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System studies of MCFC power plants
BENNY FILLMAN
Licentiate Thesis
Stockholm, Sweden 2005
TRITA KET R213
ISSN 1104-3466
ISRN KTH/KET/R--213/--SE
KTH, Kemisk Reaktionsteknik
Teknikringen 42
SE-100 44 Stockholm
Akademisk avhandling som med tillstånd av Kungl Tekniska högskolan fram-
lägges till offentlig granskning för avläggande av Licenciatexamen 2005-09-23
i seminarierum 591, Teknikringen 42, KTH, Stockholm.
c© Benny Fillman, 2005-09-01 Typsatt i LATEX2ε
Tryck: Universitetsservice US AB
iii
Tillägnad min far Kurt och farmor Edit
iv
v
Sammanfattning
Bränslecellen är en elektrokemisk reaktor som kan direkt omvandla kem-
iskt bunden energi till elektrisk energi. I stationär kraftproduktion är själva
bränslecellsstapeln endast en mindre komponent i systemet. Integrationen
av kringutrustningen, den s.k. Balance-of-Plant (BoP), som tex. pumpar,
kompressorer och värmeväxlare är en av huvudfrågeställningarna i studierna
av bränslecellskraftverk.
Denna avhandling avser systemstudier av smältkarbonatbränslecellsbaserade
(MCFC) kraftverk. Systemstudierna har utförts med processimuleringpro-
gramet Aspen PlusTM.
Artikel I beskriver en utvecklad MCFC-cellmodell, som implementeras som
"user model" i Aspen Plus, för att studera ett naturgasbaserat bränslecells-
kraftverk.
Artikel II beskriver hur olika processparametrar, som tex bränsleutnyttjande
och val av bränsle, påverkar ett MCFC-kraftverks prestanda.
Nyckelord:
Bränsleceller, bränslecellssystem, systemstudier, processimulering, smältkar-
bonatbränslecell, MCFC
vi
Zusammenfassung
Die Brennstoffzelle ist ein elektrochemischer Reaktor und wandelt chemisch
gebundene Energie direkt in elektrische Energie um. In der stationären Ener-
gieerzeugung ist der Brennstoffzellenstapel selbst nur ein kleiner Bestandteil
des vollständigen Systems. Die Integration aller zusätzlichen Bestandteile,
der Peripheriegeräte (Balance-of-Plant) (BoP), ist eine der Hauptaufgaben
in der Studie der Brennstoffzellenkraftwerke.
Diese Untersuchung betrifft die Systemstudie des auf der Schmelz-Karbonat-
Brennstoffzelle (MCFC) basierten Kraftwerks. Die Systemstudie ist mit dem
Simulationprogramm Aspen PlusTM durchgeführt worden.
Artikel I beschreibt die Implementierung eines in Aspen PlusTM entwickel-
ten MCFC Stapelmodells, um ein MCFC Kraftwerk zu studieren, das Erdgas
als Brennstoff verwendet.
Artikel II beschreibt, wie unterschiedliche Prozeßparameter, wie Brenngas-
nutzung und die Wahl des Brennstoffes, die Leistung eines MCFC Kraftwerks
beeinflussen.
Stichwort:
Brennstoffzellen, Brennstoffzellensystem, Systemanalyse, Prozeßsimulation,
Schmelz-Karbonat-Brennstoffzelle, MCFC
vii
Abstract
A fuel cell is an electrochemical reactor, directly converting chemically bound
energy to electrical energy. In stationary power production the fuel cell stack
itself is only a small component of the whole system. The integration of all
the auxiliary components, the Balance-of-Plant (BoP), is one of the main
issues in the study of fuel cell power plants.
This thesis concerns the systems studies of molten carbonate fuel cell (MCFC)
based power plants. The system studies has been performed with the simu-
lation software Aspen PlusTM.
Paper I describes on the implementation of a developed MCFC stack model
into Aspen PlusTM in order to study an MCFC power plant fueled with
natural gas.
Paper II describes how different process parameters, such as fuel cell fuel
utilization, influence the performance of an MCFC power plant.
Keywords:
Fuel cells, fuel cell systems, system studies, process simulation, molten car-
bonate fuel cell, MCFC
viii
The work presented in this thesis is based on the following papers, refered
to by their Roman numerals. The papers are appended at the end of the
thesis.
I. B. Fillman, T. Kivisaari, P. Björnbom, C. Sylwan, M. Sparr,
G. Lindbergh A stack model for MCFC system studies for
process simulations
Accepted for publication in Journal of Power Sources
after minor revisions.
II. B. Fillman, P. Björnbom, C. Sylwan, M. Sparr, G. Lindbergh
Influence of process parameters on the system efficiency of a
natural gas or a gasified biomass fueled MCFC system
Manuscript to be submitted for publication.
Contents
Contents ix
List of Figures xi
List of Tables xii
Nomenclature xiii
1 Introduction 1
1.1. Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2. Objectives and scope of the work . . . . . . . . . . . . . . . . 2
1.3. Principle of fuel cells . . . . . . . . . . . . . . . . . . . . . . . 3
1.4. Some characteristics of the different kinds of fuel cells . . . . 18
1.5. Balance of Plant (BoP) . . . . . . . . . . . . . . . . . . . . . 23
1.6. Fueling fuel cells . . . . . . . . . . . . . . . . . . . . . . . . . 27
1.7. Review of modeling and system studies MCFC . . . . . . . . 35
2 Methodology (Paper I and Paper II) 45
3 Summary of Paper I 47
3.1. Fuel cell model . . . . . . . . . . . . . . . . . . . . . . . . . . 48
3.2. Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
3.3. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
4 Summary of Paper II 53
4.1. Fuel cell model . . . . . . . . . . . . . . . . . . . . . . . . . . 54
ix
x CONTENTS
4.2. The system studied . . . . . . . . . . . . . . . . . . . . . . . . 54
4.3. Results and conclusions . . . . . . . . . . . . . . . . . . . . . 54
5 Overall conclusions 59
6 Acknowledgements 61
Bibliography 63
List of Figures
1.1. Principle of a fuel cell. . . . . . . . . . . . . . . . . . . . . . . . . 4
1.2. Typical planar stack arrangement . . . . . . . . . . . . . . . . . . 5
1.3. System boundary of a reversible fuel cell. . . . . . . . . . . . . . 8
1.4. T-S diagram - Carnot Cycle. . . . . . . . . . . . . . . . . . . . . 10
1.5. The theoretical efficiencies for a heat engine and a fuel cell . . . . 11
1.6. Schematic of types of polarization in a fuel cell. . . . . . . . . . . 14
1.7. Schematic of anode off-gas recycling and CO2 generation. . . . . 22
1.8. Schematic of a fuel cell power plant system . . . . . . . . . . . . 25
1.9. Schematic representation of the placement of the reforming part. 26
1.10. Pathway for producing synthesis gas from biomass. . . . . . . . . 31
1.11. MTU HotModule schematic . . . . . . . . . . . . . . . . . . . . . 34
3.1. The electric efficiency versus the system pressure . . . . . . . . . 51
4.1. Schematic layout of fuel cell systems. . . . . . . . . . . . . . . . . 55
4.2. Relative power density (net) vs fuel utilization. . . . . . . . . . . 57
xi
xii List of Tables
List of Tables
1.1. Classification of fuel cell subtypes . . . . . . . . . . . . . . . . . . 6
1.2. Parameters and values used in the model in Paper I . . . . . . . 16
1.3. Parameters and values used in the model in Paper II . . . . . . . 17
1.4. Typical composition of natural gas . . . . . . . . . . . . . . . . . 28
3.1. Input and output parameters for the models . . . . . . . . . . . . 50
Nomenclature
Abbreviations
AC Alternating Current
AFC Alkaline Fuel Cell
AFCo Ansaldo Fuel Cells (Italy)
BoP Balance of Plant
CHP Combined Heat and Power
DASSL Differential Algebraic equation System Solver Library
DC Direct Current
DIR Direct Internal Reforming
EMF Electro-Motive-Force or open circuit voltage
ER External Reforming
ERC Energy Research Corporation
FCE Fuel Cell Energy Inc (USA)
GUI Graphical User Interface
GT Gas Turbine
IG Integrated Gasification
IGCC Integrated Gasification Combined-Cycle
IHI Ishikawajima-Harima heavy Industries (Japan)
IIR Indirect Internal Reforming
IR Internal Reforming
LHV Lower Heating Value
MCFC Molten Carbonate Fuel Cell
MTU Motoren-und Turbinen-Union (Germany)
NASA National Aeronautics and Space Administration
xiii
xiv NOMENCLATURE
OCV Open Circuit Voltage
PAFC Phosphoric Acid Fuel Cell
PEMFC Proton Electrolyte Membrane Fuel Cell
SOFC Solid Oxide Fuel Cell
SR Steam Reforming (reaction)
STIG Steam Injection Gas Turbine
YSZ Yttria Stabilized Zirconia
VOC Volatile Organic Compounds
VCS Villars-Cruise-Smith
WGS Water Gas Shift (reaction)
Symbols
cp Specific heat capacity at constant pressure [ J/(Kg·K) ]
C Concentration of chemical species [ mol/m3 ]
d Thickness of matrix [ m ]
D Diffusion coefficient [ m2/s ]
E Open circuit voltage [ V ]
E Equilibrium (standard) potential at standard
temperature and pressure, pure reactants [ V ]
F Faraday’s constant [ A·s ]
also Flow rate [ mol/s ]
G Gibbs’ free energy [ J/mol ]
H Enthalpy [ J/mol ]
H Enthalpy at standard temperature and pressure,
pure reactants [ J/mol ]
j Current density [ A/m2 ]
jL Limiting current density [ A/m2 ]
j0 Exchange current density [ A/m2 ]
Kp Equilibrium constant
n Number of electrons transferred in
an electrochemical reaction
P Total pressure [ Pa ]
Pi Partial pressure [ Pa ]
q Heat flow [ J/s ]
xv
Q Heat per mole reacted [ J/mol ]
R Universal gas constant [ J/(mol·K)]
also Electrical resistance [ Ω · m2 ]
S Entropy [ J/(mol·K)]
also Surface area [ m2 ]
T Temperature [ K ]
TL, TH Temperature at heat sink and heat source in
the Carnot cycle [ K ]
uf Fuel utilization [ % ]
w Work [ J/s ]
W Work per mole reactant reacted [ J/mol ]
Greek
α Charge transfer coefficient
∆ Change in. . .
