System studies of MCFC power plants - kth.diva-portal.orgkth.diva-portal.org/smash/get/diva2:11142/FULLTEXT01.pdf · System studies of MCFC power plants BENNY FILLMAN ... "user model"i

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


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)


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)


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].


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


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)


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


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


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.


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


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


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)


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


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.


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


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


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


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.


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


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)


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


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


Figure 1.10: Pathway for producing synthesis gas from biomass.


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


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


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-


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.


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


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-


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


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-


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


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)


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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