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
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.
. [J]. Frontiers of Chemical Science and Engineering, 2021, 15(1): 72-89.
Yingjie Ma, Nan Zhang, Jie Li, Cuiwen Cao. Optimal design of extractive dividing-wall column using an efficient equation-oriented approach. Front. Chem. Sci. Eng., 2021, 15(1): 72-89.
V Gerbaud, I Rodriguez Donis, L Hegely, P Lang, F Denes, X You. Review of extractive distillation. Process design, operation, optimization and control. Chemical Engineering Research & Design, 2019, 141: 229–271 https://doi.org/10.1016/j.cherd.2018.09.020
2
M A Schultz, D G Stewart, J M Harris, S P Rosenblum, M S Shakur, D E O’Brien. Reduce costs with dividing-wall columns. Chemical Engineering Progress, 2002, 98: 64–71
3
S Hernández. Analysis of energy-efficient complex distillation options to purify bioethanol. Chemical Engineering & Technology, 2008, 31(4): 597–603 https://doi.org/10.1002/ceat.200700467
4
Y Tavan, S H Riazi, M Nozohouri. Energy optimization and comparative study of pre- and post-fractionator extractive dividing wall column for the CO2 ethane azeotropic process. Energy Conversion and Management, 2014, 79: 590–598 https://doi.org/10.1016/j.enconman.2013.12.029
5
D Staak, T Grützner. Process integration by application of an extractive dividing-wall column: an industrial case study. Chemical Engineering Research & Design, 2017, 123: 120–129 https://doi.org/10.1016/j.cherd.2017.04.003
6
G M Cordeiro, M F de Figueirêdo, W B Ramos, F A Sales, K D Brito, R P Brito. Systematic strategy for obtaining a dividing-wall column applied to an extractive distillation process. Industrial & Engineering Chemistry Research, 2017, 56(14): 4083–4094 https://doi.org/10.1021/acs.iecr.6b05047
7
A A Kiss, D J P C Suszwalak. Enhanced bioethanol dehydration by extractive and azeotropic distillation in dividing-wall columns. Separation and Purification Technology, 2012, 86: 70–78 https://doi.org/10.1016/j.seppur.2011.10.022
8
C Bravo Bravo, J G Segovia Hernández, C Gutiérrez Antonio, A L Durán, A Bonilla Petriciolet, A Briones Ramírez. Extractive dividing wall column: design and optimization. Industrial & Engineering Chemistry Research, 2010, 49(8): 3672–3688 https://doi.org/10.1021/ie9006936
9
R Gutiérrez Guerra, J G Segovia Hernández, S Hernández. Reducing energy consumption and CO2 emissions in extractive distillation. Chemical Engineering Research & Design, 2009, 87(2): 145–152 https://doi.org/10.1016/j.cherd.2008.07.004
10
L T Biegler. New nonlinear programming paradigms for the future of process optimization. AIChE Journal. American Institute of Chemical Engineers, 2017, 63(4): 1178–1193 https://doi.org/10.1002/aic.15674
11
M J D Powell. A fast algorithm for nonlinearly constrained optimization calculations. In: Watson G A, ed. Proceedings of the Numerical Analysis. Berlin: Springer, 1978, 144–157
12
Aspen Technology Inc. Aspen Plus User’s Guide Version V8.8. 2015
13
Y Y Loy, X L Lee, G P Rangaiah. Bioethanol recovery and purification using extractive dividing-wall column and pressure swing adsorption: an economic comparison after heat integration and optimization. Separation and Purification Technology, 2015, 149: 413–427 https://doi.org/10.1016/j.seppur.2015.06.007
14
A Yang, R Wei, S Sun, S Wei, W Shen, I L Chien. Energy-saving optimal design and effective control of heat integration-extractive dividing wall column for separating heterogeneous mixture methanol/toluene/water with multiazeotropes. Industrial & Engineering Chemistry Research, 2018, 57(23): 8036–8056 https://doi.org/10.1021/acs.iecr.8b00668
15
M Vikse, H A J Watson, D Kim, P I Barton, T Gundersen. Optimization of a dual mixed refrigerant process using a nonsmooth approach. Energy, 2020, 196: 116999 https://doi.org/10.1016/j.energy.2020.116999
16
