Key Issues and Challenges on the Liquefied Natural Gas Value Chain

Review Cite This: Ind. Eng. Chem. Res. XXXX, XXX, XXX−XXX

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Key Issues and Challenges on the Liquefied Natural Gas Value Chain: A Review from the Process Systems Engineering Point of View Inkyu Lee, Jinwoo Park, and Il Moon* Department of Chemical and Biomolecular Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea ABSTRACT: This paper reviews recent contributions on the liquefied natural gas (LNG) value chain in the field of process systems engineering (PSE). While previous review articles deal with specific topics for each issue on the LNG value chain, this paper deals with the key issues and challenges on the LNG value chain from the process systems engineering point of view. The major challenges for the LNG value chain are (a) multiscale and integrated modeling between the liquefaction process and the utility systems, (b) process and size selection for the natural gas liquefaction, (c) utilization of LNG fuel, (d) using generated boil-off gas as the raw material for other industries, and (e) commercializing LNG cold recovery to industrial sites. Identifying key issues and presenting challenges on the LNG value chain will contribute to the advancement of the PSE field and the LNG industry.

1. INTRODUCTION According to the Outlook for Energy,1 the demand for natural gas is forecasted to increase by 45% from 2015 to 2040, and the trade of global liquefied natural gas (LNG) is expected to increase by more than 2.5 times within the same period.1 The U.S. Energy Information Administration (EIA) forecasted that the natural gas production in the U.S. will grow considerably and that the production of natural gas from shale gas, and the production of associated gas from tight oil, will be the largest contributors to this growth accounting for nearly two-thirds of the total U.S. production.2 According to the Energy Outlook,2 shale gas production accounts for approximately 60 percent of the increase in the natural gas supply, and it is driven by the U.S.; meanwhile increases in conventional gas production are led by the Middle East, Russia, and Australia.3 Therefore, the growth of the global supply in LNG will be led by the U.S. and Australia. In regard to the natural gas demand, Asia is forecasted to remain the biggest consumer for LNG, while China, India, and other Asian countries, will increase their demand for LNG, helping the gas demand to grow faster compared to either oil or coal in each of these economies. In this manner, the demand for new LNG infrastructure is expected to increase. Figure 1 shows the projected net LNG exports and imports in 2035.3 The volume of LNG is approximately 600 times smaller than the same mass of natural gas in the vapor phase.4 Therefore, the LNG form is preferred for long distance transportation. The LNG value chain starts from the exploration and production steps, followed by the liquefaction, transportation, regasification, and sale steps.4 The LNG value chain and the cost breakdown are shown in Figure 2.5,6 Among the LNG value chain steps, the liquefaction step accounts for the largest cost © XXXX American Chemical Society

proportion because it is operated under cryogenic conditions. LNG is produced by cooling natural gas to −163 °C at atmospheric pressure.7 Thus, the natural gas liquefaction process is highly energy intensive owing to its cryogenic characteristics.8 The process systems engineering (PSE) community has made efforts to identify and solve the real industrial problems. From the same point of view, the PSE community has contributed a lot to solving the problems faced by the LNG industry. According to our literature survey, the research on the LNG value chain mainly have focused on liquefaction, boil-off gas (BOG) handling, and regasification. In detail, the key problems can be categorized on the LNG value chain to the design and optimization of the natural gas liquefaction process, LNG supply chain management, boil-off gas minimization and recycling, LNG cold recovery in the regasification step, offshore floating liquefied natural gas (FLNG), and safety analysis for LNG spills or leakages. Some review works on those topics have been reported in the LNG research field. Lim et al.9 published a review on LNG plant design. They reviewed developments in LNG processes with an emphasis on the commercially available refrigeration cycles. Qyyum et al.10 reviewed design and optimization of natural gas liquefaction processes. They compared various natural gas liquefaction processes and various optimization techniques. Won et al.11 Special Issue: PSE Advances in Natural Gas Value Chain Received: Revised: Accepted: Published: A

September 20, 2017 December 17, 2017 December 21, 2017 December 21, 2017 DOI: 10.1021/acs.iecr.7b03899 Ind. Eng. Chem. Res. XXXX, XXX, XXX−XXX

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Industrial & Engineering Chemistry Research

Figure 1. Projected net LNG exports and imports in 2035 (Bcf/d; created with data from ref 3).

Figure 2. LNG value chain and the cost breakdown (created with data from refs 5 and 6).

Figure 3. Heat exchange composite curves for typical natural gas liquefaction processes: (a) cascade; (b) single mixed refrigerant; (c) dual mixed refrigerant; (d) propane precooled mixed refrigerant (created with data from ref 9).

Sánchez13 also published a review on the transportation systems of natural gas. Khan et al.14 presented a retrospective review of natural gas liquefaction technologies and optimization methodologies. Sharafian et al.15 reviewed LNG refueling station studies that focused on BOG management. They discussed different on-board LNG tank architectures and design

reviewed research contributions on FLNG technologies. They introduced conventional LNG processes to FLNG, summarized the main FLNG unit technologies, and probed present and future FLNG market drivers and trends in the FLNG sector. Gómez et al.12 reviewed thermal cycles for the LNG cold ́ recovery in terms of the exergy. Rios-Mercado and BorrazB

