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27
Dynamic Modeling and Control of an Integrated Solid Sorbent Based CO 2 Capture Process Benjamin Omell a , Debangsu Bhattacharyya a , Stephen E. Zitney b , David C. Miller c a Department of Chemical Engineering, West Virginia University, Morgantown, WV 26506, USA b National Energy Technology Laboratory, Morgantown, WV 26507, USA c National Energy Technology Laboratory, 626 Cochrans Mill Rd, Pittsburgh, PA 15236, USA AICHE Annual Meeting 2014 Atlanta, GA

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Dynamic Modeling and Control of an Integrated Solid

Sorbent Based CO2 Capture Process

Benjamin Omella, Debangsu Bhattacharyyaa, Stephen E. Zitneyb, David C. Millerc

a Department of Chemical Engineering, West Virginia University, Morgantown, WV 26506, USA b National Energy Technology Laboratory, Morgantown, WV 26507, USA

cNational Energy Technology Laboratory, 626 Cochrans Mill Rd, Pittsburgh, PA 15236, USA

AICHE Annual Meeting 2014

Atlanta, GA

2

MOTIVATION

Under the auspices of US DOE’s Carbon Capture

Simulation Initiative (CCSI), government and university

researchers are collaborating to develop computational

models and tools for various post-combustion CO2

capture technologies

As part of this project, our current focus is on the

development of dynamic models and control systems for

solid-sorbent CO2 capture processes.

3

Post- Combustion Solid Sorbent CO2

Capture

Solvent based systems

typically have high energy

cost for regeneration with low

CO2 carrying capacity

Types of Beds

Fixed Bed

Bubbling Fluidized Bed

(BFB)

Moving Bed (MB)

4

Post- Combustion Solid Sorbent CO2

Capture

Solvent based systems

typically have high energy

cost for regeneration with low

CO2 carrying capacity

Types of Beds

Fixed Bed

Bubbling Fluidized Bed

(BFB)

Moving Bed (MB)

5

Model Assumptions

• Vertical shell & tube type reactor

• Mass balance modeled as plug

flow

• Particles are uniformly dispersed

through the reactor with constant

voidage

• Particle attrition ignored

• Temperature is uniform within

the particles

Model Development for BFB and MB

Solid In

Solid Out

Gas In

Gas Out

Utility In

Utility Out

1-D, two-phase, pressure-driven and non-isothermal

model developed in both ACM and gPROMS

6

• Gaseous species : CO2, N2, H2O

• Solid phase components:

bicarbonate, carbamate, and

physisorbed water.

• Stripping steam is used for

regenerator

• Solid Sorbent: NETL 32D, a

mesoporous amine-impregnated

silica substrate

Components in BFB and MB

Solid In

Solid Out

Gas In

Gas Out

Utility In

Utility Out

7

𝜕𝑄𝐻2𝑂

𝜕𝑡= 𝑘𝐻2𝑂 𝑅𝑇𝑠𝑐𝑠𝑢𝑟𝑓,𝐻2𝑂 −

1

𝐾𝐻2𝑂𝜌𝑠𝑤𝐻2𝑂

𝜕𝑄𝐵𝑖𝑐

𝜕𝑡= 𝑘𝐵𝑖𝑐 1 −

2𝜌𝑠𝑤𝐶𝑎𝑟 + 𝜌𝑠𝑤𝐵𝑖𝑐

𝑛𝑣𝜌𝑠𝑤𝐻2𝑂(𝑅𝑇𝑠𝑐𝑠𝑢𝑟𝑓,𝐶𝑂2) −

1

𝐾𝐵𝑖𝑐𝑤𝐵𝑖𝑐𝜌𝑠

2𝑤𝐶𝑎𝑟 + 𝑤𝐵𝑖𝑐

𝑛𝑣

𝜕𝑄𝐶𝑎𝑟

𝜕𝑡= 𝑘𝐶𝑎𝑟 1 −

2𝜌𝑠𝑤𝐶𝑎𝑟 + 𝜌𝑠𝑤𝐵𝑖𝑐

𝑛𝑣𝑅𝑇𝑠𝑐𝑠𝑢𝑟𝑓,𝐶𝑂2

𝑚−

1

𝐾𝐶𝑎𝑟𝑤𝐶𝑎𝑟𝜌𝑠

2𝑤𝐶𝑎𝑟 + 𝑤𝐵𝑖𝑐

𝑛𝑣

Kinetics

𝑘𝑗 = 𝐴𝑗 𝑇𝑠 + 273.15 𝑒𝑥𝑝−𝐸𝑗

𝑅𝑇𝑠

𝐾𝑗 = 𝑒𝑥𝑝−∆𝑆𝑗

𝑅𝑒𝑥𝑝

−∆𝐻𝑗

𝑅𝑇𝑠/ 𝑃 × 105

∆𝐻𝑗 [𝐽 𝑚𝑜𝑙 ] ∆𝑆𝑗 [𝐽 𝐾/𝑚𝑜𝑙 ]