A W Dowling, L T Biegler. A framework for efficient large scale equation-oriented flowsheet optimization. Computers & Chemical Engineering, 2015, 72: 3–20 https://doi.org/10.1016/j.compchemeng.2014.05.013
17
Y Ma, Y Luo, X Yuan. Simultaneous optimization of complex distillation systems with a new pseudo-transient continuation model. Industrial & Engineering Chemistry Research, 2017, 56(21): 6266–6274 https://doi.org/10.1021/acs.iecr.7b00380
18
Y Ma, Y Luo, X Ma, T Yang, D Chen, X Yuan. Fast algorithms for flowsheet simulation and optimization using psdueo-transient models. Industrial & Engineering Chemistry Research, 2018, 57(42): 14124–14142 https://doi.org/10.1021/acs.iecr.8b01461
19
T Waltermann, T Grueters, D Muenchrath, M Skiborowski. Efficient optimization-based design of energy-integrated azeotropic distillation processes. Computers & Chemical Engineering, 2020, 133: 106676 https://doi.org/10.1016/j.compchemeng.2019.106676
20
Y Ma, M McLaughlan, N Zhang, J Li. Novel feasible path optimization algorithms using steady-state and dynamic models. Computers & Chemical Engineering, 2020, 143: 107058 https://doi.org/10.1016/j.compchemeng.2020.107058
21
W L Luyben. Control of the maximum-boiling acetone/chloroform azeotropic distillation System. Industrial & Engineering Chemistry Research, 2008, 47(16): 6140–6149 https://doi.org/10.1021/ie800463h
22
A A Kiss, R M Ignat. Innovative single step bioethanol dehydration in an extractive dividing-wall column. Separation and Purification Technology, 2012, 98: 290–297 https://doi.org/10.1016/j.seppur.2012.06.029
23
H Luo, C S Bildea, A A Kiss. Novel heat-pump-assisted extractive distillation for bioethanol purification. Industrial & Engineering Chemistry Research, 2015, 54(7): 2208–2213 https://doi.org/10.1021/ie504459c
24
R C Pattison, M Baldea. Equation-oriented flowsheet simulation and optimization using pseudo-transient models. AIChE Journal. American Institute of Chemical Engineers, 2014, 60(12): 4104–4123 https://doi.org/10.1002/aic.14567
25
R C Pattison, A M Gupta, M Baldea. Equation-oriented optimization of process flowsheets with dividing-wall columns. AIChE Journal. American Institute of Chemical Engineers, 2016, 62(3): 704–716 https://doi.org/10.1002/aic.15060
26
A W Dowling, L T Biegler. Rigorous optimization-based synthesis of distillation cascades without integer variables. Computer-Aided Chemical Engineering, 2014, 33: 55–60 https://doi.org/10.1016/B978-0-444-63456-6.50010-7
27
L T Biegler. Nonlinear Programming: Concepts, Algorithms, and Applications to Chemical Processes. Philadelphia: Society for Industrial and Applied Mathematics, 2010, 160–161
28
L T Biegler, R R Hughes. Feasible path optimization with sequential modular simulators. Computers & Chemical Engineering, 1985, 9(4): 379–394 https://doi.org/10.1016/0098-1354(85)85016-X
29
N J Higham. Accuracy and Stability of Numerical Algorithms. 2nd ed. Philadelphia: Society for Industrial and Applied Mathematics, 2002, 3–4
30
Aspen Technology Inc. Aspen Custom Modeler User’s Guide Version V8.8. 2015
31
Python Software Foundation. Python language reference version 3.6. 2016
32
D. Kraft A software package for sequential quadratic programming. Braunschweig, Köln: DFVLR, 1988
33
M Aurangzeb, A K Jana. A novel heat integrated extractive dividing wall column for ethanol dehydration. Industrial & Engineering Chemistry Research, 2019, 58(21): 9109–9117 https://doi.org/10.1021/acs.iecr.9b00988
34
D J P C Suszwalak, A A Kiss. Enhanced bioethanol dehydration in extractive dividing-wall columns. Computer-Aided Chemical Engineering, 2012, 30: 667–671 https://doi.org/10.1016/B978-0-444-59519-5.50134-9
35
M Aurangzeb, A K Jana. Double-partitioned dividing wall column for a multicomponent azeotropic system. Separation and Purification Technology, 2019, 219: 33–46 https://doi.org/10.1016/j.seppur.2019.03.007
36
W L Luyben. Distillation Design and Control Using Aspen Simulation. Hoboken: John Wiley & Sons, 2006, 87–89
