1. The Next Generation of Activated
Carbon Adsorbents for the Pre-
Combustion Capture of Carbon
Dioxide.
Power Plant Modelling Workshop
at University of Warwick
Dr. Joe Wood，Prof. Jihong Wang,
Simon Caldwell, Yue Wang

2.  Dr Joe Wood - Introduction
◦ Project overview
◦ Modelling objectives
 Simon Caldwell - Modelling of carbon capture at IGCC Power
Plants
◦ Dispersion Model
◦ Adsorption Model
 Yue Wang - Modelling of power plant performance
◦ Heat recovery steam generator
◦ Gas turbine and heat recovery module

3.  General acceptance that CO2 emissions are
affecting the climate
 UK emissions targets for power stations is a
reduction from 500 to 50 gCO2/kWhr by 2030 (1)
 Up to 18 GW of investment of CCS power stations is
possible in the 2020s
 By 2030, 26% of global emissions from China,
with 98% of power generation emissions from
coal (2)
 $2.7 trillion investment in power by 2030 (3)
 50/50 split favouring pre-combustion to post-
combustion capture (3)
1. Turner, A. et al. The Fourth Carbon Budget - Reducing emissions through the
2020s. London : Committee on Climate Change, 2010.
2. Grubb, M. Generating Electricity in a Carbon Constrained World. London : Elsevier,
2010.
3. Liang, X et al. 2011, Applied Energy, Vol. 88, pp. 1873-1885

4. Diagram based on Tampa Electric IGCC Process
Flow Diagram, National Energy Technology Laboratory, USA
http://www.netl.doe.gov/index.html

5. • Could provide a CO2 emission free process of
the future
• Reaction to form Syngas
• Convert CO in to CO2 in water gas shift
• Separation of CO2 and hydrogen
Diagram based on Scottish Carbon Capture and Storage Centre
http://www.geos.ed.ac.uk/sccs/capture/precombustion.html

7.  University of Birmingham (Simon Caldwell)
 Simulation of pre-combustion carbon capture
◦ Developing a model of the adsorption step
◦ Producing cyclic model including all PSA steps
◦ Developing model to incorporate complete carbon
capture process
 Incorporates adsorption isotherms, mass transfer
models, fixed bed model
 Unsteady state heat and mass balances
 Parameter estimation from experimental data

8. Project Overview
T, P T, P
Syngas
Composition Composition Fuel gas to
from WGS
gas turbine
Reactor
Dry Molar CCS Process Molar
Flowrate Flowrate
Molecular Molecular
Weight Weight
Composition: Hydrogen, Carbon dioxide, Carbon Monoxide,
Nitrogen, Methane, Hydrogen Sulphide, Water

9. Typical PSA Process
Water Gas Shift High Purity
Product CO2
(60% H2, 40% CO2)
Adsorption Purge Blowdown Pressurisation
High Purity H2

10.  University of Warwick
◦ Modelling and simulation study of IGCC power
generation process
 Integration of power plant and CCS models
◦ Investigations of
 Dynamic response
 Impact on power transmission and distribution
network
 Effect of CCS upon plant efficiency
 Effect of different fuel types
 Quantified analysis of the process with plant
optimization

11.  Dr Joe Wood - Introduction
◦ Project overview
◦ Modelling objectives
 Simon Caldwell - Modelling of carbon capture at IGCC Power
Plants
◦ Dispersion Model
◦ Adsorption Model
 Yue Wang - Modelling of an IGCC power plant
◦ Heat recovery steam generator
◦ Gas turbine and heat recovery module

12.  Model being developed for the removal of CO2
from a H2/CO2 gas mixture by adsorption
 High CO2 content compared to post-combustion processes
 High pressure – favours physisorption
 Hierarchical model developed in gPROMS
 Based on Axial Dispersed Plug Flow Model
 Current model looks at an Adsorption system for
the separation of Carbon Dioxide and Nitrogen
 Literature review of CO2/N2 Adsorption Models
on Zeolite 13X

13.  Equations
 Component Mass Balance
 Use of overall Mass balance:
 Adsorption rate equation (Linear Driving Force):
 Equilibrium Isotherm (Langmuir):

14.  Temperature, Pressure and Transport Properties
◦ Thermal Operating Modes
 Isothermal
 Adiabatic
 Non-isothermal
◦ Momentum Balance
 No pressure drop
 Ergun’s Equation
 Darcy’s Equation
◦ Mass Balance Coefficients:
 Mass transfer coefficient
 Dispersion coefficient
 Diffusivity
◦ Heat Balance Coefficients:
 Heat transfer coefficient

15.  Fixed bed for removal of CO2
from a N2 flow
 Capable of controlling
pressure, input flowrates and
temperature
 Limited to 200° and 25 barg
C
 Maximum CO2 content of 25%
restricted by the CO2 analyser
 Main output is CO2 mole
fraction

17.  A simplified model was established where no
adsorption takes place
 Allows ability to validate model to be tested
 Tests the response of the entire experimental system
 Assumes system to be isothermal with no pressure drop
 Empirical models looking at response of the
system without the bed were established
 Experiments run with bed filled with glass beads
 Model Parameters identical to experiment (i.e. bed size,
flowrates etc.)

