Flexible operation and control of methanol production from...

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Flexible operation and control of methanol production from fluctuating syngas feed Matthias Gootz, Robert Pardemann, Bernd Meyer TU Bergakademie Freiberg

Process Chain 2

Electrolyzer

Water- gas-shift

Bypass

Sour gas treatment

Methanol synthesis

Syngas

Hydrogen

Methanol

Surplus RenewableElectricity

Oxygen

Water scrubber Gasifier

→ Methanol- Annex concept (Wolfersdorf 2015) → Biomass gasification and production of methanol (Hannula 2014)

Concepts for excess electricity storage are needed in Germany Electrolysis in combination with Demand-Side-Management in chemical industry is

an important concept for electricity storage (Dechema 2015)

Storage

Lignite

Motivation Steady State Simulation Dynamic Simulation Summary

3

Can methanol plant handle fluctuations caused by hydrogen input and water-gas-shift operation?

200 MWth Entrained flow gasifier with cooling screen (Siemens type)

Selective AGR (Rectisol type) HTS + LTS

50 MW Alkaline Quasi-Isothermal

Electrolyzer

Water- gas-shift

Bypass

Sour gas treatment

Methanol synthesis

Syngas

Hydrogen

Methanol

Surplus RenewableElectricity

Oxygen

Water scrubber Gasifier

Storage

Lignite


Process Chain

0

500

1000

1500

2000

2500

3000

3500

4000

Steady state Part load

Mol

e flo

w in

km

ole/

h Electrolyzer H2

Syngas H2

Syngas CO

Other syngascomponents

Syngas composition 4


50 MW electrolysis High WGS bypass

10 MW electrolysis Low WGS bypass

→ Boundary conditions for dynamic simulation

Reactions

Methanol Kinetics 5

𝐂𝐂𝟐 + 𝟑 𝐇𝟐 ↔ 𝐂𝐇𝟑𝐂𝐇 + 𝐇𝟐𝐂 𝐂𝐂𝟐 + 𝐇𝟐 ↔ 𝐂𝐂 + 𝐇𝟐𝐂

Kinetic model for Cu/ZnO/Al2O3 commercial catalyst (Van den Bussche and Froment 1996, Van-Dal 2013, adjustment to Aspen PlusTM data input form)

𝐂𝐂 + 𝟐 𝐇𝟐 ↔ 𝐂𝐇𝟑𝐂𝐇

𝑟𝐶𝐶𝐶𝐶𝐶 =𝑘1 𝑃𝐶𝑂2 𝑃𝐻2 − 𝑘6𝑃𝐻2𝑂𝑃𝐶𝐻3𝑂𝐻𝑃𝐻2

−2

(1 + 𝑘2 𝑃𝐻2𝑂𝑃𝐻2−1 + 𝑘3𝑃𝐻2

0,5+ 𝑘4 𝑃𝐻2𝑂)3

𝑟𝑅𝑅𝑅𝑅 =𝑘5 𝑃𝐶𝑂2 − 𝑘7𝑃𝐻2𝑂𝑃𝐶𝑂𝑃𝐻2

−1

(1 + 𝑘2 𝑃𝐻2𝑂𝑃𝐻2−1 + 𝑘3𝑃𝐻2

0,5+ 𝑘4 𝑃𝐻2𝑂)

𝑘𝑘𝑘𝑘𝑘𝑘 𝑠


𝑟𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅 = 𝐾𝑅𝑅𝑅𝑅𝑅𝑅 𝑓𝑅𝑅𝑅𝑅𝑓 ×𝐷𝑓𝑅𝐷𝑅𝑅𝐷 𝐹𝑅𝑓𝑅𝑅𝐴𝐴𝐴𝑅𝑓𝐴𝑅𝑅𝑅𝑅 𝑅𝑅𝑓𝑡


*

*


6 Methanol Reactor

Plug flow Fixed bed pressure drop:

Ergun equation Heat transfer: Syngas - Catalyst Syngas - Coolant

i=1

TGas TCoolant

i=2 …

TCat

RPLUG-Model Aspen PlusTM

Model validation against data from open literature:

Reactor configuration from kinetic data source (Van den Bussche and Froment 1996) Industrial Lurgi synthesis reactor (Chen 2011)


Steady State Results 7

Parameter Simulation Literature Syngas modulus at reactor inlet 2,07 2,07 (Abrol 2012)

Maximum temperature inside reactor 278 °C <300 °C (Bertau 2014)

Pressure at the reactor inlet 69 bar 50-80 bar (Bertau 2014)

Recycle- ratio 4 3.5-4.0 (Bertau 2014)

Yield of methanol in mole/mole (CO, CO2 in syngas)

0.94

0.9-0.96 (Bertau 2014)

Yield of methanol in kg/l (Catalyst in reactor)

1.44 1.8 (max) (Wurzel 2006)


Control system objectives Counterbalance load changes in the methanol plant Temperature control to avoid catalyst deactivation

Control System Design 8

Control scheme

Singular Value Analysis Is decoupling possible?