δ Inexact differential form
also Thickness of the diffusion layer [ m ]
ǫ Porosity
η Efficiency
also Overpotential
κ Conductivity [ S/m ]
Subscripts
a Referring to the anodic side
B In the bulk
c Referring to the cathodic side
e Electrical
ir Internal resistance
m Referring to mass or concentration
rev Reversible
Rx Reacting
S At the surface
th thermal
xvi NOMENCLATURE
Chapter 1
Introduction
1.1. Background
As the oil reserves are drained within the next five decades or so, and with
the increased consciousness about environmental issues, it is recognized that
energy from fossil fuels has to be replaced by other alternative energy sources.
One way in that direction, that also meets environmental requirements, is
the so-called renewables. This could be producing syngas via gasification of
biomass. Biomass can be retrieved from a wide range of sources, for example
wood chips, forest residues, energy forest plantations or agricultural waste.
Different technologies exist that can convert the chemically bound energy
in biomass to a more useful form of energy, e.g. electricity. They are all in
principle based on one of the oldest skills of man, combustion. The combus-
tion of wood and other renewables was the first energy source for mankind [1].
However, combustion as a technology also has its drawbacks. Although
biomass, theoretically, has no net effect on the emission of greenhouse gases,
it produces some polluting gases, such as VOC (volatile organic compounds)
and dioxins. Another drawback is its limitation in efficiency in transform-
ing the heat into mechanical energy, which was theoretically described by
1
2 CHAPTER 1. INTRODUCTION
Carnot [2].
Another means of producing electricity, bypassing the combustion route, and
hence avoiding the Carnot limitation, is to convert the fuel by an electro-
chemical route. The solution is the fuel cell technology. Fuel cell technology
has a low environmental impact, where the reaction products basically con-
sist of water.
Christian Friedrich Schönbein discovered the fuel cell effect in 1838 [3], and
William Grove constructed the first fuel cell in 1839.
One of the most important issues regarding fuel cells and fuel cell systems is
the integration of the balance of plant, in order to reach higher efficiencies,
compared to the Carnot cycle, in the transformation of chemically bound
energy into electric energy.
1.2. Objectives and scope of the work
The objectives of this thesis lay emphasis on system studies of stationary fuel
cell power plants. The specific fuel cell type studied is the molten carbonate
fuel cell (MCFC). System studies is a tool to determine the overall system
parameters, for instance flows, gas compositions, temperatures and pressure.
These calculations are based on equations of mass and energy. The results of
the simulations provide information about system efficiency and component
selection for the Balance of Plant (BoP).
However, in order to perform these simulations, a mathematical model de-
scribing the fuel cell has to be developed. The level and complexity of the
mathematical model must be decided depending of the end-use. Due to the
complexity of the mix of components, e.g. heaters and reactors, for the fuel
cell system, the level of the model should be suitable for such systems, e.g.
the calculation times should be kept within reasonable limits, without losing
any vital information. The level cannot on the other hand be too simple due
to the loss of vital information for system evaluation.
Paper I presents the development of a one-dimensional molten carbonate
1.3. PRINCIPLE OF FUEL CELLS 3
fuel (MCFC) cell model used for a system study of a 500 kW (LHV) MCFC
power plant. Additionally the results from the study were compared with
the ones from a zero-dimensional model.
Paper II presents a system study of a 500 kW (LHV) MCFC power plant,
in order to investigate how gasified biomass versus natural gas impacts as a
fuel on the fuel cell system performance at various fuel cell fuel utilization
levels and cell voltages.
1.3. Principle of fuel cells
A fuel cell is an electrochemical reactor where chemical energy is directly
converted into electricity (DC) and in some cases also heat. In principle a
fuel cell consists of five main parts, a cathode (positive electrode) and an
anode (negative electrode) separated by an electrolyte, and the electrical
connectors which connects the electrodes via an external circuit (load). The
final constituent is the separator (bipolar) plate, used for separating the cells
in a stack, simultaneously connecting them electrically in series. They are
also distributing the reactant gas in the stack. The schematic diagram of
a fuel cell organization is shown in Figures 1.1 and 1.2. The reactants, the
fuel and the oxidant, are continuously fed to the anode and the cathode,
respectively. The fuel depends on the type of fuel cell, but mostly, hydro-
gen is the preferred fuel, and the oxidant is commonly oxygen in air. The
electrochemical reactions take place at the boundary of the three-phase zone
where the electrode, the electrolyte and the gas interact.
For instance, at the cathode side in the case of MCFC, oxygen and carbon
dioxide diffuse through the porous structure of the electrode towards the
electrolyte and are reduced. At the anode side hydrogen is oxidized. The
migration ion CO2−3
, forms at the cathode and carries the charge through
the electrolyte towards the anode side. It should be noted that the migra-
tion ion, e.g. H+, CO2−3
, OH− or O2−, depends on the fuel cell type. In
Table 1.1, the charger transfer ion and the corresponding fuel cell type are
outlined. In Figure 1.1 the route of the charge transfer ions is outlined. At
the anode side the electrons pass through the electrical connectors towards
4 CHAPTER 1. INTRODUCTION
Figure 1.1: Principle of a fuel cell.
the cathode. At the boundary on the cathode side, water is produced. Due
to ion transport through the electrolyte and the transfer of electrons, an
electrical circuit is created. The fuel cell produces electricity as long as the
reactants are fed to the electrodes.
By separating the combustion reaction,
H2 +1
2O2 → H2O (1.1)
1.3. PRINCIPLE OF FUEL CELLS 5
Figure 1.2: Typical planar stack arrangement [4]; with kind permission of
Springer Science and Business Media.
into two electrochemical reactions, e.g.
H2 + CO2−3
→ CO2 + H2O + 2e− (1.2a)
1
2O2 + CO2 + 2e− → CO2−
3(1.2b)
some advantages are gained, such as a more facile route in the conversion
of chemically bound energy into electricity. The transformation route in
combustion includes first the thermal conversion, succeeded by a conversion
into mechanical energy before the final production of electricity. The elec-
trochemical route in the conversion of energy eliminates those steps, hence
produces electricity directly. As mentioned before, the electrochemical route
is a more efficient energy transformation route, which circumvents the Carnot
efficiency limitation.
This can be easily seen by studying the first and second law of the ther-
modynamics of the two different routes.
The first law of thermodynamics states that energy of a system is conserved.
This results in the well-known statement that energy can neither be gener-
ated nor destroyed, just be transformed into a different form of energy.
δQ − δW = dE (1.3)
6C
HA
PT
ER
1.IN
TR
OD
UC
TIO
N
Table 1.1: Classification of fuel cell subtypes
Low Temperature High Temperature
Subtype AFC PEMFC PAFC MCFC SOFC
Electrolyte KOH Polymer H3PO4 KLiCO3 ZrO2 with
Y2O3
Operating <350 <350 <470 920 1120-1320
temperature [K]
Charge carrier OH− H+ H+ CO2−3
O2−
Internal reforming No No No Yes Yes
Catalyst Platinum Platinum Platinum Nickel Perovskites
Product water Evaporative Evaporative Evaporative Gaseous Gaseous
management product product
Product heat Process gas + Process gas + Process gas + Internal Internal
management Electrolyte Independent Independent reforming+ reforming+
circulation cooling medium cooling medium Process gas Process gas
Fuel H2 H2 H2 H2 and CO H2 and CO
Sensitivity to Yes/yes Yes/yes Yes/yes No/<10ppm H2S (anode) No/<1ppm
CO/ S <1ppm SO2 (cathode)
1.3. PRINCIPLE OF FUEL CELLS 7
The inexact differential forms, δ, of heat and work are due the fact that
their value is dependent on the path, hence they are called path functions.
However energy is a point function, hence only dependent on the initial and
terminal points.
Equation 1.3 can be reformulated as:
Q − W = ∆E (1.4)
The change in the total energy is for a closed system formulated as:
∆E = ∆U + ∆KE + ∆PE (1.5)
and for an open system an additional term, PV, is added, reflecting the work
to keep the fluid moving.
∆E = ∆U + ∆KE + ∆PE + ∆(PV ) (1.6)
where U, KE and PE are the internal, kinetic and potential energies. P and
V are the pressure and volume, respectively. At steady state both KE and
PE can be neglected.
The enthalpy is formulated as:
H = U + PV (1.7)
The energy balance in equation 1.4 can be reformulated as:
Q − W = ∆H (1.8)
Efficiency of a reversible fuel cell
Assuming an isobaric and isothermal reversible fuel cell, enclosed by a sys-
tem boundary, the air and fuel enter with the total enthalpy ΣHi and leave
the fuel cell with the total enthalpy of ΣHj . The heat generated Qrev in the
system is withdrawn reversibly to the surrounding and in the same manner
the work Wt,rev. The energy balance of the reversible fuel cell is outlined in
Fig. 1.3 [5, 6].
8 CHAPTER 1. INTRODUCTION
Figure 1.3: System boundary of a reversible fuel cell.
Application of the first law of thermodynamics, as formulated in equation
1.8, on the system in Figure 1.3 yields:
qrev − wt,rev + ΣFinHin − ΣFoutHout = 0 (1.9)
Equation 1.9 can be rearranged further:
Qrev − Wt,rev = ∆HRx (1.10)
The second law of thermodynamics applied on the system yields the entropy
change:∮
system
dS = 0 (1.11)
due to the reversibility.
The change of entropy, arising from the reaction, must be compensated by
1.3. PRINCIPLE OF FUEL CELLS 9
the reversible heat flow, in order to hold Equation. 1.11 true. This means:
∆SRx −Qrev
T= 0 (1.12)
Combining Equations 1.10 and 1.12, the reversible work Wt,rev, is given by:
Wt,rev = ∆HRx − T × ∆SRx (1.13)
The reversible work equals the change in Gibbs’ free energy of the reaction:
Wt,rev = ∆GRx (1.14)
Now the reversible efficiency of the fuel cell can be defined as the ratio of
the change in Gibbs’ energy to the change of enthalpy, both due to the
electrochemical reaction:
ηrev =∆GRx
∆HRx
(1.15)
Efficiency of a reversible heat engine
A steam power plant is a suitable model for determining the Carnot efficiency
for a heat engine. By definition, the initial and terminal states of a cyclic
process are identical. Then the first law of thermodynamics (Equation 1.8)
states that [5, 6]:
W − Q = ∆H = 0 (1.16)
Then the work implemented by the system is associated with the heat flow
entering the system:
W = Q (1.17)
By definition, a heat engine has at least two distinctive thermal reservoirs,
a heat source and a heat sink, within the cycle. The heat enters the system
from a heat source, and the heat leaves the system to a heat sink. According
to Equation 1.16 the net work implemented by the system is the difference
in heat transferred over the system boundary:
Wnet = Qin − Qout (1.18)
10 CHAPTER 1. INTRODUCTION
Entropy
Temperature
S 1 = S 4 S 2 = S 3
T L
T H
Q in
Q out
W net
1 2
3 4
Figure 1.4: T-S diagram - Carnot Cycle.