DOI: 10.1021/acs.iecr.7b03899 Ind. Eng. Chem. Res. XXXX, XXX, XXX−XXX

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low- and high-boiling refrigerants, which are contained in mixed refrigerants.22 Both cold and warm mixed refrigerants are compressed using multistage compressions. A propane precooled mixed refrigerant (C3MR) process is one of the dominant liquefaction processes, and uses pure and mixed refrigeration cycles. 23 The C3MR process was introduced by the Air Product and Chemicals, Inc. (APCI) and combines the advantages of mixed and pure refrigeration cycles.24 The C3MR process follows the cooling curve of Figure 3d. Propane is used as the pure refrigerant to precool the natural gas to approximately −33 °C, followed by the subcooling of the natural gas by the mixed refrigerant.25 The pure refrigeration cycle is compressed by multistage compression. The natural gas is cooled down at each pressure level of the pure refrigerant, and by the multistage heat exchanging process of the mixed refrigerant. The cold mixed refrigerant is compressed by successive multistage compressors that liquefy the natural gas.26 Generally, the mixed refrigerant in the C3MR process contains nitrogen, methane, ethane, and propane, as its constituent components. 2.1.3. N2 Expander Based Liquefaction Processes. Natural gas liquefaction processes based on the N2 expander have been developed for offshore applications with the advantages of its simple configuration and safe operating conditions using inert gas as the refrigerant. The nitrogen is used as the pure refrigerant to liquefy the natural gas, and it is maintained in the gas phase during the refrigeration.27 The refrigeration cycle is configured as the reverse Brayton cycle. There are several processes based on the N2 expander, such as N2 single expander, N2 dual expander, and CO2 precooled N2 expander processes.27,28 2.2. Optimization of the Natural Gas Liquefaction Process. During the last few decades, many researchers have focused on the minimization of the compression energy requirements in the LNG refrigeration cycles. The major challenges encountered in studies of the liquefaction processes in academia are the determination of the optimal design and operating conditions. Most of these studies have focused on minimizing shaft work requirements with different target processes and different optimization techniques. The optimization field of the natural gas liquefaction process can be classified in three categories: (a) energy optimization with deterministic methods, (b) energy optimization with stochastic methods, including genetic algorithms, and (c) cost optimization of the natural gas liquefaction process. 2.2.1. Energy Optimization with Deterministic Methods. In early studies of optimization of the natural gas liquefaction process, nonlinear programming (NLP) was usually applied. Vaidyaraman and Maranas29 focused on the synthesis of refrigeration systems with mixed refrigerants as working fluids, and developed an objective function that minimized the total work input to the system. They formulated the problem as a nonconvex NLP to optimize the cascade of the process utilizing mixed refrigerants. Kim et al.30 proposed a strategy for selection of the mixed refrigerant composition by using a combined NLP and a thermodynamic approach. The target process was the PRICO process, that is, a type of single mixed refrigerant (SMR) process, and the set objective was the minimization of the shaft work requirement. Lee et al.31 performed optimization of the SMR process using the decision variables of the mixed refrigerant composition, flow rate, compressor inlet and outlet pressures, and separator temperatures. The objective functions in their study were the minimization of the crossover, the sum

strategies for LNG conditioning and BOG management technologies. In addition to these existing, dedicated reviews on the specific topics, comprehensive reviews of the LNG value chain will be of great benefit to the PSE community. Therefore, this study reviewed key issues of the overall LNG value chain as follows: • Natural gas liquefaction issues • BOG handling issues during transportation and storage • LNG cold recovery issues in the regasification process The issues are addressed based on the review of the most recent contributions in PSE, and the challenges are then discussed.

2. NATURAL GAS LIQUEFACTION ISSUES 2.1. Natural Gas Liquefaction Process Classification. General natural gas liquefaction processes are conducted under a broad temperature range using one or more refrigerants.16 The natural gas liquefaction processes can be classified in accordance with the types of refrigerants used and the number of refrigeration cycles.9 The refrigerant types can be classified into two categories, namely, pure refrigerant and mixed refrigerant. The heat exchange composite curves for typical natural gas liquefaction processes are shown in Figure 3. 2.1.1. Cascade Liquefaction Process. A cascade liquefaction process, the world’s first natural gas liquefaction process, uses three pure refrigerants to cover the broad range of heat exchanging temperatures.17 Generally, propane, ethane or ethylene, and methane are used as refrigerants in successive natural gas cooling steps.18 The three refrigerant cycles are operated at three heat exchanging temperature levels with multistage compression. The propane cycle precools the natural gas to approximately −30 °C, and the ethane or ethylene cycle cools the natural gas to approximately −100 °C. The natural gas is finally liquefied by the methane cycle at −160 °C. The cascade liquefaction process follows the heat exchanging composite curve of Figure 3a. 2.1.2. Mixed Refrigerant Based Processes. The most widely used commercial processes based on mixed refrigerants are single mixed refrigerant (SMR), dual mixed refrigerant (DMR), and propane precooled mixed refrigerant (C3MR) processes. The SMR process that uses one mixed refrigerant cycle is one of the simplest natural gas liquefaction processes.19 The SMR process follows the heat exchanging composite curve of Figure 3b. Generally, the mixed refrigerant is compressed by multistage compression using nitrogen and hydrocarbons. The DMR process is a favored natural gas liquefaction technology for on-shore locations since it is one of the processes with high efficiency.20 The DMR process uses two different mixed refrigeration cycles, one with a warm mixed refrigerant and the other with a cold mixed refrigerant.21 The DMR process follows the cooling curve of Figure 3c. The natural gas is precooled by the warm mixed refrigerant and then liquefied by the cold mixed refrigerant. Generally, the cold mixed refrigerant consists of nitrogen, methane, ethane, and propane. The warm mixed refrigerant contains components, such as methane, ethane, propane, n-butane, and i-butane. Therefore, the warm mixed refrigerant has a higher boiling point compared to the cold mixed refrigerant. Because the concentrations of mixed refrigerants can be adjusted easily, the DMR process has the advantage of high flexibility. It can cover a broad range of temperatures spanning the temperatures of C


