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TECHNOECONOMIC ANALYSIS OF THE CO-PRODUCTION OF HYDROGEN
AND POWER IN THERMOCHEMICAL-BASED BIOREFINERIES
By
Luke Hanzon
ii
A thesis submitted to the Faculty and the Board of Trustees of the Colorado
School of Mines in partial fulfillment of the requirements for the degree of Master of
Science (Engineering).
Golden, Colorado
Date ________________ Signed ___________________________________ Luke G Hanzon
Signed ___________________________________ Dr. Robert Braun
Thesis Advisor
Golden, Colorado
Date ________________ Signed ___________________________________ Dr. Kevin Moore
Interim Department Head Department of Engineering
iii
ABSTRACT
Increased global demand for energy and rising energy prices are driving
demand for domestic alternatives to fossil fuel-based energy products. This thesis
explores one alternative fuel production pathway using non-food crop biomass.
Two biorefinery concepts for the co-production of hydrogen and power via
gasification of lingo-cellulosic feedstocks are developed. Both concepts focus on a
2000 tonne/day plant size and a directly heated, pressurized oxygen- and steam-
blown fluidized-bed gasifier. The baseline-case utilizes mature gas cleaning
technology, while the advanced-case employs developing technologies for tar
removal/reforming and sulfur scrubbing.
Process efficiencies and economic performance for both cases are reported. The
baseline-case is estimated to have a process performance efficiency of 58.6% (LHV),
a plant overnight cost of $333 million, and a cost of hydrogen of $2.16/kg. The
advanced-case process efficiency improved to 61.7% (LHV) at a capital cost increase
of 4% to $347 million. The cost of hydrogen from the advanced-case dropped to
$2.14/kg due to increased production of electricity. Furthermore, a 2nd Law
(exergy) analysis of each biorefinery concept is performed and process
inefficiencies are located and quantified. Exergy analysis reveals the largest
inefficiencies are associated with the (i) gasification, (ii) steam and power
production, and (iii) gas cleanup and purification processes.
The cost of hydrogen from the biorefinery concepts developed here is still above
the US Department of Energy target of $1.50/kg (2005$), but several areas where
process modifications could improve system performance and substantially lower
the cost of hydrogen have been identified. These include increasing partial pressure
of hydrogen in synthesis gas prior to the hydrogen purification processes and
reducing capital costs by process intensification in the area of hydrogen synthesis
and purification.
iv
TABLE OF CONTENTS
ABSTRACT .......................................................................................................................................... iii
TABLE OF CONTENTS .................................................................................................................... iv
LIST OF FIGURES ............................................................................................................................ vii
LIST OF TABLES ............................................................................................................................... ix
ACKNOWLEDGEMENTS ................................................................................................................ xi
CHAPTER 1 INTRODUCTION ....................................................................................................... 1
1.1 Biomass Feedstocks and Fuel Pathways .................................................................... 3
1.1.1 Biomass Resource Availability ............................................................................ 4
1.1.2 Biomass-to-Fuel Pathways .................................................................................... 7
1.2 Themochemical Conversion ............................................................................................ 8
1.3 Research Objectives ............................................................................................................ 9
1.4 Previous Work ................................................................................................................... 10
1.5 Methodology ....................................................................................................................... 11
CHAPTER 2 THERMOCHEMICAL-BASED BIOREFINERY OVERVIEW ..................... 13
2.1 Biomass Feedstock Selection and Preparation .................................................... 13
2.1.1 Biomass Plant Sizing ............................................................................................. 14
2.1.2 Feedstock Preparation ......................................................................................... 15
2.2 Gasification .......................................................................................................................... 17
2.2.1 Technical Challenges for Biomass Gasification .......................................... 18
2.2.2 Gasifier Oxygen Supply ........................................................................................ 24
2.3 Gas Cleanup Survey .......................................................................................................... 24
2.3.1 Tar Cleanup............................................................................................................... 26
2.3.2 Physical Removal Methods – Wet Scrubbing .............................................. 30
2.3.3 Sulfur Cleanup ......................................................................................................... 32
2.4 Hydrogen Synthesis & Purification ........................................................................... 39
2.4.1 Water Gas Shift ........................................................................................................ 39
2.4.2 Pressure Swing Adsorption ............................................................................... 41
v
2.4.3 Water Gas Shift Membrane Reactors ............................................................. 42
2.5 Hydrogen Compression and Storage ........................................................................ 43
CHAPTER 3 BIOREFINERIES CONCEPTS FOR HYDROGEN PRODUCTION ............ 44
3.1 Gasifier Design Selection and Modeling .................................................................. 44
3.1.1 Design Selection ...................................................................................................... 44
3.1.2 Gasifier Modeling ................................................................................................... 45
3.2 Biorefinery Plant Models ............................................................................................... 54
3.2.1 Baseline-case Biorefinery Concept Overview ............................................ 54
3.2.2 Advanced-case Biorefinery Concept Overview.......................................... 70
3.3 System Model Benchmarking ...................................................................................... 74
3.4 Technology Readiness Level ........................................................................................ 79
CHAPTER 4 THERMODYNAMIC ANALYSIS......................................................................... 82
4.1 Second Law Analysis Overview .................................................................................. 83
4.1.1 Physical Exergy ....................................................................................................... 83
4.1.2 Chemical Exergy ..................................................................................................... 84
4.1.3 Exergetic Efficiency ............................................................................................... 85
4.2 Baseline-Case Exergy Analysis .................................................................................... 85
4.2.1 Gasifier ........................................................................................................................ 86
4.2.2 Tar Cleanup............................................................................................................... 88
4.2.3 Hydrogen Sulfide Cleanup .................................................................................. 88
4.2.4 Water Gas Shift ........................................................................................................ 89
4.2.5 Hydrogen Purification .......................................................................................... 89
4.2.6 Steam-Power Production .................................................................................... 90
4.2.7 O2 Production and Supply ................................................................................... 91
4.3 Future-Case Exergy Analysis ....................................................................................... 92
4.3.1 Tar Cleanup............................................................................................................... 93
4.3.2 Hydrogen Sulfide Cleanup .................................................................................. 94
4.3.3 Water Gas Shift ........................................................................................................ 94
4.3.4 Hydrogen Purification .......................................................................................... 94
vi
4.3.5 Steam-Power Production .................................................................................... 95
CHAPTER 5 ECONOMIC ANALYSIS ......................................................................................... 96
5.1 Capital Cost Estimation .................................................................................................. 96
5.2 Cost of Hydrogen ............................................................................................................... 99
CHAPTER 6 CONCLUSIONS ...................................................................................................... 104
CHAPTER 7 FUTURE WORK RECOMMENDATIONS ...................................................... 107
REFERENCES CITED ................................................................................................................... 109
APPENDIX A BIOREFINERY CAPITAL COSTS................................................................... 116
vii
LIST OF FIGURES
Figure 1.1 Biomass Resource Availability [10].................................................................... 5
Figure 1.2 Woody Biomass Availability [10] ........................................................................ 6
Figure 1.3 Agricultural Residue Availability [10] ............................................................... 6
Figure 1.4 Production Pathways from Biomass / Fossil Resources to Fuels .......... 7
Figure 1.5 Gasification Pathway ................................................................................................. 9
Figure 2.1 2000 TPD Biomass Availability Within 50 Mile Radius .......................... 14
Figure 2.2 Fluidized-Bed Gasifier ........................................................................................... 21
Figure 2.3 Gas Cleaning Portion of Biorefinery ................................................................ 25
Figure 2.4 Catalytic Candle Filter ........................................................................................... 28
Figure 2.5 Wet Scrubbing Spray Tower ............................................................................... 31
Figure 2.6 Selexol Process Diagram ...................................................................................... 33
Figure 2.7 Rectisol Process Diagram .................................................................................... 35
Figure 2.8 LO-CAT® Process Diagram .................................................................................. 36
Figure 2.9 WGDS Process Diagram ........................................................................................ 38
Figure 2.10 Water Gas Shift Equilibrium Extent of Reaction...................................... 40
Figure 3.1 Gasifier Schematic .................................................................................................. 46
Figure 3.2 Gasifier ASPEN Plus® Diagram .......................................................................... 47
Figure 3.3 Baseline Case Process Overview ....................................................................... 54
Figure 3.4 Detailed Baseline Case Process Flowsheet ................................................... 55
Figure 3.5 Two-Stage Tar Reforming Reactors in ASPEN Plus® ............................... 57
Figure 3.6 Wet Scrubbing Process in ASPEN Plus® ........................................................ 59
Figure 3.7 LO-CAT ® Process in ASPEN Plus® ................................................................... 61
Figure 3.8 Zinc Oxide Sulfur Polishing Bed in ASPEN Plus® ....................................... 62
Figure 3.9 WGS Reactor Train in ASPEN Plus® ................................................................ 63
Figure 3.10 PSA Process in ASPEN Plus® ............................................................................ 64
Figure 3.11 Baseline Case Pinch Composite Curve ......................................................... 66
Figure 3.12 Advanced Case Pinch Composite Curve ...................................................... 66
Figure 3.13 Circulating Water System Schematic ........................................................... 69
Figure 3.14 Counter-Flow Cooling Tower in ASPEN Plus® ......................................... 69
Figure 3.15 Advanced Case Process Overview ................................................................. 70
Figure 3.16 Detailed Advanced –Case Process Flow sheet .......................................... 71
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Figure 3.17 WGDS Process in ASPEN Plus® ....................................................................... 73
Figure 3.18 Plant Efficiency Comparison ............................................................................ 74
Figure 3.19 Technology Readiness Rubric ......................................................................... 80
Figure 4.1 Baseline-Case Thermal Profile .......................................................................... 82
Figure 4.2 Advanced-Case Thermal Profile ........................................................................ 82
Figure 4.3. Baseline-Case Exergy/Energy Flow Diagram .............................................. 86
Figure 4.4. Gasifier Exergy/Energy Flow Detail ................................................................ 87
Figure 4.5. Exergy/Energy Flow Diagram of PSA Process ............................................ 89
Figure 4.6. Exergy/Energy Flow Diagram for Steam-Power Generation ............... 90
Figure 4.7. Exergy/Energy Flow Diagram for ASU ........................................................... 91
Figure 4.8. Advanced-Case Exergy/Energy Flow Diagram ........................................... 93
Figure 4.9. Exergy/Energy Flows for Advanced-Case Steam-Power Generation 95
Figure 5.1 Capital Cost Breakdown of Hydrogen Biorefineries (a) Baseline Case
(b) Advanced Case (c) PEI Nth Generation. ............................................ 98
Figure 5.2 H2A Cost of Hydrogen ........................................................................................ 101
Figure 5.3 Process Intensification with WGSMRs ........................................................ 102
ix
LIST OF TABLES
Table 1.1 Biomass Sources ........................................................................................................... 4
Table 2.1 Biomass Proximate and Ultimate Analysis..................................................... 13
Table 2.2 Ash Composition ....................................................................................................... 23
Table 2.3 Gas Impurity Content and Targets ..................................................................... 25
Table 2.4 Gas Cleaning Summary ........................................................................................... 25
Table 2.5 Wet Scrubbing Removal Efficiencies ................................................................ 31
Table 3.1 Required Inputs for Gasifier Model ................................................................... 47
Table 3.2 Expected Tar Composition at 860°C ................................................................. 48
Table 3.3 Comparison Case Modeling Variations ............................................................ 52
Table 3.4 Outlet Composition Comparison with GTI Gasifier .................................... 52
Table 3.5 Outlet Composition Comparison with PEI Gasifier ..................................... 52
Table 3.6 Cold Gas Efficiency Comparison ......................................................................... 53
Table 3.7 Baseline Case Stream Composition ................................................................... 56
Table 3.8 Ni-Reformer Efficiencies ........................................................................................ 58
Table 3.9 Wet Scrubber Efficiencies ..................................................................................... 59
Table 3.10 Syngas Purity Post Tar-Decomposition/Removal Operation .............. 60
Table 3.11 Syngas Purity Post Sulfur Removal Operations ......................................... 63
Table 3.12 Turbine Performance ........................................................................................... 68
Table 3.13 Syngas Composition .............................................................................................. 71
Table 3.14 Catalytic Candle Filter Performance .............................................................. 72
Table 3.15 System Performance Comparison Table ...................................................... 75
Table 3.16 Mass and Energy Balance ................................................................................... 77
Table 3.17 Normalized Mass and Energy Balance .......................................................... 78
Table 3.18 Technology Readiness Levels ........................................................................... 80
Table 4.1 Exergy Accounting Summary ............................................................................... 92
Table 5.1 CEPCI from 1997-2008 ........................................................................................... 96
Table 5.2. Biorefinery Overnight Capital Cost Comparison......................................... 97
Table 5.3. Normalized Biorefinery Capital Cost Breakdown ...................................... 99
Table 5.4. Summary of Biorefinery Subsystem Hardware ........................................ 100
Table 5.5 Input Parameters for H2A Analysis Tool ..................................................... 101
Table A. 1 Capital Costs for Baseline Case ........................................................................ 116
x
Table A. 2 Capital Costs for Advanced Case ..................................................................... 119
xi
ACKNOWLEDGEMENTS
This thesis is based on work perform for the Institute of Transportation Studies
at the University of California at Davis and thanks is due for providing the funding
and motivation for this work.
Special thanks is due to several individuals for their assistance in completing
this research: Dr. Robert Braun of the Colorado School of Mines for providing
expertise and quality control while performing this research, Jered Dean for his help
in modeling and troubleshooting the initial system models, and the thesis committee
members, Dr. Jason Porter, Dr. David Muñoz, and Dr. Anthony Dean, all from the
Colorado School of Mines, for providing valuable feedback on the research
presented here.
1
CHAPTER 1
INTRODUCTION
In the post-WWII era the United States (US) has been the standard of what most
developing nations aim to be. Increasing gross domestic product along with a
growing middle class brought a new age of widespread economic prosperity. With
much more disposable income consumer demand for energy hungry appliances and
automobiles drove a marked increase in per capita energy demand. As global
communication and transportation have become more efficient and available this
economic boom has gradually spread to many nations all across the globe.
Populations in previously underdeveloped regions have experienced record levels
of economic growth and with a rise in economic prosperity there is an
accompanying spike in per capita energy use. As this trend continues in the
developing world, rapid growth in energy usage will likely dramatically alter the
global energy landscape. The two largest emerging energy consuming populations
are found in China and India.
In 2008 China used approximately 7.8 million barrels of oil per day (mbbl/day).
This places China second only to the US in oil usage and their lack of significant
domestic oil supplies requires that they import a major portion of that oil. China is
currently the 3rd largest oil importer, behind the US and Japan [1]. In 2011, oil use in
China is expected to surpass 8.2 mbbl/day which will account for 31% of the total
global oil demand growth.
With global demand expected to rise 49% (86 mbbl/day to 111 mbbl/day) from
2007 to 2035 and with demand potentially outstripping new energy sources, the
average price of oil is expected to rise to over $133/bbl by 2035 [2]. With higher
prices and higher demand for energy it will become increasingly important for both
economic and strategic reasons for the US to look for alternative sources of energy
to meet global demand and to thrive in the new global energy market.
The United States is currently the largest consumer of oil/energy in the world
consuming approximately 18.7 mbbl/day. This accounts for approximately 24% of
global oil consumption. The US only produces about 8 mbbl/day and therefore must
2
import over 10 mbbl/day or nearly 60% of the total oil used [2]. This heavy reliance
on oil imports places the US in a precarious position. If a global incident were to
interrupt the supply of oil the US would feel the impact much more than lower
energy consuming nations. According to current estimates, the US holds
approximately 727 million barrels of oil in strategic reserves [3] to buffer against
such incidents, but at current usage levels that reserve represents about 39 days of
oil supply. While it is unlikely that all foreign oil supplies would simultaneously be
interrupted, even one or two major oil producing countries reducing or suspending
oil imports to the US would severely impact oil supplies and prices. Also, a number
of the top ten US oil suppliers are either politically unstable or ideologically and
politically opposed to the US. This serves to further exacerbate the vulnerability of
the United States and its economy to fluctuation in the energy market.
In general, national economies are sensitive to energy prices and high energy
consuming economies like the US economy are especially sensitive to price
fluctuation. Two main factors contribute to the US economy’s sensitivity to fuel
prices; geography and type of economy.
The United States is large geographically; At 3.79 million square miles (9.83
million km2) the United States is the fourth largest nation in the world and some
individual states, such as Alaska, Texas, and California, exceeding the size of many
smaller nations. This large geographic area coupled with the fact that much of the
population resides in areas of relatively low population density creates an
environment that requires both products and people to utilize significant amounts
of energy on a regular basis. This is manifested by the extensive use of private
motor vehicles for intra/intercity travel as well as for the distribution of goods and
services.
The United States economy is dominated by personal consumption expenditures
(PCE). PCE includes all durable and non-durable goods as well as services. PCE
accounts for 70% of the entire Gross Domestic Product (GDP) of the United States.
23.5% of that spending is related to goods and 46.5% is related to services [4]. The
prices of many of these goods and services are affected significantly by energy
prices. The prices of goods that are manufactured and then transported over long
distances are especially sensitive to fuel prices.
3
As was previously mentioned, the population density of the United States is
relatively low. This means a large portion of the goods and services that makeup the
PCE must be transported significant distances to reach consumers. The cost of fuel
for this distribution adds to the cost of these goods or services and in order to be
profitable, businesses must pass on at least a portion of any increase in fuel cost to
the consumer via price increases. If wages do not keep pace with energy costs, the
ability of the average consumer to purchase these goods and services decreases.
Substantial increases in energy costs would lower the ability of the consumer to
purchase goods and services and would result in dramatic reductions in US
consumer spending. This, in turn, would have a strong depressive effect on the US
economy. In the early 1980’s during the energy crisis and as recently as 2008, when
oil prices climbed above $140/bbl the US saw the dampening effect that high oil
prices can have on the economy. Energy intensive industries such as the airline
industry were crippled by high fuel costs resulting in an increase in industry
bankruptcies and new fees for travelers [5, 6].
Given the US’s sensitivity to oil prices, significant efforts must be made to
develop and employ new technologies and energy sources in order to secure the
stability and long term availability of energy for the US. The following sections
explore one alternative to traditional fossil-fuel based energy.
1.1 Biomass Feedstocks and Fuel Pathways
Biomass is a generic term that describes a wide variety of biological compounds
having potential value as energy sources. Biomass includes energy crops such as
switchgrass, rapidly growing trees such as poplars and willows, agriculture residue
such as corn stover, and industrial residue from sources such as the logging and
paper industries. A number of examples of biomass feedstocks are found in Table
1.1.
If biomass based fuel and power systems become a significant part of the US
energy portfolio, energy crops production will become a profitable industry. Energy
crops are primarily fast growing native grasses and trees which, if grown
commercially, could provide much more predictable and homogeneous feedstocks
than agricultural residues or other currently available waste-derived feedstocks.
4
Homogeneous feedstocks could significantly improve the predictability of
thermochemical-based biorefinery performance.
Table 1.1 Biomass Sources
Feedstock Type Possibilities
Agricultural Residues
Corn Stover Rice Husks Wheat straw Nut Shells Bagasse
Industry Wastes
Logging Residues Wood scraps from Millworks Tree Trimmings Paper mill Remainders Construction Waste Urban Yard Waste
Dedicated Energy Crops
Switchgrass Miscanthus Poplar Trees Willow Trees
Optimization of biorefineries to deal with variability in readily available
feedstocks is not well understood and until the impact of these non-homogenous
feedstocks on gasifier performance is better understood, it must be assumed that
first and second generation biorefineries will benefit greatly from homogeneous
feedstocks provided by commercial energy crops. If biofuels are ever to reach the
level envisioned by the US Department of Energy (DOE), commercial cultivation of
energy crops will be required as current agricultural residues are not sufficient to
meet projected biomass demand [7]. The supply and demand for energy crops will
have to be carefully managed to avoid competing with food crops for land and
resources because such competition could have detrimental effect on world food
prices. Fortunately, the low water and nutrient requirements of most energy crops
means they can often be grown in regions not suitable for food crops. This will help
to minimize competition for arable land and may even improve the quality of
previously depleted land [8].
1.1.1 Biomass Resource Availability
Assessments have shown that more than 400 million tons of biomass are
currently available each year in the United States [9]. The US DOE has estimated that
5
potentially as much as 1 billion tons of biomass could be available in the US each
year [7]. The amount of biomass production depends greatly on the market for
biomass feedstocks and the competition for resources with food crops. Figure 1.1
depicts biomass resources by county generated from geographic information
system (GIS) data analysis tools at the National Renewable Energy Laboratory
(NREL) [10].
Figure 1.1 Biomass Resource Availability [10]
The resources depicted here are a combination of agricultural residues, woody
biomass, and energy crops. Agricultural crops residues include residues from corn,
wheat, soybean, cotton, sorghum, barley, oats, rice, rye, canola, beans, peas, peanuts,
potatoes, safflower, sunflower, sugarcane, and flaxseed. Woody biomass includes
mill residues from processing logs into lumber, forest residues, and wood waste
from the production of consumer goods. Energy crops included crops such as
switchgrass, miscanthus, etc. Figure 1.2 and Figure 1.3 show a county by county
accounting of woody biomass and agricultural residue availability respectively. As
is shown in Figure 1.1 – Figure 1.3, biomass is widely available in the US and so is an
attractive feedstock for producing energy products.
7
1.1.2 Biomass-to-Fuel Pathways
With the exception of coal gasification, traditional fossil-fuel based energy
production systems generally produce a limited number of energy products such as
gasoline, kerosene, diesel, etc. Biomass-based systems can produce a much wider
array of products including liquid hydrocarbons, alcohols, synthetic gases, etc.
Diversity in both the products produced and the variety of feedstocks available
allows biomass-based systems to be deployed economically over a much wider
geographic region than traditional fossil fuel based systems. This flexibility also
allows the plant design to be optimized for the locally available feedstock and
regional product needs making bio-based fuel/power systems attractive for
widespread deployment. Figure 1.4 shows a summary of production pathways for
biomass and fossil fuel based systems using first and second generation
technologies.
Fossil Fuels Biomass
Crude Oil Natural Gas Coal Ligno-cellulosic Biomass Sugar-Starch Crops Wet Biomass Oil Crops
Refining
Blending
Gasification Pyrolysis Hydrolysis
Anaerobic Digester Gas
Fermentation & Distillation
Hydro-thermal Liquefaction
Extraction
Refining EsterificationCatalytic Synthesis
LPG Petrol DieselCNGLNG
FTL DME MeOH LPG H2 Ethanol/Butanol Green Diesel Biodiesel
WGS
H2 Purification
2nd + Generation1st Generation
ThermochemicalBiochemical
Figure 1.4 Production Pathways from Biomass / Fossil Resources to Fuels
First generation technologies (purple blocs) include those that are currently utilized
in the commercial marketplace. These first generation systems would include
biodiesel via oil extraction/esterification and ethanol production via
8
fermentation/distillation of sugar crops. Second generation technologies (orange
blocs) are those that are currently under development and not widely available.
