Optimal design of extractive dividing-wall column using an efficient equation-oriented approach

doi:10.1007/s11705-020-1977-y

Front. Chem. Sci. Eng.

2021, Vol. 15

Issue (1) : 72-89 https://doi.org/10.1007/s11705-020-1977-y

RESEARCH ARTICLE

Optimal design of extractive dividing-wall column using an efficient equation-oriented approach

Yingjie Ma¹, Nan Zhang¹, Jie Li¹(

), Cuiwen Cao²

¹. Centre for Process Integration, Department of Chemical Engineering and Analytical Science, School of Engineering, The University of Manchester, Manchester M13 9PL, UK
². Key Laboratory of Advanced Control and Optimization for Chemical Processes (Ministry of Education), East China University of Science and Technology, Shanghai 200237, China

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Abstract

The extractive dividing-wall column (EDWC) is one of the most efficient technologies for separation of azeotropic or close boiling-point mixtures, but its design is fairly challenging. In this paper we extend the hybrid feasible path optimisation algorithm (Ma Y, McLaughlan M, Zhang N, Li J. Computers & Chemical Engineering, 2020, 143: 107058) for such optimal design. The tolerances-relaxation integration method is refined to allow for long enough integration time that can ensure the solution of the pseudo-transient continuation simulation close to the steady state before the required tolerance is used. To ensure the gradient and Jacobian information available for optimisation, we allow a relaxed tolerance for the simulation in the sensitivity analysis mode when the simulation diverges under small tolerance. In addition, valid lower bounds on purity of the recycled entrainer and the vapour flow rate in column sections are imposed to improve computational efficiency. The computational results demonstrate that the extended hybrid algorithm can achieve better design of the EDWC compared to those in literature. The energy consumption can be reduced by more than 20% compared with existing literature report. In addition, the optimal design of the heat pump assisted EDWC is achieved using the improved hybrid algorithm for the first time.

Keywords design extractive dividing-wall column equation-oriented optimisation pseudo-transient continuation model hybrid algorithm

Corresponding Author(s): Jie Li

Just Accepted Date: 27 September 2020 Online First Date: 16 December 2020 Issue Date: 12 January 2021

Cite this article:

Yingjie Ma,Nan Zhang,Jie Li, et al. Optimal design of extractive dividing-wall column using an efficient equation-oriented approach[J]. Front. Chem. Sci. Eng., 2021, 15(1): 72-89.

URL:

https://academic.hep.com.cn/fcse/EN/10.1007/s11705-020-1977-y
https://academic.hep.com.cn/fcse/EN/Y2021/V15/I1/72

Fig.1 A typical conventional ED process for separation of a binary azeotropic mixture A and B.

Fig.2 A typical EDWC for separation of an azeotropic or close boiling-point mixture A and B.

Fig.3 Extended column section model of the EDWC.

Fig.4 The hybrid steady-state and time-relaxation feasible path optimisation algorithm.

Fig.5 The improved tolerances-relaxed integration method.

Fig.6 The improved derivative information evaluation allowing a larger tolerance.

Tab.1 Initial values and lower and upper bounds of the decision variables for case study 1

Tab.2 Computational performance of the extended hybrid algorithm for case study 1 from six different initial points

Tab.3 Optimal design of the EDWC for case study 1 from six different initial points

Fig.7 Optimal design of the EDWC for case study 1.

Tab.4 Economic comparison between EDWC and conventional ED for case study 1

Fig.8 Optimal design of the conventional ED for case study 1.

Fig.9 Optimal design of the EDWC for case study 2 with consideration of the entrainer cost (The mass purity is shown in the bracket. This is similar in the latter figures).

Tab.5 Initial values and lower and upper bounds of the decision variables for case study 2

Tab.6 Computational performance of the extended hybrid algorithm for case study 2 from six different initial points

Tab.7 Optimal solutions for case study 2 from six different initial points

Fig.10 Optimal design of EDWC for case study 2 without consideration of the entrainer cost.

Tab.8 Initial values and lower and upper bounds of decision variables for case study 3

Tab.9 Computational performance of the improved hybrid algorithm for case study 3 starting from six initial points

Tab.10 Optimal solutions for case study 3 from six initial points

Fig.11 Optimal design of the heat pump-assisted EDWC for case study 3.

Tab.11 Cost breakdown in the optimal design of the normal EDWC in case study 2 and the optimal design of the heat pump assisted EDWC in case study 3

Tab.12 Energy consumption in our optimal design and the design of Luo et al. [²³]

Tab.13 The capital cost breakdown of the design of Luo et al. [²³] and our design

Fig.12 Optimal design of the heat pump assisted EDWC for case study 3 without consideration of the entrainer cost.

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