The thermal efficiency, ηth, can be established as the ratio of the transformed
work to the total energy transferred to the system:
ηth =Wnet
Qin
=Qin − Qout
Qin
(1.19)
In the reversible heat engine the heat transfer is performed isothermically,
then the second law can be rearranged to:
Qrev = T∆S (1.20)
giving,
Qin = TH × (S2 − S1) (1.21a)
Qout = TL × (S3 − S4) (1.21b)
Inspecting the Carnot cycle outlined in Figure 1.4, it is straightforward that
the corresponding entropies in Equation 1.21 are equivalent. The Carnot
efficiency can then be expressed by a substitution manoeuvre of Equation 1.19
1.3. PRINCIPLE OF FUEL CELLS 11
400 600 800 1000 1200 1400
20
30
40
50
60
70
80
Carnot Fuel cell
Effi
cien
cy [%
]
Temperature [K]
Figure 1.5: The theoretical efficiencies for a heat engine and a fuel cell (TL=298 K).
as:
ηth,Carnot = 1 −TL
TH
(1.22)
The graph in Figure 1.5 is made by evaluating the efficiencies of the reversible
fuel cell and the reversible heat engine by using Equations 1.15 and 1.22,
respectively. The graph shows the effect of temperature on the efficiencies
of both the fuel cell and the heat engine systems, respectively.
Efficiency of an irreversible fuel cell
In reality the work performed by a fuel cell is irreversible. Due to irreversible
losses, the operational cell potential, Ecell, is lower than the equilibrium po-
tential, E0, of the reaction. The overpotentials are a function of the current
12 CHAPTER 1. INTRODUCTION
density and originate from three dominant irreversibilities:
Activation overpotential
This kind of overpotential occurs because of a slow electrochemical reaction
at the electrode surface. An analogy for activation overpotentials for elec-
trochemical reactions is the activation energy for chemical reactions [7]. For
electrode reactions taking place at both at the cathode and the anode the
current density is given by the Butler-Volmer equation:
j = j0
[
exp
(
(1 − α) nFη
RT
)
− exp
(
−αnFη
RT
)]
(1.23)
where α is the charge transfer factor. The transfer factor is in a single-step
reaction defined as the fraction of the electrical energy or charge transfered
to the reactant.
At lower overpotentials (η ≪ RTF
) the current density, j, in Equation 1.23
follows a linear correlation of η [7, 8], resulting in:
j = j0
Fη
RT(1.24)
At higher overpotentials (| η |≫ RTF
) Equation 1.23 can be reformulated to:
ja = j0 exp
(
(1 − α) nFη
RT
)
η ≫RT
F(1.25a)
jc = j0 exp
(
−αnFη
RT
)
η ≪ −RT
F(1.25b)
depending on an anodic or cathodic overpotential, Equations 1.25a and
1.25b, respectively. If Equations 1.25 are combined in a logarithmic form,
introducing the constants a and b, the simple form of the Tafel equation is
obtained:
η = a + b log j (1.26)
Extrapolating the Tafel equation until η ⇒ 0 (i.e. to E0) yields the exchange
current density, j0.
1.3. PRINCIPLE OF FUEL CELLS 13
Ohmic overpotential
This overpotential arises due to the resistance of both the electron flow in
the electrodes and the ion flow in the electrolyte [9]. The ohmic loss can be
described as:
ηohm = IR (1.27)
Concentration overpotential
If the electrochemical reaction is faster than the supply flow of reactants,
a concentration gradient arises between the bulk and the electrode. This
causes a voltage drop. The gradient can arise from different phenomena
such as slow diffusion of the gaseous reactants in the electrode pores or slow
diffusion of reactants through the electrolyte to the reaction site.
These phenomena can be described by Fick’s first law:
j =nFD (CB − CS)
δ(1.28)
where D is the diffusion coefficient, CB and CS are the bulk concentration
and the surface concentration, respectively, and δ is the thickness of the
diffusion layer. By introducing the limiting current (jL), used as a measure
of the maximum rate of the reactant supply to the electrode, when CS = 0,
Equation 1.28 becomes:
jL =nFDCB
δ(1.29)
The Nernst equation at equilibrium is:
EOCV = E +RT
nFlnCB (1.30)
hence when the electrochemical reaction occurs and CS < CB then the
Nernst equation can be described as:
E = E +RT
nFlnCS (1.31)
The difference between the potentials in Equations 1.30 and 1.31 arises from
14 CHAPTER 1. INTRODUCTION
Figure 1.6: Schematic of types of polarization in a fuel cell.
the concentration potential:
∆E = ηm =RT
nFln
(
1 −j
jL
)
(1.32)
In Figure 1.6 the losses are schematically shown.
The open cell voltage can then be formulated as:
Ecell = E0 − |ηohm| − |ηa| − |ηc| − |ηm| (1.33)
Electrode models: Paper I and Paper II
The current distribution in the electrode can be determined by a local po-
tential balance.
Ecell = E0 − ηa − ηc − j · Rohm (1.34)
where j is the local current density and Rohm is the ohmic loss, respectively
(ηohm = j ·Rohm). In the case of MCFC the open circuit voltage is described
1.3. PRINCIPLE OF FUEL CELLS 15
by the Nernst equation
∆E0 = ∆E0 −RT
nFln
(
P 0.5O2
PCO2,cPH2
PH2OPCO2,a
)
(1.35)
where Pi is the partial pressure of each component in the gas. As described
earlier the current distribution is given by the Butler-Volmer equation (1.23),
however Fontes et al [10] noted that the experimental polarization curves for
the porous NiO cathode shows a linear shape over a wide potential range.
Lagergren and Simonsson [11] describe the relation between the overpotential
and current density as
dη
dj=
√
RT
nFSjκohm
(1.36)
where κohm is the pore electrolyte conductivity and S the surface area. The
exchange current densities for the cathode [11] and the anode [12] were
experimentally determined.
j,c = jP 0.79O2
P 0.19CO2
(1.37)
j,a = jP 0.60H2
P 0.64CO2
P 0.55H2O (1.38)
Equation 1.37 takes into account the current distribution along the depth
of the electrode. The relation between the current density and the overpo-
tential is linear and no mass transport limitations (see Eq. 1.32) in the gas
phase were included. Equation 1.37 is valid under the assumption that the
conductivity in the electrode phase is much higher than in the electrolyte
phase.
The temperature dependency for the standard current density is prescribed
by equation [13].
j00 = κ0
(
E (T − Tref )
T · Tref
)
(1.39)
The ohmic loss in the matrix is
Rohm =d
κohm ǫ1.5matrix
(1.40)
where the conductivity in the electrolyte is
κohm = κ0exp
(
−25.45 · 103
RT
)
(1.41)
16 CHAPTER 1. INTRODUCTION
according to Tanase et al [14]. The values used in the model are given in
Table 1.2.
In Paper II the expressions for the resistances were adopted from Morita et
al [15], and are described respectively as:
Rir = Air exp
(
∆Uir
RT
)
(1.42a)
Ra = Aa exp
(
∆Ua
RT
)
P (H2)−0.5 (1.42b)
Rc = Ac1 exp
(
∆Uc1
RT
)
P (O2)−0.75 P (CO2)
0.5 +
Ac2
AdM (H2O) + M (CO2)exp
(
∆Uc2
RT
) (1.42c)
The values used in the model are given in Table 1.3
Equilibrium calculations. Paper I and Paper II
In the models in Paper I and Paper II the VCS [16] algorithm was used
for determining the equilibrium gas composition in the anode compartment.
The VCS algorithm calculates the equilibrium composition by minimization
of Gibbs’ free energy by using a stoichiometric formulation. The equilibrium
reactions considered are the water gas shift (WGS) reaction and the steam
reforming reactions
CO + H2O CO2 + H2 [∆H0298K = −40 kJ mol−1] (1.43)
CH4 + H2O 3 H2 + CO [∆H0298K = 200 kJ mol−1] (1.44)
Table 1.2: Parameters and values used in the model in Paper I
Anode Cathode Matrix electrolyte Electrode
E[K] κ0 [A m−2] E[K] κ0 [A m−2] κ0 [S m−1] κ0 [S m−1]
7.8 · 103 760 1.9 · 104 72 34.2 55
1.3. PRINCIPLE OF FUEL CELLS 17
Table 1.3: Parameters and values used in the model in Paper II
Air (Ω cm−2) 1.40×10−2
∆Uir(kJ/mol) 23.0
Aa(Ω cm−2atm0.5) 2.04×10−3
∆Ua(kJ/mol) 23.7
Ac1(Ω cm−2atm0.25) 3.28×10−9
∆Uc1(kJ/mol) 132
Ac2(Ω cm−2) 3.39×10−6
∆Uc2(kJ/mol) 67.1
Ad(Ω cm−2) 2.00×10−1
In the literature there are several kinetic expressions for the steam reform-
ing reactions [17–20]. In general there is an agrement on first order kinetics
with respect to methane, however the activation energies span over a wide
range of values, which could be explained by heat transfer and pore diffusion
restrictions. The reaction order with respect to the other components varies.
Using an equilibrium calculation approach sets aside the dependency of the
kinetic expressions on a given catalyst and/or experimental setup. Another
advantage in using the VCS algorithm in the models is the simplicity of
modifying them to include higher hydrocarbons, i.e. ethane and propane,
normally present in considerable amounts in natural gas. In the equilib-
rium calculations the slow kinetics of the SRM reaction (Eq. 1.44) has been
compensated by a temperature approach method, that is also common for
industrial reformers. By this the incomplete equilibrium conversion is mea-
sured as the difference between the actual temperature and the temperature
that would have given the observed conversion as the equilibrium conver-
sion. A typical -20 K temperature approach value therefore means that the
equilibrium conversion, calculated for a reactor temperature 20 K less than
the actual value, equals the observed value.
