26 European Symposium on Computer Aided Process Engineering

588 Pages·2016·82.056 MB·English

by  Zdravko Kravanja and Miloš Bogataj (Eds.)

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Preface

These proceedings contain contributions presented at the 26th European Symposium on
Computer Aided Process Engineering (ESCAPE 26) held in Portorož, Slovenia from the
12th to 15th of June 2016.

ESCAPE 26 is the 26th edition of ESCAPE series. Previous editions were held in
Denmark (1992, 2001, 2015), France (1992, 2008), Austria (1993), Ireland (1994),
Slovenia (1995), Greece (1996, 2011), Norway (1997), Belgium (1998), Hungary
(1999, 2014), Italy (2000, 2010), The Netherlands (2002, Finland (2003, 2013),
Portugal (2004), Spain (2005), Germany (2006), Romania (2007), Poland (2009) and
United Kingdom (2012).

The ESCAPE series is a prominent European yearly event in the field of Computer
Aided Process Engineering (CAPE) bringing together people from around the world
dedicated to Process Systems Engineering. Scientists, industrial experts, academics and
students exchange and share the most recent knowledge about CAPE concepts,
methods, tools and applications, either regarding continuous developments of existing
technologies or innovative developments of new ones based on new discoveries and
inventions.

The ESCAPE 26 focused on themes: Process-product Synthesis, Design and
Integration; Modelling, Numerical Analysis, Simulation and Optimization; Process
Operations and Control; Green Bioprocess Engineering and Advances in Biomedical
Engineering; CAPE/PSE in Environmental Engineering; CAPE/PSE in Sustainable
Energy Applications; CAPE Applications; and Education in CAPE/PSE.

Out of 406 contributions, prepared by authors from 47 countries (Europe, the Americas,
Africa, Asia and Australia), the ESCAPE 26 International Scientific Committee selected
176 oral presentations, 7 being plenary lectures, 18 keynote lectures, and 230 poster
presentations.

We beleive that the contributions contained in these proceedings will serve as a
reference and motivate new ideas, developments and collaborations in the field of
computer aided process engineering and beyond.

Yours sincerely,
Zdravko Kravanja Miloš Bogataj
Conference Chair Conference Secretary
International Scientific Committee
Conference Chairman
Zdravko Kravanja, University of Maribor, Slovenia

Themes Coordinators
Process-product Synthesis, Design and Integration
Mariano Martin, University of Salamanca, Spain

Modelling, Numerical analysis, Simulation and Optimization
Stratos Pistikopoulos, Texas A&M University, USA

Process Operations and Control
Sebastian Engell, TU Dortmund University, Germany

Green Bioprocess Engineering and Advances in Biomedical Engineering
David Bogle, University College London, UK

CAPE/PSE in Environmental Engineering
André Bardow, RWTH Aachen University, Germany

CAPE/PSE in Sustainable Energy Applications
Petar Varbanov, Pázmány Péter Catholic University, Hungary

CAPE Applications
Flavio Manenti, Politecnico di Milano, Italy

Education in CAPE/PSE
Antonio Espuña, Universitat Politecnica de Catalunya, Spain

Members
Mariano Martin, University of Salamanca, Spain
Thomas Adams, McMaster University, Canada
Mario Eden, Auburn University, USA
Fengqi You, Northwestern University, USA
Michael Fairweather, University of Leeds, UK
Antonis Kokossis, National Technical University of Athens, Greece
Rafiqul Gani, Technical University of Denmark, Denmark
Andrzej Kraslawski, Lappeenranta University of Technology, Finland
Jose Caballero, University of Alicante, Spain
Gonzalo Guillén-Gosalbez, The University of Manchester, UK
Stratos Pistikopoulos, Texas A&M University, USA
Marianthi Ierapetritou, Rutgers University, USA
Andreja Nemet, University of Maribor, Slovenia
xxviii International Scientific Committee

