Efficient optimization-based design of energy-integrated azeotropic distillation processes
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.
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]
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
Azeotropic mixtures are encountered in the downstream processing of many
chemical processes and are of particular importance for the processing of bio-
renewables, for which aqueous-organic mixtures are frequently encountered.
Two established process concepts for the separation of such mixtures into
high purity products are extractive distillation (ED) and heteroazeotropic, or
heterogeneous azeotropic distillation (HAD) (Skiborowski et al., 2013; Arlt,
2014; Gerbaud and Rodriguez-Donis, 2014), which have been used in the
process industries for almost a century (Stichlmair and Herguijuela, 1992).
Both processes depend on the effect an entrainer, or mass separating agent
(MSA), has on the thermodynamic properties of the mixture. In the case
of ED the MSA facilitates the separation by interacting with the original
azeotropic mixture, by altering the relative volatility between the azeotrope
forming components, such that they can be separated in a two-feed column,
while recovering the MSA in a subsequent recovery column (cf. Figure 1
(left)) (Kossack et al., 2008). For HAD, the MSA is supposed to introduce
a minimum boiling heteroazeotrope, which facilitates the separation due to
a combination of distillation and decantation, as illustrated for a classical
configuration in Figure 1 (right)(Kraemer et al., 2011). Due to this combi-
nation and the ease of recovery of the MSA HAD was oftentimes preferred
in industry (Widagdo and Seider, 1996). Specifically for medium and large-
scale processes, as in the production of bulk chemicals and intermediates, ED
and HAD both benefit from economics of scale (Kiss and Suszwalak, 2012),
which they offer over alternative processes for the separation of azeotropic
mixtures, such as membrane separations and adsorption. However, since
distillation processes suffer from a low thermodynamic efficiency in general
(Koeijer and Kjelstrup, 2000) and due to the necessary separation and recov-
ery of the additional entrainer, ED and HAD are considered rather energy
In order to design the most effective ED and HAD processes, the choice of
MSA, is of tremendeous importance (Blahuˇsiak et al., 2018). Potential MSA
are either selected based on heuristic rules and expert knowledge, or through
computer aided molecular design approaches (CAMD) (Gani et al., 2006).
The latter allow for an automated screening of MSA based on certain fea-
sibility criteria and the estimation of thermodynamic properties based on
group contribution models or quantitative structure-property relationships
(QSPR). CAMD approaches are well established for ED, evaluating e.g. dis-
tribution coefficients, selectivities and capacities (Kossack et al., 2008; Zhou
et al., 2019), or more informative, information on the isovolatility curve (Cig-
nitti et al., 2019). Further analysis of MSA feasibility for both ED and HAD
can be derived from analysis of residue curve maps (RCM) (Julka et al., 2009;
Skiborowski and G´orak, 2016). As the feasibility of HAD processes requires
a rather complex topology with respect to the vapor-liquid-liquid equilib-
rium (VLLE), the literature on CAMD approaches for HAD is rather scarce.
Two exceptions are the articles of Yang et al. (2012) and Furzer (1994).
Both propose a group-contribution-based CAMD approach. However, Yang
et al. (2012) evaluate the suitability of a MSA based on the formation of a
heteroazeotrope, as well as the derived information on its composition, tem-
perature and heat of vaporization,while Furzer (1994) proposes a simplified
graphical evaluation of the purification of one desired product based on an
analysis of the binary x-y diagram.
Despite the lack of topology-based screening methods for MSA selection, it
is important to recognize that the evaluation generally considers a specific
process structure, for which according criteria for MSA selection are derived.
While different ED and HAD process configurations are potentially feasible,
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
temperature minimum azeotrope by introducing a heavy boiling MSA, which
shows a considerably higher affinity to component A than B. This configura-
tion is commonly preferred, because of an easier recovery of the MSA and the 6
purification of both products as distillate (Kossack et al., 2008). The recent
review article of Gerbaud et al. (2019) provides an elaborate description of
this, as well as alternative ED configurations and related feasibility criteria.
The depicted HAD process represents the most commonly considered config-
uration, which is also representative for the separation of a mixture with a
temperature minimum azeotrope, such as encountered in the dehydration of
ethanol or isopropanol. While a feasible MSA for ED should not introduce
an additional azeotrope, the occurrence of a ternary heterogeneous temper-
ature minimum azeotrope is mandatory for a feasible MSA in case of the
HAD process. The products are obtained as bottoms products in case of
the HAD process, while both columns operate in different distillation regions
and process feasibility depends primarily on the liquid phase separation in
the decanter on top of the second distillation column. Aside from the specific
HAD configuration depicted in Fig. 1, other variants are also possible such
as extractive HAD processes (Gerbaud et al., 2019), these are not covered in
the current design approach yet.
Which process and especially which combination of process and MSA per-
forms best requires a thorough investigation of the process performance,
based on appropriate thermodynamic and process specific models. The final
design tasks consists of the identification of a detailed feasible and at best eco-
nomically optimal process design, including various degrees of freedom such
as the number of trays or packing height in the different column sections,
the entrainer to feed ratio, reboiler and condenser duties and appropriately
sized columns. However, first potential MSA candidates need to be identified
and evaluated for feasibility. The various approaches for ED reach from an
investigation of the minimum entrainer flow rate and corresponding mini-
mum and maximum reflux ratios by means of RCM analysis (Wahnschafft
and Westerberg, 1993), bifurcation analysis (Knapp and Doherty, 1994) and
pinch-based shortcut methods (Br¨ uggemann and Marquardt, 2004) to var-
ious types of simulation and optimization approaches for equilibrium stage
models. For HAD the situation is similar, yet the determination of the mini-
mum entrainer flowrate and reflux ratio requires a multi-step approach, even
for sophisticated pinch-based shortcut methods (Urdaneta et al., 2002; Wa-
sylkiewicz et al., 2003; Kraemer et al., 2011; Skiborowski et al., 2018). Most
process design methods based on equilibrium stage models build on a pro-
cess simulator in combination with a manual optimization procedure (Brito
et al., 2016b), a metaheuristic (Tututi-Avila et al., 2014) or the optimiza-
tion of surrogate model, fitted to sampling data obtained from a process
simulator (Wang et al., 2013). For any of these design methods, the correct
identification of multiple liquid phases in case of HAD is mandatory. For the
common case of potential demixing into two liquid phases, this requires the
consideration of either vapor-liquid equilibrium (VLE) or VLLE in respect
to the equilibrium description. The article of Gerbaud et al. (2019) provides
an extensive review about ED in general and process synthesis, design and
optimization in specific, while the articles of Skiborowski et al. (2013, 2015a)
provide detailed reviews for ED and HAD in specific.