18 CHAPTER 1. INTRODUCTION
1.4. Some characteristics of the different kinds of
fuel cells
Fuel cell is a generic name for a variety of subtypes of the technology. The
subtype name of a fuel cell is determined by its electrolyte. Fuel cells are
further subdivided in groups determined by their operating temperature,
for example high and low temperature fuel cells. In Table 1.1 the common
types of fuel cells are listed. However it should be noted that the operating
temperature of a fuel cell and its electrolyte are closely connected. This
could of course be confusing, for example in the case of the low temperature
solid oxide fuel cell, which is a subtype in the high temperature group.
AFC - Alkaline fuel cell
The AFC is often connected with the Apollo program. It was used as a
power supply during the space flights. The pioneer of the alkaline fuel cell
technology was Francis Bacon, who in the beginning of the 1950’s completed
a 5 kW hydrogen-oxygen fuel cell power plant [21]. One of the issues for the
propagation of AFC and also one of its major advantages is its possibility to
make use of non-noble metals in the electrodes [21,22].
The electrolyte, naming the AFC, consists of an alkaline solution, potassium
hydroxide. The anode electrode reactions is:
2 H2 + 4 OH− → 4 H2O + 4 e− (1.45)
In this reaction the OH− is consumed and electrons flow through the elec-
trical circuit to the cathode:
O2 + 2 H2O + 4 e− → 4 OH− (1.46)
where the OH− is produced.
However, using an alkaline electrolyte has a drawback, the need of removing
acid CO2 both from the oxidant and the fuel feed. A common method used
for the removal is scrubbing [23]. If the CO2 is not removed, an undesired
carbonate formation occurs :
1.4. SOME CHARACTERISTICS OF THE DIFFERENT KINDS OFFUEL CELLS 19
CO2 + 2 OH− → CO−
3+ H2O (1.47)
The carbonate lowers the conductivity of the electrolyte, and also gives rise
to diffusion limitations of the OH− ion and degenerates the electrode, af-
fecting the long term stability [24].
The counter measure is using a circulating electrolyte, which can be regener-
ated outside the stack, hence reducing the effect of the carbonate formation.
A mobile electrolyte gives rise to some additional advantages, compared with
a stationary electrolyte, for instance serving for heat management and prod-
uct water management.
PEMFC - Proton electrolyte membrane fuel cell
PEMFC is low temperature fuel cell type, and was developed in the 1960’s
by General Electric (USA) mainly for power generation in space vehicles.
The major impact of the application came with the discovery of Nafionr by
DuPont as an electrolyte [22,24].
The electrochemical reactions taking place in a PEMFC are, at the anode:
2 H2 → 4 H+ + 4 e− (1.48)
and at the cathode:
O2 + 4 H+ + 4 e− → 2 H2O (1.49)
There are two major concerns regarding the water management in PEMFC,
dehydration on one hand and flooding on the other. The polymer membrane
has the ability to be hydrated by water, which promotes the migration of
H+, i.e. the conductivity in the electrolyte. In principle, at the operational
temperature (see Table 1.1), the feed stream has to be humidified to keep
the electrolyte hydrated. In spite of water being produced at the cathode,
it is not enough to keep the appropriate water balance [22]. Flooding is the
20 CHAPTER 1. INTRODUCTION
opposite situation, and reduces the migration rate due to diffusion resistance
caused by the excess water concentration.
Fuel processing is an important issue in the case of PEMFC. This is due
to the major risk of CO poisoning of the noble catalyst on the anode. Even
a CO level of some parts per million, is considered to be a risk for catalyst
poisoning [25]. The poisoning leads to lower performance and a shorter life
time. Employing fuel pre-processing, the CO in the feed gas can be converted
to CO2 (and H2) via the water gas shift reaction. The fuel pre-processing
will be further discussed later in the thesis.
PAFC -Phosphoric acid fuel cell
The PAFC is considered to be the first fuel cell type to be commercialised
[24]. The electrolyte is concentrated phosphoric acid (H3PO4) and, as for the
PEMFC, the charge transfer ion is H+. The electrolyte is kept by capillary
forces inside the pore structure of a SiC matrix. The electrodes are made of
carbon black bonded by Teflonr, and use noble metals as catalysts for the
electrochemical reactions. The electrochemical reactions in the PAFC are at
the anode:
2 H2 → 4 H+ + 4 e− (1.50)
and at the cathode:
O2 + 4 H+ + 4 e− → 2 H2O (1.51)
The electrocatalysts are, as for the PEMCF, sensitive to CO poisoning, de-
manding pretreatment of the gas fed to the fuel cell anode electrode.
MCFC - Molten carbonate fuel cell
G.H.J Broers and J.A.A Ketelaar reported in 1960 about a fuel cell resem-
bling the molten carbonate fuel cell [26]. The electrolyte used was an alkali
metal carbonate entrained by a disc of magnesium oxide.
The electrochemical reactions for MCFC are at the anode:
1.4. SOME CHARACTERISTICS OF THE DIFFERENT KINDS OFFUEL CELLS 21
H2 + CO2−3
→ CO2 + H2O + 2e− (1.52)
and at the cathode:
1
2O2 + CO2 + 2e− → CO2−
3(1.53)
Hence the overall reaction becomes:
1
2O2 + H2 → H2O (1.54)
By using nickel as a catalyst in the anode compartment, internal reforming
could be utilized. The reforming reactions are as follows:
CO + H2O CO2 + H2 [∆H0298K = −40 kJ mol−1] (1.43)
CH4 + H2O 3 H2 + CO [∆H0298K = 200 kJ mol−1] (1.44)
The water gas shift reaction (WGS) in Equation 1.43 is slightly exothermic
and the steam reforming reaction (SR) in Equation 1.44 is considerably en-
dothermic. Carbon formation, coking, inside the fuel cell is undesired due
catalyst deactivation and gas channel blocking [27, 28], hence lowering the
efficiency. The reactions are as follows:
CH4 C(s) + 2 H2 [∆H0298K = 75 kJ mol−1] (1.55)
2 CO → C(s) + CO2 [∆H0298K = −170 kJ mol−1] (1.56)
The reaction in Equation 1.55 is a hydro cracking reaction and the reaction
in Equation 1.56 is commonly known as the Boudouard reaction [29]. How-
ever, these undesired reactions can be suppressed by attending the level of
steam in the anode fuel gas. It is common to operate steam reformers with
a steam to carbon ratio in the range of 2.5:1 to 4:1 [30].
The application of internal reforming give rise to some more advantages
such as less need of steam, because it is formed in the anode reactions, the
22 CHAPTER 1. INTRODUCTION
Burner Anode
Cathode
Fresh air
Anode off-gas
Cathode off-gas
Figure 1.7: Schematic of anode off-gas recycling and CO2 generation.
hydrogen content is evenly distributed yielding a more uniform temperature
distribution [28].
One property of the MCFC is the net transfer of CO2 from the cathode
to the anode compartment:
1
2O2 + CO2,c + H2 → CO2,a + H2Oa (1.57)
As shown in Equation 1.57 CO2 is a reactant at the cathode side, and hence
must be supplied [31]. However, CO2 is also produced at the anode side of
the fuel cell. A solution to this problem is to combust the anode off-gases
in a burner in order to generate heat and produce more CO2 by combust-
ing the remaining CO and CH4, if present. After the burner, the off-gas
is enriched in CO2, and can be mixed with fresh air, and then be recycled
back to the cathode feed. In this way less pre-heating is needed in order
to reach operational temperature of the feed-gas, which benefits the total
system efficiency. A schematic of the CO2 recycling flow and generation is
outlined in Figure 1.7.
SOFC - Solid oxide fuel cell
This type of fuel cell differs from the others described in thesis, in the sense
that the electrolyte is not a liquid, a solid polymer or a melt. The electrolyte
is a ceramic, a solid oxide, consisting of yttria-stabilized zirconium oxide. At
1.5. BALANCE OF PLANT (BOP) 23
high temperatures (>1120 K) the solid oxide has capability to conduct the
O2− ion. The electrochemical reactions in a SOFC is at the anode:
2 H2 + 2 O2− → 2 H2O + 4 e− (1.58)
and at the cathode:
O2 + 4 e− → 2 O2− (1.59)
The anode is made of zirconia cermet, a mixture of a ceramic and a metal.
The metal is nickel, adopted due to its high electronic conductivity and
durability in a reducing environment. Additionally, nickel is a well-known
catalyst used industrially for steam reforming reactions. Considering this to-
gether with the high operational temperature, no additional catalyst for the
steam reforming reactions is needed [28,32]. Hence a less fuel pre-processing
is needed, resulting in a less complex balance of plant (BoP). An additional
effect of replacing the pre-reforming by internal reforming in the fuel cell is
the promotion of waste heat removal by the endothermic reactions. How-
ever, a supplementary cooling could be needed, in spite of the endothermic
reactions, and a facile solution is increasing the feed rate of air to the cathode.
Considering the solid state of the SOFC electrolyte and the high operat-
ing temperature, caution is required concerning the choice of the materials
and integral parts due to thermal expansions. A mismatch could result in
a mechanical breakdown of electrodes and fuel cell stack structure. When
using natural gas as fuel, it is important to pre-reform it to some extent
prior its direct supply to the anode. This is done in order to avoid a rapid
negative temperature gradient, due to the strongly endothermic reaction, in
the beginning of the fuel cell feed entrance causing thermal stress to materi-
als [33].
1.5. Balance of Plant (BoP)
Figure 1.5 shows that the efficiency of a reversible hydrogen fuel cell is ac-
tually lower than for the heat engine at temperatures above 1000 K. This
implies that a high temperature fuel cell such as MCFC (900-1000 K) is not
efficient compared to either low temperature fuel cells such as PEMFC or
24 CHAPTER 1. INTRODUCTION
heat engines. However, other advantages are obtained using the MCFC. The
primary advantages are that:
higher temperature results in faster electrochemical reactions due to
lower activation overpotentials.
the heat available in the stack off-gases can be used to pre-process more
complex fuels, such as natural gas.
there is an opportunity of integrating combined heat and power (CHP)
in the system.
more electricity is generated through integration of turbines with the
system (bottoming cycles).
