the chemical looping gasification of biomass for syngas
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The Chemical Looping Gasification of Biomass for Syngas Utilization in a
Solid Oxide Fuel Cell System Simulated in Aspen Plus
by
Stephen Ganesh Gopaul
A Thesis
presented to
The University of Guelph
In partial fulfillment of requirements
for the degree of
Master of Applied Science
in
Engineering
Guelph, Ontario, Canada
© Stephen G. Gopaul, April, 2014
ABSTRACT
The Chemical Looping Gasification of Biomass for Syngas Utilization in a
Solid Oxide Fuel Cell System Simulated in Aspen Plus
Stephen G. Gopaul
University of Guelph, 2014
Advisor: Dr. Animesh Dutta
Co-Advisor: Dr. Ryan Clemmer
This thesis bridges the green energy fields of high-purity H2 synthesis gas (syngas) production
from biomass chemical looping gasification (CLG) and power generation via solid oxide fuel cell
(SOFC) operation. Two distinct CLG processes were simulated in Aspen Plus using the abundant,
nonconventional poultry litter biomass type. The first process (CLG 1) involved CO2 capture using
a CaO sorbent and generated lower yields of higher-purity syngas. The second process (CLG 2)
did not involve CO2 capture but used iron-based oxygen carriers to produce higher yields of lower-
purity syngas. The resulting syngas from either process was directly fed as fuel to a simulated
SOFC to determine operational viability. Both syngas types proved effective in the SOFC,
however CLG 1 syngas exhibited relatively higher performance overall. The results contribute to
both fields through novel approaches to the respective goals of each and by outlining the benefits
of an integrated CLG-SOFC system.
iii
Dedicated to my:
Parents: Ganesh Gopaul and Rozeena Gopaul
Fiancée: Leanna Harnarain
and
Siblings: Jason Gopaul and Anesha Gopaul
iv
Acknowledgements
The author wishes to express deep gratitude to, and appreciation for, both his advisor and co-
advisor, Dr. Animesh Dutta and Dr. Ryan Clemmer, respectively, who played key roles at every
stage of his study via conceptual discussion and input. Their guidance was vital for the successful
completion of the research stages of the author’s study and instrumental in bringing this thesis to
completion. The author would also like to thank them for their constructive comments and
invaluable suggestions throughout the progression of his graduate studies.
Additionally, the author acknowledges financial support from the Discovery Grant
Program funded by the National Science and Engineering Research Council (NSERC) of Canada,
the Dean’s Scholarship from the University of Guelph, and the Queen Elizabeth II Graduate
Scholarship in Science and Technology from the Government of Ontario in partnership with
private sector donors. The author also received financial support from his parents, Mr. Ganesh
Gopaul and Mrs. Rozeena Gopaul.
Finally, the author gratefully acknowledges the enduring inspiration and patience from his
parents, named above; fiancée, Ms. Leanna K. Harnarain; and siblings, Mr. Jason J. Gopaul and
Ms. Anesha Gopaul, whose love and support have encouraged the author throughout the duration
of his graduate studies.
v
Table of Contents
ABSTRACT .................................................................................................................................. ii
LIST OF TABLES ....................................................................................................................... ix
LIST OF FIGURES ...................................................................................................................... x
NOMENCLATURE ................................................................................................................... xii
CHAPTER I: Introduction ........................................................................................................ 1
1.1 Background ............................................................................................................... 1
1.2 Objectives ................................................................................................................. 4
1.3 Contribution .............................................................................................................. 5
1.4 Co-Authorship .......................................................................................................... 6
1.5 Organization of Thesis .............................................................................................. 6
References ....................................................................................................................... 8
CHAPTER II: Biomass Gasification Literature Review – A Review of Operating
Parameters for the Production of Hydrogen via Biomass Gasification ................................. 9
2.1 Introductory Remarks ............................................................................................... 9
2.2 Biomass Gasification .............................................................................................. 11
2.3 Steam Reforming .................................................................................................... 18
2.4 Chemical Looping Gasification .............................................................................. 19
2.5 Sorption-Enhanced Reaction .................................................................................. 22
2.6 Research Gaps ........................................................................................................ 32
2.7 Concluding Remarks .............................................................................................. 32
References ..................................................................................................................... 34
CHAPTER III: Solid Oxide Fuel Cell Literature Review – A Review of the Effect of Fuel
Type and Composition on Solid Oxide Fuel Cell Performance ............................................ 37
3.1 Introductory Remarks ............................................................................................. 37
3.2 Literature Review ................................................................................................... 39
3.2.1 Performance Comparison of H2 and Hydrocarbons .............................. 40
3.2.2 Performance Comparison of H2 and CO ............................................... 44
3.2.3 Performance Comparison of H2 and Syngas ......................................... 48
3.2.4 Performance in the Presence of Sulfur .................................................. 49
vi
3.3 Research Impact ...................................................................................................... 50
3.4 Concluding Remarks .............................................................................................. 51
References ..................................................................................................................... 52
CHAPTER IV: Chemical Looping Gasification for Hydrogen Production – A Comparison
of Two Unique Processes Simulated Using Aspen Plus ......................................................... 53
4.1 Introductory Remarks ............................................................................................. 53
4.1.1 Simulated Processes .............................................................................. 55
4.1.1.1 Chemical Looping Gasification Type 1 ............................... 55
4.1.1.2 Chemical Looping Gasification Type 2 ............................... 57
4.2 Feedstock Used ....................................................................................................... 59
4.2.1 Composition of Biomass Types ............................................................. 59
4.2.2 Chemical Equations for Gasification of Biomass Types ....................... 59
4.3 Simulation Input Parameters and Description ........................................................ 60
4.3.1 Setup and Calculation Methods ............................................................. 60
4.3.2 Component Definition and Input ........................................................... 60
4.3.3 CLG 1 Flowsheet Description ............................................................... 61
4.3.4 CLG 2 Flowsheet Description .............................................................. 64
4.4 Results and Discussion ........................................................................................... 66
4.4.1 Determining the Optimal Operating Conditions ................................... 67
4.4.1.1 CLG 1 Results ...................................................................... 67
4.4.1.2 CLG 2 Results ...................................................................... 71
4.4.2 Comparison of Simulation Results ........................................................ 74
4.4.2.1 Syngas Yield Comparison .................................................... 74
4.4.2.2 Syngas Composition Comparison ........................................ 75
4.5 Potential for Future Research ................................................................................. 76
4.6 Concluding Remarks .............................................................................................. 77
References ..................................................................................................................... 78
vii
CHAPTER V: Tubular Solid Oxide Fuel Cell Operation on Syngas from Two Unique
Biomass Chemical Looping Gasification Processes – A Performance Comparison
Simulated Using Aspen Plus .................................................................................................... 80
Nomenclature ................................................................................................................ 80
5.1 Introductory Remarks ............................................................................................. 81
5.1.1 Solid Oxide Fuel Cells ........................................................................... 81
5.1.2 Syngas from Biomass CLG and SOFC Operation ................................ 85
5.2 Simulation Description and Input Parameters ........................................................ 85
5.2.1 Simulated Process .................................................................................. 85
5.2.2 Setup and Component Definition .......................................................... 88
5.2.3 Flowsheet Description ........................................................................... 88
5.2.4 Cell Performance Calculation Methods ................................................. 89
5.2.4.1 Cell Voltage .......................................................................... 89
5.2.4.2 Electrical Efficiency ............................................................. 91
5.2.4.3 Power Output ........................................................................ 91
5.3 Results and Discussion ........................................................................................... 92
5.3.1 Syngas Performance Comparison .......................................................... 92
5.3.1.1 Effect of Syngas CO Composition ....................................... 95
5.3.1.2 Effect of Syngas CO2 Composition ...................................... 96
5.3.2 Anode Temperature Sensitivity Analysis .............................................. 99
5.3.3 Anode Pressure Sensitivity Analysis ..................................................... 99
5.3.4 Fuel Utilization Factor Sensitivity Analysis ........................................ 100
5.3.5 Current Density Sensitivity Analysis .................................................. 101
5.4 Potential for Future Research ............................................................................... 103
5.5 Concluding Remarks ............................................................................................ 104
References ................................................................................................................... 105
CHAPTER VI: Integrated CLG-SOFC System .................................................................. 107
CHAPTER VII: Conclusions and Recommendations ......................................................... 109
6.1 Overall Conclusions .............................................................................................. 109
6.2 Limitations of Research ........................................................................................ 110
6.3 Recommendations for Future Research ................................................................ 111
viii
APPENDICES ......................................................................................................................... 112
APPENDIX TABLE OF CONTENTS ....................................................................... 112
APPENDIX LIST OF TABLES ................................................................................. 113
APPENDIX LIST OF FIGURES ............................................................................... 114
Appendix A: Biomass Chemical Formula Calculations ............................................. 115
Appendix B: Raw Data for Biomass CLG Simulation ............................................... 118
Appendix C: Sensitivity Analyses for Biomass CLG Simulation .............................. 123
Appendix D: Raw Data for SOFC Simulation ........................................................... 127
ix
List of Tables
Chapter II
Table 2.1. Comparison of H2 production processes from biomass sources ................................ 10
Table 2.2. Optimal operating parameters from biomass gasification studies ............................. 15
Table 2.3. Optimal operating parameters from steam reforming studies ................................... 18
Table 2.4. Optimal operating parameters for CaO sorption-enhanced studies ........................... 24
Table 2.5. Chemical reactions in the steam gasification of biomass .......................................... 27
Chapter III
Table 3.1. Chemical reactions for SOFC operation on various fuels ........................................ 38
Table 3.2. Summary of performance data at 700 °C for H2 and various hydrocarbons ............ 42
Chapter IV
Table 4.1. Chemical reactions in the steam gasification of biomass .......................................... 54
Table 4.2. Chemical reactions in syngas chemical looping ........................................................ 58
Table 4.3. Ultimate analysis of poultry litter in both the presence and absence of sulfur and
nitrogen ....................................................................................................................................... 59
Table 4.4. Proximate analysis of poultry litter ............................................................................ 59
Table 4.5. Feed stream input conditions for CLG 1 simulation .................................................. 63
Table 4.6. Block unit operating conditions for CLG 1 simulation ............................................. 63
Table 4.7. Feed stream input conditions for CLG 2 simulation .................................................. 66
Table 4.8. Block unit operating conditions for CLG 2 simulation ............................................. 66
Chapter V
Table 5.1. Feed stream input conditions ..................................................................................... 87
Table 5.2. Block unit operating conditions ................................................................................. 88
Table 5.3. Reference conditions used in voltage calculations .................................................... 90
Table 5.4. Reference voltage as a function of current density .................................................... 90
Table 5.5. Lower heating value of fuels ..................................................................................... 91
Table 5.6. Standard operating conditions ................................................................................... 92
Table 5.7. Comparison of simulation results under standard conditions to the literature ......... 94
x
List of Figures
Chapter II
Fig. 2.1. Major pathways for H2 production from biomass sources ........................................... 11
Fig. 2.2. HyPr-RING biomass gasification schematic ................................................................ 13
Fig. 2.3. Effect of reaction temperature on product gas composition ......................................... 15
Fig. 2.4. Simulation of biomass gasification in interconnected fluidized beds .......................... 17
Fig. 2.5. Coal-direct chemical looping using Fe2O3 as an O2 carrier.......................................... 20
Fig. 2.6. Syngas chemical looping separating gasification and looping ..................................... 21
Fig. 2.7. Sorption-enhanced H2 production schematic ............................................................... 23
Fig. 2.8. H2 and CO temperature profiles for sorption-enhanced reaction at low pressure ........ 25
Fig. 2.9. Comparison of product gas composition for AER and standard gasification .............. 27
Fig. 2.10. Effect of Ca/C ratio on product gas composition ....................................................... 29
Fig. 2.11. H2 concentration at H2O/CH4 ratios for various CaO/CH4 ratios ............................... 31
Chapter III
Fig. 3.1. SOFC operation on H2 fuel ........................................................................................... 37
Fig. 3.2. Voltage and power output curve comparison for H2 and CH4 ........................................................ 40
Fig. 3.3. Voltage output curves for various CH4-H2O-N2 mixtures ........................................... 41
Fig. 3.4. Voltage output curves for ethane and ethene................................................................ 41
Fig. 3.5. Voltage output curves for H2 and propane at different temperatures ........................... 43
Fig. 3.6. Voltage and power output curve comparison for H2 and n-butane .............................. 43
Fig. 3.7. Voltage output curves comparing H2-H2O and CO-CO2 systems at 1000 °C with N2 as a
diluent ......................................................................................................................................... 45
Fig. 3.8. Effect of adding N2 diluent to H2 fuel on voltage and power output at 800 °C ........... 45
Fig. 3.9. Effect of adding CO2 diluent to CO fuel on voltage and power output at 800 °C ....... 46
Fig. 3.10. Voltage and power output for various H2-CO mixtures ............................................. 47
Fig. 3.11. Comparison of H2, CO, and syngas performance with Cu-CeO2-YSZ and Ni-YSZ
anodes ......................................................................................................................................... 47
Fig. 3.12. Effect of increasing CO content on voltage and power output using Cu-CeO2-coated
Ni-YSZ anode ............................................................................................................................. 48
Fig. 3.13. Concentration polarization effects from sulfur poisoning .......................................... 49
xi
Chapter IV
Fig. 4.1. CLG 1 simulation block diagram ................................................................................. 56
Fig. 4.2. CLG 1 process schematic ............................................................................................. 57
Fig. 4.3. CLG 2 simulation block diagram ................................................................................. 58
Fig. 4.4. CLG 1 simulation flowsheet ......................................................................................... 62
Fig. 4.5. CLG 2 simulation flowsheet ......................................................................................... 65
Fig. 4.6. CLG 1 reformer temperature sensitivity analysis ......................................................... 68
Fig. 4.7. CLG 1 reformer pressure sensitivity analysis............................................................... 69
Fig. 4.8. CLG 1 WGS reactor temperature sensitivity analysis .................................................. 71
Fig. 4.9. CLG 2 reducer temperature sensitivity analysis ........................................................... 72
Fig. 4.10. CLG 2 reformer syngas yield temperature sensitivity analysis .................................. 73
Fig. 4.11. Comparison of simulation syngas yields .................................................................... 75
Fig. 4.12. Comparison of simulation syngas compositions ........................................................ 76
Chapter V
Fig. 5.1. SOFC operation on H2 and CO fuels ............................................................................ 82
Fig. 5.2. Tubular and flat plate SOFC configurations................................................................. 84
Fig. 5.3. SOFC simulation block diagram .................................................................................. 86
Fig. 5.4. SOFC simulation flowsheet .......................................................................................... 87
Fig. 5.5. Cell voltage and electrical efficiency comparison under standard conditions ............. 93
Fig. 5.6. Total power output comparison under standard conditions .......................................... 93
Fig. 5.7. Effect of syngas CO composition on cell voltage and electrical efficiency ................. 95
Fig. 5.8. Effect of syngas CO composition on total power output.............................................. 96
Fig. 5.9. Effect of syngas CO2 composition on cell voltage and electrical efficiency ................ 97
Fig. 5.10. Effect of syngas CO2 composition on total power output .......................................... 97
Fig. 5.11. Effect of anode temperature on syngas performance under standard conditions ....... 99
Fig. 5.12. Effect of utilization factor on voltage and efficiency under standard conditions ..... 100
Fig. 5.13. Effect of utilization factor on total power output under standard conditions ........... 101
Fig. 5.14. Effect of current density on voltage and efficiency under standard conditions ....... 102
Fig. 5.15. Effect of current density on total power output under standard conditions .............. 102
xii
Nomenclature
Acronyms
AER Absorption Enhanced Reforming
AFC Alkaline fuel cell
AGC Advanced Gasification-Combustion
Ca/C Calcium-to-carbon ratio
CE Carbon efficiency
CLC Chemical looping combustion
CLG Chemical looping gasification
ESP Electrostatic precipitator
GE Gasification efficiency
GHG Greenhouse gas
HHV Higher heating value
HyPr-RING Hydrogen Production by Reaction-Integrated Novel Gasification
LHV Lower heating value
MCFC Molten carbonate fuel cell
NC No CO2
OCV Open circuit voltage
PAFC Phosphoric acid fuel cell
PEMFC Polymer electrolyte membrane fuel cell
PL Poultry litter
SBR Steam-to-biomass ratio
SCR Steam-to-carbon ratio
SCW Supercritical water
SEM Scanning electron microscopy
SOFC Solid oxide fuel cell
WC With CO2
WGS Water-gas shift
XRD X-ray diffraction
ZECA Zero Emission Coal Alliance
Chemical Formulae
Al2O3 Alumina
C Elemental carbon or graphite
C2H4 Ethene
C2H5OH Ethanol
C2H6 Ethane
C3H8 Propane
C4H10 n-Butane
CaCO3 Calcium carbonate
CaO Calcium oxide
CaSO4 Calcium sulfate
Ce0.9Gd0.1O1.98 Gadolinium-doped ceria (GDC)
CeO2 Ceria
CH3OH Methanol
CH4 Methane
CO Carbon monoxide
CO2 Carbon dioxide
Cr Chromium
Cu Copper
e- Electron
Fe Iron
Fe2O3 Hematite or iron (III) oxide
Fe3O4 Magnetite or iron (II,III) oxide
xiii
Gd Gadolinium
H Elemental hydrogen
H+ Hydrogen ion or proton
H2 Hydrogen gas
H2O Water or steam
H2S Hydrogen sulfide
He Helium
La0.8Sr0.2Cr0.95V0.02O3 LSCV
LaMnO3 Lanthanum manganate
Li Lithium
M Metal
MgO Magnesia
N Elemental nitrogen
N2 Nitrogen gas
Na Sodium
NH3 Ammonia
Ni Nickel
NiO Nickel oxide
O Elemental oxygen
O= Oxide ion
O2 Oxygen gas
Pd Palladium
Pt Platinum
Rh Rhodium
Ru Rubidium
S Elemental sulfur
Sm2O3 Samaria
SO2 Sulfur dioxide
Sr Strontium
TiO2 Titania
V Vanadium
Y2O3 Yttria
YSZ Yttria-stabilized zirconia
Zn Zinc
ZnCl2 Zinc chloride
ZrO2 Zinc oxide
Greek Alphabet
ΓH2 Fuel equivalent H2 content [kmol h-1]
ΔV Voltage difference [V = 1000 mV]
η Efficiency [-]
Latin Alphabet
Ac Active cell area [m2]
F Faraday’s constant [96 485 C mol-1]
i Current density [mA cm-2]
n Number of electrons transferred [mol e- per mol]
Nc Number of cells
�̇�𝑗 Molar flowrate of species j [kmol h-1]
P Pressure [atm = 1.01325 bar]
pc Cell power [W cell-1]
ptot Total power output [kW = 1000 W]
Q Thermal energy [kJ mol-1 = 1000 J mol-1]
T Temperature [°C]
xiv
Uf Fuel utilization factor [-]
V Voltage [V = 1000 mV]
W Work [kJ mol-1 = 1000 J mol-1]
Subscripts
an Anode
c Cell
cath Cathode
e Electric
(g) Gas
op Operating conditions
P Pressure
ref Reference conditions
(s) Solid
T Temperature
tot Total
1
Chapter I
Introduction
1.1 Background
Hydrogen (H2) has the potential to be a major contributor to the replacement of carbonaceous fossil
fuels as the primary global energy source, and ultimately become a significant benefactor to the
cause of climate change mitigation. World issues such as global atmospheric carbon dioxide (CO2)
levels and other greenhouse gas (GHG) emissions can be addressed with the use of H2
technologies. H2 also presents considerable advantages over other renewable technologies due to
its energy storage and transport capabilities [1].
Biomass sources can be processed for the production of H2 and other fuel gases such as
carbon monoxide (CO) and methane (CH4). Biomass is an umbrella term for organic materials
containing carbon (C), hydrogen (H), oxygen (O), nitrogen (N), and sulfur (S), and which have
stored sunlight in the form of chemical energy. Further, it is an abundant natural resource stemming
mainly from wood and wood residues, municipal solid wastes, aquatic plants, and agricultural and
animal wastes. Poultry litter is an abundant example of such animal wastes and is the focal biomass
type of this thesis. In 2012 the world chicken population exceeded twenty-one billion, or greater
than three chickens per person [2]. Thus, poultry excreta are an omnipresent and significant
potential source for solid biomass fuel. Biomass currently accounts for roughly 15 to 20% of fuel
utilization worldwide, though it is not a major fuel in contemporary industrial practises. However,
the use of biomass as an energy source is not a novel approach exclusive to modern society as it
has been used since prehistoric times for the purposes of heat generation. In addition to being an
effective, abundant fuel source, biomass sources are also considered to be CO2-neutral, and thus
aid in addressing the aforementioned issue of atmospheric CO2 concentration. Emissions of CO2
released during biomass conversion are equivalent to the amounts of CO2 absorbed by the organic
material via photosynthetic mechanisms. Biomass types are characterized through the use of
ultimate and proximate analyses. The former is an elemental analysis which considers the C, H,
O, N, S, and ash content of the biomass fuel, while the latter is a more qualitative analysis and
considers volatile matter, moisture, fixed carbon, and ash content [3].
2
The gasification of biomass is a widely used thermochemical process with the purpose of
converting the combustion value of the solid biomass to gaseous products. Common product gas,
or syngas, constituents include H2, H2O, CO, CO2, and CH4, as well as carbonaceous char and tar
by-products. The resulting gaseous fuel stream can be utilized in further downstream energy
production processing units, e.g. combustors, boilers, gas turbines, and fuel cells. Examples of
marketable products of gasification include H2, ammonia (NH3), methanol (CH3OH), gasoline,
oxo-alcohols (precursors for detergents and plasticizers), and various liquid oils and other fuels.
Biomass gasification encompasses four simultaneous processes in which the biomass particle
undergoes thermal decomposition. Drying occurs when moisture evaporates from the particle in
the form of steam; pyrolysis allows for the formation of gaseous components such as H2, CO, CO2,
steam, as well as liquid oils, tars, and solid char in the absence of oxygen (O2); gasification involves
endothermic reactions between solid char and the resultant gaseous products from pyrolysis; and
finally combustion includes exothermic reactions between O2 and the solid char and volatile matter
surrounding the particle. The chemical reactions involved in the endothermic stage of gasification
include the Boudouard, Water-Gas, Hydrogenation, Methanation, and Water-Gas Shift Reactions,
and are represented by Equations (1) to (5), respectively.
Boudouard reaction: C + CO2 ↔ 2 CO (1)
Water-gas reaction: C + H2O ↔ CO + H2 (2)
Hydrogenation reaction: C + 2 H2 ↔ CH4 (3)
Methanation reaction: CO + 3 H2 ↔ CH4 + H2O (4)
Water-gas shift reaction: CO + H2O ↔ CO2 + H2 (5)
Equations (1) and (4) proceed very slowly in the absence of catalysis. Equation (2) is prevalent in
the gasification mechanism when steam is present as the gasification medium, and Equation (3)
becomes important when H2 is used as the medium. Equation (5) is highly desirable in the system
when H2 is the desired gasification product, and its equilibrium is driven forward in-part by the
products of Equation (1) [3].
The gasification process, regardless of fuel type, is carried out in reactors called gasifiers.
A multitude of gasifier types exist which are optimized for various scenarios and desired products.
Fixed bed gasifiers, the oldest gasifier type, consist of the up-draft (countercurrent stream flow),
3
down-draft (co-current stream flow), and cross-draft schematics. These gasifiers produce low
purity H2 syngas that is highly diluted with nitrogen (N2) and CH4, thereby requiring downstream
reforming to convert the CH4 to H2. Entrained flow gasifiers are highly effective for coal
gasification and are capable of gasifying a vast array of coal types. However, the difficulty
involved in grinding biomass particles to sufficiently small particle sizes renders entrained flow
gasifiers less suitable for biomass gasification [4]. Moreover, fluidized bed gasifiers provide
greater versatility than the other gasifier types in terms of biomass gasification and have greater
high-purity H2 syngas production capabilities. These advantages stem from the greater degree of
solid mixing and uniform temperature of the fluidized bed, and the higher fuel flexibility of the
system. Consequently, H2 syngas purity can be further increased in the presence of a CO2 sorbent,
i.e. calcium oxide (CaO), by the formation of calcium carbonate (CaCO3). Desorption of CO2 from
the sorbent via CaCO3 dissociation and subsequent recovery and recycle of the sorbent constitutes
a syngas chemical looping gasification (CLG) system, which is the focus of a major portion of this
thesis. The sorbent particles are looped between the fluidized bed gasifier and the downstream
regenerator. Sorbent performance degradation over time is a major issue facing the field of biomass
CLG. Capture and sequestration of the separated CO2 inhibits its release to the atmosphere and
thus CLG processes are considered as CO2-negative when using CO2-neutral biomass fuels [3,4].
Fuel cells are electrochemical devices which directly convert the chemical energy stored
in the inlet fuel stream to electrical and thermal energy. Fuel cells generally consist of an anode
where electrochemical oxidation reactions occur, a cathode where reduction occurs, an electrolyte
which provides contact between the two electrodes, and an interconnecting material which
electrically joins the electrodes to allow for electron (e-) flow. Fuel cells generally operate on H2
fuel, though CO, CH4, CH3OH, and other carbonaceous fuels can be oxidized at the anode
depending on the fuel cell type. The anodic and cathodic electrochemical half-cell reactions for H2
operation are summarized in Equations (6) and (7) and the overall reaction for the system can be
seen in Equation (8).
Anodic oxidation: H2 → 2 H+ + 2 e- (6)
Cathodic reduction: ½ O2 + 2 H+ + 2 e- → H2O (7)
Overall reaction: H2 + ½ O2 → H2O (8)
Equations (6) through (8) vary depending on both the utilized fuel and fuel cell type.
4
Many fuel cell types exist; each with its own set of advantages and disadvantages. For
example, alkaline fuel cells (AFCs) are optimal for space applications as they exhibit high H2-O2
performance compared to other fuel cell types and do not require the use of precious metal
catalysts. However, the presence of CO2 in the fuel stream greatly reduces AFC performance.
Phosphoric acid fuel cells (PAFCs) were developed for the use of reformed hydrocarbon fuel,
thereby increasing CO2 tolerance, however precious metal catalysts such as platinum (Pt) are
required, and are easily poisoned by very small amounts of CO. Polymer electrolyte membrane
fuel cells (PEMFCs) exhibit no carbonaceous exhaust emissions and are scalable to a wide range
of applications, though PEMFCs are also greatly susceptible to CO poisoning as direct
consequence of precious metal catalyst requirements. Higher temperature fuel cells (operating
temperature > 600 °C) include molten carbonate fuel cells (MCFCs) and solid oxide fuel cells
(SOFCs), the latter of which is focused on in this thesis. MCFCs were developed to operate directly
on coal syngas. SOFCs operate between 800 and 1000 °C and are highly versatile in terms of fuel
operation [5]. They are capable of running on product streams from a vast array of syngas
production and reforming processes, and are therefore the optimal fuel cell choice for operation
on product syngas from biomass CLG.
The purpose of this thesis is to bridge the green energy fields of high-purity H2 syngas
production from biomass chemical CLG and power generation via SOFC operation. A simulation-
based approach was utilized to achieve the main objectives of the conducted research, and Aspen
Plus was the chosen simulation software. Aspen Plus is a commercially available software package
provided by AspenTech and developed in 1981 by the chemical engineering group at the
Massachusetts Institute of Technology (MIT) under a grant from the United States Department of
Energy. It includes a comprehensive thermodynamic and physical property database allowing for
simple process simulation and analysis. Built-in process unit modules (e.g. chemical reactors,
heaters, and separators) further simplify the user interface and usability of the program [6,7].
1.2 Objectives
The overall objective of the conducted research was the comparison of two novel, simulation-
based approaches to biomass CLG on the basis of their respective syngas composition and
production capabilities. SOFC operation on the resultant syngas types was simulated for the
purpose of performance comparison and was also a main objective of the research. Specific
objectives were also to:
5
Design and simulate two unique biomass CLG processes.
Determine optimal operating conditions for the simulated reactors in both CLG processes.
Compare resultant syngas from the CLG processes in terms of H2 yield and purity.
Simulate SOFC operation on the syngas from both CLG processes.