Ruth Misener, Imperial College London, UK
Alexander Mitsos, RWTH Aachen University, Germany
Michael Georgiadis, Aristotle University of Thessaloniki, Greece
Lazaros Papageorgiou, University College London, UK
Vivek Dua, University College London, UK
Chrysanthos Gounaris, Carnegie Mellon University, USA
Pei Liu, Tsinghua University, China
Benoit Chachuat, Imperial College London, UK
Carl Laird, Purdue University, USA
Nikolaos Sahinidis, Carnegie Mellon University, USA
Hermann Feise, BASF, Germany
Davide Manca, Politecnico di Milano, Italy
Moisès Graells, Universitat Politècnica de Catalunya, Spain
Sebastian Engell, TU Dortmund University, Germany
Ana Barbosa-Póvoa, Técnico Lisboa, Portugal
Luis Puigjaner, Universitat Politecnica de Catalunya, Spain
Gintaras Reklaitis, Purdue University, USA
Sigurd Skogestad, Norwegian University of Science and technology, Norway
David Bogle, University College London, UK
Paul Agachi, Kazakh British Technical University, Kazakhstan
Andreas Linninger, University of Illinois at Chicago, USA
Ioannis Androulakis, Rutgers University, USA
Costas Kiparissides, Aristotle University of Thessaloniki, Greece
Francois Marechal, École polytechnique fédérale de Lausanne, France
Tony Kiss, AkzoNobel, The Netherlands
Filip Logist, University of Leuven, Belgium
Michael Narodoslawsky, Graz University of Technology, Austria
André Bardow, RWTH Aachen University, Germany
Jiří Klemeš, Pázmány Péter Catholic University, Hungary
Peter Mizsey, Budapest University of Technology and Economics, Hungary
Fabrizio Bezzo, University of Padova, Italy
Ferenc Friedler, University of Pannonia, Hungary
Niall Mac Dowell, Imperial College London, UK
Petar Varbanov, Pázmány Péter Catholic University, Hungary
Hon Loong Lam, The University of Nottingham Malaysia Campus, Malaysia
Zainuddin A. Manan, University of Technology, Malaysia
Sharifah Rafidah Wan Alwi, University of Technology, Malaysia
Raymond Girard R. Tan, De la Salle University, Philippines
Petro Kapustenko, Kharkiv Polytechnic Institute, Ukraine
Igor Bulatov, The University of Manchester, UK
Panos Seferlis, Aristotle University of Thessaloniki, Greece
Sakis Papadopoulos, Centre for Research and Technology Hellas, Greece
Tomislav Novosel, University of Zagreb, Croatia
Franjo Cecelja, University of Surrey, UK
Hella Tokos, University of Surrey, UK
International Scientific Committee xxix
Niyi Isafiade, University of Cape Town, South Africa
Michael Walmsley, The University of Waikato, New Zealand
Flavio Manenti, Politecnico di Milano, Italy
Tilman Barz, Austrian Institute of Technology, Austria
Mattia Vallerio, University of Leuven, Belgium
Guido Buzzi-Ferraris, Politecnico di Milano, Italy
Massimiliano Barolo, The University of Padova, Italy
Soledad Diaz, Planta Piloto de Ingeneria Quimica, Argentina
Christos Maravelias, University of Wisconsin, USA
Alessio Frassoldati, Politecnico di Milano, Italy
Chi Wai Hui, The Hong Kong University of Science and Technology, China
Rubens Maciel Filho, University of Campinas, Brazil
Antonio Espuña, Universitat Politecnica de Catalunya, Spain
Il Moon, Yonsei University, South Korea
Henrique Matos, Técnico Lisboa, Portugal
Zorka Novak Pintarič, University of Maribor, Slovenia
Emilia Kondili, Technological Education Institute of Piraeus, Greece
Valentin Plesu, Polytechnic University of Bucharest, Romania
Iqbal Mujtaba, University of Bradford, UK
Elvis Ahmetović, University of Tuzla, Bosnia and Herzegovina
Dimitrios Gerogiorgis, The University of Edinburgh, UK
Lidija Čuček, University of Maribor, Slovenia
Alexandra Elena Bonet-Ruiz, Polytechnic University of Bucharest, Romania
Jordi Bonet-Ruiz, University of Barcelona, Spain
Ignacio Grossmann, Carnegie Mellon University, USA
Iiro Harjunkoski, ABB Corporate Research, Germany
Lorenz Biegler, Carnegie Mellon University, USA
Pedro Castro, University of Lisbon, Portugal
Carlos Mendez, National University of Litoral, Argentina
Cesar de Prada, University of Valladolid, Spain
Ton Backx, Eindhoven University of Technology, Netherlands
Claudio Scali, University of Pisa, Italy
Rajagopalan Srinivasan, Indian Institute of Technology Gandhinagar, India
Nilay Shah, Imperial College London, UK
Peter Singstad, Cybernetica AS, Norway
Stefan Kraemer, TU Dortmund University, Germany
Igor Plazl, University of Ljubljana, Slovenia
Xavier Joulia, ENSIACET, France
Jean-Marc Le Lann, ENSIACET, France
Jan Thullie, Silesian University of Technology, Poland
Luis Cisternas, University of Antofagasta, Chile
Sauro Pierucci, Politecnico di Milano, Italy
Vladimir Mahalec, McMaster University, Canada
Local Organising Committee
Chairman
Zdravko Kravanja, University of Maribor, Slovenia

