(14b) Some Key Issues on a Successful Application of Real Time Optimization System to an Ethylene Plant | AIChE

(14b) Some Key Issues on a Successful Application of Real Time Optimization System to an Ethylene Plant

Authors 

Rickard, K. A. - Presenter, Equistar Chemicals, LP, A Lyondell Company
Tzouanas, V. K. - Presenter, Equistar Chemicals, LP, A Lyondell Company
Gopalakrishnan, M. - Presenter, Equistar Chemicals, LP, A Lyondell Company
Ye, N. - Presenter, Applied Manufacturing Technologies (AMT), LP
Ayala, J. - Presenter, Applied Manufacturing Technologies (AMT)
Monical, M. - Presenter, Applied Manufacturing Technologies (AMT)
Wissner, M. - Presenter, Equistar Chemicals, LP, A Lyondell Company
Arman, T. - Presenter, Equistar Chemicals, LP, A Lyondell Company
Montgomery, C. W. - Presenter, Equistar Chemicals, LP, A Lyondell Company
Ferguson, T. G. - Presenter, Equistar Chemicals, LP, A Lyondell Company
Kelly, T. E. - Presenter, Equistar Chemicals, LP, A Lyondell Company
Matthews, E. - Presenter, LyondellBasell Industries


Equistar and Applied Manufacturing Technologies (AMT) have implemented a real-time optimization (RTO) system* on the ethylene plant at Lyondell Equistar's Chocolate Bayou Facility. The RTO system contains an integrated plant model that is a combination of rigorous and simplified plant section models covering both the olefins and aromatics units. The decision of whether or not to model a plant section rigorously or simply is based on whether the model is rigorous enough to capture the majority of benefits that a RTO system can bring, while simplified to an extent that the plant model represents the needed relations about the plant production, constraints and optimal moves. As a result, the RTO system can run very robustly solving 99.9% of the time and implement setpoints at least every 30 minutes (including waiting time after setpoint implementation). This type of RTO system responds to plant operating condition changes and active constraint changes more quickly than traditional RTO systems that run less frequently. An Olefins RTO system based on this approach requires less effort in the design, development and implementation phase, and is more robust requiring less maintenance effort.

The RTO system working consistently with the advanced process control (APC) system is a key factor that directly affects the performance and success achieved by the RTO application. The interface between the RTO system and the APC system** covers setpoint implementation, constraint handling, and steady state target coordination. Additional factors affecting the success of an RTO system include: an effective way to acquire feed stock composition information and reliable pricing information; and a reliable operator interface.

This paper will discuss this new approach to on-line optimization as well as the key factors determining the overall success of the application.

Notes: * The RTO system uses furnace coil SPYRO model which is a product of Technip Corporation, and the RTO system is implemented within the environment of Aspen Plus, Aspen Optimizer and Aspen Online which are products of Aspen Technology, Inc. ** The APC/CLP system is implemented by AMT and Equistar engineers using DMCplus with feed maximization (CLP). DMCplus and CLP are products of Aspen Technology, Inc.