Compare the results of SOFC operation on syngas in terms of cell voltage, electrical
efficiency, and total power output.
Determine the effects of syngas CO composition on SOFC performance.
Study the effects of syngas CO2 composition on SOFC performance.
Research the effects of varying operating parameters on SOFC performance.
Compare the simulated results to values published in the literature.
1.3 Contribution
This thesis represents a valuable addition to the efforts of bridging the renewable energy fields of
biomass CLG and SOFC operation. Novel approaches to the respective goal of each field, H2
production and power generation, are designed, simulated, and the results compared. Specific
contributions also include the:
Development of a CLG process for H2-rich syngas production with in situ CO2 capture via
CaO sorbent, total sorbent recovery and tar reforming, and simulated using the Aspen Plus
software.
Design of a CLG process for high yields of majority-H2 syngas using Fe-based oxygen
carriers, with near-total carrier recycle, and simulated using Aspen Plus.
Direct comparison of aspects from the two resultant syngas types using the same,
nonconventional biomass feedstock, i.e. poultry litter, in both cases.
Direct tubular SOFC performance comparison of the two biomass CLG syngas types under
the same feed and operating conditions using Aspen Plus.
Investigation of the effects of CO levels in the syngas feed on simulated SOFC
performance.
Study of the effects of syngas CO2 composition on SOFC performance to determine if its
removal is a net benefactor to the combined CLG-SOFC system.
6
1.4 Co-Authorship
The following are aspects of the conducted research that underwent the peer-review process and
were published in a journal, or were submitted to a peer-reviewed journal. Although the listed
authors provided invaluable contributions in the form of suggestions, input, and critiquing, the
author of this thesis was the principal author of the listed works.
Chapter IV
Title: Chemical looping gasification for hydrogen production: A comparison of two unique
processes simulated using ASPEN Plus.
Authors: Stephen G. Gopaul, Animesh Dutta, and Ryan Clemmer.
Published in: The International Journal of Hydrogen Energy
Citation: Gopaul, S.G., A. Dutta, and R. Clemmer. “Chemical Looping Gasification for Hydrogen
Production – A Comparison of Two Unique Processes Simulated Using ASPEN Plus.” Int J
Hydrogen Energ 39 (2014): 5804-5817.
Chapter V
Title: Tubular solid oxide fuel cell operation on syngas from two unique biomass chemical looping
gasification processes: A performance comparison simulated using Aspen Plus.
Authors: Stephen G. Gopaul, Ryan Clemmer, and Animesh Dutta.
Submitted to: The International Journal of Hydrogen Energy
1.5 Organization of Thesis
A brief description of the main chapters of the thesis is provided below.
Chapter II
This chapter begins with the importance of H2 as a clean fuel and its potential to replace fossil
fuels as the dominant energy source. It then moves on to explain its connection to biomass, a
renewable energy source. Literature regarding thermochemical biomass conversion pathways such
as biomass gasification, steam reforming, CLG, and sorption-enhanced H2 production are
reviewed. The optimal operating parameters such as temperature, pressure, steam/carbon ratio, and
calcium/carbon ratio for a multitude of studies utilizing these biomass conversion pathways are
7
also summarized. Potential research gaps in the field of biomass conversion to H2 are identified
towards the end of the chapter.
Chapter III
This chapter begins with background information regarding SOFC operation and inherent
advantages and disadvantages to other fuel cell types posed by SOFC utilization. The review
proceeds to focus on determining the effects of fuel type and composition on SOFC performance
in terms of voltage output and power density. Performance from H2 operation is compared to other
fuels such as CO, CH4, coal syngas, biomass syngas, and other fuel mixtures, and the effects of
alternative anode materials are reviewed. Performance degradation due to sulfur poisoning is also
considered in this chapter.
Chapter IV
This chapter presents the comparison between two biomass CLG processes for the production of
H2 simulated using Aspen Plus. The optimal operating conditions are determined via temperature
and pressure sensitivity analyses of the constituent reactors for each process. The end of the chapter
discusses the H2 purity and production capability differences between the two processes.
Chapter V
This chapter presents the performance simulation of a tubular SOFC operating on syngas generated
from two unique biomass CLG processes using Aspen Plus. The effects of syngas CO and CO2
composition on performance are discussed. Anode temperature and pressure, fuel utilization
factor, and applied current density sensitivity analyses are conducted and shown towards the end
of the chapter. Performance values are compared to those reported in the literature.
Chapter VI
This chapter briefly summarizes the benefits of combining the CLG and SOFC processes into a
single, integrated system. The recycling of high quality heat from the SOFC stack exhaust stream
to high temperature reactors from the CLG processes is emphasized upon.
Chapter VII
The overall findings from the conducted research and limitations posed by the utilized methods
and assumptions are detailed in this chapter. Recommendations for further study are also
summarized.
8
References
[1] Levin, David B., and Richard Chahine. "Challenges for Renewable Hydrogen Production from Biomass." Inter J
Hydrogen Energ 35 (2009): 4962-969.
[2] Food and Agriculture Organization of the United Nations. “FAOSTAT – Production – Live Animals.” FAOSTAT.
7 Feb. 2014. Web. 26 Mar. 2014. <http://faostat.fao.org/site/573/DesktopDefault.aspx?PageID=573#ancor>.
[3] Fan, Liang-Shih. Chemical Looping Systems for Fossil Energy Conversions. Hoboken, NJ: Wiley-AIChE, 2010.
Print.
[4] Acharya, Bishnu. Chemical Looping Gasification of Biomass for Hydrogen-Enriched Gas Production. Thesis.
Dalhousie University, Halifax, Nova Scotia, 2011. Dalhousie University, Department of Mechanical Engineering.
Print.
[5] Li, X. Principles of Fuel Cells. New York: Taylor & Francis, 2006. Print.
[6] Aspen Plus 11.1 Users Guide, 2002. AspenTech Ltd., Cambridge, MA, USA.
[7] Zhang, W., E. Croiset, P.L. Douglas, M.W. Fowler, and E. Entchev. “Simulation of a Tubular Solid Oxide Fuel
Cell Stack using AspenPlusTM Unit Operation Models.” Energ Convers Manage 46 (2005): 181-196.
9
Chapter II
Biomass Gasification Literature Review – A Review of
Operating Parameters for the Production of Hydrogen via
Biomass Gasification
2.1 Introductory Remarks
Hydrogen (H2) has the potential to revolutionize the global energy industry and reduce and
subsequently eliminate our reliance on carbonaceous fossil fuels. H2 presents a viable alternative
to fossil fuels as its use in H2 fuel cells results in clean energy with minimal polluting or greenhouse
gas (GHG) emissions. Further, H2 is a viable alternative compared to other natural energies such
as solar and wind power due to its ability to store energy and be used as a medium for energy
transport. However, the production of H2 from current technologies requires H2 consumption and
subsequent generation of GHGs [1]. Biomass presents a renewable and environmentally friendly
alternative feedstock for H2 production.
Biomass is an organic fuel source generally consisting of carbon (C), hydrogen (H), oxygen
(O), nitrogen (N), and sulphur (S). Biomass can come in many forms including, but not limited to:
animal wastes, municipal solid wastes, crop residues and other agricultural wastes, and saw dust
[2]. The use of biomass as a fuel source is not a novel approach as it has been used since pre-
historic times as a source of heat generation. Burning wood to cook meat is exemplar of such
practices. Consequently, a more modern approach is the thermochemical or biological conversion
of biomass to H2 for use in subsequent energy-producing applications (e.g. fuel cells). Continually
rising prices for hydrocarbon-derived energy is causing H2 production from biomass to become
increasingly favourable as biomass becomes relatively cheaper. Moreover, in Canada, the most
rapidly growing demand for H2 comes from the upgrading of heavy oil in the oil sand industries
of Alberta [1].
Although the conversion of biomass to H2 does present a viable alternative to widespread
fossil fuel utilization, significant physicochemical and economic shortcomings do exist. For
example, on a weight basis, H2 is more efficient as a fuel than both oil and natural gas. However,
gaseous H2 is eight times lighter than methane and liquid H2 is ten times lighter than gasoline.
10
Thus, H2 has a relatively low volumetric energy density overall. Still, this fact has favourable
implications when considering logistics costs and energy transport. Furthermore, purification
issues exist when considering separating H2 out of product gas streams. Palladium (Pd)-based
membranes are viable technologies for H2 separation due to their high H2 permeability, although
they are rapidly deactivated by trace amounts of sulphur in the gas stream. The utilization of
palladium-metal (Pd-M) membranes has been found to improve membrane performance in the
presence of sulphur. Additionally, the degree of purification required depends on the market and
application type [1]. Economic barriers also exist. The recent contraction and relative decline of
the North American automotive industry has postponed the expected use of H2 in automobiles as
a replacement fuel for gasoline and diesel. Assuming full market penetration, roughly 40 million
tonnes of H2 per year would be required to run 100 million fuel-cell operated cars [1]. However,
the wide-scale use of H2 in automobiles requires investment and subsequent development of
necessary infrastructure and on-board storage techniques [3]. Energy costs also play a large role
in the economic barriers. Using current technologies, a 400 MWth input can produce H2 at US$ 8
to 11 per GJ given that biomass can be purchased for US$ 2 per GJ. This figure is roughly double
current gasoline production prices of US$ 4 to 6 per GJ. Reduction in biomass expense coupled
over the long-term with increased capital investment, technological advancements, and larger-
scale applications could potentially reduce the H2 production cost to approximately US$ 6 per GJ,
thus matching current gasoline production costs [3].
Table 2.1
Comparison of H2 production processes from biomass sources. Adapted from [1].
Process Biomass feedstocks Efficiency By-products
Thermochemical conversion processes
Steam reforming Methane, glycerol,
alcohols, polyols, sugars,
organic acids
70-85% CO, CO2, C10-C22 chains
Aqueous reforming Glycerols, alcohols,
polyols, sugars, organic
acids
35-100% CO, CO2, alkanes,
alcohols, polyols, organic
acids
Electrolysis H2O and electricity 50-60% None
Partial oxidation Hydrocarbons 60-75% No data
Biomass gasification Biomass 35-50% CO, CO2, CH4
Biological conversion processes
Photolysis H2O and sunlight 0.5% None
Photo-fermentation Organic acids and
sunlight
0.1% CO2
Dark fermentation Lignocellulosic biomass 60-80% CO2
11
The focus of this review is the outlining of the current processes for H2 production from
the thermochemical conversion of biomass. Consequently, Table 2.1 [1] summarizes current H2
production processes, their respective efficiencies and by-products, including both the
thermochemical and biological methods. Figure 2.1 shows the major pathways for H2 production
from biomass [4].
Fig. 2.1. Major pathways for H2 production from biomass sources [4].
2.2 Biomass Gasification
Biomass gasification is the thermochemical conversion of biomass for the production of a
combustible gaseous product stream, i.e. synthesis gas (syngas). It is carried out in the presence of
a gasification agent and is generally applicable to biomass containing less than 35% moisture. Tar
formation during the gasification process is a major concern as it results in the generation of more
complex by-products downstream. These by-products hinder H2 production, reduce the purity, and
contaminate the product gas stream [5]. The use of a rhodium (Rh)/ceria (CeO2)/M (where M is
silica, alumina, or zirconia) catalyst has been found to reduce tar formation, however this catalyst
is relatively costly and more research is required to develop a more cost-effective one [2]. CeO2-
12
zirconia (ZrO2) catalysts were found to perform better than Al2O3-supported ones in terms of H2
production [6].
Gasification is a favourable method to pyrolysis for H2 production as it aims to generate
the products in a gaseous state [5]. Further, H2 yield from gasification is generally greater than that
from pyrolysis [7]. To elaborate upon the aforementioned moisture content restriction, biomass
gasification is in fact possible for biomass containing > 35% moisture, given that it is carried out
in supercritical water (SCW) conditions. SCW is that which is subjected to temperatures and
pressures exceeding 374.3°C and 221.2 bar, respectively [4]. The properties of liquid and vaporous
H2O at the critical temperature and pressure are indistinguishable. SCW gasification eliminates the
need for any biomass drying due to its ability to withstand relatively high moisture contents [8]
and can be carried out both at lower (350 to 600 °C) and higher (> 600 °C) temperatures [4].
Consequently, SCW gasification has some advantages inherent to the thermophysical properties
of SCW itself. These include, but are not limited to [9]:
Process reactions finish rapidly and completely due to lack of mass transfer limitations.
Water is more readily separated from the products after the process is complete. This can
be done simply by changing operating parameters, and thus is advantageous when
compared to other separation methods.
The life of the active catalyst is lengthened due to decreased generation and subsequent
deposition of coke.
Moreover, 100% gas conversion can only be achieved at lower temperatures via utilization of a
bimetallic rubidium (Ru) or nickel (Ni) catalyst supported on titania (TiO2), ZrO2, or carbon.
Catalyst use is not required for high-temperature SCW gasification [4].
A more recent biomass gasification technology is the Hydrogen Production by Reaction-
Integrated Novel Gasification (HyPr-RING) method, in which the H2 production and gas
separation reactions are carried out in the same reactor at relatively lower temperatures. The
process is depicted in Figure 2.2 [5,7].
Variation of gasification operating parameters also has a significant effect on the
thermophysical properties of the product gas stream. For example, higher temperatures are
generally favourable to H2 production by gasification. In addition, reducing gasification pressure
by 10% was found to result in negligible increases in H2 production – amounting to less than a
13
0.2% increase [8]. Higher steam/biomass ratio (SBR) also favours H2 production. Methane (CH4)
and solid carbon that would be produced at lower SBRs are completely converted to H2 and CO at
higher steam flowrates. Furthermore, the use of O2 for gasification generates higher quality syngas
with a higher heating value (HHV) range of 10 to 15 MJ Nm-3. A high temperature range of 1000
to 1400 °C can be achieved using this method. In comparison, syngas generated by air gasification
has a HHV of only about 4 to 6 MJ Nm-3 with undesired by-products such as H2O, carbon dioxide
(CO2), hydrocarbons, and tars [8].
Fig. 2.2. HyPr-RING biomass gasification schematic [5,7].
14
Many studies have been conducted to determine various ways of improving H2 production
from biomass gasification. Some of the final results of the reviewed studies are summarized in
Table 2.2. For example, Moghtaderi [10] focused research on controlling operating parameters
such as reaction temperature and heating rate to determine the effect on product gas yield using
radiata pine dust. Higher temperatures and higher steam rates were found to increase gas yield.
Maximum H2 production from the low-temperature catalytic steam gasification of biomass was
observed at the optimal conditions of reaction temperature of 600 °C, steam content of roughly 90
mol-%, and a residence time of 20 min. This result was additionally improved with the use of a
Ni-based catalyst with a nickel oxide (NiO) molar ratio of 50%. Figure 2.3 shows the effect of
reaction temperature on product gas composition (at 90 mol-% steam and 20 min residence time)
from this study [10]. The figure on the left shows that 600 °C was the approximate critical point
where any reduction in reaction temperature would result in significant loss of H2 production.
Further, increasing reaction temperature beyond this point resulted in minimal (if any) increase in
H2 production accompanied by an increase in potentially adverse by-products such as CO. The
figure on the right shows the effects catalyst use on the product gas yield. It can be seen that by-
product generation was significantly reduced at temperatures above 600 °C.
Furthermore, Anuadala et al. [11] presented an analytical model of sawdust wood
gasification which predicted H2 production over the range of 10 to 32 kg biomass per second.
Biomass was fed to a gasifier at 727 to 1227 °C and was accompanied by steam at 227 °C. It was
found that input temperature and quantities of steam and biomass affected the H2 production rate.
80 to 130 g H2 / kg biomass was produced over the biomass feed range, whereas 80 g H2 / kg
biomass was produced at the gasifier operating temperature range. H2 constituency in the product
gas stream varied from 51 to 63% with 4.5 kg s-1 of steam and narrowed to 51 to 53% with 6.3 kg
s-1 of steam.
Guo et al. [12] conducted an investigation aimed at H2 production from biomass
gasification in SCW. It was found that H2 yield, gasification efficiency (GE), and carbon efficiency
(CE) all increased with an increase in temperature. Also, H2 yield, GE, and CE all slightly
increased with a pressure increase from 25 to 30 MPa. However, the increase in all three
parameters was too small to be considered significant. Further, the three parameters decreased with
increasing biomass content, as gasification became more difficult under these conditions. Higher
temperatures were required to cope with higher biomass content. Both H2 and CO2 yield increased
15
rapidly with increasing residence time. Conversely, CO production tended to behave in the
opposite manner. Thus, higher residence times were found to be favourable, albeit at the expense
of production time losses. H2 and CH4 yield decreased with increased oxygen (i.e. oxidizer)
addition. CO2 yield notably increased under the same conditions.
Table 2.2
Optimal operating parameters from biomass gasification studies.
Biomass type Maximum
H2 content
Gasifier
temperature
Steam /
biomass
Residence
time Catalyst used Reference
Radiata pine
sawdust
~1.50 m3/kg
of biomass 600 °C 0.9 20 min 50 mol-% NiO [10]
Sawdust wood 51-63% 727-1227 °C (6.3 kg
steam/s)a - - [11]
Olive oil waste 70 mol-% 900 °C - 7-10 min 5 wt.-%
ZnCl2b
[14]
- 60.5% 750-800 °Cc 0.6-0.7 - - [15]
Softwood,
Eucalyptus
globulus, and
hardwood
-d 830 °C 0.6-0.7 - - [16]
a Specific SBR value not given. b Catalyst use was optimal for H2 production at 800 °C and resulted in 69 mol-% H2. c Optimum combustor temperature was 920 °C. Also, recirculation of 4 to 14 bed particles was required to maintain
constant gasifier temperature. d No specific maximum H2 content value given; however H2 content increased by 10 to 20% with an increase in
temperature.
Fig. 2.3. Effect of reaction temperature on product gas composition [10].
16
Correspondingly, Furusawa et al. [13] also conducted research on biomass gasification in
SCW; however lignin was used in conjunction with Ni catalysts. From their research, it was
concluded that an optimal Ni particle size exists for the catalytic gasification of lignin biomass in
SCW. This conclusion was made on the basis that the carbon yield of gas products increased with
increasing Ni surface area, with the exception of 10 wt.-% Ni/magnesia (MgO) catalyst calcined
at 500 °C. Under the tested conditions, the 10 wt.-% Ni/MgO catalyst calcined at 600 °C produced
a carbon yield of 30%; the highest of the tested catalysts. Therefore, Furusawa et al. deemed this
catalyst optimal for gasification of lignin in SCW.
González et al. [14] studied the reactions influencing biomass air and air/steam gasification
for H2 production. The influence of zinc chloride (ZnCl2) and dolomite catalysts were also
investigated. It was found that maximum H2 production was 70 mol-% H2 in the product gas
stream. This was attained at a reactor temperature of 900 °C and at a residence time range of 7 to
10 min. The use of 5 wt.-% ZnCl2 catalysts were most effective at 800 °C and resulted in the
product gas stream being composed of 69 mol-% H2 with a residence time of 5 min. No significant
improvement in H2 production could be seen at 900 °C.
Shen et al. [15] simulated biomass gasification in interconnected fluidized beds. The
simulation schematic can be seen in Figure 2.4 [15]. The effect of gasifier temperature and SBR
on fuel gas composition, H2 yield, carbon conversion of biomass, recirculation of bed particles,
and other parameters were studied. The fluidized beds included a circulating bed for air-fed
combustion and a bubbling bed for steam-fed gasification. Optimum gasifier temperature was
found to be in the range of 750 to 800 °C. H2 content in this range reached a maximum of 60.5%
with an optimum combustor temperature of 920 °C and maximal SBR in the range of 0.6 to 0.7.
An increase in SBR showed a steady increase in H2 and CO2 content, while CO content decreased
steadily. Subsequently, this optimal value was found to decrease with increasing gasifier
temperature. The trend observed for carbon conversion was a decline with increasing gasifier
temperature and SBR. Furthermore, the recirculation of bed particles required to maintain a
constant gasifier temperature increased with an exponential trend for each incremental increase in
gasifier temperature. The optimal value was found to be between 4 and 14 particles at optimal
gasifier and SBR conditions.
Consequently, Franco et al. [16] investigated the reactions influencing biomass gasification
by varying biomass type. Softwood, Eucalyptus globulus, and hardwood were utilized in the study.
17
The optimum gasifier temperature was 830 °C. Increasing temperature resulted in greater product
gas generation and a reduction in the generation of various hydrocarbons. H2 content increased by
10 to 20% with the increase in temperature coupled with a reduction of hydrocarbon and tar
generation by 3 to 5%. An SBR of 0.6 to 0.7 was found to be optimal. Switching between biomass
types was not found to have a significant effect on product gas composition. This is generally a
good result since biomass availability varies seasonally depending on the regional climate.
Furthermore, the water-gas shift (WGS) reaction was dominant for eucalyptus and hardwood at
the optimal gasifier temperature. The Boudouard and WGS reactions were significant over the
entire tested temperature range for softwood.
Fig. 2.4. Simulation of biomass gasification in interconnected fluidized beds [15].
18
2.3 Steam Reforming
After the gasification process has taken place, the production of purer H2 can be achieved by steam
reforming followed by a WGS reactor. H2 is produced during the WGS reaction where CO and
steam are converted to CO2 and H2. Both high- and low-temperature WGS reaction methods
require the use of a catalyst: iron (Fe) and/or chromium (Cr)-based oxide catalysts at high
temperatures and copper (Cu)-zinc (Zn) oxide catalysts at low temperatures [4]. Although O2
would be ideal in steam reforming, O2 separation units are cost-intensive and are not practical for
smaller scale plants [2].
As with biomass gasification, many studies exist in which researchers utilized steam
reforming for the production of higher purity H2. The results from some of the reviewed studies
which use the steam reforming method are summarized in Table 2.3.
Table 2.3
Optimal operating parameters from steam reforming studies.
Biomass type Maximum
H2 content
Optimal
temperature
Steam /
carbon
Optimal
pressure
Calcium /
carbon Reference
1:1 biomass to
crude glycerin
mixture
- a 700-750 °C 1.7-2.25 100 kPa 1 [18]
Acetic acid,
ethylene glycol,
and acetone
80-90% 627 °C 9 b 1 atm - [19]
a No specific maximum H2 content value given; however H2 yield increased linearly from 0.053 to 0.059 mol H2 / kg
biomass with an increase in temperature from 650 to 825 °C. b Increasing SCR from 1 to 9 improved H2 production by 20% at 627 °C and saw a maximum value of 64.4 mol-%.
The specific SCR for the tests yielding 80 to 90% H2 content was not given.
Wang et al. [17] found that variation in temperature had the most significant effect on H2
yields. Moreover, at 600 °C, varying residence time from 0.04 to 0.15 s and increasing
steam/carbon ratio (SCR) from 4.5 to 7.5 did not have a significant effect on H2 production.
Furthermore, Chen and Zhao [18] investigated the co-steam-reforming of a 1:1 biomass to crude
glycerin mixture and determined that higher temperatures and lower pressures favoured H2
production. It was further determined that the optimal temperature range for H2 production was
700 to 750 °C. A temperature increase from 650 to 825 °C resulted in a linear increase in H2
production from 0.053 to 0.059 mol H2 / kg biomass. Optimal pressure was roughly atmospheric
at 100 kPa. The SCR that maximized H2 production was determined to be between 1.7 and 2.25
and a clear increase in H2 production was observed with increasing SCR. Finally, H2 production
19
was maximized at a calcium/carbon ratio (Ca/C) of unity, with no significant changes in gas
production beyond this value.
Thermodynamic analysis of H2 production via steam reforming of acetic acid, ethylene
glycol, and acetone was carried out by Vagia and Lemonidou [19]. It was found that maximum H2
yield ranged from 80 to 90% at 627 °C. Increased H2 content at higher operating temperatures was
accompanied by the increased presence of CO. Increasing SCR favoured H2 production over the
temperature range studied such that an increase from 1 to 9 improved H2 production by 20% at the
optimal operating temperature. Maximum H2 composition of 64.4 mol-% was obtained at a SCR
of 9. Higher pressures decreased H2 content in the product stream. Increasing pressure from 1 to
20 atm decreased H2 content from 68 to 49 mol-%. Thus, optimum pressure was found to be 1 atm.
The production of 1 kmol/s of H2 via bio-oil steam reforming required roughly the same amount
of energy as with natural gas reforming. This was demonstrated with the utilization of material
and energy balances over the entire system.
2.4 Chemical Looping Gasification
In general, chemical looping systems utilizing solid fuels (e.g. biomass) consist of a solid carrier
in a loop between two reactors. These reactors may be a combination of fixed and fluidized bed
reactors. The two main types of chemical looping systems include chemical looping combustion
(CLC) and chemical looping gasification (CLG). However, the latter will be focused on in this
review. CLG combines high-purity H2 production with CO2 capture, making it an attractive
thermochemical biomass conversion process. Two types of CLG exist. They differ based on the
type of solid carrier used – either an O2 or CO2 carrier [20].
CLG using an O2 carrier includes the cycling of the carrier between a fuel reactor and an
air reactor. A metal oxide is used as the carrier and is reduced in the fuel reactor thereby freeing
up oxygen for use by the fuel to generate the product gases. Subsequently, the reduced metal oxide
is cycled to the air reactor where it is oxidized upon contact with the air stream. Inert N2 is thus
prevented from diluting or combining with the product gas stream, ultimately eliminating any
downstream separation requirements. CLG using an O2 carrier is further divided into two
processes: biomass directly gasified in the fuel reactor and biomass gasified in a separate gasifier
prior to entering the looping system [20].
In the process where biomass is directly gasified in the fuel reactor, O2 levels are
maintained sufficiently low, below the stoichiometric level, so as to avoid biomass combustion.
20
Fan demonstrated that iron oxide (Fe2O3) was a suitable O2 carrier for this process [21]. They
developed the coal-direct chemical looping system utilizing Fe2O3 as an O2 carrier for the
production of pure H2. This process is depicted in Figure 2.5 [21]. Conversely, Scott et al. found
that significant problems occurred when utilizing Fe2O3 as an O2 carrier. Gasification was found
to be a limiting step [20]. Moreover, it was not well understood if the Fe2O3 carrier would retain
its efficiency upon increased oxidation-reduction cycling in the long-term. Furthermore, Leion
proposed that tar, char, and ash particle deposition on the Fe2O3 carrier surface reduced its efficacy
[22].
Fig. 2.5. Coal-direct chemical looping using Fe2O3 as an O2 carrier. Adapted from [21].
21
Subsequently, separating the biomass gasification and looping system processes was
developed to mitigate the shortcomings of the aforementioned process. The syngas chemical
looping system proposed by Fan is exemplar of this process, and is illustrated in Figure 2.6 [21].
In this process, pure streams of both H2 and CO2 were generated via the condensation of a steam
and CO2 stream.
Fig. 2.6. Syngas chemical looping separating gasification and looping. Adapted from [21].
In contrast, CLG using a CO2 carrier involves the use of a sorbent, usually calcium oxide
(CaO), being cycled between gasifying and regenerating reactors. As such, the sorbent undergoes
a series of calcination-carbonation cycles whereby CO2 is absorbed by CaO for the generation of
solid calcium carbonate (CaCO3). This facilitates the production of a pure CO2 product stream.
This process is reiterated and further explained in a later section of this review. Processes such as
HyPr-RING, Zero Emission Coal Alliance (ZECA), ALSTOM hybrid gasification-combustion,
22
and Advanced Gasification-Combustion (AGC) are all exemplar of CLG with the utilization of
CaO as a CO2 carrier. The major difference between the processes is their respective method for
providing sufficient energy for the calcination reaction. Note, however, that these methods are best
adapted for coal gasification under current technological conditions. Utilizing coal, these processes
were able generate H2 in the product stream at levels of 65 to 80% [21].
2.5 Sorption-Enhanced Reaction
Sorption-enhanced H2 production combines hydrocarbon reforming, WGS, and CO2 capture and
separation processes into a single step, thereby greatly enhancing H2 purity in the product gas
stream. Furthermore, CO and CO2 are reduced to parts-per-million amounts. Sorption-enhanced
H2 production is an inherently transient process as the sorbent is consumed during reaction. This
requires that the sorbent be regenerated in a downstream process to make sorption-enhanced
reaction economically viable. Consequently, maximization of sorbent life is paramount for process
efficiency [23].
