Liquefied Natural Gas Process Research Articles

Operation optimization of propane pre-cooled mixed refrigerant LNG Process: A novel integration of knowledge-based and constrained Bayesian optimization approaches

Liquefied natural gas (LNG) technology, particularly the propane precooled mixed refrigerant (C3MR) process, has demonstrated efficiency and emerged as a distinctive dual-refrigerant technology widely used in LNG production. However, the liquefaction process is the highest energy-intensive stage within its supply chain as it consumes about 8 % of the LNG energy content. Thus, for the first time, this study proposes systematic knowledge-based and constrained Bayesian optimization approaches to identify the optimal operation of the C3MR process. These approaches optimize both the operational parameters (pressures and flow rates) and the composition of the mixed refrigerant with practical equipment specifications and rigorous constraints. The results show that the specific energy consumption (SEC) is reduced to 0.264 kWh/kgLNG, which is 14.6 %, and 26 % lower than the basic C3MR process (unoptimized case) and typical industrial C3MR processes, respectively. In addition, the optimized SEC in this study is 14.5 % to 38.6 % lower than those reported in the literature. At large-scale LNG production (10,000 tons per day), the reduction in the SEC is translated into an 18 MW decrease in compression power, saving approximately 4.7 million $ per year for each C3MR train. Moreover, the coefficient of performance (COP) of the C3MR process was improved by about 15 %, and the CO2 emissions were reduced by 17 % (7 tons per year) compared to the basic C3MR process, indicating potential advancements in large-scale LNG liquefaction processes.

A novel approach for optimizing the natural gas liquefaction process

The conversion of natural gas into liquefied natural gas (LNG) requires substantial energy consumption. This study proposes a deterministic mathematical model to find the optimal operation conditions for an LNG plant to minimize the energy consumption for turbomachinery and the total thermal conductance of the heat exchangers. General Algebraic Modeling System (GAMS) linked to a Dynamic Link Library was used to calculate the thermodynamic properties of the working fluids. A derivative-based optimization algorithm is used. Results indicate that the novel optimization approach allows the satisfactory management of the model nonlinearities associated, for example, with the bilinear terms involved in the energy balances and the mathematical functions used to calculate the thermodynamic properties. A preprocessing phase for initializing process variables is developed to facilitate model convergence. In comparison to an optimal design reported in the literature, which was obtained by integrating a well-established evolutionary optimization approach with the Aspen HYSYS simulator, the results indicated that the net electrical power could be reduced by up to 10% when the derivative-based optimization algorithm is used. The proposed deterministic approach, consisting of a mathematical model, an initialization phase, and an optimization algorithm, can help process engineers overcome the challenges associated with LNG process optimization.

Advanced natural gas liquefaction and regasification processes: Liquefied natural gas supply chain with cryogenic carbon capture and storage

Natural gas combined cycle power plants generate substantial amounts of CO2. Also, since natural gas is produced in limited sites, the liquefied natural gas (LNG) supply chain consumes considerable energy in transporting natural gas overwide. Herein, advanced natural gas liquefaction and regasification processes using an LNG supply chain with cryogenic CO2 capture and storage (CCS) are proposed using Aspen Plus® V11. This solves three significant problems associated with conventional LNG supply chains. First, through the utilization of LNG cold energy, the cryogenic CCS process reduces the efficiency penalty of power generation from 14.34 to 4.45%. Second, solid CO2 from cryogenic CCS is used as an additional cold source in the natural gas liquefaction process by conveying it to the liquefaction site via the returning LNG ship. As a result, the power consumption in the refrigerant cycle is reduced by up to 67.17% than single mixed refrigerant (SMR) process. Finally, the LNG supply chain with cryogenic CCS minimizes the sustained energy waste between the natural gas liquefaction and regasification stages owing to the geographical separation. LNG cold energy from the regasification stage is utilized in the form of solid CO2 in the CCS and liquefaction stages. Consequently, the exergy efficiency in the overall LNG supply chain increases from 18.18 to 46.39%. The findings of this study can potentially provide environmentally friendly design guidelines for various LNG processes that use LNG cold energy in CCS and natural gas liquefaction.