These technologies include ethanol and other liquid fuel production from lingo-
cellulosic feedstocks via thermochemical or biochemical pathways. The fuel
production processes that would be employed in both first and second generation
technologies are depicted as second generation in Figure 1.4. The production
pathway explored in this research is the thermochemical conversion of ligno-
cellulosic biomass to hydrogen.
Hydrogen is an attractive alternative fuel. It is a carbon-free high energy density
(gravimetric) energy carrier. It has more than twice the energy content per unit
mass as other fossil fuels such as gasoline. It produces no carbon emissions when
combusted which provides for carbon-free energy at the point of use and overall
carbon negative/neutral energy when produced using renewable sources of energy
such as solar, wind, biomass, etc. The feedstocks for the production of hydrogen are
diverse, readily available, and in many cases, renewable. It can be readily produced
from biomass (as studied here), from electrolysis of water, from reforming of
hydrocarbon feedstocks, e.g. methane, and from many other sources. These
feedstocks are widely distributed so local production is possible. This reduces the
need for a large transportation infrastructure. When used in conjunction with high
efficiency fuel cells in vehicles/power plants it can directly replace hydrocarbon
fuels such as gasoline, natural gas, and coal. Hydrogen production and use are not
without challenges and shortcomings, but the diversity and abundance of feedstocks
along with the relative simplicity of production makes hydrogen an attractive
alternative energy source.
1.2 Themochemical Conversion
There are several thermochemical processes that are used in producing energy
products. They include pyrolysis, gasification, and combustion. Pyrolysis is
thermochemical decomposition of carboniferous material in the absence of oxygen.
Combustion is similar, but is carried out in the presence of oxygen. Gasification is an
intermediate process that occurs in the presence of oxygen but not at oxygen to
carbon ratios (O/C) sufficient for complete combustion to occur.
9
The gasification pathway is summarized in Figure 1.5 [11]. Gasification is unique
in that it has high carbon conversion, unlike pyrolysis, but does not convert all
carbon to carbon dioxide as is the result in complete combustion.
Hydrocarbon
Fuel
(Coal,Biomass)
Pyrolysis Gases
(CO, H2, CH4,...)
Char
Tars, oils, etc.
Oxygenated Compounds
(Phenols, acid)
CO, H2, CH4, H2O, CO2, cracking
productsGas Phase ReactionsPyrolysis
Char-Gas Reactions CO, H2, CH4, H2O, CO2
Figure 1.5 Gasification Pathway
As the biomass gasification process begins, the feedstock is rapidly heated and
the volatile portion of the organic material is quickly decomposed to form a variety
of compounds such as light gases, tars, oils, etc. Most of these compounds are in a
gaseous state and react with other gases or they are reformed in the gas phase
reactions. The remaining nonvolatile portion of the biomass is converted to solid
carbon (char). In gasification systems most of this char is eventually converted to
CO, CO2, CH4, etc. via a number of reactions including combustion, methanation,
water gas, etc. The ultimate product of gasification is a synthesis gas (syngas)
composed primarily of hydrogen and carbon monoxide. This syngas can be used as
a feedstock to make a wide variety of hydrocarbon compounds via catalytic
processes such as Fischer-Tropsch synthesis, etc.
1.3 Research Objectives
The primary purpose of this research is to evaluate gasification-based routes to
fuel production on energetic and economic bases. Some of the main questions of
interest are:
1. What system architectures could be used to produce fuel and power from
non-food crop biomass?
2. What is the technology status (feasibility timeframe) associated with such
systems?
3. What is the impact of employing advanced cleanup technologies in such
systems?
10
4. What are effective modeling approaches for these complex chemical plants?
5. In what manner can we validate or benchmark the biorefinery models?
6. What economic investment would be required to build such systems?
7. How much would electricity and energy products produced by such systems
cost?
Answering these questions will improve understanding of thermochemical-
based biorefinery systems and of the impact different technologies have on system
performance and economics. To this end, the following research objectives were
established:
1. Understand the status of technologies used in gasification based
biorefineries.
2. Develop biorefinery system concepts.
3. Develop and verify computational biorefinery models.
4. Perform thermodynamic evaluation.
5. Build a capital cost database and perform economic analysis of gasification
based biorefining systems.
1.4 Previous Work
During the literature review several similar studies were discovered: Eric
Larson of the Princeton Environmental Institute led a study of a large 5000 ton/day
biorefinery for the production of hydrogen and power using a directly heated steam
and oxygen blown bubbling fluidized bed pressurized biomass gasifier [12]. Robert
Williams, a colleague of Larson, headed a study of the production of hydrogen and
methanol in gasification based biorefineries using a wide variety of feedstocks and
gasifiers including a bubbling, fluidized bed pressurized gasifier [13]. Corradetti
Alessandro Corradetti and Umberto Desideri of the Dipartimento di Ingegneria
Industriale, Università di Perugia studied the production of hydrogen using a model
of the Battelle-Columbus indirectly heated gasifier. Finally Pamela Spath of the
National Renewable Energy Laboratory (NREL) headed the development of a near-
term biorefinery model for the production of hydrogen using the Battelle-Columbus
indirectly heated atmospheric gasifier [14]. Each of these studies provided valuable
insight into the modeling and performance of these systems.
11
While the models developed here are similar to those found in the literature,
they were created to establish a modeling methodology for use in the current and
future simulation efforts at the Colorado School of Mines, to expand the study of
thermochemical-based biorefineries in several areas not covered by the
aforementioned studies, and to provide a valuable learning platform for future CSM
modeling efforts.
In addition to the overall plant performance typical of studies found in
literature, a detailed second law analysis was performed to explore the destruction
of availability within the plant and identify areas which could be most improved.
The gasifier was included in the modeling efforts, rather than assuming a post-
gasifier syngas composition, to allow for a more detailed second law analysis of the
gasifier, and to allow for exploration of the effects of feedstock flexibility and
operating conditions in future studies. Two different cases of biorefineries were
used in this work, both producing hydrogen, to determine the effect of employing
advanced cleaning technologies on plant performance and economics. These aims,
along with providing a starting point for future systems research at the Colorado
School of Mines, are the main rational for this research.
1.5 Methodology
Because of the complexities inherent in the systems involved, accurately
modeling thermochemical-based biorefineries requires an organized approach.
The first step was to perform an extensive literature search. Specifically, an
effort was made to find related modeling efforts and review literature pertaining to
current and developing technologies related to gasification; biomass feedstock
types, availability, and processing; gas cleanup; hydrogen synthesis and purification;
thermal integration; and power generation. Based on the information gathered
from literature, two distinct biorefinery concepts were developed and possible
operating parameters were established.
The first concept developed was a “near-term” case and is representative of a
biorefinery that could be operating on a commercial scale within the next 5-10
years. The criterion for near-term subsystem classification was that the
12
technologies be mature. This means that all technologies chosen for the baseline
case should be sufficiently far along in their development that they are expected to
be commercially available by 2015. The second concept was created to explore the
impact of employing less mature but promising gas cleaning technologies under
development. The second concept includes technologies that, if developed, would
be commercially available sometime after the year 2020. The specific technologies
were chosen to address performance weaknesses identified in the first concept.
After the plant concepts and operating conditions were established, system
models for both concepts were created using ASPEN Plus® process modeling
software. These models were then benchmarked to other models found in
literature. Once the models had been benchmarked against other peer-reviewed
gasification-based biorefinery models, a thermodynamic analysis, including a
second-law analysis, was performed for each case. The final step was to compile a
database of capital costs and perform an economic analysis. The capital cost, system
performance, and hydrogen/electricity output, were then used to calculate a cost of
hydrogen produced by each concept. The remainder of this thesis details each of
these steps and provides insight into the research process used.
13
CHAPTER 2
THERMOCHEMICAL-BASED BIOREFINERY OVERVIEW
The literature review performed as the initial step to this research provided
valuable information into the design and implementation of biorefinery systems
models. An overview of this information is provided in the following sections to
provide a foundation for the modeling and analysis sections.
2.1 Biomass Feedstock Selection and Preparation
The biomass feedstock simulated in this study was untreated hybrid poplar
wood chips. Hybrid poplar was chosen because it is considered to be a viable
dedicated energy crop and there is sufficient experimental data from sub-scale
gasifiers to support model development and benchmarking. The material
characteristics for hybrid poplar were based on feedstock composition data
provided by the environmental center of the Netherlands’ Phyllis biomass
properties database. The properties of the hybrid poplar wood chips are given in
Table 2.1 [15].
Table 2.1 Biomass Proximate and Ultimate Analysis
Ultimate Analysis Proximate Analysis
Dry
(Wt %)
As-Received
(Wt %)
As-Received
(Wt %)
Carbon 50.2 46.7 Ash 2.5
Hydrogen 6.06 5.6 Water 6.9
Oxygen 40.4 37.6 Volatiles 79.0
Nitrogen 0.6 0.56 Fixed Carbon 11.6
Sulfur 0.02 0.02
Chlorine 0.01 0.009
HHV (kJ/kg) 19022 17711
LHV (kJ/kg) 17700 16312
The woodchips simulated in this research are considered to be in the as-
received-state. This means that no special pre-treatment or drying has been
performed to remove water or change the material properties. Even in the as-
received-state the wood chips have relatively low moisture content. One advantage
of the having a feedstock that has low moisture content is that drying prior to
14
feeding it into the gasifier is not necessary. Composition data for hybrid poplar
chips varies greatly, with some studies reporting moisture contents of farmed trees
as high as 50% [14]. Properties are highly dependent on the state of the feedstock
when the composition was tested e.g. amount of time after harvest, storage
conditions, storage state (logs\chips), and length of storage, etc. This type of
information is rarely reported along with feedstock proximate and ultimate analysis
but can significantly impact plant performance. High moisture content feedstocks
must be dried prior to processing and feeding. This process consumes significant
amounts of energy and therefore reduces overall plant efficiency. The poplar used
in this study is assumed to have an as-received moisture content of 6.9% and is
already in chip form. This means that no additional drying or sizing needs to be
done prior to feeding.
2.1.1 Biomass Plant Sizing
Figure 2.1, shows a composite overlay of NREL GIS data for biomass resources
availability at a level sufficient to provide for 2000 tonnes per day (TPD) within 50
miles [16].
Figure 2.1 2000 TPD Biomass Availability Within 50 Mile Radius
15
The 2000 TPD and 50 mile resource availability limits were selected based on
the optimum plant size and resource availability found in the literature. The 50 mile
collection radius is considered the economical distance biomass could be reasonably
transported, and this limits the economical plant size [17, 18]. At 2000 TPD, there
are many locations that could support this level of biomass availability. At sizes
greater than 2000 TPD the potential locations for such plants becomes greatly
limited [19].
Larger plant sizes are generally more desirable because of the economies-of-
scale enjoyed by such plants. This assumes the same technology is used in all size
plants, but this may be an unreasonable assumption. It may be possible to employ
different and/or emerging technologies, such as water-gas shift membrane reactors
(WGSMR), ion transport membranes for oxygen production, advanced
desulfurization technologies, etc. to create a variety of system configurations that
are more economical at smaller scales ( < 1000 TPD). The use of small scale
biorefineries would significantly increase the number of sites that could support
refineries. The optimal biorefinery size is an area that has not been extensively
studied and requires further exploration.
2.1.2 Feedstock Preparation
Prior to being fed into a high-pressure gasifier the feedstock must be made
suitable for pressurized feeding. Biomass would typically be delivered to the plant
site via train or truck and then, after unloading it would be dried if necessary,
ground, and then sized. In pressurized gasification systems, the reliable feeding of
processed biomass into a pressurized environment is one of the most difficult tasks
and represents one of the most significant technical challenges for pressurized
biomass gasification systems. High-pressure feeding systems exist commercially
and are found in coal gasification plants. However, these systems are not suitable
for use with biomass because the elastic and fibrous nature of biomass make it
impractical to grind into the powders that are required for use in commercial coal
feeding systems.
16
Rather than attempt to feed biomass in its as-received state, another approach is
taken; the biomass is preprocessed to modify its properties to make it suitable to
use with commercial coal feeding technology. Torrefaction is the process most often
employed for this task. Torrefaction is essentially a partial thermal decomposition
of the feedstock. In torrefaction the biomass is heated to 200-300°C in the absence
of oxygen. This results in changes in the biomass properties, converting it from a
fibrous/elastic substance to one with properties more similar to those of coal. The
more brittle torrefied biomass has improved grindability, improved resistance to
feedstock degradation, reduced adsorption of water, and increased energy density
[20, 21]. These changes allow for the biomass to be easily used with commercial
coal feeding technology. With all the improvements in the biomass properties,
torrefaction is not without its drawbacks. These including reduced heating value of
up to 10% [20]. Biomass already has a relatively low heating value as compared
with coal and the losses associated with torrefaction are often viewed as being
prohibitively high.
In biomass feeding systems that do not employ torrefaction several other steps
are taken to overcome the difficulties with pressurized feeding. First, if necessary,
the biomass is dried to a level less than 15-20% moisture. This is important for two
reasons: it improves grindability and increases the value of the biomass as a fuel.
High moisture biomass is technically useable in gasification systems but increased
moisture content requires additional heat to gasify. This means that more of the
biomass must be combusted to provide the additional heat which lowers the
efficiency of the gasifier and leaves less biomass available for syngas production.
After drying, biomass must be pelletized or ground into appropriately sized
particles. Size requirements are not standard and vary depending on gasifier design.
Smaller particles react more completely and are easier to feed into the gasifier but
are more difficult and more energy intensive to produce. Wood chips less than 1.5
inch (4 cm) long are readily attainable using commercial wood grinding
technologies and are sufficient for many gasification systems. Smaller particles
suitable for feeding and pelletization (0.2 inches or 0.6 mm) can be attained with
commercial hammer mills but the wood must be nearly moisture-free in order to
achieve such small sizes [22].
17
For the systems evaluated in this research it was assumed that the 1.5-inch (4
cm) wood chips are sufficient for pressurization and feeding. This assumption was
made primarily to avoid the energy penalty associated with biomass drying and
sizing with hammer mills.
2.2 Gasification
There are four general classifications of gasifiers: Fixed-bed co-current
(downdraft), fixed-bed counter-current (updraft), fluidized bed, and entrained flow
[23]. The fluidized bed and entrained flow gasifiers are the two types that are
generally considered for large-scale biomass gasification applications. Biomass
gasification technology has yet to be proven on a commercial scale but has been
successfully demonstrated in pilot plants and even though biomass gasification is
somewhat different from coal it still shares significant overlap in both processes and
technology. Coal gasification is already a commercially mature process, so
leveraging these technologies will greatly aid in the scale up necessary for the
commercialization of biomass gasification. While coal gasification has successfully
been used worldwide for the production of electricity, gaseous fuels, and chemicals
[24] there remains several significant differences between coal and biomass based
gasification systems that require consideration.
Coal based systems typically employ entrained flow, slagging gasifiers which
operate at high temperatures and pressures (>1300°C, >40 bar). The elevated
temperature and pressure provide several advantages including very low tar yield
along with low steam and oxygen requirements. Characteristics of biomass and the
resulting ash make it problematic for use in such high temperature systems and the
fibrous nature of most biomass makes it difficult to economically achieve the small
particle sizes required for use in the entrained-flow systems. There are two main
approaches to using biomass as a feedstock for gasification.
The first approach is to modify the biomass feedstock itself to make it suitable
for use in slagging gasifiers. This requires several processes including pretreating
the biomass with chemicals to make the resulting slag less caustic and torrifying the
18
biomass. The torrefied biomass can easily be ground and fed into the gasifier using
existing coal feeding technology.
Rather than attempt to modify the biomass for use in slagging gasifiers, another
approach is to modify the gasifier design and operating parameters to adjust for the
challenges of biomass gasification. An example of this would be changing from an
entrained-flow gasifier design to a fluidized-bed concept. This allows for much
longer residence times in the gasifier making it possible to use much larger
feedstock particles. Larger particles mean no torrefaction is necessary and much
lower energy requirements for biomass sizing prior to gasification. Also by avoiding
torrefaction the biomass retains most of its heating value, conserving more for
conversion into power and fuel products. This results in higher overall plant
efficiency. Fluidized-bed gasifiers require that the operating temperature be kept
lower than the ash agglomeration temperature to prevent ash particles from
sticking together and turning into slag and disrupting the bed fluidization. This
temperature (700°C-900°C) is much lower than operating temperatures found in
entrained-flow gasifiers and does not allow for the complete cracking of the tars
formed during gasification. Additional unit operations must be included
downstream of the gasifier to deal with these compounds. Understanding the
formation of tar compounds, their properties, and methods for mitigating the
negative impact of such compounds represents a significant technological hurdle.
Another technical challenge with non-torrefied biomass is pressurized feeding.
Both the issues of tar reforming/removal and pressurized biomass feeding are
discussed in more depth in the following section. Even with the challenges inherent
in the fluidized-bed gasifier approach, this is the method chosen to model in this
study. The potential efficiency gains associated with avoiding torrefaction provides
an attractive reason for pursuing non-torrefied feedstocks.
2.2.1 Technical Challenges for Biomass Gasification
There are three areas that present the greatest technical hurdles to large-scale
commercial biomass gasification systems. They are (1) pressurized feeding of
biomass, (2) tar management and (3) ash agglomeration [25]. These are areas that
are receiving significant research and development.
19
2.2.1.1 Pressurized Feeding
The most significant of the technical challenges is the pressurized feeding of
non-torrefied biomass. Many designs exist but the only method that has been
successfully employed at pilot scales is a lock-hopper/screw feeding system along
with pressurizing agent [26]. While lock-hoppers have been successfully employed
in biomass gasifiers they are far from an ideal feeding system. Lock-hopper based
systems require large amounts of pressurizing agent and this requires a large
amount of gas be available for use as a pressurizing agent. Nitrogen and carbon
dioxide are the most common pressurization agents because they are often available
as byproducts of other plant operations such as oxygen production or carbon
capture. Readily available pressurizing agent helps reduce the negative impact that
lock-hopper systems have on plant performance but additional energy is still
required to compress the pressurizing agent to the required pressure resulting in
reductions in overall plant efficiency.
Furthermore, significant amounts of pressurizing agent dilute concentrations of
hydrogen and carbon monoxide in the syngas produced in the gasifier. A more
dilute syngas reduces the reaction rate in any downstream chemical reactor which
then requires larger reactors and/or additional catalyst both of which add to the
capital cost of the plant. Dilute syngas can also make it much more difficult to
separate out desired products in downstream processes and therefor requires more
energy and/or additional processes. All of these factors increase plant cost and
reduce plant efficiency. In addition to the problems from pressurization, the ability
to feed fibrous biomass such as switchgrass or crop residues is questionable. The
fibrous nature of the biomass tends to lead to clumping and binding in mechanical
feeders. Much development is still needed to overcome the problems associated
with pressurized feeding of biomass.
The Gas Technology Institute (GTI), formerly The Institute of Gas Technology
(IGT), developed a pilot scale, pressurized, twelve tonne per day process research
unit (PRU) gasifier. During testing, there was no clear correlation for the amount of
nitrogen required for lock-hopper pressurization. The amount varied greatly
throughout the experiments, with the maximum amount required being 1.34 kgN2/
kgbiomass and the minimum being 0.21 kgN2/kgbiomass [27]. It is estimated that
20
employing a dual-parallel lock-hopper system could reduce the amount of
pressurization agent required by 25-30% [12]. There is no consensus in the
literature as to how to best estimate the amount of pressurization agent required
with some sources reporting as little as 0.007 kgN2/kgbiomass [28]. However, there is
agreement that the amount of inert gas required to feed biomass is directly tied to
the particle size being fed. The larger the particle, the more inert gas is required to
fill and pressurize the voids in the feedstock. This is an important trade-off between
biomass pressurization requirements and the energy and costs requirements of
feedstock sizing.
2.2.1.2 Tar Management
Another technological challenge is managing the formation and reforming of tar
compounds. Tar is a generic name for a large number of hydrocarbons produced
during gasification. While this leads to some ambiguity in its meaning, it is generally
defined as any hydrocarbon with a molecular weight greater than that of benzene
[29]. Tar compounds are categorized based on the temperature at which they
thermally decompose. Based on the classification scheme proposed by Milne et al.,
primary tars are oxygenated compounds derived from cellulose, hemi-cellulose and
lignin [30]. At temperatures greater than 800-850°C all primary tars are thermally
cracked. Secondary and tertiary tars remain and can be predicted based on gasifier
temperature [30]. The need to minimize tar production by increasing gasifier
temperature must be balanced with the necessity in fluidized-bed systems to keep
temperatures below the ash melting point to preserve bed fluidity.
Tar reduction strategies can be classified into primary and secondary measures.
Primary methods of tar reduction are meant to reduce the amount of tar within the
gasifier itself. The two most common primary methods of tar reduction are bed
additives and selective partial oxidation (POx) in the freeboard of the gasifier. A
simplified diagram of a fluidized-bed gasifier is shown in Figure 2.2. Secondary tar
reduction is accomplished in unit operations after the syngas leaves the gasifier.
Both primary and secondary strategies are discussed in this section and employed
in the system models.
21
Biomass
Oxygen/Steam
Bed Material
Syngas
Gasifier Bed(Pyrolysis Zone)
Freeboard
Figure 2.2 Fluidized-Bed Gasifier
A stationary fluidized-bed reactor is one in which there is a distinct delineation
between a bed regime and the freeboard of the gasifier [11]. In the freeboard, the
solid particles separate from the gases and fall back to the bed. The bed is made up
of biomass particles in various stages of gasification along with a bed material. A
fluidizing agent, typically steam and air/oxygen, is injected at the bottom of the
reactor vessel. The fluidizing agent travels upward with sufficient velocity to lift
(fluidize) the bed material but not enough to carry it out of the top of the gasifier
column. Circulating fluidized-bed reactors and transport reactors are similar to the
stationary fluidized-bed reactor presented here but have much higher fluid
velocities. The bed is a mixture of char, ash, unreacted biomass, and possibly
inorganic material as sand. Biomass is fed into the bed where it is heated and
gasified. As the biomass is converted to syngas it rises, leaving the gasifier, and is
sent on to downstream processes such as cleaning, shifting, etc.
In a fluidized-bed gasifier, silica sand is a typical inert inorganic bed material.
However, catalytic bed materials can be used in place of sand or can be mixed with
the sand to increase gas yields and reduce tar creation. Commercial nickel-based
catalysts as well as natural catalytic sands such as olivine and dolomites are some of
the more promising candidates. Olivine and dolomite are more feasible catalytic bed
22
materials in the short term because of cost, attrition, and deactivation concerns with
the nickel catalysts under development. Dolomite is the cheapest and most active of
the naturally occurring catalysts. It is 1.4 times more active than olivine [31] and is
an excellent candidate for fixed-bed reformers but is generally considered too
frangible to employ in fluidized-bed reactors. Olivine has a much higher hardness
than dolomite and although less active, it can be used as an additive or direct
replacement to silica sand in the gasifier with negligible increases in the production
of fines1 due to attrition [32, 33].