Overall, Scopus lists more than 1000 publications and more than 9000 patents
for the keywords ”extractive distillation” and ”heteroazeotropic distillation”,
with increasing numbers especially in the recent 10 to 20 years. Yet, only
a small fraction of these documents deals with heteroazeotropic distillation
and even for extractive distillation, articles that consider means for energy
integration have been published primarily in the recent five years. Heat in-
tegration (Cui et al., 2018), thermal coupling (Brito et al., 2016b) and the
equipment integration in terms of dividing wall columns (Kiss and Suszwalak,
2012; Franke, 2017), as well as the use of heat pumps (You et al., 2016) or
multi-effect distillation (Bessa et al., 2012) are potential options for energy
integration of extractive and heteroazeotropic distillation processes. For ex-
tractive distillation, the elaborate up-to-date review article of Gerbaud et al.
(2019) does not only extensively discuss the assessment of feasibility, syn-
thesis and design of extractive distillation processes, but also summarizes
the different publications on energy-integrated process designs. Most of the
published articles focus on the evaluation of a specific concept for energy
integration with respect to the non-integrated base case, considering a single
separation problem. Yet, even for those restricted investigations, it is high-
lighted that a reliable quantification of energy and economic saving potentials
require a case-specific evaluation, for the specific chemical system, feed and
product specifications and economic parameters (Brito et al., 2016a). The
article of You et al. (2016), which compares different heat pump configu-
rations for extractive distillation, as well as the article of Gu et al. (2019),
which presents an evaluation of three energy-integrated concepts, considering
heat integration, an intermediate reboiler, as well as vapor recompression, are
rather rare exceptions.
Fig. 2 summarizes the different steps associated with the design of ED and
HAD processes, which as previously discussed are mostly investigated subse-
quently, as in the classical hierarchical design approach proposed by Douglas
(1985). However, few efforts have been made to systematically integrate
some of the steps, especially the generation of suitable entrainers for ED
and the evaluation of the energy-based or economic performance of these
MSA candidates. The systematic synthesis framework proposed by Kossack
et al. (2008) integrates group-contribution-based CAMD with shortcut and
equilibrium-stage model-based process design optimization, while the system-
atic framework of Zhou et al. (2019) combines multi-objective optimization
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
For both studies, the rigorous design optimization is limited to a small num-
ber of MSA, for which a comparison is made based on the total annualized
costs (TAC). This is important for a fair comparison of the different MSA
candidates (Gerbaud et al., 2019). Nevertheless, neither of the approaches
includes any means for energy integration. However, the consideration of
energy integration might considerably alter the ranking of potential MSA,
since the MSA choice directly affects condenser and reboiler temperatures
and consequently the potential for energy savings. This potential problem
was already pointed out by Kossack et al. (2008). Consequently, a holistic
design approach should cover all four steps depicted in Fig. 2.
While CAMD methods for solvent screening and the preselection based on
feasibility criteria have been successfully established, at least for ED, the most 10
challenging task for the evaluation of ED and HAD considering means for
energy integration is posed by the efforts for the process design optimization.
Simulation-based methods for process optimization require at least a feasible
and converged initial flowsheet simulation, which has to be derived through a
manual trial and error approach. As highlighted by Luyben (2013) as well as
Le et al. (2015), obtaining such a convergent base case can be extremely chal-
lenging, particularly for HAD processes, for which the correct identification
of phase stability and the inherent integration of the column and decanter
are serious complexities. In order to avoid the complexity of closed-loop flow-
sheets, even for ED, most studies simplify the design task by performing a se-
quential design of the extractive and recovery column (Gerbaud et al., 2019).
Optimization-based design methods, which attempt an automatic initializa-
tion by solving a series of successive optimization problems, can overcome
these problems and simultaneously determine an optimized final process de-
sign, w.r.t. an economic objective and related problem specific constraints.
Such polylithic modeling and solution approaches (Kallrath, 2011) have pre-
viously been presented for ED (Kossack et al., 2008), HAD (Skiborowski
et al., 2015a), as well as the evaluation of various concepts for energy in-
tegration for the basic three distillation sequences for the distillation-based
separation of three products (Waltermann and Skiborowski, 2016, 2019).
Building on these preceding works, we have developed an optimization-based
design approach that enables the efficient computational screening of differ-
ent MSA candidates and means for energy integration for both ED and HAD.
This approach considers several means for energy integration, including clas-
sical heat integration, thermal-coupling and respective dividing wall column
designs as well as heat-pump assisted distillation in terms of vapor recompres-
sion. Compared with the previously considered optimization-based design of
energy-integrated distillation sequences (Waltermann and Skiborowski, 2019)
the design of the energy-integrated ED and HAD processes is considerably
more challenging, since these processes are already integrated and not fea-
sible without the additional MSA, which presents an additional degree of
freedom. To the best of our knowledge there has not been any publication
that proposed and demonstrated a simultaneous and computationally effi-
cient approach for the evaluation of various solvent candidates and means for
energy-integration. Such efficient tools are of tremendous importance to meet
the goals of designing more sustainable, yet economic processes in an ever
shrinking time window for process development (Agrawal, 2001). Besides
the comparative analysis of the different process concepts, the automatic de-
sign method can also be integrated into the process synthesis framework of
Kossack et al. (2008). This integration effectively extends the framework
by covering the last step of Fig. 2. The developed method is described in
further detail in Section 2, before Section 3 presents the results of different
applications, including a comparison of both process concepts for ethanol
dehydration with different feed specifications, as well as the comparison of
different MSA candidates for ED of acetone and methanol, illustrating the
importance of a simultaneous consideration of MSA selection and energy in-
tegration. Section 4 finally provides a conclusion and an outlook on future
2. Modeling and optimization
The developed optimization-based design approach builds on several preced-
ing publications. The general approach for model formulation and solution
of ED processes was developed by Kossack et al. (2008) and Kraemer et al.
(2009b) while the extension to HAD processes was presented by Skiborowski
et al. (2015a). The underlying superstructure models are based on equi-
librium stage models considering the well-known MESH equations (material
balances, equilibrium models, summation constraints and enthalpy balances)
(Kister, 1992) in combination with variable locations for feed, reflux and boil-
up streams, as initially proposed by Viswanathan and Grossmann (1993). In
order to integrate an efficient phase-stability test (Bausa and Marquardt,
2000) and allow for a robust computation of VLE/VLLE, these calculations
are performed by a set of dedicated algorithms, for which the results and
sensitivities are integrated into the overall optimization problem via a set of
external equations (Skiborowski et al., 2015a). The external functions used
for the thermodynamic calculations are available online through the AVT-
SVT website1 .