𝐻2𝑂 -52,100 -78.5

𝐵𝑖𝑐 -36,300 -88.1

𝐶𝑎𝑟 -64,700 -174.6

𝐸𝑗 [𝐽 𝑚𝑜𝑙 ] 𝐴𝑗

𝐻2𝑂 28,200 0.0559

𝐵𝑖𝑐 58,200 2.6167

𝐶𝑎𝑟 57,700 0.0989

𝑚 1.17

*Lee et al. A model for the Adsorption Kinetics of CO2 on Amine-Impregnated Mesoporous Sorbents in the Presence of Water, 28th

International Pittsburgh Coal Conference 2011, Pittsburgh, PA, USA.

𝐻2𝑂 𝑔 ↔ 𝐻2𝑂 𝑝ℎ𝑦𝑠

2𝑅2𝑁𝐻 + 𝐶𝑂2,(𝑔) ↔ 𝑅2𝑁𝐻2+ + 2𝑅2𝑁𝐶𝑂2

𝑅2𝑁𝐻 + 𝐶𝑂2,(𝑔) +𝐻2𝑂 𝑝ℎ𝑦𝑠 ↔ 𝑅2𝑁𝐻2+ + 𝐻𝐶𝑂3

8

MB Step Test- Sorbent Temperature

9

Limitations of Gas Throughput in the MB

𝑈𝑐

𝑔𝐷𝑥

= 0.463𝐴𝑟0.145 𝑣𝑔 < 𝑈𝑐

Limitation in superficial velocity of gas; need to maintain

MB flow regime*

* Chehbouni, et al., The Canadian Journal of Chemical Engineering 1995, 73, 41–50.

• As sorbent is regenerated gas is released increasing the

superficial gas velocity, maximizing at the top of the bed

10

Two-Stage MB Bed

• Sorbent release of CO2 increases

gas flow and velocity at the top of

reactor

• CO2 draw-off between stages

decreases velocity to stay in MB

regime

• Steady-state solution is easily

achieved, but creates a moving

boundary problem for dynamic

operation

• Control strategy required for

solution

Solid in

Stage 1

Stage 2

HX steam

downcomer

CO2 draw-off

Steam Regenerated solids

CO2 to compressor

11

Multi-Stage MB Control Strategy

Stage 1

Stage 2

Flow Regulator

Pressure Regulator

Downcomer

CO2 Draw-off

Level Regulator

12

Response to a 30 second, 22% increase ramp and 10

second, 22% decrease ramp in inlet regeneration steam

Regulation- Steam Ramp

Time Seconds

Se

t P

oin

t

Va

lve

op

en

ing (

%)

Sta

ge

2 o

utlet

pre

ssure

(b

ar)

0.0 25.0 50.0 75.0 100.0 125.0 150.0 175.0 200.0

47.5

52.5

57.5

62.5

1.2

81

.29

1.3

1.3

11

.32

Time Seconds

Se

t P

oin

t km

ol/hr

Va

lve

Op

enin

g %

Inle

t flow

to s

tag

e 1

km

ol/h

r

0.0 25.0 50.0 75.0 100.0 125.0 150.0 175.0 200.04

5.0

50.0

55.0

60.0

65.0

70.0

75.0

85.0

90.0

95.0

100

.01

05

.01

10

.01

15

.0

13

Limitations of MB for Adsorber

𝑈𝑐

𝑔𝐷𝑥

= 0.463𝐴𝑟0.145 𝑣𝑔 < 𝑈𝑐

Limitation in superficial velocity of gas; need to maintain

MB flow regime*

* Chehbouni, et al., The Canadian Journal of Chemical Engineering 1995, 73, 41–50.

• Because of the high amount of N2 in the flue gas, a

prohibitively large bed diameter or a very high number of

parallel beds would be required for a MB adsorber

• Given an adsorber that is treating 2000 mol/s with 12% CO2

and 90% capture rate, 27 MB in parallel with a diameter of

9 m each would be required.

14

Bubbling Fluidized Bed

Similar assumptions as the

moving bed

Flexible steady-state and

dynamic models that can be

used for both adsorber or

regenerator, with

underflow/overflow-type

configurations

15

Dynamic Results – Increase Inlet Gas

Flow by 20.6%

Gas CO2 Concentration (ACM) Gas H2O Concentration (ACM)

16

• Any adsorption (or gas separation) process can be applied,

especially for processes for heat input/removal and different

flow configurations.

