(651e) A Flexible Separation Network Synthesis Framework for Superstructure-Based Process Synthesis

Multiple optimization-based methods have been proposed for the synthesis of distillation networks due to a vital role of distillation in chemical/petrochemical facilities. Superstructure-based optimization methods, where a structure that embeds all potentially useful elements of the system and their interconnections is optimized, have received, in particular, a lot of attention¹. However, most existing methods for superstructure-based distillation network synthesis have been developed to be utilized within a sequential/hierarchical process synthesis approach², where the distillation network synthesis problem is solved separately after the reactor network synthesis has been solved. In other words, the information from the reactor network, such as the set of components and their component flow rates, is given a priori. Furthermore, only a single feed to the separation network system is typically considered in existing methods. Finally, it is typically assumed that the target outlet streams of the distillation network are given and are often pure components.

However, when we consider the synthesis of the distillation network along with the reactor network simultaneously, feed information and product specs can vary; for example, reaction/catalyst selection in the reactor can change the compositions of the feed into the separation system and even the set of components to be separated. Furthermore, the number of feeds (effluents from reactors) and products (final products or recycle streams into the reactors) of the distillation network can also vary depending on the activation of reactor units in the reactor system^3,4.

Accordingly, in this work, we propose a superstructure-based distillation network synthesis model for a broader problem statement that can address the aforementioned limitations of existing methods. The proposed model enables not only a seamless integration with reactor network synthesis models but also incorporates additional configurations in the superstructure. The key characteristics of the proposed model are the following: it allows (1) multiple inlets into the separation system with variable set of components; (2) thermal couplings between columns, which can reduce the energy requirement in the distillation network^5,6; and (3) stream bypasses, which can lead to significant utility load reduction while producing non-pure products. Notably, a flexible distillation column model, which can address the variability in the feed, is adopted. Also, several logic rules and constraints are proposed, which are tailored for the proposed distillation network.

Using a number of examples, we illustrate how the proposed distillation network synthesis model can be used to identify superior solutions with a significantly less energy usage due to: (1) improved modeling via the flexibility of the distillation network synthesis model and (2) extended solution space due to stream bypasses and thermal coupling. Also, we discuss some interesting interactions between stream bypasses and thermal coupling, which have not been studied in literature.

References

1. Chen Q, Grossmann IE. Recent developments and challenges in optimization-based process synthesis. Annu Rev Chem Biomol Eng. 2017;8:249-283.
2. Douglas JM. A hierarchical decision procedure for process synthesis. AIChE J. 1985;31(3):353-362.
3. Kong L, Maravelias CT. Expanding the scope of distillation network synthesis using superstructure-based methods. Comput Chem Eng. 2020;133:106650.
4. Ryu J, Kong L, de Lima AEP, Maravelias CT. A generalized superstructure-based framework for process synthesis. Comput Chem Eng. 2020;133:106653.
5. Halvorsen IJ, Skogestad S. Minimum energy consumption in multicomponent distillation. 2. Three-product Petlyuk arrangements. Ind Eng Chem Res. 2003;42(3):605-615.
6. Fidkowski ZT, Agrawal R. Multicomponent thermally coupled systems of distillation columns at minimum reflux. AIChE J. 2001;47(12):2713-2724.