The energy-integrated ED and HAD process variants are furthermore derived
from a previously presented design approach (Waltermann and Skiborowski,
2019) for the energy integration of simple sequences, considering the sepa-
ration of non-ideal mixtures into three products. The following subsections
first present a summary of the ED and HAD optimization models, before the 1
different process modifications for energy integration are described, followed
by the solution approach that allows for an automatic initialization and op-
timization of the different process variants. An elaborate description of the
different model modifications for the energy-integrated process variants is
not introduced, as these are equivalent to the modifications for the simple
sequences, which were thoroughly described by Waltermann and Skiborowski
2.1. Optimization model for extractive distillation
The graphical representation of the superstructure model of the simple ED
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
The equilibrium stages of the column model are numbered from top (1) to
bottom (Nth ), such that stage 1 corresponds to the condenser and stage Nth
to the reboiler. Thus, the column itself consists of a maximum number of Nth
- 2 theoretical stages. The corresponding MESH equations are further listed
for the ED column, while the same equations hold for the solvent recovery
column, without the appearance of the second feed stream. The mass balance
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
+ bS,n FS zS,i + bR,n RR,n xR,i + bB,n RB,n yB,i ,
n = 2, . . . , (Nth − 1), i = 1, . . . , nc
with L and V representing the flow rate of the liquid and vapor streams
leaving or entering a theoretical stage n. Moreover, x and y correspond to
the molar compositions of these liquid and vapor streams. Furthermore, FF
and zF as well as FS and zS represent the flow rate and composition of the
fresh (azeotropic) feed stream and the solvent feed, for which distribution
to a certain theoretical stage n is determined through an additional binary
decision variable (bF,n and bS,n ). Similar decision variables (bR,n and bB,n )
determine the equilibrium stage to which the reflux and reboil streams with
flow rates RR and RB and composition xR and yB are distributed. The
corresponding energy balance with the specific enthalpies of liquid, vapor
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
+ bS,n FS hS + bR,n RR,n hL,R + bB,n RB,n hV,B , n = 2, . . . , (Nth − 1). 15
For the condenser (the first equilibrium stage), modified mass and enthalpy
balances including the condenser heat duty QC and the distillate flow rate
D, as well as additional constraints for the composition xR and enthalpy hL,R
of the reflux stream are specified
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 ,
0 = hL,R − hL,1 .
NX th −1
n = 1, i = 1, . . . , nc ,
RR,j + D)hL,n − QC ,
n = 1,
1, . . . , nc ,
(4) (5) (6)
The same applies for the reboiler (the last equilibrium stage) with the reboiler
heat duty QB and the bottoms flow rate B, as well as the compositions and
enthalpy values xB and hL,B of the bottoms product and yB and hV,B of the
0 = Ln−1 xn−1,i −
NX th −1
0 = Ln−1 hL,n−1 −
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 ,
0 = xB,i − xNth ,i ,
1, . . . , nc ,
0 = yB,i − yNth ,i ,
1, . . . , nc ,
0 = hV,B − hV,Nth ,
0 = hL,B − hL,Nth .
The equilibrium relationship between the liquid and the vapor phase on each
of the equilibrium stages, as well as the computation of the specific enthalpies 16
is realized by means of the aforementioned external equations
eVLE = yi − yˆi (x, p) = 0, i
ˆ eVLE nc +1 = T − T (x, p) = 0,
ˆ ˆ eVLE nc +2 = hL − hL (x, p, T (x, p)) = 0,
ˆ y (x, p), p, Tˆ(x, p)) = 0, eVLE nc +3 = hV − hV (ˆ
which determine the equilibrium vapor composition yˆ(x, p) and temperature
Tˆ(x, p) for the current liquid composition x and pressure p, as well as the spe-
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
on pre-selected thermodynamic property models for the computation of the
liquid and vapor fugacitities, as well as specific heat capacities and enthalpies
of vaporization. Further details are provied in the article of Skiborowski
et al. (2015a). Moreover, further information on the applied thermodynamic
models in the scope of the current paper are listed in Section 3 for each
of the investigated case studies. The MESH equations for each stage are
supplemented by the summation constraints for the liquid and vapor phase
i = 1, . . . , nc ,
xn,i = 1,
n = 1, . . . , Nth ,
yn,i = 1,
n = 1, . . . , Nth .
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,
bS,n = 1,
bR,n = 1,
bB,n = 1,
as well as additional constraints that enforce an ordered location of the dif-
ferent feed, reflux and boil-up streams complete the set of equations for the
definition of the superstructure model. The optimization model for a sin-
gle column is further composed of additional sizing and costing correlations.
The sizing of the columns and additional equipment is done as described by
Waltermann and Skiborowski (2019), while the costing of the equipment is
based on the cost correlation of Guthrie (1969) and Biegler et al. (1997),
applying the CEPCI Equipment Index for September 2017 (Economic Indi-
cators, 2018) to update the calculated capital costs. The different competing
process options are optimized for TAC, which are composed of the annual
operating costs (AOC) and the annualized investment costs (AIC). The AIC
represents an annuity that reflects the depreciation of the initial investment
over a certain plant lifetime, considering a specific rate of return. The consid-
ered economic models, including the economic parameters, assumed utilities
and references are listed in further detail in the Supplementary material.
While the superstructure model of the solvent recovery column is equivalent
to the ED column, without the second feed stream, the MSA is recycled as 18
bottoms product B from the solvent recovery column to the ED column and
mixed with fresh MSA to compensate for solvent losses. For this purpose the
overall model is completed by additional mass and energy balances for the
mixing of the second feed stream
FS = FM SA + B2 − P
FS zS,i = FM SA zM SA,i + (B2 − P )xB2 ,i ,
FS hS = FM SA hM SA + (B2 − P )hL,B2
i = 1, . . . , nc − 1
and mixed with a makeup stream FM SA to cover for losses in the product
streams. Additionally, a potential purge stream P is introduced, which can
be utilized in case of a potential accumulation of impurities. Since this is
not the case for the different case studies considered in Section 3, the purge
stream is limited to a certain upper level (< 1 % of the fresh feed stream)
during the initialization and furthermore reduced to zero during the economic
optimization, when accounting for fresh solvent cost.
2.2. Optimization model for heteroazeotropic distillation
The graphical representation of the superstructure model for the simple HAD
process is illustrated in Fig. 4. Apparently, the single column superstructures
are quite similar to those in the ED process. However, contrary to the ED
process, the fresh MSA stream and the MSA-rich recycle stream are mixed
with the (azeotropic) feed. The mixed stream is fed to the first column,
which is a simple distillation column that is supposed to operate in the ho-
mogeneous region of the composition space. The top product of the first
column, which is a saturated vapor feed from the partial condenser of the
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.
This column performs the heteroazeotropic distillation, for which the top va-
por stream leaving the column, which is supposed to be closely located to the
light-boiling heteroazeotrope, is first condensed and potentially sub-cooled,
before it is separated into two liquid phases in a decanter. Either the single
phases or a mixture of both are further recycled back to the heteroazeotropic
distillation column as well as the first distillation column. A major difference
between the ED and the HAD process is the location of the product streams.
