JournalIndustrial and Engineering Chemistry Research
Volume57
Issue number17
DOIs
Publication statusPublished - 2018 May 2

Bibliographical note

Funding Information:
This study was supported by a grant from the LNG Plant R&D Center, funded by the Ministry of Land, Infrastructure, and Transport (MOLIT) of the Korean Government.

Publisher Copyright:
© 2017 American Chemical Society.

All Science Journal Classification (ASJC) codes

  • Chemistry(all)
  • Chemical Engineering(all)
  • Industrial and Manufacturing Engineering

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