Control Problem Formulation What variables need to be controlled?

What variables need to be manipulated?

Relative Gain Array Are there loop interactions?

How can input and output variables be matched?

PI controller tuning

Aspen Control Design Interface Matlab

Aspen Plus Dynamics


9 Methanol Synthesis


CO

TC

p

TC

Q

TC

F

PC F

F

10 Methanol Synthesis


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15000

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30000

0 1 2 3 4 5 6

Pres

sure

in b

ar

Mas

s flo

w in

kg/

h

Time in hours

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62

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9000

29000

49000

69000

89000

109000

129000

0 1 2 3 4 5 6

Pres

sure

in b

ar

Mas

s flo

w in

kg/

h

Time in hours

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0 1 2 3 4 5 6

Pres

sure

in b

ar

Mas

s flo

w in

kg/

h

Time in hours

RECYCLE SYNGAS INPUT

RAW METHANOL

Step Down 11


Step Up 12


13 Outlook

Summary The proposed control design allows flexible methanol

production. Step response tests show good controllability of the process.

Outlook Kinetic data for methanol synthesis under non-steady-state

conditions is needed • Plant wide dynamic simulation is required to investigate

dynamic process performance. • Implementation of deactivation data from the literature could be

used to predict influence of load changes on catalyst.


14 Acknowledgement

Thank you for your attention.


Matthias Gootz M.Sc. IEC Fuchsmühlenweg 9 / Haus 1 (Reiche Zeche) 09599 Freiberg Tel.: +49 3731 39-4710 Fax: +49 3731 39-4555 E-Mail: [email protected] Webseite: www.iec.tu-freiberg.de

Project Polygeneration-Annex Project number: 03ET7042A

mailto:[email protected]



http://www.iec.tu-freiberg.de/



15 References


Abrol, S.; Hilton, C. M., 2012. Modeling, simulation and advanced control of methanol production from variable synthesis gas feed. Computers & Chemical Engineering 40, 117–131 Bertau, M.; Offermanns, H.; Plass, L.; Schmidt, F.; Wernicke, H., 2014. Methanol: The Basic Chemical and Energy Feedstock of the Future. Springer-Verlag, Berlin Chen, L.; Jiang, Q.; Song, Z.; Posarac, D., 2011. Optimization of Methanol Yield from a Lurgi Reactor. Chemical Engineering & Technology 34 (5), 817–822. DECHEMA Gesellschaft für Chemische Technik und Biotechnologie e.V., 2015. Elektrifizierung chemischer Prozesse. Diskussionspapier. Available from: http://www.dechema.de/2015+Diskussionspapier+Elektrifizierung+Chemischer+Prozesse.html (accessed 06/01/2015) (in German). Hannula, I.; 2015. Co-production of synthetic fuels and district heat from biomass residues, carbon dioxide and electricity: Performance and cost analysis. Biomass and bioenergy 74, 26-46. Van-Dal, E. S.; Bouallou, C., 2013. Design and simulation of a methanol production plant from CO2 hydrogenation. Journal of Cleaner Production 57, 38–45 Vanden Bussche, K.M.; Froment, G.F., 1996. A steady-state kinetic model for methanol synthesis and the water gas shift reaction on a commercial Cu/ZnO/Al2O3 catalyst. Journal of Catalysis 161 (1), 1-10. Wolfersdorf, C.; Boblenz, K.; Pardemann, R.; Meyer, B., 2015. Syngas‐based annex concepts for chemical energy storage and improving flexibility of pulverised coal combustion power plants. 7th International Freiberg/ Inner Mongolia Conference on IGCC & XtL Technologies. Huhhot, Inner Mongolia, China. Wurzel, Th., 2006. Delivering the building blocks for future fuel and monomer demand. DGMK Conference „Synthesis Gas Chemistry“

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