SIMULATION AND CONTROLLABILITY ANALYSIS OF AN INDUSTRIAL HEAT INTEGRATED DISTILLATION COLUMN

Abstract

Distillation system, are highly energy intensive and always consumes a large amount of energy to achieve the objective. It is thus a prime target for energy conservation. The sources and sinks of energy for the columns can be utilities such as cooling water, refrigerants and steam or other streams within the proces. The insights now be directed toward changing process conditions to improve heat recovery. The column grand composite curve (CGCC) is readily used for targeting for different possible column modification , When developing a heat integrated distillation column, special attention should be focussed on the operating feasibility and dynamics resilience of the new process. Dynamics process models can be developed to gain and retain knowledge about process behavior, to optimize process-operating conditions, to improve control performance. To study the controllability analysis of an heat integrated distillation column, example problem selected from literature for a conventional steady state distillation column separating binary mixture (benzene-toulene). By using Super-Target (Software-Package) and basics bf CGCC heat integration of column achieved. Then three different types of dynamic models have been modelled and used one of them for study of controllability analysis. For different control structures calculated RGA and Niederlinski index and find out best control scheme. .1.1...1••■•••■.1•••■•••■••■•■■■■•1.1yealfilil■ This study successfully demonstrated the use of CGCC for heat integration. The profiles (CGCC) identify appropriate column modification and essentially set "targets" in terms of heat loads and temperature for the modification. The combined use of column targets and pinch analysis curves for the background process enhances the reliability bf column integration in comparison to conventional pinch analysis. Special attention should be focussed on the operating feasibility and dynamic resilience. Steady state controllability analysis by RGA and Niederlinski useful tool for selecting the best control scheme.