dynamic modeling of co 2 absorption plants for post ... · dynamic simulation of the capture plant...

NTNU

1st Post Combustion Capture Conference (PCCC1) 17th -19th May 2011, Abu Dhabi

1

Andrew Tobiesena*

Magne Hillestadb, Hanne M. Kvamsdala, Actor Chikukwaa

aSINTEFMaterials and Chemistry, Postbox 4760 Sluppen,7494, Trondheim, Norway bNorwegianUniversity of Science and Technology, NTNU, SemSælandsvei 4, Trondheim, 7491, Norway

Dynamic modeling of CO2 absorption plants for post combustion capture Development, validation and example case study

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Rationale• The objective of this work is to develop and implement dynamic models in CO2SIM in

order to simulate a “closed loop transient CO2 absorption system”

• Focus is placed on competence building through use of simulation models that can be:

– verified against experiment and plant data where feedback to the work is done fairly quickly

• by developing dynamic simulation models based on already established computer architecture

• In general, to assist in understanding CO2 capture processes (or any chemical process), we believe process simulation is beneficial to all phases in a projects lifetime

Dynamic modeling of CO2 absorption systemsProject description

ValidationSimulation studies

Summary

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• Large and frequent load changes of power plant requires understanding of dynamic operation– How shall the capture plant be operated and controlled?– What are the real consequences of varying loads at the CO2 removal plant?– How do we handle unsteady behavior, shut down, start up?

We are now moving towards building full scale plants

Reasons for developing a dynamic simulator Dynamic modeling of CO2 absorption systemsProject description


Summary

Exhaust: CO2,N2, O2 ,H2O

GT

ST

GeneratorAir

Pressurized NG

HRSG

LP steam(3.8 bar, 140 °C)

N2,

O2,

H2OAmine absorption

Amine stripper

CO2-rich 30 wt % MEA/H2O

CO2-lean 30 wt % MEA/H2O

Condenser

CO2 to compression

40 °C

45 °C

Re-boiler

1.9 bar

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– Difficult to foresee dynamic behavior of complex chemical processes

– Especially integrated processes such as that of a CO2 capture plant downstream from the power plant

• A dynamic simulator will help us understanding such process dynamics



Summary

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Dynamic simulation of the capture plant• Existing tools like UniSimDesign and Aspen Hysys

– Have dynamic simulation options– Columns are modeled as equilibrium stages– No in-depth control over models and assumptions (black box)

• CO2SIM– A general purpose steady-state flow sheet simulator particularly developed for CO2

absorption processes – Have been developing this software for several years and includes advanced object-

oriented programming techniques for efficient and fast development• Reuse of class methods • Existing thermodynamic and hydraulic models as well as solvers are re-used • Existing use of simulator architecture with GUI and visualization methods

– Exact understanding as to how the models are developed, w.r.t. assumptions: mathematics, physics, algorithms/numerics

– Research organization: We develop and test own solvents and it is therefore necessary to have insight to our modeling methods, at all layers of the code



Summary

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What dynamic simulator features we would like to have• Sub models describing thermodynamics and mass transfer with sufficient detail to

yield predictive power (rate based, etc)• Implement solvent systems based on established routines from CO2SIM (kinetics, VLE

etc)• Ability to visualize results

– General plotting functionality– All state variables as well as derived variables should be made available in the integration time

horizon • Efficient validation of models by use of data standardized extraction routines

– Streamlined information flow from pilot plant to simulation– Batch testing of all available campaign data

• Robust numerics when using the simulator (we want to converge the system..)– Ability to handle significant changes in load conditions (use of stiff DAE solver)

• Be able to execute in real time to give a virtual response close to the actual system



Summary

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Development Strategy:

• Task 1: Development of the dynamic CO2SIM column model– Development of the model for absorption and desorption – Test model and validate towards pilot plant data (steady state and dynamic)

• Task 2: Implementation of the connected unit operations, flash tanks, mixers, storage tanks and heat exchangers– Definition of unit operations built into CO2SIM

• Task3: Implementation of the dynamic Network solver– Flow sheet model– Programming techniques: information handling– Information structure

• relationship between an event (the cause) and a second event ( the effect) -> causality



Summary

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Task 1: The transient column model

• Based on first principle conservation laws for energy and mass

• Adaptability of the code for different chemical systems and process configurations has been emphasized– Uses CO2SIM architecture

• The subprograms and unit operations within the main module are developed using standardized syntax

• Handling of events• Data extraction routine from pilot plant to

simulator



Summary

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Outline• Dynamic modeling of CO2 absorption plants• Project description

• Simulator requirements/capabilities • Short description of simulation model

• Verification/Validation (Preliminary) • Experimental validation using pilot plant data

• Simulation studies• Ramp behavior• Robustness of code

• Summary• Further work• Acknowledgements



Summary

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Experimental validation of dynamic column model

• Tested towards the VOCC rig• Two time series cases (case A and B)• 30wt%MEA• Logging of input and output data every 5

seconds– The cases give about 500 updates

during simulation

• CO2SIM handles all these “events” automatically during integration to reflect process changes. – The events are collected and

systematically handled from log files (excel).