Whilst both product streams for the ED process are derived as top products,
both products of the HAD process are derived as bottoms product. Although
top products have decent advantages with respect to potential impurities in
the reboiler, the production of bottoms products can bring other interesting
advantages, as will be shown in Section 3.2.
One of the major challenges in the design of HAD processes is the correct 20
determination of liquid phase-stability, since both VLE and VLLE relation-
ships allow for mathematically valid solutions in the whole composition space
(Raghunathan and Biegler, 2003; Skiborowski et al., 2015a). This problem
had previously been solved by the integration of a numerically efficient hybrid
method in a special implementation of the aforementioned external equations
(Skiborowski et al., 2015a). While the correct VLE or VLLE solution is first
determined based on a homotopy continuation approach (Bausa and Mar-
quardt, 2000), resulting VLLE solutions for column equilibrium stages are
further mapped to a quasi-homogeneous VLE result, including the compu-
tations of the specific enthalpies. This approach allows for the utilization of
the same MESH model as described in Eq. (1)-(22) for the ED columns, with
the exception of the decanter and the connectivity between the decanter and
the columns. The latter modifications are further described in the follow-
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
the liquid phase split in the decanter, the decanter is modeled by the fol-
lowing set of MESH equations that match to the graphical representation in 21
LC xC,i = LI xIi + LII xII i ,
LC hL,C = LI hIL + LII hII L ,
Ld1 xd1,i = ξ I LI xIi + ξ II LII xII i ,
Ld1 hd1 = ξ I LI hIL + ξ II LII hII L ,
i = 1, . . . , nc ,
i = 1, . . . , nc ,
Ld2 xd2,i = (1 − ξ I )LI xIi + (1 − ξ II )LII xII i ,
Ld2 hd2 = (1 − ξ I )LI hIL + (1 − ξ II )LII hII L .
i = 1, . . . , nc ,
Eq. (26) and (27) provide the mass and enthalpy balances that link the
molar flow rates, compositions and specific enthalpies of the condensed top
vapor stream (Lc , xc , hL,c ) and the single liquid phases resulting from the
liquid phase split (LI , xI , hIL ) and (LII , xII , hII L ). The flow rate, composition
and specific enthalpy of the two recycle streams (Ld1 , xd1 , hd1 ) to the HAD
column and (Ld2 , xd2 , hd2 ) as recycle stream to the first column, are further
controlled by the split ratios ξ I and ξ II , as introduced in the mass and
enthalpy balances in Eq. (28)-(31). Thus, either both recylce streams can be
a mixture of the single liquid phases or either one can be limited to a single
The consideration of a partial condenser for the first column results in the
following modifications of the mass and enthalpy balances of the condenser
(Eq. (3) and (4)):
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 ,
NX th −1 j=2
RR,j hL,n + DhV,n − QC , 22
n = 1.
For the HAD column with the decanter, the whole set of equations for the
condenser (Eq. (3)-(6)) is to be replaced by the mass and enthalpy balances
0 = Vn+1 yn+1,i − LC xC,i ,
0 = Vn+1 hV,n+1 − LC hL,C − QC ,
n = 1, i = 1, . . . , nc , n = 1,
as well as additional equations that link the first outlet stream of the decanter
with the reflux stream to the HAD column:
NX th −1 j=2
RR,j − Ld1 ,
0 = xR,i − xd1,i ,
0 = hL,R − hd1 .
1, . . . , nc ,
The mixed feed stream Fmix of the first column is further determined based
on the following mass and enthalpy balances:
Fmix = FF + FM SA + Ld2 ,
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
The same sizing and costing correlations for the ED process are considered
for the HAD process as well and are listed in the Supplementary mate-
rial. Thereby, the additional costs for the decanter are not considered in
the economic evaluation, which is a pragmatic simplification, since the dis-
engagement time required for its sizing can only be obtained reliably by lab
experiments (Mersmann et al., 2011).
2.3. Heat and mass integrated processes ED and HAD processes
Based on the initial superstructure formulations of the ED and HAD pro-
cess, different means for heat and mass integration are considered, for which
a graphical illustration is presented in Fig. 6 and Fig. 7. For visual con-
venience, the potential stream distribution indicated for the simple process
configurations in Fig. 3 and Fig. 4 is spared in these illustrations. As illus-
trated, a heat-integrated option, the vapor recompression for both individual
columns, as well as a thermally-coupled and an equipment-integrated divid-
ing wall column equivalent of the thermally-coupled process are considered.
All of these energy-integrated process variants, which are further described in
more detail, are automatically derived in an automated procedure, through
constraint modifications and additional sub-models, starting from the simple
non-integrated process concepts, as will be elaborated in Section 2.4. The
following subsections provide further detail on the energy-integrated ED and
HAD process configurations, while the reader is redirected to our previous
article on the design of energy-integrated simple distillation processes (Wal-
termann and Skiborowski, 2019) for the respective model modifications.
2.3.1. Extractive distillation
While the ED process requires recycling of the MSA and accounts for the
mixed solvent stream as a second feed to the ED column, the modification
for the energy-integrated process concepts are equivalent to those presented
for the direct split sequence for a ternary product separation by Waltermann
and Skiborowski (2019). They are illustrated in Fig. 6.
For the thermally-coupled (TC) ED process, the reboiler of the first column is
removed and the liquid stream from the bottom of the ED column is directly 24
fed as feed stream to the second column, while the boil-up stream for the ED
column is provided by a vapor side stream from the second column. Although
the thermal coupling may enable an overall reduction of the energy require-
ment, as well as a reduced investment by elimination of the reboiler, the
vapor production is shifted completely to the reboiler of the second column,
which operates at a higher temperature. Consequently, energy savings may
not directly translate into reduced operational costs, especially in the case of
a very high-boiling entrainer (Wu et al., 2013). Additional cost-savings can
be established by means of an equipment integration, in terms of the imple-
mentation of the TC ED process in a dividing wall column (DWC). While
the superstructure model based on the MESH equations is identical for the
TC and DWC configuration, sizing and costing correlations are adapted, as
described by Waltermann and Skiborowski (2019).
For a direct heat integration (HI) between both columns in the ED process, a
sufficient pressure difference between the operating pressures of both columns
needs to be established, such that the reboiler of the ED column can be par-
tially or fully integrated with the condenser of the second column to minimize
the external energy requirement. Although Fig. 6 indicates two separate heat
exchangers connected by a dashed arrow, the optimization model considers
only a single heat exchanger for the heat integration. The corresponding
optimization model further includes optional auxiliary heat exchangers to
compensate for the difference between the condenser and reboiler heat duty,
as well as additional pre-heating of the feed stream to the second column, in
order to reach the saturation temperature at the increased pressure.
