Optimization strategy for long-term catalyst deactivation in a fixed-bed reactor for methanol synthesis process
Document Type
Article
Publication Date
1-1-2012
Abstract
In this study, the application of a repeated process estimation-optimization strategy is investigated for a methanol synthesis reactor system in the presence of a slowly deactivating catalyst. The purpose of this strategy is to update the optimal transition of the control variable profile with feedback from the process measurements. A state and parameter estimation method is formulated where the objective is to determine the current reactor state and model parameter from available process measurements data. In this strategy, the corresponding optimization problems are formulated as DAE-constrained optimization problems that are solved by using full discretization and large-scale NLP solver. Simulation results indicate that the strategy is able to track the theoretical optimum profile of the selected control variable as the catalyst deactivates. Moreover, with the formulated strategy, the performance of the reactor system in the presence of a long-term catalyst deactivation and unexpected plant operational changes can be improved significantly.
Keywords
Catalyst deactivation, Dynamic optimization, Interior point solver, Methanol synthesis, Process feedback, Simultaneous solution, Control variable, Fixed-bed reactors, Full discretization, Interior point, Methanol synthesis reactors, Model parameters, Operational changes, Optimal transition, Optimization problems, Optimization strategy, Optimum profile, Parameter estimation method, Process measurements, Reactor systems, Catalysts, Chemical reactors, Constrained optimization, Parameter estimation, Synthesis gas manufacture.
Divisions
fac_eng
Publication Title
Computers & Chemical Engineering
Volume
44
Publisher
Computers & Chemical Engineering
Additional Information
976SA Times Cited:0 Cited References Count:38