The sorbent is generally mixed with the reforming catalyst so both processes can occur
simultaneously [24]. Sorbents can be calcium-based oxides, K-promoted hydrotalcites, and mixed
metal oxides of lithium (Li) and sodium (Na). The mechanism of CO2 capture is that the CO2 is
absorbed by the solid sorbent, subsequently generating a CO2-solid complex. For example: if
calcium oxide (CaO) is used as the sorbent, CaO and CO2 will react to form solid CaCO3,
effectively removing CO2 from the product gas stream [23].
Some general advantages presented by sorption-enhanced H2 production when compared
with typical biomass gasification include, but are not limited to [25]:
Only two processing steps are required.
Lower temperatures and pressures are utilized.
Predicted energy savings of 20 to 25%.
Dolomite can be used as a sorbent source; it is relatively inexpensive and abundant.
Sorbent regeneration produces pure CO2 that can either be utilized in further applications
or sequestered.
A general schematic of sorption-enhanced reaction can be seen in Figure 2.7 [25]. The majority of
the reviewed studies utilize CaO as the sorbent of choice. Grasa and Abanades [26] studied the
23
effect of continuous cycling on the ability of CaO sorbent to capture CO2. It was found that capture
capacity decreased significantly within the first 20 cycles, but tended to become steady with further
cycling. This residual conversion range was stable for up to 500 cycles. Consequently, the residual
conversion range was reached more rapidly for both calcination temperatures exceeding 950 °C
and longer calcination times, as the deactivation rate constant was favoured under these conditions.
Sorption-enhanced H2 production has been extensively studied and well-reported in the
literature. The results of select studies are summarized in Table 2.4. Ortiz and Harrison [27]
obtained a purity of > 95 mol-% H2 due to sufficiently rapid rates of the reforming, WGS, and CO2
removal reactions. The majority of the Ni-based reforming catalyst and Ca-based sorbent mixture
regeneration conditions resulted in minor activity loss, even after 25 cycles. Furthermore, it was
found that most of the activity loss was attributed to the Ca-based sorbent which is inexpensive
relative to the catalyst.
Fig. 2.7. Sorption-enhanced H2 production schematic [25].
24
Table 2.4
Optimal operating parameters for CaO sorption-enhanced studies.
Biomass
type Temperature Pressure
Steam /
biomass
Steam /
carbon
Ca /
carbon H2 content CO2 content CO content Reference
CH4: steam
mix (1:4) 480 °C 5 atm - - - 97.8% - 20 ppmv [25]
- 400-460 °C 1-5 bar - 3 - > 96 mol-% - < 7 ppmv [28]
Wood pellets 841 °C - - 0.63 - 73.9 mol-% 6.0 mol-% 6.1 mol-% [29]
- 690 °C - - - - 50.6% - - [30]
Cellulose 527-627 °C 1 atm - 1.5 0.9 83 mol-% - - [31]
Bio-oil
aqueous
fractions
500-700 °C - - 1 - 83 vol.-% - - [32]
Coal / CaO
mix 600 °C 6 MPa - - - 84.8% 1.6% 1.1% [33]
Wood 700 °C 0.6 MPa - - 2 - a - - [34]
Wet 650-700 °C - - - 0.5 51.5% inc. b 28.4% red. b - [35]
Pine bark 600 °C 1 atm - - - 48.6% inc. c - - [36]
White fir 670 °C - 0.83 - 1.5-2 ~54% 1% - [37]
Glycerol 577 °C - 9 - - 95% - - [38]
Bio-oil 600-850 °C,
800 °C d
10-20 bar, 1
atm d - 2 - > 95% - - [39]
Biogas 800 °C - - - - 55-65% - - [40]
Ethanol 500-700 °C 1 atm 4 - - - a - - [41]
a No specific maximum H2 content value given; however H2 content was maximized under the listed conditions. b No specific H2 or CO2 content values given; however H2 content was increased by 51.5% and CO2 content reduced by 28.4% after increasing moisture content
by a factor of 10. c H2 content increased by 48.6% with the use of CaO sorbent. d For the reforming and desorbing reactors, respectively. e No specific H2 or CO2 content values given; however H2 content was increased by 19% and CO2 content reduced by 50.2% when the CaO sorbent was present
in the reforming reactor.
25
Additionally, thermodynamic analysis of the sorption-enhanced reaction by Harrison and
Peng [25] using a mixture of Ni-based catalyst and Ca-based CO2 sorbent showed that H2 of >
95% purity could be produced with less than 20 ppmv CO in the product stream, on a dry basis,
given that equilibrium conditions could be closely approached. The study resulted in the
production of 97.8% H2 and 17 ppmv CO in the product gas stream. This was done under an
operating temperature of 480 °C, a pressure of 5 atm, and feed composition of 20% CH4 and 80%
steam.
Moreover, Yi and Harrison [28] investigated sorption-enhanced H2 production at lower
pressures which necessitate lower temperatures, allowing the sorbent to remain effective at CO2
removal. The results of the investigation were such that an H2 concentration > 96 mol-% and CO
concentration < 7 ppmv were obtained at reaction temperatures of 400 to 460 °C, pressures ranging
from 1 to 5 bar, and a SCR of 3. Calcined Arctic SHB dolomite was used as a source for the Ca-
based sorbent as it did not require sulphur removal prior to utilization. The H2 and CO
concentrations as a function of temperature at a SCR of 3 are depicted in Figure 2.8 [28].
Fig. 2.8. H2 and CO temperature profiles for sorption-enhanced reaction at low pressure [28].
In addition, Pfeifer et al. [29] compared H2 production capacities of steam gasification
using a dual fluidized bed system both using, and in the absence of, a calcite sorbent. The use of
the sorbent was termed the absorption enhanced reforming (AER) process. Wood pellets were used
as the test biomass in both cases. The SCRs with and without calcite sorbent were 0.63 and 0.79
kg/kg, respectively. Optimal gasifier temperatures with and without calcite sorbent were found to
26
be 841 and 645 °C, respectively, with combustion temperatures of 920 and 894 °C. Overall, it was
determined from the study that the use of calcite sorbents greatly enhanced H2 content in the
product stream, as well as significantly reducing the CO and CO2 content. H2 content with and
without the calcite sorbent were 73.9 and 37.7 mol-%, respectively; CO content with and without
were 6.1 and 29.1 mol-%; and CO2 content with and without were 6.0 and 19.6 mol-%. A downside
noted in the study was that hydrocarbon content slightly increased with the use of the sorbent.
Subsequently, the aforementioned AER process was tested on an industrial scale by
Koppatz et al. [30] using an 8 MW heat and power plant and CaO sorbent. The results were also
compared to the standard gasification process. Optimal gasification temperature was found to be
at or slightly below 690 °C. Combustion temperature for AER was roughly 850 °C and for standard
gasification was approximately 950 °C. The tested gasification temperature range for standard
gasification was 850 to 900 °C. It was observed that the AER process produced higher purity H2
(50.60%) than standard gasification while simultaneously reducing gaseous by-product content.
The differences between the AER process and standard gasification are illustrated in Figure 2.9
[30].
Florin and Harris [31] investigated the consequences of thermodynamic equilibrium on H2
production utilizing steam gasification of biomass in the form of cellulose. Analytical model
predictions were subsequently compared to experimental results. Information was also presented
which summarizes all chemical reactions that take place during the steam gasification of biomass.
This is summarized in Table 2.5 [31]. The results of the experiment showed that a maximum of 83
mol-% H2 was produced using CaO as the sorbent material. The optimal temperature range was
found to be 527 to 627 °C, a relatively lower range. The most favourable pressure conditions for
maximal H2 generation were atmospheric. Furthermore, the optimal SCR was found to be 1.5 on
a molar basis. A Ca/C ratio of 0.9 was found to be optimal for successful removal of the subsequent
concentration of CO2. Moreover, it was found that the analytical equilibrium model was neither
able to predict the formation of hydrocarbon tar by-products nor the degradation of reactivity of
the CaO sorbent.
27
Fig. 2.9. Comparison of product gas composition for AER and standard gasification [30].
Table 2.5
Chemical reactions in the steam gasification of biomass. Adapted from [31].
Reaction Chemical equation ΔHo923 (kJ mol-1)
Water-gas shift CO + H2O → CO2 + H2 -35.6 (exothermic)
Methane reforming CH4 + H2O →CO + 3 H2 225 (endothermic)
Water-gas (i) C + H2O → CO + H2 136 (endothermic)
Water-gas (ii) C + 2 H2O → CO2 + 2 H2 100 (endothermic)
Oxidation (i) C + O2 → CO2 -394 (exothermic)
Oxidation (ii) C + ½ O2 → CO -112 (exothermic)
Boudouard C + CO2 → 2CO 171 (endothermic)
Methanation C + 2 H2 → CH4 -89.0 (exothermic)
28
Yan et al. [32] studied the steam reforming of bio-oil aqueous fractions using CaO and
calcined dolomite sorbents to capture CO2. A maximum H2 content of 83 vol-% was achieved
using lower temperatures. However, maximum H2 yield was 75%, achieved at higher temperatures
in the range of 500 to 700° C. Furthermore, it was observed that H2 content was found to vary only
slightly with SCR, although it was optimized at a ratio of 1. The use of the calcined dolomite
sorbent at 600 °C and a particle diameter of 250 to 500 µm were determined to be optimal for both
H2 content and yield.
Additionally, Lin et al. [33] studied the pyrolysis of a coal/CaO mixture with steam
utilizing a flow-type reactor. The results were compared to pyrolysis of pure coal. While the
pyrolysis of pure coal resulted in product gas comprised of only about 15% H2, the mixture
generated 84.8% H2. Furthermore, the use of the mixture greatly reduced the CO2 content from
12.0% to 1.6%, and the CO content from 12.0% to a mere 1.1%. Furthermore, the small amount
of remaining CO in the product gas stream could be completely converted to H2 and CO2 via WGS.
Higher gasifier temperatures were found to favour H2 production. The coal/CaO mixture generated
twice as much H2 upon gasification as pure coal did at 700 °C. Consequently, this H2 production
value was as much as four times larger than the coal/CaO mixture performance at 600 °C.
Moreover, an increase in pressure from 1 to 6 MPa increased H2 production by a factor of about
1.5, showing that increasing pressure also favoured H2 production. However, any increase beyond
6 MPa showed minimal and relatively insignificant increases in H2 generation.
Hanaoka et al. [34] produced H2 from woody biomass while testing the effects of
temperature, pressure, and Ca/C ratio. It was observed that maximum H2 yield was obtained at a
Ca/C ratio of 2. The trend can be observed in Figure 2.10 (at 700 °C temperature, 0.6 MPa pressure,
and 10 min holding time) [34]. Optimal pressure was found to be 0.6 MPa. This value was
considerably lower when compared to other forms of biomass such as coal and heavy oil.
Furthermore, increasing temperature was favourable to H2 production, with 700 °C producing
optimal results.
Further, Guoxin and Hao [35] studied the effects of gasifying wet biomass on the
production of H2. It was found that increasing moisture content by a factor of 10 (i.e. from 0.09 to
0.90) increased H2 yield by 51.5% and reduced CO2 generation by 28.4%. Increasing temperature
also favoured H2 generation. The optimal operating temperature range was found to be 650 to 700
°C. Conversely, rising temperature tended to restrict CO2 absorption by the CaO sorbent. This
29
result was further confirmed utilizing x-ray diffraction (XRD) and scanning electron microscopy
(SEM) imaging techniques. Optimal H2 production was observed at a Ca/C ratio of roughly 0.5.
While CO2 capture was not exactly maximized at this value, only minimal increases were observed
beyond a Ca/C ratio of 0.5.
Fig. 2.10. Effect of Ca/C ratio on product gas composition [34].
Subsequently, Mahishi and Goswami [36] presented a technique to enhance H2 production
from steam gasification of pine bark biomass by integrating the gasification and absorption steps.
H2 yield was found to increase by 48.6% in the presence of a CaO sorbent, as compared with in its
absence. Moreover, overall gas yield improved by 62.2% and carbon conversion efficiency by
83.5%. These optimal conditions were produced at a gasification temperature of 600 °C and
atmospheric pressure. The use of the CaO sorbent led to reduced concentrations of CO and CH4 in
the product gas stream. CaO acted as both a sorbent and catalyst in that it aided in the reforming
of hydrocarbons and tars in the product gas stream. It is important to note that no sorbent
regeneration was conducted in this study.
Dutta et al. [37] studied the effect of varying SBR, CaO/biomass ratio, and temperature on
H2 production from the steam gasification of white fir biomass. A maximum H2 concentration of
30
about 54% was obtained at an optimal SBR of 0.83. Further, varying SBR at a CaO/biomass ratio
of 1.5 was found to produce a CO2 concentration of 1%. Increasing temperature favoured H2
production. Maximum H2 content was observed at 670°C, with a decline at higher temperatures.
However, maximum H2 yield of 315.08 mL H2 / g biomass was observed at 710 °C. A reduction
of 93.33% in CO2 concentration was observed at a CaO/biomass ratio of 2, as compared with the
no-CaO sorbent case.
Wang et al. [38] studied the effects of utilization of CaO sorbent on glycerol steam
reforming. It was found that a Ni/ZrO2 catalyst was unable to bring the system to equilibrium
conditions as maximum H2 content achieved was 64% – down from the theoretical maximum value
of 67%. A maximum H2 purity of 95% was found using the CaO sorbent with the balance being
CH4. This was conducted at 577 °C and steam/glycerol (i.e. steam/biomass) ratio of 9. The addition
of CaO was found to be highly effective in removal of CO from the product gas stream.
Furthermore, Kinoshita and Turn [39] investigated the production of transportation-fuel-
grade H2 using CaO as a CO2 sorbent via steam reforming of bio-oil. The study was simulated
using the Aspen Plus simulation software. It was found that optimal operating temperatures of the
reforming and desorbing reactors were 600 to 850 °C and roughly 800 °C, respectively. Further, a
pressure of 10 to 20 bar was utilized for the reforming reactor, while atmospheric pressure was
optimal for the desorbing reactor. At higher pressures, CO2 regeneration became difficult in the
desorbing reactor and thus lower pressures were favourable. The optimal SCR was found to be 2.
Consequently, the maximum H2 content in the product gas stream was > 95% under the
aforementioned conditions.
Assabumrungrat et al. [40] found that a mixture of CaO and Ni/SiO2·MgO was the optimal
sorbent/catalyst arrangement to maximize H2 yield for H2 production from biogas.
Thermodynamic analysis determined that thermal neutral conditions can be acquired by utilizing
higher steam/CH4 feed ratio and higher O2/CH4 or CaO/CH4 ratios. It was further observed that a
maximum H2 production value existed at an optimal steam/CH4 ratio and at 800 °C for each
CaO/CH4 ratio tested. This observation is depicted in Figure 2.11 [40].
31
Fig. 2.11. H2 concentration at H2O/CH4 ratios for various CaO/CH4 ratios [40].
Comas et al. [41] found that the utilization of a CaO sorbent greatly enhanced H2
production and reduced CO formation in the product gas stream. Ethanol steam reforming with
the use of CaO was optimal for H2 production in the temperature range of 500 to 700 °C – lower
than in the absence of the sorbent. The case utilizing CaO as sorbent also had a higher thermal
efficiency and removed the necessity for a WGS reactor. In addition to the previously mentioned
temperature range, H2 production was found to be optimized at atmospheric pressure and a
water/ethanol (i.e. steam/biomass) ratio of 4 (molar basis).
Subsequently, Mahishi et al. [42] used the Aspen Plus simulation software to simulate
ethanol sorbent-enhanced gasification for H2 production. Three cases were considered: no CaO
sorbent, reforming with CaO sorbent in the reformer, and reforming with CaO sorbent in the WGS
reactor. The optimal case was determined to be that of CaO sorbent in the reformer, with an optimal
gasification temperature of 777 °C and optimal pressure of 1 atm. The optimal SBR was
determined to be 4. Furthermore, it was observed that the sorbent utilization increased the
equilibrium H2 yield from conventional gasification by roughly 19% while simultaneously
reducing CO2 content by 50.2%.
32
2.6 Research Gaps
Future research proposed by Kinoshita and Turn [39] focuses on ascertaining a better
understanding of the kinetic limitations of the involved reactions, as well as further identification
of optimal operating parameters and assessment of CaO sorbent regeneration and compatibility
with any reforming catalysts that may be utilized. The solid form of the utilized sorbent (i.e.
powder or pellet) also leaves room for any potential research, as mentioned by Mahishi et al. [42].
Moreover, further research may be conducted on the kinetic mechanisms of the reaction
between the CaO sorbent and CO2 during the latter’s absorption and desorption processes.
Maximizing the rate of this equilibrium reaction would be the aim of such research. It is suggested
that the tar-reforming capabilities of the CaO sorbent be further addressed to enhance in situ tar
removal from the product gas stream [42,43].
In addition, Florin and Harris [43] suggested that more research is required in determining
the effect of biomass chemical composition (i.e. ultimate analysis) on H2 production. It was also
proposed that there is merit in research regarding the modification of the crystal structure of CaO
sorbent. Ion addition to enhance the CO2 capture capabilities of CaO is exemplar of such
adaptations. Subsequently, the effect of impurities in the CaO sorbent bed on H2 production should
also be considered.
2.7 Concluding Remarks
In conclusion:
1. H2 presents a clean, efficient alternative energy production source to fossil fuels and its
utilization has the potential to become widespread in the near future. The thermochemical
conversion of biomass is a viable H2 production technique capable of achieving high-purity
H2 syngas streams.
2. Biomass gasification in conjunction with the use of Ni- or other metal-based catalysts
resulted in H2 production purities upwards of 70 mol-%. Increasing gasification
temperature favoured H2 production, with an average optimal temperature range between
750 and 850 °C. Maximal H2 production occurred at steam/biomass ratios of 0.6 to 0.7 with
residence times varying from 10 to 20 min.
33
3. Following biomass gasification with the steam reforming method further enhanced H2
production and purified the product gas stream. H2 production using this method reached
upwards of 80 to 90%. Increasing temperature favoured H2 production and optimal
temperatures ranged from 627 to 750 °C. Steam/carbon ratios varied as some studies found
lower ranges of 1.7 to 2.25 to be optimal, while others found higher values of 9 to be
optimal. Optimal pressures were atmospheric or roughly so.
4. Chemical looping gasification (CLG) combines H2 production with CO2 capture and
purification, and can be achieved using either an O2 or CO2 carrier. Fe2O3 was found to be
a suitable O2 carrier, although reduced efficiency was an issue reported in some studies
when considering increased reduction-oxidation cycles. CaO was found to be an effective
CO2 carrier, permitting superior CO2 separation and downstream concentration.
5. Enhancing H2 production with the utilization of Ca-based sorbent for CO2 capture greatly
enhanced the purity of the product gas stream. Purities > 95 mol-% H2 were observed in
many studies, with an average upwards of 80%. CO2 and CO content in the gas stream
were also greatly reduced. Higher reaction temperatures favoured H2 production with an
optimal range of 600 to 700 °C. Atmospheric pressures were favourable. Optimal
steam/carbon and Ca/carbon ratios of 1.5 to 2 were characteristic.
6. Finally, potential research opportunities are rife. Major focuses include acquiring a better
understanding of the kinetic mechanisms and limitations of the reactions involved in
thermochemical biomass conversion processes as well as further identification of optimal
operating parameters for the maximization of H2 production. More research is required
regarding CaO sorbent performance, regeneration, and tar-reforming capabilities. The
effect of the chemical composition of biomass feed on H2 production and purity should
also be considered in future work.
34
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37
Chapter III
Solid Oxide Fuel Cell Literature Review – A Review of the
Effect of Fuel Type and Composition on Solid Oxide Fuel Cell
Performance
3.1 Introductory Remarks
Solid oxide fuel cells (SOFCs) are electrochemical devices which directly convert chemical energy
into electrical energy at high temperatures (typically 600 to 1000 °C). Similar to other fuel cell
types, SOFCs consist of an anode, electrolyte, cathode, and interconnect. However, due to the
higher operating temperatures, no liquid components are utilized and all portions of the cell
assembly are solid-state. The anode material is usually a nickel-yttria-stabilized zirconia (Ni-YSZ)
cermet (ceramic-metal), the electrolyte is YSZ ceramic, and the cathode material usually consists
of strontium (Sr)-doped lanthanum manganate (LaMnO3). Moreover, due to the high operating
temperature, SOFCs can operate on a multitude of fuel types and compositions. SOFC operation
on hydrogen (H2) is illustrated in Figure 3.1. The electrochemical reactions and consequent overall
reactions for H2, carbon monoxide (CO), and methane (CH4) fuels are displayed in Table 3.1.
Fig. 3.1. SOFC operation on H2 fuel.
38
Table 3.1
Chemical reactions for SOFC operation on various fuels.
Fuel Anodic Oxidation Cathodic Reduction Overall Reaction a
H2 H2 + O= → H2O + 2e- ½ O2 + 2e- → O= H2 + ½ O2 → H2O + We + Q
CO CO + O= → CO2 + 2e- ½ O2 + 2e- → O= CO + ½ O2 → CO2 + We + Q
CH4 CH4 + 4 O= → CO2 + 2 H2O + 8e- ½ O2 + 2e- → O= CH4 + 2 O2 → CO2 + 2 H2O + We + Q a We = electrical work [J mol-1] and Q = thermal energy [J mol-1].
Oxygen (O2) reduction at the cathode occurs independent of inlet fuel type, and thus the
electrochemical reaction is the same in each case. The resultant oxide ions (O=) migrate across the
YSZ electrolyte to react with the inlet fuel at the Ni-YSZ anode, hence initiating electrochemical
anodic oxidation of the fuel. Overall, the system involves the reaction of the fuel with O2, the
production of desired electrical work (i.e. electricity), and the generation of heat, H2O, and/or CO2
by-products, depending on the carbon content of the fuel. Specifically, the generation of CO2
during SOFC operation becomes unavoidable with the use of carbonaceous fuels like CO, CH4,
and higher-order hydrocarbons. Hydrocarbon operation will be further discussed in the following
sections of this review.
Table 3.1 suggests that direct oxidation of CO and CH4 is possible for SOFC operation.
However, another mechanism of utilization exists for each of the two fuels. Given that the SOFC
operates on CO, the water-gas shift reaction may proceed when the gas is humidified. This reaction
is illustrated by the following:
Water-gas shift: CO + H2O → H2 + CO2
Following the water-gas shift reaction, the product H2 continues on to be oxidized at the anode in
the same manner as if the SOFC were operating on H2. Furthermore, SOFC operation on CH4 may
proceed via the steam reforming of methane reaction, shown by the following:
Steam reforming: CH4 + H2O → CO + 3 H2
The resulting H2 undergoes anodic oxidation while the generated CO undergoes the water-gas shift
reaction to produce more H2.
Subsequently, the major advantages and disadvantages of SOFCs stem mainly from the
high operating temperatures and overall geometric design of the cell. Further, some disadvantages
arise due to the electrochemistry of the involved fuels, electrolyte, electrodes, and other
components of the cell assembly. For example, the main advantages of SOFC use include [1,2]:
39
High versatility – not limited to one type of fuel,
No precious metal catalyst requirements for operation (e.g. platinum),
Faster electrochemical kinetics due to high operating temperatures,
Solid-state electrolyte – allows for both planar and tubular geometric designs,
High efficiency and long life time.
Conversely, some disadvantages for SOFCs include [1,2]:
Difficult to find materials that can withstand such high temperatures for extended periods
of time,
Constant reduction-oxidation (redox) cycling implies that nickel is constantly being
converted from Ni to NiO – leads to volume changes and potential cracking of electrodes,
Graphite formation by the Ni-catalyzed cracking of hydrocarbons leads to carbon
deposition at the anode and ultimate reduction in cell performance,
Susceptible to sulfur poisoning.
Although many challenges are presented by the listed disadvantages, extensive research is
being conducted in an attempt to address the concerns. For example, much research focuses on
SOFC operating temperature reduction while avoiding the necessity for precious metals to catalyze
anodic fuel oxidation. Also, materials research is being undertaken to find alternative materials
which can withstand the high temperatures. Many studies also look at volume changes during
operation upon redox cycling and the subsequent effect on the structural integrity of the electrodes.
Finally, the subject of this report, much research has been conducted on the fuel flexibility of
SOFCs and the effects of fuel type and composition on overall cell performance.
3.2 Literature Review
Extensive research has been conducted and presented in the literature regarding SOFC
performance with the utilization of fuels other than H2. These include CO, CH4, and other
hydrocarbon fuels. Furthermore, experiments have been conducted using various fuel mixtures
including coal syngas, biomass syngas, and hydrocarbon mixtures.
The purpose of this review is to determine the effect of fuel type or composition on SOFC
performance. Additionally, the performance characteristics for the various fuel types and
compositions are compared and contrasted so as to highlight the optimal type and/or advantages
40
and disadvantages of the utilization of each. Performance characteristics under consideration
include voltage and power output for a given range of input current densities and cell lifetime over
an extended time period. Therefore, the following is a review of the aforementioned works and
research activities and summary of the main results and conclusions.
3.2.1 Performance Comparison of H2 and Hydrocarbons
Hydrocarbons present a plausible fuel for SOFCs since high temperature operation allows for their
direct oxidation in the cell. Further, Ni acts as an electrocatalyst for the direct oxidation of
hydrocarbons thereby enhancing their performance and potential usability in SOFCs.
For instance, Barnett et al. [2] operated an anode-supported Ni-YSZ SOFC on CH4 and
compared the results to that of H2 under the same conditions for various temperatures. The voltage
and power characteristic output curves obtained can be seen in Figure 3.2 below. The maximum
power output was greater for H2 at 1.44 W cm-2 than for CH4 at 1.27 W cm-2. Furthermore, higher
temperatures favoured greater performance in both cases. CH4, however, did produce higher open
circuit voltages (OCV) than H2 at the higher temperature measurements, especially that of 800 °C.
It was suggested that the slightly poorer performance of CH4 could be attributed to coking and
carbon deposition on the Ni-YSZ anode during cell operation.
Fig. 3.2. Voltage and power output curve comparison for (a) H2 and (b) CH4 [2].
Subsequently, Eguchi et al. [3] also studied the effect of CH4 fuel on SOFC performance.
However, mixtures of CH4, steam, and N2 in varying proportions were utilized as test fuel, and the
output voltages measured and recorded. The results can be seen in Figure 3.3. The results showed
41
that increasing CH4 fuel dilution with N2 led to reduced performance at all current densities. The
OCV also decreased with increasing N2 content. Furthermore, ethane (C2H6) and ethene (C2H4)
were also utilized as fuels and compared with CH4 [3]. The results can be seen in Figure 3.4. The
voltage characteristic curves for both ethane and ethene decrease more slowly with increasing
current density than CH4 shown in Figure 3.3. However, the increased carbon content of the former
two fuels accelerated carbon deposition in the anode and accordingly reduced the overall life of
the cell [3].
Fig. 3.3. Voltage output curves for various CH4-H2O-N2 mixtures [3].
Fig. 3.4. Voltage output curves for (a) ethane and (b) ethene [3].
42
In addition to CH4 and ethane, higher-order hydrocarbons such as propane (C3H8) and n-
butane (C4H10) were compared to H2 by Barnett and Madsen [4], using a La0.8Sr0.2Cr0.98V0.02O3
(LSCV) anode also containing Ce0.9Gd0.1O1.98 (gadolinium-doped ceria, or GDC) and 5 wt.-% NiO
for catalytic hydrocarbon oxidation. The SOFC performance using propane can be seen in contrast
to H2 in Figure 3.5. The performance for both fuels improved with increasing temperature.
However, H2 outperformed propane at every temperature and for all current densities tested.
Additionally, H2 achieved a maximum power output of 140 mW cm-2 at 750 °C while propane
reached the slightly lower value of 130 mW cm-2. Again, the weaker performance of the
hydrocarbon may be attributed to carbon deposition issues which ultimately reduce the
performance of the cell [4]. A summary of the results obtained by Barnett and Madsen for direct
utilization of hydrocarbon fuels can be seen in Table 3.2 below, including those for n-butane. The
table shows that H2 has the highest power output with the exception of propane, which is higher
for direct utilization of the fuels in the SOFC cell. Furthermore, all OCVs were roughly 800 mV,
and n-butane had the lowest maximum power density.