Freezing-Based Acid Gas Removal and Its Integration with the Cold Section in an LNG Plant

Natural gas (NG) feed undergoes a series of liquefaction and upgradation processes to produce the final liquefied natural gas (LNG) product that meets customer specifications. LNG processes have a significant capital investment and a high energy requirement, and hence many researchers have focused on process improvement and optimization. While much of the previous research has concentrated on the development of more energy-efficient processes (such as acid gas removal unit (AGRU), liquefaction, natural gas liquid (NGL) recovery, and nitrogen removal), reducing the energy consumption of the whole LNG plant has received little attention. Moreover, the power needs of the LNG plant and LNG product and fuel gas quality constraints remain briefly addressed. The present work proposes an integration between the acid gas freezing unit (FAGRU) with the cold section and suggests multiple structural changes to the cold section. The results showcase that the proposed integration and structural design changes lower the total energy requirement by 16.6% and increase the production rate by 60 kt/a (1.76%). Both these reduce specific energy consumption (SEC) by 17.98%. The feed-to-fuel (FFF) ratio decreases from 6.94% for the base process to 5.7% for the integrated process.

The Design and Optimization of Natural Gas Liquefaction Processes: A Review

As the energy crisis intensifies, the global demand for natural gas is growing rapidly. Liquefied natural gas (LNG) technology is among the delivery solutions with flexible and reliable application prospects and is already a significant field of research in energy utilization. The performance of natural gas liquefaction process has a major influence on the production capacity, energy consumption, economics, and safety of the entire supply chain. Many scholars have conducted numerous studies on various LNG processes and designed many classical processes. This paper summarizes and discusses current research status and development level in the design and optimization of natural gas liquefaction processes in recent years, mainly focusing on cascade liquefaction process, expansion liquefaction process, and mixed refrigerant liquefaction process. The advantages and disadvantages of various liquefaction processes are compared and analyzed in terms of liquefaction capacity, energy consumption, economy, safety, and adaptability. In addition, the rapid development of pressurized liquefaction technology in recent years and its application outlooks are also introduced in detail. Finally, the present situation and industrial demand of LNG process are analyzed, and reasonable suggestions and future research prospects are put forward.

CO2 precooled dual phase expander refrigeration cycles for offshore and small-scale LNG production: Energy, exergy, and economic evaluation

Small-scale liquefied natural gas (LNG) processes have gained considerable attention owing to the development of offshore natural gas (NG) reserves. Low energy efficiency and high process costs are the major challenges associated with small-scale LNG processes. In this study, to reduce energy consumption and improve process economics, a dual-phase expander-based process assisted by carbon dioxide (CO2) precooling has been proposed. Three proposed cases were developed using two precooling refrigerants (propane (C3) and CO2) and dual-phase expander-based liquefaction cycles utilizing a mixture of high-boiling (ethane (C2) and propane (C3)) and low-boiling refrigerant (nitrogen (N2)). These processes were optimized with the multivariate Coggins algorithm to exploit the energy-saving opportunities. The results show that proposed case II (using CO2 in precooling and C2/N2 in liquefaction) is the most energy-efficient, with a specific energy consumption of 0.3790 kWh/kgNG. Proposed case II is 1.73% and 16.6% more energy-efficient than proposed cases I and III, respectively. The exergy analysis results show that proposed case II has the lowest exergy destruction, while the economic evaluation shows the lowest capital investment ($44.4 MM) compared to the other proposed cases. These results show the superior performance of case II among the proposed cases.

Particle Swarm-Assisted Artificial Neural Networks for Making Liquefied Natural Gas Processes Feasible Under Varying Feed Conditions

Natural gas (NG) has been widely recognized as a cleaner fuel compared to other fossil fuels. Reserves of NG are typically located in remote areas, and their conditions and compositions vary geographically. The NG from such areas is transported in the form of liquefied natural gas (LNG). Liquefying NG is highly complex. Generally, the process is designed to be carried out under fixed natural gas (NG) conditions; hence, it may not perform well under variable NG conditions. Considering this issue, the use of an artificial intelligence approach, rather than the conventional optimization one, was investigated to make the LNG process feasible under variable NG conditions. This study is the first in this research area to train an artificial neural network (ANN) using the particle swarm optimization (PSO) algorithm as a learning method. The developed PSO-ANN model was used to predict the decision variables of a single mixed refrigerant (SMR) LNG process for its feasible design under varying NG conditions. The correctness of the predicted set of decision variables (NG conditions) was verified by inputting them into Aspen HYSYS. The output of the SMR-LNG process was the overall power at a constrained minimum internal temperature approach (MITA) value, i.e., 1.0 ≤ MITA ≤3.0. The prediction results of the PSO-ANN model were compared with those of the classical ANN backpropagation learning method. The success rate of the proposed PSO-ANN model was 80%. Furthermore, the proposed model can make the LNG process feasible for a diverse range of temperature and pressure values. A feasible process with a better MITA value can also be achieved by tuning the model parameters.