Conference Secretary
Miloš Bogataj, University of Maribor, Slovenia

Members
Igor Plazl, University of Ljubljana, Slovenia
Neven Duić, University of Zagreb, Croatia
Zorka Novak Pintarič, University of Maribor, Slovenia
Mojca Slemnik, University of Maribor, Slovenia
Andreja Nemet, University of Maribor, Slovenia
Lidija Čuček, University of Maribor, Slovenia
Zdravko Kravanja, Miloš Bogataj (Editors), Proceedings of the 26th European Symposium on
Computer Aided Process Engineering – ESCAPE 26
June 12th -15th, 2016, Portorož, Slovenia © 2016 Elsevier B.V. All rights reserved.
http://dx.doi.org/10.1016/B978-0-444-63428-3.50005-9
Modelling and iterative Real-time Optimization of a
homogeneously catalyzed hydroformylation process
ReinaldoHerna´ndezandSebastianEngell
ChairofProcessDynamicsandOperations,TechnischeUniversita¨tDortmund,
Emil-Figge-Strasse70,Dortmund44227,Germany
{reinaldo.hernandez,sebastian.engell}@bci.tu-dortmund.de
Abstract
Inthiscontribution,thereal-timeoptimization(RTO)ofanovelmultiphasehomogeneouslycat-
alyzedprocessisinvestigated. Specifically,theconversionoflongchainolefinsisstudiedforthe
exampleofthehydroformylationof1-dodecene. Afirstprinciplemodelwasbuiltandvalidated
withexperimentaldataavailablefromaminiplant. Aniterativeoptimizationschemeisproposed
inordertoensureconvergence totheplantoptimuminpresenceofmodeluncertainties. Local
quadraticapproximationcombinedwithderivative-freeoptimizationisusedfortheestimationof
theplantgradientsunderpresenceofnoisymeasurements.Thesimulationresultsshowsignificant
improvementsintheeconomicperformanceoftheprocessdespitemodeluncertaintiesconcerning
thegassolubilityandtheamountofactivecatalystinsolution.
Keywords:real-timeoptimization,homogeneouscatalysis,modifieradaptation.
1.Introduction
Thehighselectivityandactivityatmildconditionsthatcanbeachievedbymeansofhomogeneous
catalysishavemotivatedsignificantresearch,aswellasthedevelopmentofimportantindustrial
applications,wherethehydroformylationofpropeneintheRuhrchemie/Rhone-Poulencprocess
(RCH-RP)isthebestknownexample(Frey,2014). Theprocessingoflongchainedolefinispar-
ticularlychallengingduetotheirlowsolubilityinthepolarcatalystphase.Novelprocessconcepts
havebeendevelopedduringthelastyearsinordertoovercometheselimitations,includingtheuse
ofcomplexsolventsystemswhichareabletoperformthereactionhomogeneouslyathightem-
peratures,whileatalowtemperaturethemixtureseparatesintotwophasesandefficientcatalyst
recoveryispossibleinsuchaThermomorphicMulticomponentSolvent(TMS)System(Brunsch
andBehr,2013).
Fortheeconomicsuccessofthistechnology,minimizingcatalystleachingwhileachievinghigh
conversionandselectivityoftheprocessarecrucial. Processoptimizationcanbeappliedbased
on kinetic models and thermodynamic descriptions of the phase equilibrium (Hentschel et al.,