Table 3.2
Summary of performance data at 700 °C for H2 and various hydrocarbons. Adapted from [4].
Fuel Type Open circuit voltage
(mV)
Maximum current
density (mA cm-2)
Maximum power
density (mW cm-2)
Elapsed time in test
(h)
H2 785 508 114 362
CH4 770 490 107 266
C2H6 763 488 105 265
C3H8 801 430 128 195
C4H10 812 338 85 408
The performance characteristics of n-butane were further explored by Park et al. [5] using
a copper-ceria (Cu-CeO2) anode, as opposed to the conventional Ni-YSZ anodes. Unlike Ni, Cu
does not catalyze hydrocarbon oxidation and therefore avoids the issue of graphite formation and
subsequent carbon deposition in the anode. Regardless of this fact, the performance of n-butane
still did not match up to that of H2, as illustrated in Figure 3.6. In the figure, filled in shapes
represent data at 700 °C and open shapes correspond to data at 800 °C. Triangles represent H2 and
circles represent n-butane. H2 outperformed the hydrocarbon in terms of voltage and power output
at all tested current densities and for both tested temperatures. At 800 °C, H2 reached a maximum
power output of 0.31 W cm-2, whereas n-butane was less than two-thirds of that value at 0.18 W
cm-2. In fact, maximum power output for H2 at 700 °C was greater than that of n-butane at 800 °C.
43
Fig. 3.5. Voltage output curves for H2 and propane at different temperatures [4].
Fig. 3.6. Voltage and power output curve comparison for H2 and n-butane [5].
44
3.2.2 Performance Comparison of H2 and CO
As previously mentioned, CO is another potential SOFC fuel. SOFCs do not contain
platinum (Pt) catalysts as a result of the higher operating temperatures and consequently faster
electrochemical kinetics. Thus, Pt catalyst poisoning by CO, a major issue in polymer electrolyte
membrane fuel cells (PEMFCs), is not an issue in SOFCs. For example, Eguchi et al. [3] compared
the voltage outputs of H2-H2O and CO-CO2 binary systems at 1000 °C. H2O and CO2 were present
in fixed compositions of 0.6 and 0.5%, respectively. The study was conducted with increasing
amounts of N2 diluent, as illustrated in Figure 3.9. No major decrease in performance was observed
for either H2 or CO when dropping their respective compositions to 66.6 and 77.1% suggesting
that some fuel dilution will not significantly affect voltage output. This phenomenon has
implications in fuel costs savings, since the utilization of less fuel leads to a similar output.
Furthermore, H2 outperformed CO at all tested dilution levels at the test temperature of 1000 °C.
This occurred in spite of similar OCVs in both cases [3].
However, in contrast to the findings of Eguchi et al., Jiang and Virkar [6] determined that
dilution of H2 fuel does, in fact, significantly reduce the voltage and power output of the cell, even
at smaller dilution levels. The findings are illustrated in Figure 3.10. It is clear that even at the 15%
N2 level, the performance of the SOFC was significantly reduced when compared to pure H2. This
effect remained for all dilution levels tested. Additionally, the same effect was noticed for voltage
and power output when using helium (He), H2O, and CO2 as diluents at the same temperature [6].
Diluting CO with CO2 and operating in the same SOFC at the same temperature showed similar
results. These can be seen in Figure 3.11. Cell performance greatly reduced with each dilution
level of CO2. This is especially seen in terms of the voltage characteristic curves. Further, it is
important to note that the maximum power achieved by pure CO, roughly 0.7 W cm-2, was much
less than that of pure H2, approximately 1.8 W cm-2. The weaker performance of CO may be
attributed to greater concentration polarization at the anode and slower oxidation of CO than H2
[6].
45
Fig. 3.7. Voltage output curves comparing H2-H2O and CO-CO2 systems at 1000 °C with N2 as a diluent [3].
Fig. 3.8. Effect of adding N2 diluent to H2 fuel on voltage and power output at 800 °C [6].
46
Fig. 3.9. Effect of adding CO2 diluent to CO fuel on voltage and power output at 800 °C [6].
Finally, Jiang and Virkar [6] also tested mixtures of H2 and CO under the same
aforementioned conditions. The results are summarized in Figure 3.12 below. It can be seen that,
generally, increasing CO composition hindered cell performance in terms of both voltage and
power output, with the exception of the 14% CO-86% H2 mixture. This mixture outperformed pure
H2 in terms of power output. Thus, it was found that performance remained high given that H2
concentration remained above the approximate value of 50%, as the balance CO generates more
H2 via the water-gas shift reaction [6].
Moreover, H2-CO binary systems provide different results depending on the anode used in
the SOFC. Vohs et al. [7] compared H2 and CO performance in SOFCs for Cu-CeO2-YSZ and Ni-
YSZ anode-supported cells. Figure 3.13 demonstrates the performance characteristics of each
anode type at 700 °C. The squares represent H2, circles represent CO, and diamond shapes
represent syngas. It is evident that the OCVs of all three fuel types are higher for the Cu-CeO2-
YSZ anode. Further, the slope of the voltage curve for CO is far less steep for that anode as well.
In fact, it is very similar to that of H2, which is evidently not the case for the Ni-YSZ anode. Thus,
CO performance becomes closer to that of H2 with the use of a Cu-CeO2-YSZ anode. This is
because Ni does not catalyze CO oxidation. This effect was also readily apparent when H2 and CO
were mixed with n-butane and tested under the same conditions. 90% mixtures were made of each
47
– with the balance being n-butane – and the resulting voltage characteristic curves were only
slightly less than that of pure H2 or CO. Further, the slopes of the curves were all very similar [7].
Fig. 3.10. Voltage and power output for various H2-CO mixtures [6].
Fig. 3.11. Comparison of H2, CO, and syngas performance with (A) Cu-CeO2-YSZ and (B) Ni-YSZ anodes [7].
Correspondingly, Wang et al. [8] found that a Cu-CeO2 coating over the Ni-YSZ anode
under H2-CO conditions greatly improved cell performance. The optimal mixture composition was
found to be 65% H2-32% CO-3% H2O. The cell operating on this mixture at 750 °C ran for 1050
48
hours without any notable decrease in performance or materials degradation. Figure 3.14
summarizes the obtained data. Increasing CO content again decreased cell performance, in
accordance with the other data presented in this section.
Fig. 3.12. Effect of increasing CO content on voltage and power output using Cu-CeO2-coated Ni-YSZ anode [8].
3.2.3 Performance Comparison of H2 and Syngas
Syngas derived from coal or biomass sources can be used in SOFCs due to their relatively
high concentrations of H2, CO, CH4, and various other hydrocarbons. For example, Figure 3.8 of
Section 3.2.2 compares the voltage and power outputs for a 25 kW SOFC system operating on
biogas and coal syngas. It can be seen that biogas produces favourable performance when
compared to coal syngas [9].
Furthermore, Figure 3.13 compares syngas data to H2 and CO at 700 °C. It can be seen that
syngas underperforms when compared to H2 and CO when the Cu-CeO2-YSZ anode is utilized,
but greatly outperforms CO when using the standard Ni-YSZ anode. This result is attributed to the
fact that Ni does not catalyze the electrochemical oxidation of CO; however it will make use of
the H2 present in syngas [7].
Moreover, extensive research has been conducted in regards to the direct utilization of the
products of biomass gasification in SOFCs. Such a study was conducted by Panapoulos et al. [10]
49
wherein a 100 kWth circulating fluidized bed gasifier was used to produce heavy tar (i.e.
hydrocarbon) loadings (> 10 g Nm-3) and fed to a SOFC using a Ni-GDC (gadolinium-doped ceria)
anode. No carbon deposition was found upon inspection of the Ni-GDC anode and cell voltages
upwards of 787 mV were produced at a current density of 130 mA cm-2. This value corresponded
to a cell voltage of 811 mV under virtually tar-free conditions, resulting in a drop in performance
of less than 3%. It must also be noted that the sulfur content of the fuel, in the form of hydrogen
sulfide (H2S), was controlled via feed stream pre-treatment [10].
3.2.4 Performance in the Presence of Sulfur
The presence of sulfur in the fuel feed stream to a SOFC can poison the Ni catalyst and
significantly reduce cell voltage and power output. Sulfur blocks reaction sites on the Ni catalyst
which is thereby unable to catalyze oxidation reactions, significantly increasing concentration
polarization and ultimately worsening cell performance. Figure 3.15 [11] summarizes the effects
of the presence of sulfur at various concentrations at 1000 °C and a current density of 0.3 A cm-2.
Fig. 3.13. Concentration polarization effects from sulfur poisoning after (a) addition and (b) removal [11].
As such, Matsuzaki and Yasuda demonstrated that the greater the concentration of sulfur,
the higher the overvoltage, or voltage consumed due to the aforementioned concentration
polarization effects. Further, it is important to note that sulfur poisoning effects were reversed upon
the removal of sulfur, regardless of the concentration, and overvoltage due to concentration
polarization returned to normal levels within approximately 50 min [11].
50
3.3 Research Impact
The ability to predict the performance of a SOFC based on the fuel fed to it has implications
for the entire SOFC industry and any industries or academic settings that wish to employ SOFCs
as a major part of fulfilling their energy requirements. Different fuel types will be available
depending on where the fuel is being purchased and/or acquired from, and thus the utilized SOFC
can be tailored to suit that fuel type/composition. For example, if fuel is being acquired from
gasified biomass sources, knowledge of the performance of H2-CO, CO-CO2, CH4, and other
syngas constituent mixtures would allow for optimal SOFC selection. Accordingly, different
SOFC types and designs would be used for different fuel types. Subsequently, knowledge of the
energy requirements for the given application would aid in the designing and implementing of an
appropriate SOFC. Thus, prior knowledge of the fuel type and amounts of power that fuel can
generate would further help the process of selection.
Increased knowledge of the effects fuel type and composition play on SOFC performance
could lead to a catalogue or guidebook of commercial SOFCs that are ready to be ordered. The
consumer, whether private or public, could simply choose their desired SOFC based on their
available fuel type and energy requirements. Such a system would eliminate complications
inherent to designing SOFCs on a case-by-case basis and greatly contribute to the use of renewable
technologies. Furthermore, adapting SOFCs to accommodate for as-received fuel types would
eliminate costly and energy-intensive process steps such as fuel gas cleaning and pre-treatment.
The SOFC would then simply use the “contaminant” gases as fuel.
Furthering knowledge in this research area is likely to continue in both the near and long-
term future. Extensive research is already conducted regarding the performance of SOFCs under
various fuel types, as explained in previous sections of this review. Continuing investment into
research and development activities in this research area are required for further breakthroughs
and for further understanding of the effect of more fuel types and compositions under varying
operating conditions such as temperatures, pressures, and current densities. Creating interest
amongst researchers, both younger and older, is also of paramount importance in regards to
ensuring more advances in this research area in the near future.
51
3.4 Concluding Remarks
In conclusion:
1. Increasing temperature favoured an increase in performance for all fuel types and
compositions.
2. H2 outperformed CH4 both in terms of voltage and power output.
3. H2 outperformed ethane (C2H6), ethene (C2H4), propane (C3H8), and n-butane (C4H10).
Higher-order hydrocarbons showed better performance than lower-order ones due to a
greater number of electrons released upon oxidation; however the issue of graphitic carbon
deposition at the anode became worse.
4. H2 outperformed CO under most conditions tested.
a. Increasing CO content in H2-CO mixtures generally reduced overall performance.
b. Dilution of H2 with N2, He, or H2O and CO with CO2 reduced cell performance but
presented a trade-off between fuel cost savings and performance.
5. Ni-GDC (gadolinium-doped ceria) anodes could effectively handle high tar loadings
present in fuel streams from biomass gasification. Sulfur (present in the form of H2S)
removal was required as pre-treatment.
6. The presence of sulfur greatly contributed to concentration polarization. Upwards of 290
mV of overvoltage were consumed under the presence of 15 ppm H2S at 1000 °C and 0.3
A cm-2 current density.
7. Knowledge of SOFC performance based on fuel input would allow for appropriate
selection of SOFC designs to fit given energy requirements and on-hand fuel types and
compositions.
52
References
[1] Minh, N.Q. “Solid Oxide Fuel Cell Technology – Features and Applications.” Solid State Ionics 174 (2004):
271-77.
[2] Barnett, S., Lin, Y., Z. Zhan, and J. Liu. "Direct Operation of Solid Oxide Fuel Cells with Methane
Fuel." Solid State Ionics 176.23-24 (2005): 1827-835.
[3] Eguchi, K., H. Kobo, T. Takeguchi, R. Kikuchi, and K. Sasaki. "Fuel Flexibility in Power Generation by
Solid Oxide Fuel Cells." Solid State Ionics 152-153 (2002): 411-16.
[4] Barnett, S., and Madsen, B. "Effect of Fuel Composition on the Performance of Ceramic-based Solid Oxide
Fuel Cell Anodes." Solid State Ionics 176.35-36 (2005): 2545-553.
[5] Park, S., J.M. Vohs, and R.J. Gorte. “Direct Oxidation of Hydrocarbons in a Solid-Oxide Fuel Cell.” Nature
404 (2000): 265-67.
[6] Jiang, Yi, and Anil V. Virkar. "Fuel Composition and Diluent Effect on Gas Transport and Performance of
Anode-Supported SOFCs." Journal of the Electrochemical Society 150.7 (2003): A942-951.
[7] Vohs, J.M., O. Costa-Nunes, and R.J. Gorte. “Comparison of the Performance of Cu-CeO2-YSZ and Ni-
YSZ Composite SOFC Anodes with H2, CO, and Syngas.” Journal of Power Sources 141 (2005): 241-49.
[8] Wang, S.R., Xiao-Feng Ye, J. Zhou, F.R. Zeng, H.W. Nie, and T.L. Wen. "Assessment of the Performance
of Ni-yttria-stabilized Zirconia Anodes in Anode-supported Solid Oxide Fuel Cells Operating on H2–CO
Syngas Fuels." Journal of Power Sources 195.21 (2010): 7264-267.
[9] Samuelsen, G., Yi, Y., A. Rao, and J. Brouwer. "Fuel Flexibility Study of an Integrated 25kW SOFC
Reformer System." Journal of Power Sources 144.1 (2005): 67-76.
[10] Panopoulos, K.D., Hofmann, Ph., P.V. Aravind, M. Siedlecki, A. Schweiger, J. Karl, J.P. Ouweltjes, and
E. Kakaras. "Operation of Solid Oxide Fuel Cell on Biomass Product Gas with Tar Levels 10 g
Nm−3." International Journal of Hydrogen Energy 34 (2009): 9203-212.
[11] Matsuzaki, Yoshio, and Isamu Yasuda. “The poisoning effect of sulfur-containing impurity gas on a SOFC
anode: Part I. Dependence on temperature, time and impurity concentration.” Solid State Ionics 132 (2000):
261-69.
53
Chapter IV
Chemical Looping Gasification for Hydrogen Production – A
Comparison of Two Unique Processes Simulated Using Aspen
Plus
4.1 Introductory Remarks
Hydrogen (H2) has the potential to shift the global reliance on fossil fuel energy sources to cleaner,
more efficient forms of energy as it presents a viable alternative. The issues of global carbon
dioxide (CO2) and other greenhouse gas (GHG) emissions and overall atmospheric concentration
can also be addressed with the utilization of H2 technologies for the generation of energy.
Furthermore, H2 presents an advantage over other conventional alternative energies such as wind
and solar due to its energy storage and transport capabilities. Thus, H2 utilization has the potential
to become widespread in the near future.
Current methods of H2 production involve the reforming of fossil fuels; processes that
ultimately contribute to the societal and environmental issues mentioned above. Correspondingly,
contemporary H2 energy systems are neither GHG-neutral nor sustainable since these non-
renewable fossil fuels are responsible for equivalent CO2 emissions. Thus, it is essential that H2 be
produced from a renewable, carbon-neutral energy source. The thermochemical gasification-based
conversion of biomass in the presence of steam presents a viable renewable H2 source and is a
strong contender for the replacement of fossil fuel-based H2 production.
Chemical looping gasification (CLG) using biomass fuel is an example of such H2 energy
technologies as it capitalizes on renewable, environmentally friendly, and abundant sources of
energy. Biomass is an organic fuel source containing carbon, hydrogen, oxygen, nitrogen, and
sulfur, and can come in the form of agricultural wastes, municipal solid wastes, animal wastes,
saw dust, etc. [1]. The gasification of biomass involves thermochemical conversion to H2, as well
as various hydrocarbons, for subsequent use in H2 conversion technologies with the aim of energy
production. Furthermore, biomass gasification is a complex, endothermic process consisting of
many chemical reactions. These reactions depend on the gasification agent being used which is
commonly steam. The reactions are summarized in Table 4.1 [2].
54
Table 4.1
Chemical reactions in the steam gasification of biomass. Adapted from [2].
Reaction Chemical Equation ΔHo923 (kJ mol-1)
Water-gas shift CO + H2O → CO2 + H2 -35.6 (exothermic)
Methane reforming CH4 + H2O → CO + 3H2 225 (endothermic)
Water-gas (i) C + H2O → CO + H2 136 (endothermic)
Water-gas (ii) C + 2 H2O → CO2 + 2H2 100 (endothermic)
Oxidation (i) C + O2 → CO2 -394 (exothermic)
Oxidation (ii) C + ½ O2 → CO -112 (exothermic)
Boudouard C + CO2 → 2CO 171 (endothermic)
Methanation C + 2H2 → CH4 -89.0 (exothermic)
At the present time, minimal research has been conducted regarding CLG systems
development. Moreover, the major research focus involves the chemical looping combustion
(CLC) process, with emphasis on oxygen carrier development for use in CLC. Though widely
recognized by many researchers, work conducted on the CLG process developed by Fan et al. at
Ohio State University [3] requires further research and development to become a fully-
implemented, renewable H2 production technology. Furthermore, other advanced chemical
looping systems exemplar of CLG processes for the purpose of H2 production include the HyPr-
RING (Hydrogen Production by Reaction-Integrated Novel Gasification), fuel-flexible advanced
combustion-gasification, ALSTOM hybrid gasification-combustion, Advanced Gasification-
Combustion (AGC), and Zero Emission Coal Alliance (ZECA) processes [3-5].
The mitigation and subsequent elimination of sorbent/catalyst performance degradation
over time is an ongoing challenge in most chemical looping systems. Successful operation of
chemical looping systems is often jeopardized by unpredictable sorbent behaviour. Thus, research
has been conducted to identify the mechanisms contributing to sorbent losses and develop
performance improvement methods to ensure sufficient system operation and longevity.
Subsequently, sintering of the chemical looping sorbent particles as a result of high-temperature
operation and cyclic heating/cooling cycles, in conjunction with char and tar deposition,
significantly reduces sorbent capture and regeneration capabilities. The detrimental effects of these
phenomena are most notably felt in CLG systems. Another challenge presented by chemical
looping systems involves the continuous flow of solid materials between a multitude of
interconnected reactors operating at high temperatures and pressure [6].
The CLG of biomass is advantageous in that it is a clean, renewable source of H2; however
some disadvantages remain prominent. For example, product syngas streams resulting from the
55
CLG of biomass contain many impurities. Consequently, much research has been conducted
regarding syngas impurity removal, whether it be the end-of-pipe or in situ approaches. Therefore,
the research compares two different CLG processes under similar feed and operating conditions
for the purpose of H2 production using a computer simulation. The novelty of the conducted
research lies in the development of the two CLG processes using the Aspen Plus simulation
software and subsequent comparison of the results using the same biomass feedstock in both cases.
The paper also includes temperature and pressure sensitivity analyses conducted on all
relevant reactors and the results compared between the CLG 1 and CLG 2 processes. Relevant
parameters included optimal operating temperature and pressure for each reactor and product
syngas molar yield and composition. Comparison of the H2 production and purity capabilities of
the two processes is emphasized upon.
4.1.1 Simulated Processes
Two CLG mechanisms were simulated and analyzed using the Aspen Plus V7.3 software. The
simulation results were compiled for poultry litter (PL), a nonconventional biomass type.
4.1.1.1 Chemical Looping Gasification Type 1
The first CLG simulation (CLG 1) incorporated in situ product CO2 capture in the absorbing
reactor with the use of a CaO sorbent. A representative block diagram can be seen in Figure 4.1.
CO2 absorption occurs according to the following chemical reaction [7]:
CaO (s) + CO2 (g) → CaCO3 (s)
This reaction is exothermic with a heat of reaction of -178.3 kJ mol-1 [7]. In addition, near-total
CaO sorbent recovery and recycle was inherent to the simulation setup. CO2 desorption is the
reverse of CO2 absorption and is therefore an endothermic reaction. The energy required for the
reaction to occur is provided by the higher operating temperature of the desorbing reactor. The
resulting theoretical product stream is pure CO2 which can be sent for sequestration. Furthermore,
the overall reaction prior to sorbent regeneration is as follows:
CnHmOp + (2n – p) H2O + n CaO → n CaCO3 + (m/2 + 2n – p) H2
This overall reaction is endothermic with a heat of reaction of +107.5 kJ mol-1 [6]. The constants
n, m, and p represent the respective carbon, hydrogen, and oxygen contents in the biomass being
gasified.
56
Fig. 4.1. CLG 1 simulation block diagram.
Another key aspect of the CLG 1 simulation is the use of steam (H2O (g)) to address the
issue of tar and char formation. Tar and char were modelled as pure carbon and the reforming
reactions correspond to water-gas (i) and water-gas (ii) from Table 4.1 as follows:
C(s) + H2O (g) → CO (g) + H2 (g)
C(s) + 2 H2O (g) → CO2 (g) + 2 H2 (g)
These reactions were assumed to reform all tar compounds exiting the desorbing reactor.
Furthermore, the use of steam is preferable to conventional air since the thermo-oxidative
reforming of pure carbon in air results in a nitrogen (N2) stream which must be subsequently
separated from the CO2 product stream. This process is energy-intensive and therefore costly [8],
however the condensation of steam from an exit gas stream can also be a costly process. A more
practical process schematic illustrating an overview of the CLG 1 process can be seen in Figure
4.2.
57
Fig. 4.2. CLG 1 process schematic [6].
4.1.1.2 Chemical Looping Gasification Type 2
Subsequently, syngas chemical looping is another H2-production process involving the
gasification of biomass. This process separates the gasification and looping stages and produces
H2 via reduction, oxidation, and combustion cycles involving iron (Fe), hematite (Fe2O3 or iron
(III) oxide), and magnetite (Fe3O4 or iron (II,III) oxide) [6]. This process was simulated using
Aspen Plus V7.3 using poultry litter as the chosen biomass type (CLG 2). The block diagram for
the CLG 2 process can be seen in Figure 4.3.
58
Fig. 4.3. CLG 2 simulation block diagram [3].
Similarly to CLG 1, CLG 2 is comprised of many chemical reactions involving a multitude
of reactors. These reactions and corresponding reactors are outlined in Table 4.2 [3]. The reactions
persist under theoretical conditions. In actuality, tar formation in the reducer is unavoidable. Tar
reforming in the CLG 2 simulation is carried out in the oxidizer, where large amounts of steam are
introduced. Here, tar is completely reformed by the steam to CO, CO2, and H2 via the
aforementioned water-gas reactions presented in Table 4.1. Additionally, pure O2 is utilized in the
combustor as opposed to air for the same reasons explained for steam in the CLG 1 simulation [8].
Table 4.2
Chemical reactions in syngas chemical looping [3].
Reactor Chemical Equation Description
Gasifier Biomass + H2O → H2 + CO Steam gasification of biomass.
Combustor 4 Fe3O4 + O2 → 6 Fe2O3 Forms Fe2O3 for reducer.
Reducer 3 CO + Fe2O3 → 3 CO2 + Fe
3 H2 + Fe2O3 → 3 H2O + 2 Fe
Forms Fe for oxidizer and CO and
H2O to be separated.
Oxidizer 3 Fe + 4 H2O → Fe3O4 + H2 Forms product H2 and Fe3O4 for
recycle to combustor.
59
4.2 Feedstock Used
4.2.1 Composition of Biomass Types
The characteristics of three biomass types were compared to identify a suitable feedstock for
utilization in the two simulations. The types are: poultry litter, wood pellets, and oak pellets. The
biomass types vary in their chemical composition and are thus representative of a spectrum of
biomass types, with poultry litter representing a nonconventional type. Table 4.3 summarizes
ultimate analyses of poultry litter while Table 4.4 summarizes its proximate analysis.
Table 4.3
Ultimate analysis of poultry litter in both the presence and absence of sulfur and nitrogen.
Mass Composition (wt.-%)
Element Sulfur and Nitrogen Present Sulfur and Nitrogen Absent
Carbon 43.30 46.49
Hydrogen 6.62 7.11
Oxygen 5.95 6.39
Nitrogen 5.72 -
Sulfur 1.15 -
Ash 37.26 40.01
Table 4.4
Proximate analysis of poultry litter.
Parameter Mass Composition (wt.-%)
Moisture Content 20.10
Fixed Carbon 3.33
Volatile Matter 54.29
Ash 22.28
4.2.2 Chemical Equations for Gasification of Biomass Types
Each biomass type was assumed to gasify according to the following chemical formula [9]:
CnHmOp + (n – p) H2O → n CO + (m/2 + n – p) H2
The ultimate analysis of each biomass type assuming an absence of both sulfur and nitrogen was
used to calculate the n, m, and p values in the equation above. Moreover, the chemical composition
of each biomass type varied in terms of hydrogen and oxygen content, and was calculated relative
to carbon molar content. The corresponding chemical formulas for each of the biomass types were
found to be CH0.01286O0.1831, CH0.00973O0.6331, and CH0.01061O0.8667 for poultry litter, willow pellets,
and oak pellets, respectively. Poultry litter can be seen to contain the greatest hydrogen and lowest
60
oxygen content per mole of biomass. Consequently, the chemical equation for the steam
gasification of poultry litter is as follows:
CH0.01286O0.1831 (s) + 0.8169 H2O (g) → CO (g) + 0.8234 H2 (g)
It is evident that the steam gasification equations for willow and oak pellets would be of the same
form as poultry litter but rather with different molar coefficients for steam consumption and lesser
values for H2 generation. Poultry litter generated the greatest theoretical H2 yield as roughly 0.82
moles were generated per mole of biomass and was therefore chosen as the biomass type to be
used for both the CLG 1 and CLG 2 simulations.
4.3 Simulation Input Parameters and Description
The following sections outline the input data to the Aspen Plus simulation engine as well as the
chosen calculation methods. Moreover, detailed descriptions of the utilized flowsheets are
provided.
4.3.1 Setup and Calculation Methods
The flowsheet type was chosen as “Solids with metric units”, allowing for the analysis and results
presentation for solid-state input and output streams. The setup of the flowsheet involved assigning
the MIXCINC stream class to the simulation. This allowed fluid and aqueous streams (MIXED),
conventional solid streams (CISOLID), and nonconventional solid streams (NC) to be input and
analyzed during simulation runs and calculations.
Subsequently, the process type was chosen as COMMON. This allotted a generic industry
type to the simulation, as opposed to chemical, petrochemical, pharmaceutical, etc. The IDEAL
base calculation method was selected for simplicity and thus phase equilibrium calculations were
conducted using Raoult’s Law, Henry’s Law, the ideal gas law, etc.
4.3.2 Component Definition and Input
Solid biomass was modelled using a user-defined, nonconventional solid based on ultimate,
proximate, and sulfur analyses. Thus, the input for the poultry litter biomass type was based on
these parameters. Sulfur analyses – including pyritic, sulfate, and organic – were set to zero.
Furthermore, the enthalpy and density of biomass were approximated using coal properties. The
methods used by Aspen Plus for these calculations are HCOALGEN and DCOALIGT,
respectively.
61
Fluid streams were modelled using conventional components which have thermophysical
data stored in Aspen Plus databanks. Therefore, no data input were required for these components.
The components include: hydrogen (H2), water (H2O), carbon monoxide (CO), carbon dioxide
(CO2), methane (CH4), and oxygen (O2).