Larmine et al [22] point out how high temperature fuel cells should be re-
garded:
"these can never be considered simply as fuel cells, but they must
always be thought of as an integral part of a complete fuel
processing and heat generating system."
In a fuel cell power plant, the stack itself is only a small part of the total
system. In Figure 1.8 an example of a fuel cell system is outlined. The
auxiliary equipment, e.g. heat exchangers, compressors, pumps, blowers,
reformer, power conditioning etc. is the "balance-of-plant". The integration
of all parts is one of the main issues in studying the fuel cell power systems.
Discussion about ER-MCFC, IIR-MCFC and DIR-MCFC
There are three design types of the MCFC stack: external reforming (ER),
indirect internal reforming (IIR) and direct internal reforming (DIR). The
main distinction between them is the placement of the active reforming com-
partment, which is outlined in Figure 1.9. In the ER approach the reforming
part occurs adjacent outside the fuel cell stack. The two other types are
both in the category of internal reforming stacks, i.e. the reforming part is
situated inside the stack, however with different geometric configurations, as
shown in Figure 1.9(b) and 1.9(c).
1.5. BALANCE OF PLANT (BOP) 25
Figure 1.8: Schematic of a fuel cell power plant system [34].
In the IIR concept the reforming compartment is adjacent to the stack,
using the evolved heat from the electrochemical reactions for the reforming
reactions. However, even if the reforming reactions benefit from the close
thermal contact, the drawbacks are that the steam must be supplied sepa-
rately and only the heat from adjacent cells can be utilized.
In the other type of internal reforming, namely DIR, both the reforming
and electrochemical reactions occur in same compartment. Compared with
the IIR concept, the heat transfer is better, steam is produced in the electro-
chemical reactions, hence removing the need of supply of additional steam
as in the case of IIR. In addition the heat management is more facile due to
the exothermic reforming reaction.
26 CHAPTER 1. INTRODUCTION
The heat management (cooling demand) for MCFC is normally made with
an excess cathode flow, and/or cathode off-gas recycling, in order to suppress
the temperature rise within the fuel cell stack.
By the integration of the reforming part within the fuel cell some advan-
tages are gained, such as system cost reduction, a more evenly distributed
temperature profile in the stack, a higher methane conversion due to the
simultaneous consumption of hydrogen driving the methane conversion for-
ward (see Equation 1.44). Additionally the global efficiency is higher in the
IR cases, due to less need of cooling by excess cathode air, hence lowering the
parasitic power loss of air compressors etc, used for the recycling streams.
(a) ER-MCFC.
(b) IIR-MCFC. (c) DIR-MCFC.
Figure 1.9: Schematic representation of the placement of the reforming part.
1.6. FUELING FUEL CELLS 27
1.6. Fueling fuel cells
Hydrogen is without doubt the preferable fuel for fuel cell applications, due
to its high reactivity. Unfortunately it is not the most obtainable fuel, bear-
ing in mind infrastructure issues. Hydrogen has to be produced from a
primary fuel source by means of energy, before it can be used directly as a
fuel. The fuel cell system used, as well its location, governs the fuel and its
pre-processing requirements. A simple rule of thumb is that a fuel cell with
a higher operating temperature demands a lower hydrogen purity than the
one with a lower operating temperature. Hence, the complexity of the fuel
pre-processing decreases with a higher operating temperature [4, 5, 35]. The
typical operating temperatures for the different types of fuel cells are shown
in Table 1.1.
In the following sections, some possible routes for fuel processing are outlined.
Though if the outline is limited to high temperature fuel cell applications,
it is also valid for low temperature fuel cells. Fuels are described as pri-
mary or secondary fuel. Primary fuels are fossil fuels such as oil or natural
gas, and secondary fuels are for example methanol, gasoline and processed
biomass [36]. The fuel pre-processing aims at cleaning and converting the
fuel to hydrogen. This could either be made at a pre-processing plant or in
direct connection to the fuel cell application. The former implies a hydrogen
infrastructure or/and a hydrogen storage facility. In the case of stationary
fuel cell power plants the latter is a more advantageous option. The reason
is that the heat generation (off-gas waste heat) in the fuel cell system can
be incorporated in the fuel pre-processing scheme.
The fuels considered in this thesis are either natural gas or gasified biomass.
These fuels are more explained in the following sections.
Natural gas
Natural gas is a fossil fuel found close to crude oil reserves or in underground
gas reservoirs. It consists of a combustible mixture of low temperature-
boiling hydrocarbons. The major component is methane, but higher hydro-
carbon such as pentane and butane are also present. In Table 1.4 a typical
28 CHAPTER 1. INTRODUCTION
Table 1.4: Typical composition of natural gas [38]
Component Formula Mole-%
Methane CH4 >75-95
Ethane C2H6
Propane C3H8 0-20
Butane C4H10
Carbon dioxide CO2 0-8
Nitrogen N2 0-5
Hydrogen sulphide H2S 0-5
composition of natural gas is given. It should be noted that the composition
of natural gas can differ from one geographic area to another, but still the
major component is methane [22].
Natural gas has been used in Sweden since 1985. Natural gas is imported
via pipelines from Denmark to Klagshamn south of Malmö. The distribution
line is located along the coast from Trelleborg to Göteborg [37].
Purification of natural gas
Sulfur occurs in various forms in natural gas, such as hydrogen sulfide (H2S)
or mercaptans (R-SH) etc. The level of the sulfur must be restrained at a
certain maximum level in order to protect the nickel-based catalyst in the
MCFC anode electrode and the electrolyte in the cathodic compartment.
The level should be <10 ppm H2S in the anode compartment, and <1 ppm
SO2 in the cathode compartment (see Table 1.1) [9]. On one hand sulfur
adsorbs on the nickel catalyst, hence preventing the reforming reactions from
being fully performed in the anode compartment.
NiO + H2S Ni − S + H2O (1.60)
1.6. FUELING FUEL CELLS 29
In the prolongation the adsorption causes a larger deviation from the reform-
ing equilibrium, decreasing the conversion of methane into hydrogen [9, 18].
On the other hand H2S reacts with steam forming SO2:
H2S + 2 H2O SO2 + 3 H2 (1.61)
Commonly the anode off-gas is passed to the cathode compartment, in order
to supply CO2 (see Equation 1.57), where SO2 reacts with the electrolyte [9].
However, the adsorption of sulfur on nickel is reversible at lower temper-
atures, and the nickel catalyst can be regenerated by steaming or by passing
sulfur-free gas feed over it for some hours [18,39].
A common method for removing sulfur from a gas stream is the adsorp-
tion process [18,35]. The adsorbent used in the process is zinc oxide (ZnO).
The zinc oxide particles have a high porosity, yielding a large internal surface
for the adsorption process.
ZnO + H2S ZnS + H2O [∆H
298 = −75kJ/mol] (1.62)
The equilibrium constant, Kp, in Equation 1.62 is:
Kp =PH2O
PH2S
(1.63)
Due to the exothermic reaction the equilibrium constant, Kp, is decreased
at higher reaction temperatures. A higher water content in the natural gas
results in a lowered adsorption of the sulfur on the ZnO.
According to Rostrup-Nielsen [18] the sulfur content could be reduced to
a level lower than 10 ppb.
Biomass
The sun is the source of all life on earth. It is the origin of all renewable and
fossil energy sources we use on earth. Solar energy is stored as chemically
bound energy in fossil fuels and plants. The process of transforming the solar
energy into chemically bound energy is called photosynthesis. Through this
30 CHAPTER 1. INTRODUCTION
process carbon dioxide and water form organic molecules, such as cellulose,
hemicellulose and lignin [40]. Biomass is a generic term for organic matter
that originates from plants. Wood, straw and even algae are considered as
biomass. The main elements in biomass are carbon, oxygen, hydrogen and
nitrogen. The bound chemical energy can be utilized in different ways, which
depend on the purpose of the end-user. In the fuel cell application a gaseous
fuel is preferable.
Gasification of biomass
Gasification is a technology used to convert biomass into a more suitable
form for fuel cell application. It is a thermochemical process, where the solid
biomass reacts with a gaseous medium, such as steam, air or oxygen. In
this process the chemical bonds in the biomass are broken, basically form-
ing a hydrogen and carbon monoxide-rich gas, i.e. synthesis gas [35, 41–44]
of medium- or low-calorific value 5-6 MJ/Nm3 and 13-14 MJ/Nm3 if air or
oxygen is used, respectively [44]. The pathway for producing synthesis gas
from biomass is outlined in Figure 1.10.
In Sweden there have been studies on gasification of biomass since the oil
crises in the 70’s, due to the availability of inexpensive raw material, e.g.
wood and wood residues. Depending on the geographical area and species,
the biomass raw material composition can vary. In sugarcane-producing ar-
eas or countries such as Brazil, Zimbabwe and India, the waste from sugar
production could be used as biomass for producing synthesis gas [45].
The composition of the gasified biomass is highly dependent on the gasi-
fication technology (e.g. reactor type), operating conditions such as gasifica-
tion temperature and pressure [44], and oxidizing medium (e.g air, oxygen,
and/or steam). Additionally the type of biomass used gives rise to different
gas compositions.
Conditioning of gasified biomass
The product gas from the gasification unit contains beside the fuel gases
impurities such as particulates, tar and alkali [42,46]. The produced gasified
1.6. FUELING FUEL CELLS 31
Figure 1.10: Pathway for producing synthesis gas from biomass.
32 CHAPTER 1. INTRODUCTION
biomass needs to be cleaned before using it as a fuel for the fuel cell. The
particulates can be reduced by using hot gas filter technology [47], which
consists of filter candles in a filter casing. The temperature of the gas in
this stage is about 620-690 K. Tars can be removed by either using a cooling
unit or venturi scrubbers. Condensing has the disadvantage of needing large
cooling areas, hence not suitable for the treatment of high flows [46]. By
spraying water into the product gas the tars condense on the water droplets
and can be separated. In addition some of the particulates are also removed.
The alkali metal compounds are at high temperature present in the vapor
phase and condense on cold surfaces causing scaling. However these metal
compounds can also be removed by using water scrubbing.
Reformer technology in short
Steam reforming is a well-known technology, used industrially for producing
hydrogen [18, 19, 22, 28, 30]. In the case of high temperature fuel cells, e.g.