Towards time-effective optimization: Enviro-economic study of the C3MR LNG process

Liquefied natural gas (LNG) is an important energy carrier and one of the pillars of secure energy supply in many countries. However, energy requirements and the associated carbon footprint of its production are substantial. This, incombination with the rapidly growing production capacities, calls for efficient process design and operation. Arobustmulti-objective optimization study of a3.5 MTPA propane-precooled mixed-refrigerant (C3MR) LNG plant has been done employing the genetic algorithm (GA/NSGA-II), with 18 process parameters varying in a ±75% interval. The study has been performed in a novel Aspen Plus – Matlab interface for parallel flowsheet simulations which exploits the full computational capacity of a desktop computer. An over seven-fold increase in calculation speed has been achieved, allowing for a significant increase in the GA/NSGA-II population count (up to 1000 individuals) without the computations being excessively time-consuming. To choose the most suitable individual from the 1000 individuals in the final Pareto front, four decision making methods: Euclidean distance, fuzzy non-dimensionalized distance, and two statistical methods have been used and the results have been compared and discussed. As a result, amore than 12% reduction in LNG processing costs and a 14% cut in carbon dioxide emissions was achieved. This roughly translates into approx. 76 mil. USD/year decrease in the total annual processing costs and an over 76 KTPA decrease in the carbon dioxide emissions. In addition, the in-optimization behavior of process parameters was studied. Out of the 18 studied parameters, only six exhibited significant changes throughout theoptimization process while the others converged to a seeming overall optimum already in the first two runs. This implies a possibility of using similar parameter analyses in future optimization studies. Finally, results of the single- and dual-objective optimization were confronted with similar studies in the field and compared between each other. As the single-objective optimization yielded only marginal decrease in the respective objective function while significantly increasing the other one, the dual-objective optimization is favored.

Risk assessment of a liquefied natural gas process facility using bow‐tie and Bayesian networks

AbstractIn this paper, a risk assessment methodology is presented to identify, analyze, and evaluate the risk associated with different consequences of a liquefied natural gas (LNG) process facility from west Algeria. Bow‐tie analysis (BT) is used to identify the possible causes of hazardous events and the dangerous outcomes and consequences resulting from the failure of the safety barriers. Moreover, the bow‐tie is mapped into Bayesian networks (BNs) to overcome some limitation of dependencies and updating in the events. Finally, the risk‐reducing measures implemented in the process are examined using BNs. The performances of the safety barriers are investigated considering the occurrence of fire and explosion in the facility. BN uses diagnostic (posterior) and predictive (prior) analysis to calculate the probabilities of the components and to predict the occurrence frequency of the consequences and the effectiveness of safety barriers. The results from the BN model indicate that pool fire is the most likely scenario that potentially causes damage to the LNG process.

Life cycle assessment of liquefied natural gas production from coke oven gas in China

Producing liquefied natural gas (LNG) from coke oven gas (COG) is a promising option to partly alleviate the shortage of natural gas supply and effectively utilize the byproduct of coking production in China. In order to systematically evaluate the energy consumption and environmental impact of COG-based LNG process, the life cycle assessment (LCA) method was introduced in this study. Two synthesized approaches were considered and compared, namely decarbonization process and methanation process. Besides, whether with or without H2 extraction in methanation process is also discussed. Inventory data are obtained from onsite investigations of representative enterprises in China. The results indicate that, LNG production stage is the dominated unit in the overall environmental impacts of decarbonization process, next is LNG evaporation stage, while coking stage only contributes 2.38%. The reason is that COG is only responsible for less upstream environmental burdens as a byproduct. In LNG production stage, medium pressure steam, COG and electricity are the key substances. Comparative LCA shows that methanation process shows better environmental performance than decarbonization process in COG-based LNG production since more LNG product are produced. It is suggested that methanation process with H2 extraction is more desirable considering economic performance. This work intends to provide useful insights on the sustainability development of COG utilization in coking industry.