Additionally, solid components were modelled using conventional solids which also have
necessary thermophysical data stored in the databanks. Tar formation was approximated as solid
carbon (i.e. graphite) in the simulation. The components include: tar (C), calcium oxide (CaO),
calcium carbonate (CaCO3), iron (Fe), hematite (Fe2O3), and magnetite (Fe3O4). Calcium-based
components were exclusive to the CLG 1 simulation while iron-based components were exclusive
to the CLG 2 simulation, with fluid components being involved in both.
4.3.3 CLG 1 Flowsheet Description
The CLG 1 simulation flowsheet can be seen in Figure 4.4. The input and operating conditions for
all feed streams and block units are summarized in Tables 4.5 and 4.6, respectively.
Biomass and water at ambient conditions were fed to the gasifier after being heated to the
reactor temperature. This block gasified the biomass based on user-defined output for H2 and CO.
The output from the gasifier was then fed to the reforming reactor where further gasification
reactions occurred, resulting in H2, CO, CO2, CH4, tar, and steam formation. Subsequently, the
output from the reformer was fed to the absorbing reactor in conjunction with a CaO feed stream
used for CO2 absorption and capture. The solid and gaseous products from the absorber were then
separated with a gas-solid separator with an efficiency of 99.9%. The product gases were heated
to the WGS reactor temperature and further gasified to convert the majority of the remaining CO
to H2. Tar products contained in the WGS reactor exit stream were removed at a removal efficiency
of 99.9%, and sent to the desorbing reactor for steam reforming. The gaseous products of this
stream were subsequently condensed to remove most of the remaining steam and small amounts
of tar from the syngas, consequently increasing H2 purity in the product gas. It is important to note
that the gasification process was modelled with the combined use of the gasifying, reforming,
absorbing, and WGS reactor blocks rather than in a single reactor step. This resulted from
limitations inherent to the Aspen Plus block unit input capabilities.
62
Fig. 4.4. CLG 1 simulation flowsheet.
63
Table 4.5
Feed stream input conditions for CLG 1 simulation.
Feed Stream
Input Conditions
Temperature
(°C)
Pressure
(atm)
Flowrate
(kmol h-1) Component
BIOMASS 25 1 1a Biomass (Nonconventional)
H2O-FEED 25 1 1 H2O (Conventional)
CAO-FEED 25 1 6b CaO (Conventional Solid)
STEAM 240 1 85b H2O (Conventional) a Input as mass flowrate (kg h-1) using biomass molecular weight. b Fed in excess of required stoichiometric amount.
Table 4.6
Block unit operating conditions for CLG 1 simulation.
Block Information Operating Conditions
Name Type Temperature
(°C)
Pressure
(atm)
Other
GASIFIER RYield 750 1 Output based on set values for H2 and CO (units of kg /
kg total feed)
REFORMER RGibbs 750a 1d -
ABSORBER RGibbs 500b 1d -
WGS-RCTR RGibbs 750c 1d -
DESORBER RGibbs 650 1 -
HEATER Heater 750 1 -
HEAT-GAS Heater 750e 1 -
COOL-CAO Heater 25 1 -
COOL-GAS Heater 25 1 -
G-S-SEP1 Sep - -
Separated gaseous components (H2, CO, CO2, CH4, and
H2O) from 99.9% of solid components (C, CaO, and
CaCO3).
G-S-SEP2 Sep - - Separated DESORBER gases from 99.9% of CaO.
G-S-SEP3 Sep - - Separated syngas products from 99.9% of tar (C).
CONDENSE Flash2 20 5 - a Represents optimal operating temperature. Reformer temperature was varied from 500 to 900 °C. b Represents optimal operating temperature. Absorber temperature was varied from 300 to 800 °C. c Represents optimal operating temperature. WGS reactor temperature was varied from 400 to 1000 °C. d Represents optimal operating pressure. Pressure was varied from 1 to 20 atm. e HEAT-GAS heater temperature was set to the WGS reactor temperature being simulated.
Furthermore, the solids stream exiting the initial gas-solid separator containing CaCO3, tar,
and unused CaO was fed to the desorbing reactor, along with tar products from the WGS reactor
exit. Here, CaCO3 was thermally dissociated into CaO and CO2, whereas all of the present tar was
reformed to CO, CO2, and H2 with the use of steam. An additional gas-solid separator was utilized
to separate the resulting solids (CaO and remaining tar) and desorber gases. The unused and
regenerated CaO stream was cooled to ambient temperature and sent for re-use in the absorber.
64
Further, the resulting CO2-rich stream was also cooled to ambient temperature and sent for
sequestration.
4.3.4 CLG 2 Flowsheet Description
The CLG 2 simulation flowsheet can be seen in Figure 4.5. The input and operating conditions for
all feed streams and block units are summarized in Tables 4.7 and 4.8, respectively.
Biomass and water at ambient conditions were fed to the gasifier after being heated to the
reactor temperature. This block gasified the biomass based on user-defined output for H2 and CO.
The output from the gasifier was then fed to the reducer. Conversion of Fe3O4 to Fe2O3 via
combustion using pure O2 was carried out to facilitate Fe-generating reduction reactions, of which
the product Fe was further oxidized using H2O for H2 production. As such, the Fe2O3 resulting
from combustion was combined with the gasification products in the reducer. Here, Fe2O3 was
reduced to Fe and the gasification products underwent the various gasification reactions, resulting
in H2, CO, CO2, CH4, tar, and steam. The solid-state and gaseous products were separated in the
cyclone at a solids removal efficiency of 99.9%. The gases were then fed to the reforming reactor
while the Fe and tar were fed to the oxidizing reactor for Fe3O4 regeneration. Furthermore, CH4
completely reformed to CO and H2 in the oxidizer. The oxidizer exit gases and solids were then
separated in a secondary cyclone, with over 99.8% regenerated Fe3O4 to be recycled to the
combustor and gases fed to the reformer.
Consequently, the reducer and oxidizer exit gases were further reformed to H2 and CO2 in
the reformer to increase the H2 yield of the system. Small amounts of CH4 were regenerated in the
reformer. The reformer exit gases were next fed to a condenser to remove most of the remaining
steam and residual solids from the resulting syngas. This increased H2 purity in the syngas. CO2
capture was not inherent to CLG 2 as was the case with CLG 1.
65
Fig. 4.5. CLG 2 simulation flowsheet.
66
Table 4.7
Feed stream input conditions for CLG 2 simulation.
Feed Stream
Input Conditions
Temperature
(°C)
Pressure
(atm)
Flowrate
(kmol h-1) Component
BIOMASS 25 1 1a Biomass (Nonconventional)
H2O-IN 25 1 1 H2O (Conventional)
FE3O4-IN 25 1 0.0370b Fe3O4 (Conventional Solid)
O2 25 1 0.10b O2 (Conventional)
STEAM 240 32 20 H2O (Conventional) a Input as mass flowrate (kg h-1) using biomass molecular weight. b Required stoichiometric amount for down-stream reducer reactions to occur.
Table 4.8
Block unit operating conditions for CLG 2 simulation.
Block Information Operating Conditions
Name Type Temperature (°C) Pressure
(atm)
Other
GASIFIER RYield 750 1 Output based on set values for H2 and CO
(units of kg / kg total feed)
COMBUST RGibbs 1250 1 -
REDUCER RGibbs 870 30 -
OXIDIZER RGibbs 720 30 -
REFORMER RGibbs 500 1 -
HEATER Heater 750 1 -
CYCLONE Sep
- - Separated 99.9% of Fe and tar (C) from
reducer exit gases (H2, CO, CO2, H2O, and
CH4).
CYCLONE2 Sep
- - Separated 99.9% of Fe3O4 from oxidizer
exit gases (H2, CO, CO2, and H2O)
CONDENSE Flash2 20 1 -
4.4 Results and Discussion
Important assumptions were initially applied to the simulation to ensure that it ran smoothly and
produced results. These included:
1. Chosen biomass types contained no nitrogen or sulfur.
2. Biomass and steam reacted completely in the first gasification reactor (i.e. the gasifier) and
the only products were H2 and CO.
3. Tar by-products formed in the various reactors were pure carbon.
4. Tar reforming using steam in the CLG 1 simulation was 100% efficient.
5. CO2 desorption from CaCO3 in the CLG 1 simulation was 100% efficient.
6. Gas-solid separators were 99.9% efficient.
67
The following sections detail the results obtained from both simulations using poultry litter.
Temperature and pressure sensitivity analyses were conducted for each of the main reactors to
determine the optimal operating conditions for those reactors. The outputs to the gasifier were
specified as part of the simulation in both cases, and thus no sensitivity analysis could be carried
out on those block units.
Furthermore, the reactor type utilized for the absorber, WGS reactor, desorber, combustor,
reducer, oxidizer, and both reformers was RGibbs. This reactor is an Aspen Plus block unit which
calculates its output using the Gibbs free energy minimization method. The calculations are based
on the chemical equilibrium reactions of the components being input to the reactor under the
specified operating conditions.
4.4.1 Determining the Optimal Operating Conditions
4.4.1.1 CLG 1 Results
The reformer in the CLG 1 simulation aimed to produce more H2 following the gasifier via CO
conversion. The aforementioned gasification equations occurred simultaneously, resulting in by-
product formation in the output stream. The results of the reformer temperature sensitivity analysis
can be seen in Figure 4.6, which shows that H2 and CO yield at the reformer exit increased with
increasing operating temperature. Further, by-product formation, aside from CO, tended to
decrease with temperature, and sharply so at the higher end of the temperature scale. These
phenomena are the result of the gasification equations proceeding in the reformer. The forward
reactions favour H2 and CO production and are endothermic. Thus, increasing temperature
favoured the formation of these species. As a result, the optimal operating temperature was subject
to debate based on the criterion of higher H2 yield versus greater H2 purity. The temperature of
750 °C was chosen as optimal since H2 yield was relatively high at this point while CO yield had
not yet reached its highest value. Moreover, by-product yield was relatively low at this
temperature. The trends observed for the reformer temperature sensitivity analysis closely
reflected those found by Mahisi et al. [8]. However, ethanol (C2H5OH) was used as the source
biomass in that case.
Next, the results of the pressure sensitivity analysis on the reformer can be seen in Figure
4.7, which illustrates that the opposite phenomenon from temperature sensitivity occurred. Both
H2 and CO yield began to decrease rapidly with increasing pressure, especially within the first five
atmospheres of pressure increase. Correspondingly, other by-product formation increased rapidly
68
within the first five atmospheres. Due to the relatively large reduction in H2 yield and rapid rise of
by-product formation at higher pressures, atmospheric pressure was determined to be optimal for
the reforming reactor. The trends observed for the pressure sensitivity analysis also closely
reflected those observed by Mahisi et al. [8].
Fig. 4.6. CLG 1 reformer temperature sensitivity analysis.
Furthermore, the main goal of the absorber was to capture generated CO2 using CaO as the
sorbent. As previously mentioned, this is an exothermic equilibrium reaction which typically
occurs at temperatures from 600 to 650 °C. Absorber exit yield, CO2 capture efficiency, and CO2
product yield (i.e. CO2 sent for sequestration) were parameters of consideration. It was noted that
H2 yield tended to decrease at the absorber exit relative to H2 in the feed to the reactor. This
phenomenon was deemed a necessary sacrifice to ensure total CO2 capture, and was compensated
for further downstream with the use of the WGS reactor.
0
0.2
0.4
0.6
0.8
1
1.2
500 550 600 650 700 750 800 850 900
Yie
ld:
km
ol/
km
ol
PL
Reformer Temperature (°C)
Reformer Exit Yield vs. Reformer Temperature
H2 CO CO2 CH4 Tar H2O
69
Fig. 4.7. CLG 1 reformer pressure sensitivity analysis.
A temperature sensitivity analysis was also conducted on the absorbing reactor. The
analysis showed that H2 production increased with increasing absorber temperature. Conversely,
CO2 production decreased until reaching a local minimum at 750 °C. Accordingly, CO2 capture
efficiency slowly decreased with temperature before being rendered totally ineffective at 750 °C.
Approximately 500 °C was concluded as the optimal operating temperature for the absorber, based
on H2 and CO2 production and CO2 capture efficiency. Higher CO2 production, relatively high H2
yield, and a CO2 capture efficiency of over 99% were all present at this temperature, which
occurred prior to the rapid decline in CO2 capture. Moreover, the pressure sensitivity analysis
conducted on the absorber yielded similar results to that of the reformer, and thus atmospheric
pressure was deemed optimal for the absorber. Both CO2 production and capture efficiency slightly
increased with pressure; however minimal gains, on the order of 0.01%, were observed and were
insufficiently beneficial to merit operating the absorber at higher pressures.
In addition, CO2 desorption was totally effective in the simulation. CaO sorbent recovery
was not, since 0.01% of the sorbent feed was lost due to inefficiencies in the gas-solid separators
throughout the process. In an experimental setting, however, greater amounts of sorbent would be
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Yie
ld:
km
ol/
km
ol
PL
Reformer Pressure (atm)
Reformer Exit Yield vs. Reformer Pressure
H2 CO CO2 CH4 Tar H2O
70
rendered ineffective as a result of calcium sulfate (CaSO4) formation from any sulfur components
present in the biomass feedstock [8], which was not considered in the conducted research. Thus,
greater amounts of sorbent regeneration would be required in experimental and real-life scenarios
than what is implied by the CLG 1 simulation.
Subsequently, the purpose of the WGS reactor was to provide a final block unit for H2
production as well as to regain H2 that was lost as a result of CO2 absorption in the absorbing
reactor. The lowered temperature required for CO2 absorption to proceed was unfavourable to H2
production and retention in the absorbing reactor. Both H2 yield and content significantly increased
as a result of the gasification reactions that occurred within the WGS reactor. Furthermore, H2
content in the syngas product stream was further upgraded with condenser utilization in the
following step. This block unit effectively liquefied the majority of the steam present in the WGS
reactor exit stream, thereby altering the syngas composition in favour of H2.
The results of the temperature sensitivity analysis conducted on the WGS reactor can be
seen in Figure 4.8. Both H2 and CO yield increased significantly after 500 °C with increasing
temperature, and then began to plateau at higher temperatures. Although the CO yield increase
with temperature was pronounced, the H2 to CO yield ratio remained very high due to low
concentrations of CO. Other by-product formation generally declined with increasing temperature
and was even negligible in the case of CO2. Accordingly, the optimal operating temperature for
the WGS reactor was found to be 750 °C, which provided relatively high H2 yield while
maintaining a lower total by-product yield. This temperature is considerably higher than the 300
°C value observed by Mahisi et al. [8]. However, H2 yield increased following WGS reactor
utilization in both CLG 1 and the simulation conducted by Mahisi et al. The reactor in that
simulation accounted for an 8% increase in H2 yield, while the CLG 1 simulation exhibited an
approximate 170% increase. The substantially larger increase in CLG 1 can be attributed to the
requirement for the regeneration of reduced amounts of H2 following the CO2 absorption step.
Additionally, the pressure sensitivity analysis conducted on the WGS reactor demonstrated that
atmospheric pressure was optimal. H2 production decreased and by-product formation increased
with pressure, similarly to trends observed for the previous reactors.
Overall, the optimal reactor temperatures for the CLG 1 simulation were 750 °C, 500 °C,
and 750 °C for the reformer, absorber, and WGS reactors, respectively. Therefore, a value of 750
°C was chosen for the gasifier as a conservative estimate. Moreover, this value is in agreement
71
with some gasifier temperatures utilized in coal-type or wood-type biomass gasification studies
outlined in the literature [10-20], and is 80 °C warmer than the value of 670 °C reported by Acharya
[6].
Fig. 4.8. CLG 1 WGS reactor temperature sensitivity analysis.
4.4.1.2 CLG 2 Results
Combustor operating conditions were chosen as 1250 °C and 1 atm based on data presented by
Fan [3]. These conditions proved sufficient to fully convert Fe3O4 to Fe2O3 via thermo-oxidation
given a stoichiometric excess of pure O2.
The CLG 2 simulation reducer aimed to generate Fe by reacting Fe2O3 with the H2 and CO
gasification products. By-product formation was evident in the simulation. These phenomena are
better illustrated in the temperature sensitivity analysis of Figure 4.9. The analysis was conducted
at 30 atm rather than atmospheric pressure as this was the recommended pressure proposed by Fan
[3]. Also, Fe formation was determined to be undesirably low at atmospheric pressure. Figure 4.9
displays that minimal increases in H2 and CO yield were initially observed before slowly
decreasing at the critical point of roughly 875 °C. Conversely, at this critical point, by-product
formation (CO2, H2O, CH4, and tar) tended to increase with temperature. Fe formation was
0
0.002
0.004
0.006
0.008
0.01
0.012
0.014
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
400 500 600 700 800 900 1000
Yie
ld:
km
ol/
km
ol
PL
(C
O,
CO
2,
H2O
)
Yie
ld:
km
ol/
km
ol
PL
(H
2an
d C
H4)
WGS Reactor Temperature (°C)
Syngas Yield vs. WGS Reactor Temperature
H2 CH4 CO CO2 H2O
72
virtually unaffected by temperature variation for the tested range. Therefore, 870 °C was chosen
as the optimal reducer temperature. This value was chosen due to its slightly lower cost
implications when compared to the critical point of 875 °C which was too proximate to the
decreasing portion of the H2 yield curve. Moreover, the optimal operating pressure of 30 atm was
confirmed via a pressure sensitivity analysis on the reducer, ranging from 30 to 37 atm, conducted
at the optimal temperature of 870 °C. H2 and CO production decreased with increasing pressure
while by-product formation increased, similar to the trends of the CLG 1 pressure sensitivity
analyses.
Fig. 4.9. CLG 2 reducer temperature sensitivity analysis.
In addition, the general purpose of the CLG 2 oxidizer was both to produce H2 in greater
quantities than the gasifier and to regenerate spent Fe3O4. The temperature sensitivity analysis for
the oxidizer was again conducted at 30 atm rather than atmospheric pressure as this was the
recommended pressure proposed by Fan [3]. The analysis demonstrated that temperature variation
only had a significant effect on CO and CH4 yield. CO increased relatively quickly with
temperature and quantities of CH4 were negligible below about 680 °C. Thus, 720 °C was chosen
as the optimal oxidizer temperature as only trace amounts CH4 were present, and negligible
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
870 872 874 876 878 880 882 884 886 888 890
Yie
ld:
km
ol/
km
ol
PL
Reducer Temperature (°C)
Reducer Exit Yield vs. Temperature at 30 atm
H2 CO CO2 H2O CH4 Tar Fe
73
changes in H2 yield were observed. Oxidizer pressure was incrementally increased to 40 atm to
determine pressure effects. However, minimal changes in component yield were observed in any
case, and 30 atm was confirmed as the optimal operating pressure. Finally 20 kmol h-1 was chosen
as the design feed steam flowrate to the oxidizer after flowrate variation analysis was conducted
from 5 to 25 kmol h-1 to determine the effects on component yields. The analysis was carried out
under steam conditions of 240 °C and 32 atm. By-product CO yield tended to decrease with
increasing flowrate, with other component species virtually unaffected, and so a higher flowrate
was chosen to minimize CO yield.
Fig. 4.10. CLG 2 reformer syngas yield temperature sensitivity analysis.
Subsequently, the CLG 2 reformer was meant to further increase H2 yield and content via
reforming of the remaining by-products. The temperature sensitivity analysis was conducted and
the optimal operating temperature chosen based on H2 yield and by-product levels present in the
syngas stream exiting the condenser unit at the process termination. The observed results from the
analysis can be seen in Figure 4.10. It can be seen that H2 and CO2 yield in the syngas begin to
decrease after reformer temperatures reach roughly 500 °C. CO yield increased rapidly over the
simulated range, albeit at lower concentrations throughout. CH4 yield rapidly decreased between
0
0.01
0.02
0.03
0.04
0.05
0.06
0.07
0.08
0.09
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
400 450 500 550 600 650 700 750 800 850
Yie
ld:
km
ol/
km
ol
PL
(C
O,
H2O
, C
H4)
Yie
ld:
km
ol/
km
ol
PL
(H
2an
d C
O2)
Reformer Temperature (°C)
Syngas Yield vs. Reformer Temperature
H2 CO2 CO H2O CH4
74
400 and 500 °C. H2 yield tended to peak at approximately 1.60 kmol / kmol PL. In addition, syngas
composition was closely examined under varying temperature conditions. The respective
component curves had roughly the same shape as the syngas yield curves which are illustrated in
Figure 4.10. H2 and CO2 comprised the majority of the syngas with CO, H2O, and CH4 by-products
accounting for smaller percentages. Again, H2 composition peaked in the 450 to 500 °C range and
began to decrease with further temperature increase.
Based on the aforementioned trends, 500 °C was chosen as the optimal operating
temperature for the CLG 2 reforming reactor. This is due to both higher H2 yield and content in
the resulting syngas stream, as well as lower by-product yields and compositions in proximity to
this temperature. Increasing operating pressure above atmospheric conditions tended to decrease
desirable product yield and correspondingly increased by-product yield and concentration. Thus,
a detailed pressure sensitivity analysis was not further pursued for the CLG 2 reformer.
4.4.2 Comparison of Simulation Results
The following section details a comparison between the results of the two biomass gasification
simulations. Comparisons are made based on syngas yield and composition.
4.4.2.1 Syngas Yield Comparison
A comparison of the absolute syngas yields for the CLG 1 and CLG 2 simulations can be seen in
Figure 4.11. It is evident that CLG 2 generated more syngas than CLG 1, at values of roughly 2.54
and 0.79 kmol / kmol PL, respectively. However, it is also important to note that CO2 removal was
not a focal point of CLG 2, and thus almost 0.87 kmol CO2 / kmol PL adds to the absolute CLG 2
syngas value. Furthermore, H2 can be seen to be the main constituent in both cases, with the CLG
2 syngas producing more H2 in absolute terms.
CLG 1 generated 0.73 kmol H2 / kmol PL while CLG 2 generated 1.60 kmol H2 / kmol PL.
These values are less than those reported in the literature for either case. Processes similar to CLG
1 reported H2 yields ranging from 1.6 to roughly 5.7 kmol H2 / kmol biomass [2,8], while Fan
outlined a process similar to CLG 2 capable of producing approximately 11.73 kmol H2 / kmol
coal [3]. The latter process, however, used coal as the solid fuel and greater amounts of iron-based
oxygen carriers than CLG 2.
Furthermore, the assumption that all biomass and steam were completely converted to H2
and CO in the gasifier was challenged, and its effect on syngas yield in both cases was determined.
75
This was done in terms of conversion efficiency, labelled as gasifier efficiency. The analyses
showed that the yields of all syngas components linearly decreased with a decrease in gasifier
efficiency. It is also noted that the reduction in H2 yield from 100 to 50% gasifier efficiency is
relatively drastic; 0.73 to 0.36 kmol / kmol PL.
Fig. 4.11. Comparison of simulation syngas yields.
4.4.2.2 Syngas Composition Comparison
A comparison of the syngas compositions in either simulation can be seen in Figure 4.12, which
also includes individual component compositions. It can be seen that H2 is the main component in
either syngas stream, at 92.45 mol-% and 62.94 mol-% for CLG 1 and CLG 2, respectively. The
former value is greater than the 80.94% H2 value reported by Acharya under similar conditions.
Further, the CO2 concentration of 0.01% in CLG 1 syngas is significantly lower than the value of
5.71% reported in the literature [6]. Other studies similar to CLG 1 reported lower obtained H2
concentrations, ranging from roughly 70 to 90 mol-% [2,7,8].
However, as previously mentioned, CO2 was not removed from the syngas stream in CLG
2, and thus its relatively large constituency of 34.11 mol-% is accounted for by that fact. Had CO2
removal been inherent to the design of CLG 2, and assuming removal efficiency upwards of 99%,
0.87
2.54
0
0.5
1
1.5
2
2.5
3
CLG 1 CLG 2
Yie
ld (
km
ol/
km
ol
PL
)
Syngas Yield Comparison at Optimal Operating Conditions
H2 CO CO2 CH4 H2O
76
the H2 composition of the CLG 2 syngas would be over 95 mol-%. Further, the 62.94 mol-% value
from CLG 2 is similar to the 62.1 mol-% found in the literature [3].
Fig. 4.12. Comparison of simulation syngas compositions.
4.5 Potential for Future Research
Potential for future research stems in-part from the simulation flowsheets and block unit setups
themselves. Determining a method to model biomass gasification in a single gasifying reactor, as
opposed to four separate reactors in the case of the CLG 1 process, is exemplar of this. This would
allow for biomass gasification to occur spontaneously in an equilibrium-based reactor, i.e. RGibbs,
rather than in a reactor with user-defined outputs, as is the case for both simulations. Further, this
would allow for an investigation of the sensitivity of the gasifying reactor to steam-to-biomass,
calcium-to-biomass, and equivalence ratios.
In addition, the nitrogen and sulfur components of each biomass type could be included in
calculations to further enhance the accuracy of the simulation. Consequently, this would require
modification of the flowsheet and input parameters to deal with any sulfur dioxide (SO2), hydrogen
sulfide (H2S), or nitrogen (N2) streams that may be present from gasification of biomass containing
these elements [21].
92.45%
62.94%
1.28%
0.62%
0.01%
34.11%
6.03% 0.03%0.23% 2.30%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
CLG 1 CLG 2
Co
mp
osi
tio
n (
mo
l-%
)
Syngas Composition Comparison at Optimal Operating Conditions
H2 CO CO2 CH4 H2O
77
Moreover, more detailed design of the gas-solid separators (e.g. cyclones) utilized in the
simulation would further increase its accuracy. For example, cyclones, baghouses, or electrostatic
precipitators (ESPs) could be designed for gas-solid separation. These process units would be more
representative of an industrial-scale scenario, as opposed to the generic separator blocks used in
this simulation. Furthermore, the energy requirements of such block units could be accurately
represented as well.
Finally, a cost analysis for each block unit could be conducted to obtain an overall syngas
production cost for each simulated process type. The cost analysis could be based on energy
requirements and feed stream raw materials supply costs. Subsequently, comparing the cost
estimates would provide an idea of the feasibility of the proposed processes from a practical
standpoint.
4.6 Concluding Remarks
In conclusion:
1. Poultry litter was the chosen biomass type to be simulated both because it is a
nonconventional biomass type and due to its greater H2 yield potential when compared
with willow pellets and oak pellets.
2. The optimal operating condition estimates determined for the main reactors in both
simulations were in line with those presented in the literature.
a. CLG 1 simulation:
i. Reformer: 750 °C, 1 atm.
ii. Absorber: 500 °C, 1 atm.
iii. WGS reactor: 750 °C, 1 atm.
b. CLG 2 simulation:
i. Combustor: 1250 °C, 1 atm.
ii. Reducer: 870 °C, 30 atm.
iii. Oxidizer: 720 °C, 30 atm.
iv. Reformer: 500 °C, 1 atm.
3. CLG 1 and CLG 2 syngas yields were 0.87 and 2.54 kmol / kmol PL, respectively. CLG 2
generated the most H2 in the product syngas stream, 1.60 kmol / kmol PL, based on absolute
78
yield, with CLG 1 producing only 0.73 kmol / kmol PL. H2 production was significantly
less than that outlined in the literature for both simulations.
4. CLG 1 produced purer syngas with an H2 concentration of 92.45 mol-%, while CLG 2 had
62.94 mol-% H2. The lower CLG 2 concentration was due to the presence of CO2 in that
syngas stream, as its removal was not a focus of that simulation. CLG 1 exhibited more H2
rich syngas than other studies while CLG 2 produced results similar to those found in the
literature.
5. Future research could focus on increasing the accuracy and scalability of the simulations
through assumption mitigation or removal. Examples include modelling biomass
gasification in a single gasifying reactor, detailed design of gas-solid separators, and
inclusion of nitrogen and sulfur elements in biomass ultimate analyses.
References
[1] Holladay, J., J. Hu, D. King, and Y. Wang. "An Overview of Hydrogen Production Technologies." Catal
Today 139.4 (2009): 244-60.
[2] Florin, N., and A. Harris. "Hydrogen Production from Biomass Coupled with Carbon Dioxide Capture: The
Implications of Thermodynamic Equilibrium." Int J Hydrogen Energ 32.17 (2007): 4119-134.