MCFC or SOFC, the purpose of the external reforming/pre-reforming is
mainly to remove the hydrocarbons higher than methane, C2-C4, in natural
gas. Otherwise there is an imminent risk of carbon deposition [22, 30, 48] in
the fuel cell according to the following reaction:
CxH2y → x C(s) + y H2 (1.64)
The general reforming reaction for generic hydrocarbons is:
CxHy + x H2O → x CO + (x + y/2) H2 [∆H0298K > 0 kJ mol−1] (1.65)
and the earlier shown reforming reaction of methane:
CH4 + H2O 3 H2 + CO [∆H0298K = 200 kJ mol−1] (1.44)
The higher hydrocarbons are readily reformed compared with methane, which
means that the pre-reformed natural gas mainly consists of methane, with
carbon oxides, water and hydrogen. The reforming process can be driven
even further to reduce the methane content. This is done because of the
strongly endothermic reaction methane undergoes when reformed. Feeding
1.6. FUELING FUEL CELLS 33
mainly methane as fuel to a fuel cell would cause a large temperature drop
in the inlet zone of the fuel cell. This will cause severe thermal stress on the
electrodes, resulting in a shortened life time of the fuel cell.
MCFC systems
The 2 MW Santa Clara demonstration project is a well-known MCFC sys-
tem [49], placed in Santa Clara, CA, USA. The fuel cell stack technology
was accomplished by Fuel Cell Energy (FCE), formerly Energy Research
Corporation (ERC), Danbury, CT, USA. The fuel cell power plant consists
of sixteen 250 kW stacks consisting of 40000 cells. The power plant delivered
2500 MWh for over 5290 h. Today FCE are producing internal reforming
MCFC stacks in the range of 250 - 2000 kW [50], also known as the Direct
Carbonate CellTM(DFC) [51, 52]. FCE is also developing fuel cell/gas tur-
bine hybrid systems (DFC/Tr), featuring electrical efficiency up to 75 % on
natural gas and 60 % on coal gas [53]. FCE have conducted a preliminary
design of a 40 MW power plant.
GenCell Corporation, Southbury, CT, USA is manufacturer of fuel cells and
integrated fuel cell power generators. They started their development work
in 1997, and they are aiming for the 40-100 kW Distributed Generation mar-
ket [54].
In Italy Ansaldo Fuel Cells (AFCo) is developing MCFC stacks for com-
mercializing for power plants in the range of 100 kW up to 500 kW [55, 56].
They plan to commercialize their product at the end of 2005.
MTU Friedrichshafen, a DaimlerCrysler subsidiary, in Germany are using
the technology based on a license from FCE and are developing their 250
kWe HotModule concept, which is illustrated in Figure 1.11. The system con-
sists of three separate components, a central steel container with the fuel cell
stack, upstream gas treatment and the electrical subsystems including sys-
tem control system. They have installed several demonstration power plants
in Germany, USA and Japan [57–59]. They have developed the world’s first
dual-fuel operation high temperature fuel cell, and have since September
2004 entered in service with the German utility Vattenfall in Berlin at the
34 CHAPTER 1. INTRODUCTION
Figure 1.11: MTU HotModule schematic. c©MTU CFC Solutions, 2003
"Fuel Cell Innovation Park" [60]. The fuel cell runs on natural gas, methanol
or both [61]. MTU has a target of series production in 2006.
In Japan the Ishikawajima-Harima heavy industries (IHI) was leading the
overall stack development and system design of 1000 a kW MCFC power
plant in Kawagoe [62, 63]. During 2005 IHI are planning to demonstrate
commercial MCFC power plants in the range of 3 to 7 MW [62].
1.7. REVIEW OF MODELING AND SYSTEM STUDIES MCFC 35
1.7. Review of modeling and system studies
MCFC
In the literature several MCFC models and systems studies are presented
[64-97]. Depending on the end-use and the purpose of the models, they are
more or less detailed from a mathematical point of view. Fuel cell models
can generally be divided into three groups: electrode, cell and stack models.
The review is focused on steady-state models in the literature at cell and
stack level and on system studies.
The models described are often of an empirical kind, i.e. the conductiv-
ity is based on experimental data and correlated to temperature, pressure
and gas composition. The models can be further divided into level of di-
mensions, referring to the geometric solution space of the problem. A zero-
dimension model is independent of the geometry, hence also independent
of the geometry-dependent parameters, such as temperature, pressure etc.
A three-dimensional model includes all three directions, i.e x, y and z-
directions, and every solution point in the geometry is dependent on pressure
and temperature etc. In between are one and two-dimensional models, which
consider the geometry in the flow directions of the anode and cathode com-
partments.
In stack and system studies the term efficiency occurs frequently, however,
having two meanings. In stack studies or stack modeling the term efficiency
refers to the electrical efficiency of the stack, and in system studies it refers
to the electrical efficiency of the whole system. Avoiding confusion in the
following text, the electrical efficiency of the system is called global electrical
efficiency, and in the other case simply electrical efficiency.
Cell models
Wilemski et al [64] are considered as the pioneers in cell modeling of MCFC.
The model is a nonisothermal empirical two-dimensional steady-state model.
Their model takes into account the gas stream utilization due to electrochem-
36 CHAPTER 1. INTRODUCTION
ical reactions, conductive heat transfer by the bulk streams and the in-plane
heat conduction through the hardware. They studied cross-, co- and coun-
terflow geometries. One of the main results of their calculations showed that
a larger cell area (>1 m2) gives rise to a temperature distribution field, dif-
fering about 200 K.
Bosio et al [65–67] have developed an empirical two-dimensional cell model.
In their simulations [65] they study a rectangular geometry with a crossflow
feeding. The oxidant is fed at the long-side of the fuel cell. They have also
developed an empirical three-dimensional stack model. The purpose of the
models is the need for studying scale-up phenomena in MCFC.
One of the articles of Bosio et al [66] studies the behavior of the fuel cell
when changing the geometry, i.e. using a square or a rectangular geometry.
In those studies they use an empirical three-dimensional stack model. They
concluded that a rectangular stack geometry has a better heat management
behavior, it is then possible to increase the oxidant flow rate without in-
creasing the pressure drop too much (< 3 kPa).
Standaert et al [68] have developed an analytical co-flow isothermal cell
model which was extended to a non-isothermal cell model [69]. The models
are independent of the fuel cell type, and this is a presentation showing that
simple expressions relating the cell current, cell voltage and fuel utilization
can be accurate in spite of their simplicity. In the analytical model the
Nernst equation is linearized. Results show that deviations between their
cell model and a numerically computed model is of the order of mV.
Chung et al [70] developed a two-dimensional cross-flow cell model. They
studied how the reformer affects the temperature distribution and perfor-
mance in an internal-reforming MCFC (IR-MCFC) cell unit. They con-
cluded that the temperature is more evenly distributed compared with an
externally reformed MCFC (ER-MCFC), additionally that the best cell per-
formance was achieved with a steam to methane ratio of 2:1.
1.7. REVIEW OF MODELING AND SYSTEM STUDIES MCFC 37
Stack models
In another article [67] Bosio et al present a further developed stack model.
They found an abrupt voltage drop at high current densities in an experi-
mental fuel cell, which was not foreseen in the former stack model [66]. This
was attributed to a mass transport limitation in the electrodes due to a gas
diffusion phenomenon, hence reaching the limiting current density. They ex-
perimentally studied the limiting performance at high reactant utilization, in
order to extend the stack model with the diffusional effects in the electrodes.
Yoshiba et al [71] developed an empirical three-dimensional stack model.
They studied the influence of different gas flow geometries on the stack per-
formance. The results showed that the best stack performance was achieved
when using a co-flow geometry.
In another study Yoshiba et al [72] wanted to use the model to study why an
unexpected voltage difference in some cells occurred in their 100 kW MCFC
stack. One of the results that explain this phenomenon of the voltage drop,
was an increased partial internal resistance and an insufficient supply of fuel
to particular cells.
In a third article Yoshiba et al [73] experimentally studied two 10 kW fuel
cell stacks. They wanted to predict the temperature distribution in the 10
kW stacks using a modified model of the stack described previously. They
found out that the predicted temperature distribution agreed with the mea-
sured.
Koh et al [74] developed a three-dimensional stack model, in order to study
the effect of scale-up on the maximum temperature rise and average cell
potential. They concluded that use of overall heat-transfer coefficient in
the model resulted in a limited accuracy of the temperature prediction.
They predicted the temperature profile from an experimental size to a near-
commercial one, and they concluded a significant effect of the scale-up on
the temperature and no effect of stack size on average cell voltage.
Koh et al [75] also developed a co-flow two-dimensional stack model. They
conducted a study on how the gas utilization and system pressure affect
38 CHAPTER 1. INTRODUCTION
the temperature distribution and stack performance in the stack at constant
load. They concluded that two temperature distributions occurred. The
first one is when a hot spot is created near the stack outlet, due to insuffi-
cient stack cooling. In the other case Koh et al stated that an isothermal
temperature distribution curve propagates from the cathode inlet along the
cathode gas flow, when sufficient stack cooling was achieved due to an in-
creased cathode flow. However, they said further that a higher operational
pressure of the system could counteract the higher pressure drop due to the
increased cathode flow. They finally concluded that a moderate operational
pressure (0.1-0.5 MPa), benefits the performance of the stack and counter-
acts the pressure drop effects.
In another study Koh et al [76] studied several issues regarding numerical
analysis of a co-flow stack model. The topics were grid number for channel
depth at constant velocity, thermal radiation and constant gas properties, in
order to investigate the numerical accuracy of temperature prediction and
computational time. They concluded that using a single computational grid
for the gas channel depth (vertical coordinate) does not cause significant er-
rors in the temperature calculation, however causing an underestimation of
the pressure drop. They concluded further that the prediction of the tem-
perature is not accurate without using momentum equations. This due to
constant velocities not accounting for mass flux changes, which influence the
convection heat transfer. Finally they concluded that constant gas property
parameters can be used for the cathode flow, normally used for heat man-
agement, because the gas contains a large amount of nitrogen and hence has
small variation of the gas composition in the flow direction. For the anode
flow they recommend using a gas capacity estimated as a function of gas
composition and temperature, in order to avoid overestimated heat convec-
tion.
