67b Better Plant Startup Via Simulation

Ku Yen Li1, Helen H. Lou2, Amarnath Singh2, Sandeep Gore1, Vijay Patel2, and Sasha Vragolic3. (1) Lamar University, Chemical Engineering Department, P. O. Box 10053, Beaumont, TX 77710, (2) Department of Chemical Engineering, Lamar University, P.O.Box 10053, Beaumont, TX 77710, (3) Oxides and Olefins Plant, Huntsman Corporation, P.O. Box 847, Port Neches, TX 77651

The process industries are faced with an increasingly competitive environment, ever-changing market conditions, and government regulations; yet, they still must increase productivity and profitability. Out of many tasks performed by operations department in chemical process industry safe startup of a plant or unit is the most important task. Even though the operating procedure of unit is standardized, the actual path followed differs from one operation group to another. Generally, experience alone is not always sufficient to answer the questions that continually arise – and ‘trial and error' efforts to provide meaningful insight are usually not acceptable.

This paper presentation discusses the use of simulation, both steady state and dynamic, as a tool for making critical decisions during plant startup. Although steady state simulation can give useful information it fails to describe the dynamic behavior of a process during startup. Dynamic simulation is highly beneficial to the operations group. By knowing the dynamic behavior of the process plant the operations group can identify and correct the anticipated problems before they occur. This minimizes the costs of flaring and raw material and reduces emissions associated with startup.

Huntsman Petrochemical and the Center of Process & Information Technology (CPIT) at Lamar University worked together to study a flare reduction during an olefin plant startup. The study was focused on the recovery section of the olefin plant. The recovery section consists of three columns, namely demethanizer, deethanizer and ethylene tower. Initial steady state model was developed and validated by using the process data from the plant. After validation, this steady state model was transferred into a dynamic simulation model using control strategies, control parameters, and equipment dimensions. The dynamic simulation of the startup procedures was used to predict the time required for achieving product specification for towers, suggest the optimum control tray location in towers, provide the dynamic responses of the tower with and without additional side stream feeds.