(212a) Rigorous Dynamic Modeling and Model Predictive Control of Air Separation Unit as Part of IGCC Power Plant

A cryogenic air separation unit (ASU) plays a vital role in future oxygen-blown combustion/gasification-based power plant. It is subject to periods of significant changes in production demand due to which an effective control structure is needed to minimize the impact of transient operation on product purity. ASU specifically designed for IGCC operate at elevated pressures leading to design complexities due to decreased separation efficiency. In addition, the column pressure, temperature and composition dynamics float in tune with the oxygen-product flowrate and rapid pressure fluctuation from the gas-turbine-combustor section (disturbances), leading to erratic mass flow-fluctuations in the distillation columns, specifically due to tight reboiler-condensor energy integration. It must also be emphasized that current floating pressure arrangements pose significant control design difficultly in terms of fixed temperature control, and alternate control schemes using either composition control loops or differential tray temperature loops must be devised.

In this paper, rigorous study involving many possible steady state design configuration within a single flow-sheet using optimization and sensitivity tools is presented. These studies have been done using a fully pressure-driven dynamic modeling using Aspen Plus/Aspen Dynamics. Different process flow-sheets corresponding to IGCC and non-IGCC scenarios have been studied and compared in terms of structural design, energy requirements and process controllability. A rigorous heat-exchanger design has been incorporated into the model to study carefully the effect of thermal lags and wrong-way (inverse response) temperature effects due to feed-effluent heat exchange. Currently, direct oxygen and nitrogen purity control is attained by measuring compositions directly. The prospect of controlling the unit, especially during vast pressure variations, solely using temperature measurements is highlighted using a differential tray-temperature approach. Further, a model predictive control strategy that handles rate-of-change constraints imposed by the process design of the air separation unit has been studied and compared with performance using decentralized classical PID schemes. Additionally, results showing controller performance when the ASU is integrated with IGCC power cycle have been given.