The use of catalytic bed materials in the fluidized-bed of a biomass gasifier may
drastically reduce the amount of tar created. Some sources have reported tar
reductions of as much as 94% versus use of a silica bed material [32]. However,
there have been a wide range of values reported in literature and the results are
highly dependent on bed temperature and other operating conditions in the gasifier
(temperature, pressure, and steam to carbon ratio). In addition, bed additives may
reduce tar at the expense of increased production of ammonia in the gasifier [34].
Another primary tar reduction method is the use of selective partial oxidation
(POx) to reduce tars in the freeboard of the gasifier. In this process a small amount
of oxygen is injected into the freeboard resulting in a reduction of tars and other
species. Based on lab scale experiments by Pan et al., tar destruction rates as high as
90% can be achieved with a properly designed secondary air injection system [35].
The secondary oxygen injection also results in an increase in gasifier freeboard
temperature. Freeboard temperatures as high as 1030°C have been reported for
systems using secondary air injection and even higher temperatures are achievable
if pure oxygen or oxygen-rich air are used. One additional benefit of POx is that other
problematic species such as ammonia are thermally cracked as a result of the
increased freeboard temperature [36]. A concern with using secondary oxygen
injection is that the oxidation reactions will consume significant amounts of
hydrogen and carbon monoxide present in the syngas. This would be undesirable
due to the value of these compounds for downstream fuel and power production.
However, work performed by Villano et al. suggests that at low oxygen
1 Fines are very fine powders produced by the pulverization of inorganic bed material
23
concentrations selective partial oxidation of hydrocarbons is possible without
significant reductions in hydrogen and carbon monoxide [37].
2.2.1.3 Ash Agglomeration
Ash agglomerating temperature is highly dependent on biomass feedstock
composition. The ash contained in cellulosic biomass is composed primarily of salts.
Table 2.2 shows the ash composition of the hybrid poplar woody biomass used in
this analysis [15]. The presence of alkalis in the ash makes it extremely corrosive to
refractory walls and produces a low ash melting temperature (~900°C). To
minimize corrosion and avoid adverse effects on the fluidized reactor bed, ash
agglomeration must be kept to a minimum [11].
Table 2.2 Ash Composition
Ash Component wt % (ash)
CO2 8.2
SO3 2
P2O5 1.3
SiO2 5.9
Fe2O3 1.4
Al2O3 0.8
CaO 49.9
MgO 18.4
Na2O 0.1
K2O 9.6
TiO2 0.3
Ash agglomeration is the easiest of the technical challenges to address.
Maintaining the bed temperature of the gasifier below 800-950°C generally
minimizes ash agglomeration [11]. A range is given since the maximum allowable
bed temperature is highly dependent on the type of biomass being used. In addition
to temperature control, adding catalysts, such as Magnesite (MgO), to the bed
material can help neutralize the more corrosive potassium components of molten
ash (slag)
24
2.2.2 Gasifier Oxygen Supply
The primary oxygen stream is injected into the gasifier so a small, controlled
portion of the biomass feedstock is combusted in the gasifier. This supplies the
necessary thermal energy to drive the endothermic gasification reactions. Oxygen is
used rather than air to avoid excessive dilution of the syngas by nitrogen. For fuel
synthesis, it is preferable to avoid nitrogen dilution so that downstream synthesis
steps do not have to be oversized or nitrogen removed from the syngas stream prior
to synthesis.
A cryogenic air separation unit (ASU) is used to produce the oxygen at 95%
purity for this study. In addition to producing oxygen, a nitrogen stream of 97%
purity is available as a byproduct from the ASU and is used as the inert
pressurization agent for the lock-hopper system. According to literature sources,
260 – 340 kWh of electricity are needed for every tonne of oxygen produced [38],
therefore 300 kWh per tonne of oxygen was assumed. This value does not include
compression of the oxygen and nitrogen product gases, which exit the ASU at
approximately 1.5 bar, and must be raised to gasifier operating pressure [39].
2.3 Gas Cleanup Survey
Raw syngas leaving the gasifier is not suitable for use in any power or fuel
generation application. Biomass gasification produces a variety of chemical
compounds in addition to the desired hydrogen and carbon monoxide. Many of
these compounds are of concern because of the potential for them to condense and
cause fouling of downstream process equipment and deactivation of catalysts. This
along with governmental emission regulations requires that the syngas be
processed to destroy or remove these compounds to levels suitable for downstream
processing and/or eventual exhausting to the environment. Table 2.3 shows the
minimum purity levels recommended for downstream processes, as well as the
contaminant level in the syngas stream upon leaving the gasifier [30]. Fuel synthesis
as discussed in this thesis includes both liquid fuel synthesis and hydrogen
production/purification.
25
Table 2.3 Gas Impurity Content and Targets
Impurity Gas Turbine mg/Nm3 (ppmv)
Fuel Synthesis
mg/Nm3 (ppmv)
Gasifier Outlet mg/Nm3
Tar 0.5–5 (0.07–0.7) 0.1 (0.01) 724.96
Particulate 30 0.02 --
NH3 -- 0.7 (1) 96.61
H2S -- 1.4 (1) 139.31
Alkalis (Na + K etc) 0.1 0.1 --
Most of the differences between the two biorefinery plant designs presented in
this research are found in the gas cleaning portion of the biorefinery, Figure 2.3.
Oxygen
H2S Removal Water Gas Shift Separation
Power Island
Biomass
Preparation
Pressurized
Gasification
Gas Cooling &
Cleanup
Air Separation
Unit
Process
Electricity
Small Export of
Electricity
Unconverted
Synthesis Gas
Biomass
Air
Compression H2
Figure 2.3 Gas Cleaning Portion of Biorefinery
The gas cleanup represents one of the areas where there exist a number of
technologies that could have a significant impact on overall plant performance.
There are many technological and economic factors to consider when selecting the
unit operations for the gas cleanup pathway so to facilitate a better understanding
of gas processing technology as well to understand the rational for the two different
plant designs, an overview of each of these technologies is given in the following
section. A summary of the gas cleaning technologies to be explored is given in Table
2.4.
Table 2.4 Gas Cleaning Summary
Contaminant Mitigation Options
Tar
1. Reforming a. Packed-bed Reactors b. Fluidized-bed Reactors c. Catalytic Candle Filters
2. Removal a. Wet Scrubbing
Sulfur (H2S)
1. ZnO 2. LO-CAT® Process 3. Warm Gas Desulfurization 4. Selexol® Process 5. Rectisol® Process 6. Amine Process
Ammonia Same as Tar Options
26
The tar/ammonia cleaning portion of the plant is discussed first and is followed by
sulfur removal processes.
2.3.1 Tar Cleanup
Tar cleanup methods are divided into two main categories: primary and
secondary. Primary methods are those that are employed within the actual gasifier
including catalytic bed materials, secondary oxygen injection, etc. The secondary
methods include all those methods employed downstream of the gasifier. To
efficiently reach the impurity tolerances required for power generation and fuel
synthesis, a combination of both primary and secondary methods needs to be
employed. As the primary methods were described in the previous section, the
following section will primarily deal with secondary tar removal methods.
Secondary tar removal methods center on two main approaches: chemical
decomposition and physical removal. In the first approach, tars are decomposed
into smaller compounds, ideally hydrogen and carbon monoxide. The second is to
physically remove the unreformed tars from the gas stream via a filtration or
scrubbing process. The former method is the preferred approach for several
reasons. First, tar compounds can contain a significant portion of the heating value
of the syngas, values as high as 25% of the total heating value of the syngas has been
reported [40]. Simply removing these compounds is not desirable because
scrubbing non-reformed tars can results in a low heating value syngas. In addition,
tar compounds are generally toxic to the environment and therefore any tars
removed in a washing process will contaminate the washing water and must be
dealt with outside the biorefinery. This adds significantly to the operating cost of
the biorefinery and therefor increases the cost of refinery products.
The decomposition of tars is accomplished via thermal or catalytic cracking in
one or more chemical reactors. There are a variety of reactor designs that are
suitable for tar reforming but they fall into the two basic designs: packed-bed and
fluidized-bed reactors.
27
2.3.1.1 Reforming Reactors
Packed-Bed Reactors (PBR)
A packed or fixed bed reactor is one of the simplest types of catalytic reactors.
In gas cleanup processes, the packed beds are often configured vertically where gas
entering the bottom of the tower flows up through the catalyst material and after
chemically reacting is exhausted out the top of the reactor. This design provides for
high catalyst density within the bed which leads to high conversion rates per unit
volume. However, there are several drawbacks to this design. The stationary bed
material limits mixing within the reactor and may lead to non-uniform conditions,
resulting in non-uniform catalyst performance, temperature gradients, etc. As with
most catalysts there is a drop-off in catalytic activity over time due to poisoning or
other deactivation mechanisms and once the catalyst activity drops below a
standard, the entire bed of catalyst material must be removed and replaced. There
is no method for removing deactivated catalyst in a PBR while the reactor is
operating. The operating conditions of a PBR depend primarily on the design of the
reactor (reactor diameter, amount of bed material, reactions taking place, etc.).
Fluidized-Bed Reactors (FBR)
The stationary fluidized-bed reactor is similar in design to the PBR except that
the gas velocities in a FBR are sufficiently high so that bed material becomes
suspended. A FBR have several advantages over PBR. The continuous circulation of
material within the bed ensures a well-mixed reactor and promotes thermodynamic
equilibrium throughout. This encourages uniformity of catalytic activity and also
allows for the material to be more easily replaced without shutting down the
reactor. This allows the reactor operate on a continuous basis rather than having to
be shut down periodically to replace the catalyst. Even with all the advantages there
are some disadvantages to the FBR. The continuously circulating bed can lead to
increased attrition of the catalyst material, which reducing the catalyst life and can
generating a large number of fine particles depending on the catalyst material
properties. These fines are very difficult to remove and if not removed they can be
damaging to downstream processes equipment. The fluidized-bed requires a larger
overall reactor volume per mass of catalyst as compared with a PBR, higher
required gas velocities to fluidize the bed material, and greater pressure losses
28
across the reactor. These factors lead to increased capital costs for the reactor itself
and can also require the addition of more pumping equipment leading to higher
utility/maintenance requirements. Also, the fluidized-bed can increase wear on the
reactor walls resulting in lower reactor lifetimes. Like the PBR, the operating
specifications are dictated by the reactor design.
Catalytic Candle Filter (CCF)
Another type of catalytic reactor under development is a hybrid of a candle filter
and a packed bed reactor. Candle filters are typically used for particulate removal
from gas streams and are made from either a ceramic or a sintered metal. As the gas
passes through the filter media, the particulates cake on the outside of the filter
body. The cake is removed periodically via a back flow of gas or a pressurized gas
burst. In a catalytic candle filter, the inner cavity of the candle filter is packed with a
catalyst material. Gas enters the bed material after passing through the filter media,
then percolates up through the catalyst and is exhausted through the top of the
filter. A diagram of a catalytic candle filter is shown in Figure 2.4.
Catalyst
Material
Syngas
Filter Media
Syngas
Figure 2.4 Catalytic Candle Filter
29
Candle filters are typically arrayed in banks of multiple filters. This
configuration provides for high catalyst surface area and slow gas velocities leading
to high conversion efficiencies. Laboratory-scale experiments have reported
conversion efficiency as high as 100% for secondary tars [41].
2.3.1.2 Tar Reforming Catalysts
Regardless of reactor design, the most critical factor in tar reforming is the
catalyst selection. There are a wide variety of catalysts available. Three major
catalysts were examined for this study; Dolomite, Olivine, and Ni-based metal
catalysts. A brief description of each catalyst as well as reported tar reforming
performance is given.
Dolomite
Dolomite (CaCO3) is a class of naturally occurring soft limestone. Sands
produced from dolomite have been shown to have catalytic properties suitable for
tar reforming. The catalytic properties vary greatly depending on the exact mineral
content of the sand. Dolomite sands are primarily carbonates with layers of iron,
magnesium, zinc, manganese, or some combination of these metals. The catalytic
performance of specific compositions of the sands is beyond the scope of this
research. The dolomite simulated for this thesis is generic sand with average
conversion efficiency as reported in the literature. In FBRs, dolomite has high
attrition rates and produces a very high number of fines making it unsuitable for use
in this reactor type. This limits the dolomite to use in either PPRs or CCFs. Tar
conversion efficiencies of 60% have been reported for packed bed reactors [32].
Olivine
Olivine is another mineral that has shown catalytic properties for tar reforming.
It is a magnesium iron silicate that often contains traces of other elements such as
Ni. It is a very hard mineral and the sands it produces are suitable for use in both
PBRs and FBRs. Olivine is extremely common, but not all olivine sands are suitable
for use as tar reforming catalysts. The melting point of olivine is between 1200 -
1900°C which makes it suitable for use in high temperature reforming reactors.
Olivine is generally less active than dolomite but still shows significant catalyst
30
behavior, especially at higher temperatures. Tar conversion efficiencies of 54%
have been reported at temperatures of 900°C [32].
Ni-Based
Nickel based metal catalysts are one of the most common and effective types of
catalysts. The catalytic behavior of nickel is well established. There is a wide
variety of Ni-based catalysts with varying activity levels for tar reforming. The Ni
catalyst considered here is generic, and the properties are an average of those found
in literature. The Ni-based catalysts have very high conversion efficiencies; values
as high as 99% have been reported [42]. There are some problems with Ni-based
catalysts. First, they are very sensitive to certain types of contaminants and
experience significant deactivation when in the presence of tars and sulfur. It has
been reported that tar levels lower than 10g/Nm3 and sulfur levels below 150 ppmv
are sufficient to prevent poisoning [43]. Therefore tar levels must be below this 10
g/Nm3 level to protect the catalyst from excessive deactivation. The Ni-based
catalysts are very expensive as compared to the Dolomite and Olivine catalysts and
require a significant investment.
2.3.2 Physical Removal Methods – Wet Scrubbing
Wet scrubbing is very effective at removing particulates, ammonia, tar and it is
the only method that is effective at removing vapor phase tars. There are a variety of
designs for wet scrubbers, but in general they consist of a cyclone or tower that has
one or more spray rings, Figure 2.5. Tar rich gas enters the tower where a fine mist
of water is being sprayed. The tar and ammonia are absorbed by the liquid water
and the water is then collected at the bottom of the tower and removed.
Approximately 2 liters of water per m3 of syngas are required for effective removal
[44]. The scrubbing water is unsuitable for discharge into existing water systems
and must be treated to remove dissolved contaminants. The high cost of water
treatment may prove to be cost prohibitive in biomass applications [45].
In all cases the moisture content of the syngas is an essential factor for
successful tar removal [41].
31
Syn
gas
H2O H2O
Waste H2O
Figure 2.5 Wet Scrubbing Spray Tower
If the water content in the syngas stream is too low it must be increased to an
acceptable level prior to scrubbing to ensure effective removal. The inlet gas stream
should be fully saturated to maximize tar removal effectiveness. The amount and
type of tars present in the inlet gas significantly affects the effectiveness of the
scrubbing process [46]. In turn, tar composition and amounts are greatly influenced
by whether or not prior tar cracking steps have taken place. In general, a properly
designed wet scrubbing system can meet the tar removal requirements for fuel
synthesis. Generic particulate, ammonia, and tar removal efficiencies of a wet
scrubbing process as reported in literature are seen in Table 2.5 [30].
Table 2.5 Wet Scrubbing Removal Efficiencies
Compound Removal Efficiency
NH3 99.0%
Tar 95.8%
Particulates 99.9%
32
There are several disadvantages to wet scrubbing. As previously stated, the
heating value of the gas is reduced when tars are simply scrubbed out. Biomass tars
have a tendency to form an aerosol which is not as easily absorbed by water spray
as the vapor phase tars possibly reducing the effectiveness of the scrubbing process.
In addition to efficacy concerns, wet scrubbing is a thermally inefficient process for
high temperature gas streams. In order for wet scrubbing to be effective, the
scrubbing water must remain in liquid phase in order to dissolve tars and other
contaminants. This requires that gas inlet temperatures be sufficiently low to
prevent flashing of the scrubbing water to steam which would render it ineffective
as a scrubbing agent. Low inlet temperatures require that significant cooling must
be done prior to wet scrubbing, and significant heating must be done prior to
downstream fuel synthesis processes.
2.3.3 Sulfur Cleanup
After tar cleanup, the most significant impurities remaining are sulfur
containing compounds. Biomass derived syngas typically has much lower sulfur
content than coal derived syngas, but even with reduced sulfur levels it still is not
suitable for fuel or power production. Fuel production catalysts are extremely
sensitive to sulfur poisoning. To avoid deactivation, sulfur must be removed from
the syngas prior to any catalytic process. Sulfur tolerant catalysts are receiving
increased research attention but there has not been significant enough evidence of
sulfur tolerance in any near term catalyst to justify ignoring the presence of sulfur
and the need for sulfur removal technology.
Sulfur in syngas exists in a variety of forms i.e. H2S, COS, SOx, and long-chain
sulfur compounds. In biomass derived gas the majority of sulfur is found as
hydrogen sulfide. This will be the compound of focus in this study. Commercially
there are many options for dealing with sulfur removal. These include a wide
variety of chemical solvents, physical solvents, and catalytic sorbents. The following
sections will give brief overview of each process considered, along with pertinent
operating conditions.
33
2.3.3.1 Physical Solvents
Selexol Process
The Selexol process is a physical absorption process originally developed by
Allied Chemical Corporation and is now licensed by UOP. Physical solvent processes
have many advantages over the chemical absorption process including: high
selectivity for hydrogen sulfide and carbonyl sulfide over carbon dioxide, solvent
stability, low heat requirements for regeneration, and high loading capability at high
acid-gas partial pressures [47]. The Selexol solvent is a proprietary mixture of
polyethylene glycol diakyl ethers which are non-toxic, non-corrosive to metals, and
biodegradable. Selexol plants are one of the most commercially deployed
technologies for acid-gas removal with more than 55 Selexol plants in operation
worldwide. The process can be configured in a number of ways, depending on the
types and amount of acid-gas removal required. Figure 2.6 shows a typical Selexol
process configuration.
H2S
AbsorberH2S
Stripper
H2S Rich
Stream
H2S Free
Stream
Gas
Feed
Figure 2.6 Selexol Process Diagram
The process is basically the same as for other absorber-stripper configurations:
feed gas enters the bottom of the absorber tower and bubbles up through the
solvent which selectively absorbs the hydrogen sulfide. Lean gas exhausts out the
34
top of the absorber tower and the hydrogen sulfide-rich solvent solutions is
removed from the bottom of the tower and circulated to the stripping unit. The rich
solvent is regenerated via a multi-stage flashing process. The regenerated solvent is
then re-circulated to the top of the absorbing tower to begin the cycle again.
The Selexol process is capable of producing highly concentrated acid-gas
streams (hydrogen sulfide or carbon dioxide) which may then be recovered as
either sulfuric acid through a wet sulfuric acid (WSA) process or elemental sulfur
through a Claus process. In the case of carbon dioxide removal, secondary absorber-
stripper configuration is required in which the solvent absorbs the carbon dioxide
and is regenerated in another tower. The captured carbon dioxide can then be
compressed and transported to a sequestration location. The Selexol solvent is
highly selective towards absorbing hydrogen sulfide and is particularly suited to
high pressure operation (> 300 psia) as it becomes more efficient as the pressure
increases [45]. This makes it particularly good for pressurized gasification systems.
The Selexol process is capable of producing a syngas with < 1 ppmv [48]. The
system operates at approximately 60°C making this a low point in the thermal
integration of the gas cleanup system.
Rectisol Process
The Rectisol process is another acid-gas removal system very similar to the
Selexol process. It is the one of the most widely used processes with more than 100
plants installed worldwide. Rather than employing a complex proprietary solvent,
the Rectisol process uses refrigerated methanol. Methanol is very inexpensive and
when chilled (-40°C) has a very high selectivity for hydrogen sulfide over carbon
dioxide. This allows for very deep sulfur removal (< 0.1 ppmv H2S.) The process is
similar to Selexol, except that after being regenerated the methanol must be chilled
again to ensure sufficient selectivity, Figure 2.7. This makes the process more
energy-intensive than the Selexol process.
The Rectisol process can produce a highly concentrated hydrogen sulfide stream
which can then be processed to recover the sulfur via a Claus or WSA process. Also,
with the addition of carbon dioxide absorbing-stripping towers a high purity carbon
dioxide stream can be produced. From a cost perspective the complex nature of the
35
process hardware as well as the energy required to refrigerate the methanol to the -
40°C to -80°C, make this one of the more effective but expensive gas cleanup options
[49]. It is typically used in situation where the syngas will later be processed
through catalytic reactors that require a high-purity syngas to prevent catalyst
poisoning.
H2S
AbsorberH2S
Stripper
H2S Rich
Stream
H2S Free
Stream
Gas
Feed
Methanol
Chiller
Figure 2.7 Rectisol Process Diagram
2.3.3.2 Chemical Solvents
Amine Gas Treating
There are a wide variety of processes that fall into the amine gas treating
category. These processes use an amine e.g. MEA, DEA, MDEA in an absorbing tower
where they form a weak chemical bond with the acid-gases as they pass up through
the amine solution. Once the amine solution has chemically absorbed the acid-
gases, it is circulated through a reboiler and stripping tower to break them chemical
bond. The acid-gas may then be removed. Amine processes are energy intensive
due to the need to heat the solution to break the chemical bonds, but are capable of
removing acid-gases in systems with much lower partial pressures. They are most
often employed in carbon dioxide removal from post-combustion gases. Similar to
Rectisol and Selexol processes, the amine type processes produce highly
36
concentrated acid gas streams which are then suitable for sulfur recovery or carbon
dioxide compression and storage [49].
2.3.3.3 Catalytic Redox - LO-CAT® Process
The LO-CAT® process is owned by Merichem Company. It uses a liquid chelated
iron catalyst that is non-toxic and regenerable, which provides for a low operating
cost and no environmental concerns. The liquid catalyst is circulated through an
absorber tower where the hydrogen sulfide from the syngas absorbs into the
catalyst solution. The hydrogen sulfide is oxidized to solid sulfur state by reducing
the iron ion in the catalyst from a ferric to a ferrous state. In this solid state the
sulfur precipitates and can be recovered for later processing. The catalyst solution is
then circulated out of the absorber tower into an oxidizing tank where it is exposed
to atmospheric oxygen. The iron ion is once again re-oxidized to the ferric ion and
can be recycled to the absorbing tower [50], Figure 2.8.
Sulfur
Free
Gas
Sulfur
Rich
Gas
Exhaust
Air
Oxidizer
Air
Oxidizer
Vessel
Figure 2.8 LO-CAT® Process Diagram
The LO-CAT® process operates at approximately 60°C which typically requires
significant cooling in gasification systems prior to being admitted into the absorber
tower. Typically the LO-CAT® process is capable of removing hydrogen sulfide down
to a concentration of about 10 ppmv [14].
37
2.3.3.4 Catalytic Absorbents
Zinc Oxide
Zinc oxide-based sulfur removal systems are one of the simplest technologies.
They consist of a packed bed reactor filled with a zinc oxide sorbent. Hydrogen in
the feed gas stream reacts with the zinc oxide according to Equation 2.1.