The heat pump assisted ED process considering vapor recompression (VRC)
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).
may enable significant savings in terms of energy requirements and operat-
ing costs, but at a considerable increase in capital costs due to the required
compressor. VRC can be considered as a state-of-the-art industrial system
for energy integration in binary splits, which has been applied specifically 26
for close boiling systems (Kiss et al., 2012). Despite the comparably large
temperature difference between top and bottoms products in the ED process,
VRC is of particular interest for the improvement of ED processes (Gerbaud
et al., 2019). While the superstructure allows for a partial or complete bypass
of the VRC section, two additional heat exchangers are integrated for super-
heating the vapor up-front the compressor in order to avoid condensation in
the compressor, as well as behind the valve to ensure saturation conditions
for the reflux to the column. The compression is modeled as isentropic with
a specific isentropic efficiency (Harwardt and Marquardt, 2012; Waltermann
and Skiborowski, 2019). As for the HI variant, the separate heat exchangers
connected by the dashed arrow are considered as single heat exchanger in
the optimization model.
2.3.2. Heteroazeotropic distillation processes
Similar to the ED process, the modification for the energy-integrated HAD
concepts are equivalent to those presented for the indirect split sequence for
a ternary product separation by Waltermann and Skiborowski (2019). The
major differences are the integration of the decanter in the HAD column and
the recycle stream to the first column, which is mixed with the fresh feed
and MSA. The different energy-integrated process options are illustrated in
Fig. 7,consisting of a thermally-coupled process configuration, a dividing wall
column as well as directly heat integrated distillation columns and heat-pump
assisted distillation by means of vapor recompression.
For the thermally-coupled (TC) HAD process, the condenser of the first col-
umn is eliminated, such that the top vapor stream is introduced as feed
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).
a liquid side stream from the HAD column. Thereby, both reboilers are main-
tained and only the heat duty for condensation is shifted from the first to the
second column, for which condensation is performed at a lower temperature.
The thermal coupling can again result in considerable overall energy savings
(Kiss et al., 2012; Wu et al., 2014), while especially the equipment integration
of the thermally-coupled process in terms of a dividing wall column (DWC)
offers additional investment savings. As both reboilers are maintained, possi-
ble energy savings should directly translate into operating cost savings, unless 28
condensation in the HAD column cannot be performed with cheap cooling
water (Wu et al., 2014). The absence of a vapor split for the DWC variant
of the HAD column makes it particularly interesting from the operational
point of view.
For direct heat integration (HI), the first column of the HAD process is op-
erated at elevated pressure, such that the top vapor stream can be used as
heat source for the reboiler of the HAD column. Similar to the ED process,
the separate heat exchangers connected by the dashed arrow are modeled as
single heat exchanger and additional heat exchangers are considered in order
to compensate for the difference between the condenser and reboiler heat
duty, as well as additional pre-heating of the feed stream to the first column.
Same as for the ED process, mechanical vapor recompression (VRC) enables
a partial or complete integration between the reboiler and condenser of each
individual column in the HAD process. The separate heat exchangers con-
nected by the dashed arrows are considered as single heat exchanger in the
optimization model, but are only considered present in the economic evalu-
ation in case the VRC system is actually utilized.
2.4. Solution procedure
The proposed approach is termed ”optimization-based design”, since all indi-
vidual problems in the solution procedure are solved as undetermined math-
ematical programming problems, especially considering the inequality con-
straints for the product specifications rather than any fixation of the design
degrees of freedom (such as energy duties, product streams or distillate-to-
feed ratios). As already mentioned, a polylithic modeling and solution ap-
proach (Kallrath, 2011) is applied, which allows for an automatic initializa29
tion and optimization of the different process configurations. The approach
builds on the topological analysis of the composition space and initial mass
balance calculations for the individual column of the basic process configura-
tions of ED and HAD illustrated in Fig. 1. By approximating the potential
product compositions of the individual columns, these are initialized con-
sidering flash calculations for linearized composition profiles. Subsequently
mass balances and enthalpy balances are added and the individual columns
are optimized for minimum energy duties, considering a fixed column size
with a maximum number of equilibrium stages. For both extractive and
heteroazeotropic distillation, the individual columns are than connected in
series (first to second), while depending on the specific process variant the
necessary modifications for heat and mass integration are performed. As the
last step of the automatic initialization procedure, the recycle streams are
closed and the energy duty is minimized once more for the final product spec-
ifications. Finally, all constraints on feed, reflux and boil-up locations are
relaxed and the process design is optimized for minimum TAC, for which the
additional sizing and costing models are added to the optimization model.
Figure 8: Automated initialization and solution procedure for ED and HAD processes
The sequence of steps in the polylithic modeling and solution approach are
summarized in Fig. 8. The developed solution procedure is a direct ex-
tension of the design approach for energy integration distillation sequences
(Waltermann and Skiborowski, 2019). The final mixed-integer non-linear
programming (MINLP) problem, which includes the integer decisions on the
number of equilibrium stages and feed positions, is solved as a series of suc-
cessively relaxed nonlinear programming (NLP) problems. This approach
proofed to result in improved robustness and numerical efficiency of the cal-
culations in previous design optimizations (Kraemer et al., 2009b; Kraemer
and Marquardt, 2010; Skiborowski et al., 2014, 2015a). As in the reformu-
lation of mathematical programming problems with equilibrium constraints,
additional nonlinear complementary constraints are added as penalty terms
in the objective function to ensure that integer values are obtained for the
relaxed binary variables (Skiborowski et al., 2015a).
For the problem definition, only the feed and product specifications as well as
the thermodynamic model and some specifications for initialization need to
be defined. The latter includes the maximum number of equilibrium stages
as well as initial guesses for feed locations and entrainer-to-feed ratio. Since
the resulting optimization problem is highly non-linear and non-convex, the
obtained solution is limited to a local optima. While current research activi-
ties are dedicated to extend the optimization approach in order to overcome
this limitation through an additional global search (Kruber et al., 2019), the
sensitivity of the applied optimization approach with respect to the initial
structure was checked for the subsequently addressed case studies, to check
for the possible entrapment in local solutions of poor quality.
3. Case Studies
In order to demonstrate the capabilities of the developed optimization-based
design method, its application is illustrated for three case studies in the sub-
sequent subsections. Setting up the problem specification and constraints
for the individual case studies requires only few modifications, providing a
general design method, as presented in Section 2. All computations have
been performed with GAMS V22.7.2., using SNOPT as NLP solver, on a
R stand-alone PC with an Intel CoreTM i7-7700 CPU with 3.6 GHz. Infor-
mation on the economic evaluation and the applied thermodynamic models
and parameters are provided in the Supplementary material.