Effects of the Henry Hub Price on U.S. LNG Exports and on Gas Flows in Western Europe

Natural gas plays an important role in energy supply, and its fields of application are diverse. However, the world’s largest growth potential among fossil fuels is attributed to liquefied natural gas (LNG). In the last few years, the U.S. rapidly increased LNG exports, and it is expected that they will further increase the liquefaction capacities. The cost of the LNG value chain is composed of the natural gas price in the country of origin, and the LNG process costs for liquefaction, transportation, storage, and regasification. Thus, the Henry Hub (HH) price in the U.S. is important for U.S. LNG exports to Western Europe. In this paper, gas flows in Western Europe at the beginning of the 2030s are analyzed if the price at HH is higher or lower than expected. Furthermore, the effect of the HH price on monthly U.S. LNG exports are studied. For the calculations, the global gas market model WEGA is used. The results reveal that the price at HH has a significant effect on annual gas flows in Western Europe and also on U.S. LNG exports during the summer. Furthermore, it is shown that pipeline gas in Western Europe will absorb fluctuations of U.S. LNG exports between the presented scenarios.

A novel hybrid liquefied natural gas process with absorption refrigeration integrated with molten carbonate fuel cell

Abstract The production of liquefied natural gas (LNG) is a high energy-consuming process. The study of ways to reduce energy consumption and consequently to reduce operational costs is imperative. Toward this purpose, this study proposes a hybrid system adopting a mixed refrigerant for the liquefaction of natural gas that is precooled with an ammonia/water absorption refrigeration (AR) cycle utilizing the exhaust heat of a molten carbonate fuel cell, 700°C and 2.74 bar, coupled with a gas turbine and a bottoming Brayton super-critical carbon dioxide cycle. The inauguration of the ammonia/water AR cycle to the LNG process increases the cooling load of the cycle by 10%, providing a 28.3-MW cooling load duty while having a 0.45 coefficient of performance. Employing the hybrid system reduces energy consumption, attaining 85% overall thermal efficiency, 53% electrical efficiency and 35% fuel cell efficiency. The hybrid system produces 6300 kg.mol.h−1 of LNG and 146.55 MW of electrical power. Thereafter, exergy and sensitivity analyses are implemented and, accordingly, the fuel cell had an 83% share of the exergy destruction and the whole system obtained a 95% exergy efficiency.

Effect of Ag-Addition on the Catalytic and Physicochemical Properties of Ni/ZrO2 Catalyst in Oxy-Steam Reforming of CH4 and LNG Processes

This work presents, for the first time, the catalytic studies of bimetallic Ag-Ni catalysts in the oxy-steam reforming (OSR) of liquefied natural gas (LNG) to hydrogen generation. The physicochemical properties of monometallic Ni and bimetallic catalysts were investigated using various techniques, such as: BET, TPR-H2, TPD-NH3, XRD, TG and SEM-EDS. The catalytic studies showed that the promotion of 20% Ni/ZrO2 catalyst by silver (by 1 or 2 wt.%) improves the efficiency of the produced hydrogen in the oxy-steam reforming of LNG at high temperature. The promotional effect of silver on the reducibility of a Ni/ZrO2 catalyst has been proven. The interactions between Ag and Ni have been proven, and explain the catalytic activity of the catalysts in the investigated processes. TG-DTA-MS results obtained for the spent catalysts proved that the small addition of silver to monometallic nickel catalyst reduces the amount of the carbon deposit formed on the catalyst surface during the oxy-steam reforming of LNG process. Obtained results in this work confirmed that liquid natural gas processing may become an alternative to fossil fuels and confirmed the validity of the hydrogen production via oxy-steam reforming of LNG.

Performance Enhancement of Nitrogen Dual Expander and Single Mixed Refrigerant LNG Processes Using Jaya Optimization Approach

The nitrogen (N2) expander and single mixed refrigerant (SMR) liquefaction processes are recognized as the most favorable options to produce liquefied natural gas (LNG) at small-scale and offshore sites. These processes have a simple and compact design that make them efficient with respect to their capital costs. Nevertheless, huge operating costs, mainly due to their lower energy efficiency, remains an ongoing issue. Utilization of design variables having non-optimal values is the primary cause for the lower energy efficiency; which, in turn, leads to exergy destruction (i.e., entropy generation), and ultimately the overall energy consumption is increased. The optimal execution of the design variables of LNG processes can be obtained through effective design optimization. However, the complex and highly non-linear interactions between design variables (refrigerant flowrates and operating pressures) and objective function (overall energy consumption) make the design optimization a difficult and challenging task. In this context, this study examines a new optimization algorithm, named “Jaya”, to reduce the operating costs of nitrogen dual expander and SMR LNG processes. The Jaya approach is an algorithm-specific parameter-less optimization methodology. It was found that by using the Jaya algorithm, the energy efficiency of the SMR process and nitrogen dual expander natural gas (NG) liquefaction process can be enhanced up to 14.3% and 11.6%, respectively, as compared to their respective base cases. Using the Jaya approach, significant improved results were observed even compared to other previously used optimization approaches for design optimization. Results of conventional exergy analysis revealed that the exergy destruction of SMR and N2 dual expander process can be reduced by 17.4% and 14%, respectively. Moreover, economic analysis identified the 13.3% and 11.6% relative operating costs savings for SMR and N2 dual expander LNG processes, respectively.

