Efficient optimization-based design of energy-integrated azeotropic distillation processes

Efficient optimization-based design of energy-integrated azeotropic distillation processes

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Efficient optimization-based design of energy-integrated azeotropic distillation processes Thomas Waltermann, Tamara Grueters, Daniel Muenchrath, Mirko Skiborowski PII: DOI: Reference:

S0098-1354(19)30851-8 https://doi.org/10.1016/j.compchemeng.2019.106676 CACE 106676

To appear in:

Computers and Chemical Engineering

Received date: Revised date: Accepted date:

13 August 2019 3 December 2019 5 December 2019

Please cite this article as: Thomas Waltermann, Tamara Grueters, Daniel Muenchrath, Mirko Skiborowski, Efficient optimization-based design of energy-integrated azeotropic distillation processes, Computers and Chemical Engineering (2019), doi: https://doi.org/10.1016/j.compchemeng.2019.106676

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Highlights • Optimization-based design of extractive and heteroazeotropic distillation processes. • Automatic initialization and polylithic modeling and solution approach. • Evaluation of heat integration, vapor recompression and dividing wall columns. • Integration of solvent selection and energy integration. • Efficient comparison of competing process options in three complex case studies.

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Efficient optimization-based design of energy-integrated azeotropic distillation processes Thomas Waltermann, Tamara Grueters, Daniel Muenchrath, Mirko Skiborowski∗ TU Dortmund University, Department of Biochemical and Chemical Engineering, Laboratory of Fluid Separations, 44227 Dortmund, Germany

Abstract The separation of azeotropic mixtures is frequently performed by extractive or heteroazeotropic distillation processes. The design of these processes requires careful selection of a suitable solvent and is specifically challenging since feasibility and optimality of the processes require consideration of the closed loop design including solvent recovery. Consideration of energy integration further complicates the design task and is usually conducted as post-evaluation step. The current publication proposes an efficient optimization-based design approach, which allows for the direct evaluation of several energy-integrated process concepts, while significantly reducing manual effort and computational time through a polylithic modeling and solution approach. The developed approach allows for a simultaneous evaluation of solvent selection and energy integration and is illustrated for different case studies, including the evaluation extractive and heteroazeotropic distillation for the dehydration of ethanol, as well as the evaluation of multiple solvent ∗

Corresponding author Email address: [email protected] (Mirko Skiborowski)

Preprint submitted to Computers & Chemical Engineering

December 5, 2019

candidates for the extractive distillation of acetone and methanol. Keywords: Extractive distillation, heteroazeotropic distillation, optimization, energy integration, solvent selection, conceptual design

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1. Introduction

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Azeotropic mixtures are encountered in the downstream processing of many

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chemical processes and are of particular importance for the processing of bio-

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renewables, for which aqueous-organic mixtures are frequently encountered.

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Two established process concepts for the separation of such mixtures into

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high purity products are extractive distillation (ED) and heteroazeotropic, or

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heterogeneous azeotropic distillation (HAD) (Skiborowski et al., 2013; Arlt,

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2014; Gerbaud and Rodriguez-Donis, 2014), which have been used in the

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process industries for almost a century (Stichlmair and Herguijuela, 1992).

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Both processes depend on the effect an entrainer, or mass separating agent

11

(MSA), has on the thermodynamic properties of the mixture. In the case

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of ED the MSA facilitates the separation by interacting with the original

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azeotropic mixture, by altering the relative volatility between the azeotrope

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forming components, such that they can be separated in a two-feed column,

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while recovering the MSA in a subsequent recovery column (cf. Figure 1

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(left)) (Kossack et al., 2008). For HAD, the MSA is supposed to introduce

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a minimum boiling heteroazeotrope, which facilitates the separation due to

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a combination of distillation and decantation, as illustrated for a classical

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configuration in Figure 1 (right)(Kraemer et al., 2011). Due to this combi-

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nation and the ease of recovery of the MSA HAD was oftentimes preferred

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in industry (Widagdo and Seider, 1996). Specifically for medium and large-

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scale processes, as in the production of bulk chemicals and intermediates, ED

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and HAD both benefit from economics of scale (Kiss and Suszwalak, 2012),

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which they offer over alternative processes for the separation of azeotropic

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mixtures, such as membrane separations and adsorption. However, since

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distillation processes suffer from a low thermodynamic efficiency in general

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(Koeijer and Kjelstrup, 2000) and due to the necessary separation and recov-

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ery of the additional entrainer, ED and HAD are considered rather energy

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intensive.

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In order to design the most effective ED and HAD processes, the choice of

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MSA, is of tremendeous importance (Blahuˇsiak et al., 2018). Potential MSA

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are either selected based on heuristic rules and expert knowledge, or through

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computer aided molecular design approaches (CAMD) (Gani et al., 2006).

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The latter allow for an automated screening of MSA based on certain fea-

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sibility criteria and the estimation of thermodynamic properties based on

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group contribution models or quantitative structure-property relationships

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(QSPR). CAMD approaches are well established for ED, evaluating e.g. dis-

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tribution coefficients, selectivities and capacities (Kossack et al., 2008; Zhou

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et al., 2019), or more informative, information on the isovolatility curve (Cig-

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nitti et al., 2019). Further analysis of MSA feasibility for both ED and HAD

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can be derived from analysis of residue curve maps (RCM) (Julka et al., 2009;

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Skiborowski and G´orak, 2016). As the feasibility of HAD processes requires

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a rather complex topology with respect to the vapor-liquid-liquid equilib-

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rium (VLLE), the literature on CAMD approaches for HAD is rather scarce.

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Two exceptions are the articles of Yang et al. (2012) and Furzer (1994).

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Both propose a group-contribution-based CAMD approach. However, Yang

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et al. (2012) evaluate the suitability of a MSA based on the formation of a

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heteroazeotrope, as well as the derived information on its composition, tem-

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perature and heat of vaporization,while Furzer (1994) proposes a simplified

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graphical evaluation of the purification of one desired product based on an

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analysis of the binary x-y diagram.

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Despite the lack of topology-based screening methods for MSA selection, it

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is important to recognize that the evaluation generally considers a specific

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process structure, for which according criteria for MSA selection are derived.

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While different ED and HAD process configurations are potentially feasible,

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we will focus in this article on the classical ED and HAD processes illustrated in Fig. 1.

Figure 1: Illustration of the considered extractive distillation (left) and heteroazeotropic distillation (right) process configurations. 57 58

The depicted ED process is feasible for the separation of a mixture with a

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temperature minimum azeotrope by introducing a heavy boiling MSA, which

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shows a considerably higher affinity to component A than B. This configura-

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tion is commonly preferred, because of an easier recovery of the MSA and the 6

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purification of both products as distillate (Kossack et al., 2008). The recent

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review article of Gerbaud et al. (2019) provides an elaborate description of

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this, as well as alternative ED configurations and related feasibility criteria.

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The depicted HAD process represents the most commonly considered config-

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uration, which is also representative for the separation of a mixture with a

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temperature minimum azeotrope, such as encountered in the dehydration of

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ethanol or isopropanol. While a feasible MSA for ED should not introduce

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an additional azeotrope, the occurrence of a ternary heterogeneous temper-

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ature minimum azeotrope is mandatory for a feasible MSA in case of the

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HAD process. The products are obtained as bottoms products in case of

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the HAD process, while both columns operate in different distillation regions

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and process feasibility depends primarily on the liquid phase separation in

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the decanter on top of the second distillation column. Aside from the specific

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HAD configuration depicted in Fig. 1, other variants are also possible such

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as extractive HAD processes (Gerbaud et al., 2019), these are not covered in

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the current design approach yet.