2015;Schaferetal.,2012). Inthiscontribution,optimaleconomicaloperationofahydroformy-
lationprocesshasbeenaddressedbymeansofReal-timeOptimization(RTO).Inthisapproach
the problem is decomposed hierarchically: an upper layer uses a rigorous static model to de-
termine the optimal set-points that are tracked by a lower layer operating at a higher sampling
frequency(Darbyetal.,2015).
However,duetomodelinaccuracies,thiswillnotleadtoanoptimaloperationoftherealplant.We
proposetheuseofaniterativeReal-timeOptimizationscheme(GaoandEngell,2005)tooptimize
thedosingofthecatalystandthereactiontemperatureinpresenceofmodel-plantmismatch.The
2 R.Herna´ndez andS.Engell
Figure1:Left:ThermomorphicMulticomponentSolvent(TMS)system.Right:Reactionnetwork
ofthehydroformylationof1-dodecene.
algorithmemployedheremakesuseofalocalquadraticapproximationfortheestimationofthe
plant gradients which leads to reduced sensitivity to measurement noise (Gao et al., 2015). In
addition,atrustregionframeworkisappliedtoavoidoscillations.
This contribution is structured as follows: section two describes the integrated process for the
hydroformylationof1-dodeceneinaThermomorphicMulticomponentSolvent(TMS)systemand
insection3themodelispresented. SectionfourgivesageneraloverviewoftheproposedRTO
scheme.Finally,inthesectionsfiveandsixtheresultsandthemainconclusionsarepresented.
Acknowledgment: ThisworkwassupportedaspartoftheCollaborativeResearchCenter: ”In-
tegratedChemicalProcessesinLiquidMultiphaseSystems”(SFB/Transregio63InPROMPT)by
theDeutscheForschungsgemeinschaft(DFG).
2.ProcessDescription
InFigure1,thediagramofaTMSsystemisshown. Aswasstatedintheintroduction,theidea
is to use a predefined mixture of a nonpolar solvent (solvent 1) and a polar solvent (solvent 2)
suchthatathightemperaturesthesystemishomogeneous; thereforethelimitationsinthemass
transferofthereactanttothecatalystphaseareavoided. Atlowtemperatures,phaseseparation
takes place, and the expensive catalyst in the polar phase can be recovered and recirculated to
the reactor while the product in the nonpolar phase goes to further purification steps (Brunsch
andBehr,2013).TheTMSconcepthasbeenalreadyappliedtodifferenthomogeneouscatalyzed
reactions, includingthehydroformylationoflongchainalkenes. Theprocessconcepthasbeen
proveninacontinuouslyoperatedminiplantatTUDortmund(Zagajewskietal.,2015). Besides
themainreactioncorrespondingtotheproductionofthelinearaldehyde(tridecanal),isomeriza-
tiontoiso-dodecene,hydrogenationtododecaneandformationofbranchedaldehydetakeplace;
asisshowninthereactionnetwork(Figure1). Highselectivityatmildconditions(90◦Canda
syngas pressure of 20 bar) has been achieved by using a catalyst-ligand complex consisting of
