(282e) Dynamic Simulation and Optimization for Automation of Distillation Columnshut-Down Operations | AIChE

(282e) Dynamic Simulation and Optimization for Automation of Distillation Columnshut-Down Operations


Xu, Q., Lamar University
Wang, Z., Lamar University
Dynamic Simulation and Optimization for Automation of Distillation Column

Shut-down Operations


Song Wang, Ziyuan Wang, Yiling Xu, and Qiang Xu

Dan F. Smith Department of Chemical Engineering

Lamar University, Beaumont, TX 77710, USA




The shut-down operation of a distillation column is one of critical abnormal operations to a chemical/petrochemical plant. Normally, a planned distillation column shutdown operation consists of three operating procedures: (1) feed and liquid inventory reduction; (2) facility shut-down; (3) decommissioning including liquid discharge, vapor discharge, and nitrogen (N2) purge. The shut-down operation involves concerns of operating time duration, on-spec product recovery, energy consumption, and emission generations, which needs sufficient cares. Because of the complexity in heat and mass transfer in different transient operating procedures, shut-down operations of distillation columns are usually conducted by manual and highly depending on industrial expertise in the reality. Considerably, there are many potential opportunities in the optimal operation of such shut-down operations.

In this paper, a methodology on dynamic simulation and optimization for automation of a distillation column shutdown has been developed. The shutdown operation of C2splitter in an ethylene plant is employed in the base case study. The main objective is to accomplish a quick and automated shut-down operation on the basis of safety and in the meantime to save energy and materials. An Automated Selective Control (ASC) scheme is developed for improving the shutdown operation. The new PID controllers and different operational procedures are also investigated for obtaining a successful shutdown. In this work, associated with various shut-down control strategies, all their operating procedures during the column shutdown are programmed and automated in their rigorous simulation models, respectively. Through iterative dynamic simulations and fine tuning, the identified optimal operating case has significantly improved the column shutdown performance compared with the base case in terms of reducing the total shut-down time and recovering more on-spec products. Meanwhile, this study has also contributions on shut-down operating automation and smooth and safe transitional operations. It has laid out a solid foundation for distillation column shut-down automation and control improvement.

Keywords: Dynamic simulation, Process control, Shutdown, Distillation column, Ethylene plant, Automation.