Real-time optimization results processing

Zhang, Y. Nadler, D. Forbes, J.F. Results analysis for trust constrained real-time optimization. J. Process Control 2001, 11 (3), 329-341. 

Some recent applications have benefited from advances in computing and computational techniques. Steady-state simulation is being used off-line for process analysis, design, and retrofit process simulators can model flow sheets with up to about a million equations by employing nested procedures. Other applications have resulted in great economic benefits these include on-line real-time optimization models for data reconciliation and parameter estimation followed by optimal adjustment of operating conditions. Models of up to 500,000 variables have been used on a refinery-wide basis. 

It should be noted that the optimization problems solved for levels 2 and 3 begin to merge as the plantwide optimization begins to set targets for the unit operations in many process units. This large-scale, frequent optimization of operating conditions is known as real-time optimization (RTO). RTOs are run approximately every 30 minutes to 1 hour, with the resulting optimal setpoints downloaded to model predictive controllers (MPC). 

We have recently reviewed the use of vibrational spectroscopy in supercritical fluids [2] and the theme common to most of our projects is the use of spectroscopy for real-time optimisation of processes in supercritical solution. Such optimisation is considerably more important in supercritical fluids than in conventional solvents because the tunability of the fluids results in a greater number of parameters which can affect the outcome of a reaction. Thus, the chances of hitting the optimal conditions purely by trial and error are much less in supercritical solution than in conventional reactions. Below, we give three examples of our approach, synthesis of polymers, transition metal hydrogen compounds, and the use of flow-reactors. 

Yip, W.S. Marlin, T.E. Results analysis for a Constrained real-time optimization. International Symposium on Advanced Control of Chemical Processes, ADCHEM 2003, Hong Kong Jan 2004, 501-506. 

Recent improvements of process controls have resulted in improved operations and higher profits. Real-time optimization of thermal cracking furnaces based on the feedstock and product flow rates, pricing, and fuel cost has become a reality. Implementation of pinch technology, process separation network analysis, and optimization has made significant reductions in energy demands. 

This paper investigate the feasibility using of grey-box neural type models (GNM) for design and operation of model based Real Time Optimization (RTO) systems operating in a dynamical fashion. The GNM is based on fundamental conservation laws associated with neural networks (NN) used to model uncertain parameters. The proposed approach is applied to the simulated Williams-Otto reactor, considering three GNM process approximations. Obtained results demonstrate the feasibility of the use of the GNM models in the RTO technology in a dynamic fashion. 

The results indicate that NIR does indeed have both the resolution (specificity) and the sensitivity needed for this application. The NIR method was successfully implemented in the plant, replacing the conventional GC method and allowing real-time control and optimization of the PDEB separation process. 

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