– Moisture removal

– Natural gas processing

– Hydrogen purification

– Novel solid sorbent processes

– etc.

• These models can be adapted to other applications by:

– Define new components and update physical properties

– Input new reaction kinetic model/data

Applications of the BFB and MB Models

Other than CO2 Capture

17

CO2 Compression Model

Compressor stages 7-8 A

bso

rbe

r

Str

ipp

er

CO2 for

sequestration

Dry

CO2

Wet CO2

Solvent

Pump

Make-up

TEG MP CO2 rich

stream

Water

LP CO2 rich stream

from regenerator

Dynamic model of multi-stage integral-gear compression system with inter-

stage coolers and flash vessels, recycle valves for surge control, and TEG

absorber and regenerator

18

0.08 0.1 0.12 0.14 0.16 0.18 0.2 0.22 0.240.4

0.5

0.6

0.7

0.8

0.9

1

1.1

1.2

1.3

Psi3

Ps

i s

-15

0

15

30

40

50

60

70

75

Performance Curves

Dimensionless Performance Curves for

the 1st Stage

• Dimensionless exit flow coefficient

and impeller isentropic head

coefficient for applicability to

varying Mach numbers and inlet

operating conditions

19

Transient Step Response

Transient response in pressure as

a result of 10% ramp increase in

flowrate

Transient response in power as

a result of 10% ramp increase in

flowrate

PRESSURE

Time Hours

Co

mp

_s

tag

e7

.o_

po

rt.P

ba

r

Co

mp

_S

tag

e6

.o_

po

rt.P

ba

r

Co

mp

_S

tag

e5

.o_

po

rt.P

ba

r

Co

mp

_S

tag

e4

.o_

po

rt.P

ba

r

Co

mp

_s

tag

e3

.o_

po

rt.P

ba

r

Co

mp

_s

tag

e2

.o_

po

rt.P

ba

r

Co

mp

_s

tag

e1

.o_

po

rt.P

ba

r

0.0 5.0 10.0 15.0 20.0 25.030.0 35.0 40.045.0 50.0

96.

097.

098.

099.

0100

.0101

.0102

.0

60.

061.

062.

063.

064.

065.

066.

067.

0

36.

037.

038.

039.

040.

041.

042.

0

21.

021.

522.

022.

523.

023.

524.

0

11.

011.

512.

012.

5

5.2

55.5

5.7

56.0

6.2

5

2.4

2.4

52.5

2.5

52.6

2.6

52.7

2.7

5

Time Hours

Com

p_sta

ge8.e

lec_

pow

kW

Com

p_sta

ge7.e

lec_

pow

kW

Com

p_S

tage6.

ele

c_po

w k

W

Com

p_S

tage5.

ele

c_po

w k

W

Com

p_S

tage4.

ele

c_po

w k

W

Com

p_sta

ge3.e

lec_

pow

kW

Com

p_sta

ge2.e

lec_

pow

kW

Com

p_sta

ge1.e

lec_

pow

kW

0.0 20.0 40.0 60.0

16

40

.01

66

0.0

16

80

.0

16

40

.01

68

0.0

17

20

.01

76

0.0

26

00

.02

70

0.0

28

00

.02

90

0.0

24

00

.02

50

0.0

26

00

.02

70

0.0

30

00

.03

10

0.0

32

00

.03

30

0.0

34

00

.0

34

00

.03

60

0.0

38

00

.04

00

0.0

42

00

.04

40

0.0

46

00

.04

80

0.0

50

00

.0

44

00

.04

60

0.0

48

00

.05

00

0.0

20

Integrated Model

• Adsorber

• Bubbling Fluidized Bed (BFB)

• Regenerator

• Moving Bed (MB)

• CO2 Compression

• Balance of Plant

Adsorber

(CO2 Capture)

Solid Sorbent

Regenerator

Balance

of Plant

CO2

Compression

Rich

Sorbent

Flue

Gas

Lean

Sorbent

21

Integrated Process Model

Compressor Train: 8 Stages

TEG Absorber and Stripper Sorbent BFB Adsorber and

MB Regenerator

22

Combined System Model (Single Train)