3.1. Extractive distillation of methanol from a ternary mixture with acetoni-
trile and benzene
The first case study investigates the separation of methanol from a mix-
ture with acetonitrile and benzene, as considered by Zhu et al. (2016) and
Wang et al. (2018). The components in the mixture are representative of
common solvents in the chemical and pharmaceutical industry and the con-
sidered feed stream is a saturated liquid with a flow rate of 10 mol/s and
a composition of 25 mol-% acetonitrile, 10 mol-% benzene and 65 mol-%
methanol. The complex topology of this ternary mixture, which possesses
three binary azeotropes that separate the composition space into three dis-
tillation regions, impedes a direct methanol recovery by simple distillation,
as indicated in Fig. 9.
The objective of the process design study is to evaluate the cost-optimal de-
sign of an ED process, using chlorobenzene as a suitable MSA (Wang et al.,
Topology of ternary mixture of acetonitrile, benzene and methanol including
simple distillation boundaries and considered feed composition for first case study.
2018). The cost of the MSA is assumed to be 1000 $/t2 for the poten-
tial make-up stream. Methanol is to be recovered with a purity of at least
99.5 mol-% and a recovery of at least 99.5 %, while the mole fraction of
chlorobenzene in the distillate of the solvent recovery column shall also be
less than 0.01 mol-%. VLE calculations are based on the Wilson g E -model
in combination with the extended Antoine equation and DIPPR correlations
for the specific heat capacities and the enthalpy of vaporization. All param-
R eters are extracted from the Aspen Plus APV-V88 VLE-IG and PURE32
exchange rate of 0.8465 e$
database. Optimization-based design calculations are performed for the sim-
ple, as well as the HI, TC, DWC and VRC configurations, for which the
superstructures of the individual columns offer up to 80 equilibrium stages.
For the economic assessment a depreciation within 10 years is considered.
The HI ED process is identified as the cost optimal solution. The detailed
design of the HI ED process is depicted in Fig. 10. In order to exploit
the heat from the condenser of the second column for partial integration of
the reboiler of the first column, the second column is operated at 2.4 bar.
Thereby the external steam demand for column 1 is reduced by 38 %, while
additional 94.3 kW are required to preheat the feed to the second column to
saturation conditions. Overall, HI allows for the reduction of external heat
demand from 1008 kW to 803 kW, when compared to the simple ED process,
resulting in AOC savings of about 17 %.
However, overall TAC savings of just 2 % are obtained, due an increase in
AIC. Fig. 11 illustrates the cost distribution of the optimized simple and
energy-integrated ED processes. Further details for each of the process de-
signs are provided in the Supplementary material. While the results indicate
only little economic saving potential for the HI variant, the potential appli-
cation of VRC is not utilized as the potential energy savings are not high
enough to cover for the additional investment for the compressor. Moreover,
the thermal coupling in case of the TC and DWC variant results in even
higher costs as a higher steam grade has to be used. The latter is in agree-
ment with investigations of Wu et al. (2013), who evaluated DWC for ED
for several chemical systems and concluded that economic savings can only
be obtained for few certain cases.
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.
While only little improvements can be obtained by means of energy inte-
gration in case of this ED process, the optimization-based design method
enables the efficient evaluation of all process configurations. For all five pro-
cess configurations optimized designs were obtained within less than an hour
of computational time, without parallelization of the computations. Thus, a
quick evaluation of the saving potential is enabled based on a quantitative
evaluation of optimized process configurations.
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.
3.2. Dehydration of ethanol by ED and HAD
Alcohol and ethanol dehydration in specific are the most prominent exam-
ples for ED, as well HAD. Specifically the purification of bioethanol from
dilute fermentation broth is considered quite energy intensive (Singh and
Rangaiah, 2017). Consequently, Kiss and Suszwalak (2012) already inves-
tigated the saving potential of DWC designs for ED and HAD processes,
concluding that both processes enable energy savings compared to the non-
integrated processes. Considering the same pre-concentrated feed stream of
100 kmol/h with an ethanol fraction of 85 mol-%, the optimization-based
design approach is first applied to evaluate the different options for energy
integration for both ED and HAD. According to international standards and
as considered by Kiss and Suszwalak (2012), the bioethanol product has to 37
contain less than 2 wt-% water, translated to a purity of at least 99.5 mol-
%, while the water byproduct has to have a purity of at least 99.9 mol-%.
Ethylene glycol and cyclohexane are selected as preferred and established sol-
vents for ED and HAD respectively (Singh and Rangaiah, 2017). For both, a
price of 1000 $/t3 is considered for the potential make-up stream. The ther-
modynamic properties of both systems are modeled by the NRTL model in
combination with the extended Antoine equations and DIPPR correlations
R for the specific enthalpies, using parameters from the Aspen Plus APV-V88
VLE-IG and PURE32 database. For the economic assessment a depreciation within 3 years is considered.
Figure 12: Overview of cost distribution for the simple and energy-integrated optimized ED and HAD process designs for the dehydration of a pre-concentrated ethanol stream. 668
exchange rate of 0.8465 e$
Fig. 12 illustrates the cost distribution of the optimized simple and energy-
integrated ED and HAD processes. Obviously, the ED process configurations
are significantly less expensive than the HAD process, with the simple ED
process being the most economic choice for the given problem specifications.
Again, the compressor sections in the VRC variant are bypassed for both ED
and HAD. For the ED process, no HI design was derived, since the necessary
operating pressure for heat integration between both columns requires the
reboiler temperature of the second column to exceed the maximum tempera-
ture limit of 492 K, which was specified based on a limitation of the available
utilities. HI for the HAD results in almost the exact same TAC as the simple
variant, however, with a considerable shift between AIC and AOC. While for
the ethanol dehydration the economic advantage of the thermally-coupled
side rectifier over the thermally-coupled ED process are significant, the po-
tential benefit of the side-rectifier depends majorly on the contribution of
investment costs to the overall TAC values. Since for the other case studies,
the AIC contribute (significantly) less to the overall TAC than for the ethanol
dehydration, the expected economic advantages of the thermally-coupled side
rectifier over the thermally-coupled ED process are less pronounced and only
the thermally-coupled ED option is considered.
Similar to the previous case study, the TC and DWC options result in in-
creased costs for the ED process, particularly since both process need to use a
higher steam grade for their sole reboiler covering the total heat duty. For the
TC process as depicted in Fig. 6, the reboiler of the second column produces
the complete vapor stream that is split by the thermal coupling between the
first column and the second column’s rectifying section. Since the separation
in the extractive column is commonly more difficult than the solvent recovery,
the majority of the vapor will be transferred to the first column. However,
due to the large vapor load in the second column’s stripping section, the di-
ameter of the second column will be relatively large. While the consideration
of a constant column diameter might even result in hydrodynamic problems
in the rectifying section, moving the stripping section to the first column and
operating a thermally-coupled side rectifier (that corresponds to the second
column’s rectifying section) may also provide additional cost savings. The
potential of such a thermally-coupled side rectifier was further evaluated in
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.