theprecatalystRh(acac)(CO) andtheligandbiphephos. Assolventsystem,amixtureofthepo-
2
lar solvent dimethylformamide (DMF) and the nonpolar solvent decane was used. The cost of
rhodiumandligandmakesthecatalystrecoverycrucialforthesuccessoftheprocessconcept.
3.ModelDescription
Afirstprinciplesmodelfortheintegratedoperationofthereactoranddecanterispresentedinthis
section.
3.1.Reactormodel
ThereactorismodelledasanidealCSTR,andtwo-filmtheoryisusedfordescriptionofthemass
transferbetweenthegasandtheliquidphases. Accordingtothematerialbalance,theconcentra-
ModellinganditerativeReal-timeOptimizationofahomogeneouslycatalyzed
hydroformylationprocess 3
tionofthedifferentliquidcomponentsC (i=1-dodecene,tridecanal,dodecane,etc)isgivenby
i
equation(1). M isthemassofactivecatalystinthereactorandV isthereactorvolume. The
cat R
inflowandoutflowvolumetricflowratesaregivenbyV˙in andVo˙ut,whileνi,l arethecoefficients
ofthestoichiometricmatrixandr isthereactionrateforthereactionl. Theinterestedreaderis
l
referredtotheliteratureforthekineticmodel(Hentscheletal.,2015).
VRddCti =V˙in·Ci,in−Vo˙ut·Ci,out+McatN∑reactνi,l·rl (1)
l=1
Forthe jgascomponents(j=COandH ),theconcentrationintheliquidphasedependsonthe
2
masstransfercoefficient(k )andtheequilibriumconcentrationattheinterface(Ceq):
eff
ddCtj =−keff·(Cj−Ceqj)+V˙in·Cj,in−Vo˙ut·Cj,out+McatN∑reactνj,l·rl. (2)
l=1
TheGLequilibriumismodelledbymeansofHenry’slaw(3),whichdescribestherelationbetween
theliquidconcentrationstothepartialpressureP.ThedependenceoftheHenrycoefficientH on
j j
thereactiontemperatureT ismodelledbyanArrheniusexpression(4).
P =Ceq ·H (3)
j j j
(cid:2) (cid:3)
−E
Hj=Hj,0·exp RTj (4)
Aswasstatedinequation(1)thereactionrateisproportionaltothemassofactivecatalystand
thereforeproportionaltoitsconcentrationC .Athighcarbonmonoxideconcentrations,catalyst
cat
deactivationtakesplacebyformationofinactiveRh-dimers. Thisphenomenonhasbeenapprox-
imatelyquantifiedaccordingtoequation(5),wheretheactivecatalystconcentrationisexpressed
asafunctionoftheconcentrationofcatalystprecursorCRh,precursorandtheequilibriumconstants
Kcat,1andKcat,2:
C = CRh,precursor . (5)
cat 1+Kcat,1·CCO+Kcat,2·CCO/CH2
3.2.Decantermodel
LLEisassumedbetweenthephasesinthedecanter. Simpleexpressionsoftheequilibriumcon-
stantK asafunctionofthedecantertemperatureT areused:
i decanter
(cid:4) (cid:5)
Ki=exp Ai,0+TAi,1 +Ai,2Tdecanter , (6)
decanter
whereAi,0,Ai,1 andAi,2 wereobtainedbyregressionofexperimentaldata(Schaferetal.,2012).
Thesplitfactorζiandthemolarflowofthecomponentsintheproductstream(ni,product)andthe
catalystrecycle(ni,catalyst)asafunctionoftheinletflowtothedecanter(ni,decanter)canbedefined
accordingto(7)-(9):
K
ζ= i , (7)
i 1+K
i
ni,product=ζi·ni,decanter, (8)
ni,catalyst=(1−ζi)·ni,decanter. (9)
Based on experimental data, expressions similar to (7)-(9) are used for the description of the