Regenerated Solids

Top

Adsorber

Bottom

Adsorber

Flue Gas In

Post Heat

Exchanger

Pre Heat

Exchanger

HX steam

CO2 out

Clean Gas Out

Regeneration

Steam

HX steam

23

Inputs and Conditions

MB Variable Base Value Units

Stage Diameter 7 m

Stage Height 2.5 m

Steam inlet flow rate 400 kmol/hr

Solids inlet flow rate 658000 kg/hr

Solids inlet temperature 110 oC

Loading of bicarbonate 0.62 mol/kg sorbent

Loading of carbamate 1.8 mol/kg sorbent

Loading of water 1.03 mol/kg sorbent

BFB Variable Base Value Units

Stage diameter 6 m

Stage height 2.5 m

Steam flue gas rate 400 kmol/hr

Solids inlet flow rate 658000 kg/hr

Solids inlet temperature 60 oC

Loading of bicarbonate 0.25 mol/kg sorbent

Loading of carbamate 1.23 mol/kg sorbent

Loading of water 0.56 mol/kg sorbent

24

Ramp In Flue Gas Example

Flow into compressor train

Time Hours

Inle

t flo

w k

mo

l/h

r

0.0 20.0 40.0

56

00

.05

80

0.0

CO2 % Removed

Time Hours

%

0.0 20.0 40.0-0.2

-0.1

0.0

0.1

0.2

0.3

0.4

Ramp in flue gas

Time=0 : 15.8% increase

Time=20: 28.8% decrease

Time Hours

Co

mp

_sta

ge

8.e

lec_

po

w k

W

Co

mp

_sta

ge

7.e

lec_

po

w k

W

Co

mp

_S

tag

e6

.ele

c_

po

w k

W

Co

mp

_S

tag

e5

.ele

c_

po

w k

W

Co

mp

_S

tag

e4

.ele

c_

po

w k

W

Co

mp

_sta

ge

3.e

lec_

po

w k

W

Co

mp

_sta

ge

2.e

lec_

po

w k

W

Co

mp

_sta

ge

1.e

lec_

po

w k

W

0.0 20.0 40.0

16

40

.0

16

20

.01

64

0.0

16

60

.01

68

0.0

26

20

.02

64

5.0

26

70

.02

69

5.0

24

00

.02

50

0.0

26

00

.0

30

00

.03

10

0.0

32

00

.0

34

00

.03

60

0.0

38

00

.0

42

00

.04

40

0.0

46

00

.0

44

00

.04

60

0.0

48

00

.0

25

Ramp in Regeneration Steam

Time HoursCo

mp

_sta

ge

8.e

lec_

po

w k

W

Co

mp

_sta

ge

7.e

lec_

po

w k

W

Co

mp

_S

tag

e6

.ele

c_

po

w k

W

Co

mp

_S

tag

e5

.ele

c_

po

w k

W

Co

mp

_S

tag

e4

.ele

c_

po

w k

W

Co

mp

_sta

ge

3.e

lec_

po

w k

W

Co

mp

_sta

ge

2.e

lec_

po

w k

W

Co

mp

_sta

ge

1.e

lec_

po

w k

W

0.0 10.0 20.0 30.0 40.0

16

60

.01

68

0.0

17

00

.01

75

0.0

18

00

.0

27

00

.02

80

0.0

29

00

.03

00

0.0

25

00

.02

60

0.0

27

00

.02

80

0.0

32

00

.03

30

0.0

34

00

.0

36

00

.03

80

0.0

40

00

.0

46

00

.04

80

0.0

50

00

.0

46

00

.04

80

0.0

50

00

.0

Flow into compressor train

Time Hours

km

ol/hr

0.0 10.0 20.0 30.0 40.0

6000.0

6200.0 CO2 % removed

Time Hours

%

0.0 10.0 20.0 30.0 40.00.2

50

.275

0.3

0.3

25

0.3

5

Ramp in steam

Time=0: 27% increase

26

Conclusions

• Developed flexible, high-fidelity, first principle, dynamic

bubbling fluidized bed and moving bed solid sorbent

models for CO2 capture and CO2 compression

• Multi-stage moving bed model requires reduced gas

velocity, resulting in a moving boundary problem

• Model can handle common disturbances

• Work still to be done

• Process needs optimization for increase in CO2

removal

• Develop MB model that has several CO2 draw-off

points with advanced process controller

• Develop Reduced order model

27

Acknowledgements : As part of the National Energy Technology Laboratory’s Regional

University Alliance (NETL-RUA), a collaborative initiative of the

NETL, this technical effort was performed under the RES contract

DE-FE0004000.

Disclaimer: This presentation was prepared as an account of work sponsored by an

agency of the United States Government. Neither the United States

Government nor any agency thereof, nor any of their employees, makes

any warranty, express or implied, or assumes any legal liability or

responsibility for the accuracy, completeness, or usefulness of any

information, apparatus, product, or process disclosed, or represents that

its use would not infringe privately owned rights. Reference herein to any

specific commercial product, process, or service by trade name,

trademark, manufacturer, or otherwise does not necessarily constitute or

imply its endorsement, recommendation, or favoring by the United States

Government or any agency thereof. The views and opinions of authors

expressed herein do not necessarily state or reflect those of the United

States Government or any agency thereof.