The LNG industry is reshaping and small-scale LNG activities have been growing at an impressive rate. These activities include the use of LNG as a marine fuel, although LNG bunkering is challenging due to the plurality of vessels, containment technologies as well as operational profiles.
However, LNG’s cryogenic nature entails a completely different behaviour than traditional oil-based fuels. Thus, the sustainable development of this new market for LNG requires adequate technologies and best practices to ensure an optimised energy chain. For example, multiple parameters have to be taken into account in order to perform safe LNG bunkering operations and prevent the risk of venting natural gas to the atmosphere.
Today’s available models are mostly used to simulate LNG behaviour in large onshore or offshore tanks. However, limited feedbacks is available on LNG behaviour inside small-scale bunkering tanks. This new small-scale LNG chain implies hotter inner shells, complex transfer phenomena and potential mixings. All of these features make the large-scale findings irrelevant if applied to smaller volumes. The use of LNG as a marine fuel together with new technologies and practices makes the development of adapted simulation capabilities necessary.
ENGIE Lab LNG developed the “LNGgauge” to provide, at minimum cost and with a few sensors only, crucial data for LNG-fuelled vessel operators; such as an accurate live estimation of the holding time, energy content and Methane Number inside an LNG storage. It could also be adapted to predict the LNG composition. In 2017, this model was validated during an experimental campaign carried out on a 300 litre pressurised tank fitted with multiple sensors, in cooperation with the fuel tank manufacturer, SAG. The “LNGgauge” is now ready to be implemented on small-scale LNG vessels, onshore or offshore storages.
Figure 1 - LNGgauge: from theory to real testing
Another interesting tool developed at the LNG Lab is the “LNG bunkering software” meant to enable the simulation of any situation related to LNG bunkering. It will therefore help with optimising boil-off-gas (BOG) management, assessing the BOG quality and LNG ageing as well as predicting the pressure changes and LNG qualities mixing. This software will support both designers and operators while simulating a wide range of operations:
Appropriate models for each physical phenomenon have been selected and implemented in the software. Both experiments and operational feedback have highlighted the software’s ability to predict LNG behaviour inside small-scale tanks.
Figure 2 - ENGIE Zeebrugge bunkering vessel
Moreover, in 2016, data was collected and analysed from two of ENGIE’s LNG carriers. This data included pressure, the temperature of liquid and gas phases inside LNG tanks, the volume of gas used by compressors and LNG forcing vaporizers, and also the movement of the ships. A big data methodology was used to gather and analyse the data coming from LNG carriers (several million data points). LNG cargo reactions to different management procedures were deduced from this analysis. Parallel to this, heat transfer and thermodynamics modelling was carried out based on ENGIE Lab LNG behaviour expertise. The final model of “Cargo On Board” is able to predict, for any possible cargo management strategy, the resulting evolution of cargo characteristics. The validity of this predictive model was successfully confirmed with data collected on LNG carriers, and in particular during harsh maritime conditions.
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Image courtesy of ENGIE lab CRIGEN
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