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and Saffari39 focused on the minimization of the compression energy requirement in the C3MR process using the genetic algorithm. The commercial software MATLAB was used for the modeling and simulation of the C3MR process in their work. Alabdulkarem et al.40 minimized the energy consumption in the C3MR process using the genetic algorithm. They used the commercial process simulation software Aspen HYSYS to calculate the thermodynamic properties in conjunction with the genetic algorithm optimizer in MATLAB. They performed and compared four different optimizations with different pinch temperatures, and they concluded that a lower pinch temperature makes power consumption savings possible. Xu et al.41 coupled the genetic algorithm with the process simulation software Aspen Plus. They focused on the determination of the composition of the mixed refrigerant of the PRICO process. They found that the concentrations of methane, ethylene, and propane, had to be decreased, and ipentane had to be increased, when the ambient temperature increased. In their subsequent study, Xu et al.42 also applied the genetic algorithm with Aspen Plus, where they minimized the specific energy consumption of the PRICO process. Some researchers have employed other stochastic optimization techniques that do not use the genetic algorithm. Aspelund et al.43 developed a gradient-free optimization-simulation method. They applied the Tabu search (TS) and the Nelder−Mead downhill simplex (NMDS) method. The objective of their work was to minimize the total required compression energy of the PRICO process. Morin et al.44 applied an evolutionary search method to minimize the energy requirement of the SMR, PRICO, and TEALARC processes. Khan and Lee45 employed the particle swarm paradigm to optimize the SMR process. Minimization of the compression energy requirement was selected as the optimization objective function. Honeywell’s UniSim design software was coupled with the particle swarm optimization model in MATLAB for the simulation. 2.2.3. Economic Optimization. Some studies have expended efforts to consider the cost of the LNG plants. One of the earliest studies for cost minimization was adapted to the pure refrigeration system by Barnés and King.46 Cheng and Mah47 developed an interactive synthesis approach for cascade refrigeration systems, while Vaidyaraman and Maranas48 used mixed-integer linear programming to minimize investment and the operating costs for refrigerant selections. Jensen and Skogestad49 developed a total annual cost (TAC) equation to minimize capital and operating costs. In their work, the capital cost of the heat exchanger and operating costs for the compression energy were considered. Castillo and Dorao50 focused on cost minimization by considering the market cost, power consumption, and heat transfer area. Jensen and Skogestad51 introduced the cost factor as an adjustable parameter in a study whose objective was to maximize the LNG flow rate, and minimize the heat exchanger and natural gas costs. In other studies, Jensen and Skogestad52,53 focused on the minimization of the total annual cost, which is the sum of fuel, feed, and operating costs. Wang et al.54 performed optimizations with four different objective functions, including the total shaft work, total cost investment, total annual cost, and total capital cost of compressors and main cryogenic heat exchangers. 2.3. Challenges in Natural Gas Liquefaction Process Design and Optimization. 2.3.1. Process Design Challenge. The process development challenges for natural gas liquefac-

of the crossovers, and the shaft work requirement. They applied pinch technology and NLP techniques to solve the problem. Aspelund et al.32 focused on the minimization of the total shaft work requirement of the expander process. They developed extended pinch analysis and design (ExPAnD), which is a methodology for process synthesis that extends pinch and exergy analysis. Shah and Hoadley33 used the targeting method, which demonstrates the relationship between the expansion− compression pressure ratio, the heat exchange design parameter, and the minimum temperature difference. The optimization objective was shaft work minimization of the cascade N2 expander process. Wang et al.34 applied a simulation-based optimization conducted in Aspen Plus, in which the sequential quadratic programming (SQP) solver was employed. The objective of their work was to minimize the total shaft work requirement of the precooled mixed refrigerant (C3MR) process for propane. In their subsequent study, Wang et al.23 employed the LINDO global solver in the software GAMS, in which the mixed integer nonlinear programming (MINLP) model was developed for the energy minimization of the C3MR process. Hatcher et al.35 presented a systematic analysis of optimization formulations of the natural gas liquefaction process. To identify the most appropriate formulation, they applied eight objective functions, namely, four for the operational aspects and four for the design aspects. The most effective objective function used for the optimization minimized the compressor power that was the major operating cost in their study. For design optimization, minimization of the net present value (NPV) was favored without imposing a limit on the plant area, while the minimization of the objective function (Ws−UA) was favored in cases where a limit was imposed on the plant area. Wahl et al.36 applied the SQP solver to minimize the energy requirement of the SMR process and concluded that most of the optimization results were better and that the execution times were much lower than in most studies employing similar optimization cases with stochastic optimization methods. Lee et al.25 focused on the energy minimization of the pure refrigeration cycle in the C3MR process. They applied the successive reduced quadratic programming (SRQPD) solver with gPROMS, which is an equation-oriented commercial software, and proposed a new design for the pure refrigerant process for subcooling. Tak et al.37 compared four different configurations of the SMR process with three natural gas compositions. Thus, 12 different cases were optimized with the SRQPD solver. They concluded that to reduce the specific work, adding a pump to a specific configuration was better than adding a compressor. Lee et al.26 applied the SRQPD solver to minimize the compression energy requirement of the C3MR process. They attempted to determine the optimal liquefaction ratio of the natural gas liquefaction. Four different cases were set, and the optimizations were performed to analyze the effects of the liquefaction ratio. The objective functions were the total energy consumption and the specific energy consumption, with and without the natural gas feed flow rate. The latter was set as the decision variable. 2.2.2. Energy Optimization with Stochastic Methods. One of the major stochastic optimization techniques applied in research on natural gas liquefaction processes is the genetic algorithm. Nogal et al.38 applied the genetic algorithm to overcome local optima. The target process of their work was a cascade process utilizing a mixed refrigerant. Shirazi and Mowla19 also applied the genetic algorithm to minimize the shaft work requirement of the PRICO process. Taleshbahrami D