18. 0.1
0.08
CO2 Mole Fraction
0.06
Flowrate (ml/min) 8.5
Pressure (barg) 25 Experimental Output
CO2 Mole Fraction 0.1 Model Output
0.04
Estimated Dispersion 2.75 x 10-6
Coefficient (m2s-1)
Literature Dispersion ≃10-6
0.02
Coefficient (m2s-1)
0
0 200 400 600 800 1000 1200
Time (s)

19.  More complex model developed for simulation of
the adsorption step
 Model Assumptions
1. Fluid flow is governed by axially dispersed plug flow
model
2. Equilibrium relations are given by the Langmuir
Isotherm
3. MT rates are represented by LDF equations
4. Thermal effects are negligible
5. Pressure drop represented by Ergun Equation
 Parameters Estimated
 Dispersion coefficient, Langmuir Isotherm parameters
 All other parameters match experiment conditions

20. 0.12
0.1
CO2 Mole Fraction
0.08
Experimental Output
Model Output
0.06
Flowrate (ml/min) 8.5
0.04
Pressure (barg) 25
CO2 Mole Fraction 0.1
0.02
Bed length (cm) 7.7
Experimental Adsorption 3.3
Capacity (mmol/g)
0
0 1000 2000 3000 4000 5000 6000 7000 8000
Time (s)

21.  Parameters Estimated:
◦ Langmuir Isotherm Parameters:
◦ Dispersion Coefficient
 Literature results vary widely for Isotherm parameters and often do not
give Dispersion Coefficient values
 Start point for parameter estimation severely affects estimated value
Parameter Range Closest Fit
Dispersion Coefficient (m2s-1) 8.2x10-7  1.1x10-4 8.2x10-7
A (N2) (mol kg-1 Pa-1) 4.4x10-7  3.1x10-5 4.4x10-7
B (N2) Pa-1) 5.5x10-7  1.4x10-5 5.5x10-7
A (CO2) (mol kg-1 Pa-1) 1.9x10-5  6.5x10-4 1.9x10-5
B (CO2) (Pa-1) 5.4x10-6  5.0x10-4 5.4x10-6
CO2 Adsorption Capacity (mol kg-1) 1.29  3.61 3.61

22.  Validation of estimated parameters
by testing them against a shorter
bed
Glass
 Experiment repeated with 5g Beads
adsorbent instead of 18g, the
remainder filled with glass beads
 All other conditions kept the same
Zeolite 13X
 Dispersion model used for glass
bead part and adsorption model CO2/N2
Mixture
for 5g adsorbent part

23. 0.12
0.1
0.08
CO2 Mole Fraction
0.06
Flowrate (ml/min) 8.5 Experimental Output
Pressure (barg) 25
0.04 Model Output
CO2 Mole Fraction 0.1
Bed Length (cm) 2.4
0.02
Experimental Adsorption 2.8
Capacity (mmol/g)
0
0 500 1000 1500 2000 2500 3000 3500 4000
Time (s)

24. Parameter Full Bed Best Estimate Short Bed Best Estimate
Dispersion Coefficient 8.2x10-7 8.2x10-7
(m2s-1)
A (N2) (mol kg-1 Pa-1) 4.4x10-7 4.4x10-7
B (N2) Pa-1) 5.5x10-7 5.5x10-7
A (CO2) (mol kg-1 Pa-1) 1.9x10-5 4.5x10-5
B (CO2) (Pa-1) 5.4x10-6 2.5x10-5
CO2 Adsorption 3.61 1.81
Capacity (mol kg-1)
 Dispersion coefficients and Nitrogen Langmuir constants kept constant as they
approached their bounds
 Other models fit adsorption capacity closer but with significantly different
parameters

25.  Hierarchy model developed based on axial
dispersed plug flow model
 Simplistic dispersion only model validated
 More complex adsorption model able to
mimic experimental work
◦ 5 parameters estimated to give very close
approximations to experiments

