(87c) Use Exergy Analysis to Increase Efficiencies of Mid-Scale LNG Processes
AIChE Spring Meeting and Global Congress on Process Safety
2014
2014 Spring Meeting & 10th Global Congress on Process Safety
14th Topical Conference on Gas Utilization
LNG Simulation, Operations and Control
Tuesday, April 1, 2014 - 2:30pm to 3:00pm
Mid-scale LNG processes are widely used all around the world, and it has the potential to compete with pipeline transportation for small and medium shale gas fields.
To compete with pipeline transportation, cost is essential for mid-scale LNG processes. In a typical LNG value chain, the liquefaction section consumes 30%-45% of the total operating costs. If the operating cost of an LNG process could be reduced, the total cost of LNG value chain will also be reduced.
LNG processes are basically refrigeration systems. Exergy is a very useful thermodynamic property to analysis refrigeration systems. Exergy means the maximum useful work possible during a process that brings the system into equilibrium with environment. From exergy point of view, LNG processes get exergy from mechanical work and transfer it to natural gas to make it far from equilibrium with environment.
In this paper, a new exergy analysis method was developed for LNG processes. In this method, not only the overall exergy of the whole process, but also exergy transfer between facilities in the process are considered. Exergy is classified as three categories: temperature related exergy, pressure related exergy and phase-change related exergy. The three types of exergy could change to each other, and every facility can only process certain types of exergy. Exergy loss for each facility is evaluated. Process improvement methods are used to reduce exergy loss and increase process efficiency.
A C3MR process was used as case study. Two improvements were made for the original process. The first improvement only changes operation conditions, and the second improvement changes process itself. Results show that the overall operating cost could be reduced by 15% for the second improvement, and device investment for the second improvement is relatively small.