Koh et al [77] further developed a three-dimensional stack model in order
to predict the temperature distribution at constant-load operation. They
identified some key issues regarding the temperature profiles in the fuel cell
stack. One was that the cell length has a larger impact on the temperature
rise than the number of cells. Another issue was that the cathode gas flow
rate is the most effective parameter for controlling the heat management in-
1.7. REVIEW OF MODELING AND SYSTEM STUDIES MCFC 39
side the fuel cell. It should be noted that they did not consider the internal
reforming.
System studies
De Simon et al [78] performed system studies of an MCFC power plant in
Aspen Plus TM. They implemented a cell model described earlier [65] as
a user model in order to study factors affecting the global efficiency of the
power plant. They studied how the steam to carbon ratio, the operating
pressure and the fresh air flow rate effect the global efficiency. The results
were that a higher steam to carbon ratio (5.5:1) increased the global electric
efficiency. By increasing the pressure from 3 bar to 5 bar the global electric
efficiency was increased 3 percentage units. However, the increase of the
fresh air flow rate slightly decreases the global electric efficiency.
Au et al [79, 80] developed a one-dimensional empirical cell model, used
for prediction of their bench cell. They also made a system study on how
the operating temperature influences the efficiency of a fuel cell system [81].
In the model used, they incorporated the empirical relations for the ohmic
resistances from Yosihba et al [71]. In their system study they found that
the operating temperature has only a minor influence on the global efficiency
and they concluded further that this gives freedom to optimize other perfor-
mance variables such as cost and endurance.
In another system study Au and coworkers [82] studied the influence on
the global efficiency of connecting MCFC stacks serially and varying the op-
erating temperature and gas composition. They used two multistage sets.
In one, both cathode and anode flows were serially connected. In the other,
the cathode flow was connected in parallel and the anode flow serially con-
nected. They found an improvement of 0.6 % for the first case and 0.8 % for
the second case versus a reference system.
In a further study, Au et al [83] made a case study of a 250 kW externally
reformed MCFC system, and varied the operating temperature between 873
K and 973 K. They found that an operating temperature between 923 K
and 973 K did not significantly influence the global efficiency. However at
40 CHAPTER 1. INTRODUCTION
948 K they found the maximum for the net electrical efficiency (51.9 %).
They concluded that these results are in accordance with an earlier system
study [81].
Kivisaari et al [84] used a zero-dimensional model in a benchmarking chem-
ical flowsheeting study. They evaluated whether three different flowsheeting
software give rise to any difference in the results, based on the same MCFC
system. They found that the differences could be derived from the thermo-
dynamic data in the steam-reforming part in the flowsheeting software.
In another system study Kivisaari et al [85] conducted a study on an IGCC-
MCFC system. They studied how gasification pressure, gasifier temperature
and internal reforming impacts on the global system efficiency. The results
show that a higher gasifier pressure and a higher temperature yield a higher
global electrical efficiency. The introduction of internal reforming was the
most important factor for increasing the global electrical efficiency.
A third system study was performed by Kivisaari et al [86] on a coal gasifier
combined with a SOFC or an MCFC stack, in order to predict the feasibility
of the combination. They found that SOFC is a better option than MCFC.
Other results show that the introduction of both anode and cathode off-gas
recycling somewhat decreases the global electrical efficiency in the MCFC
system.
In another system study Koh et al [87] performed a system study of a 100 kW
system using a model based on experimental data from a 25 kW stack. They
simulated four cases, (A) Heat exchanger network for thermal integration;
(B) Recycling of anode off-gas, or use as a fuel in an external steam reformer
unit; (C) cathode off-gas recycling and (D) using a turbo charger. The sim-
ulations revealed that the highest contribution to the global efficiency was
the introduction of the turbo charger into the system.
Lobachyov et al [88] simulated an advanced integrated biomass gasification
and MCFC system. They used a stoichiometric zero-dimensional MCFC
model with a fixed electrical efficiency. They emphasize the concept of the
integration of the technologies. The authors strongly recommend the con-
1.7. REVIEW OF MODELING AND SYSTEM STUDIES MCFC 41
cept, yielding an global electrical efficiency of around 53 %.
Morita et al [89] developed an empirical two-dimensional cell model using
data from a benchmark MCFC cell. They later conducted a study on the
performance of an integrated biomass gasification\MCFC system [15], and
compared the results with a biomass gasification\gas turbine system in order
to understand the behavior of the former system. They concluded that an
MCFC unit has no advantages at operating pressures over 0.8 MPa due to
carbon deposition and a lower system efficiency. Additionally the methane
should be totally reformed before the stack, in order to increase the system
efficiency, and have a higher efficiency than the gas turbine.
In an article by Yoshiba et al [90] a study was performed on how the partial
load of an MCFC\GT system influences the efficiency. They used the model
developed by Morita et al described earlier [89]. They simulated four cases.
In cases (A) and (B) a constant pressure air compressor was included with a
power load in the range of 50-100 %. In cases (C) and (D) a pressure swing
air compressor was included with a power load of 20-100 %. In cases (B)-(D)
a gas cooling of the cathode off-gas recycle was introduced. The results show
that in cases (C) and (D) at a power load of 20-30 % the global electrical
efficiency remains >35 %, the maximum being 53 % at middle load opera-
tion; in case (D) at full load the global electrical efficiency is 50 %. They
concluded that the introduction of a pressure swing air compressor with a
cathode off-gas gas cooler results in a wider operation range (20-100 %) yet
having a high thermal efficiency.
Yoshiba et al [91] also made a system study on an integrated coal gasifi-
cation/ molten carbonate fuel cell (IG-MCFC) combined system. The study
considered a gas composition of non-carbon deposition conditions, i.e. a
lower limit of H2 concentration of 1 mol% at the anode outlet and an up-
per limit of CO2 partial pressure of 0.1 MPa at the cathode inlet, required
for stabilized electricity generation. The operating pressure of the MCFC is
1.2 MPa. They studied the anode gas recycling system and the anode heat
exchange system supposing a non-equilibrium state of the WGS reaction in
the anode compartment. Yoshiba et al concluded that carbon deposition at
the anode inlet can be avoided if approximately 80 % of the anode outlet gas
42 CHAPTER 1. INTRODUCTION
is recycled in the gas recycling system and 60 % humidity in the fuel gas in
the anode heat exchanger is maintained.
Sugiura et al [92] used a stoichiometric model to simulate a co-generation
system for residential use. They studied the power requirement in a residen-
tial house, based on room layout, members in family etc. In the study they
used either city gas or propane as fuel in order to optimize the operational
costs. They found that the optimal scale of the co-generation system when
using city gas is 3 kW, being appropriate for the power need in a house.
When using propane as fuel the optimal system size is 6 kW. This is suitable
for apartment houses.
Fermeglia et al [93] used a previously developed cell model [78] in a sys-
tem study. They studied how steam to carbon ratio, the pressure and the
air feed ratio influence the global electrical efficiency by using sensitivity
analysis. They concluded that the reforming and the shift equilibrium are
improved as well as the global electrical efficiency with an increased the
steam to carbon ratio. Fermeglia et al asserted that the increase of the
global electrical efficiency was due to an increased fuel conversion inside the
fuel cell stack, yielding more of available hydrogen. They concluded further
that the increased amount of steam removed more heat out from the stack
into the bottoming cycle part of the system and increased its efficiency. Fer-
meglia et al concluded that a higher pressure increased the global electrical
efficiency, even if a higher pressure caused a deterioration of the methane
conversion. They showed that an increased air feed rate reduced the global
electrical efficiency.
Desideri et al [94] made a thermodynamical analysis on the integration of
hybrid cycles with MCFC systems (GT/MCFC plant). They studied two
plant layouts, for determining the main working parameters, and different
working fluids (air, argon and CO2) in the closed loop GT. They found that
using air and argon in the closed loop GT, the global electrical efficiency was
67 %. However, commenting that allmost all GTs are designed for air.
In another system study Ubertini together with Lunghi [95] studied the ther-
modynamical potential of combining a Steam Injected Gas Turbine (STIG)
1.7. REVIEW OF MODELING AND SYSTEM STUDIES MCFC 43
with an MCFC. They also studied the introduction of a combustion cham-
ber before the gas turbine, and compared the performance of simple and
fired bottoming cycles. They found out the fired bottoming cycle cycle has
a higher GT power output compared to the non-fired one, however yielding
a lower global electric efficiency of the system, 66 % to 69 %, respectively.
Lunghi et al [96] studied the performance of a hybrid MCFC gas turbine
system, by varying the fuel cell section size and the fuel utilization. They
used a one-dimensional MCFC stack model [97] and found that at a fuel
utilization of 70 % the global electric efficiency was 58 %.
Chapter 2
Methodology (Paper I and
Paper II)
All the systems studies within this work were performed with the Aspen
PlusTM, from Aspen Technology Inc. Aspen PlusTM is a chemical process
simulation software with pre-defined unit models and a built-in thermody-
namic library. The unit model is a separate mathematical model describing
the behavior of the unit as a component in a chemical process system. This
software has a graphical user interface (GUI), and a built-in expertise guid-
ance system providing support for the user in order to define the system. It
has an abundant model library for process unit models, e.g. reactors, mixers
and heaters [98,99].
However if the needed unit process model is not available, or an in-house
model is preferred, it is possible to implement these unit models as user
models [100]. The user models could be created in either Excel or Fortran77.
In this way Aspen PlusTM is powerful and versatile. Hence it is possible to
integrate in-house models with the extensive thermodynamic and unit model
library in Aspen PlusTM. This is the strength of Aspen Plus. However, As-
pen PlusTM simulates only steady-state processes.
45
46 CHAPTER 2. METHODOLOGY (PAPER I AND PAPER II)
In this work a fuel cell (MCFC) model was implemented as a user model,
fully able to interact with Aspen PlusTM. The programming language used
was Fortran77 from Compaq Visual Fortran 6.1 [101]. Aspen PlusTM uses
a sequential modular solving approach, which means it solves the process
scheme module by module. The complexity of the solving procedure grows
rapidly with the size of the process scheme. A normal-sized process scheme
could give rise to thousands of non-linear equations of both algebraic and
differential type, which have to be solved simultaneously. The solving proce-
dure of this kind of systems is even more complicated due to the complexity
of the process scheme, especially as recycle streams are commonly present.
This implies that the sequential modular approach is limited in those cases.