(2.1)
In non-regenerable systems zinc oxide sorbents are only employed as a primary
sulfur removal step when the sulfur levels in the inlet gas are relatively low < 20
ppmv. In gases with concentrations >20 ppmv the sorbent saturates very quickly
increasing the frequency at which the bed material must be replaced. In these
conditions another primary method is typically used and the Zinc oxide sorbent bed
is employed as a polishing step. Zinc oxide sorbent beds are very effective at sulfur
removal; final gas concentrations in the ppb range have been reported [14]. Zinc
oxide sorbent beds must be operated at temperatures >350°C which can be a energy
intensive process when placed after other primary sulfur removal methods that
operate at much lower temperatures.
Regenerable Zinc Oxide
Another zinc oxide-based bulk hydrogen sulfide removal process is warm gas
desulfurization (WGDS). Although it is not commercially employed in biomass
gasification it is being developed for coal systems and provides an attractive
alternative to other methods. All commercial bulk sulfur removal options require
significantly cooler operating temperatures. If sulfur can be removed without
significant cooling of the gas stream, overall plant efficiencies are improved for both
fuel synthesis and power production pathways.
Significant research is currently being done to produce a commercially viable
WGDS process. Research is currently limited to laboratory-scale experiments, but
the fundamentals of the process are becoming clearer and the outlook is promising.
Zinc-titanate transport desulfurization is one of the most likely candidates for WGDS
though many other options are being explored. Representative sulfur adsorption
and desorption reactions are shown in Equations 2.2 and 2.3.
38
(2.2)
(2.3)
The reactor is basically a fluidized-bed reactor paired with a regenerating
column. Gas enters the FBR and is mixed with the catalyst in the fluidized bed.
Sulfur is absorbed by the catalyst via the reactions previously mentioned, and the
clean syngas is exhausted out of the top of the column. During circulation of the bed
material, a portion is drawn off to the regenerating tower. Here the catalyst is
exposed to oxygen from air to reform the zinc sulfide and release the sulfur as sulfur
dioxide, Equation 2.3. The regenerated catalyst is then recycled to the absorbing
reactor to begin the cycle again, Figure 2.9.
Reactor
Column
Regenerator
Column
Gas
Outlet
Gas Inlet Air
Figure 2.9 WGDS Process Diagram
Inlet temperatures of 350–650°C have been reported in literature, which is a
drastic improvement over the 80°C possible with options such as Selexol[51]. Since
both reactions are exothermic, outlet temperatures from the reactor are higher than
inlet temperatures and dependent on the amount of hydrogen sulfide in the syngas.
Representative values would be syngas inlet temperatures of 425-500°C and a
catalyst regenerator temperature of 600–650°C [52]. While outlet concentrations of
less than 1ppmv have been reported [53], concentrations of 10–20 ppmv are more
likely [54].
39
To recover elemental sulfur from the catalyst regenerator tail gas a direct sulfur
removal process (DSRP) would be needed. In a DSRP the SO2 is converted to
elemental sulfur by the reaction shown in Equation 2.4. A slipstream of clean syngas
could be used to provide the required hydrogen, or hydrogen product could be
recycled [55].
(2.4)
The major technical challenges for WGDS being addressed are soot formation,
carbon deposition and catalyst degradation. Initial designs favor oxygen blown
gasification systems because syngas with elevated carbon monoxide levels seem to
have reduced soot formation/carbon deposition [53].
2.4 Hydrogen Synthesis & Purification
To produce a high quality hydrogen product suitable for export an number of
steps are required: the concentration of hydrogen in the syngas must be increased
as much as possible and separated from other constituent gases. The following
sections detail each of these steps.
2.4.1 Water Gas Shift
The water-gas shift (WGS) reaction is an exothermic reaction where carbon
monoxide reacts with steam to form carbon dioxide and hydrogen. The reaction is
shown in Equation 2.5. To produce the maximum amount of hydrogen from the
available syngas, a two-stage water-gas shift system is used to convert some of the
available carbon monoxide to carbon dioxide and water to hydrogen via the water
gas shift reaction.
(2.5)
Water-gas shift is a widely used commercial technology for steam methane
reforming and other hydrocarbon cracking applications. For maximum shift of
carbon monoxide, a two-stage process is typical where both a high and low
temperature catalyst is used in series. Commercial high temperature WGS systems
are typically fixed bed reactors which use an iron-chromium oxide-based catalyst.
40
High temperature WGS catalyst activity drops off for temperatures less than 300°C
and the catalyst is highly sensitive to oxidation if exposed to air. Commercial low
temperature WGS reactors operate at temperatures less than 250°C and use zinc-
copper oxide-based catalysts.
At high temperatures, the reverse water gas shift reaction is thermodynamically
preferred rather than the forward reaction which produces hydrogen. The tendency
to shift is predicted by Le Chatelier’s principle and is highly dependent on the partial
pressures of the reactants in the inlet stream. To maximize the forward shift
reaction, the steam to carbon monoxide ratio should be kept above stoichiometric.
Figure 2.10 shows the relationship between the amounts of extra steam available in
the syngas versus the conversion for a reactor temperature of 350°C.
Figure 2.10 Water Gas Shift Equilibrium Extent of Reaction
While commercial water-gas shift equipment is widely available, it is generally
sensitive to sulfur. Existing iron-chromium-based high temperature catalysts can be
used as long as sulfur concentrations are below 50 ppmv [56]. Low temperature
catalysts are extremely sensitive to sulfur and require desulfurization to less than 1
ppmv hydrogen sulfide prior to use. Even though sulfur levels in biomass-based
syngas are significantly lower than those produced by coal, the sulfur level leaving
the gasifier exceeds acceptable levels for use with existing commercial sulfur-
tolerant WGS catalysts [57].
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1 1.25 1.5 1.75 2 2.25 2.5 2.75 3
Ex
ten
t o
f R
ea
ctio
n (
%)
S/C Ratio
41
Sulfur tolerant catalysts are an active area of research. With much of the world’s
hydrocarbon energy extracted from “sour” resources, there is increased incentive to
improve the sulfur tolerance of catalysts. Cobalt/magnesium and cobalt/chromium
catalysts are commercially available and operate at temperatures from 350-375°C.
These catalysts are sulfur tolerant up to several thousand ppmv. These catalysts
actually require sulfur content for effective operation but many suffer from
significantly lower reactivity than current commercial WGS catalysts. In addition,
cobalt catalysts are only viable for high temperature operation [56]. There are other
catalysts under development such as SSK sour-WGS catalyst from Haldor-Topsoe.
This catalyst is sulfur tolerant and operates at temperatures from 200-500°C and up
to 50 bar [58].
Several sulfur tolerant catalysts exist in laboratory scale experiments including
molybdenum carbide (Mo2C), cobalt and nickel molybdenum compounds [45], and
rhenium-based catalysts [59]. All of these laboratory scale catalysts suffer from
rapid deactivation and are in their infancy.
2.4.2 Pressure Swing Adsorption
Hydrogen is typically separated from the syngas using pressure swing
adsorption (PSA) technology which is a commercial technology in wide use today.
Special adsorptive materials, typically zeolites, are used to preferentially adsorb
hydrogen at high pressure (~350 psi). The reactor then swings to a low pressure
stage (~2.5 psi) where the hydrogen desorbs. The process is non-continuous and so
multiple units in parallel are required for continuous operation.
For optimum performance in a PSA system, several constraints must be met.
Adsorption efficiency decreases with increasing temperature, and the absorptive
materials are extremely sensitive to entrained liquids. Therefore, syngas must be
cooled and condensable liquids removed with a flash drum before entering the PSA.
A pressure ratio of 4:1 is maintained so that 90% of the inlet hydrogen is captured
at a purity greater than 99.9% [14].
In order to achieve the optimum hydrogen capture from the PSA it is important
that there be greater than 70% molar fraction in the syngas inlet stream [14]. If the
42
syngas entering the PSA is below the 70% molar fraction a portion of the product
hydrogen stream can be recycled to the inlet to raise the hydrogen mole fraction to a
sufficiently high level. The recycle of the product stream requires the addition of a
compressor and is not ideal. In the case of syngas with low hydrogen mole fraction,
it may be better to examine other hydrogen separation technology such as
membrane WGS reactors.
The remaining gas steam is composed primarily of carbon dioxide, carbon
monoxide and nitrogen. The heating value is too low for use in a gas turbine and is
generally burned to provide heat and power to the plant [60].
The zeolites used as sorbents can typically handle hydrogen sulfide
concentrations between 50-100 ppmv [61]. The major concern for hydrogen sulfide
in a PSA unit is the potential for the hydrogen sulfide to desorb along with hydrogen
into the product stream and could potentially be damaging to downstream
operations. For this reason it is recommended that hydrogen sulfide be removed
prior to the PSA operation.
2.4.3 Water Gas Shift Membrane Reactors
An interesting alternative to the pressure swing adsorption method of hydrogen
purification is the use of proton conducting membranes. These membranes are
currently being developed for the DOE hydrogen from coal project but would also be
applicable to biomass-based systems. They are catalytically active, promote the
water gas shift reaction, and by selectively removing hydrogen from the reacting gas
stream they allow near complete shift of carbon monoxide to hydrogen. This has
large implications for biorefinery plant designs because it combines the unit
operations of water gas shift and hydrogen purification into a single unit operation.
If DOE target levels for membrane performance and cost are achieved, this
technology could dramatically reduce refinery capital cost and lower the cost of
hydrogen. A more detailed analysis of this technology is given in the biorefinery
modeling section of this thesis.
43
2.5 Hydrogen Compression and Storage
Many of the biomass resources available in the United States are in remote
locations so in order for hydrogen to be a viable fuel, the costs for delivery to market
must be minimized. Currently liquid hydrogen storage is the most economical
choice for long distance shipping, while compressed gas storage is the best option
for short distance transportation of limited quantities [62]. Unfortunately, the
liquefaction process can require energy equivalent to almost half of the heating
value of the fuel (LHV basis) and long-term liquid storage requires open system
storage where evaporative losses can be significant [63]. In this study, hydrogen
compression to 70 bar (7 MPa) is employed as detailed further in Section 3.2.1 of
this thesis.
44
CHAPTER 3
BIOREFINERIES CONCEPTS FOR HYDROGEN PRODUCTION
Two biorefinery concepts were developed for study as part of this research. The
following sections detail the steps taken to model all the processes/technologies
required to produce hydrogen from a biomass feedstock including: gasification, gas
cleanup, water gas shift, hydrogen purification, steam/power production, and air
separation.
3.1 Gasifier Design Selection and Modeling
To establish the performance and operating parameters of the gasifier, a
combination of empirical data published in literature [27] and current research
efforts were utilized. Commercial-scale gasification of biomass has yet to be
realized and no plant-scale empirical data exists with which to correlate large-scale
system models. To overcome the lack of correlation data, operating characteristics
and performance specification of many lab-scale/pilot-scale studies were adapted to
estimate the inputs and outputs of a large-scale directly heated fluidized-bed
gasifier. When empirical data did exist, as in the case of the GTI correlation, it was
used to correlate model results and when it was not available, models were
benchmarked with similar models found in literature.
3.1.1 Design Selection
One of the most significant empirical studies was performed by IGT. The PRU
design stood over 50 feet tall (15 m) and had an 11.5-inch diameter (29 cm) by 10
feet tall (3 m) reaction zone. Above the reaction zone was an 18-inch diameter (46
cm) by 11-foot tall (3.4 m) solids removal zone (freeboard) prior to the product gas
leaving the gasifier. Oxygen and steam were fed into the bottom of the reactor
through adjustable fluidizing gas distributors. The PRU operated using poplar wood
chips as the feedstock which was fed into the gasifier slightly above the bottom
through a combined lock-hopper, screw drive system. Tests were performed over a
temperature range from 750–911°C and at pressures up to 24 bar.
45
The gasifier modeled in this study is based on the IGT PRU design [27, 64] but
several significant alterations were made to incorporate technology developed since
the IGT study. These modifications include a dual lockhopper/screw drive feeding
system replacing the single lock-hopper/screw used in the pilot-scale study which
reduces the pressurizing agent requirement by 25-30% [12]. The other significant
change was the addition of a partial oxidation step in the freeboard of the gasifier. A
gasifier bed temperature of 860 °C was chosen to ensure that primary tars would be
completely cracked inside the bed but ash agglomeration could be kept to a
minimum. The secondary oxygen injection raises the outlet temperature of the
gasifier from 860°C to approximately 1030°C (ΔT ≅ 170°C) and results in a decrease
in tars and ammonia by 88% and 60% respectively [35]. While the higher outlet
temperature could potentially cause concern that ash agglomeration would
increase, but this is not expected to occur because the actual oxygen injection/POx
reactions occur in the freeboard of the reactor well above the bed. Catalytic bed
materials were considered but not implemented in this study because there was not
sufficient data in the literature to adequately understand the effect of operating
parameters combined with POx.
3.1.2 Gasifier Modeling
The modeling of the gasifier is one of the most important and complex portions
of the biorefinery. Fluidized-bed biomass gasifiers do not produce syngas
consistent with equilibrium compositions at given operating conditions. This makes
them difficult to simulate since reaction kinetics for these types of gasifiers are
poorly understood. The non-equilibrium non-kinetic based simulation utilized in
this study requires that multiple unit operations and constraint equations be
utilized to adequately simulate the gasifier performance. The gasifier design is
modeled using ASPEN Plus® process modeling software and the basic modeling
methodology is based upon the method presented by Eric Larson et al. of the
Princeton Environmental Institute [12]. The modeling methodology was
supplemented with calibration data derived from empirical results generated from
GTI’s pilot plant [27]. Figure 3.1 depicts a schematic of the basic gasifier design.
46
Biomass
Raw
Syngas
Solids
Recycle
Secondary
O2 Injection
Oxygen
Steam
Inert
Gas
Syngas
Ash
Heat
Figure 3.1 Gasifier Schematic
The gasifier model requires six separate reactors, seven calculator blocks, and
four design specifications to adequately simulate the gasification process. The
model can be broken down into six main steps. They are as follows:
1. Decomposition
2. Tar formation
3. Gibbs free energy minimization
4. Hydrocarbon formation/tar reforming
5. Oxygen adjustment
6. Water Gas Shift
While an effort was made to create a model that would be flexible enough to use
with a variety of operating conditions and feedstocks, a significant amount of
empirical information is still required for this simulation to accurately predict
gasifier output. The required parameters to run a simulation are shown in Table
3.1.
47
Table 3.1 Required Inputs for Gasifier Model
Input
Proximate, ultimate, sulfur analysis of biomass Pressurization characteristics [kgN2/kgbiomass] Gasifier pressure H2/CO ratio in product syngas Gasifier bed temperature Mole fraction of CH4, C2H4, and C2H6 in syngas Freeboard temperature Tar formation (%mass bone-dry feed) Temperature, pressure, feed rate of biomass
3.1.2.1 Detailed Modeling Steps
The following section provides a detailed account of all the unit operations
required for gasification simulation. The names in parentheses all reference unit
operations and streams depicted in Figure 3.2.
1
2 3
Q1 Q2
6
7
8
911 12
Q3
DECOMP TARFIX
REACTOR
HCADJUST WGS 2NDBURN5
413
14
10
Figure 3.2 Gasifier ASPEN Plus® Diagram
Decomposition
ASPEN Plus® does not have extensive capabilities for modeling solid-to-gas
conversions such as those present in thermochemical processes like gasification.
Therefore several separate steps are required to accomplish this.
The first step is to convert the solid biomass feedstock into its fundamental
components. This is accomplished by creating a non-conventional (NC) solid,
WOOD, to approximate the biomass feed stream (1) and decomposing it utilizing the
RYIELD reactor unit operation (DECOMP).
The composition of the NC solid is based on the proximate, ultimate, and sulfur
analysis of the feedstock. The process is carried out under isothermal and isobaric
conditions and the heat duty of the process is passed on to the next reactor via a
heat stream. The linking of reactors via heat stream is used throughout the gasifier
48
model because it allows ASPEN Plus® to simulate the multiple steps as if they were
occurring in the same reactor and allows for the energy balance to be performed on
the entire system. The decomposition portion of the model assumes 100% carbon
conversion despite the GTI regression suggesting that approximately 2.7% of
carbon is lost as char. This modification was made to account for lower than
predicted syngas flow rates uncovered during initial benchmarking efforts.
Tar Formation
After the NC solid is broken down in the RYIELD reactor the next step, tar
creation, begins. An overview of tar compounds was given in the introduction and
challenges of gasification sections of this thesis and will not be repeated here. In this
study tars are defined as any compound heavier than benzene (C6H6) [36]. These
heavy compounds are additionally subdivided into smaller categories such as
secondary tars, tertiary-PNA, tertiary-alkine, etc. but to simplify the simulations, it
was determined that a single representative compound would be used to represent
all tars. This is to avoid the difficulties inherent in trying to predict the formation
and reforming of a wide variety of tar species. Based on an analysis done by Milne
[30], at a gasifier bed temperature of 860°C, the approximate tar composition is
expected to be as show in Table 3.2.
Table 3.2 Expected Tar Composition at 860°C
Tar Class % Description Representative
Tar Formula
LHV (MJ/kmol)
Primary 0 - - - - Secondary 20 Phenolics, Olefins Benzene C6H6 3136
Tertiary-PNA 40 Condensed tertiary products Naphthalene C10H8 4981 Teretiary-Alkine 40 Alkyl tertiary products Picene C22H14 9912
Weighted Average: C14H10 6584
Based on the weighted averages of both molecular mass and heating value, the
compound anthracene (C14H10) was chosen to be the representative compound.
Anthracene has also been used by others in literature to approximate tars formed
during biomass gasification [65]. The formation of tar is carried out as an
isothermal-isobaric process in an RSTOIC reactor (TARFIX).
Tar is created from the hydrogen and solid carbon present in the stream
produced from the decomposition reactor (2) via that following:
49
14 (3.1)
The extent of the tar formation reaction is set to produce tar equivalent to
1.6%mass of the bone-dry biomass flow [30, 64]. The heat of reaction due to tar
formation is passed along to the next reactor in the heat stream (Q2).
Gibbs Reactor
The next step in the process is to feed the output from the tar forming reactor
into a RGIBBS reactor (REACTOR). This reactor simulates the reaction environment
inside the bed of the gasifier and allows for compounds to be formed in a
distribution according to the minimization of Gibbs free energy. The reactor has
multiple inputs to provide for all the streams that would be present in a fluidized-
bed pressurized gasifier. These streams include nitrogen from the biomass
pressurization/feeding step (6), steam (7) and oxygen (8) fed into the gasifier as
fluidizing/gasifying agents, as well as the simulated gas created in the first two steps
of the modeling process. In order to prevent the premature reforming of tar, the
anthracene created in the previous unit operation, is considered to be inert in the
RGIBBS reactor. The flow rates of these feed streams are set by several calculator
blocks and a design specification. The first calculator block, STEAMSET, sets the
steam to bone-dry-biomass mass ratio to be 0.8 [64]. The second calculator block,
PRESSURE, sets the nitrogen mass flow that would be associated with pressurizing
the biomass during the feeding step. The GTI experimental results [27] show a best
case scenario of 0.21 kgN2/kgbiomass. The GTI gasifier used a single lock hopper
system and literature suggests that switching to a dual parallel lock hopper system
could reduce the inert gas requirement by 25-30%. Based on this information a
0.15 kgN2/kgbiomass was used as the foundation for the PRESSURE calculator block.
The actual amount of pressurizing agent would depend on several factors including
biomass type and size. To allow for comparison/calibration with the published GTI
data the assumption was made that the biomass would be the same 1.5 inch wood
chips used in the GTI study. This is approximately the chip size that would exist if
the chips were processed in a tub grinder [22]. Further reduction in inert
pressurizing gas could be made if the biomass size was reduced to sizes typical of
hammer mill output (0.6 mm), however this would require significant energy input
to first dry and then process the biomass in hammer mills. Additional reduction in
50
biomass size was not considered as part of this study. The oxygen flow into the
gasifier was set by a design specification, O2FEED. This design specification varies
the oxygen flow rate into the gasifier until the outlet temperature matched the
desired bed temperature of 860°C.
Hydrocarbon Adjustment
In the gasifier model the decomposition reactor, tar creation reactor, and
RGIBBS reactor all simulate the bed of the gasifier. The subsequent RSTOIC reactor
(HCADJUST), is an attempt to simulate what takes place primarily within the
freeboard portion of the gasifier.
In this reactor, lighter hydrocarbons (CH4, C2H4, C2H6) are formed and both tar
and ammonia that were previously formed in the RGIBBS are reformed into
hydrogen and carbon monoxide. These processes are simulated by the following
reactions:
(3.2)
(3.3)
(3.4)
(3.5)
(3.6)
A calculator block sets the extent of each of these reactions (2)-(6) to match
effluent gas composition and tar levels found in the literature.
Water Gas Shift
The final step in the model is to adjust the hydrogen to carbon monoxide ratio to
match empirical correlations. A water gas shift reactor is simulated using an RSTOIC
reactor (WGS) and the water gas shift equation.
(3.7)
51
The extent of this reaction is varied using a calculator block to set the hydrogen
to carbon monoxide ratio of the outlet to be 1.43 [64]. The process is considered to
be isobaric and adiabatic and the outlet temperature is adjusted for energy balance.
Primary Tar Reduction
In addition to the typical gasification process an additional step to reduce the
amount of tar produced by the gasifier. This is accomplished by simulating selective
partial oxidation of tars in the freeboard by secondary oxygen injection. Work
carried out by Devi et al. [36] show that secondary oxygen injection provides
significant reductions in effluent tar compounds when compared with gasifiers with
no primary (internal to gasifier) tar removal-reforming steps. In this simulation an
additional oxygen stream (10) is fed into the HCADJUST reactor to simulate this tar
control approach. The amount of oxygen injected is controlled by a design
specification, 2NDAIR, and is varied till the outlet temperature of the reactor is
typical of secondary oxygen injections schemes, approximately 1030°C [35].
Not all the oxygen injected into the gasifier is consumed in the oxidation
reactions. Any excess oxygen remaining after the partial oxidation of tar is
completed is assumed to provide oxidant for combustion reactions. This process is
simulated in the second RSTOIC reactor (2NDBURN). Combustion reactions are
generated by ASPEN Plus® and nitrous oxide is allowed to form.
3.1.2.2 Calibration-Benchmarking
As described in the previous modeling sections, the tar creation, tar reforming,
and hydrocarbon formation were all calibrated to the GTI empirical regression
reported in literature [64]. It is difficult to gauge the accuracy of large biomass
gasifier models since very few empirical studies have been performed. To ensure
the gasifier model developed here is at least comparable to other published studies,
the gasifier performance was compared to a similar modeling effort published by
the Princeton Environmental Institute (PEI), Eric Larson et al. [12]. The differences
in modeling assumptions are given in Table 3.3
52
Table 3.3 Comparison Case Modeling Variations
Parameter CSM Gasifier PEI Gasifier
Feedstock Hybrid poplar Switchgrass Amount of tar formed 1.6% bone dry biomass 1% bone dry biomass Representative tar compound Anthracene (C14H10) Abietic-acid (C20H30O2) Primary tar reduction 88% 90% Outlet temperature 1030°C 1015°C Pressurization 0.15 kgN2/kgbiomass 0.08 kgN2/kgbiomass
To ensure comparability of the two models, the feedstock inputs to the CSM gasifier
model were matched exactly to those of the PEI model. The comparisons of the
outlet gas composition and gas conditions (temperature/pressure) are given in
Table 3.4 and Table 3.5.