Single-Solution-Based Vortex Search Strategy for Optimal Design of Offshore and Onshore Natural Gas Liquefaction Processes

Propane-Precooled Mixed Refrigerant (C3MR) and Single Mixed Refrigerant (SMR) processes are considered as optimal choices for onshore and offshore natural gas liquefaction, respectively. However, from thermodynamics point of view, these processes are still far away from their maximum achievable energy efficiency due to nonoptimal execution of the design variables. Therefore, Liquefied Natural Gas (LNG) production is considered as one of the energy-intensive cryogenic industries. In this context, this study examines a single-solution-based Vortex Search (VS) approach to find the optimal design variables corresponding to minimal energy consumption for LNG processes, i.e., C3MR and SMR. The LNG processes are simulated using Aspen Hysys and then linked with VS algorithm, which is coded in MATLAB. The results indicated that the SMR process is a potential process for offshore sites that can liquefy natural gas with 16.1% less energy consumption compared with the published base case. Whereas, for onshore LNG production, the energy consumption for the C3MR process is reduced up to 27.8% when compared with the previously published base case. The optimal designs of the SMR and C3MR processes are also found via distinctive well-established optimization approaches (i.e., genetic algorithm and particle swarm optimization) and their performance is compared with that of the VS methodology. The authors believe this work will greatly help the process engineers overcome the challenges relating to the energy efficiency of LNG industry, as well as other mixed refrigerant-based cryogenic processes.

Use of exergy efficiency for the optimization of LNG processes with NGL extraction

In this paper, processes for liquefied natural gas (LNG) production with upstream or integrated natural gas liquids (NGL) removal have been optimized and compared. Since the NGL and LNG production systems use both work and heat to deliver products with different energy quality, it is challenging to measure accurately the thermodynamic efficiency by using conventional energy performance indicators. Thus, two different objective functions, specific energy consumption and exergy efficiency, have been applied in the optimization of these complex systems in order to evaluate the effectiveness of the two performance indicators. The results indicate that use of the exergy-based objective function results in a richer NGL and a larger amount of LNG production with a marginal increase in energy consumption, showing a higher thermodynamic efficiency than the result with the energy-based objective function. Besides, integrated NGL extraction shows a lower thermodynamic performance than upstream removal, indicating that further advanced schemes are required for effective integration of the NGL extraction part in the LNG process.

Working together to establish a world-class mercury recovery facility for the Australian liquefied natural gas industry

Mercury is a heavy metal that is widespread and persistent in the environment and, even at low concentrations, poses a risk of adverse effects to human health and ecosystems. Mercury is commonly found in hydrocarbon reservoirs. Approximately 1.5 tonnes of mercury arrive at the Karratha Gas Plant each year in feed gas from offshore platforms. Because mercury reacts with aluminium, it must be removed from the liquefied natural gas (LNG) process before the main cryogenic heat exchangers, which comprise ~1000 km of aluminium tubing. For over a decade mercury has been safely removed from the Woodside LNG process and sent to Switzerland for recovery of metals and complete recycling of waste constituents. Here we present the outcome of a 3-year collaboration between Woodside and Contract Resources that resulted in the opening of Australia’s first industrial-scale state-of-the-art mercury recovery facility in Karratha in July 2018. The AU$20 million plant is the largest of its type in the Southern Hemisphere and was underpinned by Woodside providing foundation funding through a long-term contract. The facility can handle all mercury-contaminated waste produced by the Australian oil and gas sector now and into the foreseeable future. An unparalleled project delivery taking 3 years to implement from initial discussion to the first batch of waste being processed in Karratha. This paper illustrates the collaboration, innovation and acceleration that occurred to deliver a sustainable outcome for Australian LNG.