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Figure 4. Configuration of the KSMR process (created with data from ref 55).

natural gas liquefaction process and the research scheme used for the optimization are illustrated in Figure 5.

tion have steadily increased in the last several decades due to the need to simultaneously improve energy efficiency and decrease costs. One of the representative works of liquefaction process design was performed by Park et al.55 The developed process is called the Korea Single Mixed Refrigerant (KSMR) process which is modified from the SMR process. The KSMR process uses a single mixed refrigerant which is separated into light mixed refrigerant (LMR) and heavy mixed refrigerant (HMR) before the heat exchange process. The LMR is used to precool the natural gas and expanded to medium pressure. The HMR is expanded to low pressure to make it a lower temperature than the LMR, and it is used to liquefy the natural gas. The process configuration of the KSMR process is illustrated in Figure 4. By splitting the refrigerant into two different pressure levels, the compression work requirement can be reduced compared to that in the SMR process. Moreover, the required amount of equipment is much smaller than that in the DMR and C3MR processes. Pham et al.56 performed energy optimization of the KSMR process and announced that the KSMR process is more efficient than the DMR process even though the configuration is simpler. This kind of process development can contribute greatly to the LNG industry and process design challenges still remain in the direction of enhancing efficiency and reducing costs. 2.3.2. Modeling and Optimization Challenge. The thermodynamic model of the natural gas liquefaction process is highly nonlinear and is not easy to converge. Therefore, researchers within the PSE community have used various methods to identify the globally optimum outcomes in terms of energy or cost. Because the problem is very complex, most of the previous studies targeted the specific type of process, whereby the process scheme was simplified or divided into parts. In addition, many assumptions were posed to simplify the optimization model. However, these efforts were not reflective of real plant conditions. Conversely, the driver selection and the utility optimization problems have been studied separately.57−61 Thus, the challenges of the integrated model that arise include the liquefaction process, driver, and utility. The modeling of the

Figure 5. Natural gas liquefaction process modeling and optimization research scheme.

With the improvements in computational performance, rigorous modeling challenges arise from the need to reduce the gap between the computational model and the conditions in real industrial plants. One of the remedies can be multiscale modeling. By adapting the multiscale modeling technique, rigorous operating data analysis can be applied to the process design level. Moreover, the data obtained from the analysis of the design modeling process can be used to supply the chain optimization model. This multiscale modeling approach can improve the quality of the optimization, and it can also contribute to chemical engineering in terms of the economy E


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Figure 6. Multiscale optimization methodologies: (a) conceptual diagram (created with data from ref 60) and (b) specific methodology for natural gas liquefaction.

Table 1. Required Amount of Major Equipment and Energy Requirement for SMR, DMR, and C3MR Processes61 equipment total required number of pieces of equipment compressor pump heat exchanger MSHE cooler specific energy requirement (kJ/kg·LNG)

SMR process

DMR process

8 3 1

12 5 1

1 3 1216.9−1265.6

1 5 1124.4−1162.9

C3MR process 16 6 6 1 3 992.0−974.0

Figure 7. Economic optimization model development including energy and cost models (Reprinted from ref 61. Copyright 2017. American Chemical Society).

and environment. Figure 6 illustrates the multiscale optimization concept60 and specific multiscale modeling and optimization methodology for the natural gas liquefaction. 2.3.3. Process and Size Selection Challenges. Different liquefaction processes have different energy requirements and amount of equipment. Therefore, a comparison has to be performed among the various liquefaction processes in terms of the energy utilization and economics. Generally, a complex configuration process requires lower energy than a simple configuration process. However, a simple configuration is economically advantageous in small-scale plants, while a complex configuration is more economical in large-scale plants. Thus, the selection of the appropriate process is different in different situations. Therefore, a challenge arises from the need to select the most economical process for a given plant size. The required amount of major equipment and energy

requirements of mixed refrigerant based natural gas liquefaction processes are summarized in Table 1.61 Lee and Moon61 suggested the strategies for the process and size selections of natural gas liquefaction processes. This study constitutes one of the representative studies that attempted to solve this challenge. To determine the economic size range of each process, an optimization model can be developed by integrating the energy and cost models. The cost model can be developed based on the cost of each piece of equipment in accordance with size, to calculate size and operating conditions simultaneously. By applying this method, the economically optimal operating condition can be found. Figure 7 illustrates the development of the economic optimization model that includes the energy and cost models.61 The first step is the development of the energy optimization model based on thermodynamics. This model can calculate the energy requireF


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Figure 8. Problem description and specific profit portfolios for various natural gas liquefaction processes (Reprinted from ref 61. Copyright 2017. American Chemical Society).

