Dynamic optimization of an LNG plant

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This work aims to enhance the economic profitability of the GL2Z Liquefied Natural Gas (LNG) plant in Arzew, Algeria, by implementing a newly developed plant-wide online optimization strategy. The GL2Z plant operates under challenging conditions, requiring continuous adjustments to LNG productivity to meet downstream demand while maximizing economic returns from liquefaction facilities. The developed online optimization strategy effectively addresses these challenges while adhering to environmental regulations. It leverages operating data from the GL2Z LNG plant and integrates on-line optimization with Model Predictive Control (MPC) technology for each liquefaction train. The online optimization functions as a comprehensive control layer, while MPC serves as the real-time process optimizer. This methodology includes the design of an IT-based plant-wide control system and the development of customized software. A strong emphasis was placed on constructing a dynamic plant model, which is crucial for MPC technology and represents significant engineering savings. The proposed online optimization leads to a 3% reduction in total energy consumption for the plant. By adopting a global control and dynamic optimization approach, this work significantly contributes to the LNG industry's development, opens new research avenues, and translates advanced technologies into customer value.