Table 3.4 Outlet Composition Comparison with GTI Gasifier
Parameter Units GTI Regression CSM Gasifier Deviation
Outlet Temp. T (°C) 860 860 0.0% Pressure bar 24 24 0.0%
Dry Gas wt % 122.3 122.80 0.4% Carbon Conversion wt % 92.3 100 8.3%
Gas Volume scf/lb BDW 39.7 38.9 -2.0% Char Yield wt % (maf) 2.68 0.00 -100.0%
Tar/Oil Yield wt % (maf) 1.57 1.57 0.1% H2 mole % 13.4 13.5 0.8% CO mole % 9.4 9.5 0.6%
CO2 mole % 19.8 19.9 0.6% H20 mole % 48.9 48.5 -0.7% CH4 mole % 8.0 8.1 0.3%
C2H4 mole % 0.2 0.2 -3.3% C2H6 mole % 0.2 0.2 0.0% C3H8 mole % 0.0 0.0 0.0%
Table 3.5 Outlet Composition Comparison with PEI Gasifier
Parameter Units PEI Gasifier CSM Gasifier Deviation
Outlet Temp. T (°C) 1014 870 14.2% Pressure bar 29 29 0.0%
Mass Flow kg/sec 99.7 99.7 0.0% Mole Flow kmol/sec 4.39 4.39 0.0%
H2/CO ratio 1.35 1.35 0.0% H2 mole % 20.3 20.2 0.3% CO mole % 15.0 15.0 0.0%
CO2 mole % 23.1 23.0 0.3% H2O mole % 28.1 28.2 0.3% CH4 mole % 8.1 8.1 0.1%
N2 mole % 4.7 4.7 0.0% Ar mole % 0.4 0.4 0.0%
Other mole % 0.3 0.4 27.0%
As can be seen in both benchmarking efforts, in most aspects the model closely
matches both cases. Inlet and outlet flow rates are identical in the Larson case but
53
there is a significant discrepancy in the outlet temperature. Larson predicts 14%
higher outlet temperatures than the CSM models. No definite cause for this
discrepancy was found and it is assumed that different assumptions must have been
made about the heat of reaction of the formation reactions in the gasifier. The GTI
benchmarking effort also resulted in very close correlation with the CSM models in
gas compositions and outlet temperature. There was some discrepancy with the
outlet gas volumetric flow rate (-2%) and the carbon conversion rate (8.3%) but
these are to be expected considering the assumptions about 100% carbon
conversion. The exact cause of why the CSM model predicts less gas volume per
tonne of biomass than the GTI correlation is not understood. The second method of
benchmarking was to compare gasifier performance. This was accomplished by
calculating the cold gas efficiency of the gasifier. The cold gas efficiency compares
the heating value of the effluent syngas to the heating value of the biomass input and
is given by the following:
(3.8)
The result of this cold gas efficiency comparison is found in Table 3.6.
Table 3.6 Cold Gas Efficiency Comparison
Source Cold Gas Efficiency
Princeton Environmental Institute 79.7 % CSM Gasifier Model 77.9 % GTI Regression2 77.7 %
The CSM model very closely matches the GTI regression which is expected due
to the calibration of many of the portions of the model with the published GTI data.
Even with the non-GTI calibrated PEI models the cold gas efficiency differed by only
1.8%. The close agreement between the CSM gasifier model and other published
models gives confidence that it accurately represents a poplar-fed fluidized-bed
pressurized biomass gasifier.
2 An error was found in the Bain regression result and the regression was redone using a 2nd
order polynomial fit.
54
3.2 Biorefinery Plant Models
Two biorefinery plant designs for the production of gaseous hydrogen were
developed for analysis. The first design is designated as the “Baseline-case” and is
representative of “near-term” biorefinery, utilizing currently available technologies.
The second design is designated as the “Advanced-case” and is representative of a
biorefinery design that incorporates new and developing technologies in the areas
of gas cleanup and processing in order to improve plant thermal performance. The
following sections provide detailed process descriptions of each biorefinery
concept, model specifications, and plant performance results.
3.2.1 Baseline-case Biorefinery Concept Overview
The purpose of the Baseline-case is to simulate performance of a near-term
biorefinery. In this context “near-term” is defined as employing hardware and
process technologies that are commensurate with a 2015 timeframe, this implies
hardware demonstration at commercial or pilot scales. It should be noted that
while the technology is commercially available this does not mean that the
technology has been deployed in the exact manner depicted in the Baseline-case. A
high-level process flow sheet for the production of hydrogen can be seen in .Figure
3.3 and a more detailed process flow sheet is provided in Figure 3.4.
Oxygen
H2S Removal Water Gas Shift Separation
Power Island
Biomass
Preparation
Pressurized
Gasification
Gas Cooling &
Cleanup
Air Separation
Unit
Process
Electricity
Small Export of
Electricity
Unconverted
Synthesis Gas
Biomass
Air
Compression Hydrogen
· Dolomite Guard
Bed
· Ni-Tar Cracker
· Water Scrubber
· LO-CAT II
System
· ZnO Bed
· HTS
· LTS
Figure 3.3 Baseline Case Process Overview
Biomass is typically prepared for gasification through drying to remove moisture,
milling the feedstock to the appropriate particle size, and pressurization to gasifier
operating conditions in lock-hoppers. Following gasification, syngas cleanup and
water-gas shift, the cleaned hydrogen-rich syngas is further purified via a pressure
swing adsorption process and the final hydrogen product is compressed to 70 bar
55
for transport. Offgas from the PSA is combusted to produce steam for onsite power
production. A detailed process flow sheet and stream composition table are
provided in Figure 3.4 and Table 3.7, respectively and will be referenced throughout
the process description.
PSA
POx Tar
Cracking
Guard
Bed
Tar
Cracker
Wet
Scrubber
HPIPLPCD
Process
Steam
Boiler
CondenserMake-up
H2O
Sulfur
Air
ASU
HTS
LTS
WGS
Steam
Purge Syngas
Recycle
CompressorH2
H2
H2
Compressor
Compressor
Compressor
O2
N2
Exhaust
Biomass
Raw
Syngas
Ash
Gas CleanupGasifier
O2 Generation and
Supply
Waste
Water
H2 Purification
Power Generation
2
1
ZnO
Bed
Combustion
Air
Water Gas Shift
6 7
10
9
8
22
20
Syngas
Cooler
1&2
Syngas
Heater
24
23
Water
19 Combustor
LO-CAT
Process
3
To
Exhaust
Cooling
Tower HX
4 5
25
2627
21
16
12
13
1514
11
AC
17
N2 Vent
WGS
Steam
28
Air
T (°C) P(bar) m(kg/s)
1 25 1.0 23.1
2 1030 22.0 50.4
3 1028 22.0 50.4
4 693 21.0 50.4
5 161 21.0 50.4
6 40 20.0 35.4
7 375 20.0 35.4
8 375 20.0 35.4
9 444 19.0 50.0
10 200 19.0 50.0
11 264 19.0 50.0
12 40 17.0 41.9
13 41 17.0 44.0
14 41 17.0 3.8
15 41 17.0 2.1
16 41 2.0 40.2
17 60 70.0 1.7
18 4 1.2 40.2
19 890 1.2 105.7
20 334 25.0 31.1
21 334 25.0 14.6
22 90 1.0 105.7
23 10 1.5 7.4
24 10 1.5 29.5
25 254 25.0 5.8
26 254 25.0 1.6
27 281 25.0 3.5
28 25 1.0 36.9
29 25 1.0 65.5
30 35 1.15 65.5
31 -17 1.05 26.0
Condensate
Syngas
Cooler 5
Syngas
Cooler 4
Syngas
Cooler 3
21
18
Purge Gas
Expander30
29
Vent
31
N2
Expander
Combustion
Air Blower
Figure 3.4 Detailed Baseline Case Process Flowsheet
3.2.1.1 Gasifier
In both the Baseline and Advanced-case studies, the same biomass gasifier
model is employed. The details of the gasifier modeled in ASPEN Plus® were given in
the gasifier section of this thesis and the model was validated with published data
from the GTI PRU.
As shown in Figure 3.4, woody biomass with a moisture content of 6.9% enters
the plant as stream (1) and is fed to a dual-lock-hopper-system where it is
pressurized with nitrogen (27) from the ASU. The moisture content of the raw
biomass is low-enough to avoid drying operations, resulting in significant cost
reduction. Inside the gasifier the biomass is fluidized with high pressure steam (20)
56
and oxygen (25) and reacts to form primarily H2, CO, CH4, Tars, and CO2. The
compositions of critical streams can be seen in Table 3.7.
Table 3.7 Baseline Case Stream Composition
Stream #
Mole Fraction 2 3 4 5 6 8 9 11 14 16
N2 0.055 0.055 0.049 0.049 0.071 0.071 0.049 0.049 0.000 0.097
H2 0.148 0.149 0.307 0.307 0.449 0.449 0.393 0.451 1.000 0.255
O2 0.000 0.000 0.000 0.000 0.000 4.5E-06 3.1E-06 3.1E-06 0.000 6.1E-06
CO 0.110 0.111 0.158 0.158 0.231 0.231 0.076 0.018 0.000 0.035
CO2 0.175 0.175 0.154 0.154 0.225 0.225 0.239 0.297 0.000 0.588
H2O 0.436 0.435 0.323 0.323 0.010 0.010 0.235 0.177 0.000 0.007
CH4 0.069 0.069 0.006 0.006 0.009 0.009 0.006 0.006 0.000 0.012
C2H4 0.002 0.002 1.5E-04 1.5E-04 2.2E-04 2.2E-04 1.5E-04 1.5E-04 0.000 2.9E-04
C2H6 0.002 0.002 1.6E-04 1.6E-04 2.4E-04 2.4E-04 1.6E-04 1.6E-04 0.000 3.2E-04
NH3 1.3E-04 6.2E-05 2.7E-06 2.7E-06 1.3E-06 1.3E-06 8.6E-07 8.6E-07 0.000 6.1E-07
H2S 9.4E-05 9.4E-05 8.3E-05 8.3E-05 1.0E-05 1.0E-06 6.9E-07 6.9E-07 0.000 1.4E-06
Ar 0.003 0.003 0.003 0.003 0.004 0.004 0.003 0.003 0.000 0.006
NO 6.8E-06 6.8E-06 6.0E-06 6.0E-06 8.8E-06 8.8E-06 6.0E-06 6.0E-06 0.000 1.2E-05
C14H10 (Tar) 9.1E-05 3.2E-05 2.8E-07 2.8E-07 2.0E-08 2.0E-08 1.4E-08 1.4E-08 0.000 2.8E-08
Total Flow (kmol/hr)
8300 8310 9433 9433 6450 6451 9366 9366 6829 4725
Total Flow (kg/hr)
181305 181305 181305 181305 127563 127563 180081 180081 13767 144782
Temperature (°C)
1030 1028 693 161 40 375 445 264 41 41
Pressure (bar)
22 22 21 21 20 20 19 19 17 2
In the free-board of the reactor, a slipstream of oxygen (26) is supplied to crack
a portion of the tars formed before the syngas is fed to a cyclone for particulate and
ash removal. The raw syngas (2) exits the gasifier with about 14.8% H2, 11% CO,
17.5% CO2, 43.6% H2O, 6.8% CH4, and elevated levels of H2S and tars. The cold-gas
gasifier efficiency is approximately 77.9% (LHV-basis).
3.2.1.2 Gas Cleanup
Upon leaving the gasifier the syngas (2) enters the gas cleanup train of the
refinery. The cleaning of the syngas is technologically challenging and there is
substantial research interest in both the coal and biomass gasification research
communities as it represents one of the major barriers to commercialization. Due to
57
the high level of interest the gas cleaning unit operations represent one of the areas
most likely to see dramatic improvement in the coming years.
Chemical Reforming – Physical Removal
The first portion of the gas cleaning process involves the decomposition and
removal of tar. In order to reform as much of the tar as possible, it is necessary to
use a nickel-based metal catalyst. At tar concentrations of >10 g/Nm3 there is
significant risk of catalyst deactivation. The syngas in stream (2) has a tar
concentration of approximately 8 g/Nm3 and while this is less than the critical 10
g/Nm3 it is close enough that there may be deactivation concerns. In order to
protect the nickel-based catalyst, a two-stage tar reforming process is used. The
process is modeled using RSTOIC reactors as shown in Figure 3.5 with the extent of
reaction in each reactor is set to match values found in literature.
Figure 3.5 Two-Stage Tar Reforming Reactors in ASPEN Plus®
The first stage (GBED) consists of a packed bed reactor filled with a dolomite
sand catalyst. Dolomite does not show the sensitivity to high tar concentrations that
metal catalysts do and so this first reactor acts as a guard bed for the Ni-based
reformer. In the reformers, the tar, modeled as anthracene, is converted into carbon
monoxide and hydrogen via the steam reforming reaction,
(3.9)
Ammonia is also decomposed in the reformers via the reaction,
(3.10)
58
Devi et al., report 62.5% of tar conversion in a dolomite reforming reactor
operating at 900°C and expect that increasing temperature should increase catalyst
performance [32]. Thus, with the guard bed operating at 1030°C, a 65% tar
conversion was selected for the model as a reasonable estimate of reforming
effectiveness. Using this effectiveness the dolomite guard bed removes the bulk of
the tar, leaving a concentration of 3 g/Nm3 at the outlet. This value is well below the
10 g/Nm3 limit and thereby should alleviating concerns over catalyst deactivation
[43]. An olivine based fluidized bed guard reactor was considered as another
candidate for the guard bed catalyst as it has higher hardness and does not generate
high levels of fine particles or have the attrition problems associated with dolomite
when operating in a fluidized-bed environment. Ultimately dolomite was chosen as
the catalyst for the guard bed because it demonstrates a much higher catalytic
activity and dolomite packed beds show better tar conversion than fluidized olivine
beds operating under similar conditions [32]. In addition to tar decomposition,
there also is a significant conversion of ammonia (NH3). Ammonia conversion levels
of approximately 53% have been reported [42].
Upon leaving the guard bed the syngas (3) enters the second stage of the
reforming process. The catalytic reformer is a packed bed reactor similar to the
guard bed, but employs a generic Ni-based steam reforming catalyst. This catalyst is
significantly more active than the dolomite in the guard bed. The reactor converts
not only tar but also ammonia, ethane, ethylene, and methane at the conversion
efficiency reported in Table 3.8. Reformer efficiency is defined as the percent
decrease in mole fraction of the compound as it passes through the reactor.
Table 3.8 Ni-Reformer Efficiencies
Compound Efficiency
NH3 95%
Tar 99%
C2H4 90%
C2H6 90%
CH4 90%
After reforming 4 mg/Nm3 of tar remain in the syngas (4). For fuel synthesis
and hydrogen purification, tar levels must be < 0.1 mg/Nm3, therefore, a final
59
removal step is needed. The final step for the tar cleaning portion of the Baseline-
case model is a wet scrubbing tar removal step. The syngas must first be cooled in a
series of heat exchangers and then passed into a wet scrubbing unit (5). The wet
scrubber is modeled using a flash drum and separator. The flash drum accounts for
the water removal from the spray tower and the separator allows for the removal of
a fraction of the contaminant species shown in Table 3.9. The ASPEN Plus®
implementation is shown in Figure 3.6.
Figure 3.6 Wet Scrubbing Process in ASPEN Plus®
Wet scrubbing is very effective at removing particulates and tars and is the only
method currently available for dealing with these substances. There are a variety of
designs for wet scrubbers including spray towers and cyclonic scrubbers. No
specific wet scrubber design was selected for this study, and it was determined that
generic performance specification for wet scrubbing technology would be sufficient.
The generic scrubbing performance for wet scrubbers used in the Baseline-case is
shown in Table 3.9.
Table 3.9 Wet Scrubber Efficiencies
Compound Removal Efficiency
NH3 99%
Tar 95.8%
Particulates 99.9%
A significant amount of water is required for wet scrubbing (approximately 2
LH2O/min/Nm3) and the process itself generates a contaminated wastewater stream.
This wastewater requires onsite treatment or a municipal wastewater treatment
60
system capable of dealing with the tar compounds removed during syngas wet
scrubbing [44]. As previously mentioned this is a serious concern for biomass
gasification systems due to the high cost of treating the wastewater. This additional
cost could make such systems not economically viable.
The gas purity requirements for combustion and fuel synthesis as well as the
post-tar decomposition/removal syngas purity can be seen in Table 3.10. Gas
turbine purity requirements levels are much more relaxed than fuel synthesis
requirements. This gives an advantage to systems using syngas to generate power
rather than produce fuel because of the high cost of cleaning the syngas to the purity
required to produce fuel.
Table 3.10 Syngas Purity Post Tar-Decomposition/Removal Operation
Impurity Gas Turbine
[mg/Nm3] (ppmv) Fuel Synthesis
[mg/Nm3] (ppmv) Post Tar Cracking [mg/Nm3] (ppmv)
Tars 0.5–5 (0.07–0.7) 0.1 (0.01) < 0.1
Particulates 30 0.02 --
NH3 -- 0.7 (1) < 0.1
H2S -- 1.4 (1) 122.02 (87.7)
Alkalis (Na, K, etc.) 0.1 0.1 --
Sulfur Removal
After leaving the wet scrubber the syngas is essentially free from tar and
ammonia. The remaining contaminant of concern is sulfur. For biomass-based
systems sulfur is primarily found in the form of hydrogen sulfide and to a much
lesser extent, carbonyl sulfide (COS), which is neglected in these analyses. Since
carbon dioxide capture was not considered for the biorefinery models in this study,
the most economical method to remove hydrogen sulfide from the syngas involves
using Merichem’s liquid redox process (LO-CAT®) followed by a zinc oxide polishing
bed. The LO-CAT® stripping tower is simply modeled using a separator. The LO-
CAT® process is capable of removing hydrogen sulfide to levels of approximately 10
ppmv and this is used to set the output of the LO-CAT® separator. The hydrogen
sulfide stream leaving the separator is then passed to an oxidizing reactor where it
is reacted with oxygen from an air stream to produce water and elemental sulfur.
The reaction of hydrogen and oxygen is set for complete conversion of hydrogen
61
sulfide to water and elemental sulfur. The ASPEN Plus® model is shown in Figure
3.7.
Figure 3.7 LO-CAT ® Process in ASPEN Plus®
The 10 ppmv purity level is sufficient for downstream combustion, but is not
adequate for use with most fuel production catalysts. This results in the need for a
second polishing step. While there is significant research interest in improving
sour-gas catalysts, the majority of commercial fuel production catalysts remain
extremely sensitive to sulfur poisoning and for this reason, the models that were
developed for the baseline-case this study do not assume any sulfur tolerance in the
downstream processes.
Syngas leaving the LO-CAT® unit (6) must be first heated in a heat exchanger to
375°C before entering the zinc oxide beds. Zinc oxide beds are capable of producing
a syngas with a hydrogen sulfide concentration in the ppb range but for the cases
considered in this study, it is sufficient to conservatively model the zinc oxide
62
reactors as removing hydrogen sulfide down to the 1 ppmv level. The zinc oxide
reactor was modeled using a RSTOIC reactor and an overall reaction for the
conversion of sulfur. The sulfur would actually be in the form of zinc sulfide in a
non-regenerating zinc oxide system but for simplicity the overall reaction was
considered to be sufficient.
(3.11)
The extent of reaction was set so the outlet hydrogen sulfide concentration was
at 1 ppmv. The zinc oxide reactor (ZNOBED) is shown in Figure 3.8. The solid sulfur
is then removed from the stream via a separator (SSPLIT2).
Figure 3.8 Zinc Oxide Sulfur Polishing Bed in ASPEN Plus®
Ultimately, the primary reason for the selection of LO-CAT® process was
economic rather than technical. LO-CAT® is by far the least expensive of the sulfur
removal technologies when carbon capture is not considered. However, carbon
dioxide capture can be an important factor in the plant design for two reasons: (i) it
can improve sub-system efficiency by increasing the partial pressure of reactants in
the water-gas shift reactors and hydrogen in the PSA train, and (ii) for sequestration
purposes. Pre-combustion carbon capture and removal is typically accomplished
with either Selexol or Rectisol processes, but can be costly, representing some 12%
of the biorefinery installed capital cost [12]. Carbon mitigation may eventually be of
interest because of future carbon tax legislation, other carbon regulations, and the
63
impact on overall plant efficiency. The final syngas purity results can be seen in
Table 3.11.
Table 3.11 Syngas Purity Post Sulfur Removal Operations
Impurity Fuel Synthesis
[mg/Nm3] (ppmv) Gasifier Outlet
[mg/Nm3] Final Concentrations
[mg/Nm3]
Tars 0.1 (0.01) 724.96 < 0.1
Particulates 0.02 -- --
NH3 0.7 (1) 96.61 < 0.1
H2S 1.4 (1) 139.31 1.37
Alkalis (Na, K, etc.) 0.1 -- --
3.2.1.3 Hydrogen Synthesis & Purification
After the syngas has been freed of the hazardous contaminants it is then ready
for hydrogen upgrading and purification. The clean syngas (8) first passes through
a two-stage water-gas shift process. The first stage is a high-temperature shift
reactor operating isothermally at 375°C which is followed by a low-temperature
shift stage at 250°C. The WGS reaction is exothermic and any heat generated by the
reaction is recovered as part of the heat recovery/steam generation system. The
details of the WGS reactors were discussed in the technology review section. The
operating conditions for the WGS reactors are intended to maximize the selectivity
towards hydrogen production.
The water gas shift reactors are simulated in ASPEN Plus® using RSTOIC
reactors.
8
21
9 10 11
HTWGS LTWGS
Figure 3.9 WGS Reactor Train in ASPEN Plus®
For each reactor a calculator block uses the behavior described in Figure 2.10 to
set the extent of reaction. The reactors are set to be isothermal and the heat
64
generated from the WGS reaction is used to generate steam. The syngas stream is
cooled in a HRSG heat exchanger between the high temperature and low
temperature shift reactors. A steam stream in fed into the HT-WGS reactor to ensure
the steam-to-carbon ratio is above stoichiometric which helps ensure the forward
WGS reaction dominates. This steam-to-carbon ratio is set by a calculator block
(SSTEAM).
After the WGS reactors, the syngas (11) goes through several cooling/drying
steps and then enters a PSA unit to isolate the hydrogen from carbon dioxide and
other constituent gases. The ASPEN Plus® model of the PSA process includes 4 unit
operations (PSAMIX, PSA, PSASLPT, PSARECY) and one design specification:
PSAPSAMIX PSASPLT
PSARECY
15 14b
141316
12 14a
Figure 3.10 PSA Process in ASPEN Plus®
The first step is a simple mixer which mixes the incoming syngas with a slip
stream of recycled hydrogen from the product stream. The hydrogen mole fraction
in the syngas entering the plant is only about 58%, well below the recommended
70% so a design specification is used to vary the amount of hydrogen recycled to
ensure the mole fraction of hydrogen at the inlet is > 70%.
