Dynamic optimization of an LNG plant

This work aims to increase the economical profitability of the GL2Z Liquefied Natural Gas (LNG) plant, in Arzew, Algeria by implementing a newly developed plant-wide on-line optimization strategy. The GL2Z plant is very challenging to operate as the LNG productivity must continuously be adjusted to the demand of the downstream facilities on one hand and for the maximization of the economical return from the liquefaction facilities on the other. The developed on-line optimization strategy for the GL2Z LNG plant faces successfully such a challenging task and satisfies the environmental restrictions. The proposed strategy is based on operating data of the GL2Z LNG plant. It combines the plant on-line optimization with the Model Predictive Control (MPC) Technology implementation on each liquefaction train. On-line Optimization is, functionally, a plant-wide control layer, whereas the MPC Technology is the on-line process Optimizer. According to this methodology, the required IT-based plant-wide control system has been designed and customized software has been developed. Since the liquefaction process model is the corner-stone of the MPC technology, a particular attention was brought to the modeling effort as it also represents significant savings of engineering effort. The work describes the methodology aimed to construct the required dynamic plant model. The proposed on-line optimization yields to a reduction of the plants total energy consumption by 3%. By implementing a global control and dynamic optimization approach to the GL2Z LNG plant, this work offers a significant contribution to the development of the entire LNG industry, opens new challenging research perspectives and transforms advanced technologies into customer values.