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Which process and especially which combination of process and MSA per-

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forms best requires a thorough investigation of the process performance,

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based on appropriate thermodynamic and process specific models. The final

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design tasks consists of the identification of a detailed feasible and at best eco-

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nomically optimal process design, including various degrees of freedom such

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as the number of trays or packing height in the different column sections,

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the entrainer to feed ratio, reboiler and condenser duties and appropriately

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sized columns. However, first potential MSA candidates need to be identified

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and evaluated for feasibility. The various approaches for ED reach from an

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investigation of the minimum entrainer flow rate and corresponding mini-

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mum and maximum reflux ratios by means of RCM analysis (Wahnschafft

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and Westerberg, 1993), bifurcation analysis (Knapp and Doherty, 1994) and

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pinch-based shortcut methods (Br¨ uggemann and Marquardt, 2004) to var-

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ious types of simulation and optimization approaches for equilibrium stage

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models. For HAD the situation is similar, yet the determination of the mini-

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mum entrainer flowrate and reflux ratio requires a multi-step approach, even

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for sophisticated pinch-based shortcut methods (Urdaneta et al., 2002; Wa-

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sylkiewicz et al., 2003; Kraemer et al., 2011; Skiborowski et al., 2018). Most

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process design methods based on equilibrium stage models build on a pro-

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cess simulator in combination with a manual optimization procedure (Brito

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et al., 2016b), a metaheuristic (Tututi-Avila et al., 2014) or the optimiza-

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tion of surrogate model, fitted to sampling data obtained from a process

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simulator (Wang et al., 2013). For any of these design methods, the correct

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identification of multiple liquid phases in case of HAD is mandatory. For the

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common case of potential demixing into two liquid phases, this requires the

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consideration of either vapor-liquid equilibrium (VLE) or VLLE in respect

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to the equilibrium description. The article of Gerbaud et al. (2019) provides

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an extensive review about ED in general and process synthesis, design and

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optimization in specific, while the articles of Skiborowski et al. (2013, 2015a)

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provide detailed reviews for ED and HAD in specific.

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Overall, Scopus lists more than 1000 publications and more than 9000 patents

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for the keywords ”extractive distillation” and ”heteroazeotropic distillation”,

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with increasing numbers especially in the recent 10 to 20 years. Yet, only

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a small fraction of these documents deals with heteroazeotropic distillation

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and even for extractive distillation, articles that consider means for energy

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integration have been published primarily in the recent five years. Heat in-

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tegration (Cui et al., 2018), thermal coupling (Brito et al., 2016b) and the

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equipment integration in terms of dividing wall columns (Kiss and Suszwalak,

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2012; Franke, 2017), as well as the use of heat pumps (You et al., 2016) or

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multi-effect distillation (Bessa et al., 2012) are potential options for energy

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integration of extractive and heteroazeotropic distillation processes. For ex-

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tractive distillation, the elaborate up-to-date review article of Gerbaud et al.

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(2019) does not only extensively discuss the assessment of feasibility, syn-

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thesis and design of extractive distillation processes, but also summarizes

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the different publications on energy-integrated process designs. Most of the

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published articles focus on the evaluation of a specific concept for energy

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integration with respect to the non-integrated base case, considering a single

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separation problem. Yet, even for those restricted investigations, it is high-

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lighted that a reliable quantification of energy and economic saving potentials

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require a case-specific evaluation, for the specific chemical system, feed and

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product specifications and economic parameters (Brito et al., 2016a). The

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article of You et al. (2016), which compares different heat pump configu-

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rations for extractive distillation, as well as the article of Gu et al. (2019),

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which presents an evaluation of three energy-integrated concepts, considering

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heat integration, an intermediate reboiler, as well as vapor recompression, are

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rather rare exceptions.

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Fig. 2 summarizes the different steps associated with the design of ED and

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HAD processes, which as previously discussed are mostly investigated subse-

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quently, as in the classical hierarchical design approach proposed by Douglas

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(1985). However, few efforts have been made to systematically integrate

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some of the steps, especially the generation of suitable entrainers for ED

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and the evaluation of the energy-based or economic performance of these

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MSA candidates. The systematic synthesis framework proposed by Kossack

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et al. (2008) integrates group-contribution-based CAMD with shortcut and

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equilibrium-stage model-based process design optimization, while the system-

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atic framework of Zhou et al. (2019) combines multi-objective optimization

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for CAMD with RCM analysis and manual optimization of a process simulator model.

Figure 2: Sequence of steps associated with the design of ED and HAD processes. 145

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For both studies, the rigorous design optimization is limited to a small num-

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ber of MSA, for which a comparison is made based on the total annualized

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costs (TAC). This is important for a fair comparison of the different MSA

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candidates (Gerbaud et al., 2019). Nevertheless, neither of the approaches

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includes any means for energy integration. However, the consideration of

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energy integration might considerably alter the ranking of potential MSA,

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since the MSA choice directly affects condenser and reboiler temperatures

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and consequently the potential for energy savings. This potential problem

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was already pointed out by Kossack et al. (2008). Consequently, a holistic

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design approach should cover all four steps depicted in Fig. 2.

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While CAMD methods for solvent screening and the preselection based on

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feasibility criteria have been successfully established, at least for ED, the most 10

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challenging task for the evaluation of ED and HAD considering means for

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energy integration is posed by the efforts for the process design optimization.

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Simulation-based methods for process optimization require at least a feasible

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and converged initial flowsheet simulation, which has to be derived through a

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manual trial and error approach. As highlighted by Luyben (2013) as well as

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Le et al. (2015), obtaining such a convergent base case can be extremely chal-

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lenging, particularly for HAD processes, for which the correct identification

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of phase stability and the inherent integration of the column and decanter

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are serious complexities. In order to avoid the complexity of closed-loop flow-

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sheets, even for ED, most studies simplify the design task by performing a se-

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quential design of the extractive and recovery column (Gerbaud et al., 2019).

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Optimization-based design methods, which attempt an automatic initializa-

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tion by solving a series of successive optimization problems, can overcome

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these problems and simultaneously determine an optimized final process de-

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sign, w.r.t. an economic objective and related problem specific constraints.

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Such polylithic modeling and solution approaches (Kallrath, 2011) have pre-

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viously been presented for ED (Kossack et al., 2008), HAD (Skiborowski

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et al., 2015a), as well as the evaluation of various concepts for energy in-

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tegration for the basic three distillation sequences for the distillation-based

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separation of three products (Waltermann and Skiborowski, 2016, 2019).

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Building on these preceding works, we have developed an optimization-based

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design approach that enables the efficient computational screening of differ-

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ent MSA candidates and means for energy integration for both ED and HAD.

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This approach considers several means for energy integration, including clas-

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sical heat integration, thermal-coupling and respective dividing wall column

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designs as well as heat-pump assisted distillation in terms of vapor recompres-

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sion. Compared with the previously considered optimization-based design of

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energy-integrated distillation sequences (Waltermann and Skiborowski, 2019)

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the design of the energy-integrated ED and HAD processes is considerably

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more challenging, since these processes are already integrated and not fea-

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sible without the additional MSA, which presents an additional degree of

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freedom. To the best of our knowledge there has not been any publication

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that proposed and demonstrated a simultaneous and computationally effi-

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cient approach for the evaluation of various solvent candidates and means for

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energy-integration. Such efficient tools are of tremendous importance to meet

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the goals of designing more sustainable, yet economic processes in an ever

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shrinking time window for process development (Agrawal, 2001). Besides

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the comparative analysis of the different process concepts, the automatic de-

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sign method can also be integrated into the process synthesis framework of

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Kossack et al. (2008). This integration effectively extends the framework

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by covering the last step of Fig. 2. The developed method is described in

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further detail in Section 2, before Section 3 presents the results of different

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applications, including a comparison of both process concepts for ethanol

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dehydration with different feed specifications, as well as the comparison of

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different MSA candidates for ED of acetone and methanol, illustrating the

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importance of a simultaneous consideration of MSA selection and energy in-

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tegration. Section 4 finally provides a conclusion and an outlook on future

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work.

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2. Modeling and optimization

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The developed optimization-based design approach builds on several preced-

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ing publications. The general approach for model formulation and solution

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of ED processes was developed by Kossack et al. (2008) and Kraemer et al.

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(2009b) while the extension to HAD processes was presented by Skiborowski

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et al. (2015a). The underlying superstructure models are based on equi-

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librium stage models considering the well-known MESH equations (material

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balances, equilibrium models, summation constraints and enthalpy balances)

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(Kister, 1992) in combination with variable locations for feed, reflux and boil-

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up streams, as initially proposed by Viswanathan and Grossmann (1993). In

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order to integrate an efficient phase-stability test (Bausa and Marquardt,

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2000) and allow for a robust computation of VLE/VLLE, these calculations

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are performed by a set of dedicated algorithms, for which the results and

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sensitivities are integrated into the overall optimization problem via a set of

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external equations (Skiborowski et al., 2015a). The external functions used

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for the thermodynamic calculations are available online through the AVT-

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SVT website1 .