catalystleaching.
4 R.Herna´ndez andS.Engell
4.IterativeReal-timeOptimization
4.1.Problemformulation
InRTO,thesolutiontothestaticoptimizationproblem(10)isaddressed:
min φ(u) (10a)
u
s.t. G(u)≤0, (10b)
whereustandsforthesetofinputs/degreesoffreedomwhichminimizethecostfunctionφ(u).
G(u) is the vector of constraint functions which includes the model equations and the process
constraintsthatmustbesatisfied.Duetomodellinginaccuraciesanddisturbances,thevalueofthe
costfunctionandconstraintsfortheactualprocess(φ(u)andG respectively)willbedifferent
p p
fromthemodel.Asaconsequence,thesolutionoftheproblem(10)canleadtoasuboptimalorto
anunfeasibleoperatingpoint.
Iterativeoptimizationaddressesthemodel-plantmismatchbyamodificationoftheproblem(10)
withcorrectiontermsthatrepresenttheactualvaluesoftheobjectivefunctionandconstraintsas
well as their gradients. In each iteration k, the problem (11) is solved and a new input uk+1 is
computed(GaoandEngell,2005).
(cid:2) (cid:3) (cid:2) (cid:3)
T
min φ(uk+1)+φp(uk)−φ(uk)+ ∇φp(uk)−∇φ(uk) uk+1−uk (11a)
uk+1 (cid:2) (cid:3) (cid:2) (cid:3)
T
s.t. G(uk+1)+GP(uk)−G(uk)+ ∇Gp(uk)−∇G(uk) uk+1−uk ≤0. (11b)
Thealgorithmensuresconvergencetotheoptimalpointundermodeladequacyconditions(Chachuat
etal.,2009).
4.2.Estimationofthegradientsandquadraticapproximation
Themostimportantissueintheapplicationofiterativeoptimizationistheestimationofthegradi-
entsundernoisyconditions.Differentapproachescanbefoundintheliterature,includingamong
others, nested modifier-adaptation (Navia et al.,2013) and dual-modifier adaptation (Marchetti,
2015). Inthiswork,localquadraticapproximationoftheplant,asproposedbyGaoetal.(2015)
incombinationwithatrustregionframework(Biegleretal.,2015)isapplied. Thequadraticap-
proximationcanbeconsideredasareducedmodel(RM)ofthetrueplantmodel,whiletheoriginal
detailedmodel(ODM)istheplantitself.
Giventhenumberofinputsn ,theideaofquadraticapproximationistoconstructalocalquadratic
u
modelofthecostfunctionandtheconstraintsoftheplantbasedonatleastn =[(n +1)(n +
r u u
2)/2−1] regression pointsU ={u(cid:6)k,uk−1,...,uk−nr(cid:7)+1}. The problem is reduced to finding the
valuesofthesetofparametersθ:= ai,j,...,bi,...,c whichminimizethesquareoftheestimation
errors,accordingtoproblem(12):
(cid:2) (cid:3)
min ∑nr φp(uk−i+1)−φq(uk−i+1,θ) 2 (12a)
θ
i=1
s.t. φq(uri,θ)=∑nu ∑nu ai,juiuj+∑nu biui+c, (12b)
i=1j=1 i=1
Aftertheproblem(12)hasbeensolved,thegradientsareestimatedusingthequadraticapproxima-
tionoftheobjectivefunction(φ ≈φ)andtheoptimizationproblem(11)issolved.Anadditional
q p
constraintisintroducedtotheproblem(11)whichrepresentsboundsontheinputssuchthatthey
staywithinthetrustregion. Thetrustregionisupdatedineachstepandthealgorithmisrepeated
untilconvergence.