[3] Fan, Liang-Shih. Chemical Looping Systems for Fossil Energy Conversions. Hoboken, NJ: Wiley-AIChE,
2010. Print.
[4] Ni, M., D. Leung, M. Leung, and K. Sumathy. "An Overview of Hydrogen Production from Biomass." Fuel
Process Technol 87.5 (2006): 461-72.
[5] Kirtay, Elif. "Recent Advances in Production of Hydrogen from Biomass." Energ Convers Manage 52
(2011): 1778-789.
[6] Acharya, Bishnu. Chemical Looping Gasification of Biomass for Hydrogen-Enriched Gas Production.
Thesis. Dalhousie University, Halifax, Nova Scotia, 2011. Dalhousie University, Department of Mechanical
Engineering. Print.
[7] Acharya, B., A. Dutta, and P. Basu. "Chemical-Looping Gasification of Biomass for Hydrogen-Enriched Gas
Production with In-Process Carbon Dioxide Capture." Energ Fuels 23 (2009): 5077-083.
[8] Mahishi, Madhukar R., M. S. Sadrameli, Sanjay Vijayaraghavan, and D. Y. Goswami. "A Novel Approach
to Enhance the Hydrogen Yield of Biomass Gasification Using CO2 Sorbent." J Eng Gas Turb Power 130
(2008): 011501-1 to 11501-8. Print.
[9] Moghtaderi, B. "Effects of Controlling Parameters on Production of Hydrogen by Catalytic Steam
Gasification of Biomass at Low Temperatures." Fuel 86.15 (2007): 2422-430.
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[10] Abuadala, A., I. Dincer, and G.F. Naterer. "Exergy Analysis of Hydrogen Production from Biomass
Gasification." Int J Hydrogen Energ 35 (2010): 4981-990.
[11] Gonzalez, J., S. Roman, D. Bragado, and M. Calderon. "Investigation on the Reactions Influencing Biomass
Air and Air/steam Gasification for Hydrogen Production." Fuel Process Technol 89.8 (2008): 764-72.
[12] Shen, L., Y. Gao, and J. Xiao. "Simulation of Hydrogen Production from Biomass Gasification in
Interconnected Fluidized Beds." Biomass Bioenerg 32.2 (2008): 120-27.
[13] Franco, C., F. Pinto, I. Gulyurtlu, and I. Cabrita. "The Study of Reactions Influencing the Biomass Steam
Gasification Process." Fuel 82.7 (2003): 835-42.
[14] Pfeifer, C., B. Puchner, and H. Hofbauer. "Comparison of Dual Fluidized Bed Steam Gasification of Biomass
with and without Selective Transport of CO2." Chem Eng Sci 64.23 (2009): 5073-083.
[15] Lin, Shiying, Michiaki Harada, Yoshizo Suzuki, and Hiroyuki Hatano. "Hydrogen Production from Coal by
Separating Carbon Dioxide during Gasification." Fuel 81 (2002): 2079-085.
[16] Hanaoka, T., Takahiro Yoshida, Shinji Fujimoto, Kenji Kamei, Michiaki Harada, Yoshizo Suzuki, Hiroyuki
Hatano, Shin-ya Yokoyama, and Tomoaki Minowa. "Hydrogen Production from Woody Biomass by Steam
Gasification Using a CO2 Sorbent." Biomass Bioenerg 28.1 (2005): 63-68.
[17] Guoxin, Hu, and Huang Hao. "Hydrogen Rich Fuel Gas Production by Gasification of Wet Biomass Using a
CO2 Sorbent." Biomass Bioenerg 33.5 (2009): 899-906.
[18] Mahishi, M., and D. Goswami. "An Experimental Study of Hydrogen Production by Gasification of Biomass
in the Presence of a CO2 Sorbent." Int J Hydrogen Energ 32.14 (2007): 2803-808.
[19] Acharya, Bishnu, Animesh Dutta, and Prabir Basu. "An Investigation into Steam Gasification of Biomass for
Hydrogen Enriched Gas Production in Presence of CaO." Int J Hydrogen Energ 35.4 (2010): 1582-589.
[20] Faaij, A., R. van Ree, L. Waldheim, E. Olsson, A. Oudhuis, A. van Wijk, et al. "Gasification of Biomass
Wastes and Residues for Electricity Production." Biomass Bioenerg 12.6 (1997): 387-407.
[21] Piroonlerkgul, P., W. Wiyaratn, A. Soottitantawat, W. Kiatkittipong, A. Arpornwichanop, N. Laosiripojana,
et al. "Operation Viability and Performance of Solid Oxide Fuel Cell Fuelled by Different Feeds." Chem Eng
J 155 (2009): 411-18.
80
Chapter V
Tubular Solid Oxide Fuel Cell Operation on Syngas from Two
Unique Biomass Chemical Looping Gasification Processes – A
Performance Comparison Simulated Using Aspen Plus
Nomenclature
Latin Alphabet
Ac Active cell area [m2] – Eqn. (17)
F Faraday’s constant [96 485 C mol-1] – Eqn. (15)
i Current density [mA cm-2] – Eqns. (12) and (17)
n Number of electrons transferred [mol e- per mol] – Eqn. (15)
Nc Number of cells – Eqn. (18)
�̇�𝑗 Molar flowrate of species j [kmol h-1] – Eqn. (16)
P Pressure [atm = 1.01325 bar] – Eqns. (10), (11), (13), and (14)
pc Cell power [W cell-1] – Eqns. (17) and (18)
ptot Total power output [kW = 1000 W] – Eqn. (18)
Q Thermal energy [kJ mol-1 = 1000 J mol-1] – Eqns. (3), (5), and (7)
T Temperature [°C] – Eqns. (10) and (12)
Uf Fuel utilization factor [-] – Eqn. (15)
V Voltage [V = 1000 mV] – Eqns. (10), (15), and (17)
W Work [kJ mol-1 = 1000 J mol-1] – Eqns. (3), (5), and (7)
Greek Alphabet
ΓH2 Fuel equivalent H2 content [kmol h-1] – Eqns. (15) and (16)
ΔV Voltage difference [V = 1000 mV] – Eqns. (11) to (14)
η Efficiency [-] – Eqn. (15)
Subscripts
an Anode
c Cell
cath Cathode
e Electric
op Operating conditions
P Pressure
ref Reference conditions
T Temperature
tot Total
Acronyms
CLG Chemical looping gasification
LHV Fuel lower heating value [kJ mol-1 = 1000 J mol-1] – Eqn. (15)
NC No CO2
SOFC Solid oxide fuel cell
WC With CO2
81
5.1 Introductory Remarks
The use of hydrogen (H2) as an alternative to fossil fuel energy sources has the potential to shift
the global search for cleaner, renewable forms of energy towards more efficient green technologies
by mitigating reliance on carbonaceous fuels. The major issue of global climate change resulting
from rapidly increasing atmospheric concentrations of carbon dioxide (CO2) and other greenhouse
gases (GHGs) can be addressed via the utilization of various H2 production and utilization
technologies. H2 is also beneficial when compared to conventional alternative energies such as
wind and solar power due to its effective capabilities as a medium for both energy storage and
transport; however both of these beneficial aspects are still considerable challenges. Consequently,
the widespread use of H2 as an energy source in the near future is highly probable.
Contemporary H2 production methods ultimately contribute to the consumption and
subsequent generation of GHGs [1]. Further, these methods are neither GHG-neutral nor
sustainable since their designs are based on the use of non-renewable fossil fuels. Therefore, the
production of H2 from a renewable, carbon-neutral energy source is of paramount importance.
Chemical looping gasification (CLG) is exemplar of such technologies and is a thermochemical
conversion process that is a feasible candidate for the replacement of fossil fuel-based H2
production. It involves the conversion of biomass fuel to synthesis gas (or syngas), mainly H2,
carbon monoxide (CO), and various hydrocarbons, for subsequent use in H2 conversion
technologies for the purpose of energy generation.
Poultry litter is an example of such biomass fuels and is both globally abundant and readily
available. The global poultry population in 2012 exceeded twenty-one billion chickens, or more
than three chickens per person on Earth [2]. The utilization of poultry excrement wastes in biomass
CLG systems for the production of high purity H2 syngas would provide a plentiful fuel source for
small-to-medium scale power generation via SOFC operation. It would also provide a critical link
between the green energy fields of biomass gasification and fuel cell power.
5.1.1 Solid Oxide Fuel Cells
Solid oxide fuel cells (SOFCs), high-temperature electrochemical devices which directly convert
chemical energy into electrical energy, are one such H2 utilization technology. Typical operating
temperatures range from 600 to 1000 °C. The cell assembly for SOFCs generally consists of an
anode, cathode, electrolyte, and interconnect, with all portions of the cell existing as solid-state,
82
thus requiring the higher operating temperature. Generally, the anode material is constructed of a
nickel and yttria-stabilized zirconia (Ni-YSZ) cermet (ceramic-metal), the cathode is strontium
(Sr)-doped lanthanum manganate (LaMnO3), and the electrolyte is YSZ, however these materials
may be altered or switched out entirely depending on the SOFC application [3-7].
A schematic of typical SOFC operation on H2 and CO can be seen in Figure 5.1 [8].
Electrochemical oxidation of the active fuel occurs at the cell anode and the reduction of oxygen
(O2) occurs at the cathode. Equation (1) shows the former for H2 fuel and Equation (2) shows the
latter. The overall reaction for the process can be seen in Equation (3).
Anodic H2 oxidation: H2 + O= → H2O + 2e- (1)
Cathodic O2 reduction: ½ O2 + 2e- → O= (2)
Overall reaction (H2): H2 + ½ O2 → H2O + We + Q (3)
Fig. 5.1. SOFC operation on H2 and CO fuels [8].
SOFCs may also operating using CO and methane (CH4) directly. The electrochemical reaction
for the cathodic reduction of O2 remains unchanged from H2 operation in either case, except for
multiples of both sides of the equation in the case of CH4. The direct oxidation of CO at the anode
and its corresponding overall reaction can be seen in Equations (4) and (5), respectively.
Anodic CO oxidation: CO + O= → CO2 + 2e- (4)
Overall reaction (CO): CO + ½ O2 → CO2 + We + Q (5)
83
In addition, the direct anodic oxidation of CH4 and its respective overall reaction can be seen in
Equations (6) and (7) [3].
Anodic CH4 oxidation: CH4 + 4 O= → CO2 + 2 H2O + 8e- (6)
Overall reaction (CH4): CH4 + 2 O2 → CO2 + 2 H2O + We + Q (7)
The advantages of SOFCs over other fuel cell technologies stem mainly from the geometric design
of the cell assembly and the higher operating temperatures. These advantages include the use of
non-precious metal catalysts, higher efficiency and longer cell life than other fuel cell types, high
fuel flexibility, and the use of a solid-state electrolyte. The electrochemical kinetics of the half-
cell reactions are faster than other fuel cell types as a result of the higher operating temperatures
[9,10]. This allows Ni to be used as a catalyst for anodic oxidation rather than precious metal
catalysts.
SOFC operation is possible using H2, CO, and CH4, as well as higher-order hydrocarbons
such as ethane (C2H6) [11,12], propane (C3H8), n-butane (C4H10) [11], etc. Generally, CO and CH4
are reformed to H2 and CO2 prior to reaching the SOFC anode and undergoing direct oxidation.
Pre-reforming of CO occurs via the water-gas shift reaction which can be seen in Equation (8).
Water-gas shift reaction: CO + H2O → H2 + CO2 (8)
The H2 generated in Equation (8) is ultimately oxidized at the anode and undergoes the process
outlined by Equations (1) to (3). Similarly, pre-reforming of CH4 occurs via the endothermic steam
reforming of methane reaction and can be seen in Equation (9).
Steam reforming of CH4: CH4 + H2O → CO + 3 H2 (9)
The CO generated in Equation (9) undergoes the water-gas shift reaction illustrated in Equation
(8), while the H2 produced proceeds to be oxidized as shown in Equations (1) to (3).
Multicomponent inlet fuel streams consisting of active fuels diluted with inert or inactive gases,
i.e. nitrogen (N2), CO2, and steam (H2O), can also be used in SOFCs, however overall performance
generally decreases as diluent gas concentration increases [11,13].
The use of a non-fluid electrolyte allows for multiple geometries for the SOFC electrolyte
and overall cell design. These include the planar (bipolar or flat plate) and tubular configurations;
both of which are depicted in Figure 5.2 [8]. The flat plate configuration is relatively simple
84
conceptually, and consists of the cell components in a series connection, however issues of
improper gas sealing and fabrication of thin layer structures arise. The flexibility of the solid-state
electrolyte allows for the tubular configuration, which was developed by Siemens-Westinghouse
[14,15]. This SOFC geometry simplifies gas sealing and individual cells are easily connected by
attachment to a common support tube [8]. The performance and operation of the tubular design is
well studied and will be the SOFC configuration used in this paper [16-21].
Fig. 5.2. Tubular and flat plate SOFC configurations [8].
In contrast, some drawbacks of SOFCs remain prominent and include material durability
issues and inlet fuel stream type or composition. Degradation of the solid-state cell assembly
results from prolonged exposure to the higher operating temperatures. Difficulties arise in seeking
out alternative materials that can withstand such high temperatures for extended periods of time.
Furthermore, the possible reduction-oxidation (redox) cycling during operation suggests that Ni is
constantly often between Ni and nickel oxide (NiO). These conversion cycles induce anode
volume changes during operation which have a detrimental effect on the structural integrity of the
anode, and consequently to performance degradation overall [9,10,22-24].
Reduction in cell performance also stems from the Ni-catalyzed thermal cracking of
hydrocarbons present in the inlet fuel stream. By-product graphite formation is generated as a
result and leads to carbon deposition at the anode, thereby occupying anode active sites and
inhibiting H2 adsorption [9,10]. Additionally, SOFCs are highly sensitive to sulfur poisoning in
the form of hydrogen sulfide (H2S), which significantly reduces cell performance. Successful
operation of SOFCs is often jeopardized by even small, parts-per-million (ppm) levels of H2S.
Corresponding research has therefore been conducted to identify the mechanisms contributing to
performance degradation in the presence of H2S, and to develop gas cleaning techniques for sulfur
removal to ensure sufficient operational longevity and performance [9,10,25].
85
5.1.2 Syngas from Biomass CLG and SOFC Operation
Direct operation of SOFCs on product syngas from the CLG of biomass is advantageous since the
inlet fuel stream can be fed directly to a SOFC with minimal pre-operation gas cleaning
requirements. Therefore, the research compares the operation of a tubular SOFC for two different
syngas streams, each resulting from unique biomass CLG processes for the purpose of H2
production. The first process (CLG-1) produced H2-rich syngas using a calcium oxide (CaO)
sorbent for CO2 capture with total sorbent recovery. The second process (CLG-2) used iron (Fe)-
based oxygen carriers to produce majority-H2 syngas. Poultry litter was used as the biomass
feedstock in both cases. More information regarding the two syngas production processes can be
found in a previous study conducted by the authors [26].
Performance comparisons are measured in terms of cell voltage, electrical efficiency, and
total power output for each syngas type. The effects of varying anode operating temperature and
pressure, inlet fuel utilization factor, and applied current density on overall cell performance are
investigated. The originality of the conducted research lies in the investigation of the effects of CO
and CO2 syngas feed composition on tubular SOFC performance and in the direct performance
comparison of multiple biomass CLG syngas types modelled in a SOFC under similar feed and
operating conditions simulated using the Aspen Plus software. The SOFC model developed in
ASPEN Plus was adapted from Zhang et al. [16].
5.2 Simulation Description and Input Parameters
The following sections provide a detailed description of the simulated process. In addition, the
input data to the Aspen Plus simulation engine are outlined, as well as the chosen and utilized
calculation methods and equations.
5.2.1 Simulated Process
A tubular SOFC was simulated and analyzed using Aspen Plus V8.0 by following the design
presented by Zhang et al. [16] as a guide. A conceptual block diagram of the process can be seen
in Figure 5.3 and the simulation flowsheet can be seen in Figure 5.4. The input and operating
conditions for all feed streams and block units can be found in Tables 5.1 and 5.2, respectively.
CLG-1 incorporated CO2 removal while CLG-2 did not. Modified versions of both
processes were run in the simulation to determine the effect of CO2 removal from the syngas stream
on SOFC performance. Modified CLG-1 syngas was similar to regular CLG-1 syngas, however
86
CO2 removal from the stream was not implemented in the former. Modified CLG-2 syngas was
similar to regular CLG-2 syngas, though CO2 removal was applied to the stream. The following
labels were used to differentiate between the processes: regular CLG-1 was denoted as CLG-1-
NC, modified CLG-1 was labelled CLG-1-WC, regular CLG-2 was CLG-2-WC, and modified
CLG-2 was CLG-2-NC. Note that NC = “No CO2” and WC = “With CO2”.
The effect of sulfur poisoning on SOFC performance was not studied since the designed
model did not accurately simulate the mechanism by which contaminant H2S inhibits anodic H2
oxidation. This is a result of the simulation engine bypassing Equation (1) to effectively model
Equation (3). Furthermore, no sulfur compounds were present in any tested syngas type [26].
Fig. 5.3. SOFC simulation block diagram.
87
Fig. 5.4. SOFC simulation flowsheet.
Table 5.1
Feed stream input conditions.
Condition Air Syngas
(CLG-1-NC)
Syngas
(CLG-1-WC)
Syngas
(CLG-2-WC)
Syngas
(CLG-2-NC)
Temperature (°C) 630 20 20 20 20
Pressure (atm) 1 10 10 10 10
Flowrate (kmol h-1) 40 a 0.87 1.68 2.54 1.66
H2 (mol-%) - 92.46 45.78 62.49 97.49
H2O (mol-%) - 0.23 0.23 2.30 2.31
CO (mol-%) - 1.28 45.16 0.62 0.00
CO2 (mol-%) - 0.01 7.44 34.11 0.19
CH4 (mol-%) - 6.03 1.40 0.03 0.00
N2 (mol-%) 79 - - - -
O2 (mol-%) 21 - - - - a Fed in excess of required stoichiometric amount.
88
Table 5.2
Block unit operating conditions.
Block
Name
Block
Type
Temperature
(°C)
Pressure
(atm) Other
Anode RGibbs 950 a 1 -
Cathode Sep - - Separated a specified molar fraction of O2 from heated
inlet air stream (CATH-IN) as feed to ANODE. b
Burner RStoich 950 1
Output based on defined reactions governed by
stoichiometric input, i.e.:
CO + ½ O2 CO2
H2 + ½ O2 H2O
Heat-1 Heater 950 1 -
Heat-2 Heater 910 1 -
Heat-3 Heater 1012.35 1 -
Heat-X HeatX - -
Flow direction: Countercurrent. Type: Design.
Specification: Hot/cold outlet temperature approach.
Value: 10 delta-C. a Represents design operating temperature. Anode temperature was varied from 900 to 1000 °C. b Molar split fraction for O2 was based on roughly half of the theoretical inlet H2 molar flowrate in the syngas feed,
and differed based on utilized syngas type. A split fraction of 6 mol-% O2 was used for CLG-1-NC, while 9.5 mol-%
O2 was used for the other syngas types.
5.2.2 Setup and Component Definition
The Aspen Plus flowsheet type was chosen as “General with metric units”, allowing for the
analysis and results presentation for fluid and aqueous (MIXED) input and output material streams.
The process type was chosen as COMMON, allotting a generic industry type the simulation. The
IDEAL base calculation method was selected for simplicity and ease of operation. Thus, phase
equilibrium calculations were conducted using Raoult’s Law, Henry’s Law, the Ideal Gas Law,
etc.
Moreover, fluid streams were modelled using conventional components which have
thermophysical data stored in Aspen Plus databanks. Thus, no physical property data input were
required for fluid components. These components include: H2, H2O, CO, CO2, CH4, O2, and N2.
5.2.3 Flowsheet Description
Syngas from a biomass CLG process was heated to 950 °C in the HEAT-1 block unit. The Heater
is an Aspen Plus temperature changing module [16]. The heated syngas stream (GAS-WARM)
was then fed to the ANODE block. Simultaneously, hot air (AIR) was heated by being fed to the
cold fluid side of the HeatX (labelled as HEAT-X) heat exchanger module prior to being fed to the
CATHODE block unit, a Sep separation module which allowed for the direct splitting of inlet
streams into multiple outlet streams. Equation (2) did not proceed in the simulated cathode since
89
Aspen Plus does not easily model electrochemical reactions Thus, the CATHODE separated a
defined molar fraction of O2 from the heated air stream as feed to the ANODE block. This process
is equivalent to oxide ion (O=) migration from the cathode to the anode. The CATHODE sent
sufficient O2 to the ANODE for Equation (3) to proceed. The O2-depleted air (AIR-DEPL) was
then heated in the HEAT-2 unit before being sent to the BURNER block unit.
The ANODE block is an RGibbs reactor module which calculates its output using the Gibbs
free energy minimization method, dependent on the defined operating temperature and pressure.
The calculations were based on the chemical equilibrium reactions of the components being input
to the reactor under the pre-defined conditions. Here, all reacted H2 and O2 underwent Equation
(3), the overall SOFC equation when operating on H2. Equations (8) and (9) were assumed to have
much faster kinetics than Equations (4) and (6), respectively, and thus all reacted CO and CH4
were presumed to undergo conversion to H2 and CO2 [16-19,27].
The ANODE products (AN-PROD) were also sent to the BURNER block unit for
combustion at under sufficient O2 conditions provided by the heated BURN-IN stream. The
combustion unit is an isothermal RStoich reactor module which has outputs based on user-defined
chemical reactions. Residual CH4 combustion was not considered since its molar flowrate in the
AN-PROD stream was negligible for all tested syngas types. The combustion products (BURN-
OUT) were heated in the HEAT-3 block unit to represent the temperature increase following
combustion and ultimately sent to the hot fluid side of the HEAT-X unit to provide heat for the
inlet AIR stream. The combustion products then exit the HEAT-X block as the EXHAUST stream.
5.2.4 Cell Performance Calculation Methods
5.2.4.1 Cell Voltage
Semi-empirical equations were used to convert the inlet and outlet anodic molar flowrates to
voltages, and were based on reference operating conditions. The reference conditions can be found
in Table 5.3. The expression for cell voltage is shown by Equation (10) [14,16,28].
Cell voltage: Vc = Vref + ΔVP + ΔVT + ΔVcath + ΔVan (10)
The reference voltage is a function of current density [14] and accounts for detriments to SOFC
performance such as ohmic, activation, and concentration polarization losses. Table 5.4 outlines
reference voltage values for different current densities. The remainder of the terms in Equation
(10) account for contributions to the overall cell voltage by the simulated operating conditions.
90
Table 5.3
Reference conditions used in voltage calculations [14].
Reference Parameter Symbol Condition
Temperature Tref 1000 °C
Pressure Pref 1 bar
O2 Partial Pressure (PO2)ref 0.164 bar a
Ratio of H2 to H2O Partial Pressures (PH2/PH2O)ref 0.15 a
a From Zhang et al. [16].
Table 5.4
Reference voltage as a function of current density [14].
ic (mA cm-2) Vref (mV)
0 720
180 a 650 a
200 640
400 560
600 460
720 400 a Standard condition.
The effect of operating pressure, and its corresponding contribution to Vc, is summarized
in Equation (11) [14,16].
Operating pressure: ΔVP [mV] = 76 (P/Pref) (11)
Subsequently, the effect of operating temperature can be seen in Equation (12) [8,14,16].
Operating temperature: ΔVT [mV] = 0.008 (Top – Tref) ic (12)
Current density has units of milliamps per square centimetre (mA cm-2) in Equation (12).
Furthermore, the effect of deviation from the reference cathodic O2 partial pressure is illustrated
in Equation (13) [14,16].
Cathode composition: ΔVcath [mV] = 92 log[PO2/(PO2
)ref] (13)
Finally, the expression for the effect of deviation from the reference anodic H2-to-H2O partial
pressure ratio is shown in Equation (14) [14,16].
Anode composition: ΔVan [mV] = 172 log[(PH2/PH2O)/(PH2
/PH2O)ref] (14)
H2 and H2O partial pressures were calculated as averages of anode inlet and outlet (SYNGAS and
AN-PROD streams, respectively).
91
5.2.4.2 Electrical Efficiency
The electrical efficiency of the cell was calculated using Equation (15) [14,16].
Electrical efficiency: ηe = We/LHV = (nFVcUf ΓH2)/LHV (15)
The quantity ΓH2 represents the equivalent H2 flowrate in the inlet syngas stream, and is determined
according to Equation (16) [14,16]. LHV values can be found in Table 5.5 [29].
Equivalent H2 flowrate: ΓH2 [kmol h-1] = �̇�H2
+ �̇�CO + 4�̇�CH4 (16)
The coefficients in Equation (16) correspond to the contribution of each species to the equivalent
H2 flowrate in the syngas stream. For example, each mole of CO contributes 1 mol H2 via Equation
(8) and each mole of CH4 contributes 4 mol H2 via Equation (9).
Table 5.5
Lower heating value of fuels [29].
Fuel LHV (kJ mol-1) a
H2 242.57
CO 284.58
CH4 800.14 a Converted from averaged values in units of [MJ Nm-3].
5.2.4.3 Power Output
The calculation of power output per cell and total power output were based on the geometry of the
simulated SOFC. The corresponding formulae are outlined in Equations (17) and (18).
Power output per cell: pc = ic Ac Vc (17)
Total power output: ptot = pc Nc (18)
Thus, a design cell geometry was assumed with an active area of 96.1 m2 and a total of 1152 cells
based on SOFC performance data [16,17,20,21].
92
5.3 Results and Discussion
The following sections detail the data obtained from the simulation and corresponding analysis
and discussion. Table 5.6 outlines the standard operating conditions utilized for the data collection
process of the simulation. Simulated SOFC performance results were obtained and compared for
the effects of the presence of CO, the presence of CO2, temperature, pressure, utilization factor,
and current density.
5.3.1 Syngas Performance Comparison
The two syngas types (CLGs 1-NC and 2-WC) and their respective modified versions (CLGs 1-
WC and 2-NC) were run in the SOFC simulation to determine the differences in the resulting cell
performance. The cell voltage and electrical efficiency comparison can be seen in Figure 5.5 and
the total power output comparison is illustrated in Figure 5.6. Although certain syngas types
outperformed others, the range of values was not immense (< 100 mV for voltage, < 5% for
efficiency, and < 15 kW for total power output).
Table 5.6
Standard operating conditions.
Operating Parameter Symbol Condition
Temperature Top 950 °C
Pressure Pop 1 atm (1.01325 bar)
Fuel Utilization Factor Uf 85%
Current Density ic 180 mA cm-2
Reference Voltage Vref 650 mA
CLG-1-WC exhibited the greatest SOFC performance in terms of cell voltage at roughly
0.77 V, while CLG-1-NC displayed the greatest performance in terms electrical efficiency at about
51%. However, the measured efficiencies were similar in magnitude. In addition to cell voltage,
CLG-1-WC showed superior performance in terms of total power output and cell power (i.e. power
per cell), with corresponding values of 133 kW and 116 W cell-1. CLG-2-WC exhibited the lowest
performance for all measured parameters.
The simulation results are compared to the literature [16,17,20,21] in Table 5.7. The
obtained cell voltages for all syngas types were greater than or similar to those in research
conducted by Zhang et al. [16], Doherty et al. [17], Calí et al. [20], and Verda and Calí [21] under
similar operating current density conditions. This was also the case for electrical efficiency and
total power output. The stack exhaust compositions obtained for each syngas type were similar to
93
those reported in the literature with CLGs 1-NC and 2-NC having significantly smaller molar
concentrations of CO2. Thus, SOFC operation on these syngas types inherently reduce
contributions to atmospheric CO2 levels.
Fig. 5.5. Cell voltage and electrical efficiency comparison (Top = 950 °C, Pop = 1 atm, Uf = 85%, ic = 180 mA cm-2,
Vref = 650 mV, NC = No CO2, WC = With CO2).
Fig. 5.6. Total power output comparison (Top = 950 °C, Pop = 1 atm, Uf = 85%, ic = 180 mA cm-2, Vref = 650 mV,
NC = No CO2, WC = With CO2).