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The energy-integrated ED and HAD process variants are furthermore derived

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from a previously presented design approach (Waltermann and Skiborowski,

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2019) for the energy integration of simple sequences, considering the sepa-

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ration of non-ideal mixtures into three products. The following subsections

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first present a summary of the ED and HAD optimization models, before the 1

http://www.avt.rwth-aachen.de/cms/AVT/Forschung/Software/ iptu/Softwaresammlung-

Prozesssynthese/

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different process modifications for energy integration are described, followed

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by the solution approach that allows for an automatic initialization and op-

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timization of the different process variants. An elaborate description of the

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different model modifications for the energy-integrated process variants is

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not introduced, as these are equivalent to the modifications for the simple

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sequences, which were thoroughly described by Waltermann and Skiborowski

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(2019).

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2.1. Optimization model for extractive distillation

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The graphical representation of the superstructure model of the simple ED

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process is illustrated in Fig. 3. The simple (homogeneous) distillation column model is based on the work of Kraemer et al. (2009a).

Figure 3: Illustration of the superstructure of the simple ED process (left), with variable feed, reflux and boil-up locations, as well as a single equilibrium stage (right) with the different in- and outgoing streams and corresponding variables for flow rates, compositions, enthalpies and feed locations. 238

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The equilibrium stages of the column model are numbered from top (1) to

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bottom (Nth ), such that stage 1 corresponds to the condenser and stage Nth

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to the reboiler. Thus, the column itself consists of a maximum number of Nth

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- 2 theoretical stages. The corresponding MESH equations are further listed

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for the ED column, while the same equations hold for the solvent recovery

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column, without the appearance of the second feed stream. The mass balance

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for each of the equilibrium stages inside the ED column is given by 0 = Ln−1 xn−1,i − Ln xn,i − Vn yn,i + Vn+1 yn+1,i + bF,n FF zF,i

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+ bS,n FS zS,i + bR,n RR,n xR,i + bB,n RB,n yB,i ,

(1)

n = 2, . . . , (Nth − 1), i = 1, . . . , nc

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with L and V representing the flow rate of the liquid and vapor streams

249

leaving or entering a theoretical stage n. Moreover, x and y correspond to

250

the molar compositions of these liquid and vapor streams. Furthermore, FF

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and zF as well as FS and zS represent the flow rate and composition of the

252

fresh (azeotropic) feed stream and the solvent feed, for which distribution

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to a certain theoretical stage n is determined through an additional binary

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decision variable (bF,n and bS,n ). Similar decision variables (bR,n and bB,n )

255

determine the equilibrium stage to which the reflux and reboil streams with

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flow rates RR and RB and composition xR and yB are distributed. The

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corresponding energy balance with the specific enthalpies of liquid, vapor

258

and feed streams hL , hV , hF and hS is 0 = Ln−1 hL,n−1 − Ln hL,n − Vn hV,n + Vn+1 hV,n+1 + bF,n FF hF

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+ bS,n FS hS + bR,n RR,n hL,R + bB,n RB,n hV,B , n = 2, . . . , (Nth − 1). 15

(2)

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For the condenser (the first equilibrium stage), modified mass and enthalpy

262

balances including the condenser heat duty QC and the distillate flow rate

263

D, as well as additional constraints for the composition xR and enthalpy hL,R

264

of the reflux stream are specified

265

266

NX th −1

0 = Vn+1 yn+1,i − (

RR,j + D)xn,i ,

0 = Vn+1 hV,n+1 − ( 0 = xR,i − x1,i ,

268 269

0 = hL,R − hL,1 .

(3)

j=2

NX th −1

267

n = 1, i = 1, . . . , nc ,

j=2

RR,j + D)hL,n − QC ,

n = 1,

1, . . . , nc ,

(4) (5) (6)

270

The same applies for the reboiler (the last equilibrium stage) with the reboiler

271

heat duty QB and the bottoms flow rate B, as well as the compositions and

272

enthalpy values xB and hL,B of the bottoms product and yB and hV,B of the

273

boil-up stream

274

275

0 = Ln−1 xn−1,i −

NX th −1

0 = Ln−1 hL,n−1 −

j=2

RB,j yn,i − Bxn,i , n = Nth , i = 1, . . . , nc ,

NX th −1 j=2

RB,j hV,n − BhL,n + QB , n = Nth ,

(7)

(8)

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0 = xB,i − xNth ,i ,

1, . . . , nc ,

(9)

277

0 = yB,i − yNth ,i ,

1, . . . , nc ,

(10)

278

0 = hV,B − hV,Nth ,

(11)

279 280

0 = hL,B − hL,Nth .

(12)

281

The equilibrium relationship between the liquid and the vapor phase on each

282

of the equilibrium stages, as well as the computation of the specific enthalpies 16

283

is realized by means of the aforementioned external equations

284

eVLE = yi − yˆi (x, p) = 0, i

285

ˆ eVLE nc +1 = T − T (x, p) = 0,

(14)

286

ˆ ˆ eVLE nc +2 = hL − hL (x, p, T (x, p)) = 0,

(15)

287 288

ˆ y (x, p), p, Tˆ(x, p)) = 0, eVLE nc +3 = hV − hV (ˆ

(16)

289

which determine the equilibrium vapor composition yˆ(x, p) and temperature

290

Tˆ(x, p) for the current liquid composition x and pressure p, as well as the spe-

291

ˆ L (x, p, Tˆ(x, p)) and vapor enthalpy h ˆ V (ˆ cific liquid h y (x, p), p, Tˆ(x, p)), based

292

on pre-selected thermodynamic property models for the computation of the

293

liquid and vapor fugacitities, as well as specific heat capacities and enthalpies

294

of vaporization. Further details are provied in the article of Skiborowski

295

et al. (2015a). Moreover, further information on the applied thermodynamic

296

models in the scope of the current paper are listed in Section 3 for each

297

of the investigated case studies. The MESH equations for each stage are

298

supplemented by the summation constraints for the liquid and vapor phase

299

compositions

300

X

i = 1, . . . , nc ,

(13)

xn,i = 1,

n = 1, . . . , Nth ,

(17)

yn,i = 1,

n = 1, . . . , Nth .

(18)

i

301 302

X i

17

303

304

305

306

307 308

Closure relationships for each of the binary decision variables Nth X

n=1 Nth X

n=1 N th X

n=1 Nth X

bF,n = 1,

(19)

bS,n = 1,

(20)

bR,n = 1,

(21)

bB,n = 1,

(22)

n=1

309

as well as additional constraints that enforce an ordered location of the dif-

310

ferent feed, reflux and boil-up streams complete the set of equations for the

311

definition of the superstructure model. The optimization model for a sin-

312

gle column is further composed of additional sizing and costing correlations.

313

The sizing of the columns and additional equipment is done as described by

314

Waltermann and Skiborowski (2019), while the costing of the equipment is

315

based on the cost correlation of Guthrie (1969) and Biegler et al. (1997),

316

applying the CEPCI Equipment Index for September 2017 (Economic Indi-

317

cators, 2018) to update the calculated capital costs. The different competing

318

process options are optimized for TAC, which are composed of the annual

319

operating costs (AOC) and the annualized investment costs (AIC). The AIC

320

represents an annuity that reflects the depreciation of the initial investment

321

over a certain plant lifetime, considering a specific rate of return. The consid-

322

ered economic models, including the economic parameters, assumed utilities

323

and references are listed in further detail in the Supplementary material.

324

While the superstructure model of the solvent recovery column is equivalent

325

to the ED column, without the second feed stream, the MSA is recycled as 18

326

bottoms product B from the solvent recovery column to the ED column and

327

mixed with fresh MSA to compensate for solvent losses. For this purpose the

328

overall model is completed by additional mass and energy balances for the

329

mixing of the second feed stream

330

FS = FM SA + B2 − P

(23)

331

FS zS,i = FM SA zM SA,i + (B2 − P )xB2 ,i ,

332 333

FS hS = FM SA hM SA + (B2 − P )hL,B2

i = 1, . . . , nc − 1

(24) (25)

334

and mixed with a makeup stream FM SA to cover for losses in the product

335

streams. Additionally, a potential purge stream P is introduced, which can

336

be utilized in case of a potential accumulation of impurities. Since this is

337

not the case for the different case studies considered in Section 3, the purge

338

stream is limited to a certain upper level (< 1 % of the fresh feed stream)

339

during the initialization and furthermore reduced to zero during the economic

340

optimization, when accounting for fresh solvent cost.

