Post-Combustion Processes Employing Polymeric Membranes 21. 06. 2011 / Frankfurt Torsten Brinkmann a , Thorsten Wolff a , Jan-Roman Pauls b a: Institute of Polymer Research b: Institute of Materials Research 2 nd International Conference on Energy Process Engineering Efficient Carbon Capture for Coal Power Plants June 20 - 22, 2011 in Frankfurt/Main, Germany
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Comp. pilot plant/simulationProcess simulation/design
4
Contents
Introduction Permeation data and membrane production Membrane module model Pilot plant experiments Process simulation Upscaling aspects Conclusions
5
Membrane Data - Laboratory Scale
1. A. Car er al., Adv. Funct. Mater. 18 (2008) 2815-2823 2. S. Kipp, Diploma Thesis, TUHH/HZG, 20103. C. Naderipour, Diploma Thesis, HAW Hamburg/HZG, 20094. T. Merkel et al., Selecting Membranes for Carbon Dioxide Capture from Power Plant Flue Gases
In Book of Abstracts XXVI EMS Summer School 29 September – 2. Oktober 2009 Geesthacht/Ratzeburg, 2009.
Multilayer composite membranes Single gas permeation data HZG data determined using pressure increase apparatus Temperature dependency can be described by Arrhenius type relationship
POLYACTIVE® composite membrane [1]
73°C 14°C
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Membrane Production in m2 Scale
2.00
2.20
2.40
2.60
2.80
3.00
0.0 40.0 80.0 120.0
Production Batch Length L [m]
O2/N
2 Sel
ectiv
ity
O2/
N2
[-]
Average
POLYACTIVE® multilayer composite membrane
O2/N2 permeation data for quality control
Casting of porous support
Coating of selective/ protection layers
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Contents
Introduction Permeation data and membrane production Membrane module model Pilot plant experiments Process simulation Upscaling aspects Conclusions
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Permeatetube
Membraneenvelope
PressurevesselFeed
Retentate
Permeate Permeate
Top view of a membrane envelope
Feed
Per-meate
Baffle plateO-ring
Feed Permeate
Retentate
FeedRetentate
Permeate
Simulation Model GS Module Boundary conditions
- Module geometry and feed definition Flow patterns: differential balances
- Material- Energy- Pressure drop
Equation of state- Fugacities- Enthalpies- Densities …
Permeation- Arrhenius- Free Volume model
Concentration polarisation- Mass transfer coefficients- Stefan-Maxwell
iP,iR,imolar,iM, ffLn
0naz
niM,
iR,
z
RyR,CH4
vR
9
Equation oriented process simulator- Parameterised models- Numerical mathematics- Physical properties- Dynamic simulation- PDE support- Integrated development environment
Detailed model development Flowsheet and process development
Implementation: Aspen Custom Modeler®
10
Contents
Introduction Permeation data and membrane production Membrane module model Pilot plant experiments Process simulation Upscaling aspects Conclusions
11
Pilot Plant Operating Conditions
Operating data: Membrane area: 7.38 m2
Feed pressures: 1.4 to 3 bar Feed flowrates: 13 to 34 Nm3/h Feed CO2 mole fraction: 13.7 to 18.0 %
Feed temperatures: 20 to 25°C Permeate pressure: 200 mbarWater vapour saturation by employing liquid
ring compressor and vacuum pump
PDI
PI2
FI1 PI1 FI2
QI1 QI2
QI3
Gas-chroma-tograph
V1
V2
V3
moduleMembrane
Permeatevacuum pump
Feedvessel
FeedCompressor
Externalvacuum pump
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Pilot Plant Experimental Results
0
0.03
0.06
0.09
0.12
10 15 20 25 30 35 40
Volumetric Flowrate Feed VF [Nm3/h]
CO
2 Mol
e Fr
actio
n R
eten
tate
y R
,CO
2 [-]
pF = 3 barpF = 2 barpF = 1.4 barpF = 3 bar, SimpF = 2 bar, SimpF =1.4 bar, Sim
0
0.05
0.1
0.15
0.2
0.25
10 15 20 25 30 35 40
Volumetric Flowrate Feed VF [Nm3/h]
Stag
ecut
VF/
V P [-
]
pF = 3 barpF = 2 barpF = 1.4 barpF = 3 bar, SimpF = 2 bar, SimpF = 1.4 bar, Sim
0.5
0.55
0.6
0.65
0.7
0.75
10 15 20 25 30 35 40
Volumetric Flowrate Feed VF [Nm3/h]
CO
2 Mol
e Fr
actio
n Pe
rmea
te
y P,C
O2
[-]
pF = 3 barpF = 2 barpF = 1.4 barpF = 3 bar, SimpF = 2 bar, SimpF = 1.4 bar, Sim
Feed Retentate
Permeate
Gas permeationmodule
VF = 13 to 34 Nm3/hyF,CO2 = 13 to 18%pF = 1.4 to 3barF = 20 to 24 °C
yR,CO2
VPyP,CO2pP = 0.2 bar
A=7.4m2
13
Pilot Plant Results Interpretation
Operating behaviour of module asexpected Module and membranes were used in
biogas pilot plant before Simulation model predicts performance
satisfactorily Single gas permeation data to predict
multicomponent mass transfer Deviations experiment – simulation
- Influence of water permeation on other components correctly considered?
14
Contents
Introduction Permeation data and membrane production Membrane module model Pilot plant experiments Process simulation Upscaling aspects Conclusions
15
Input Data
Power plant [1] Coal fired power plant Nominal power: 600 MW Efficiency: 45.9% Flue gas:
V = 1 704 000 Nm3/hp = 1.013 bar = 48°CyCO2 = 0.133yH2O = 0.113yN2 = 0.754
Process simulation Aspen Custom Modeler®
Membrane module model- Cross flow with free permeate withdrawal- Permeances as function of temperature,
pressure and composition based on single gas experiments
- Real gas and Joule Thomson effect considered
- No pressure drops and mass transfer resistances
Rotating equipment- Isentropic efficiency of 85 %- Assumed as adiabatic compressors or
turbines- No specific type assumed
1. Notz et al., Chem. Ing. Tech. 82 No.10 (2010) 1639-1653
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Performance of POLYACTIVE® Composite Membranes: Humid Flue Gas
A pressurised motive mediumpRetentate > pd > pPermeate
B suction flow (permeate) at pressure pPermeate
C mixed flow at pressure pd
1. Körting Hannover AG, Arbeitsblätter für die Strahlpumpen-Anwendung, www.koerting.de
2. Sterling SIHI GmbH, www.sterlinsihi.com
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Conclusions
POLYACTIVE® composite membrane- Permeance and selectivity are suitable- Can be produced on large scale
Accurate module models are required to develop efficient process designs Piloting is essential
- Process performance- Influence of various components- Determination of unknowns (level of filtration necessary,…)
Competitive process designs have been developed (Merkel et al., Zhao et al.) - Important to consider water- Cooling has to be accounted for- Integration with power plant process
New vacuum pump concepts required Novel module concepts would be advantageous