Optimization-based methodologies for integrating design and control in cryogenic plants
Academic Article
Overview
Identity
Additional Document Info
Other
View All
Overview
abstract
The aim of this work has been to investigate the potential of advanced mixed-integer dynamic optimization (MIDO) strategies 2 to identify optimal design and control schemes for an industrial cryogenic air separation plant (ASP). The MIDO framework is applied to include, along with the control structure choice, selection and sizing of process components. From an economic point of view, this technique has shown that utility consumption and capital cost can be reduced, giving an improvement in the overall profitability. By considering discrete decisions within the optimization framework (instead of a sequential approach) great benefits can be achieved. The MIDO framework has shown to work efficiently for such a large problem, reaching a solution (optimal design and control structure) in four iterations.2Under development at the Centre for Process Systems Engineering, Imperial College (E.N. Pistikopoulos, J.D. Perkins and co-workers). 2002 Elsevier B.V. All rights reserved.