greenhouse gas (GHG) regulations are becoming stricter, and therefore, it is necessity to suggest options alternative to releasing BOG to the atmosphere. Recent contributions have shown that the methane emissions from the natural gas value chain are expected to elicit a beneficial impact on climate change that will be 72 times larger than carbon dioxide within the next 20 years.65,66 For this reason, researchers within the PSE community have expended numerous efforts toward the study of BOG, in an effort to minimize BOG or recycle it. The research directions pertaining to BOG can be classified into two categories, namely: (a) minimization and (b) reliquefaction. BOG issues for the LNG value chain can arise in the liquefaction, transportation, and regasification steps that utilize LNG storage tanks. 3.1. Minimizing Boil-off Gas. Identifying the variable which affects BOG generation from the LNG storage tank is one of the important aspects required to minimize BOG. Chen et al.62 developed thermodynamic and heat transfer models to analyze the mechanisms of heat leak on the LNG fuel. Hasan et al.63 performed rigorous and detailed dynamic simulations of BOG generation during the various steps of LNG transportation. They identified various critical and effective factors, such as the nitrogen content, tank pressure, ambient temperature, and voyage length. Adom et al.67 developed a model for the BOG in LNG tanks and found that the structure of the tank affects the BOG generation rate. Lee et al.68 developed a computational method for temperature prediction in the insulated wall of the storage tank on ships carrying cryogenic fluids. Roh et al.69 solved the conservation equations of mass, momentum, and energy, with a computational fluid dynamics (CFD) method to investigate the transient natural convection in a pressurized LNG storage tank. Kurle et al.70 performed simulation studies on BOG minimization and recovery strategies on LNG terminals. They found that the temperature of the LNG highly affects the BOG generation and concluded that BOG generation can be decreased by subcooling LNG. Sharafian et al.71 conducted a performance analysis for LNG storage tanks in refueling stations. They reported that the ratio of the surface area for heat transfer to the LNG volume is a crucial factor in comparing the holding times of storage tanks with different sizes. Migliore et al.72 developed a weather prediction model for LNG storage. Based on the results of their study, it has been reported that a 1 °C change in the ambient temperature results in a BOG change of 0.2%. Miana et al.73

ment and the operating conditions of the equipment. Subsequently, the individual equipment cost model is incorporated in the developed energy optimization model. Finally, the raw materials, and the product cost data are incorporated and added into the model. In addition, the physical constraints for the equipment, e.g., maximum capacity of the equipment, must be included in the model. Using the integrated energy and cost optimization model, specific portfolios can be obtained. By dividing value by the mass of the product, the specific values for energy, cost, and profit can be calculated. Specifically, the specific energy denotes the energy requirement per unit mass of LNG product, the specific cost denotes the cost per unit mass of the LNG product, and the specific profit denotes the profit per unit mass of the LNG product. Therefore, a specific portfolio concept is a very useful tool to compare different plant sizes in accordance with the same standard. The problem description and the results of the process and size selections are presented in Figure 8. The simplified model was adopted for the example mentioned above. Moreover, the continuous cost equation was applied for the optimization of the formulated model. However, the equipment costs do not always lay on the continuous equation because vendors offer equipment in specific capacities and specific costs. Thus, another optimization technique has to be implied to reflect real industrial conditions, such as mixed-integer programming. In addition, the process and size selection model can be applied to the multiscale problem. Upon application, the design of the natural gas liquefaction process and its optimization can contribute considerably to the LNG industry.

3. BOIL-OFF GAS HANDLING ISSUES ON STORAGE Because of the volumetric advantage and the high energy density characteristics, LNG is a highly preferable fuel for transportation using trucks, trains, and ships.15 However, the heat transfer from the environment to the LNG causes the evaporation of LNG. For this reason, BOG is generated, and the pressure of the storage tank increases naturally.62 Currently, LNG carriers either release the BOG to the atmosphere, reliquefy it, or consume it as the fuel needed to maintain the stored LNG at a low temperature and pressure.63,64 However, the loss of BOG directly affects economic losses. Moreover, G


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Figure 9. Schematic diagram of carbon dioxide BOG reliquefaction process utilizing LNG fuel as the cold source: (a) a typical CO2 BOG reliquefaction cycle for CO2 carriers; (b) CO2 BOG reliquefaction process utilizing LNG fuel as the refrigerant (created with data from ref 87).

LNG carriers by applying ejectors. In their proposed design, the ejectors were used to improve the efficiency of the expansion of the pressurized BOG. Rye et al.85 adapted a spray recondenser to the BOG reliquefaction process and performed static simulations for three compositions. They reported that the proposed system provided higher efficiencies up to 6.9% compared to the conventional reliquefaction system. Kochunni and Chowdhury86 compared the LNG BOG reliquefaction systems which are based on the reverse Brayton and the Kapitza cycles. They performed steady state simulations and concluded that the Kapitza system required only a BOG compressor that operated without the need of additional nitrogen gas, yielding a comparable exergy efficiency to that elicited by the reverse Brayton cycle. Many BOG reliquefaction processes have been proposed within the field, and simulations and optimizations have been performed to achieve efficiency enhancements. These types of studies are still being actively conducted and are anticipated to contribute further to the LNG industry. 3.3. Challenges with BOG Recycling. The BOG recycling studies have been mainly focused on the BOG reliquefaction system. These types of research studies aim to minimize BOG for LNG storage. However, alternative access approaches may constitute alternative solutions for BOG handling. One of the appropriate options is the utilization of LNG fuel to other industries, e.g., carbon capture and storage (CCS). Recently, the concept of the use of LNG fuel as a carbon dioxide carrier was proposed and reported in the field of PSE.87,88 In this system, the carbon dioxide is stored in a liquid state, and the BOG of the carbon dioxide is reliquefied through its heat exchange with the LNG fuel. The cold LNG fuel is vaporized during the heat exchange process, and it is subsequently transported to the engine in a gas state. Figure 9 shows the schematic diagram of the carbon dioxide BOG reliquefaction process that utilizes LNG fuel as the cold source.87 Conversely, by using LNG to reliquefy BOG of other materials, considerable savings can be achieved in operational costs for the main equipment and in additional fuel costs for reliquefication of the BOG. The introduced design can also contribute to the use of LNG as a marine fuel, and as CCS technology, by providing more cost-effective solutions for the transportation of liquefied carbon dioxide. By applying CO2 BOG reliquefaction processes, BOG could be fully reliquefied and LNG fuel consumption in engines can be reduced by 26.4− 29.7%. Another option for LNG BOG recycling is the use of produced BOG as a raw material for other industries. One of the issues faced by industry pertains to the improvement of the gas management system for LNG ships. The LNG ships that do not possess reliquefaction plants consume the generated BOG

