(50c) Improving the Profitability of LNG Plants Using Advanced Process Control | AIChE

(50c) Improving the Profitability of LNG Plants Using Advanced Process Control

Authors 

Valappil, J. V. - Presenter, Bechtel Oil & Gas Inc
Mehrotra, V. - Presenter, Bechtel Corporation
Ramani, R. - Presenter, ConocoPhillips Company
Gandhi, S. - Presenter, ConocoPhillips Company


The rapid growth in the natural gas demand has posed unique technical challenges for the Liquefied Natural Gas (LNG) industry. There is a significant emphasis on utilizing the existing plant up to their maximum potential. LNG plants are characterized by operation challenges including varying ambient conditions, heat integration and product quality constraints. There are many benefits to be derived from the application of advanced process control (APC) to LNG units. For LNG plant owners, the main benefit that can be realized using the optimization is in increasing the plant production. Other benefits like efficiency increase, increase in natural gas liquids (NGL) production and reduced operator intervention are also valuable. This paper discusses the application of advanced process control technology to LNG plants based on ConocoPhillips Optimized CascadeSM process. Plantwide dynamic simulation model is used as a tool to design and develop the advanced control.

The Optimized Cascade LNG Process is characterized by three refrigeration systems that share the refrigeration load. The main constraints that limit the production rate are the gas turbine power outputs (Other constraints may become active less frequently). In order to maximize production, the different plant-operating conditions have to be varied to operate the plant at the turbine or other equipment constraints. The main external factors that affect the operation are the ambient conditions and the feed composition.

A first-principle dynamic model of the LNG plant is used to develop the advanced control scheme. This dynamic model is interfaced to the advanced control software to facilitate testing of the controller. Further, the dynamic model is used to conduct the step testing, develop APC models and to tune the controller. It is important to accurately estimate the benefits from advanced control to justify its implementation. In most cases, purely plant data driven methods have been used to estimate the benefits. For the application considered here, the actual operation of the plant with and without the advanced controller is simulated to get an accurate estimate of the benefits. The performance of the plant with optimization under various conditions is studied with dynamic simulation. There are several advantages to doing this. The first one is that the constraints during the normal operation of the plant are easily identified. Second, any changes in constraints are detected using dynamic simulation. It helps to prepare the operators and train them to be ready for hitherto unknown operating regions. Thirdly, the plantwide dynamic simulation provides accurate representation of the operating conditions without the disturbances and noise.