341

2.2. Optimization model for heteroazeotropic distillation

342

The graphical representation of the superstructure model for the simple HAD

343

process is illustrated in Fig. 4. Apparently, the single column superstructures

344

are quite similar to those in the ED process. However, contrary to the ED

345

process, the fresh MSA stream and the MSA-rich recycle stream are mixed

346

with the (azeotropic) feed. The mixed stream is fed to the first column,

347

which is a simple distillation column that is supposed to operate in the ho-

348

mogeneous region of the composition space. The top product of the first

349

column, which is a saturated vapor feed from the partial condenser of the

350

first column, is further introduced as feed stream to the second column. 19

Figure 4: Illustration of the superstructure of the simple HAD process configuration, with variable feed, reflux and boil-up locations.

351

This column performs the heteroazeotropic distillation, for which the top va-

352

por stream leaving the column, which is supposed to be closely located to the

353

light-boiling heteroazeotrope, is first condensed and potentially sub-cooled,

354

before it is separated into two liquid phases in a decanter. Either the single

355

phases or a mixture of both are further recycled back to the heteroazeotropic

356

distillation column as well as the first distillation column. A major difference

357

between the ED and the HAD process is the location of the product streams.

358

Whilst both product streams for the ED process are derived as top products,

359

both products of the HAD process are derived as bottoms product. Although

360

top products have decent advantages with respect to potential impurities in

361

the reboiler, the production of bottoms products can bring other interesting

362

advantages, as will be shown in Section 3.2.

363

One of the major challenges in the design of HAD processes is the correct 20

364

determination of liquid phase-stability, since both VLE and VLLE relation-

365

ships allow for mathematically valid solutions in the whole composition space

366

(Raghunathan and Biegler, 2003; Skiborowski et al., 2015a). This problem

367

had previously been solved by the integration of a numerically efficient hybrid

368

method in a special implementation of the aforementioned external equations

369

(Skiborowski et al., 2015a). While the correct VLE or VLLE solution is first

370

determined based on a homotopy continuation approach (Bausa and Mar-

371

quardt, 2000), resulting VLLE solutions for column equilibrium stages are

372

further mapped to a quasi-homogeneous VLE result, including the compu-

373

tations of the specific enthalpies. This approach allows for the utilization of

374

the same MESH model as described in Eq. (1)-(22) for the ED columns, with

375

the exception of the decanter and the connectivity between the decanter and

376

the columns. The latter modifications are further described in the follow-

377

ing, while the interested reader is referred to the article of Skiborowski et al. (2015a) for a more detailed description.

Figure 5: Illustration of the decanter and the variables related to the computation of the in- and outgoing streams. 378 379

Besides the computation of the V(L)LE relationship, which is used to model

380

the liquid phase split in the decanter, the decanter is modeled by the fol-

381

lowing set of MESH equations that match to the graphical representation in 21

382

Fig. 5:

383

LC xC,i = LI xIi + LII xII i ,

384

LC hL,C = LI hIL + LII hII L ,

385

Ld1 xd1,i = ξ I LI xIi + ξ II LII xII i ,

386

Ld1 hd1 = ξ I LI hIL + ξ II LII hII L ,

i = 1, . . . , nc ,

(26) (27)

i = 1, . . . , nc ,

(28) (29)

387

Ld2 xd2,i = (1 − ξ I )LI xIi + (1 − ξ II )LII xII i ,

388 389

Ld2 hd2 = (1 − ξ I )LI hIL + (1 − ξ II )LII hII L .

i = 1, . . . , nc ,

(30) (31)

390

Eq. (26) and (27) provide the mass and enthalpy balances that link the

391

molar flow rates, compositions and specific enthalpies of the condensed top

392

vapor stream (Lc , xc , hL,c ) and the single liquid phases resulting from the

393

liquid phase split (LI , xI , hIL ) and (LII , xII , hII L ). The flow rate, composition

394

and specific enthalpy of the two recycle streams (Ld1 , xd1 , hd1 ) to the HAD

395

column and (Ld2 , xd2 , hd2 ) as recycle stream to the first column, are further

396

controlled by the split ratios ξ I and ξ II , as introduced in the mass and

397

enthalpy balances in Eq. (28)-(31). Thus, either both recylce streams can be

398

a mixture of the single liquid phases or either one can be limited to a single

399

phase.

400

The consideration of a partial condenser for the first column results in the

401

following modifications of the mass and enthalpy balances of the condenser

402

(Eq. (3) and (4)):

403

404 405

0 = Vn+1 yn+1,i −

NX th −1

0 = Vn+1 hV,n+1 −

RR,j xn,i + Dyn,i ,

n = 1, i = 1, . . . , nc ,

(32)

j=2

NX th −1 j=2

RR,j hL,n + DhV,n − QC , 22

n = 1.

(33)

406

For the HAD column with the decanter, the whole set of equations for the

407

condenser (Eq. (3)-(6)) is to be replaced by the mass and enthalpy balances

408

0 = Vn+1 yn+1,i − LC xC,i ,

409 410

0 = Vn+1 hV,n+1 − LC hL,C − QC ,

n = 1, i = 1, . . . , nc , n = 1,

(34) (35)

411

as well as additional equations that link the first outlet stream of the decanter

412

with the reflux stream to the HAD column:

413

0=

NX th −1 j=2

RR,j − Ld1 ,

414

0 = xR,i − xd1,i ,

415 416

0 = hL,R − hd1 .

(36)

1, . . . , nc ,

(37) (38)

417

The mixed feed stream Fmix of the first column is further determined based

418

on the following mass and enthalpy balances:

419

Fmix = FF + FM SA + Ld2 ,

420

421 422

(39)

Fmix zFmix ,i = FF zF,i + FM SA zM SA,i + Ld2 xd2,i , Fmix hFmix = FF hF + FM SA hM SA + Ld2 hd2 .

i = 1, . . . , nc − 1

(40) (41)

423

The same sizing and costing correlations for the ED process are considered

424

for the HAD process as well and are listed in the Supplementary mate-

425

rial. Thereby, the additional costs for the decanter are not considered in

426

the economic evaluation, which is a pragmatic simplification, since the dis-

427

engagement time required for its sizing can only be obtained reliably by lab

428

experiments (Mersmann et al., 2011).

23

429

2.3. Heat and mass integrated processes ED and HAD processes

430

Based on the initial superstructure formulations of the ED and HAD pro-

431

cess, different means for heat and mass integration are considered, for which

432

a graphical illustration is presented in Fig. 6 and Fig. 7. For visual con-

433

venience, the potential stream distribution indicated for the simple process

434

configurations in Fig. 3 and Fig. 4 is spared in these illustrations. As illus-

435

trated, a heat-integrated option, the vapor recompression for both individual

436

columns, as well as a thermally-coupled and an equipment-integrated divid-

437

ing wall column equivalent of the thermally-coupled process are considered.

438

All of these energy-integrated process variants, which are further described in

439

more detail, are automatically derived in an automated procedure, through

440

constraint modifications and additional sub-models, starting from the simple

441

non-integrated process concepts, as will be elaborated in Section 2.4. The

442

following subsections provide further detail on the energy-integrated ED and

443

HAD process configurations, while the reader is redirected to our previous

444

article on the design of energy-integrated simple distillation processes (Wal-

445

termann and Skiborowski, 2019) for the respective model modifications.

446

2.3.1. Extractive distillation

447

While the ED process requires recycling of the MSA and accounts for the

448

mixed solvent stream as a second feed to the ED column, the modification

449

for the energy-integrated process concepts are equivalent to those presented

450

for the direct split sequence for a ternary product separation by Waltermann

451

and Skiborowski (2019). They are illustrated in Fig. 6.

452

For the thermally-coupled (TC) ED process, the reboiler of the first column is

453

removed and the liquid stream from the bottom of the ED column is directly 24

454

fed as feed stream to the second column, while the boil-up stream for the ED

455

column is provided by a vapor side stream from the second column. Although

456

the thermal coupling may enable an overall reduction of the energy require-

457

ment, as well as a reduced investment by elimination of the reboiler, the

458

vapor production is shifted completely to the reboiler of the second column,

459

which operates at a higher temperature. Consequently, energy savings may

460

not directly translate into reduced operational costs, especially in the case of

461

a very high-boiling entrainer (Wu et al., 2013). Additional cost-savings can

462

be established by means of an equipment integration, in terms of the imple-

463

mentation of the TC ED process in a dividing wall column (DWC). While

464

the superstructure model based on the MESH equations is identical for the

465

TC and DWC configuration, sizing and costing correlations are adapted, as

466

described by Waltermann and Skiborowski (2019).