Modeling and Analysis of Coal-Based Lurgi Gasification for LNG and Methanol Coproduction Process

A coal-based coproduction process of liquefied natural gas (LNG) and methanol (CTLNG-M) is developed and key units are simulated in this paper. The goal is to find improvements of the low-earning coal to synthesis natural gas (CTSNG) process using the same raw material but producing a low-margin, single synthesis natural gas (SNG) product. In the CTLNG-M process, there are two innovative aspects. Firstly, the process can co-generate high value-added products of LNG and methanol, in which CH4 is separated from the syngas to obtain liquefied natural gas (LNG) through a cryogenic separation unit, while the remaining lean-methane syngas is then used for methanol synthesis. Secondly, CO2 separated from the acid gas removal unit is partially reused for methanol synthesis reaction, which consequently increases the carbon element utilization efficiency and reduces the CO2 emission. In this paper, the process is designed with the output products of 642,000 tons/a LNG and 1,367,800 tons/a methanol. The simulation results show that the CTLNG-M process can obtain a carbon utilization efficiency of 39.6%, bringing about a reduction of CO2 emission by 130,000 tons/a compared to the CTSNG process. However, the energy consumption of the new process is increased by 9.3% after detailed analysis of energy consumption. The results indicate that although electricity consumption is higher than that of the conventional CTSNG process, the new CTLNG-M process is still economically feasible. In terms of the economic benefits, the investment is remarkably decreased by 17.8% and an increase in internal rate of return (IRR) by 6% is also achieved, contrasting to the standalone CTSNG process. It is; therefore, considered as a feasible scheme for the efficient utilization of coal by Lurgi gasification technology and production planning for existing CTSNG plants.

Determination of Maintenance Task on Rotary Equipment Using Reliability Centered Maintenance II Method

The process of natural gas into LNG (Liquefied Natural Gas) requires many steps and various types of chemical products. The process also produces waste. The Liquid Incinerator treats waste from LNG process. This unit often experiences damages which causes the plant do not work properly and even a down/trip problems due to the continuous operation and the absence of maintenance program, especially for rotary equipments. This causes environmental pollution because the waste is unprocessed and could have an impact on the increased cost to treat the waste elsewhere. One of approaches to analyze the causes of the damage, the impact and effective treatment for equipment is using Reliability Centered Maintenance (RCM). The RCM method is expected to be able to identify the primary and secondary functions of the system, possible failure function, Failure Mode and Effect Analysis (FMEA), and the maintenance actions on the plant. The FMEA result will be used to determine the proposed maintenance task. Based on the proposed maintenance task, the maintenance interval for each equipment is obtained. After RCM analysis is done on 4 equipments, liquid waste feeding pump (34-G-2), quencher pump (34-G-3), scrubber pump (34-G-4) and air compressor (34-K-4). For 34-G-2 failure mode, requires 78% preventive maintenance and 22% corrective maintenance, 34-G-3 requires 87% preventive maintenance and 13% corrective maintenance, 34-G-4 requires 87% preventive maintenance and 13% corrective maintenance and 34-K-4 requires 70% preventive maintenance and 30% corrective maintenance. Workpackage for each interval is created from every failure mode for each interval for maintenance / inspection.

Normalized sensitivity analysis of LNG processes - Case studies: Cascade and single mixed refrigerant systems

The sensitivities of two liquefied natural gas (LNG) cycles, single mixed refrigerant (SMR) and propane pre-cooled mixed refrigerant (C3MR) to input variables are investigated and compared using normalized sensitivity analysis. The normalized sensitivity coefficients indicate the output of the cycles, specific energy consumption (SEC) is more sensitive to the inlet temperature and pressure of the mixed refrigerant compressors, the mixed refrigerant composition and the discharge temperature of the aftercoolers. The sensitivity analysis shows even perturbations below the accuracy level of ordinary measuring instruments are still large enough to break the 0.5–1.5 K minimum approach temperature (MAT) in cryogenic heat exchangers, commonly used in many earlier studies. Very few studies have addressed the optimality of the liquefaction process in an operation stability perspective. In this paper, sensitivity analysis is used to investigate the effect of disturbances and uncertainty on the stability of the cycles’ operation. 3 K MAT is suggested and tested by sensitivity analysis and verified by the economic assessment of the cycles. It is also shown that such perturbations cannot break 3 K MAT in cryogenic heat exchangers, hence the recent results are more reliable.