(158c) A Framework for Integration of Design, Scheduling and Control for Chemical Processes Under Disturbances

Chemical process design is key for the optimal operation and control of chemical processes under the effect of external perturbations and process uncertainty. In addition to this, process scheduling also plays a critical role in facilities from various sectors, e.g. semiconductor manufacturing, electricity generation, chemical process industry, etc. The most common approach to address optimal design is known as the sequential approach, where the design, control, and scheduling are all considered separately. This approach is often inadequate, as it assumes steady state optimization for the specification of design and scheduling decisions, which are often suboptimal, as the dynamic interactions of design, control, and scheduling are not taken into account. An alternative emerging approach is to perform simultaneous optimization of design, control, and scheduling. This approach has the potential to produce improved solutions; however, it is a challenging task because it greatly increases the complexity of the problem to be addressed. Some of the challenging tasks associated with this approach are finding suitable approximations for process disturbances, accounting for parameter uncertainty, and reducing the computational time required to solve the resulting optimization formulations.

The aim of this research is to develop a mathematical framework for integrated optimization of design, control, and scheduling of chemical engineering systems under process disturbances. At this stage, the proposed framework optimizes design, control, and scheduling of a non-linear chemical system by using an iterative decomposition algorithm. At each iteration, the design, control, and scheduling are optimized under critical realizations of the process disturbances. Following that, the specified design, control, and scheduling scheme is fixed, and a dynamic feasibility problem is solved to determine the worst-case realization in the process disturbances (identified from a pre-specified set of possible disturbance realizations). The identified critical disturbance realization is then added to the set of worst-case disturbance realizations encountered from previous iterations in the algorithm. The loop then continues to the next iteration, where a new design, control and scheduling scheme is sought in the presence of the updated set of critical realizations in the disturbances. The decomposition algorithm continues up until no further critical realizations in the disturbances that produce process constraint violations are detected. This framework has been applied to a case study, which involves a single CSTR continuously switching between production of multiple different product grades. The design, control, and scheduling provided by the framework have been proven to be optimal when compared to the sequential design approach.

In future work, this framework will be expanded to include multiple process units and parameter uncertainty. This framework will be of great value to the chemical process industry, as the integrated optimization of design, control, and scheduling facilitates improvements in overall efficiency and process economics.