applied a numerical analysis method to calculate the BOG generation rate for the LNG tanks of ship carriers. They compared heat flow models to predict the evaporation rate of the LNG during ship transportation. Kurle et al.74 performed dynamic simulations to obtain the BOG generation profiles on LNG exporting terminals. These research studies on BOG minimization have contributed considerably to real, industrial applications, by providing valuable information and guidelines on BOG handling. 3.2. Boil-off Gas Reliquefaction. Other contributions have focused on the design of the BOG reliquefaction process and its optimization. Reliquefaction is one of the most efficient alternative approaches to replace the release of the BOG to the atmosphere. Shin et al.75 performed an optimization of the operating conditions for the BOG compression process on LNG storage tanks by applying a boil-off rate model. In their work, an optimal algorithm was proposed for a safe and energy-efficient BOG compressor operation, based on the minimization of the power consumption as the target objective. Sayyaadi and Babaelahi76 performed thermodynamic optimizations of the BOG liquefaction refrigeration cycle. Beladjine et al.77 analyzed the LNG BOG reliquefaction plant by using an exergy approach. Based on the results of their work, it was found that large amounts of exergy losses were dissipated in the compressor and the expander. Baek et al.78 proposed a new design for the BOG reliquefaction process using the cold exergy of the subcooled LNG for recondensing. The major characteristic of the proposed design was the separation of the vaporized light components from heavier components. Park et al.79 suggested a retrofit design for a BOG handling process in LNG receiving terminals by recycling the cold energy from the LNG. Romero et al.80 applied the Brayton cycle to the BOG reliquefaction process and identified the important factors that influence the operating conditions and power requirements. Beladjine et al.81 applied oxygen as the refrigerant to the LNG BOG reliquefaction plant. In their work, the reliquefaction system was designed based on the Claude refrigeration cycle. Liu et al.82 numerically analyzed the energy consumption of the BOG reliquefaction cycle. They simulated and analyzed four different liquefaction systems, including a Claude cycle driven by electrical motor, Brayton cycle driven by a gas turbine, Claude cycle by using BOG as its fuel, and using liquid nitrogen produced in industry. Gómez et al.83 analyzed the cascade of the BOG reliquefaction system for LNG carrier ships. They performed energy and exergy analysis based on the thermodynamic model and proposed evaluation indicators, such as the coefficient of performance (COP), exergy efficiency, irreversibility, and specific energy consumption. Tan et al.84 developed a new system for the BOG reliquefaction system of H


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Figure 10. (a) Gas management system for LNG ships and (b) layout of the steam reforming process using the LNG BOG (created with data from ref 89).

Figure 11. Conceptual energy flow diagram of the LNG value chain.

in the engines, and the excess of it is burned without any energy production. In this manner, the hydrogen production system was introduced based on a steam reforming process using the produced BOG as the raw material.89 The proposed hydrogen production system through a steam reforming plant uses the excess BOG as the raw material and thus avoids its combustion in the gas combustion unit (GCU). Figure 10 presents (a) the gas management system of the LNG in ships and (b) the layout

of the steam reforming process using the LNG BOG. The installation of a hydrogen production plant onboard can offer great versatility to the vessel and can lead to energy savings. The energy efficiency of the suggested process is 64% and 0.37 kg/s of hydrogen can be produced by 1 kg/s of BOG. This approach can contribute considerably to the LNG storage, and the stringent space availability of the ship has to be considered I


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Figure 12. Conceptual energy flows: (a) general LNG regasification process, (b) electricity generation LNG regasification process without intermediate storage, and (c) electricity generation LNG regasification process with intermediate storage.

energy. They proposed a design for a power generation process using a sequence of argon RC, methane RC, direct LNG expansion, and methane (or R14) RC. In another study by Garcia et al.,98 a process design based on two cascaded RCs with a direct LNG expander was suggested for the production of power from LNG cold exergy. A sensitivity analysis of the pinch-point temperature and natural gas outlet pressure was also performed in their work. Choi et al.99 also tried to utilize LNG cold energy to generate power by adopting different process configurations, including a direct expander, RC, direct expander with RC, two-stage cascade RCs, and three-stage cascade RC configurations. The performance indicators used in their work were net power, thermal efficiency, and exergy efficiency. Sun et al.100 suggested the combination of an LNG regasification power plant with an RC using a mixed composition working fluid. The results indicated that a high efficiency could be achieved with a relatively simple configuration. Mehrpooya et al.101 proposed two-stage RCs coupled with LNG and solar energy. In their work, the cold energy of LNG was used to reduce the condensate pressure of the system, and for the production of extra power. Mehrpooya and Sharifzadeh102 introduced an oxyfuel power generation cycle using a solar cycle as its heat source, and LNG as its heat sink. Carbon dioxide was used as the working fluid in their work. 4.2. Cold Utilization to Other Industries. Another method to recover the cold energy from the LNG is using cold energy for other industries. Fazlollahi et al.103 proposed a cryogenic carbon capture system with an energy storage, using natural gas as the working fluid to store energy at off-peak times and to capture carbon at on-peak times. Some of the LNG regasification studies have focused on the integration of the LNG regasification plant and cryogenic air separation unit for the oxy-combustion. Mehrpooya et al.104 proposed an integrated coal gasification process with an air separation unit (ASU). In their system, LNG was used as the heat sink for the ASU and for the cryogenic carbon capture. Mehrpooya and Zonouz105 performed exergy and sensitivity analysis for the integrated power generation system which utilized an ASU, oxyfuel combustion, and carbon capture with LNG regasification. On the other hand, some studies have focused on the LNG cold exergy recovery by utilizing the cold energy in the

in terms of the commercial viability of this approach in the future.

