A novel synthesis of ditrimethylolpropane biphosphoramide ...
Process Synthesis and Global Optimization of Novel ......Process Synthesis and Global Optimization...
Transcript of Process Synthesis and Global Optimization of Novel ......Process Synthesis and Global Optimization...
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ProcessSynthesisandGlobalOptimizationofNovelAmmonia
ProductionProcesses
C.Doga Demirhan1,2,WilliamW.Tso1,2,Efstratios N.Pistikopoulos1,21.ArtieMcFerrinDepartmentofChemicalEngineering
2.TexasA&MEnergyInstitute
November2,2017
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AIChE AnnualMeeting,Minneapolis,MN
§ Worldpopulationisexpectedtoreach8.6billionby2035and9.4billionby2050andtheworldGDPwilldouble!
§ Ammoniawillcontinuetobeproducedandusedinextensiveamounts.
§ Biomassisanenvironmentallyfriendlyalternativehydrogensourcetonaturalgas withnonetCO2 emissions
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Introduction&Motivation
NRELGeospatialDataScienceReport,2014
365milliontons/yearofsolidbiomasswasavailablein2015!
Possible>1billiontons/yearwillbeavailableby2040!
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USCensusBureau, USGeologicalSurvey,WorldBank,USEIA
USDOE,2016Billion-TonReportEIAMonthlyEnergyReview,Sept2017
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AIChE AnnualMeeting,Minneapolis,MN
Aim1: Mathematicalmodelingoftheprocessesinfossil- and/orrenewablefuel-based(hybridfuel)ammoniaproductionprocesses
§ Developadata-drivenmodelforammoniaconverter§ Presentmodelsforprocessalternativesforsyngasgeneration,syngascleaning,andammoniasynthesisloopsections
Aim2: Processsynthesisandglobaloptimizationofammoniaproductionprocesses
§ Incorporateallprocessalternativesinaprocesssuperstructurewithsimultaneousheat,power,andwaterintegration
§ Applyglobaloptimizationmethodstofindthegloballyoptimaltopologiesfordifferentfeedstockavailabilities,greenhousegasemissionreductions,andplantscales
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AimsofthisWork
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AIChE AnnualMeeting,Minneapolis,MN
Challengesofbuildingdata-drivenmodels:§ Howtofindthebestfittingmodel?§ Whichtermsshouldbeincludedinthemodel?§ Overfitting?
Oursolution:§ Wepreparedtrain/validation/test sets§ 5-fold cross-validation approachisappliedtocreate5models§ These5modelsaretestedwithnewdata(testset)§ Belowarethescatteredresultsofanexampletrain/validation/testwith55totalpoints(40-10-5)
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AmmoniaConverterModeling
Conversion = β+ +-β.
�
.
x.
Quadraticpressuretermisfoundtobe
insignificant!
Additionofquadratictermsof
temperatureandpressureresultedin
overfitting!
Linearmodelisselected!
Nowwecanmoveontotheprocessalternatives!
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AIChE AnnualMeeting,Minneapolis,MN11/2/17
NaturalGas-BasedAmmoniaProduction
PrimaryReforming
SecondaryReforming
Water-Gas-Shift
SyngasPurification
AmmoniaSynthesis
Water
AirRecycle
Ammonia
PurgeCarbondioxideCompression
Oxygen
AirSeparationUnit
Nitrogen
Air
Nitrogen
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Natural gasSyngas
AmmoniaSynthesisGas
H2-richSyngas
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AIChE AnnualMeeting,Minneapolis,MN11/2/17
Biomass-BasedAmmoniaProduction
Water-Gas-Shift
SyngasPurification
AmmoniaSynthesis
AirRecycle
Ammonia
PurgeCarbondioxideCompression
BiomassGasificationBiomass
- Switchgrass- Hardwood- CornStover- MunicipalSolidWaste
Oxygen
AirSeparationUnit
Nitrogen
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SynGasCleaning
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Carbondioxide
CleanBio-Syngas
AmmoniaSynthesisGas
H2-richSyngas
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AIChE AnnualMeeting,Minneapolis,MN
§ Processsynthesisproblemisalarge-scalenonconvexmixed-integernonlinearoptimization(MINLP)problem
§ Binaryvariablesareusedfortechnology/reactortypeselection§ Modelincludes:
§ Mass&energybalanceequations§ Thermodynamicrelations(phaseandchemicalreactionequilibria)§ Simultaneousheatandpowerintegration§ Concavecostfunctionsforcalculationofunitinvestmentcosts
§ Nonlinearitycomesfromthefollowingterms:§ Bilinear: equilibriumreactors,splitters,flashcalculations,streamcompositions,etc.§ Trilinearandquadrilinearterms: Thermodynamicsandequilibriumcalculations
§ Objectivefunctionisminimizingthelevelizedcostofammoniaproduction:
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OptimizationProblem
MIN - Cost5667 + Cost6869:;.9.:< + Cost=>?A6BC6A:;D:.EF − CostHIJ + - CostCF.:A
�
C∈LMNO
�
5∈P667
TDC = (1 + BOP)C+SS+
A5
xC,CO,A[ − KC,A]H^ _ xC,C`,A
[ = 0
xC,C`,A[ _ NC,C`
b − NC,C`,A[ = 0
xC,Cc,=>[ _ xC,Cc,d?[ e − KC[f _ xC,Cc,=dg
[ _ xC,Cc,d?>[ = 0
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AIChE AnnualMeeting,Minneapolis,MN
§ Weuseatailoredbranch-and-boundalgorithmcombinedwithadvancedterm-basedrelaxationtechniquestosolvetheproblemtoglobaloptimality.
§ Piecewiselinearunderestimatorsareusedwithlogarithmicpartitioningscheme.
§ TheproblemisdecomposedintoanMILPlowerboundandanNLPupperboundproblem.
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GlobalOptimizationAlgorithm
§ Feasibility- andoptimality-basedboundstightening(FFBTandOBBT)methodsareusedtoobtaingoodqualitybounds.
§ Branchingisdoneonthevariablewiththelargestrelaxationerror.
§ Theaimisthegetasolutionwithinafewpercentofthebestpossiblevalue.
MINLP
MILP
NLP
SolvetheMILPtogetalowerboundsolution(LB)
SolvetheNLPtogetanupperboundsolution(LB)
(LB-UB)/UB<ε-RelativeTolerance
Yes
No
Fixthebinaries!
BranchonvariablesandsolveOBBTtogetnewbounds!
Relaxtheproblem!
Globaloptimalityistheoreticallyguaranteed!
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AIChE AnnualMeeting,Minneapolis,MN
§ Adata-drivenmathematicalmodelisdevelopedforammoniaconverter§ Aprocesssuperstructureissynthesizedandmodeledforbiomass-basedammoniaproductionandsolvedtoglobaloptimality
§ Casestudiesshowedthatforsingletypeoffeedstock:§ Ammoniaproducedfromhardwoodtypebiomasshadthelowestbreak-evenpriceofammoniawith50%reductioninGHGemissionsbeingpossible
§ Atsmallerplantsize,NG-basedproductionhaslowerbreak-evenprice;astheplantsizebecomeslarger,biomass-basedprocesshasthelowestbreak-evenprice
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Conclusions
Acknowledgements