0.4
0.45
0.5
0.55
0.6
0.65
0.7
0.75
0.8
CLG-1-NC CLG-1-WC CLG-2-WC CLG-2-NC
Vo
ltag
e (V
) an
d E
ffic
iency
Cell Voltage Electrical Efficiency
116
118
120
122
124
126
128
130
132
134
CLG-1-NC CLG-1-WC CLG-2-WC CLG-2-NC
Po
wer
(k
W)
94
Table 5.7
Comparison of simulation results under standard conditions to the literature [16,17,20,21].
Parameter Simulation Results Literature Values
CLG-1-NC CLG-1-WC CLG-2-WC CLG-2-NC [16] [17] [20,21]
Cell Voltage (V) 0.73 0.77 0.71 0.72 0.70 0.683 0.661
Current Density
(mA cm-2) 180 180 180 180 178 182.86 200.6
Anode Inlet Composition
(mol-%)
H2 (92.46),
H2O (0.23),
CO (1.28),
CO2 (0.01),
CH4 (6.03),
N2 (0.0)
H2 (45.78),
H2O (0.23),
CO (45.16),
CO2 (7.44),
CH4 (1.40),
N2 (0.0)
H2 (62.49),
H2O (2.30),
CO (0.62),
CO2 (34.11),
CH4 (0.03),
N2 (0.0)
H2 (97.49),
H2O (2.31),
CO (0.00),
CO2 (0.19),
CH4 (0.00),
N2 (0.0)
H2 (67.0),
H2O (11.0),
CO (22.0),
CO2 (0.0),
CH4 (0.0),
N2 (0.0)
H2 (26.9),
H2O (27.8),
CO (5.6),
CO2 (23.1),
CH4 (10.4),
N2 (6.2)
H2 (2.9),
H2O (27.4),
CO (8.3),
CO2 (52.8),
CH4 (7.4),
N2 (1.3) a
Anode Outlet
Composition (mol-%)
H2 (1.90),
H2O (91.57),
CO (0.19),
CO2 (6.34),
N2 (0.0)
H2 (0.62),
H2O (46.85),
CO (1.00),
CO2 (51.53),
N2 (0.0)
H2 (0.54),
H2O (64.72),
CO (0.38),
CO2 (34.37),
N2 (0.0)
H2 (1.39),
H2O (98.41),
CO (0.0),
CO2 (0.20),
N2 (0.0)
H2 (11.6),
H2O (50.9),
CO (7.4),
CO2 (24.9),
N2 (5.1)
H2 (11.6),
H2O (50.9),
CO (7.4),
CO2 (24.9),
N2 (5.1)
H2 (1.39),
H2O (39.88),
CO (11.91),
CO2 (45.88),
N2 (0.94) a
Stack Exhaust
Temperature (°C) 830.57 832.74 835.02 831.80 834 833.7 279
Stack Exhaust
Composition (mol-%)
N2 (78.09),
O2 (19.49),
H2O (2.26),
CO2 (0.16)
N2 (77.23),
O2 (18.54),
H2O (2.01),
CO2 (2.22)
N2 (75.72),
O2 (18.19),
H2O (3.98),
CO2 (2.12)
N2 (77.35),
O2 (18.58),
H2O (4.06),
CO2 (0.01)
N2 (77.3),
O2 (15.9),
H2O (4.5),
CO2 (2.3)
N2 (77.3),
O2 (15.9),
H2O (4.5),
CO2 (2.3)
N2 (75.62),
O2 (17.38),
H2O (3.14),
CO2 (3.87) a
Electrical Efficiency
(%, LHV-based) 50.90 48.57 47.89 48.56 52 49.15 48 b
Cell Power (W cell-1) 109.20 115.51 106.49 107.82 103.94 c 104.16 d 110.56 d
Total Power Output (kW) 125.79 133.07 122.68 124.21 120 120 127.4 a All composition values reported in units of [wt.-%], not [mol-%]. b Reported as gross AC efficiency using the fuel LHV. All other efficiency values are based on net AC efficiency using the fuel LHV. c Calculated using the reported active area of 96.1 m2 with 1152 cells and reported cell voltage and current density values. d Calculated using the reported active area of 96.0768 m2 with 1152 cells and reported cell voltage and current density values.
95
The differences between the simulation results and those reported in the literature may be
explained by differences in calculation methods and initial assumptions. For example, a power
output of 120 kW was initially assumed in the study conducted by Zhang et al. [16] and the
resultant current density of 178 mA cm-2 was calculated based on the obtained cell voltage. In
contrast, a similar current density of 180 mA cm-2 was initially assumed for all syngas types in this
paper and the total power output was then calculated based on the obtained cell voltages.
5.3.1.1 Effect of Syngas CO Composition
CO composition levels were varied from 0.01 to 60 mol-% while maintaining the balance syngas
at fixed proportions of the other constituents. This was done for both of the unmodified syngas
types (CLGs 1-NC and 2-WC) to determine the effects of CO composition on their respective
performance in the simulated SOFC. The results for cell voltage and electrical efficiency can be
found in Figure 5.7 while those for total power output are illustrated in Figure 5.8.
Fig. 5.7. Effect of CO syngas composition on cell voltage and electrical efficiency.
Increasing CO concentrations under standard conditions significantly increased
performance for voltage and power, which both raised by 13.83% and 20.23% over the tested
range for CLGs 1 and 2, respectively. Both performance metrics also continually increased in a
linear fashion, achieving values higher than that of standard CLG-1-WC at the higher end of the
CO composition scale. Changes in efficiency with increasing CO were not as prominent. CLG-1
efficiency rose to a local maximum at 5 mol-% CO, began to decrease, and gradually increasing
0.47
0.48
0.49
0.5
0.51
0.52
0.53
0.54
0.55
0.6
0.65
0.7
0.75
0.8
0.85
0.9
0% 10% 20% 30% 40% 50% 60%
Eff
icie
ncy
Vo
ltag
e (V
)
CO Composition (mol-%)
Voltage (CLG-1) Voltage (CLG-2)
Efficiency (CLG-1) Efficiency (CLG-2)
96
for an overall percent increase of 1.49%. In contrast, CLG-2 efficiency continually increased in a
non-linear manner, achieving an increase from 47.90 to 51.33% (percent difference of 7.16%).
Fig. 5.8. Effect of CO syngas composition on total power output.
The simulated results are in disagreement with experimental findings due to the mechanism
by which CO is utilized in the simulated SOFC. Literature data suggest that increasing CO content
decreases SOFC performance [9-11]. The inconsistency is attributed to the assumption of complete
CO water-gas shift reforming to H2 via Equation (8). Experimental trials conducted in the
literature, however, included both reforming and direct anodic oxidation of CO via Equation (4).
The oxidized CO was unable to undergo conversion to H2 and ultimately be utilized in the cell.
The active CO fuel in the simulation was sufficient to enhance cell performance and
simultaneously counterbalance the detrimental effects of any inactive or inert species, as is the
case with the relatively high prevalence of CO2 in CLG-1-WC syngas.
5.3.1.2 Effect of Syngas CO2 Composition
CLGs 1-NC and 2-WC differed in-part due to their inherent CO2 removal aspects, of which only
the former of the two utilized. Their respective modified versions (CLGs 1-WC and 2-NC),
however, were considered to determine any benefits or drawbacks related to altering the designed
processes to SOFC cell performance under standard conditions, and thus correspondingly excluded
and included CO2 removal steps. The effects of varying CO2 composition in the syngas feed stream
120
125
130
135
140
145
150
155
0% 10% 20% 30% 40% 50% 60%
Po
wer
(kW
)
CO Composition (mol-%)
Power (CLG-1) Power (CLG-2)
97
on voltage, efficiency, and total power output were also considered for the unmodified syngas
types and can be seen in Figures 5.9 and 5.10, respectively.
Fig. 5.9. Effect of CO2 syngas composition on cell voltage and electrical efficiency.
Fig. 5.10. Effect of CO2 syngas composition on total power output.
CO2 composition levels from 0.01 to 60 mol-% were simulated for both of the unmodified
syngas types while maintaining the balance syngas at fixed proportions of the other constituents.
0.46
0.47
0.48
0.49
0.5
0.51
0.52
0.53
0.54
0.6
0.65
0.7
0.75
0.8
0.85
0.9
0% 10% 20% 30% 40% 50% 60%
Eff
icie
ncy
Vo
ltag
e (V
)
CO2 Composition (mol-%)
Voltage (CLG-1) Voltage (CLG-2)
Efficiency (CLG-1) Efficiency (CLG-2)
115
117
119
121
123
125
127
129
131
133
0% 10% 20% 30% 40% 50% 60%
Po
wer
(kW
)
CO2 Composition (mol-%)
Power (CLG-1) Power (CLG-2)
98
Increasing CO2 concentrations at standard conditions decreased performance for voltage,
efficiency, and total power output, all of which decreased with an approximate linear trend. The
performance metrics underwent a reduction of 5.78% for CLG-1 and only about 2.82% for CLG-
2 over the tested range. CLG-1 syngas exhibited relatively higher performance than that of CLG-
2 over the range tested as well.
Excluding the CO2 removal step from unmodified CLG-1 syngas improved SOFC cell
voltage and total power output by an absolute percent difference of 5.78%, while efficiency was
found to decrease by 4.58%. This is evident since CLG-1-WC outperformed the other syngas types
despite its elevated levels of CO2. An explanation for this phenomenon is that CLG-1-WC
exhibited much higher levels of CO than its unmodified counterpart (45.16 and 1.28 mol-%,
respectively) which accounted for its greater relative performance. Further, the decrease in
efficiency was likely attributed to the fact that ηe is inversely proportional to the fuel LHV, as
outlined by Equation (15), and CLG-1-NC had a much smaller inlet flowrate of CO, even while
maintaining slightly greater flowrates of both H2 and CH4. The LHV of CO is greater than that of
H2 and roughly one third of the value for CH4, as shown in Table 5.5 [29].
The presence of CO2 in CLG-2 syngas had the opposite effect of CLG-1, with voltage and
total power output all decreasing by a percent difference of 1.23%. However, the same trend as
CLG-1-NC was followed for efficiency which decreased by 1.37% in the presence of CO2.
Nevertheless, CO2 removal had very little effect on performance for CLG-2-WC. This was
expected since CO2 variation within the CO2 composition range for CLG-2 (0.01 to 35 mol-%)
showed a voltage decrease of only about 8 mV, as shown in Figure 5.9. The decrease in efficiency
may be explained by the coupled effects of CLGs 2-WC and 2-NC having similar fuel LHV and
ΓH2 values, with CLG-2-NC exhibiting slightly greater performance in terms of Vc, which ηe is
directly proportional to.
The results obtained regarding the presence of CO2 in feed syngas are in line with those
reported in the literature. Jiang and Virkar [13] demonstrated that increasing concentrations of CO2
in binary H2-CO2 systems significantly reduced SOFC performance in terms of cell voltage and
power output. Feed streams containing CO were found to behave similarly to H2 given that H2
composition remained above 50%, and water-gas shift played a significant role in SOFC operation
on CO [13]. This finding provides further evidence for CO being the main factor contributing to
the observed higher performance of CLG-1-WC syngas regardless of its high CO2 content.
99
5.3.2 Anode Temperature Sensitivity Analysis
The anode operating temperature for each syngas type was varied from 900 to 1000 °C to
determine the effects on cell performance under standard conditions. The results of the analysis
are displayed in Figure 5.11. An increase in cell voltage, electrical efficiency, and total power
output was observed with increasing temperature for all syngas types. Voltage increased by
roughly 144 mV for the four cases over the range tested, and efficiency and power exhibited
respective increases of 9% and 25 kW.
Fig. 5.11. Effect of anode operating temperature on syngas performance (Pop = 1 atm, Uf = 85%, ic = 180 mA cm-2,
Vref = 650 mV, NC = No CO2, WC = With CO2).
SOFC thermodynamics theoretically predict that performance generally declines with
increasing temperature [30]. However, in practical systems, SOFC performance tends to increase
with increasing temperature due to the mitigation of kinetic barriers posed by the involved
electrochemical reactions [10,12]. Thus, the observed trends in regards to anode temperature are
in line with the literature.
5.3.3 Anode Pressure Sensitivity Analysis
An anode operating pressure sensitivity analysis was also conducted for each syngas type under
standard conditions. However, simulated pressure variation had negligible effects on cell voltage,
electrical efficiency, and total power output. This was the case for all syngas types. This trend is
100
105
110
115
120
125
130
135
140
145
150
0.4
0.45
0.5
0.55
0.6
0.65
0.7
0.75
0.8
0.85
0.9
900 920 940 960 980 1000
Po
wer
(kW
)
Vo
ltag
e (V
) an
d E
ffic
iency
Anode Temperature (°C)
Volt. (1-NC) Volt. (1-WC) Volt. (2-WC) Volt. (2-NC)
Eff. (1-NC) Eff. (1-WC) Eff. (2-WC) Eff. (2-NC)
Pwr. (1-NC) Pwr. (1-WC) Pwr. (2-WC) Pwr. (2-NC)
100
contrary to the theoretical thermodynamic effects of pressure on overall SOFC cell operation since
increasing pressure should increase cell voltage [30].
The discrepancy between the results of the simulation and real-world operation can be
explained by the limitations of the Aspen Plus RGibbs reactor type chosen to model the cell anode.
The software calculation engine determined that pressure effects on Equation (3) were negligible
in comparison to the effects of the high operating temperature at 950 °C, which remained constant
throughout pressure variation. No variation in the performance parameters was apparent as a result.
5.3.4 Fuel Utilization Factor Sensitivity Analysis
The fuel utilization factor was varied from 50 to 90% for each syngas type to determine the effects
on SOFC cell voltage, electrical efficiency, and total power output. The results for voltage and
efficiency can be seen in Figure 5.12 and those for total power output are shown in Figure 5.13.
Fig. 5.12. Effect of utilization factor on cell voltage and electrical efficiency (Top = 950 °C, Pop = 1 atm, ic = 180 mA
cm-2, Vref = 650 mV, NC = No CO2, WC = With CO2).
Cell voltage underwent a slight parabolic increase for all syngas types over the range of
utilization factors tested, with CLG-1-WC again exhibiting the greatest cell voltage overall. Cell
voltage for all syngas types continually increased with Uf over the tested range. Efficiency
increased linearly with increasing Uf for all syngas types. CLG-1-NC once more exhibited the
highest efficiency, averaging about 2.20% higher than the other syngas types over the tested range.
0.2
0.25
0.3
0.35
0.4
0.45
0.5
0.55
0.6
0.68
0.69
0.7
0.71
0.72
0.73
0.74
0.75
0.76
0.77
0.78
0.5 0.55 0.6 0.65 0.7 0.75 0.8 0.85 0.9
Eff
icie
ncy
Vo
ltag
e (V
)
Utilization Factor
Volt. (1-NC) Volt. (1-WC) Volt. (2-WC) Volt. (2-NC)
Eff. (1-NC) Eff. (1-WC) Eff. (2-WC) Eff. (2-NC)
101
Moreover, Figure 5.13 shows that total power output increased with Uf. This trend occurred as
expected due to the utilized calculation method for each performance metric; i.e. Equation (18) is
directly proportional to Vc and thus the power measurements differed from cell voltage only by
constant coefficients.
Fig. 5.13. Effect of utilization factor on total power output (Top = 950 °C, Pop = 1 atm, ic = 180 mA cm-2, Vref = 650
mV, NC = No CO2, WC = With CO2).
Upon comparison of the simulated results to the literature, it was found that the slight
parabolic trend observed for the effect of Uf on cell voltage was in line with that of the sensitivity
analysis conducted by Doherty et al. [17], yet decreasing cell voltage was observed over the entire
tested Uf range in the analysis conducted by Zhang et al. [16]. The linear increase in electrical
efficiency was also observed by both Doherty et al. [17] and Zhang et al. [16] over the 50 to 90%
tested Uf range.
5.3.5 Current Density Sensitivity Analysis
The current density applied to the simulated SOFC stack was varied from 0 to 720 mA cm-2 to
determine the effects on cell voltage, electrical efficiency, and total power output. The results for
voltage and efficiency are illustrated in Figure 5.14 and those for total power output are in Figure
5.15.
Cell voltage decreased linearly by about 0.61 V over the tested range of current densities
for all syngas types. CLG-1-WC once more achieved the overall highest voltages. Electrical
118
120
122
124
126
128
130
132
134
0.5 0.55 0.6 0.65 0.7 0.75 0.8 0.85 0.9
Po
wer
(kW
)
Utilization Factor
CLG-1-NC CLG-1-WC CLG-2-WC CLG-2-NC
102
efficiency also decreased linearly, dropping by roughly 40% for all syngas types (over 66% in
terms of percent difference). CLG-1-NC, again having the highest efficiency, was no exception to
this trend. Total power output increased over the tested range until reaching a local maximum
value upwards of about 200 kW at 550 mA cm-2 prior to decreasing at higher values of ic. This
trend occurred despite the notable reduction in cell voltage.
Fig. 5.14. Effect of current density on cell voltage and electrical efficiency (Top = 950 °C, Pop = 1 atm, Uf = 85%,
NC = No CO2, WC = With CO2).
Fig. 5.15. Effect of current density on total power output (Top = 950 °C, Pop = 1 atm, Uf = 85%, NC = No CO2,
WC = With CO2).
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 100 200 300 400 500 600 700 800
Eff
icie
ncy
Vo
ltag
e (V
)
Current Density (mA/cm2)
Volt. (1-NC) Volt. (1-WC) Volt. (2-WC) Volt. (2-NC)
Eff. (1-NC) Eff. (1-WC) Eff. (2-WC) Eff. (2-NC)
0
50
100
150
200
250
0 100 200 300 400 500 600 700 800
Po
wer
(kW
)
Current Density (mA/cm2)
CLG-1-NC CLG-1-WC CLG-2-WC CLG-2-NC
103
The resulting trends from the simulation were comparable to those outlined in the literature.
Both Zhang et al. [16] and Doherty et al. [17] observed decreasing cell voltage and electrical
efficiency over their respective tested ranges of current density. The decrease was linear or
approximately so in both cases, as was the case for the simulated results presented in this paper.
However, the decrease in efficiency found in reference [17] was far more pronounced than either
the simulated results or reference [16] in terms of percent difference, decreasing by more than 80%
and over a narrower range of current densities (50 to 450 mA cm-2). Though, the absolute drop of
about 40% closely matched with the results obtained in this paper, as efficiency declined from
about 60% to roughly 20% over the tested range of current densities. The curvature of the power
curves in the simulated results agreed with the shape of the power density curve obtained by
Doherty et al. [17], although the latter curve rose to a local maximum of about 130 kW at 325 mA
cm-2. For comparison, the tested syngas types valued power outputs upward of 175 kW at the same
current density. Zhang et al. [16] determined a linear increase in power, however that study varied
ic over a smaller range (160 to 240 mA cm-2). Near-linearity was observed for that portion of the
power curves in this paper, and thus the results are in agreement with reference [16].
The minor discrepancies between the simulated results and those reported by Doherty et
al. [17] may again be attributed to differences in calculation methods and simulation inputs and
assumptions. For example, reference [17] used different equations than the ones used in this paper
to calculate certain performance metrics such as electrical efficiency and voltage loss due to ohmic,
activation, and concentration polarization.
5.4 Potential for Future Research
The potential for future research stems in-part from the calculation method used to convert anode
outlet composition and flowrates to electrochemical SOFC performance measurements.
Determining a method to utilize external programming software linked to Aspen Plus via user-
defined subroutines to allow for modelling of the electrochemical half-cell reactions is an example
of this. Such action would mitigate some of the limitations posed by the model, such as the inability
to detect anode pressure variation and polarization effects associated with the presence of sulfur
in the feed syngas stream.
Future research may focus on a subsequent user-defined subroutine detailing the
mechanism by which H2S occupies Ni-YSZ active sites and inhibits anodic H2 oxidation. Linking
104
this code to the SOFC model would allow for more effective prediction of the effects of sulfur
poisoning and therefore any requirements for pre-operation gas cleaning and sulfur removal.
A thermal analysis of the SOFC model would allow for a better understanding of the energy
requirements and the balance of plant for the system. Such an analysis could be based on both the
process as a whole and on the individual Aspen Plus block units in the flowsheet, and has
implications for studying the effects of varying inlet feed stream temperatures.
Finally, a cost analysis could be conducted on the system, both as a whole and on the
individual block units. The analysis could be based on the ascertained energy requirements and
feed stream raw materials supply costs. Consequently, knowledge of cost estimates would provide
an idea of the feasibility of scaling up the designed tubular SOFC system, from a practical
standpoint, for real-life implementation.
5.5 Concluding Remarks
In conclusion:
1. Syngas from the two biomass CLG processes operated well in the simulated SOFC and
their respective performance values were comparable to those reported in the literature.
CLG-1 syngas exhibited higher performance and thus that process is favourable to CLG-2
for power generation via SOFC operation.
2. CLG-1-WC syngas exhibited the greatest SOFC performance in terms of cell voltage, total
power output, and cell power, achieving respective values of 0.77 V, 133.01 kW, and
115.51 W cell-1. CLG-2-WC exhibited the lowest performance.
3. Increasing CO composition significantly improved cell voltage and total power output, but
had less of an effect on efficiency for both CLGs 1 and 2.
4. Increasing CO2 composition reduced performance overall. While almost no effect was
observed for CLG-2 syngas in the presence of CO2, large amounts of CO in CLG-1 syngas
allowed its performance to increase despite the presence of CO2. CO2 removal from the
CLG-1 process is not favourable for power generation via SOFC operation.
5. Increasing anode operating temperature increased performance parameters for each syngas
type, as was the case in the literature. Anode operating pressure variation had negligible
effects on performance due to limitations of the simulation software.
105
6. Cell voltage and total power output increased with increasing fuel utilization factor for all
syngas types, with efficiency increasing linearly. Voltage and efficiency decreased with
increasing current density, while total power output increased regardless of the drop in cell
voltage. The simulated utilization factor and current density sensitivities were comparable
to published trends.
7. Future research could focus on the development of user-defined subroutines linked to
Aspen Plus to model electrode half-cell reactions and sulfur poisoning mechanisms at the
anode. Thermal and economic analyses of the SOFC system would allow for improved
simulation-to-real-world predictability.
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107
Chapter VI
Integrated CLG-SOFC System
Integration of the biomass CLG and SOFC systems presents overall benefits to the combined
system. Designing the CLG process such that no syngas cleaning or pre-treatment is required prior
to being sent to the SOFC permits the direct integration of the two systems, and removes the
necessity for intermittent syngas post-processing. CLG-SOFC integration offers in situ separation
of syngas diluents such as CO2, N2, and H2O, in situ removal and capture of SOFC performance
inhibitors such as H2S, and in situ tar and char reforming processes.
The regeneration of CaO sorbent via CaCO3 dissociation in CLG 1 occurs at the relatively
high temperature of 850 °C. Large quantities of heat are required to both achieve and maintain the
necessary temperature for maximum sorbent regeneration, thereby increasing energy costs. For
example, Figure 4.2 of Chapter IV shows the use of electric heaters for CaO regeneration in CLG
1. However, the requirement for external heating can be minimized with the use of an integrated
CLG-SOFC system by recycling the high-quality waste heat of the SOFC exhaust stream. Table
5.7 of Chapter V shows that the exhaust streams exit the SOFC stack at more than 830 °C.
Therefore, the use of this heat to drive sorbent regeneration would reduce heating costs and
improve the overall efficiency of the combined system.
As an added benefit, the CO2 present in the SOFC exhaust stream could combine with the
desorbed CO2 from the sorbent regeneration reaction to increase the flowrate of the CO2-rich
product stream used for sequestration or other processes requiring CO2. Furthermore, the H2O
present in the exhaust could be separated via condensation. The N2 present in the exhaust would,
however, dilute the CO2 product stream. The issue of CO2 dilution may be addressed through the
use of indirect heating via heat exchangers applied to the sorbent regeneration step of the process.
For example, the electric heaters shown in Figure 4.2 could be replaced with a heat exchanger unit
as a heat source for sorbent regeneration. Indirect heating would therefore prevent mixing of the
product CO2 stream with the N2 present in SOFC stack exhaust.
The benefit of recycling the SOFC exhaust stream heat may not exist for CLG 2 in the
same manner that it exists for CLG 1. The heat quality of the exhaust stream is too low to provide
sufficient heat to the combustion unit, which operates at 1250 °C. External heating would be
108
required to account for the > 400 °C temperature difference between the exhaust stream and the
reactor operating temperature required for the thermo-oxidative conversion of Fe3O4 to Fe2O3.
However, this requirement for external heating is still desirable in comparison to heating the
combustion unit from ambient conditions to the combustion temperature. Moreover, recycling the
exhaust heat to another high temperature reactor, the reducer, which operates at 870 °C, would
significantly reduce the required external heating to that reactor. However, both the CO2 and N2
present in the exhaust would ultimately dilute the syngas product stream since their respective
removals are not inherent to the CLG 2 process. This leads to reduced SOFC performance and
lower power generation. The extra H2O provided by the exhaust stream to the reducer would be
separated from the syngas via condensation in downstream reactors. The same issues arise when
considering recycle of the exhaust stream heat to the oxidizer, which operates at 720 °C and would
require no external heating when using the exhaust stream as a heat source.
Although the combined CLG-SOFC system using CLG 2 is not as well matched as with
CLG 1, the integrated system is still beneficial and more efficient when altering the system to
employ the use of heat exchangers. The exchangers would make use of the majority of the high
quality heat from the SOFC exhaust stream without diluting the syngas product stream with CO2
and N2. Thus, the use of this heat as a heat source to the reactors would decrease energy expenses
and increase the overall efficiency of the combined system.
Overall, the integration of the CLG 1 and SOFC systems provides the best match in terms
of SOFC performance and system efficiency improvements. These benefits arise in the form of
near-sufficient heating from the SOFC stack exhaust stream to the CaCO3 dissociation reaction.
Further, the removal of CO2 diluent from the syngas product stream is beneficial for SOFC
operation and performance, and for applications involving CO2 sequestration. Finally, CLG 1 is a
better match than CLG 2 since the exhaust heat is not solely sufficient for the high temperature
reactors of the latter and the requirement for external heating still exists.
109
Chapter VII
Conclusions and Recommendations
6.1 Overall Conclusions
Overall, it was found that:
H2 compositions in CLGs 1 and 2 syngas were 92.45 and 62.94 mol-%, respectively, when
using poultry litter (PL) as the biomass type and Aspen Plus as the simulation software.
Therefore, CLG 1 exhibited greater high-purity H2 syngas production capabilities.
Syngas yields for CLGs 1 and 2 were 0.87 and 2.54 kmol / kmol PL, respectively. Thus,
CLG 2 demonstrated greater absolute syngas production capabilities.
Although both CLG processes performed well in the simulated tubular SOFC, CLG 1
syngas demonstrated superior performance and is therefore the favourable process for
power generation by SOFC operation.
Modifying the CLG 1 process to exclude CO2 removal improved its performance as a result
of elevated amounts of CO present in the syngas. Very little effect on SOFC performance
was observed when modifying CLG 2 to include CO2 removal. In general, increasing
syngas CO2 concentration while maintaining fixed proportions of the other constituents
reduced performance.
Increasing syngas CO concentration greatly improved SOFC cell voltage and total power
output for both CLG types. Less of an increase was observed for electrical efficiency in
both cases.
The results of both of the biomass CLG processes and the tubular SOFC simulation
compared well to published literature in terms of absolute values and operating parameter
sensitivity trends.
The reduction of heating costs and the improvement of overall efficiency can be achieved
by recycling high quality heat from the SOFC exhaust in the integrated CLG-SOFC system.
110
6.2 Limitations of Research
The results of the conducted research were limited in-part by aspects of the utilized methods for
data acquisition. The limitations mainly stemmed from the Aspen Plus simulation software, the
employed calculation methods, and the assumptions used to simplify implementation of the former
two. The following lists the research limitations in greater detail.
Aspen Plus does not contain the required thermophysical or kinetic data regarding biomass
components to allow for the occurrence of spontaneous biomass steam gasification in an
equilibrium-based reactor. User-defined gasifier output is necessary when using
nonconventional biomass components. This limitation restricted sensitivity analyses from
variation of parameters such as SBR, SCR, Ca/C, and equivalence ratio.
Aspen Plus is unable to model electrochemical reactions as it does not recognize the input
of, and interaction between, ionic components. Consequently, the overall SOFC cell
reaction for operation on H2 was modelled as opposed to the anodic and cathodic half-cell
reactions. Considering the direct anodic oxidation of any reacted CO or CH4 also was not
possible as a result.