467

For a direct heat integration (HI) between both columns in the ED process, a

468

sufficient pressure difference between the operating pressures of both columns

469

needs to be established, such that the reboiler of the ED column can be par-

470

tially or fully integrated with the condenser of the second column to minimize

471

the external energy requirement. Although Fig. 6 indicates two separate heat

472

exchangers connected by a dashed arrow, the optimization model considers

473

only a single heat exchanger for the heat integration. The corresponding

474

optimization model further includes optional auxiliary heat exchangers to

475

compensate for the difference between the condenser and reboiler heat duty,

476

as well as additional pre-heating of the feed stream to the second column, in

477

order to reach the saturation temperature at the increased pressure.

478

The heat pump assisted ED process considering vapor recompression (VRC)

25

Figure 6: Heat and mass integrated ED processes: Thermally-coupled (TC) (top left), dividing wall column (bottom left), direct heat integration (top right) and mechanical vapor recompression (bottom right).

479

may enable significant savings in terms of energy requirements and operat-

480

ing costs, but at a considerable increase in capital costs due to the required

481

compressor. VRC can be considered as a state-of-the-art industrial system

482

for energy integration in binary splits, which has been applied specifically 26

483

for close boiling systems (Kiss et al., 2012). Despite the comparably large

484

temperature difference between top and bottoms products in the ED process,

485

VRC is of particular interest for the improvement of ED processes (Gerbaud

486

et al., 2019). While the superstructure allows for a partial or complete bypass

487

of the VRC section, two additional heat exchangers are integrated for super-

488

heating the vapor up-front the compressor in order to avoid condensation in

489

the compressor, as well as behind the valve to ensure saturation conditions

490

for the reflux to the column. The compression is modeled as isentropic with

491

a specific isentropic efficiency (Harwardt and Marquardt, 2012; Waltermann

492

and Skiborowski, 2019). As for the HI variant, the separate heat exchangers

493

connected by the dashed arrow are considered as single heat exchanger in

494

the optimization model.

495

2.3.2. Heteroazeotropic distillation processes

496

Similar to the ED process, the modification for the energy-integrated HAD

497

concepts are equivalent to those presented for the indirect split sequence for

498

a ternary product separation by Waltermann and Skiborowski (2019). The

499

major differences are the integration of the decanter in the HAD column and

500

the recycle stream to the first column, which is mixed with the fresh feed

501

and MSA. The different energy-integrated process options are illustrated in

502

Fig. 7,consisting of a thermally-coupled process configuration, a dividing wall

503

column as well as directly heat integrated distillation columns and heat-pump

504

assisted distillation by means of vapor recompression.

505

For the thermally-coupled (TC) HAD process, the condenser of the first col-

506

umn is eliminated, such that the top vapor stream is introduced as feed

507

stream to the HAD column, while the reflux to the first column is provided by 27

Figure 7: Heat and mass integrated HAD processes: Thermally-coupled (TC) (top left), dividing wall column (bottom left), direct heat integration (top right) and mechanical vapor recompression (bottom right).

508

a liquid side stream from the HAD column. Thereby, both reboilers are main-

509

tained and only the heat duty for condensation is shifted from the first to the

510

second column, for which condensation is performed at a lower temperature.

511

The thermal coupling can again result in considerable overall energy savings

512

(Kiss et al., 2012; Wu et al., 2014), while especially the equipment integration

513

of the thermally-coupled process in terms of a dividing wall column (DWC)

514

offers additional investment savings. As both reboilers are maintained, possi-

515

ble energy savings should directly translate into operating cost savings, unless 28

516

condensation in the HAD column cannot be performed with cheap cooling

517

water (Wu et al., 2014). The absence of a vapor split for the DWC variant

518

of the HAD column makes it particularly interesting from the operational

519

point of view.

520

For direct heat integration (HI), the first column of the HAD process is op-

521

erated at elevated pressure, such that the top vapor stream can be used as

522

heat source for the reboiler of the HAD column. Similar to the ED process,

523

the separate heat exchangers connected by the dashed arrow are modeled as

524

single heat exchanger and additional heat exchangers are considered in order

525

to compensate for the difference between the condenser and reboiler heat

526

duty, as well as additional pre-heating of the feed stream to the first column.

527

Same as for the ED process, mechanical vapor recompression (VRC) enables

528

a partial or complete integration between the reboiler and condenser of each

529

individual column in the HAD process. The separate heat exchangers con-

530

nected by the dashed arrows are considered as single heat exchanger in the

531

optimization model, but are only considered present in the economic evalu-

532

ation in case the VRC system is actually utilized.

533

2.4. Solution procedure

534

The proposed approach is termed ”optimization-based design”, since all indi-

535

vidual problems in the solution procedure are solved as undetermined math-

536

ematical programming problems, especially considering the inequality con-

537

straints for the product specifications rather than any fixation of the design

538

degrees of freedom (such as energy duties, product streams or distillate-to-

539

feed ratios). As already mentioned, a polylithic modeling and solution ap-

540

proach (Kallrath, 2011) is applied, which allows for an automatic initializa29

541

tion and optimization of the different process configurations. The approach

542

builds on the topological analysis of the composition space and initial mass

543

balance calculations for the individual column of the basic process configura-

544

tions of ED and HAD illustrated in Fig. 1. By approximating the potential

545

product compositions of the individual columns, these are initialized con-

546

sidering flash calculations for linearized composition profiles. Subsequently

547

mass balances and enthalpy balances are added and the individual columns

548

are optimized for minimum energy duties, considering a fixed column size

549

with a maximum number of equilibrium stages. For both extractive and

550

heteroazeotropic distillation, the individual columns are than connected in

551

series (first to second), while depending on the specific process variant the

552

necessary modifications for heat and mass integration are performed. As the

553

last step of the automatic initialization procedure, the recycle streams are

554

closed and the energy duty is minimized once more for the final product spec-

555

ifications. Finally, all constraints on feed, reflux and boil-up locations are

556

relaxed and the process design is optimized for minimum TAC, for which the

557

additional sizing and costing models are added to the optimization model.

30

Figure 8: Automated initialization and solution procedure for ED and HAD processes

31

558

The sequence of steps in the polylithic modeling and solution approach are

559

summarized in Fig. 8. The developed solution procedure is a direct ex-

560

tension of the design approach for energy integration distillation sequences

561

(Waltermann and Skiborowski, 2019). The final mixed-integer non-linear

562

programming (MINLP) problem, which includes the integer decisions on the

563

number of equilibrium stages and feed positions, is solved as a series of suc-

564

cessively relaxed nonlinear programming (NLP) problems. This approach

565

proofed to result in improved robustness and numerical efficiency of the cal-

566

culations in previous design optimizations (Kraemer et al., 2009b; Kraemer

567

and Marquardt, 2010; Skiborowski et al., 2014, 2015a). As in the reformu-

568

lation of mathematical programming problems with equilibrium constraints,

569

additional nonlinear complementary constraints are added as penalty terms

570

in the objective function to ensure that integer values are obtained for the

571

relaxed binary variables (Skiborowski et al., 2015a).

572

For the problem definition, only the feed and product specifications as well as

573

the thermodynamic model and some specifications for initialization need to

574

be defined. The latter includes the maximum number of equilibrium stages

575

as well as initial guesses for feed locations and entrainer-to-feed ratio. Since

576

the resulting optimization problem is highly non-linear and non-convex, the

577

obtained solution is limited to a local optima. While current research activi-

578

ties are dedicated to extend the optimization approach in order to overcome

579

this limitation through an additional global search (Kruber et al., 2019), the

580

sensitivity of the applied optimization approach with respect to the initial

581

structure was checked for the subsequently addressed case studies, to check

582

for the possible entrapment in local solutions of poor quality.