4. LNG COLD ENERGY RECOVERY ISSUES IN REGASIFICATION In the LNG value chain, transported LNG has to be regasified before it is used.9 Generally, the cold energy of LNG is wasted to seawater during the regasification step.90 The amount of the wasted energy of the regasification process is tremendous in the overall LNG value chain. Figure 11 illustrates the conceptual energy flow diagram of the LNG value chain. Based on this point of view, the cold energy recovery is one of the major issues for the LNG regasification process. Many researchers have studied cold energy recovery processes by integrating other processes into the LNG regasification process.12 LNG cold recovery research studies can be categorized into (a) electricity generation approaches and (b) those that use cold energy for other industrial applications. 4.1. LNG Cold Recovery by Electricity Generation. The majority of the cold energy recovery of the LNG is applying the power generation cycle to the LNG regasification process. Aspelund and Gundersen91−94 proposed an LNG transport chain that integrated natural gas power plants with carbon capture and storage (CCS), focusing on the use of cold exergy in their proposed liquefied energy chain. In the onshore section, the cold exergy of LNG is recovered to liquify nitrogen and carbon dioxide. The gasified natural gas was used as fuel in an oxyfuel combustion power plant, and nitrogen and carbon dioxide were produced during power generation. The cold energy of liquid carbon dioxide and liquid nitrogen was used in the offshore natural gas well section to liquify natural gas. Gomez et al.95 tried to utilize the cold energy of LNG to produce electricity using closed Brayton cycles (CBC) and Rankine cycles (RC). The case studies performed in their work used different working fluids: helium or nitrogen for CBC, and carbon dioxide, ammonia, ethanol, or water for RC. In their subsequent work, Gomez et al.96 performed thermodynamic analysis of an integrated system of helium CBC, carbon dioxide RC, and fuel combustion. The effects of different variables, such as the turbine inlet temperature, compressor inlet temperature, compression ratio, and LNG pressure, were analyzed. Garcia et al.97 used RCs in series as a heat sink to recover the LNG cold J


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Figure 13. Process flow diagram of the energy storage system including the LNG regasification process (Adapted with permission from ref 110. Copyright 2017. Elsevier).

important factor for the LNG cold recovery field. To perform the supply chain optimization in this field, several issues must be resolved first. Primarily and foremost, the physical and chemical constraints must be considered in the process of integration design aiming to the commercialization of the technology. Subsequently, the energy and economic analysis for the integration of the suggested process must be performed to provide the information to the supply chain. Finally, the possible options must be well organized, which can be obtained from the LNG cold recovery. Providing rigorous and industrial related information will identify a more economical and environmentally friendly supply chain from the LNG industry to other industries. Correspondingly, this type of work can contribute considerably to the LNG, world energy, and to the industries in the field of process systems engineering.

food industry. Dispenza et al.106 suggested the use of the cold exergy of LNG to make liquid carbon dioxide for use in the agro-food industry and hypermarkets. This concept was introduced and analyzed in detail in the works of Rocca.107,108 4.3. Challenges on LNG Cold Recovery. The electricity generation concept is one of the most efficient ways to recover the cold energy from the LNG. However, the proportion of the produced electricity from the LNG regasification process occupied in the entire energy grid is relatively small. Therefore, using the generated power by the LNG regasification process as an auxiliary power source rather than the main power source can be a more appropriate and efficient way for practical industrial applications. Figure 12 presents the conceptual energy flow for the general LNG regasification process, the electricity generation LNG regasification process without intermediate storage, and the electricity generation LNG regasification process with intermediate storage. In this manner, the challenge arises from the need to store the cold energy and release it flexibly. The cryogenic energy storage (CES) concept can be one solution to the LNG cold energy storage issue. For example, some recent studies proposed the use of the LNG CES process to utilize cold heat suitable for the energy grid.109,110 The cold energy of LNG can be transferred to an energy storage material into two forms, namely, cold heat, and power. The cold heat is used to cool and liquify the working fluid, and the power is used to pressurize the working fluid. The process flow diagram of the energy storage system with the LNG regasification process is illustrated in Figure 13 as a representative example.110 The supply chain management based on the consideration of LNG regasification and other industries is another important challenge in the recovery field of the cold energy from LNG. Most of the supply chain management studies have mostly considered the options in only one specific industry. However, the interaction from industry to industry can be the most

5. CONCLUSION This study has reviewed the key issues and discussed the challenges relevant to the LNG value chain from the process systems engineering point of view. Three major issues were discussed, including the design of the natural gas liquefaction process, its optimization, the BOG handling issue, and the LNG cold recycle issue. First, the modeling, and the process and size selection challenges were discussed for natural gas liquefaction processes. The multiscale and integrated modeling between the liquefaction process and the utility systems can constitute excellent solutions for the advancement of the natural gas liquefaction step in the LNG value chain. Second, the BOG handling issues and the challenges were discussed. Most of the research studies in this field have focused on BOG minimization in the LNG storage tank and on the improvement of the BOG reliquefaction process. In addition to these studies, finding different ways to handle the stored LNG can contribute considerably to the LNG industry. Several appropriate options K