ED process with
thermally-coupled side rectifier
While for the initial TC configuration both columns have similar diameters,
the side-rectifier configuration enables a significantly smaller column diame40
ter for the side rectifier, while the height of the first column HCol1 increases
due to the movement of the stripping section of the second column. However,
the AIC are significantly smaller for the side rectifier. Moreover, as the side
rectifier is optimized as an individual process, the optimization exploits the
reduced column diameter by means of an increased number of theoretical
stages in the individual sections, such that the overall energy demand and
the AOC are also reduced in the optimized process design. Overall, the TAC
of the thermally-coupled side rectifier is about 14 % smaller than the initial
TC option, so that this option becomes competitive to the extractive DWC.
However, for the considered case study the simple ED process is econom-
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
In contrast to the thermally-coupled and DWC options for extractive distil-
lation, TC and DWC allow for cost improvements of the HAD process (cf.
Fig. 12). This is again in agreement with the results of Wu et al. (2013, 2014)
who reported a larger potential of DWC for application in HAD. A detailed
comparison of the simple and DWC process options for ED is illustrated in
Despite the economic benefits of the simple process, it is important to note
that the DWC variant enables energy savings of about 6 %, being quite com-
parable to the 9 % energy savings reported by Kiss et al. (2012). Yet, the
shift of the complete energy provision to the highest temperature level in
the single reboiler, requires the use of high pressure steam, due to the high
boiling temperature of ethylene glycol. Thus, the possible energy savings
do not translate into cost savings in terms of AOC, as pointed out by Wu
et al. (2013). Moreover, though the dimensions of the single DWC shell are
comparable to the extractive column of the simple process, due to the more
complicated construction of the split-shell arrangement that is considered by
a surcharge factor of 20 % for the DWC, the savings in investment costs for
the DWC are also negligible, when comparing the AIC values of simple and
DWC variants of the extractive distillation process.
Interestingly the derived results change substantially based on the feed com-
position, as has been shown in our preceding work (Waltermann et al., 2017),
in which we investigated a feed of 10 mol/s with an ethanol content of just
6 mol-%, representative of an aqueous ethanol stream from fermentation
broth, without additional pre-concentration. In this case, for which the re-
sults of the optimization-based design are summarized in Fig. 14.
Figure 14: Annualized costs of different process variants for the dehydration of a diluted ethanol feed with 6 mol-% ethanol (Waltermann et al., 2017)
Obviously, the HAD process is for this problem specification significantly less
expensive than the ED process, whereas the DWC design of the HAD pro-
cess is the economically favorable choice. In order to further elucidate the
importance of the pre-concentration for the ED process, the optimization-
based design is performed for an adapted feed stream with an ethanol content
of 6 mol-% and a flowrate of 1416.7 kmol/h, which corresponds to the feed
stream considered by Kiss and Suszwalak (2012), prior the pre-concentration.
This feed flowrate results in a capacity of about 31000 t/a bioethanol, which
also corresponds well to other publications (Singh and Rangaiah, 2017). In
accordance with the previous results the simple ED and the DWC version
of the HAD process are investigated, while an additional beer column for
pre-concentration is considered as well for the ED process. The total heat 43
duties and the cost distribution for the three optimized process variants are
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
with pre-concentration free xpre D
xpre D = 0.85
Obviously the ED process with pre-concentration in the beer column results
in a much more economic design, compared to the simple ED process for the
modified feed specification. However, according to the optimization results
that consider all three columns simultaneously the preferred economic process
design performs a pre-concentration from 6 mol-% to 79.2 mol-% ethanol, in-
stead of the previously considered 85 mol-%. Specifying a pre-concentration
to 85 mol-% in the beer column results in a significant increases of the re-
quired energy demand and an overall increase in TAC from 1.56 Me/a to
1.78 Me/a. Despite the feed-forward connection of the pre-concentration
and the ED, there is a clear interdependency between both steps, such that
simultaneous optimization of the combined process is mandatory.
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
effect on the DWC version of the HAD process. While the optimized design
has about 10 % higher TAC compared to the ED process with beer column,
it is also only about 21 % more expensive compared to the previous design
for the pre-concentrated feed (cf. Figure 12).
Considering the cost of the pre-concentration and the beer column in the
ED design (TAC of 1.78 Me/a for the 85 mol-% case) it can be concluded
that the HAD process does not benefit from such separate pre-concentration,
while the HAD process is presumably also more flexible with respect to feed
fluctuations. The latter should be evaluated further based on a fixed design
and process performance evaluations, accounting for the operation limita-
tions of the selected internals and performance variations for variable gas
and liquid loads.
Since the computational times for each of the evaluated process variants did
not exceed 15 minutes, the complete case study can be evaluated in less than
4 h of computational time. This time could be reduced further through par-
allelization of the evaluations by means of simple multi-threading, given a
sufficient amount of licenses. The case study clearly demonstrates that the
proposed design approach can be used to efficiently evaluate ED and HAD
and potential means for energy integration for a specific separation problem
and variations in the problem specifications.
3.3. Separation of acetone and methanol by ED
The last case study investigates the separation of acetone and methanol by
means of ED with various MSA, similar to the preceding work of Kossack
et al. (2008) and Skiborowski et al. (2015b). However, the current investi-
gation includes the different means for energy-integration and evaluates the
effect on the preferred solvent choice. The considered saturated liquid feed
consists of an equimolar mixture of acetone and methanol with a flow rate of
540 kmol/h. The considered MSA candidates correspond to the selection of
Kossack et al. (2008) and are listed in Table 3 with their corresponding costs,
adopted from Skiborowski et al. (2015b). The thermodynamic properties are
calculated by the UNIQUAC g E model, the extended Antoine equations and
DIPPR correlations, for which the parameters are taken from the Aspen
R Plus APV-V88 VLE-IG and PURE32 database. Purity requirements for
both products are 99.5 mol-% and the plant is depreciated for a period of
As indicated in Figure 16, DMSO represents the most favorable solvent
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.
chlorobenzene 1000 $/t DMSO
cess. While its high boiling point mandates the use of high pressure steam,
the low energy requirement results in the overall lowest AOC, which for the
comparable high depreciation time determines largely the TAC.