32

583

3. Case Studies

584

In order to demonstrate the capabilities of the developed optimization-based

585

design method, its application is illustrated for three case studies in the sub-

586

sequent subsections. Setting up the problem specification and constraints

587

for the individual case studies requires only few modifications, providing a

588

general design method, as presented in Section 2. All computations have

589

been performed with GAMS V22.7.2., using SNOPT as NLP solver, on a

590

R stand-alone PC with an Intel CoreTM i7-7700 CPU with 3.6 GHz. Infor-

591

mation on the economic evaluation and the applied thermodynamic models

592

and parameters are provided in the Supplementary material.

593

3.1. Extractive distillation of methanol from a ternary mixture with acetoni-

594

trile and benzene

595

The first case study investigates the separation of methanol from a mix-

596

ture with acetonitrile and benzene, as considered by Zhu et al. (2016) and

597

Wang et al. (2018). The components in the mixture are representative of

598

common solvents in the chemical and pharmaceutical industry and the con-

599

sidered feed stream is a saturated liquid with a flow rate of 10 mol/s and

600

a composition of 25 mol-% acetonitrile, 10 mol-% benzene and 65 mol-%

601

methanol. The complex topology of this ternary mixture, which possesses

602

three binary azeotropes that separate the composition space into three dis-

603

tillation regions, impedes a direct methanol recovery by simple distillation,

604

as indicated in Fig. 9.

605

The objective of the process design study is to evaluate the cost-optimal de-

606

sign of an ED process, using chlorobenzene as a suitable MSA (Wang et al.,

33

Figure 9:

Topology of ternary mixture of acetonitrile, benzene and methanol including

simple distillation boundaries and considered feed composition for first case study.

607

2018). The cost of the MSA is assumed to be 1000 $/t2 for the poten-

608

tial make-up stream. Methanol is to be recovered with a purity of at least

609

99.5 mol-% and a recovery of at least 99.5 %, while the mole fraction of

610

chlorobenzene in the distillate of the solvent recovery column shall also be

611

less than 0.01 mol-%. VLE calculations are based on the Wilson g E -model

612

in combination with the extended Antoine equation and DIPPR correlations

613

for the specific heat capacities and the enthalpy of vaporization. All param-

614

R eters are extracted from the Aspen Plus APV-V88 VLE-IG and PURE32

2

exchange rate of 0.8465 e$

34

615

database. Optimization-based design calculations are performed for the sim-

616

ple, as well as the HI, TC, DWC and VRC configurations, for which the

617

superstructures of the individual columns offer up to 80 equilibrium stages.

618

For the economic assessment a depreciation within 10 years is considered.

619

The HI ED process is identified as the cost optimal solution. The detailed

620

design of the HI ED process is depicted in Fig. 10. In order to exploit

621

the heat from the condenser of the second column for partial integration of

622

the reboiler of the first column, the second column is operated at 2.4 bar.

623

Thereby the external steam demand for column 1 is reduced by 38 %, while

624

additional 94.3 kW are required to preheat the feed to the second column to

625

saturation conditions. Overall, HI allows for the reduction of external heat

626

demand from 1008 kW to 803 kW, when compared to the simple ED process,

627

resulting in AOC savings of about 17 %.

628

However, overall TAC savings of just 2 % are obtained, due an increase in

629

AIC. Fig. 11 illustrates the cost distribution of the optimized simple and

630

energy-integrated ED processes. Further details for each of the process de-

631

signs are provided in the Supplementary material. While the results indicate

632

only little economic saving potential for the HI variant, the potential appli-

633

cation of VRC is not utilized as the potential energy savings are not high

634

enough to cover for the additional investment for the compressor. Moreover,

635

the thermal coupling in case of the TC and DWC variant results in even

636

higher costs as a higher steam grade has to be used. The latter is in agree-

637

ment with investigations of Wu et al. (2013), who evaluated DWC for ED

638

for several chemical systems and concluded that economic savings can only

639

be obtained for few certain cases.

35

Figure 10: Detailed results of the optimized design of the HI ED process for the separation of methanol from a ternary, azeotropic mixture of acetonitrile, benzene, and methanol.

640

While only little improvements can be obtained by means of energy inte-

641

gration in case of this ED process, the optimization-based design method

642

enables the efficient evaluation of all process configurations. For all five pro-

643

cess configurations optimized designs were obtained within less than an hour

644

of computational time, without parallelization of the computations. Thus, a

645

quick evaluation of the saving potential is enabled based on a quantitative

646

evaluation of optimized process configurations.

36

Figure 11: Overview of cost distribution for the simple and energy-integrated optimized ED process designs for the separation of methanol from a ternary, azeotropic mixture of acetonitrile, benzene, and methanol.

647

3.2. Dehydration of ethanol by ED and HAD

648

Alcohol and ethanol dehydration in specific are the most prominent exam-

649

ples for ED, as well HAD. Specifically the purification of bioethanol from

650

dilute fermentation broth is considered quite energy intensive (Singh and

651

Rangaiah, 2017). Consequently, Kiss and Suszwalak (2012) already inves-

652

tigated the saving potential of DWC designs for ED and HAD processes,

653

concluding that both processes enable energy savings compared to the non-

654

integrated processes. Considering the same pre-concentrated feed stream of

655

100 kmol/h with an ethanol fraction of 85 mol-%, the optimization-based

656

design approach is first applied to evaluate the different options for energy

657

integration for both ED and HAD. According to international standards and

658

as considered by Kiss and Suszwalak (2012), the bioethanol product has to 37

659

contain less than 2 wt-% water, translated to a purity of at least 99.5 mol-

660

%, while the water byproduct has to have a purity of at least 99.9 mol-%.

661

Ethylene glycol and cyclohexane are selected as preferred and established sol-

662

vents for ED and HAD respectively (Singh and Rangaiah, 2017). For both, a

663

price of 1000 $/t3 is considered for the potential make-up stream. The ther-

664

modynamic properties of both systems are modeled by the NRTL model in

665

combination with the extended Antoine equations and DIPPR correlations

666

R for the specific enthalpies, using parameters from the Aspen Plus APV-V88

667

VLE-IG and PURE32 database. For the economic assessment a depreciation within 3 years is considered.

Figure 12: Overview of cost distribution for the simple and energy-integrated optimized ED and HAD process designs for the dehydration of a pre-concentrated ethanol stream. 668

3

exchange rate of 0.8465 e$

38

669

Fig. 12 illustrates the cost distribution of the optimized simple and energy-

670

integrated ED and HAD processes. Obviously, the ED process configurations

671

are significantly less expensive than the HAD process, with the simple ED

672

process being the most economic choice for the given problem specifications.

673

Again, the compressor sections in the VRC variant are bypassed for both ED

674

and HAD. For the ED process, no HI design was derived, since the necessary

675

operating pressure for heat integration between both columns requires the

676

reboiler temperature of the second column to exceed the maximum tempera-

677

ture limit of 492 K, which was specified based on a limitation of the available

678

utilities. HI for the HAD results in almost the exact same TAC as the simple

679

variant, however, with a considerable shift between AIC and AOC. While for

680

the ethanol dehydration the economic advantage of the thermally-coupled

681

side rectifier over the thermally-coupled ED process are significant, the po-

682

tential benefit of the side-rectifier depends majorly on the contribution of

683

investment costs to the overall TAC values. Since for the other case studies,

684

the AIC contribute (significantly) less to the overall TAC than for the ethanol

685

dehydration, the expected economic advantages of the thermally-coupled side

686

rectifier over the thermally-coupled ED process are less pronounced and only

687

the thermally-coupled ED option is considered.