The mechanism by which H2S inhibits H2 oxidation at the anode and subsequently reduces
SOFC performance could not be modelled in Aspen Plus. This limitation restricted the
sensitivity analysis from variation of H2S levels in the syngas feed stream.
The assumption that all reacted CO and CH4 fed to the simulated SOFC was converted to
H2 implies that direct anodic oxidation did not occur for either of the fuels. Both are
equilibrium reactions and, although the assumption is valid as an approximation, will not
go entirely to completion during pre-reforming. Thus, some direct anodic oxidation of both
carbonaceous fuels is possible under the simulated conditions. This has further implications
regarding carbon deposition at the anode and consequent performance degradation, the
mechanism of which could not be modelled in Aspen Plus.
The reference voltage used to acquire SOFC cell voltage, electrical efficiency, and total
power output values was based on a semi-empirical reference curve developed for a fuel
stream consisting of 67% H2, 22% CO, and 11% H2O at standard operating conditions of
1000 °C, 1 bar, 85% fuel utilization factor, and 25% air utilization factor. Both CLGs 1 and
111
2 had compositions different from that of the reference fuel stream and therefore the
literature reference voltage was used in approximation and for the simplicity of the model.
The simulated results were compared to literature values, however no experimentation was
conducted to further validate the obtained data. Lab-scale experiments regarding the steam
gasification of poultry litter for H2 production with subsequent SOFC operation on the
resultant syngas would provide this data for comparison to the simulated results.
6.3 Recommendations for Future Research
This thesis presents research conducted on two very broad fields in engineering and science and it
was therefore not possible to explore all aspects of the fields. The following is a list of suggested
topics that may aid in further understanding the covered concepts.
Linking an external programming software to the Aspen Plus simulation flowsheet via
user-defined subroutines would allow for the increased efficacy of both the biomass CLG
and SOFC simulated processes. This would mitigate or eliminate some of the limitations
posed by the models. Biomass gasification could occur spontaneously in an equilibrium-
based unit module rather than in a module based on user-defined outputs. The inability to
detect anode pressure variation and the mechanism by which H2S inhibits anodic H2
oxidation would also be corrected. A user-defined subroutine to allow Aspen Plus to
integrate electrochemical reactions is an example of this.
Considering the presence of sulfur and nitrogen compounds in the poultry litter feedstock
and determining their respective effects on the H2 composition and production capabilities
of CLGs 1 and 2 would further increase the real-world accuracy of the processes.
A thermal analysis of the models would provide a better understanding of the energy
requirements for both systems. This analysis could be based both on the processes as a
whole and the individual Aspen Plus unit modules.
A cost analysis of the models would provide deeper insight into the feasibility and
scalability of the processes from an economic perspective. This analysis could be based on
system energy requirements and feed stream raw material supply expenses.
112
Appendices
Appendix Table of Contents
APPENDIX LIST OF TABLES ............................................................................................... 113
APPENDIX LIST OF FIGURES.............................................................................................. 114
Appendix A: Biomass Chemical Formula Calculations ...................................................... 115
A.1 Poultry Litter Calculations ................................................................................... 115
A.2 Willow Pellet Calculations .................................................................................. 116
A.3 Oak Pellet Calculations ........................................................................................ 117
Appendix B: Raw Data for Biomass CLG Simulation ........................................................ 118
B.1 CLG 1 Raw Data .................................................................................................. 118
B.2 CLG 2 Raw Data .................................................................................................. 121
Appendix C: Sensitivity Analyses for Biomass CLG Simulation ....................................... 123
C.1 CLG 1 Sensitivity Analysis Plots......................................................................... 123
C.2 CLG 2 Sensitivity Analysis Plots......................................................................... 125
Appendix D: Raw Data for SOFC Simulation ..................................................................... 127
D.1 CLG-1-NC Raw Data .......................................................................................... 127
D.2 CLG-1-WC Raw Data ......................................................................................... 128
D.3 CLG-2-WC Raw Data ......................................................................................... 129
D.4 CLG-2-NC Raw Data .......................................................................................... 130
113
Appendix List of Tables
Appendix A
Table A.1. Poultry litter chemical formula calculations including nitrogen and sulfur ........... 115
Table A.2. Poultry litter chemical formula calculations without nitrogen or sulfur present .... 115
Table A.3. Willow pellet chemical formula calculations including nitrogen and sulfur .......... 116
Table A.4. Willow pellet chemical formula calculations without nitrogen or sulfur present ... 116
Table A.5. Oak pellet chemical formula calculations including nitrogen and sulfur ............... 117
Table A.6. Oak pellet chemical formula calculations without nitrogen or sulfur present ........ 117
Appendix B
Table B.1.1. CLG 1 simulation raw data (part 1 of 3) .............................................................. 118
Table B.1.2. CLG 1 simulation raw data (part 2 of 3) .............................................................. 119
Table B.1.3. CLG 1 simulation raw data (part 3 of 3) .............................................................. 120
Table B.2.1. CLG 2 simulation raw data (part 1 of 2) .............................................................. 121
Table B.2.2. CLG 2 simulation raw data (part 2 of 2) .............................................................. 122
Appendix D
Table D.1. CLG-1-NC simulation results ................................................................................. 127
Table D.2. CLG-1-WC simulation results ................................................................................ 128
Table D.3. CLG-2-WC simulation results ................................................................................ 129
Table D.4. CLG-2-NC simulation results ................................................................................. 130
114
Appendix List of Figures
Appendix C
Fig. C.1. CLG 1 absorber temperature sensitivity analysis ...................................................... 122
Fig. C.2. CLG 1 absorber pressure sensitivity analysis ............................................................ 122
Fig. C.3. CLG 1 WGS reactor pressure sensitivity analysis ..................................................... 123
Fig. C.4. CLG 2 reducer pressure sensitivity analysis .............................................................. 124
Fig. C.5. CLG 2 oxidizer temperature sensitivity analysis ....................................................... 124
Fig. C.6. CLG 2 oxidizer steam flowrate sensitivity analysis ................................................... 125
Fig. C.7. CLG 2 reformer syngas composition temperature sensitivity analysis ..................... 125
115
Appendix A: Biomass Chemical Formula Calculations
A.1 Poultry Litter Calculations
Table A.1
Poultry litter chemical formula calculations including nitrogen and sulfur.
Element Wt.-% Mass (kg) Moles (kmol) Molecular Formula (based on C)
Carbon 43.3 0.433 5.20033 1
Hydrogen 6.62 0.0662 0.066862 0.012857261
Nitrogen 5.72 0.0572 0.801372 0.154100221
Sulfur 1.15 0.0115 0.368805 0.070919538
Oxygen 5.95 0.0595 0.952 0.183065305
Total 62.74 0.6274 7.389369
Ash 37.26
Table A.2
Poultry litter chemical formula calculations without nitrogen or sulfur present.
Element Mass (kg) Wt.-% Mass (kg/kg biomass) Moles (kmol) Molecular Formula (C-based)
Carbon 0.433 46.494148 0.46494148 5.583947171 1
Hydrogen 0.0662 7.1083432 0.071083432 0.071794266 0.0128573
Oxygen 0.0595 6.3889187 0.063889187 1.022226995 0.1830653
Ash 0.3726 40.00859 0.400085901 - -
Total 0.9313 100 1
116
A.2 Willow Pellet Calculations
Tab
Willow pellet chemical formula calculations including nitrogen and sulfur.
Element Wt.-% Mass (kg) Moles (kmol) Molecular Formula (based on C)
Carbon 50.65 0.5065 6.083065 1
Hydrogen 5.86 0.0586 0.059186 0.009729635
Nitrogen 0.52 0.0052 0.072852 0.011976199
Sulfur 0.44 0.0044 0.141108 0.023196859
Oxygen 24.07 0.2407 3.8512 0.633101898
Total 81.54 0.8154 10.207411
Ash 18.46
Table A.4
Willow pellet chemical formula calculations without nitrogen or sulfur present.
Element Mass (kg) Wt.-% Mass (kg/kg biomass) Moles (kmol) Molecular Formula (C-based)
Carbon 0.5065 51.14095315 0.511409532 6.14202847 1
Hydrogen 0.0586 5.916801292 0.059168013 0.05975969 0.0097296
Oxygen 0.2407 24.30331179 0.243033118 3.88852989 0.6331019
Ash 0.1846 18.63893376 0.186389338 - -
Total 0.9904 100 1
117
A.3 Oak Pellet Calculations
Table A.5
Oak pellet chemical formula calculations including nitrogen and sulfur.
Element Wt.-% Mass (kg) Moles (kmol) Molecular Formula (based on C)
Carbon 52.23 0.5223 6.272823 1
Hydrogen 6.59 0.0659 0.066559 0.010610693
Nitrogen 0.62 0.0062 0.086862 0.013847354
Sulfur 0.29 0.0029 0.093003 0.014826339
Oxygen 33.98 0.3398 5.4368 0.866723005
Total 93.71 0.9371 11.956047
Ash 6.29
Table A.6
Oak pellet chemical formula calculations without nitrogen or sulfur present.
Element Mass (kg) Wt.-% Mass (kg/kg biomass) Moles (kmol) Molecular Formula (C-based)
Carbon 0.5223 52.70965789 0.527096579 6.33042991 1
Hydrogen 0.0659 6.65051973 0.066505197 0.06717025 0.0106107
Oxygen 0.3398 34.29205773 0.342920577 5.48672924 0.866723
Ash 0.0629 6.347764658 0.063477647 - -
Total 0.9909 100 1
118
Appendix B: Raw Data for Biomass CLG Simulation
B.1 CLG 1 Raw Data
Table B.1.1
CLG 1 simulation raw data (part 1 of 3).
ABS-
IN
ABS-
OUT
BIOMA
SS CAO
CAO-
FEED
CAO-
OUT
COND-
IN
DES-
OUT
GAS-
OUT
Temperature C 750 500 25 650 25 25 750 650 25
Pressure bar 1.013 1.013 1.013 1.013 1.013 1.013 1.013 1.013 1.013
Mass VFrac 0.927 0.015 0 0 0 0 0.999 0.823 0.018
Mass SFrac 0.073 0.985 1 1 1 1 0.001 0.177 0
*** ALL
PHASES ***
Mass Flow
kg/hr
32.96
7 369.432 14.952
336.12
8 336.464 336.128 2.848
1897.8
82
1561.75
5
Volume Flow
cum/hr
149.4
27 39.09 0.013 0.102 0.102 0.102 73.487
6518.1
59 41.048
Enthalpy
Gcal/hr
-
0.027 -0.95 -0.011 -0.863 -0.91 -0.909 0.003 -5.344 -5.831
Density
kg/cum 0.221 9.451
1133.79
6
3297.6
32
3297.63
2
3297.63
2 0.039 0.291 38.047
Mass Flow
kg/hr
H2 1.556 0.601 0 0 0 0 1.63 1.998 1.998
WATER 1.762 0.226 0 0 0 0 0.055 1513.4
42
1513.44
2
CO 21.29
7 0.015 0 0 0 0 0.314 0.168 0.168
CO2 5.564 0.005 0 0 0 0 0.002 45.811 45.811
CH4 0.378 4.86 0 0 0 0 0.844 0 0
O2 0 0 0 0 0 0 0 0 0
C 2.41 3.106 0 0 0 0 0.003 0 0
CAO 0 3.06E+
02 0
336.12
8 336.464 336.128 0
336.46
4 0.336
CACO3 0 54.933 0 0 0 0 0 0 0
BIOMASS 0 0 14.952 0 0 0 0 0 0
119
Table B.1.2
CLG 1 simulation raw data (part 2 of 3).
GAS
ES
GASE
S-2
GASIF-
IN
H2O-
FEED
H2O-
OUT
REF-
IN
SOL-
IDS
STE-
AM
SYN-
GAS
Temperature C 500 650 750 25 20 750 500 240 20
Pressure bar 1.013 1.013 1.013 1.013 10.133 1.013 1.013 1.013 10.133
Mass VFrac 0.94 1 0.546 0 0 1 0 1 1
Mass SFrac 0.06 0 0.454 0 0.145 0 1 0 0
*** ALL
PHASES ***
Mass Flow kg/hr 6.07 1561.7
55 32.967 18.015 0.022 32.967
363.36
1
1531.2
99 2.826
Volume Flow
cum/hr
38.97
5
6518.0
57 83.969 0.018 0
1.70E+
02
1.14E-
01
3579.1
01 2.103
Enthalpy
Gcal/hr
-
0.004 -4.48 -0.055 -0.068 0 -0.019 -0.946 -4.759 -0.001
Density kg/cum 0.156 0.24 0.393 993.957 1084.94
2 0.194
3175.7
68 0.428 1.344
Mass Flow kg/hr
H2 0.601 1.998 0 0 0 1.848 0 0 1.63
WATER 0.226 1513.4
42 18.015 18.015 0.019 0 0
1531.2
99 0.036
CO 0.015 0.168 0 0 0 31.119 0 0 0.314
CO2 0.005 45.811 0 0 0 0 0 0 0.002
CH4 4.86 0 0 0 0 0 0 0 0.844
O2 0 0 0 0 0 0 0 0 0
C 0.003 0 0 0 0.003 0 3.103 0 0
CAO 0.306 0.336 0 0 0 0 305.38 0 0
CACO3 0.055 0 0 0 0 0 54.878 0 0
BIOMASS 0 0 14.952 0 0 0 0 0 0
120
Table B.1.3
CLG 1 simulation raw data (part 3 of 3).
TAR WGS-IN WGS-OUT
Temperature C 750 750 750
Pressure bar 1.013 1.013 1.013
Mass VFrac 0 0.94 0.469
Mass SFrac 1 0.06 0.531
*** ALL PHASES ***
Mass Flow kg/hr 3.222 6.07 6.07
Volume Flow cum/hr 0.001 51.578 73.488
Enthalpy Gcal/hr 0 -0.003 0.003
Density kg/cum 2327.14 0.118 0.083
Mass Flow kg/hr
H2 0 0.601 1.63
WATER 0 0.226 0.055
CO 0 0.015 0.314
CO2 0 0.005 0.002
CH4 0 4.86 0.844
O2 0 0 0
C 2.886 0.003 2.889
CAO 0.336 0.306 0.336
CACO3 0 0.055 0
BIOMASS 0 0 0
121
B.2 CLG 2 Raw Data
Table B.2.1
CLG 2 simulation raw data (part 1 of 2).
Parameter
FE+
TAR
FE2
O3
FE3O4-
EX
FE3O4
-IN
GASE
S-1
GASE
S-2
H2+
CO
H2O+
GAS O2
OXID-
OUT
Temperature C 870 1250 720 25 870 720 750 20 25 720
Pressure bar 30.398
1.01
3 30.398 1.013 30.398 30.398 1.013 1.013
1.0
13 30.398
Mass VFrac 0
0.24
7 0 0 1 1 1 0 1 0.977
Mass SFrac 1
0.75
3 1 1 0 0 0 0 0 0.023
*** ALL
PHASES ***
Mass Flow
kg/hr 7.465
11.7
75 8.558 8.576 33.981
359.21
2 29.67
350.27
7 3.2 367.77
Volume Flow
cum/hr 0.001
11.3
8 0.002 0.002 4.897 54.616
153.0
82 0.35
2.4
47 54.617
Enthalpy
Gcal/hr 0.001
-
0.00
7 -0.009 -0.01 -0.045 -1.021
-
0.017 -1.32 0 -1.03
Density
kg/cum
5449.1
98
1.03
5 5200.31
5200.3
1 6.938 6.577 0.194
1001.7
53
1.3
08 6.734
Mass Flow
kg/hr
H2 0 0 0 0 0.848 0.721 1.66 0.002 0 0.721
CO 0 0 0 0 15.14 0.036 28.01 0.004 0 0.036
CO2 0 0 0 0 12.244 4.582 0 5.099 0 4.582
H2O 0 0 0 0 4.525
353.86
5 0
345.15
5 0 353.865
CH4 0 0 0 0 1.216 0 0 0 0 0
C 1.266 0 0 0 0.001 0 0 0 0 0
O2 0
2.90
4 0 0 0 0 0 0 3.2 0
FE 6.199 0 0 0 0.006 0 0 0 0 0
FE2O3 0
8.87
2 0 0 0 0 0 0 0 0
FE3O4 0 0 8.558 8.576 0 0.009 0 0.017 0 8.567
122
Table B.2.2
CLG 2 simulation raw data (part 2 of 2).
Parameter REDU-OUT REF-OUT STEAM SYNGAS
Temperature C 870 500 240 20
Pressure bar 30.398 1.013 32.424 1.013
Mass VFrac 0.82 1 1 1
Mass SFrac 0.18 0 0 0
*** ALL PHASES ***
Mass Flow kg/hr 41.446 393.193 360.306 42.916
Volume Flow cum/hr 4.899 1384.416 26.317 61.244
Enthalpy Gcal/hr -0.044 -1.114 -1.12 -0.085
Density kg/cum 8.46 0.284 13.691 0.701
Mass Flow kg/hr
H2 0.848 3.234 0 3.233
CO 15.14 0.447 0 0.443
CO2 12.244 43.275 0 38.176
H2O 4.525 346.207 360.306 1.053
CH4 1.216 0.012 0 0.012
C 1.267 0 0 0
O2 0 0 0 0
FE 6.205 0 0 0
FE2O3 0 0 0 0
FE3O4 0 0.017 0 0
123
Appendix C: Sensitivity Analyses for CLG Simulation
C.1 CLG 1 Sensitivity Analysis Plots
Fig. C.1. CLG 1 absorber temperature sensitivity analysis.
Fig. C.2. CLG 1 absorber pressure sensitivity analysis.
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0
0.2
0.4
0.6
0.8
1
1.2
300 400 500 600 700 800
Yie
ld:
km
ol/
km
ol
PL
Absorber Temperature (°C)
CO2 Production and Capture Efficiency vs. Absorber Temperature
H2 Exiting Absorber CO Exiting Abs CH4 Exiting Abs
CO2 Product Stream CO2 Capture Efficiency
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0
0.2
0.4
0.6
0.8
1
1.2
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Cap
ture
Eff
icie
ncy
(%
)
Yie
ld:
km
ol/
km
ol
PL
Absorber Pressure (atm)
CO2 Production and Capture Efficiency vs. Absorber Pressure
H2 Exiting Absorber CO Exiting Abs CH4 Exiting Abs
CO2 Product Stream CO2 Capture Efficiency
124
Fig. C.3. CLG 1 WGS reactor pressure sensitivity analysis.
0
0.002
0.004
0.006
0.008
0.01
0.012
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Yie
ld:
km
ol/
km
ol
PL
(C
O,
CO
2,
H2O
)
Yie
ld:
km
ol/
km
ol
PL
(H
2an
d C
H4)
WGS Reactor Pressure (atm)
Syngas Yield vs. WGS Reactor Pressure
H2 CH4 CO CO2 H2O
125
C.2 CLG 2 Sensitivity Analysis Plots
Fig. C.4. CLG 2 reducer pressure sensitivity analysis.
Fig. C.5. CLG 2 oxidizer temperature sensitivity analysis.
0
0.1
0.2
0.3
0.4
0.5
0.6
30 31 32 33 34 35 36 37
Yie
ld:
km
ol/
km
ol
PL
Reducer Pressure (atm)
Reducer Exit Yield vs. Pressure at 870°C
H2 CO CO2 H2O CH4 Tar Fe Fe3O4
0
0.0005
0.001
0.0015
0.002
0.0025
0.003
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
600 620 640 660 680 700 720
Yie
ld:
km
ol/
km
ol
(CO
and
CH
4)
Yie
ld:
km
ol/
km
ol
PL
(H
2, C
O2,
Fe 3
O4)
Oxidizer Temperature (°C)
Oxidizer Exit Yield vs. Temperature at 30 atm
H2 CO2 Fe3O4 CO CH4
126
Fig. C.6. CLG 2 oxidizer steam flowrate sensitivity analysis.
Fig. C.7. CLG 2 reformer syngas composition temperature sensitivity analysis.
0
0.005
0.01
0.015
0.02
0.025
0.03
0.035
0.04
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
5 7 9 11 13 15 17 19 21 23 25
Yie
ld:
km
ol/
km
ol
(CO
, C
H4,
Fe 3
O4)
Yie
ld:
km
ol/
km
ol
(H2
and
CO
2)
Steam Flowrate (kmol/h)
Oxidizer Exit Yield vs. Steam Flowrate at 720°C and 30 atm
H2 CO2 CO CH4 Fe3O4
0.0%
0.5%
1.0%
1.5%
2.0%
2.5%
3.0%
3.5%
0%
10%
20%
30%
40%
50%
60%
70%
400 450 500 550 600 650 700 750 800 850
Co
mp
osi
tio
n (
CO
, H
2O
, C
H4)
Co
mp
osi
tio
n (
H2
and
CO
2)
Reformer Temperature (°C)
Syngas Composition vs. Reformer Temperature
H2 CO2 CO H2O CH4
127
Appendix D: Raw Data for SOFC Simulation
D.1 CLG-1-NC Raw Data
Table D.1
CLG-1-NC simulation results.
AIR AIR-
DEPL
AN-
PROD
BURN-
IN
BURN-
OUT
CATH-
IN
EXH-
AUST
GAS-
WARM
HOT-
SIDE O2
SYN-
GAS
kmol/hr
H2 0 0 0.018608 0 0 0 0 0.806931 0 0 0.806931
H2O 0 0 0.895492 0 0.9141 0 0.9141 0.001998 0.9141 0 0.001998
O2 8.4 7.896 9.22E-13 7.896 7.885758 8.4 7.885758 0 7.885758 0.504 0
N2 31.6 31.6 0 31.6 31.6 31.6 31.6 0 31.6 0 0
C 0 0 2.91E-29 0 0 0 0 0 0 0 0
CO 0 0 0.001876 0 0 0 0 0.01121 0 0 0.01121
CO2 0 0 0.061966 0 0.063841 0 0.063841 4.54E-05 0.063841 0 4.54E-05
CH4 0 0 3.84E-12 0 3.83E-12 0 3.83E-12 0.052586 3.83E-12 0 0.052586
Total Flow
kmol/hr 40 39.496 0.977941 39.496 40.4637 40 40.4637 0.87277 40.4637 0.504 0.87277
Total Flow
kg/hr 1154.016 1137.888 18.94968 1137.888 1156.838 1154.016 1156.838 2.82229 1156.838 16.1274 2.82229
Total Flow
l/min 49405.95 59076.83 1635.882 63907.57 65473.38 59830.69 61077.65 1412.209 71137.25 753.8667 34.99041
Temperature
C 630 820.5662 950 910 910 820.5662 830.566 910 1012.35 820.5662 20
Pressure bar 1.01325 1.01325 1.01325 1.01325 1.01325 1.01325 1.01325 1.01325 1.01325 1.01325 10.1325
128
D.2 CLG-1-WC Raw Data
Table D.2
CLG-1-WC simulation results.
AIR AIR-
DEPL
AN-
PROD BURN-IN
BURN-
OUT CATH-IN
EXH-
AUST
GAS-
WARM
HOT-
SIDE O2
SYN-
GAS
kmol/hr
H2 0 0 0.010795 0 0 0 0 0.770297 0 0 0.770297
H2O 0 0 0.810309 0 0.821104 0 0.821104 0.003829 0.821104 0 0.003829
O2 8.4 7.602 3.97E-12 7.602 7.587955 8.4 7.587955 0 7.587955 0.798 0
N2 31.6 31.6 0 31.6 31.6 31.6 31.6 0 31.6 0 0
C 0 0 1.72E-28 0 0 0 0 0 0 0 0
CO 0 0 0.017294 0 0 0 0 0.759836 0 0 0.759836
CO2 0 0 0.891184 0 0.908478 0 0.908478 0.125153 0.908478 0 0.125153
CH4 0 0 2.44E-12 0 0 0 0 0.023489 0 0 0.023489
Total Flow
kmol/hr 40 39.202 1.729583 39.202 40.91754 40 40.91754 1.682604 40.91754 0.798 1.682604
Total Flow
kg/hr 1154.016 1128.481 54.32496 1128.481 1182.806 1154.016 1182.806 28.78992 1182.806 25.53504 28.78992
Total Flow
l/min 49405.95 58753.6 2893.213 63431.86 66207.73 59949.59 61884.33 2722.584 71935.12 1195.994 67.45691
Temperature
C 630 822.7397 950 910 910 822.7397 832.7397 910 1012.35 822.7397 20
Pressure bar 1.01325 1.01325 1.01325 1.01325 1.01325 1.01325 1.01325 1.01325 1.01325 1.01325 10.1325
129
D.3 CLG-2-WC Raw Data
Table D.3
CLG-2-WC simulation results.
AIR AIR-
DEPL
AN-
PROD BURN-IN
BURN-
OUT CATH-IN
EXH-
AUST
GAS-
WARM
HOT-
SIDE O2
SYN-
GAS
kmol/hr
H2 0 0 0.01376 0 0 0 0 1.600495 0 0 1.600495
H2O 0 0 1.646666 0 1.660426 0 1.660426 0.058435 1.660426 0 0.058435
O2 8.4 7.602 2.83E-12 7.602 7.590349 8.4 7.590349 0 7.590349 0.798 0
N2 31.6 31.6 0 31.6 31.6 31.6 31.6 0 31.6 0 0
C 0 0 8.55E-30 0 0 0 0 0 0 0 0
CO 0 0 0.009543 0 0 0 0 0.015816 0 0 0.015816
CO2 0 0 0.87446 0 0.884003 0 0.884003 0.867439 0.884003 0 0.867439
CH4 0 0 1.35E-12 0 0 0 0 0.000748 0 0 0.000748
Total Flow
kmol/hr 40 39.202 2.544429 39.202 41.73478 40 41.73478 2.542933 41.73478 0.798 2.542933
Total Flow
kg/hr 1154.016 1128.481 68.445 1128.481 1196.926 1154.016 1196.926 42.90996 1196.926 25.53504 42.90996
Total Flow
l/min 49405.95 58876.02 4117.082 63431.86 67530.09 60074.51 63250.44 4114.662 73371.87 1198.486 1019.459
Temperature
C 630 825.0232 910 910 910 825.0232 835.0191 910 1012.35 825.0232 20
Pressure bar 1.01325 1.01325 1.01325 1.01325 1.01325 1.01325 1.01325 1.01325 1.01325 1.01325 1.01325
130
D.4 CLG-2-NC Raw Data
Table D.4
CLG-2-NC simulation results.
AIR AIR-
DEPL
AN-
PROD BURN-IN
BURN-
OUT CATH-IN
EXH-
AUST
GAS-
WARM
HOT-
SIDE O2
SYN-
GAS
kmol/hr
H2 0 0 0.023041 0 0 0 0 1.618812 0 0 1.618812
H2O 0 0 1.634285 0 1.657326 0 1.657326 0.038402 1.657326 0 0.038402
O2 8.4 7.602 3.40E-12 7.602 7.590446 8.4 7.590446 0 7.590446 0.798 0
N2 31.6 31.6 0 31.6 31.6 31.6 31.6 0 31.6 0 0
C 0 0 7.05E-31 0 0 0 0 0 0 0 0
CO 0 0 6.70E-05 0 0 0 0 7.14E-05 0 0 7.14E-05
CO2 0 0 0.003264 0 0.003331 0 0.003331 0.003204 0.003331 0 0.003204
CH4 0 0 4.95E-14 0 0 0 0 5.61E-05 0 0 5.61E-05
Total Flow
kmol/hr 40 39.202 1.660657 39.202 40.8511 40 40.8511 1.660545 40.8511 0.798 1.660545
Total Flow
kg/hr 1154.016 1128.481 29.63409 1128.481 1158.115 1154.016 1158.115 4.099048 1158.115 25.53504 4.099048
Total Flow
l/min 49405.95 58702.99 2777.916 63431.86 66100.23 59897.96 61731.33 2686.89 71818.32 1194.964 665.7045
Temperature
C 630 821.7958 950 910 910 821.7958 831.7995 910 1012.35 821.7958 20
Pressure bar 1.01325 1.01325 1.01325 1.01325 1.01325 1.01325 1.01325 1.01325 1.01325 1.01325 1.01325
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