The next step is a separator (PSA) which separates out the hydrogen from the
other constituent gases. The separator the split fraction for each component gas
and the hydrogen split fraction is set so that 85% of the hydrogen in the inlet stream
(13) is recovered. The remaining gases (16) are then sent to a simple combustor
where they are mixed with air and burned to provide heat for steam generation.
After the separation step the final step is the stream splitter (PSASPLT). A portion
of the hydrogen product stream (14) is pulled off to be recycled (14b) to the inlet as
described previously and the remaining product (14a) is compressed for export. To
avoid the energy requirements and evaporative losses associated with liquefaction,
65
hydrogen is stored as a compressed gas in this study. While most gas tanks
currently store hydrogen at 20 MPa, the industry goal is to make tanks capable of 70
MPa storage [63] Hydrogen can be compressed with standard mechanical piston
(reciprocating) compressors to this level, though modified seals may be required.
For this study, hydrogen is compressed to a pressure of 70 bar with a multi-stage
intercooled compressor. This pressure is suitable for pipeline transport.
3.2.1.4 Thermal Integration
The number of operations required to convert biomass to a usable fuel leads to a
complex plant with significant heating and cooling requirements. Syngas leaving the
gasifier at over 1000°C eventually must be cooled to near ambient temperature
prior to some unit operations such as PSA, wet scrubbing, LO-CAT®, etc. This
requires multiple cooling and reheating steps; the exact number of which is based
on the gas cleaning approach chosen. Regardless of the specific arrangement, there
is significant thermal energy available for on-site power production. The primary
purpose of thermal integration in the biorefinery is to effectively match process
heating and cooling of the syngas with the steam plant water streams. The following
subsections examine matching of hot and cold streams via pinch analysis and
integration with the steam Rankine cycle for power production.
Pinch Analysis
Pinch analysis was performed in order to minimize plant utility requirements
and maximize power production for each of the plant concepts. Pinch analysis is a
set of techniques developed to optimize the energy efficiency of process integration
[66]. Using stream temperatures and heat content requirements of each plant, “hot”
and “cold” streams are defined; a “hot” stream is one that requires cooling and a
“cold” stream is one that requires heating. For this analysis, hot streams were
defined for each plant per the individual gas clean-up process requirements. Once
the hot streams were identified, a composite curve was constructed. This composite
curve represents the combined total of all available thermal energy in the system. A
similar approach was taken in constructing the cold composite curve. The cold
composite curve represents the combined total of all the heating requirements in
the process. A pinch temperature of 20°C was used for both cases. This is the
66
minimum allowable temperature difference between the hot and cold composite
curves which still allows for economic heat transfer to be possible and represents
the maximum allowable heat transfer for a particular system. The composite curves
for both the baseline and advanced cases are shown in Figure 3.11 and Figure 3.12
respectively.
Figure 3.11 Baseline Case Pinch Composite Curve
Figure 3.12 Advanced Case Pinch Composite Curve
In order to maximize plant power production, the amount of steam produced is
maximized to recover as much thermal energy as possible. Low stream
0
100
200
300
400
500
600
700
800
900
1000
0 50000 100000 150000 200000 250000
Te
mp
era
ture
(°C
)
Heat Duty (kW)
Cold Stream Composite
Hot Stream Composite
Pinch
0
100
200
300
400
500
600
700
800
900
1000
0 50000 100000 150000 200000 250000
Te
mp
era
ture
(°C
)
Heat Duty (kW)
Cold Stream Composite
Hot Stream Composite
Pinch
67
temperatures in the condensing step in the Rankine cycle and in the water knockout
prior to the PSA requires that an on-site water-cooling system be included to
provide cooling for the low-grade hot stream. The steam cycle sizing as determined
by optimizing the cold composite curve was later verified in ASPEN Plus® by using a
design specification to maximize the steam generated by minimizing process waste
heat. While the composite curves determine the maximum possible power plant
sizing, they do not determine the heat exchanger network directly. The network was
determined by comparing temperature and heat capacitance of the available hot and
cold streams. The heat exchanger network was analyzed in Excel and hot/cold
streams were matched based on information gleaned from the pinch analysis. As
with the steam cycle sizing, the heat exchanger network designed by using pinch
techniques was later verified and validated by ASPEN Plus® simulations.
The process integration goal in this study was to maximize the capture of
available thermal energy. While this provides the maximum power output possible
from the plant, it may not be the most economic approach to process integration.
Economic considerations were not part of the pinch analysis performed for this
research and a study of capital costs may change the thermal integration network
design.
Steam Generation
Using the thermal integration network designed through pinch analysis, steam is
generated from cool process water and then expanded in a multi-stage steam
turbine to produce power. The major source of thermal energy for steam
generation is provided by burning the PSA off-gas (16). The heating value of the
PSA off-gas is too low to be used directly as a fuel in a gas turbine but is high enough
to be combined with air from the environment and burned in a simple combustor.
The high-temperature exhaust gas produced in the combustor (19) is then utilized
in the heat exchanger network to produce steam required for gasification and power
production.
Steam Turbine
Steam generated in the heat exchanger network is fed into a multi-stage steam
turbine with one stage of reheat. The steam enters the high pressure turbine at a
68
temperature of 540°C and 120 bar. These conditions fall within the typical
operating parameters for GE multi-stage steam turbines [67]. The steam is
expanded in the high pressure turbine and exhausts at 334°C and 25 bar. The high
pressure turbine exhaust pressure was determined by estimating the optimum
reheat pressure ratio at 0.21 [68]. At this point the process steam required by the
gasifier and the pre-WGS saturator in the Baseline-case is diverted for its intended
purpose, bypassing the reheater and intermediate and low-pressure steam turbines.
The remaining steam then re-enters the heat exchanger network where it is
reheated 540°C. After the reheat the steam enters the intermediate pressure
portion of the turbine and is expanded from 25 to 5 bar. The steam further expands
through two more pressure regions in the turbine: from 5 to 1 bar in the low-
pressure turbine; and finally from 1 to 0.05 bar in the condensing turbine. The
steam exits the turbine with a quality of 94%. This steam is condensed in a two-
stage on-site cooling process and is passed into a deareator where it mixes with
process make-up water before being pumped back into the boiler feedwater heat
exchanger network. The steam expansion process is simulated in four stages to
allow for the use of different efficiencies at each stage. The efficiencies employed for
each turbine stage are found in Table 3.12.
Table 3.12 Turbine Performance
Turbine Section Pressure (inlet-outlet) Isentropic Efficiency
High Pressure 120 bar – 25 bar 75%
Intermediate Pressure 25 bar – 5 bar 82%
Low Pressure 5 bar – 1 bar 85%
Condensing 1 bar – 0.05 bar 82%
Cooling Tower
Many existing gasification studies assume a once-through circulating water
system. This assumption means that in addition to plant location restrictions due to
biomass availability (which are significant), zoning, and emissions controls, the
plant must be located next to a natural body of water such as a lake or river. This
may not be feasible for many locations that would otherwise meet all requirements
and thus, a closed-loop circulating water system was used for this study. The
general arrangement of the system can be seen in Figure 3.13. A counter-flow
69
induced draft cooling tower is used to cool circulating water used for the
condensers and other low temperature cooling needs of the plant.
CONDENSER
MAKE-UP WATER
PUMP
TO PLANT
FEEDWATER
SYSTEM
COOLING TOWER
CONDENSING
TURBINE
EXHAUST
V-1
COOL RETURN
HOT WATER
Figure 3.13 Circulating Water System Schematic
While assuming a closed-loop system is a more reasonable assumption, it has a
negative effect on plant efficiencies. Tower design, the wet bulb temperature, and
ambient temperature determine the temperature of cool water returning from the
cooling tower. Typically this return temperature is warmer than water available
from a river or lake. In addition, induced draft cooling towers require electricity for
fans and pumps. Finally, there are still significant water demands due to evaporative
losses (approximately 1.8% of the water input) in the tower. The process was
modeled in ASPEN Plus® as shown in Figure 3.14.
Evaporation H2O Loss
Evaporative Cooling
Hot Process Water
Make-up H2O
Cool Process Water
Figure 3.14 Counter-Flow Cooling Tower in ASPEN Plus®
Process water enters the condenser and cools the condensing turbine exhaust
before being pumped into the cooling tower. A portion of the water is lost to
70
evaporation and the rest condenses at the bottom of the cooling tower where it is
mixed with makeup water and then recycled into the cooling system. The fraction of
water lost to evaporation is given by the following [69]:
( ) ( ) (3.12)
The flow rate of cooling water was controlled by a design specification to meet
cooling demand. Power duty for the tower was calculated by another equation [69]:
( ) (3.13)
3.2.2 Advanced-case Biorefinery Concept Overview
The Advanced-case biorefinery concept was created to improve the plant thermal
integration by eliminating the wet-scrubbing tar removal and LO-CAT® sulfur
removal processes. The technology envisioned for this plant concept is
commensurate with the beyond 2020 timeframe.
Figure 3.15 shows a high level process flow diagram for the Advanced-case plant
concept. A detailed process flow sheet,
Figure 3.16, and a detailed stream composition table, Table 3.13, are provided below
and are referenced throughout the process description.
Oxygen
H2S Removal Water Gas Shift Separation
Power Island
Biomass
Preparation
Pressurized
Gasification
Gas Cooling &
Cleanup
Air Separation
Unit
Process
Electricity
Small Export of
Electricity
Unconverted
Synthesis Gas
Biomass
Air
Compression Hydrogen
· Dolomite Guard
Bed
· Ni-Tar Cracker
· Catalytic
Candle Filter
· HGDS
· ZnO Bed
· HTS
· LTS
Figure 3.15 Advanced Case Process Overview
The majority of the Advanced-case design concept is identical to the Baseline-
case with the exception of differences in the gas cleanup portion of the plant. Only
differences between the Baseline and Advanced-cases are discussed in the following
subsections as all other processes and performance specifications are identical.
71
PSA
POx Tar
Cracking
Guard
Bed
Tar
Cracker
HPIPLPCD
Steam
Boiler
Condenser
Make-up
H2O
ASU
HTS
LTS
Purge Syngas
Compressor
H2
H2
Compressor
Compressor
Compressor
O2
N2
Vent
Exhaust
Biomass
Raw
Syngas
Ash
Gas CleanupGasifier
Air Separation Unit
H2 Purification
Power Generation
1
ZnO
Bed
Combustion
Air
Water Gas Shift
26
Air
25
Hot Gas
Desulfurization
Catalytic
Candle Filter
Syngas
Coolers
1&2 Syngas
Cooler 3
Air
7
6
21 20
3
Purge Gas
Combustor
Compressor
19
AC
4 5
8
9
18
14
16
24
23
22
N2Vent
2
27
T (°C) P(bar) m(kg/s)
1 25 1.0 23.1
2 1030 22.0 50.4
3 1028 21.7 50.4
4 693 21.0 50.4
5 500 21.0 50.4
6 500 20.0 50.4
7 375 20.0 50.4
8 375 19.0 50.4
9 459 19.0 50.4
10 200 18.0 50.4
11 266 18.0 50.4
12 40 17.0 41.9
13 44 16.0 44.1
14 42 15.0 3.8
15 51 16.0 2.1
16 60 70.3 1.7
17 43 2.0 40.3
18 18 1.1 40.3
19 890 1.1 105.8
20 334 25.0 16.5
21 95 1.0 105.8
22 10 1.5 7.4
23 10 1.5 1.6
24 254 25.0 5.8
25 254 25.0 1.6
26 281 25.0 3.5
27 25 1.0 36.9
28 25 1.0 65.5
29 35 1.15 65.5
30 -17 1.05 26.0
Condensate
Syngas
Cooler 5
10
11
12
13
Syngas
Cooler 4
Syngas
Cooler 6
Cooling
Tower HX
15
17
29
28
30
N2Vent
N2
Expander
Purge Syngas
Expander
Combustion
Air Blower
Figure 3.16 Detailed Advanced –Case Process Flow sheet
Table 3.13 Syngas Composition
Stream #
Mole Fraction 2 3 4 5 6 8 9 11 14 17
N2 0.055 0.055 0.049 0.049 0.049 0.049 0.049 0.049 0.000 0.097
H2 0.148 0.149 0.307 0.307 0.307 0.307 0.389 0.448 1.000 0.255
O2 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
CO 0.110 0.111 0.158 0.158 0.158 0.158 0.077 0.018 0.000 0.035
CO2 0.175 0.175 0.154 0.154 0.154 0.154 0.235 0.294 0.000 0.587
H2O 0.436 0.435 0.323 0.323 0.323 0.323 0.242 0.182 0.000 0.007
CH4 0.069 0.069 0.006 0.006 0.006 0.006 0.006 0.006 0.000 0.012
C2H4 0.002 0.002 1.5E-04 1.5E-04 1.5E-04 1.5E-04 1.5E-04 1.5E-04 0.000 2.9E-04
C2H6 0.002 0.002 1.6E-04 1.6E-04 1.6E-04 1.6E-04 1.6E-04 1.6E-04 0.000 3.2E-04
NH3 1.3E-04 6.2E-05 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
H2S 9.4E-05 9.4E-05 8.3E-05 8.3E-05 2.0E-05 9.0E-07 9.0E-07 9.0E-07 0.000 1.8E-06
Ar 0.003 0.003 0.003 0.003 0.003 0.003 0.003 0.003 0.000 0.006
NO 6.81-06 6.81-06 6.00-06 6.00-06 6.0E-06 6.0E-06 6.0E-06 6.0E-06 0.000 1.2E-05
C14H10 (Tar) 9.1E-05 3.2E-05 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
Total Flow (kmol/hr)
8300 8310 9433 9433 9433 9433 9433 9433 6834 4728
Total Flow (kg/hr)
181305 181305 181305 181305 181295 181293 181293 181293 13776.3 144825
Temperature (°C)
1030 1028 693 500 500 375 459 266 42 43
Pressure (bar)
22.0 21.7 21.0 20.6 19.9 19.2 18.9 17.9 15.3 2.0
72
3.2.2.1 Tar Decomposition and Removal
The first two steps in the syngas tar reduction process (guard bed and tar
reformer) are identical to the Baseline-case. The wet scrubbing step in the Baseline
process is essential because it is the only commercially available method of
removing remaining particulates and tars from the gas stream. The problem with
the wet scrubbing step is that it makes the process thermodynamically inefficient.
The gas must be first cooled down to the operating conditions of the wet scrubber
(60°C) and then it must be reheated downstream for the final sulfur removal step.
To avoid this problem, the wet scrubbing step was replaced in the Advanced-case
with a catalytic candle filter. The details of this technology are found in the
technology overview section of this report. The catalytic candle filter operates at
temperatures much higher than the wet scrubber (700°C vs. 165°C). According to
published reports, these filters have shown excellent tar, ammonia, and particulate
removal rates [43, 70]. The catalytic candle filter is modeled in ASPEN Plus® using
another RSTOIC reactor with the tar/ammonia reforming reactions extent of
reaction set according to values found in the literature. Advanced-case reforming
efficiencies can be seen in Table 3.14. The final tar removal performance is the same
as the Baseline-case performance (see Table 3.10).
Table 3.14 Catalytic Candle Filter Performance
Conversion/Removal Efficiency
Tar ≈100%
Ammonia ≈100%
Particulates ≈100%
3.2.2.2 Sulfur Removal
The other major difference between the Baseline and Advanced-cases is the
utilization of a warm gas transport desulfurization unit in place of the LO-CAT®
system for sulfur removal. This was done to improve the thermal integration of the
system. The LO-CAT® process operates at approximately 60°C which would require
significant cooling and reheating prior to the gas passing through the zinc oxide bed.
The hot gas desulfurizer operates between 350°C and 650°C which allows for the
gas to remain at elevated temperatures throughout the process, eliminating the
73
need for additional downstream heating operations. Process specifics were detailed
in the technology review section of this thesis. The WGDS is capable of removing
hydrogen sulfide down to 20ppmv, which is sufficiently low so that a final polishing
bed of ZnO can be used downstream to economically remove any remaining
hydrogen sulfide to reach a final purity of < 1 ppmv [14]. The final syngas purity is
the same for the Advanced-case as for the Baseline-case (see Table 3.11).
This process is modeled in ASPEN Plus® using two RSTOIC reactors, Figure 3.17.
The first acts as an absorbing column and the second as a regenerating column.
17
16
18
19
21
2022
WGDS-1
ZNOSEP
WGDS-2
Figure 3.17 WGDS Process in ASPEN Plus®
Two streams enter the first reactor (WGDS-1), Sulfur-rich syngas (16) and a
solid stream containing regenerated zinc oxide sorbent (17). The sulfur reacts with
the zinc oxide via the overall reaction shown in equation 11, the extent of the
reaction is set to 100% and the flow of zinc oxide in (17) is set by a design
specification (ZNOFLO). The amount of zinc oxide fed into the reactor is varied until
the outlet stream concentration is ≤ 20 ppmv for hydrogen sulfide. While outlet
concentrations of less than 1 ppmv have been reported [53], concentrations of 10–
20 ppmv are more likely [54] and so are used as the basis for this study.
After leaving the first reactor the solid and gas portions of the outlet stream (18)
are separated in a simple separation unit operation (ZNOSEP). The clean syngas
(19) is then exhausted out of the top of the column and continues on to downstream
processes. The solids, primarily zinc sulfide, are then fed into the second RSTOIC
reactor (WGDS-2) which simulates the regenerating tower. In this reactor the zinc
sulfide stream (20) and an air stream (21) are combined and react according to
equation 12. The air flow of (21) is set by another design specification (ZNOREGEN)
74
and is varied until all the zinc sulfide is regenerated back to zinc oxide and the outlet
temperature of (WGDS-2) matches values found in literature. The reformed zinc
oxide stream would then be recycled back into the first reactor (WGDS-1)
3.3 System Model Benchmarking
The mass and energy balances for the two biorefinery concepts are compared
with other studies from the literature. Figure 3.18 shows the overall, fuel, and
electrical efficiency of the two cases developed in this research as well as those of
the comparison cases from literature and Table 3.15 shows a comparison of key
parameters. The plant performance benchmarking data can be found in Table 3.16
and Table 3.17.
Figure 3.18 Plant Efficiency Comparison
As shown in Table 3.15, when compared to other biorefinery models from
literature that co-produce hydrogen and power, the CSM cases have higher
electricity output and the plant power usage is comparable to the median values.
This results in higher than average net electrical output.
59% 59% 63%
67% 62%
54%
4% 7%
4%
63% 66% 68%
59% 58% 52%
0%
10%
20%
30%
40%
50%
60%
70%
80%fuel efficiency electrical efficiency plant efficiency
75
Table 3.15 System Performance Comparison Table
Baseline +/- Advance +/-
Hydrogen Output
(tonne/hr/MWb)
High 0.0169
0.0147 -0.0006 0.0147 -0.0006 Low 0.0138
Median 0.0153
Electricity Output
(MW/MWb)
High 0.1143
0.0849 -0.0076 0.1143 0.0218 Low 0.0548
Median 0.0925
Plant Power Use
(MWe/MWb)
High 0.0795
0.0531 -0.00265 0.0533 -0.00245 Low 0.0469
Median 0.05575
Net Electricity
(MWe/MWb)
High 0.0711
0.0417 0.03175 0.0711 0.06115 Low -0.0708
Median 0.00995
Plant Efficiency
High 0.6762
0.0147 -0.5935 0.0147 -0.5935 Low 0.5218
Median 0.6082
This is to be expected given the optimization of the thermal integration to
maximize heat recovery and steam generation and the use of thermodynamically
preferable technologies. Even with the increase in electricity production the CSM
models have slightly lower overall plant efficiencies than the top performing model.
This is due to lower fuel production efficiencies resulting from dilute syngas
entering the PSA unit. The Nth generation plant [71] and the Williams-Larson plant
[13] use a Rectisol® process to remove carbon dioxide prior to the hydrogen
purification step. The Nth generation plant also uses the carbon dioxide removed by
the Rectisol® process as the pressurizing agent rather than nitrogen from an ASU.
By avoiding nitrogen dilution and removing carbon dioxide, the partial pressure of
hydrogen in the syngas is significantly elevated over cases where there is no carbon
dioxide removal. This dramatically improves the performance of the PSA unit and
eliminates the need for a hydrogen recycle stream. Pre-PSA carbon dioxide
removal increases the partial pressure of hydrogen in the syngas to over 80% and
enables the PSA unit to recover approximately 95% of the available hydrogen.
In the models presented here there are no readily available carbon dioxide
streams so a nitrogen stream from the air separation unit must be used as the
76
pressurizing agent. This significantly dilutes the syngas and with no cost-effective
method to remove the nitrogen the partial pressure of the hydrogen in the gas
stream is low and this negatively affects the efficiency of the PSA unit. The baseline
and advanced-case models recover approximately 72% of the available hydrogen.
This is the most significant difference between the CSM and literature models and is
responsible for the difference in overall plant efficiency. As shown in Table 3.17, the
Nth generation model produces 0.63 MWH2/MWbiomass whereas the Baseline and
Advanced-cases produce 0.58 MWH2/MWbiomass. The vast majority of the plant
energy export resides in the hydrogen export so small improvements in hydrogen
production/recovery translate to large gains in overall plant efficiency.
A basic simulation of the CSM models using a carbon dioxide pressurization and
removal strategy showed potential improvements in the advanced-case plant fuel
efficiency of up to 10 percentage points. This jump in plant efficiency is the result of
an improvement in PSA hydrogen recovery of 5 percentage points. If implemented,
this strategy would also require additional unit operations which would result in an
increase of capital cost of approximately $35 million (10%). Even with this
additional cost the improved plant efficiency could provide the motivation for
employing carbon capture technology even without carbon legislation. If carbon
legislation were implemented this would provide a very strong case for including
such technology in the type of biorefineries presented in this study.
However, this basic simulation was simple and did not take into account any
impacts that using carbon dioxide as a pressurizing agent might have on processes
upstream of the acid-gas removal. Studies suggest that since carbon dioxide is
already present in the gasifier, small increases in carbon dioxide concentration
would not likely have a detrimental effect and may even promote the dry reforming
reactions resulting in lower tar yields [36]. Also the simulation did not take into
account any parasitic power requirements that are sure to accompany inclusion of
an energy intensive process such as carbon capture. Additional detailed studies are
required before the true impact of this strategy can be adequately quantified.