688

Similar to the previous case study, the TC and DWC options result in in-

689

creased costs for the ED process, particularly since both process need to use a

690

higher steam grade for their sole reboiler covering the total heat duty. For the

691

TC process as depicted in Fig. 6, the reboiler of the second column produces

692

the complete vapor stream that is split by the thermal coupling between the

693

first column and the second column’s rectifying section. Since the separation

39

694

in the extractive column is commonly more difficult than the solvent recovery,

695

the majority of the vapor will be transferred to the first column. However,

696

due to the large vapor load in the second column’s stripping section, the di-

697

ameter of the second column will be relatively large. While the consideration

698

of a constant column diameter might even result in hydrodynamic problems

699

in the rectifying section, moving the stripping section to the first column and

700

operating a thermally-coupled side rectifier (that corresponds to the second

701

column’s rectifying section) may also provide additional cost savings. The

702

potential of such a thermally-coupled side rectifier was further evaluated in

703

addition to the standard TC process of Fig. 6 for the current case study and the results of the design optimization are compared in Table 1. Table 1:

Information on cost and sizes of the optimized thermally-coupled ED process

and the thermally-coupled side rectifier.

thermally-coupled

ED process with

ED process

thermally-coupled side rectifier

HCol1 [m]

16.0

19.0

DCol1 [m]

1.1

1.02

HCol2 [m]

8.5

7.0

DCol2 [m]

1.03

0.26

AIC [ke/a]

301.0

129.4

AOC [ke/a]

591.8

520.6

TAC [ke/a]

892.9

770.7

704 705

While for the initial TC configuration both columns have similar diameters,

706

the side-rectifier configuration enables a significantly smaller column diame40

707

ter for the side rectifier, while the height of the first column HCol1 increases

708

due to the movement of the stripping section of the second column. However,

709

the AIC are significantly smaller for the side rectifier. Moreover, as the side

710

rectifier is optimized as an individual process, the optimization exploits the

711

reduced column diameter by means of an increased number of theoretical

712

stages in the individual sections, such that the overall energy demand and

713

the AOC are also reduced in the optimized process design. Overall, the TAC

714

of the thermally-coupled side rectifier is about 14 % smaller than the initial

715

TC option, so that this option becomes competitive to the extractive DWC.

716

However, for the considered case study the simple ED process is econom-

717

ically still slightly more favorable than the process configuration with the thermally-coupled side rectifier.

Figure 13: Economic and energetic comparison of simple extractive distillation process with ED-DWC 718

41

719

In contrast to the thermally-coupled and DWC options for extractive distil-

720

lation, TC and DWC allow for cost improvements of the HAD process (cf.

721

Fig. 12). This is again in agreement with the results of Wu et al. (2013, 2014)

722

who reported a larger potential of DWC for application in HAD. A detailed

723

comparison of the simple and DWC process options for ED is illustrated in

724

Fig. 13.

725

Despite the economic benefits of the simple process, it is important to note

726

that the DWC variant enables energy savings of about 6 %, being quite com-

727

parable to the 9 % energy savings reported by Kiss et al. (2012). Yet, the

728

shift of the complete energy provision to the highest temperature level in

729

the single reboiler, requires the use of high pressure steam, due to the high

730

boiling temperature of ethylene glycol. Thus, the possible energy savings

731

do not translate into cost savings in terms of AOC, as pointed out by Wu

732

et al. (2013). Moreover, though the dimensions of the single DWC shell are

733

comparable to the extractive column of the simple process, due to the more

734

complicated construction of the split-shell arrangement that is considered by

735

a surcharge factor of 20 % for the DWC, the savings in investment costs for

736

the DWC are also negligible, when comparing the AIC values of simple and

737

DWC variants of the extractive distillation process.

738

Interestingly the derived results change substantially based on the feed com-

739

position, as has been shown in our preceding work (Waltermann et al., 2017),

740

in which we investigated a feed of 10 mol/s with an ethanol content of just

741

6 mol-%, representative of an aqueous ethanol stream from fermentation

742

broth, without additional pre-concentration. In this case, for which the re-

743

sults of the optimization-based design are summarized in Fig. 14.

42

Figure 14: Annualized costs of different process variants for the dehydration of a diluted ethanol feed with 6 mol-% ethanol (Waltermann et al., 2017)

744

Obviously, the HAD process is for this problem specification significantly less

745

expensive than the ED process, whereas the DWC design of the HAD pro-

746

cess is the economically favorable choice. In order to further elucidate the

747

importance of the pre-concentration for the ED process, the optimization-

748

based design is performed for an adapted feed stream with an ethanol content

749

of 6 mol-% and a flowrate of 1416.7 kmol/h, which corresponds to the feed

750

stream considered by Kiss and Suszwalak (2012), prior the pre-concentration.

751

This feed flowrate results in a capacity of about 31000 t/a bioethanol, which

752

also corresponds well to other publications (Singh and Rangaiah, 2017). In

753

accordance with the previous results the simple ED and the DWC version

754

of the HAD process are investigated, while an additional beer column for

755

pre-concentration is considered as well for the ED process. The total heat 43

756

duties and the cost distribution for the three optimized process variants are

757

listed in Table 2, while the design results for the two most economic process variants are depicted in Fig. 15. Table 2:

Energy and cost values for ethanol dehydration of diluted feed by simple ED,

ED with additional pre-concentration and DWC version of HAD

simple ED

simple ED

HAD-DWC

with pre-concentration free xpre D

xpre D = 0.85

QB,tot [kW]

18965.0

5409.3

6004.0

6383.0

AOC [Me/a]

4.80

1.03

1.16

1.12

AIC [Me/a]

0.95

0.53

0.62

0.58

TAC [Me/a]

5.76

1.56

1.78

1.71

758 759

Obviously the ED process with pre-concentration in the beer column results

760

in a much more economic design, compared to the simple ED process for the

761

modified feed specification. However, according to the optimization results

762

that consider all three columns simultaneously the preferred economic process

763

design performs a pre-concentration from 6 mol-% to 79.2 mol-% ethanol, in-

764

stead of the previously considered 85 mol-%. Specifying a pre-concentration

765

to 85 mol-% in the beer column results in a significant increases of the re-

766

quired energy demand and an overall increase in TAC from 1.56 Me/a to

767

1.78 Me/a. Despite the feed-forward connection of the pre-concentration

768

and the ED, there is a clear interdependency between both steps, such that

769

simultaneous optimization of the combined process is mandatory.

770

Unlike the ED process the increased amount of water has a much less decisive 44

Figure 15: Illustration of simple ED with pre-concentration (left) and HAD-DWC (right) for ethanol dehydration of a low concentrated feed

771

effect on the DWC version of the HAD process. While the optimized design

772

has about 10 % higher TAC compared to the ED process with beer column,

773

it is also only about 21 % more expensive compared to the previous design

774

for the pre-concentrated feed (cf. Figure 12).

775

Considering the cost of the pre-concentration and the beer column in the

776

ED design (TAC of 1.78 Me/a for the 85 mol-% case) it can be concluded

777

that the HAD process does not benefit from such separate pre-concentration,

778

while the HAD process is presumably also more flexible with respect to feed

779

fluctuations. The latter should be evaluated further based on a fixed design

780

and process performance evaluations, accounting for the operation limita-

781

tions of the selected internals and performance variations for variable gas

782

and liquid loads.

45

783

Since the computational times for each of the evaluated process variants did

784

not exceed 15 minutes, the complete case study can be evaluated in less than

785

4 h of computational time. This time could be reduced further through par-

786

allelization of the evaluations by means of simple multi-threading, given a

787

sufficient amount of licenses. The case study clearly demonstrates that the

788

proposed design approach can be used to efficiently evaluate ED and HAD

789

and potential means for energy integration for a specific separation problem

790

and variations in the problem specifications.

791

3.3. Separation of acetone and methanol by ED

792

The last case study investigates the separation of acetone and methanol by

793

means of ED with various MSA, similar to the preceding work of Kossack

794

et al. (2008) and Skiborowski et al. (2015b). However, the current investi-

795

gation includes the different means for energy-integration and evaluates the

796

effect on the preferred solvent choice. The considered saturated liquid feed

797

consists of an equimolar mixture of acetone and methanol with a flow rate of

798

540 kmol/h. The considered MSA candidates correspond to the selection of

799

Kossack et al. (2008) and are listed in Table 3 with their corresponding costs,

800

adopted from Skiborowski et al. (2015b). The thermodynamic properties are

801

calculated by the UNIQUAC g E model, the extended Antoine equations and

802

DIPPR correlations, for which the parameters are taken from the Aspen

803

R Plus APV-V88 VLE-IG and PURE32 database. Purity requirements for

804

both products are 99.5 mol-% and the plant is depreciated for a period of

805

10 years.

806

As indicated in Figure 16, DMSO represents the most favorable solvent

807

choice, based on the economic performance of the optimized simple ED pro46

Table 3: Considered MSA candidates and their specific costs (exchange rate of 0.8465 e$ ) for acetone/methanol separation by means of ED.

MSA

Costs

ethanol

800 $/t

chlorobenzene 1000 $/t DMSO

1400 $/t

water

0.03 $/t

p-xylene

1250 $/t

808

cess. While its high boiling point mandates the use of high pressure steam,

809

the low energy requirement results in the overall lowest AOC, which for the

810

comparable high depreciation time determines largely the TAC.