Review


(13) Ríos-Mercado, R.; Borraz-Sánchez, C. Optimization Problems in Natural Gas Transportation Systems: A State-of-the-art Review. Appl. Energy 2015, 147, 536−555. (14) Khan, M.; Karimi, I.; Wood, D. Retrospective and Future Perspective of Natural Gas Liquefaction and Optimization Technologies Contributing to Efficient LNG Supply: A Review. J. Nat. Gas Sci. Eng. 2017, 45, 165−188. (15) Sharafian, A.; Talebian, H.; Blomerus, P.; Herrera, O.; Mérida, W. A Review of Liquefied Natural Gas Refueling Station Designs. Renewable Sustainable Energy Rev. 2017, 69, 503−513. (16) Finn, A. J.; Johnson, G. L.; Tomlinson, T. R. Developments in Natural Gas Liquefaction. Hydrocarb. Process. 1999, 78 (4), 47−56. (17) Kanoğlu, M. Exergy Analysis of Multistage Cascade Refrigeration Cycle used for Natural Gas Liquefaction. Int. J. Energy Res. 2002, 26 (8), 763−774. (18) Bosma, P.; Nagelvoort, R. K. In Liquefaction Technology; Developments through History, 1st Annual Gas Processing Symposium; Doha, Qatar, January 10−12, 2009. (19) Mokarizadeh Haghighi Shirazi, M.; Mowla, D. Energy Optimization for Liquefaction Process of Natural Gas in Peak Shaving Plant. Energy 2010, 35, 2878−2885. (20) Hwang, J.; Roh, M.; Lee, K. Determination of the Optimal Operating Conditions of the Dual Mixed Refrigerant Cycle for the LNG FPSO Topside Liquefaction Process. Comput. Chem. Eng. 2013, 49, 25−36. (21) Nibbelke, R.; Kauffman, S.; Pek, B. Double Mixed Refrigerant LNG Process Provides Viable Alternative for Tropical Conditions. Oil Gas J. 2002, 100 (27), 64−66. (22) Khan, M. S.; Karimi, I. A.; Lee, M. Evolution and Optimization of the Dual Mixed Refrigerant Process of Natural Gas Liquefaction. Appl. Therm. Eng. 2016, 96, 320−329. (23) Wang, M.; Zhang, J.; Xu, Q. Optimal Design and Operation of a C3MR Refrigeration System for Natural Gas Liquefaction. Comput. Chem. Eng. 2012, 39, 84−95. (24) Castillo, L.; Dorao, C. A. On the Conceptual Design of Precooling Stage of LNG Plants using Propane or an Ethane/Propane Mixture. Energy Convers. Manage. 2013, 65, 140−146. (25) Lee, I.; Tak, K.; Kwon, H.; Kim, J.; Ko, D.; Moon, I. Design and Optimization of a Pure Refrigerant Cycle for Natural Gas Liquefaction with Subcooling. Ind. Eng. Chem. Res. 2014, 53 (25), 10397−10403. (26) Lee, I.; Tak, K.; Lee, S.; Ko, D.; Moon, I. Decision Making on Liquefaction Ratio for Minimizing Specific Energy in a LNG Pilot Plant. Ind. Eng. Chem. Res. 2015, 54, 12920−12927. (27) Khan, M. S.; Lee, S.; Getu, M.; Lee, M. Knowledge inspired investigation of selected parameters on energy consumption in nitrogen single and dual expander processes of natural gas liquefaction. J. Nat. Gas Sci. Eng. 2015, 23, 324−337. (28) Khan, M. S.; Lee, S.; Hasan, M.; Lee, M. Process knowledge based opportunistic optimization of the N2−CO2 expander cycle for the economic development of stranded offshore fields. J. Nat. Gas Sci. Eng. 2014, 18, 263−273. (29) Vaidyaraman, S.; Maranas, C. D. Synthesis of Mixed Refrigerant Cascade Cycles. Chem. Eng. Commun. 2002, 189 (8), 1057−1078. (30) Kim, J. K.; Lee, G. C.; Zhu, F. X.; Smith, R. Cooling System Design. Heat Transfer Eng. 2002, 23 (6), 49−61. (31) Lee, G. C.; Smith, R.; Zhu, X. X. Optimal Synthesis of Mixedrefrigerant Systems for Low-temperature Processes. Ind. Eng. Chem. Res. 2002, 41 (20), 5016−5028. (32) Aspelund, A.; Berstad, D. O.; Gundersen, T. An Extended Pinch Analysis and Design Procedure Utilizing Pressure based Exergy for Subambient Cooling. Appl. Therm. Eng. 2007, 27 (16), 2633−2649. (33) Shah, N. M.; Hoadley, A. F. A Targeting Methodology for Multistage Gas-phase Auto Refrigeration Processes. Ind. Eng. Chem. Res. 2007, 46 (13), 4497−4505. (34) Wang, M.; Zhang, J.; Xu, Q.; Li, K. Thermodynamic-analysisbased Energy Consumption Minimization for Natural Gas Liquefaction. Ind. Eng. Chem. Res. 2011, 50 (22), 12630−12640.

have been discussed, such as the utilization of LNG fuel by other industries, and the use of generated BOG as the raw material for other industries. Third, the cold recovery issues have been presented and the challenges have been introduced. The PSE community has expended to this date numerous efforts to recover the cold energy from LNG during the regasification step. The majority of these studies have considered electricity generation and the cold utilization to other industries. This study has presented the challenges on the field of cold energy recovery from LNG in ways appropriate for the commercialization of the approaches to real industrial applications. Identifying key issues and presenting challenges relevant to the research of the LNG value chain will contribute to the advancement of the PSE field and the LNG industry.

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AUTHOR INFORMATION

Corresponding Author

*Tel.: +82 2 2123 2761. Fax: +82 2 312 6401. E-mail: ilmoon@ yonsei.ac.kr. ORCID

Il Moon: 0000-0003-1895-696X Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This work was supported by the Technology Innovation Program (10067793, Engineering Education System of Integrated Design by Case Based Plant Process and Safety) funded by the Ministry of Trade, Industry & Energy (MOTIE, Korea) and Korea Evaluation Institute of Industrial Technology (KEIT, Korea).

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Key Issues and Challenges on the Liquefied Natural Gas Value Chain

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