77
Table 3.16 Mass and Energy Balance
CSM-
Baseline
CSM-
Advanced
Larson-Nth
Generation
Williams-
Larson
Corradetti-
Desideri
NREL-
Current
Gasifier Type IGT IGT IGT IGT BCL BCL
Feedstock
Wood-
Poplar (ar)
Wood-Poplar (ar)
Switchgrass (ar)
CH1.52O0.68 (daf)
CH1.54O0.67 (daf)
Wood-
Poplar (dry)
Feed rate (tonne/hr) 83.33 83.33 236.3 68.75 54.1 83.33
Biomass LHV (MJ/kg) 16.31 16.31 13.5 -- -- 18.75
Biomass HHV (MJ/kg) 17.71 17.71 15 19.28 19.46 20.17
Energy Inputs (MW)
Biomass Energy Input HHV 409.98 409.98 984.38 368.19 292.44 466.85
Plant Power Output (MW)
Hydrogen Output (tonne/hr) 6.01 6.01 15.84 6.23 4.63 6.44
Hydrogen Energy Output
(LHV) 203.84 203.84 531.96 209.14 155.56 216.23
Hydrogen Energy Output
(HHV) 240.84 240.84 624.36 245.46 182.58 253.79
Electricity Power Output
Steam Cycle 34.8 46.87 98.56 -- -- 25.6
Nitrogen and Purge Expanders 4.1 4.1 -- 3.19 -- --
Gross Output LHV 242.74 254.81 630.52 209.14 154.35 241.83
Gross Output HHV 279.74 291.81 722.92 245.46 182.55 279.39
Internal Power Use (MW)
Air Separation Unit 9.3 9.3 20.68 9.87
Oxygen Compressor 2.3 2.3 7.26
Nitrogen Compressor 1.4 1.4
Biomass Prep 0.3 0.3 0.66
Lock-hopper 0.3 0.3 0.52 1.15
LO-CAT/HGDS Comp/CO2
removal 0.01 0.02 5.2
PSA Purge Gas Compressor 0.28 0.28 7.27 10.5 8.6
Hydrogen Compressor 3.93 3.93 9.74
Cooling Tower (Fan, Pumps) 2.87 2.87
Combustion Air Compressor 1 1.02
Other Auxiliary Power 0.1 0.12 5.99 7.74 5.11
Total Plant Power Use (MW) 21.79 21.84 57.32 29.26 13.71 35.8
Net Power Production (MW)
Net Electric Power Out 17.11 29.13 41.24 -26.07 -13.71 -10.2
Net Power Output HHV 257.95 269.97 665.6 216.2 168.84 243.59
Fuel Efficiency HHV 58.74% 58.74% 63.43% 66.67% 62.43% 54.36%
Electrical Efficiency HHV 4.17% 7.11% 4.19%
Plant Efficiency HHV 62.92% 65.85% 67.62% 58.72% 57.73% 52.18%
78
Table 3.17 Normalized Mass and Energy Balance
CSM-
Baseline
CSM-
Advanced
Larson-Nth
Generation
Williams-
Larson
Corradetti-
Desideri
NREL-
Current
Gasifier Type IGT IGT IGT IGT BCL BCL
Feedstock Wood-
Poplar (ar) Wood-
Poplar (ar) Switchgrass
(ar) CH1.52O0.68
(daf) CH1.54O0.67
(daf)
Wood-
Poplar (dry)
Feed rate (tonne/hr) 83.33 83.33 236.3 68.75 54.1 83.33
Biomass LHV (MJ/kgb) 16.31 16.31 13.5 -- -- 18.75
Biomass HHV (MJ/kgb) 17.71 17.71 15 19.28 19.46 20.17
Energy Inputs (MW)
Biomass Energy Input HHV 409.98 409.98 984.38 368.19 292.44 466.85
Plant Power Output (MW/MWb)
Hydrogen Output
(tonne/hr/MWb) 0.0147 0.0147 0.0161 0.0169 0.0158 0.0138
Hydrogen Energy Output LHV 0.4972 0.4972 0.5404 0.568 0.5319 0.4632
Hydrogen Energy Output HHV 0.5874 0.5874 0.6343 0.6667 0.6243 0.5436
Electricity Power Output
Steam Cycle 0.0849 0.1143 0.1001
0.0548
Nitrogen and Purge
Expanders 0.01 0.01 0.0087
Gross Output LHV 0.5921 0.6215 0.6405 0.568 0.5278 0.518
Gross Output HHV 0.6823 0.7118 0.7344 0.6667 0.6242 0.5985
Internal Power Use (MW/MWb)
Air Separation Unit 0.0227 0.0227 0.021 0.0268
Oxygen Compressor 0.0056 0.0056 0.0074
Nitrogen Compressor 0.0034 0.0034
Biomass Prep 0.0007 0.0007 0.0007
Lock-hopper 0.0007 0.0007 0.0005 0.0031
LO-CAT/HGDS Comp/CO2 removal
0 0 0.0053
PSA Purge Gas Compressor 0.0007 0.0007 0.0074 0.0285 0.0294
Hydrogen Compressor 0.0096 0.0096 0.0099
Cooling Tower (Fan, Pumps) 0.007 0.007
Combustion Air Compressor 0.0024 0.0025
Other Auxiliary Power 0.0002 0.0003 0.0061 0.021 0.0175
Total Plant Power Use
(MW/MWb) 0.0531 0.0533 0.0582 0.0795 0.0469 0.0767
Net Power Production
(MW/MWb)
Net Electric Power Out 0.0417 0.0711 0.0419 -0.0708 -0.0469 -0.0218
Net Power Output HHV 0.6292 0.6585 0.6762 0.5872 0.5773 0.5218
Fuel Efficiency HHV 58.74% 58.74% 63.43% 66.67% 62.43% 54.36%
Electrical Efficiency HHV 4.17% 7.11% 4.19%
Plant Efficiency HHV 62.92% 65.85% 67.62% 58.72% 57.73% 52.18%
79
The other cases, Corradetti-Desideri, Williams-Larson, and NREL Current, are
provided primarily to give a comparison to other currently employed biorefinery
models and their potential efficiencies. The Williams-Larson model is an IGT
directly-heated gasifier operating at 34.5 bar and is optimized for hydrogen
production with no power export. Both the Corradetti-Desideri and the NREL
Current cases are indirectly-heated atmospheric gasifiers (Battelle Columbus
Laboratory) and so are not directly comparable to the IGT pressurized oxygen
blown gasifiers, however, they do provide another comparison to the available plant
concepts.
3.4 Technology Readiness Level
To aid in understanding the present status of technologies, a rubric was
developed to quantify the “readiness” of a technology. As each technology was
reviewed it was assigned a Technology Readiness Level (TRL) according to the
rubric. The TRL designations used are based on the Department of Defense (DOD)
TRL scale of 1 through 9, with one being a basic concept with no experimental
validation and nine being a mature, commercially deployable technology. Figure
3.19 shows the TRL designations along with descriptions from the DOD definitions
modified for application to gasification-based biorefinery technology. Each
technology deployed in the biorefinery concepts was evaluated according to the
rubric shown in Figure 3.19 and the results are shown in Table 3.18.
The purpose of the Baseline-case is to provide a realistic model for a near-term
biorefinery that could potentially be constructed within 5 years. With the exception
of the gasifier, the Baseline-case biorefinery has a high overall TRL. While the
gasifier does not meet the near-term goal it is based on the IGT pilot scale plant and
potentially, with enough capital and research investment, could be scaled to match
the plant size and performance objectives established in this study. As was
mentioned previously, the Advanced-case biorefinery concept provides several
advantages over the Baseline-case but utilizes technologies in the areas of tar
cleanup and hydrogen sulfide removal that have significantly lower TRLs. These low
TRLs for gas cleanup combined with the non-commercial state of the IGT gasifier
80
means that a refinery built on the Advanced-case concept model would be 10-20
years in the future.
1
2
3
4
5
6
7
8
9
Basic principles/properties of technology observed and reported. Scientific results not yet translated into application.
Concept for application of technology developed. Analytical/paper studies completed.
Laboratory studies to physically validate analytical predictions of individual elements of the technology completed.
Component and/or breadboard validation of system in laboratory environment.
Component and/or breadboard validation of system in simulated operating environment.
Prototype system tested in a relevant environment.
Pilot plant demonstration (sub-scale) under actual operational conditions.
Numerous demonstrations of technology that is currently being used under similar operating conditions. Minor testing
needed to verify proper operation under design/off design conditions.
Commercial technology depolyed with warrenty
TRL Description of Technology Readiness Level (TRL)
Figure 3.19 Technology Readiness Rubric
Table 3.18 Technology Readiness Levels
Process Technologies Baseline Case Advanced Case
IGT Gasifier Pressurized Biomass Feeding 6 6
High Pressure Operation 7 7
Fluidized Bed 7 7
Steam-O2 Blown 7 7
Secondary O2 Injection 4 4
Gas Cooling & Cleanup Dolomite Guard Bed 4 4
Tar Cracker (Ni catalyst) 5 5
Wet Scrub/Catalytic Candle Filter 8 4
H2S Removal LO-CAT/Hot Gas Desulfurization 9 5
ZnO Polishing Bed 9 9
Water Gas Shift Commercial HT WGS 9 9
Commercial LT WGS 9 9
Separation Pressure Swing Adsorption (PSA) 9 9
81
The technology readiness level for the gasifier concept is particularly
challenging to accurately state since it is not based on a single technology or an
existing reactor. Several of the technologies used in the concept have been proven
at the pilot-plant level while others like secondary oxygen injection have only been
demonstrated in the laboratory. The GTI PRU unit demonstrated high-pressure
operation, successful control of the fluidized bed and operated on a mixture of
steam and oxygen [27]. The PRU unit successfully fed pressurized wood chips into
the gasifier at pressures up to 24 bar [27]. However, successfully feeding
pressurized wood into a reactor has not been demonstrated with the higher
efficiency dual-lockhopper system assumed in this study. The other technologies
such as feeding other biomass species, particularly fibrous ones, have not been
successfully done at a pilot scale. Finally, the effects of secondary oxygen injection or
POx in the gasifier freeboard have only been demonstrated at the laboratory scale
for biomass gasification.
82
CHAPTER 4
THERMODYNAMIC ANALYSIS [72]
Approximately 83.3 tonnes/hr of biomass are supplied to the baseline and
advanced biorefinery concepts or 410 MW of energy. About 240 MW of hydrogen
and 39 MW of electric power are produced in the Baseline-case concept. In contrast,
the Advanced-case produces the same amount of hydrogen (240 MW) but it also
generates about 51 MW (31%) more electric power. This is primarily due to the
improved thermal integration made possible by elimination of the wet scrubbing tar
removal and the LO-CAT® sulfur removal steps. Figure 4.1 and Figure 4.2 show the
thermal profiles for the Baseline- and Advanced-case designs respectively.
Figure 4.1 Baseline-Case Thermal Profile
Figure 4.2 Advanced-Case Thermal Profile
0
200
400
600
800
1000
1200
Gasifier Dolomite Bed Tar Cracker Wet Scrub LO-CAT ZnO Bed HTS LTS
Tem
pera
ture (°C
)
0
200
400
600
800
1000
1200
Gasifier Dolomite Bed Tar Cracker CCF HGDS ZnO HTS LTS
Tem
peratu
re (°C
)
83
Both cases have approximately the same in-plant power requirements of
approximately 22 MW with nearly 60% of that total derived from the air-separation
unit duty and about 18% coming from the multi-staged hydrogen compressor. The
Baseline-case has fuel efficiency of 58.7%, an electrical efficiency of 4.2%, and an
overall plant efficiency of 62.9% (HHV) [58.5% (LHV)]. The Advanced-case fuel
efficiency is identical but the major improvement is seen in the electrical efficiency
of 7.1%. This increase leads to an overall plant efficiency of 65.8% (HHV) [60.1%
(LHV)].
4.1 Second Law Analysis Overview
While mass-energy performance assessments are helpful, a second law
(exergetic) analysis is more revealing and quantitatively insightful in understanding
the location and magnitude of process inefficiencies within the plant. So to provide
this understanding an exergy analysis is performed for Baseline and Advanced-cases
and an examination of each plant concept is carried out in terms of exergy
destructions and efficiencies within their respective subsystems.
Thermodynamic property evaluation for exergy of a substance largely follows
the methods of Moran [73, 74] and Szargut [75]. The reference environment chosen
here is that of Szargut [76] or as also given by Moran and Shapiro [77] as ‘Model II.’
4.1.1 Physical Exergy
Physical (thermomechanical) exergy is a measure of a non-reacting substance’s
departure from thermal and mechanical (i.e., pressure) equilibrium with a reference
environment. The specific physical exergy is expressed as:
(4.1)
Where is the physical exergy of the stream, is the relative enthalpy as
defined by Equation 4.2, is the reference temperature, and is the relative
entropy as defined by Equation 4.3. The and
are the enthalpy and
entropy at the reference state.
84
(4.2)
(4.3)
When considering an ideal mixture, the exergy of the mixture, , is the sum
of the partial physical exergy of the constituents. It is expressed by:
∑ ( (
))
(4.4)
Where is the mole fraction of the ith component in the mixture, and enthalpy,
h and entropy, s are evaluated using property data from ASPEN Plus®. For the solid
state carbon and sulfur, the following approximations for and were used:
(4.5)
⁄ (4.6)
4.1.2 Chemical Exergy
The chemical exergy of a substance is calculated according to,
∑( )
(4.7)
The first term, , is the chemical exergy of the ith pure component and the
second term, , is a correction factor that accounts for the change in exergy
of the pure component due to its presence in the mixture. The chemical exergy of
the majority of the pure components was taken from Appendix III of Szargut [75].
The total exergy of the biomass feedstock was estimated from[77],
( ⁄ ⁄ ⁄ )
(4.8)
where is the lower heating value of the dry biomass, ⁄ is the hydrogen
to carbon ratio (mass), is the oxygen to carbon ratio (mass), and is the
nitrogen to carbon ratio (mass), and is the mass fraction of sulfur. The total exergy
of the streams is the sum of the physical and chemical exergy of the mixture.
85
(4.9)
4.1.3 Exergetic Efficiency
Efficiency definitions are primarily a matter of consensus; i.e., an agreement
over the purpose of the component or system is made such that the appropriate
terms in the numerator and denominator can be entered. In the analysis presented
here, the biorefinery was subdivided into seven primary subsystems:
1. Gasifier
2. Tar Cleanup
3. Hydrogen Sulfide Cleanup
4. Water Gas Shift (WGS)
5. Hydrogen Purification and Compression (PSA)
6. Steam and Power Generation
7. Air Separation (ASU)
Within each subsystem, the exergy inputs and outputs were calculated using the
approach described above and from state point information provided by the ASPEN
Plus® models. The second law efficiency was calculated according to the
following:
∑
∑
(4.10)
4.2 Baseline-Case Exergy Analysis
An exergy and energy flow diagram for the Baseline-case is given in Figure 4.3
where energy flows are shown parenthetically on a HHV-basis (MW) and exergy
destructions within each subsystem are shown within brackets as a negative
quantity. Overall, 467 MW of exergy in the form of biomass enter the plant and 205
MW of hydrogen exergy and 18.4 MW of net electrical energy are produced, yielding
an overall exergetic (2nd Law) efficiency of 47.8%. The largest exergy destructions
are found within the gasifier (117 MW), steam and power generation subsystem
86
(~67 MW), pressure swing adsorption unit (~10.6 MW), and the water-gas shift
reactors (~6 MW). Table 4.1 also provides an exergy accounting summary.
Biomass
Electricity
Gasifier
[-117]
Tar Cleanup
[-2.15]
H2S Cleanup
[-2.4]
WGS
[-5.7]
PSA
[-10.6]
27.8 (50)
1.4 (2.6)
4.5 (15.4)
333.3 (365)
340.3 (383.5)
338.4 (404.8)
467 (410)
Steam-
Power
Generation
[-67]
2.9 (1)
1.2 (0.5)
18.4 (50.6)
1 (0.2)
116 (123)
O2
N2
Ash
Gasifier
Steam
205 (240)
H2
Purge
34.8
Exhaust
13.6 (23)
1 (1.1)
7.2 (43)
Sulfur
Waste
Water
15.7 (43.5)
Steam
4.6
Electricity
0.8 (4.1)
Heat
Heat
Heat
Heat
1.2
(42)
H2O to
Cooling
Tower
10.4
(19.6)
15.7 (43.5)
WGS
Steam
5 (25) Heat to Air
Cooler
370.4 (458)
ASU
[-7.7]
0 (0)
12.6
0.8 (-1.2)
Air
Net
Electricity
N2 Vent
Syngas
0.2 (3)Heat to
Cooling Tower
0.03 (0.5)
Condensate
0 (0)H2O
1
Electricity
1.8
Electricity
Figure 4.3. Baseline-Case Exergy/Energy Flow Diagram
4.2.1 Gasifier
As the gasifier represents the largest single source of exergy destructions within
the plant (25% of the total exergy entering in the form of biomass or 55% of the
total exergy destroyed and lost within the plant), a more detailed analysis of the
losses within it was made. Figure 4.4 shows an exergy/energy flow diagram that
summarizes losses within the directly-heated, fluidized-bed gasifier unit. About 117
MW of exergy are destroyed and/or lost within the gasifier. Heat loss from the
gasifier is estimated at a 100°C surface temperature and amounts to only ~0.8 MW
of exergy. The efficiency of the gasifier is estimated by,
87
%7.754.181.19.2467
4.370
in
syngas
II
This value is slightly lower than the gasifier cold-gas efficiency of 77.8%. The
exergy of the hydrogen and carbon monoxide make up 37% of the total availability
in the syngas, at 19.7% and 17.3%, respectively. Of the 103 MW of exergy destroyed
within the gasifier, only about 2.2 MW are lost within the gasifier due to the mixing
of the oxygen and steam in the fluidizing stream. Gasifier losses are dominated by
the irreversibility associated with the uncontrolled gasification reactions and heat
transfer/mixing losses between reactant and product streams. Additionally, tar
cracking in the freeboard consumes 13.5 MW (11.4% of the total destroyed/lost)
and particulate/ash removal only 0.3 MW.
Biomass
Raw
Syngas
Solids
Recycle
Secondary
O2 Injection
Oxygen
Steam
Inert
Gas
Syngas
Ash
Heat0.82
(4.09)
467
(410)
1.15
(0.5)
2.2
(0.72)
18.4
(50.6)
1 (0.2)
0 (0)
0.7
(0.2)
371.7
(457.9) 370.4
(457.7)
-103.4
MW
385.3 (461.8)
POx Tar
Cracking
-13.5 MW
-0.3 MW
Total
Exergy Destruction
[-117 MW]
1
25
6
9
4
3
7 8
T(°C) P(bar) m (kg/s)
1 25 1 23.1
2 281 25 3.5
3 334 25 16.5
4 275 25 5.8
5 860 24 48.9
6 275 25 1.6
7 1030 23 50.5
8 1030 22 50.4
9 1030 22 0.1
Figure 4.4. Gasifier Exergy/Energy Flow Detail
88
4.2.2 Tar Cleanup
The tar in the syngas leaving the gasifier is converted to hydrogen and carbon
monoxide in the reactors and the syngas is then quenched from 693°C to 161°C
prior to the wet scrubbing operation. The thermal energy from the quenching
process is recovered and transferred to the steam cycle via a heat exchanger
network. The overall efficiency of the tar cleanup process (from station (2) in
Figure 3.4 to downstream of the wet scrubber) is given by,
%904.370
3.333
,
,
insyngas
outsyngas
II
The tar compounds only compromise 1.45 MW of the 370 MW of exergy in the
syngas stream. If the exergy associated with the thermal energy transfer to the
steam cycle is included in the numerator, the second law efficiency improves to
97.5%. The exergy destruction is largely due to the chemical transformations of tar
within the reactors and the direct contact mixing from cooling water injection in the
quench process. The exergy destroyed due to the heat transfer is accounted for in
the steam-power production block exergy analysis.
4.2.3 Hydrogen Sulfide Cleanup
Desulfurization of the syngas requires 10.4 MW of exergy in the form of process
heat for reheat of the syngas stream back to 375°C prior to the ZnO polishing beds.
The output of the LO-CAT process is elemental sulfur suitable for export. While the
captured sulfur has exergetic value, it is viewed as a waste stream in this process.
The efficiency of the hydrogen sulfide cleanup process is then given by,
%994.103.333
3.340
,
,
heatinsyngas
outsyngas
II
The majority of the exergy destroyed in this subsystem occurs in the reheater
for the zinc oxide polishing bed.
89
4.2.4 Water Gas Shift
Downstream of the desulfurization process, the carbon monoxide in the syngas
is shifted to carbon dioxide in the water-gas shift reactor train to increase hydrogen
content. This is to ensure the maximum amount of hydrogen is available in the
syngas stream for recovery in the PSA unit. The efficiency for the WGS process is
given by
%957.153.340
5.338
,
,
steaminsyngas
outsyngas
II
4.2.5 Hydrogen Purification
After two-stages of water-gas shift, the hydrogen content of the syngas is about
55% on a molar basis. For efficient recovery of hydrogen in the PSA unit, the molar
fraction should be greater than 70% and therefore, a fraction of the product
hydrogen is recycled to the inlet. While recycle is employed, the hydrogen mole
fraction is only just above the required level which leads to lower recovery
efficiency. This also contributes to the exergy destruction in this process. An
exergy/energy flow diagram is given in Figure 4.5.
PSA
ηII = 59.7%
(-10.6)
338.5
(404.8)
1.8
205 (240)Syngas
Heat to Air Cooler
H2
116 (123)
Purge
4.6
Compressor
Electricity
0.2 (3)
Heat to Cooling Tower
4.5 (15.4)
Heat to HRSG
0.03 (0.5)
Condensate
5 (24)
Purge Gas Expander
Figure 4.5. Exergy/Energy Flow Diagram of PSA Process
The exergy of the purge stream is recaptured in the steam-power production
process but is not considered in the second-law efficiency for the hydrogen
purification process. The efficiency for the hydrogen purification process is given
by,
90
%7.596.45.338
205
,
2
compinsyngas
H
II
Inclusion of the exergy of the purge gas and the purge gas expander electricity
increases the second-law efficiency to,
%1.946.45.338
8.1116205
,
2
compinsyngas
yelectricitpurgeH
II
4.2.6 Steam-Power Production
The purge gas and the process heat from the system are sent to the steam-
power production subsystem. The purge gas is burned in a combustor and heat is
recovered from the exhaust via a heat exchanger network. An exergy and energy
flow diagram of the subsystem is given in Figure 4.6 and includes the purge gas
combustor.
H2O
Steam-Power
Generation
ηII(Power) = 33.7%ηII(Power+Steam) = 64.8%
(-22.7)
0 (0)
1.2 (41)
H2O to
Cooling
Tower
116 (123)
Purge 33.7 (68)
Heat
34.8
Electricity
34.1 (94.1)
Steam
13.6 (23.2)
ExhaustCombustor
ηII = 60.7%
(-44.3)
0(0)
72.7(124)
Exhaust
Air
1
Power
Figure 4.6. Exergy/Energy Flow Diagram for Steam-Power Generation
The exhaust is vented to the atmosphere at 90°C and carries with it about 13.6
MW of exergy. Process steam in the plant is required for the gasifier and WGS
reactors. Approximately 34 MW of steam are extracted from the intermediate
pressure (25 bar) turbine in the plant. The efficiency of the steam-power generation
process is given by,
%9.687.337.72
1.348.34
in
steamyElectricit
II
91
Within the steam-power generation subsystem the purge gas combustor is
responsible for 44 MW (or ~66%) of the total exergy destroyed. About 6.5 MW of
that destruction is associated with irreversible mixing of purge gas and combustion
air. Over 92% of the destruction due to mixing is diffusional and with the remainder
due to heat transfer between reactants. The bulk of the exergy destroyed (44.3 MW)
is due to combustion. The reminder of the destruction (22.7 MW) is attributed to
the heat transfer within the heat exchangers in the heat exchanger network. If the
second-law efficiency is examined as only a function of exportable power, the
efficiency becomes,
%7.327.337.72
8.34
in
yElectricit
II
4.2.7 O2 Production and Supply
The subsystem related to oxygen production and supply consists of the
cryogenic air separation unit and the oxygen and nitrogen compressors for supply
to the gasifier. Only a small fraction of the produced N2 in the ASU is required by the
lock-hopper feeding system thus, any N2 not required for pressurization is expanded
and then vented to the atmosphere prior to compression. An exergy/energy flow
diagram is given in Figure 4.7.
