(125f) Regulatory Process Control of an Advanced Post-Combustion Amine Scrubbing System

Authors: 
Walters, M. S., The University of Texas at Austin
Edgar, T. F., The University of Texas at Austin
Rochelle, G. T., The University of Texas at Austin

Regulatory Process Control of an
Advanced Post-Combustion Amine Scrubbing System

Matthew S. Walters, Thomas F. Edgar,
Gary T. Rochelle

McKetta Department of Chemical
Engineering, The University of Texas at Austin, 200 E. Dean Keeton St. Stop
C0400, Austin, TX 78705


Keywords:
amine scrubbing,
dynamic modeling, pilot plant validation, process control


Amine scrubbing is a leading technology for capturing CO2
from fossil fuel power plant emissions. The in-and-out intercooled absorber1
and advanced flash stripper2 process configuration (Figure 1) using concentrated
piperazine solvent has been proposed to reduce the capital and operating costs
associated with separating CO2 from flue gas and compressing it for
geological sequestration. A low-fidelity dynamic model of this advanced process
has been developed and implemented in MATLAB® for the purpose of screening
regulatory process control strategies. The low-fidelity model has been
validated with both a high-fidelity model and pilot plant data, and it is valid
for simulating the system near the design conditions. 

The primary process control objective of an amine scrubbing
plant will likely depend on environmental regulations, electricity markets, and
enhanced oil recovery (EOR) economics. Two possible objectives are proposed
here: delivering a constant rate of CO2 to an EOR facility and
maintaining a 90% removal rate in the absorber. We consider a capture unit
integrated with a base-loaded coal-fired power plant that experiences disturbances
in boiler load of ≤ 5%. Steam is extracted from the power plant turbine
intermediate pressure/low pressure (IP/LP) crossover. The steam extraction
valve is assumed to be 100% open at design conditions, which limits steam availability
during a disturbance. The off-design turbine operation is predicted using
Stodola's Ellipse Law. 

In the constant CO2 delivery case, the compressor
is flow controlled to meet the specified CO2 rate and the CO2
inventory in the solvent is allowed to vary. In the case where removal rate from
the flue gas is controlled, two choices for manipulated variables are examined:
the solvent circulation rate (set by the lean solvent pump) and the CO2
delivery flowrate (set by the compressor speed). After assigning manipulated
variables for level and water balance control, the remaining variables are
paired with self-optimizing process variables.

With constant CO2 delivery, the removal rate in
the absorber floats for a period of several hours when a disturbance is
introduced. Because the process variables spend long periods away from steady
state, the steam extraction rate is also floating. The process is not optimal
when it is away from steady state, and there is an energy penalty associated
with the transient period. There is also a clear tradeoff between electricity
produced and the amount of CO2 available for EOR. This scenario may
require an oversized compressor to avoid reaching the capacity limit as the pressure
of the stripper drops. In the event of a sustained disturbance, the CO2
inventory may become depleted and cause the solvent to approach the solid
solubility limit. No oscillations in process variables were observed in this
scenario.

As a result of the heavy material and
energy recycle in the process, maintaining a constant removal rate in the
absorber is challenging with only feedback control3. Manipulating
solvent rate to control removal with a small process inventory leads to
significant oscillations in process variables. The oscillations could possibly
be reduced by less aggressive tuning or a larger lean storage tank; however
this will make the response much slower and a large inventory is likely not
acceptable. These observations are consistent with previous work that
investigated using solvent rate to control removal on a simple absorber and
reboiled stripper with monoethanolamine4,5. Without any knowledge of
the absorber, a feedback controller that manipulates compressor speed must be
tuned non-aggressively to assure stability and is subject to slow oscillations
as the system comes to steady state. A model-based supervisory controller is
proposed to improve upon this strategy by making control moves that take into
account the heavy material recycle. 

advanced_flowsheet

Figure 1. In-and-out
intercooled absorber with advanced flash stripper configuration.

 

References

[1] Sachde D, Rochelle GT. Absorber Intercooling
Configurations using Aqueous Piperazine from Sources with 4 to 27% CO2.
Energy Procedia 2014;63:1637-56.

[2]
Lin Y-J, Madan T, Rochelle GT. Regeneration with Rich Bypass of Aqueous
Piperazine and Monoethanolamine for CO2 Capture. Ind Eng Chem Res
2014;53:4067-74.

[3]
Walters MS, Edgar TF, Rochelle GT. Dynamic Modeling, Validation, and Time Scale
Decomposition of an Advanced Post-Combustion Amine Scrubbing Process. Energy
Procedia
2014;63:1296-1307.

[4]
Ziaii SF. Dynamic
Modeling, Optimization, and Control of Monoethanolamine Scrubbing for CO2
Capture
. The University of Texas at Austin. Ph.D. Dissertation. 2012.

[5]
Ceccarelli N, van Leeuwen M, Wolf T, van Leeuwen P, van der Vaart R, Maas W,
Ramos A. Flexibility of Low-CO2 Gas Power Plants: Integration of CO2
Capture Unit with CCGT Operation. Energy Procedia 2014;63:1703-1726.