Only the AOC of the water-based ED process are comparable, while chloroben-
zene results in considerably higher AOC and around 25 % higher TAC. The
TAC of the p-xylene and ethanol-based ED process are significantly higher,
being more than 50 % and 90 % more expensive compared to the DMSO-
based ED process. It has to be mentioned that despite the large price differ-
ences of the considered MSA, especially water, the solvent make-up stream
is negligible small, resulting in a maximum cost share of less than 2.4 % of
the TAC, also due to the high product purity specifications.
Based on these initial results it is further checked if the consideration of en-
ergy integration can alter this ranking, focussing on the first three solvents,
since energy savings of more than 50 % are highly unlikely. The results of
this evaluation are further summarized in Figure 17, for which the dashed
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
is discarded, since the reboiler temperature of the solvent recovery column
would exceed the maximum temperature limit of 492 K, which was specified
based on a limitation of the available utilities. The TC and DWC options are
both more expensive, since despite an overall reduced heat duty, the overall
AOC increase significantly due to the increased high pressure steam require-
ment, since all of the heat has to be supplied at the highest temperature of
Only the VRC option allows for slight savings of 2 % in TAC. However,
the VRC section is only utilized in the extractive distillation column, but
Figure 17: Economic results for the optimized energy-integrated ED processes for the separation of acetone and methanol with different MSA.
bypassed in the recovery column. In fact, despite the relatively high tem-
perature difference between reboiler and condenser of about 33 K for the
extractive column, the necessary compression can be performed with low
energy requirements and offers economic savings. For the recovery column,
however, the VRC offers no saving potential due to the very high temper-
ature difference of 126 K between reboiler and condenser. Altogether, the
potential AOC savings are, however, canceled mostly out by the increased
AIC for the required compressor.
For chlorobenzene, the results are comparable and none of the options for
energy integration apart from the VRC allows for TAC savings. As for the 49
DMSO-based process, the VRC option allows for a slight reduction of 9 % of
the TAC, which however does not suffice to outperform the DMSO process.
The situation looks quite different for the water-based ED process. While
the thermally-coupled process configurations also do not offer economic ben-
efits, both HI and VRC can significantly improve the economic performance,
even beyond the DMSO-based process. In fact, the HI process configura-
tion becomes the overall most attractive process, being 21 % less expensive
than the simple DMSO-based process. Thus, it has to be concluded that the
consideration of energy integrated process concepts can effectively alter the
results of the solvent screening.
Besides the economic saving potential, water offers additional benefits, being
sustainable, non-toxic and extremely cheap. The comparably big impact of
energy integration for the water-based ED process stems from the compara-
bly low boiling point of water, which on the one hand enables the use of low
pressure stream and on the other hand results in smaller temperature differ-
ences between the different heat exchanger’s that are to be integrated. The
process design of the optimized HI ED process with water is depicted in Fig-
ure 18. Allowing for the integration of around 6 MW, it reduces the external
heat duty by 39 % compared to the simple ED process. Consequently, MSA
selection should be performed with the additional consideration of energy
Figure 18: Detailed design of HI ED as optimal process variant for case study 3
The case study illustrates that energy integration should not be considered
as a final post-processing step for the best solvent choice for non-integrated
processes, but rather be included in the solvent screening. While feasibility
criteria can be considered for a pre-evaluation of suitable solvents, the final
solvent screening should be performed on the basis of the optimized process
design, since the complex interactions between solvent properties, process
performance and energy integration potential cannot be depicted by simple
The design of extractive and heteroazeotropic distillation processes is a chal-
lenging task, which requires the correct identification of a mass separating
agent, as well as the optimization of an integrated closed-loop process, consid-
ering the primary separation and solvent recovery. On top of that, different
means for energy integration can be considered, which can very well alter the
results in terms of optimal solvent choice and process selection. While sol-
vent selection and process design are nowadays supported by computational
tools, there are still distinct limitations that need to be resolved in order to
determine the best solvent and process combination. MSA selection is usu-
ally focussed on simplified criteria, which are important for pre-screening but
should not determine the final choice, whereas process simulators oftentimes
lack the necessary capabilities for process optimization and require a tedious
initialization and optimization approach, relying to a large extend on manual
tuning and expert knowledge. The potential of energy integration is rarely
evaluated for more than the finally selected solvents.
The presented optimization-based method for the design of extractive and
heteroazeotropic distillation processes overcomes the problems related to the
use of commercial process simulators and enables a direct evaluation of dif-
ferent means for energy integration for multiple solvents. The capabilities of
the presented design approach are illustrated for three different case stud-
ies, highlighting different features of the proposed method. The application
for the separation of methanol from the ternary mixture with acetonitrile
and benzene by extractive distillation with chlorobenzene shows that the
design method is can be applied to multi-azeotropic mixtures with four or 52
even potentially more components. The ethanol dehydration case study il-
lustrates how effective extractive and heteroazeotropic distillation processes
with potential energy-integration can be evaluated and compared for varying
problem specifications. Finally, the separation of the acetone and methanol
mixture illustrates the potential for an integrated evaluation of solvent se-
lection and energy integration. It further highlights the advantages of such
a simultaneous consideration in determining the optimal process design.
As presented for the case studies, the approach facilitates a computationally
efficient quantitative comparison of the different process concepts for specific
separation problems and enables a detailed analysis of the benefits and lim-
itations of these process concepts through modification of feed and product
specifications. While the results of the case studies validate previous results
for the concept of dividing wall columns in extractive and heteroazeotropic
distillation, reported by Wu et al. (2013, 2014), the presented design method
enables an efficient evaluation of the potential and the comparison with al-
ternative means for energy integration. It provides an important computa-
tionally efficient tool for the integration of solvent and process design, which
is mandatory for the evaluation of a multitude of solvent candidates, which
cannot rely on manual initialization and optimization.
Future work will investigate the utilization of the current approach for com-
puter aided solvent screening and design, as in the work of Kruber et al.
(2018), exploring the already indicated potential for parallelization of the
required computations. Furthermore, in order to overcome the potential en-
trapment in sub-optimal local solutions of the highly nonlinear mixed-integer
optimization problems, the extension of the optimization approach to a hy-
brid stochastic deterministic approach (Skiborowski et al., 2015b) is also
under current investigation (Kruber et al., 2019). At last, an extension of
the considered process concepts, including concepts such as internally heat-
integrated distillation-columns (Harwardt and Marquardt, 2012) or combi-
nations of the different concepts (Jana, 2019), as well as a potential energy
integration with a background process will be explored as well.
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Conflict of Interest
The authors declare that they have no known competing financial interests
or personal relationships that could have appeared to influence the work
reported in this paper.
Thomas Waltermann: Conceptualization, Methodology, Software, Investi-
gation, Visualization, Writing Original Draft. Tamara Grueters: Method-
ology, Software. Daniel Muenchrath: Methodology, Software. Mirko
Skiborowski: Conceptualization, Methodology, Supervision, Project ad-
ministration, Writing Review & Editing.