811

Only the AOC of the water-based ED process are comparable, while chloroben-

812

zene results in considerably higher AOC and around 25 % higher TAC. The

813

TAC of the p-xylene and ethanol-based ED process are significantly higher,

814

being more than 50 % and 90 % more expensive compared to the DMSO-

815

based ED process. It has to be mentioned that despite the large price differ-

816

ences of the considered MSA, especially water, the solvent make-up stream

817

is negligible small, resulting in a maximum cost share of less than 2.4 % of

818

the TAC, also due to the high product purity specifications.

819

Based on these initial results it is further checked if the consideration of en-

820

ergy integration can alter this ranking, focussing on the first three solvents,

821

since energy savings of more than 50 % are highly unlikely. The results of

822

this evaluation are further summarized in Figure 17, for which the dashed

823

line indicates the TAC of the simple DMSO process, which serves as refer47

Figure 16: Economic results for the optimized ED processes for the separation of acetone and methanol with different MSA. 824

ence value for the subsequent evaluation. A HI variant of the DMSO process

825

is discarded, since the reboiler temperature of the solvent recovery column

826

would exceed the maximum temperature limit of 492 K, which was specified

827

based on a limitation of the available utilities. The TC and DWC options are

828

both more expensive, since despite an overall reduced heat duty, the overall

829

AOC increase significantly due to the increased high pressure steam require-

830

ment, since all of the heat has to be supplied at the highest temperature of

831

the process.

832

Only the VRC option allows for slight savings of 2 % in TAC. However,

833

the VRC section is only utilized in the extractive distillation column, but

48

Figure 17: Economic results for the optimized energy-integrated ED processes for the separation of acetone and methanol with different MSA.

834

bypassed in the recovery column. In fact, despite the relatively high tem-

835

perature difference between reboiler and condenser of about 33 K for the

836

extractive column, the necessary compression can be performed with low

837

energy requirements and offers economic savings. For the recovery column,

838

however, the VRC offers no saving potential due to the very high temper-

839

ature difference of 126 K between reboiler and condenser. Altogether, the

840

potential AOC savings are, however, canceled mostly out by the increased

841

AIC for the required compressor.

842

For chlorobenzene, the results are comparable and none of the options for

843

energy integration apart from the VRC allows for TAC savings. As for the 49

844

DMSO-based process, the VRC option allows for a slight reduction of 9 % of

845

the TAC, which however does not suffice to outperform the DMSO process.

846

The situation looks quite different for the water-based ED process. While

847

the thermally-coupled process configurations also do not offer economic ben-

848

efits, both HI and VRC can significantly improve the economic performance,

849

even beyond the DMSO-based process. In fact, the HI process configura-

850

tion becomes the overall most attractive process, being 21 % less expensive

851

than the simple DMSO-based process. Thus, it has to be concluded that the

852

consideration of energy integrated process concepts can effectively alter the

853

results of the solvent screening.

854

Besides the economic saving potential, water offers additional benefits, being

855

sustainable, non-toxic and extremely cheap. The comparably big impact of

856

energy integration for the water-based ED process stems from the compara-

857

bly low boiling point of water, which on the one hand enables the use of low

858

pressure stream and on the other hand results in smaller temperature differ-

859

ences between the different heat exchanger’s that are to be integrated. The

860

process design of the optimized HI ED process with water is depicted in Fig-

861

ure 18. Allowing for the integration of around 6 MW, it reduces the external

862

heat duty by 39 % compared to the simple ED process. Consequently, MSA

863

selection should be performed with the additional consideration of energy

864

integration.

50

Figure 18: Detailed design of HI ED as optimal process variant for case study 3

865

The case study illustrates that energy integration should not be considered

866

as a final post-processing step for the best solvent choice for non-integrated

867

processes, but rather be included in the solvent screening. While feasibility

868

criteria can be considered for a pre-evaluation of suitable solvents, the final

869

solvent screening should be performed on the basis of the optimized process

870

design, since the complex interactions between solvent properties, process

871

performance and energy integration potential cannot be depicted by simple

872

heuristics.

51

873

4. Conclusion

874

The design of extractive and heteroazeotropic distillation processes is a chal-

875

lenging task, which requires the correct identification of a mass separating

876

agent, as well as the optimization of an integrated closed-loop process, consid-

877

ering the primary separation and solvent recovery. On top of that, different

878

means for energy integration can be considered, which can very well alter the

879

results in terms of optimal solvent choice and process selection. While sol-

880

vent selection and process design are nowadays supported by computational

881

tools, there are still distinct limitations that need to be resolved in order to

882

determine the best solvent and process combination. MSA selection is usu-

883

ally focussed on simplified criteria, which are important for pre-screening but

884

should not determine the final choice, whereas process simulators oftentimes

885

lack the necessary capabilities for process optimization and require a tedious

886

initialization and optimization approach, relying to a large extend on manual

887

tuning and expert knowledge. The potential of energy integration is rarely

888

evaluated for more than the finally selected solvents.

889

The presented optimization-based method for the design of extractive and

890

heteroazeotropic distillation processes overcomes the problems related to the

891

use of commercial process simulators and enables a direct evaluation of dif-

892

ferent means for energy integration for multiple solvents. The capabilities of

893

the presented design approach are illustrated for three different case stud-

894

ies, highlighting different features of the proposed method. The application

895

for the separation of methanol from the ternary mixture with acetonitrile

896

and benzene by extractive distillation with chlorobenzene shows that the

897

design method is can be applied to multi-azeotropic mixtures with four or 52

898

even potentially more components. The ethanol dehydration case study il-

899

lustrates how effective extractive and heteroazeotropic distillation processes

900

with potential energy-integration can be evaluated and compared for varying

901

problem specifications. Finally, the separation of the acetone and methanol

902

mixture illustrates the potential for an integrated evaluation of solvent se-

903

lection and energy integration. It further highlights the advantages of such

904

a simultaneous consideration in determining the optimal process design.

905

As presented for the case studies, the approach facilitates a computationally

906

efficient quantitative comparison of the different process concepts for specific

907

separation problems and enables a detailed analysis of the benefits and lim-

908

itations of these process concepts through modification of feed and product

909

specifications. While the results of the case studies validate previous results

910

for the concept of dividing wall columns in extractive and heteroazeotropic

911

distillation, reported by Wu et al. (2013, 2014), the presented design method

912

enables an efficient evaluation of the potential and the comparison with al-

913

ternative means for energy integration. It provides an important computa-

914

tionally efficient tool for the integration of solvent and process design, which

915

is mandatory for the evaluation of a multitude of solvent candidates, which

916

cannot rely on manual initialization and optimization.

917

Future work will investigate the utilization of the current approach for com-

918

puter aided solvent screening and design, as in the work of Kruber et al.

919

(2018), exploring the already indicated potential for parallelization of the

920

required computations. Furthermore, in order to overcome the potential en-

921

trapment in sub-optimal local solutions of the highly nonlinear mixed-integer

922

optimization problems, the extension of the optimization approach to a hy-

53

923

brid stochastic deterministic approach (Skiborowski et al., 2015b) is also

924

under current investigation (Kruber et al., 2019). At last, an extension of

925

the considered process concepts, including concepts such as internally heat-

926

integrated distillation-columns (Harwardt and Marquardt, 2012) or combi-

927

nations of the different concepts (Jana, 2019), as well as a potential energy

928

integration with a background process will be explored as well.

929

Acknowledgement

930

This work was performed in the knowledge transfer project “Hybrid separa-

931

tion processes: Modeling and design of membrane-assisted distillation pro-

932

cesses”, which is part of the Collaborative Research Center on ”Integrated

933

Chemical Processes in Liquid Multiphase Systems”. Financial support by

934

the Deutsche Forschungsgemeinschaft (DFG) is gratefully acknowledged.

935

54

936

55

937

56

938

939

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Conflict of Interest

1137

The authors declare that they have no known competing financial interests

1138

or personal relationships that could have appeared to influence the work

1139

reported in this paper.

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1140

Author Contribution

1141

Thomas Waltermann: Conceptualization, Methodology, Software, Investi-

1142

gation, Visualization, Writing Original Draft. Tamara Grueters: Method-

1143

ology, Software. Daniel Muenchrath: Methodology, Software. Mirko

1144

Skiborowski: Conceptualization, Methodology, Supervision, Project ad-

1145

ministration, Writing Review & Editing.

68