(576e) Rigorous, Dynamic, Two-Film Model Development and Part-Load Optimization of a Solvent-Based CO2 Capture Process Under Variable Capture Rate

Fossil fuels will
continue to play a dominant role in power generation for the foreseeable
future. One potential option to reduce the carbon footprint of these plants is
post-combustion CO₂ capture. However, leading post-combustion
capture technologies using aqueous solvents lead to high energy penalties causing
considerable decrease in plant efficiency (MacDowell et al. 2010; Wang et al.
2011).  The energy penalty in these systems primarily stems from the reboiler (Freguia
and Rochelle 2003; Ziaii, Rochelle, and Edgar 2009). As a result, research
efforts have been focused on developing accurate predictive models to minimize
the energy cost associated with solvent regeneration under various scenarios
for 90% CO₂ capture (Hasan et al. 2012; Oh and Kim 2018). However, an
increasing large number of power plants are cycling their load rapidly due to
the ever-increasing penetration of the renewable energy sources into the grid (Roeder
and Kather 2014). Thus, the plant operating conditions must be optimized under varying
part-load conditions. However, tower models for solvent-based capture systems
using aqueous amines are highly complex and nonlinear. Few models for these
processes exist that have been validated with the part-load operational data
from the pilot/industrial plants. Furthermore, rigorous models of the balance
of plant (BOP) for the capture process that provides accurate estimates of
their performance under part-load condition need to be developed since the BOP
plays a critical role in the overall energy efficiency of the capture process.
BOP models in the existing literature are generally not capable of accurate
prediction under part-load operation. In this work, a detailed, dynamic tower
model is developed where the mass and heat transfer between the liquid and gas
phase is modeled using a two-film model. The vapor-liquid equilibrium is
modeled by an electrolyte NRTL model considering the ion-ion, ion-molecule and
molecule-molecule interactions, while the heat and mass fluxes are modeled
using Maxwell-Stefan transport equations with reactions in the liquid phase.
Maximum-likelihood estimate of parameters for the thermodynamic, kinetic,
column hydraulics, mass transfer coefficient and interfacial area models is
obtained using the data from contactors spanning multiple spatial scales. A
rigorous algebraic model of a plate heat exchanger (PHE) based on the
effectiveness-Number of Transfer Units (ε-NTU) approach is developed for
the lean-rich solvent cross heat exchanger, while a detailed reboiler model is
presented with the chemistry model for the reactions in the liquid phase. Other
auxiliary units such as the cooler, condenser, and mixer are also developed for
the complete CO₂ capture process.

The plant-wide model is
implemented in the modeling and optimization framework being developed by the
U.S. Department of Energy’s Institute for Design of Advanced Energy Systems
(IDAES) (Miller et al. 2018). The IDAES framework is being built on Pyomo, an
algebraic modeling language (Hart et al. 2017). The plant-wide model is
validated using the operational data from the National Carbon Capture Center
pilot plant under considerable variation of solvent flowrate, gas flow rate, CO₂
concentration in the gas, variable capture rate and steam flowrate to the
reboiler as would be expected under the part-load operation of the host power
plant. The model is used for optimizing the plant operation under part-load and
variable capture rates.  

References

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Stefano, and Gary T Rochelle. 2003. 'Modeling of CO₂ capture by
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Hart,
William E, Carl D Laird, Jean-Paul Watson, David L Woodruff, Gabriel A
Hackebeil, Bethany L Nicholson, and John D Siirola. 2017. Pyomo—Optimization
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Hasan,
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MacDowell,
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