(273h) Novel Method for the Integration of Flexibility and Stability in Design of Chemical Processes Under Parametric Uncertainties

Chen, Y., Tsinghua University
Yuan, Z., Tsinghua University
Chen, B., Tsinghua University
Process optimization under parametric uncertainties is a challenging topic of practical importance in the Process Systems Engineering since uncertainties can always cause infeasibilities, detrimental production disturbances and extra capital or operating costs. Flexibility and stability are two crucial components of chemical process operability [1]. Flexibility guarantees feasible steady-state operation over a range of uncertain operating conditions, while stability represents the tolerance for slight perturbations and emphasizes the dynamic characteristics of a system [2]. In previous research, flexibility and stability have been studied separately, resulting in flexible regions containing unstable areas that are difficult to operate and control.

The major difficulty of integrating flexibility and stability lies in how to convert the Lyapunov stability conditions into specific constraints embedded within the flexibility analysis model. This paper proposes a novel method for integrating flexibility with stability, which incorporates stability constraints obtained by singularity theory based stability analysis method into the MINLP model to calculate flexibility index. The singularity theory based stability analysis method can characterize regions in parameter space over which different kinds of stability characteristics may exist.

As a result, a stable flexible region is obtained, which not only adapts to variations in uncertain parameters, but also ensures stable operation and process inherent safety. 1,3-propanediol fermentation system and methyl methacrylate polymerization process have been studied to demonstrate the effectiveness of the proposed methodology. The obtained results illustrate that the novel method for considering flexibility and stability simultaneously possesses distinct computational advantages over the eigenvalue optimization algorithm, so it has great potential for applications in large-scale systems.


[1] Floudas, C. A., Gümüş, Z. H., & Ierapetritou, M. G. (2001). Global optimization in design under uncertainty: feasibility test and flexibility index problems. Industrial & Engineering Chemistry Research, 40(20), 4267-4282.

[2] Jiang, H., Chen, B., Wang, H., Qiu, T., & Zhao, J. (2014). Novel method for considering process flexibility and stability simultaneously. Industrial & Engineering Chemistry Research, 53(38), 14765-14775.