Summary

Validation of CO2 Capture - The VOCC-project (2007)

Absorber:Packing height = 5.4mID = 0.5m

NTNU

• Case B: Stepwise variations in CO2gas concentration

• Inlet gas concentration of CO2 increased in two single step-changes

• then decreased in a large reverse single step-change

• All other process variables kept constant Stable liquid and gas flow over

the experiment.

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VOCC test caseDynamic modeling of CO2 absorption systems

Project descriptionValidation

Simulation studiesSummary

1000 1500 2000 2500 3000 35000.02

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0.055Property logging of inputs (only at events): molfracCO2vap and phase:vap

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Simulated and measured:liquid solvent outlet temperature

Input co2 concentration (molfraction)

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VOCC Case B

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Summary

Blue line –SIMULATIONRed line - PILOT

Input data (Pilot and Simulation)

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Simulated and measured:Rich loading

VOCC Case B

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Summary

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Input CO2 concentration (molar fraction)

Blue line –SIMULATIONRed line - PILOT

Input data (Pilot and Simulation)

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Simulation examples

• Increasing molar ratio between the gas and liquid flow rate– Varying the liquid and vapor input

flow rates by ~50%?• In a time frame of 50 seconds

– Initially running at steady state then increase gas flow with 50% over a short time interval

– Observe the transients, then run end situation to steady state again

• 20 meter packing, identical inlet concentrations , only vary flow rate



Summary

Blue: gas flow rate (kmol/h)Green: liquid flow rate (kmol/h)

Case A: Increasing gas load

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time [s]

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Summary

Green liquid flow rate (kmol/h)

Blue: gas flow rate (kmol/h)

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Case A: Increasing the flue gas loadEffect on loading

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Summary



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Case A: Increasing the flue gas loadEffect on percent CO2 removed

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• Varying the molar ratio between the gas and liquid flow rate– In a time frame of ~300 seconds– Initially running at steady state

then increase/reduce gas flow with 50%

– Observe the transients, then run end situation to steady state again




Summary

Blue: gas flow rate (kmol/h)Green: liquid flow rate (kmol/h)

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Case B: Varying flue gas load

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Summary



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Case B: Varying the flue gas loadEffect on loading

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Summary



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Case B: Varying the flue gas loadEffect on CO2 removed

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Summary• At this point in the project a robust codebase is developed for dynamic simulation

– Absorber, desorber packing model (this presentation)– Verified numerics– Validated towards plant data (preliminary)

• The event updating procedures facilitates rapid simulation using plant data for validation• Current model gives acceptable match towards pilot plant data for MEA

– Both at dynamic and steady state operation

• The implementation methodology allows for efficient simulation of the units’ transient behavior for continuously changing input conditions or design parameters, part load operation, varying input conditions and ramping behavior.



Summary

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Currently under development• Network solver to handle sequential dynamic integration (finished but needs testing)

– Builds the network from a GUI (graphical user interface) – Including recycles

• Integrated handling of events (input changes) during simulation of networks with recycles• A few units implemented: Storage tank, dynamic flash, mixer tank and the column model



Summary

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Summary

Acknowledgement This presentation forms a part of the BIGCO2 project, performed under the strategic Norwegian research program Climit. The authors acknowledge the partners: StatoilHydro, GE Global Research, Statkraft, Aker Clean Carbon, Shell, TOTAL, ConocoPhillips, ALSTOM, the Research Council of Norway (178004/I30 and 176059/I30) and Gassnova(182070) for their support.

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Example simulation case study • Changing the power plant load:

increasing/decreasing the volumetric ratio between gas flow rate and liquid flow rate

• What are the consequences of varying the liquid and vapor input flow rates by ~50%?– Running at steady state, vary

loads at a short time interval to see the transients, then run end situation to steady state again




Summary

1 1.005 1.01 1.015 1.02 1.025 1.03 1.035

x 104

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red = liquid flowblue = gas flow

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Simulation Case study

• Simulated outlet vapor and liquid temperatures at each event

1 1.005 1.01 1.015 1.02 1.025 1.03 1.035

x 104

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Summary

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• Simulated rich loadings and percent CO2 removed from gas at each event

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x 104

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Summary

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• Simulated outlet vapor and liquid temperatures, forward to steady state– at each event

1.01 1.02 1.03 1.04 1.05 1.06 1.07 1.08

x 104

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0.785

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Property logging of outputs (only at events): loading and phase:liq

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Summary

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Summary



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Case B: Varying the flue gas loadEffect on outlet solvent temperature

dynamic modeling of co 2 absorption plants for post ... · dynamic simulation of the capture plant...

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