Dynamic simulation of LNG loading, BOG generation, and BOG recovery at LNG exporting terminals

Kurle, Yogesh M.; Wang, Sujing; Xu, Qiang

doi:10.1016/j.compchemeng.2016.11.006

Cited by 47 publications

(17 citation statements)

References 17 publications

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“…Compared with other fossil fuels, natural gas (NG) is considered a sustainable and potential source of energy in the future [3][4][5]. Considering that the volume of liquefied natural gas (LNG) is 600 times smaller than the gaseous state of NG [6,7], LNG is considered as an economic transportation approach when the gas transportation pipeline is longer than 1500 km [8][9][10].…”

Section: Introductionmentioning

confidence: 99%

MINLP Model for Operational Optimization of LNG Terminals

Xiaoyan

Zhao

2021

Processes

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Liquefied natural gas (LNG) is a clear and promising fossil fuel which emits less greenhouse gas (GHG) and has almost no environmentally damaging sulfur dioxide compared with other fossil fuels. An LNG import terminal is a facility that regasifies LNG into natural gas, which is supplied to industrial and residential users. Modeling and optimization of the LNG terminals may reduce energy consumption and GHG emission. A mixed-integer nonlinear programming model of the LNG terminal is developed to minimize the energy consumption, where the numbers of boil-off gas (BOG) compressors and low-pressure (LP) pumps are considered as integer variables. A case study from an actual LNG terminal is carried out to verify the practicality of the proposed method. Results show that the proposed approach can decrease the operating energy consumption from 9.15% to 26.1% for different seasons.

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Section: Introductionmentioning

confidence: 99%

MINLP Model for Operational Optimization of LNG Terminals

Xiaoyan

Zhao

2021

Processes

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“…The study proposed a new design to minimize energy consumption and improve exergy efficiency. More recently, Kurle et al [28] performed dynamic simulations of an LNG vessel's loading process to obtain the JBOG generation profile. The researchers also studied the effect of the holding mode heat leak, initial ship-tank temperature, tank cooling rate, and JBOG compressor capacity.…”

Section: Introductionmentioning

confidence: 99%

Study on Boil-off Gas (BOG) Minimization and Recovery Strategies from Actual Baseload LNG Export Terminal: Towards Sustainable LNG Chains

et al. 2021

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Boil-off Gas (BOG) generated at the liquefied natural gas (LNG) export terminal causes negative economic and environmental impacts. Thus, the objective of this study is to develop and evaluate various handling schemes to minimize and/or recover the generated BOG from an actual baseload LNG export terminal with a capacity of 554 million standard cubic feet per day (MMSCFD) of natural gas feed. The following three main scenarios were assessed: JBOG re-liquefaction, LNG sub-cooling, and lean fuel gas (LFG) reflux. For the LNG subcooling, two sub-cases were considered; standalone subcooling before LNG storage and subcooling in the prevailing liquefaction cycle. Steady-state models for these scenarios were simulated using Aspen Plus® based on a shortcut approach to quickly evaluate the proposed scenarios and determine the promising options that should be considered for further rigorous analysis. Results indicated that the flow of attainable excess LNG is 0.07, 0.03, and 0.022 million metric tons per annum (MTA) for the standalone LNG sub-cooling, LNG sub-cooling in the main cryogenic heat exchanger (MCHE), and both LFG-refluxing and jetty boil-off gas (JBOG) liquefaction, respectively. This in turn results in a profit of 24.58, 12.24, 8.14, and 7.63 million $/year for the LNG price of 7$ per Metric Million British Thermal Unit (MMBtu) of LNG.

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“…Results show that jetty BOG generation ranges from 1.2% to 2.5% of total amount of LNG transfer. LNG loading time increased by about 8 h due to the ship-tank being warmer by 30 • C [21].…”

Section: Introductionmentioning

confidence: 99%

Effect of Parameters on Vapor Generation in Ship-to-Ship Liquefied Natural Gas Bunkering

Lee,

Choi,

Jung

et al. 2020

Applied Sciences

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Liquefied natural gas (LNG) is attracting increasing attention as an alternative fuel in the maritime sector, as it can reduce harmful emissions for compliance with stricter environmental regulations. Owing to this environmental advantage, the number of ships using LNG as a fuel is increasing; thus, the demand for ship-to-ship LNG bunkering is increasing. One of the challenges of ship-to-ship LNG bunkering is boil-off gas (BOG) management, as it is more difficult than normal BOG management. This study analyzed the influences of the parameters on vapor generation, including the temperature difference between the bunker tank and receiving tank, bunkering flow rate, insulation performance, and compositions. A model based on a typical bunkering system was established, and a dynamic simulation was conducted using a commercial process simulator, Aspen HYSYS. The results indicated that as the initial temperature of the receiving tank increased, the amount of vapor return increased proportionally. In addition, increasing the bunkering flow rate decreased the amount of heat entering through the pipes and tanks; however, the heat dissipated by the pump shaft power increased. Different LNG compositions in the bunker tank led to changes in the initial pressure of the bunker tank, influencing the vapor return and vapor generation in the receiving tank. Through a parametric study, it was found that the pressure of the tank is the most important factor in terms of vapor return and vapor generation. As such, a pressure control method was proposed for the tank, so as to reduce vapor generation and vapor return. With pressure control, the total amount of vapor return to the bunker tanks is reduced from 7392 to 3317 kg. The net vapor generation in the receiving tank is reduced by up to 4047 kg and the net vapor generation in the overall system is reduced by 16.2%.

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Dynamic simulation of LNG loading, BOG generation, and BOG recovery at LNG exporting terminals

Cited by 47 publications

References 17 publications

MINLP Model for Operational Optimization of LNG Terminals

MINLP Model for Operational Optimization of LNG Terminals

Study on Boil-off Gas (BOG) Minimization and Recovery Strategies from Actual Baseload LNG Export Terminal: Towards Sustainable LNG Chains

Effect of Parameters on Vapor Generation in Ship-to-Ship Liquefied Natural Gas Bunkering

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