However using so-called tear streams, in which the recycle streams are teared
and give rise two streams, re-renders the use of the sequential modular ap-
proach. The Aspen PlusTM calculation engine employs as a default the
Wegstein method, which is a method of successive substitution which accel-
erates convergence [102, 103]. However there are other solving procedures,
which use for example the Broyden method, which is a variant of the secant
method [104,105].
Chapter 3
Summary of Paper I
Power generation is today mainly based on fossil fuel combustion. An al-
ternative energy source especially in focus in Sweden is the gasification of
biomass, due to the accessibility of inexpensive raw material. Finding out
the possibilities and the performance of a molten carbonate fuel cell (MCFC)
based power generation plant requires a balance of plant analysis (BoP) per-
formed for instance with the help of Aspen PlusTM. Aspen PlusTM does
not however include any MCFC internal block in its model library, so the
MCFC model has to be developed in-house and then implemented into As-
pen PlusTM. In earlier similar studies a so-called zero-dimensional model of
the fuel cell has been used [85], i.e. the model does not interact with the
system as a whole. In this project a one-dimensional model of a co-current
MCFC in MATLAB is translated into FORTRAN 77 so that the model can
be implemented into Aspen Plus as a user model.
The model is developed for different fuels, not the least gasified biomass
fed to the MCFC, and it takes into account the gas stream utilization due
to the electrochemical reaction, and the heat evolved due to the reactions.
The model predicts the local current density (at a given cell voltage) de-
pendence on temperature and gas composition, and the outgoing gas com-
position. It also takes into account the shift and the reforming reactions
occurring at the anode electrode compartment.
47
48 CHAPTER 3. SUMMARY OF PAPER I
The aim of the present work is to compare results obtained with both our
models, the zero-dimensional and the one-dimensional, on a normal MCFC
power plant, in which we use natural gas as fuel.
3.1. Fuel cell model
Assumptions of the model
The following assumptions have been made in the one-dimensional model:
Co-flow is considered
Local gas temperatures for the anode, cathode and as well the hardware
are equal
No end effects, and the performance of all individual cells is identical
Steady-state
Ideal plug flow in the gas channels
The shift and reforming reactions are assumed to be in equilibrium at
all time when adopting a temperature approach for methane reforming
The equilibrium composition of the reactions in Equations (1.43) and (1.44)
are computed by using the Villars-Cruise-Smith (VCS) algorithm [16]. The
method of calculating the equilibrium composition of a chemical system is
based on a minimization of Gibbs’ free energy using a stoichiometric formu-
lation of the reaction set.
Zero-dimensional model vs One-dimensional model
The main characteristic differences between the zero-dimensional and the
one-dimensional model are summarized in Table 3.1. As shown in Table 3.1
the benefits of the one-dimensional model over the zero-dimensional one, is
the dependency of systems parameters such as pressure, temperature and gas
3.2. RESULTS 49
compositions. Additional features of the one-dimensional model are the pos-
sibility of switching between external and internal reforming modes, which
is lacking in the zero-dimensional model.
3.2. Results
Temperature control and heat management in the fuel cell stack is vital for
its performance. The temperature influences the reaction rates, both electro-
chemical and reforming reactions, conductivities and open cell voltage. The
temperature profile is of particular importance considering stack electrode
lifetime, i.e. avoiding material thermal stress.
The net power production is larger in the internal reforming cases com-
pared to the external reforming cases. This is mainly due to the to larger
power consumption of the cathode recycle blower in order not to overheat the
stack. However, the power demand of the cathode recycle blower decreases
with increasing system pressure, due to the favorable compression ratio.
The results shows a good agreement between the zero-dimensional model and
the one-dimensional model (Figure 3.1). However, using the one-dimensional
model gives the advantage of additional information, such as gas compo-
sitions, temperature profiles and determining stack areas by using design
specifications in Aspen Plus TM.
3.3. Conclusion
The results showed that the one-dimensional (Figure 3.1), yields of the im-
portant benefits of producing more information such as temperature as well
as gas composition profiles and cell stack area, which is not the case with the
zero-dimensional model. The one-dimensional model also has an advantage
in the simplicity of switching between internal reforming mode and external
reforming mode.
Further it is possible to study systems using gasified biomass and coal powder
as primary fuels, since the one-dimensional model is based on first principles.
50 CHAPTER 3. SUMMARY OF PAPER I
Table 3.1: Input and output parameters for the models
One-D Model Zero-D Model
INPUT
Pressure ×
External reforming × (×)
Internal reforming × ×
Gas composition × (×)
Fuel utilisation ×
Cell voltage × ×
Stack dimensions ×
Electrode kinetics ×
OUTPUT
Gas composition × ×
-profile ×
Temperature × ×
-profile ×
Local current density ×
-profile ×
Fuel utilization ×
-profile ×
Pel × ×
3.3. CONCLUSION 51
4 5 6 7 8
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
Ele
ctric
effi
cien
cy (%
)
System pressure (bar)
IR one-dim IR zero-dim ER one-dim ER zero-dim
Figure 3.1: The electric efficiency versus the system pressure for the internal
and the external reforming cases.
Chapter 4
Summary of Paper II
Fuel cell technology is promising in converting a fuel to electricity directly
without raising any pollutants such as SOx and NOx as in the case of genera-
tion of electricity via a combustion route. Further fuel cells are not limited by
the Carnot efficiency, which implies a higher theoretical electrical efficiency
than normally possible from thermal production of electrical power.
The high operational temperature of molten carbonate fuel cell systems
(650 C) benefits the introduction of CHP and bottoming cycles [22] yield-
ing a higher electrical efficiency compared with low temperature fuel cell
systems such as PAFC. A higher operating temperature broadens the range
of available fuels, when reforming reactions can occur directly within the
MCFC stack or in connection with utilizing the fuel cell stack off-gas heat.
In this paper the objective was to study the influence of process parame-
ters on the system efficiency of a 500 kW(LHV) MCFC power plant. The
cell operational voltage, fuel utilization and type of fuel were the parameters
studied. The fuels studied were natural gas and gasified biomass.
The MCFC power plant produces both electrical power and waste-heat uti-
lized for district-heat production.
53
54 CHAPTER 4. SUMMARY OF PAPER II
4.1. Fuel cell model
The core of the developed in-house one-dimensional stack model is presented
in Paper I, however in Paper II, the expressions of the resistances were
adopted from Morita et al [15] (Equation 1.42).
4.2. The system studied
The schematic layouts of both the natural gas and the gasified biomass fueled
systems are shown in Figure (4.1). The main difference between the systems
is the absence of the pre-reforming unit in the gasified biomass case, due to
low content of methane in the fuel.
4.3. Results and conclusions
Comparing the results from the simulations of the MCFC systems, shows
that the gasified biomass system has a larger power demand through the
cathode recycle blower and the fuel compressor. In order not to overheat
the fuel cell stack some cathode off-gas is recycled back to cathode inlet. In
the natural gas system the heat management is performed with the help of
the endothermic steam reforming reaction of the large amount of methane
in natural gas.
The low methane content in gasified biomass compared to natural gas, im-
plies a larger demand for cathode recycling. The fuel mass flow in the gasified
biomass system is about ten times larger than in the natural gas system due
to the large amount of nitrogen, hence yielding a larger power demand by
the fuel compressor in the gasified biomass case.
This also explains the larger generation of district heat in the gasified bio-
mass cases, when the heat generated in the fuel cell stack is removed by the
off-gases rather than used by the reforming reactions.
The net power density in all cases is largest for the natural gas cases at
an operational cell voltage of 750 mV (Figure 4.2). The net power produced
4.3. RESULTS AND CONCLUSIONS 55
(a) Natural gas fueled MCFC system.
(b) Gasified biomass fueled MCFC system.
Figure 4.1: Schematic layout of fuel cell systems.
56 CHAPTER 4. SUMMARY OF PAPER II
in the natural gas cases at 800 mV reaches a maximum at a fuel utilization
of 80-85 % and then decreases. The anode off-gas is recycled to a burner,
where the remaining fuel is combusted with air, and then mixed with fresh
air, in order to preheat it before being fed to the cathode inlet. At higher fuel
utilization, the remaining fuel in the anode off-gas is insufficient to generate
enough heat in order to pre-heat the fresh air up to 853 K.
Another co-effect of the higher fuel utilization is that the cathode off-gases
have a lower temperature, due to a larger degree of methane reforming. This
effect in combination with less available fuel for the fresh air-preheating sys-
tem, causes a demand for some auxiliary preheating power for the fresh air
pre-heating. In these simulations this is compensated with a lower net power
produced.
However, due to the lower conversion rate, the heat evolved due to the
electrochemical reactions is lowered, hence lowering the need of the cool-
ing demand in the fuel cell stack.
4.3. RESULTS AND CONCLUSIONS 57
70 75 80 85 900.7
0.8
0.9
1.0
1.1
1.2
Rel
ativ
e po
wer
den
sity
(net
)
Fuel utilization, uf [%]
BM750 mV BM800 mV NG750 mV NG800 mV
Figure 4.2: Relative power density (net) vs fuel utilization.
Chapter 5
Overall conclusions
The work presented in this thesis shows that flowsheeting software, such as
Aspen PlusTM , is an imperative instrument in the art of studying fuel cell
systems, due to their rather high complexity regarding the process scheme.
In addition it is possible to implement in-house models with Aspen PlusTM ,
hence improving the overall fuel cell system evaluations.
However, availability of real plant data is desirable in order to improve the
stack model, hence also the systems evaluations with a flowsheeting software.
MCFC system studies is a useful tool for fuel cell developers regarding the
balance of plant.
59
Chapter 6
Acknowledgements
First of all, I would like to express my sincere gratitude to my supervisor Professor
Pehr Björnbom, for accepting me as a member of the fuel cells and system analysis
group and for guidance and constant support during the project.
Christopher Sylwan for accepting me in the project.
I would like to thank all my colleagues at the Department of Chemical Engineering
and Technology. Also I wish to thank everyone involved with this project.
Especially I would like to thank Dr Yohannes Kiros and Massoud Pirjamali, for
valuable discussions throughout the years. Monica Söderlund, Britt-Mari Rydberg
and Rolf Beckman for keeping the cog-wheels working.
Christina Hörnell for the linguistics.
Michel Bellais for all the fun during these years. Genki da ne !
I would like to thank my family and friends for their support.
The Swedish National Energy Administration (STEM) and the Division of Chem-
ical Reaction Engineering are acknowledged for financial support.
61
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