Abstract
In today's competitive LNG market, reducing energy consumption is critical for enhancing both profitability and sustainability. The hot section of the LNG processing, which includes inlet receivers, acid gas removal, and dehydration units, is the most thermally demanding. Previous optimisation methods targeted each unit separately. On the other hand, this work details the development of a data-driven optimisation framework to minimise energy across these interdependent units. Preliminary application of the framework has yielded encouraging results. Utilising HYSYS process simulation data, the study successfully identifies critical operating variables-such as reboiler duty, amine circulation rate, and air-to-furnace stoichiometry-that drive production efficiency and energy consumption. Results indicate that a baseline condensate mass flow of 2, 048.71 kg/h is achieved at a stripper bottom temperature of 137.74 °C, while the AGRU produces sweet gas with 0.18 ppm H2S. Optimisation using Pareto frontier analysis reveals a "knee" point in the SRU at 96.9% recovery efficiency, balancing elemental sulfur production (7, 622.24 kg/h) against heating loads. The findings provide mathematical coefficients for plant control to maximise yield while maintaining strict environmental stack limits.