Dual mixed refrigerant LNG process: Uncertainty quantification and dimensional reduction sensitivity analysis

Muhammad Abdul Qyyum, Pham Luu Trung Duong, Le Quang Minh, Sanggyu Lee and Moonyong Lee

Applied Energy, 2019, vol. 250, issue C, 1446-1456

Abstract: The dual mixed refrigerant (DMR) liquefaction process is complicated and sensitive compared to the competitive propane pre-cooled mixed refrigerant liquefied natural gas (LNG) process. When any uncertainty is introduced to the process operation conditions, it is necessary for the DMR process to be re-optimized to maintain efficient operation at a minimal cost. However, in actual operation, re-optimization is a challenging task when the process operational input variables are varied, typically owing to the lack of information regarding the nature, impact, and levels of uncertainty. Within this context, this study investigates the uncertainty levels in the overall energy consumption and minimum internal temperature approach (MITA) inside LNG heat exchangers with variations in the operational variables of the DMR processes. Moreover, a global sensitivity analysis is conducted to identify the influence of random inputs on the process performance parameters. The required energy is significantly influenced by the variations in the variables in the cold mixed refrigerant (approximately 63%), while changes in the warm mixed refrigerant (WMR) section only slightly affect the uncertainty of the required specific energy. Furthermore, the probability distribution of the approach temperature (MITA1) inside the WMR exchanger is mainly affected by changes in the compositions of methane, ethane, and propane, as well as the high pressure of the cold mixed refrigerant (approximately 97%). Conversely, the flow rate of ethane and low pressure of the WMR significantly affect the uncertainty of the approach temperature (MITA2) inside the cold mixed refrigerant exchanger.

Keywords: DMR natural liquefaction process; Uncertainty quantification; Sensitivity analysis; Monte Carlo; Multiplicative dimensional reduction method (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (13)

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DOI: 10.1016/j.apenergy.2019.05.004

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