26.  Adsorption Model
 Improve parameter estimation
 Implement energy balance
 Pre-Combustion Model
 Switch system to using Activated Carbon adsorbent
 Move towards conditions found in pre-combustion
capture (i.e. Hydrogen)
 Produce cyclic PSA model
 Power Plant Model
 Complete carbon capture unit model
 Combine model together with power plant model

27.  Dr Joe Wood - Introduction
◦ Project overview
◦ Modelling objectives
 Simon Caldwell - Modelling of carbon capture at IGCC Power
Plants
◦ Dispersion Model
◦ Adsorption Model
 Yue Wang - Modelling of an IGCC power plant
◦ Heat recovery steam generator
◦ Gas turbine and heat recovery module

28. Figure1. Simplified IGCC power plant procedure
Key modules for IGCC process:
a.GEM with auxiliary systems：Coal feed, ASU, Gasifier, WGS;
b.Combined cycle system: Gas turbine, Heat recovery boiler, steam
turbine.

29. Coal slurry feed system
Pulverize coal to 5mm particles and mixed with water to feed coal
slurry to the gasifier.
Coal mill model has been developed from our previous work.

30. ASU unit in IGCC power plant
• Supplies oxygen to gasification island/ sulphur removal processes
• Optimal integration with gas turbine –efficiency

31. ASU unit in IGCC power plant
Figure3 simplified ASU unit

32. The GEM (Gasification Enabled Module )unit
• Use coal slurry oxygen and air to produce syngas;
• CO shift promotes the CO2 content in syngas and prepare for
the PSA removal;
• Supply HP &LP steam to HRSG.

33. CO+H O  CO +H -41MJ/kmol
2 2 2
•Water gas shift reaction provide high partial
pressure of CO2 preferred in PSA system
• Improved hydrogen extraction; • Direct contact gas / liquid exchange
• Increased power output through improved where water flows against a gas
gasification waste heat recovery. stream passing upwards；
• Considerably aid waste heat recover
• Main model based on gas and solid and lower costs, and is especially
phase mass balance and energy advantageous in a shifted scheme
conservation; • All of the cooling train heat exchang
are liquid – liquid making them much
• Chemical reaction submodel
smaller and cheaper
inculdes devolatilization and
drying,
homogeneous reactions and
heterogeneous reactions;
Figure 4 the GEM unit
• Heat transfer submodel;
• Slag layer submodel.

34. Brayton cycle
Gas turbine components:

35. Gas turbine mathematical model:
The Compressor (Isentropic) block increases the pressure of
an incoming flow to a given outlet pressure. It determines
the thermodynamic state of the outgoing flow along with the
compressor's required mechanical power consumption at a
given isentropic efficiency.
The realized output mass flow rate
A characteristic time is used to delay the mass flow.

36. Gas turbine mathematical model:
Mixes two fluids with or without phase change. The
Mixer block calculates temperature, composition and
pressure after an adiabatic mixing of two fluids. The
output enthalpy is the sum of the input enthalpies.
The pressure of the resulting flow
Pressure loss
K is the pressure loss factor

37. Gas turbine mathematical model:
The Reactor block computes the outgoing flow bus (FB)
after one reaction, a heat exchange with the environment
and a pressure loss. Heat exchange with the surrounding
environment is taken into account. In general, the
outgoing flow is not in chemical equilibrium as the Reactor
performs a chemical reaction depending on a rate of
reaction.

38. Gas turbine mathematical model:
The Turbine (Isentropic) block decreases the pressure
of an incoming flow to a given outlet pressure. It
determines the thermodynamic state of the outgoing
flow along with the produced mechanical power at a
given isentropic efficiency.
Subscripts, ‘s’ and ‘ac’ states for isentropic
and actual change of state.
h3  h4'
oi  Turbine is adiabatic and used with gaseous flows
h3  h4

40. This heat exchanger support counter flow
The Heat Exchanger block calculates the change
of state of two media caused by indirect heat
exchange.
It is assumed, that this heat transfer rate is constant
over the area of the heat exchanger or it represents a
mean of the heat exchange rate.
To approximate the dynamic thermal behavior of
the block, the heat exchanger is assumed to have a
thermal mass
The heat exchange with environment is divided in four
parts:
 both thermal masses (for flow 1 and flow 2) exchange
heat with environment,
Each of the two flows entering the heat exchanger exchange heat with environment.
 both output flows exchanges heat with its own
thermal mass, The two thermal masses are not interacting, but they have a term
representing the heat exchange with environment.

41. • to complete the whole system modelling
• implementation of the model to software
environment;
• integrate the model with CCS process model.