O2 Production
&
Supply
ηII = 32.5%
(-7.7)
0 (0)
0.8 (0)
2.9 (1)
Air
N2 (Vent)
O2
12.6
Electricity
1.2 (0.5)
N2
Figure 4.7. Exergy/Energy Flow Diagram for ASU
The efficiency of the O2 production and supply process is given by,
%5.326.12
2.19.222
yelectricit
NO
II
92
A detailed analysis of losses in air separation is not performed here, but
according to Yong et al., the majority of the exergy destroyed in air separation
processes occurs in the heat exchangers (56%) and the distillation towers (23%)
[78]. However, as previously discussed, a conservative assumption of electrical
energy consumption per kg of oxygen produced was employed in the biorefinery.
An optimistic value of 0.260 kWh/kgO2 (rather than 0.35 kWh/kg O2) would increase
the efficiency by 25%, giving a 2nd Law efficiency performance of about 44%.
Table 4.1 Exergy Accounting Summary
Exergy Input Baseline
Case % of Total
Future Case
% of Total
Biomass 467 467
Exergy Output
Electricity 18.4 3.9 30.4 6.5
Hydrogen 205 43.9 205 43.9
Water (Cooling Tower, Condensate, etc.)
13.4 2.9 5.6 1.2
Sulfur 1 0.2 1 0.2
Other (Ash, N2 Vent, Heat, etc.)
16.4 3.5 17.6 3.8
Total 254.2 54.4 259.6 55.6
Exergy Destroyed
Gasifier 117.3 25.1 117.3 25.1
Tar Cleanup 2.2 0.5 0.4 0.1
H2S Cleanup 2.4 0.5 0.1 0
WGS 5.7 1.2 1.1 0.2
PSA 10.6 2.3 10.5 2.2
Steam + Power 67 14.3 70.6 15.1
ASU 7.7 1.6 7.7 1.6
Total 212.8 45.6 207.6 44.4
4.3 Future-Case Exergy Analysis
An exergy flow diagram for the Future-case is given in Figure 4.8 and a table
summary is also provided in Table 4.1. Overall, 467 MW of exergy in the form of
biomass enter the plant and 205 MW of hydrogen exergy and 30.4 MW of net
93
electrical energy are produced, yielding an overall exergetic (2nd Law) efficiency of
50.4%. Compared with the Baseline-case, the largest improvements in subsystem
exergetic efficiency are achieved in the steam-power generation and PSA units. The
gasifier and ASU subsystems are identical to the Baseline case.
Electricity
Gasifier
[-117]
Tar Cleanup
[-0.4]
H2S Cleanup
[-0.1]
WGS
[-1.1]
PSA
[-10.5]
10 (16.3)
12.5
(24.4)
5.5 (9.1)
360 (441.8)
352 (430.1)
338.5 (404.8)
467 (410)
Steam-
Power
Generation
[-70.6]
2.9 (1)
1.2 (0.5)
18.4 (50.6)
1 (0.2)
116 (123)
Biomass
O2
N2
Ash
Gasifier
Steam
205 (240)
H2
Purge
46.8
Exhaust
14.1
(25.4)
1 (1.1)
Sulfur
4.6
Electricity
0.8 (4.1)
Heat
Heat
Heat
Heat
2 (63.2)
H2O to
Cooling
Tower
6.9
(10.7)
3.5 (21) Heat to Air
Cooler
370.4 (458)
ASU
[-7.7]0 (0)
12.6
0.8 (-1.2)
Air
Electricity
N2 Vent
Syngas
0.8 (13.6)Heat to
Cooling Tower
0.05 (0.9)
Condensate
0 (0)H2O
Heat
1
Electricity
1.8
Electricity
Figure 4.8. Advanced-Case Exergy/Energy Flow Diagram
4.3.1 Tar Cleanup
The Future-case tar cleanup reduces the amount of cooling that is required and
shifts the exergy from the process heat stream to the syngas stream. This improves
the ηII from 90% to 97.2%.
94
4.3.2 Hydrogen Sulfide Cleanup
The Future-case hydrogen sulfide process is a significant improvement over the
Baseline-case. The exergy destruction reduces from 2.4 MW to only 0.1 MW and
rather than requiring process heat to reheat the stream, the future-case provides an
additional 6.9 MW of availability as process heat for steam generation. The
efficiency of the hydrogen sulfide cleanup process is 97.8% and despite the decrease
in exergy destruction, would appear to be lower than the Baseline-case. However,
when the availability of the heat transferred to the steam plant is included, the 2nd
Law efficiency improves to 99.7%.
4.3.3 Water Gas Shift
The elimination of the wet scrubbing step preserves more water in the syngas
stream. This eliminates the need for additional steam before the WGS reactor train
and leads to a significant increase steam that is available for power production. The
exergy destruction reduces from 5.7 MW to 1.1 MW. 96.1% exergetic efficiency for
the WGS process is achieved.
4.3.4 Hydrogen Purification
The alterations in the syngas cleanup train results in a higher partial pressure of
hydrogen which slightly improves the efficiency of the PSA unit. The efficiency for
the hydrogen purification process is given by,
%8.596.44.338
205
II
If the purge is included the second law efficiency jumps to,
%5.946.44.338
119205
II
As expected this result is similar to the Baseline-case. The only pertinent
improvement in the process is observed in the additional 1 MW of available energy
delivered to the steam-power generation process.
95
4.3.5 Steam-Power Production
The largest improvements in system efficiency are achieved in the steam
generation and power production subsystem. The use of emerging gas cleanup
technologies enabled process improvements that primarily served to improve the
thermal integration of the system. The improved thermal integration and reduction
in process steam allows for an additional 12 MW of electricity to be produced for
export thereby raising the subsystem 2nd Law efficiency from 35 to 46%. The
increased amount of steam available for power production also increases the
amount of heat transfer in the heating-cooling equipment in the steam-power
system. This which results in a slight increase in exergy destroyed (70.6 MW vs. 67
MW). An exergy/energy flow diagram that summarizes these results is given in
Figure 4.9.
H2O
Steam-Power
Generation
ηII(Power) = 43.5%ηII(Power+Steam) = 60.6%
(-26.3)
0 (0)
2 (63.2)
H2O to
Cooling
Tower
116 (123)
Purge
34.9 (60.5)
Heat
46.8
Electricity
18.4 (63.2)
Steam
14.1 (25.4)
Exhaust
Combustor
ηII = 62.1%
(-44.3)0(0)
72.7
(124)
Exhaust
Air
1
Power
Figure 4.9. Exergy/Energy Flows for Advanced-Case Steam-Power Generation
96
CHAPTER 5
ECONOMIC ANALYSIS
5.1 Capital Cost Estimation
Capital costs estimates were created for both the Baseline and Advanced-cases
presented in this work. Capital cost estimation is based on an extensive literature
review of the technologies utilized in these biorefinery concepts. The capital costs
found during the literature review are typically given as a function of a certain
capacity, So. For these costs to be useful in estimating the costs of the specified plant
concepts they were scaled according to the costing equation, Equation 5.1.
(
) (
)
(5.1)
where C is the capital cost, Co is the reference cost, P is Chemical Engineering
Plant Cost Index (CEPCI) for the desired cost year, Po is the CEPCI of the referenced
year, S is the modeled capacity, So is the reference capacity, S is the model capacity, R
is the scaling factor. The CEPCI data from 1997 to 2008 is given in Table 5.1.
Table 5.1 CEPCI from 1997-2008
Year CEPCI Year CEPCI
1997 386.5 2003 401.7
1998 389.5 2004 444.2
1999 390.6 2005 468.2
2000 394.1 2006 499.6
2001 394.3 2007 525.4
2002 395.6 2008 575.5
The CEPCI is a factor used to estimate annual variability in costs due to a variety
of factors including inflation, steel prices, labor prices, and raw material prices, etc.
The nature of modeling theoretical plant concepts makes accurately estimating
plant capital cost difficult. To minimize the potential error inherent in such
estimation, the sources of costing information used as the reference capital cost was
restricted to references no older than 10 years from the reference year (2008). Even
97
with these restrictions cost information is assumed to have an error of
approximately ⁄ 30%. All plant capital costs are given in the reference year
dollars (2008 USD).
Many capital costs found during the literature search only include the cost of the
hardware itself and do not account for any additional costs associated with the
actual construction of such a plant. There are many additional costs associated with
plant construction including site preparation, auxiliary equipment (cabling,
instrumentation, support structures, etc.), initial catalyst charging, waste disposal,
etc. These additional costs are significant and must be included in overall plant
costs to obtain an accurate understanding of capital investment required and the
impact that these costs would have on product prices. These additional costs are
accounted for in this model by introducing an overnight installed cost. This
overnight cost is estimated by multiplying the equipment or sub-system capital cost
by an “overnight” factor that includes both the installation and indirect cost factors.
A summary of the overnight cost for the two biorefinery cases present here as well
as the benchmarking costs given for a Nth-Generation plant concept [71], are shown
in Table 5.2.
Table 5.2. Biorefinery Overnight Capital Cost Comparison
System Baseline Case Advanced Case Nth Generation
Feed Preparation $27,035,065 $27,035,065 $66,762,011
Air Separation Unit 43,582,503 43,582,503 66,017,028
Gasification 26,521,389 26,521,389 49,412,484
Gas Cleanup 79,512,225 91,587,724 181,947,971
Water Gas Shift 58,063,734 57,890,720 43,509,920
Pressure Swing Adsorption 35,647,707 35,665,687 42,421,098
Steam and Power 63,088,371 64,733,710 118,151,568
TIC USD2008 $333,450,993 $347,016,797 $568,222,081
Dry Biomass Input tonnes/day 1880 1880 4536
USD2008/tonnes/day $177,368 $184,583 $125,269
Significant differences in cost per tonne are found when comparing the Nth
generation hydrogen from switchgrass plant with the two cases presented here.
This is likely due to differences in syngas composition due to feedstock selection as
98
well as assumptions and scaling advantages enjoyed by the larger plant sizes. The
Nth generation plant is based on a much larger 5000 short ton per day plant size and
therefor enjoys a significant size advantage.
A subsystem breakdown for each of the cases is given in Figure 5.1. The
majority of both plant capital costs are associated with gas cleanup, hydrogen
purification (WGS+PSA), and steam and power production
(a.) Baseline-case H2 from Woody Biomass (b.) Advanced-case H2 from Woody Biomass
(c.) Nth Generation Biorefinery H2 from Switchgrass
Figure 5.1 Capital Cost Breakdown of Hydrogen Biorefineries (a) Baseline Case (b) Advanced Case (c) PEI Nth Generation.
In order to more easily identify variation between the cases the capital costs
were normalized by plant feed rates as shown in Table 5.3. However, cost scaling
adjustment to account for the larger plant size is not taken into account. A
99
breakdown of subsystem hardware included in each system is given in Table 5.4 and
detailed cost estimates can be found in the appendix.
Table 5.3. Normalized Biorefinery Capital Cost Breakdown
Sub-system Baseline Advanced Nth Generation
Feed Preparation $14,380 $14,380 $21,086
Air Separation Unit 23,182 23,182 20,851
Gasification 14,107 14,107 15,607
Gas Cleanup 42,294 48,717 57,467
Water Gas Shift 30,885 30,793 13,742
Pressure Swing Adsorption 18,962 18,971 13,398
Steam and Power 33,558 34,433 37,317
Overnight Capital Cost 2008$ $177,368 $184,583 $125,269
The most significant variation is in the area of hydrogen purification. The WGS
cost estimates from Larson are nearly 25% of the cost estimates for the baseline and
advanced cases. This disparity is surprising but the values derived from the two test
cases here (baseline and advanced) are much more in line with estimates given by
NREL and so the Larson values are considered to be very optimistic. The other large
variation is in the gas cleanup area. These differences are to be expected as the Nth
generation plant utilized a Rectisol® acid-gas removal process to remove hydrogen
sulfide rather than the much less expensive LO-CAT® process favored by the
systems presented here as well as NREL [14]. Since carbon capture is not
specifically considered in any of the plant designs examined in this study the
additional cost of employing carbon capture and storage is not warranted. The
equipment list for each subsystem is given in Table 5.4 and includes all equipment
used to determine the plant overnight cost.
5.2 Cost of Hydrogen
To determine the cost of hydrogen produced ($/kgH2) by the biorefinery, plant
capital costs, hydrogen and electricity production, plant utility/biomass
consumption was entered into the H2A analysis tool developed by NREL3. A
summary of inputs to the H2A tool, including assumptions, are shown in Table 5.5.
3 For more information see: http://www.hydrogen.energy.gov/h2a_analysis.html
100
The baseline estimated biomass feedstock cost of $53.8/tonne is based on the 2012
DOE target for commercial biomass.
Table 5.4. Summary of Biorefinery Subsystem Hardware
Baseline Advanced Larson
Feed Preparation Truck Scale/Unloader Receiving Hopper/Magnet Rotary Disc Screen/Hopper RDS Conveyor HM Conveyor Dozer #1 Dozer #2 Reclaim Hopper Reclaim Conveyor Feed Bin Feed Conveyor Dual Lockhopper
Truck Scale/Unloader Receiving Hopper/Magnet Rotary Disc Screen/Hopper RDS Conveyor HM Conveyor Dozer #1 Dozer #2 Reclaim Hopper Reclaim Conveyor Feed Bin Feed Conveyor Dual Lockhopper
Conveyer Dry Biomass Storage Feed Bin Rotary Air Lock Feed Screw
Air Separation Unit ASU O2 and N2 Compressors
ASU O2 and N2 Compressors
ASU O2 Compressor
Gasification GTI Gasifier Ash Cyclone
GTI Gasifier Ash Cyclone
GTI Gasifier Ash Cyclone
Gas Cleanup Dolomite Guard Bed Catalytic Tar Cracker Syngas Cooler Wet Scrubber LO-CAT Oxidizer Vessel ZnO Polishing Bed
Dolomite Guard Bed Catalytic Tar Cracker Syngas Cooler Catalytic Candle Filter Hot Gas Desulfurization ZnO Polishing Bed
Tar Cracker Syngas Cooler Ceramic Filter Rectisol AGR AGR & CO2 Compressors
Water Gas Shift 2-Stage WGS 2-Stage WGS Saturator & 2-Stage WGS
Pressure Swing Adsorption
PSA Multi-stage H2 Compressor Purge Gas Compressor Blower
PSA Multi-stage H2 Compressor Purge Gas Compressor Blower
PSA H2 Compressor Purge Gas Compressor
Steam and Power HRSG Steam Cycle (Multi-stage Steam + Condenser Turbine) N2 + PSA Purge Expanders Heat Exchangers
HRSG Steam Cycle (Multi-stage Steam + Condenser Turbine) N2 + PSA Purge Expanders Heat Exchangers
HRSG Steam Cycle (Steam + Condenser Turbine)
The baseline cost of electricity is assumed to be a mid-western average cost and
the H2A tool also assumes that there exists a sufficiently large market for hydrogen
to be readily sold. The H2A base cost of hydrogen for the baseline-case was
$2.16/kgH2 and the advanced case was $2.14/kgH2. This difference in price is mainly
the result of the increased electricity production in the advanced-case due to
improved thermal integration. A study was conducted to examine the effect of
101
feedstock and electricity costs on cost of hydrogen. The results are shown in of the
H2A are given in Figure 5.2.
Table 5.5 Input Parameters for H2A Analysis Tool
Parameter Value
Constant Dollar Value 2005 Internal Rate of Return (after-tax) 10% Debt/Equity 0%/100% Plant Life 40 years Depreciation MACRS Depreciation Recovery Period 20 years Construction Period 1st year 2nd year
2 years 75% 25%
Start-up Time Revenues Variable Costs Fixed Costs
12 months 50% 75%
100% Working Capital 15% of Total Capital Investment Inflation Rate Total Taxes Decommissioning Costs Salvage Value
1.9% 38.9%
10% of depreciable capital 10% of total capital investment
Sell-back Price of Exported Electricity $0.0433 / kWh Biomass Feedstock Cost $53.8/tonne
Figure 5.2 H2A Cost of Hydrogen
As the sellback cost of electricity increases the cost of hydrogen from the
advanced case decreases more rapidly than that of the baseline case. This is
because at higher sellback costs, the additional power production in the advanced
1.50
1.75
2.00
2.25
2.50
2.75
$20 $30 $40 $50 $60 $70 $80 $90
Co
s o
f H
yd
rog
en
($
/k
g)
Biomass Feedstock Costs ($/tonne)
2 ¢/kwh (Advanced)
2 ¢/kwh (Baseline)
4.33 ¢/kwh (Advanced)
4.33 ¢/kwh (Baseline)
6 ¢/kwh (Advanced)
6 ¢/kwh (Baseline)
102
case becomes a much larger source of income. While the annual energy outlook
predicts that electricity prices will only increase 0.4 cents per kilowatt-hour
between 2016-2035 [79], any increase in electricity production along with
reductions in plant capital cost could quickly bring the cost of hydrogen from
biomass sources down to DOE 2015 target levels ($1.50/kgH2).
One such reduction in plant capital cost could come from adopting process
intensifying technologies such as WGSMRs. As is shown in Figure 5.3 replacing the
water gas shift reactors and the PSA unit (outlined in red) with a WGSMR (shown to
the side), a number of unit operations are eliminated from the plant. This results in
a simpler and less expensive biorefinery.
PSA
POx Tar
Cracking
Guard
Bed
Tar
Cracker
HPIPLPCD
Steam
Boiler
Condenser
Make-up
H2O
ASU
HTS
LTS
Purge Syngas
Compressor
H2
H2
Compressor
Compressor
Compressor
O2
N2
Vent
Exhaust
Biomass
Raw
Syngas
Ash
Gas CleanupGasifier
Air Separation Unit
H2 PurificationPower Generation
1
ZnO
Bed
Air
Water Gas Shift
25
Air
23
Hot Gas
Desulfurization
Catalytic
Candle Filter
HRSG
CoolersHRSG
Cooler
Air
7
6
20 19
3
Purge Gas
Combustor
Compressor
Blower
18
AC
4 5
8
9
17
14
16
22
24
21
N2Vent
2
26
H2O
HRSG
Cooler
10
11
12
13
HRSG
Cooler
Air
Cooler
Cooling
Tower
HX
15
8
1417
Figure 5.3 Process Intensification with WGSMRs
Preliminary simulations, using syngas compositions derived from the models
developed for this thesis, estimate that some 3,000 m2 (32,291 ft2) of Pd-based
membranes would be required to achieve 90% recovery of hydrogen from the
syngas. Assuming the manufacturing of these membranes could be accomplished at
the DOE 2015 target cost of 100 $/ft2, the cost of such a membrane would be
approximately $3 million. Even if the auxiliary equipment and installation cost
resulted in an installed unit cost of ten times the membrane cost, this would still
103
represent a capital cost reduction of nearly $70 million. Assuming plant hydrogen
and power output are not significantly changed by the substitution of the WGSMR
for the WGS+PSA, the cost of hydrogen could drop up to 20%. WGSMR would likely
improve plant performance by increasing hydrogen production and reducing plant
energy costs which would further improve plant economics and reduce the cost of
hydrogen.
104
CHAPTER 6
CONCLUSIONS
Biorefinery plant concepts for the co-production of hydrogen and electricity
were developed and studied. Plant configurations were established from a survey of
gasification and syngas cleanup technologies and process operating conditions and
component performance characteristics were guided by a thorough review of the
extant literature. Two hydrogen biorefinery plants were modeled using ASPEN
Plus® process modeling software and benchmarked and calibrated against
experimental data. The first plant configuration (baseline-case) employed only
near-term technology (2010-2015) meaning that only commercial or pilot scale
technologies were considered. The second case (advanced-case) utilized emerging
gas cleanup technologies to study the impact that such improvements would have
on system performance.
It was found that even the modest gas cleaning changes, replacing wet scrubbing
step with the catalytic candle filter and the LO-CAT® sulfur removal technology with
warm gas desulfurization technology improved the thermal integration of the plant.
This provided for greater recovery of waste heat leading to 31% more electricity
production. This increased the plant efficiency from 58.5% to 61.1% with an
increase in capital cost of 4%. The increased electricity production directly
impacted the production cost of hydrogen, lowering it from $2.16/kgH2 to
$2.14/kgH2
While the optimization of the thermal integration increased plant electrical
efficiency by 3%, the majority of the plant efficiency is derived from the hydrogen
product produced. With this understanding, research efforts should primarily focus
on improving fuel production and recovery. A 5 percentage point improvement in
hydrogen recovery efficiency resulted in nearly 10 percentage point improvement
in plant efficiency. Since the cost of hydrogen is primarily a function of the amount
of fuel produced per unit input, moderate improvements in this area dramatically
reduce the cost of hydrogen. Some approaches to improving the production and
recovery of hydrogen are to improve PSA performance by increasing partial
pressure of hydrogen at the inlet by removing carbon dioxide prior to the PSA and
105
by leveraging WGSMR technology to increase the forward water gas shift reaction
and improve hydrogen recovery. Employing WGSMR also has significant cost
advantages including reductions in the capital cost of hydrogen synthesis and
recovery by as much as 70%.
Another way to improve system performance is to identify the areas of the
biorefinery that are the most inefficient. A second law analysis was performed to
accomplish this and it revealed that the greatest areas of exergy destruction were
found to be gasification, steam and power generation, and hydrogen purification via
the pressure swing adsorption process. The exergetic losses in the gasifier are
mostly the result of the chemical kinetics and heat transfer with the gasifier. One
way to reduce these losses would be to increase the temperature of the gasifier.
This would minimize the losses within the gasifier but would require that the
gasifier changed to a slagging-type typical of coal gasification. This may require the
torrefaction of the biomass to facilitate feeding and should be studied in more detail
to ensure that efficiency losses due to the torrefaction process do not outweigh the
gains made by improving second law efficiency.
The losses in steam-power generation are primarily concentrated boiling-
superheating portions of the process. This is an area that has already seen
significant research effort in the power industry and these efforts could be
leveraged to optimize the steam-power portions of the plant. The losses in the
hydrogen purification portion are due to the low partial pressure of hydrogen in the
PSA feed gas. The dilute mixture does not allow for the PSA to operate at its most
efficient. The method described above for improving hydrogen recovery efficiency
would also serve to reduce the exergy destroyed in this process. It is important to
examine the impact that any modification in system technology/architecture would
have on the entire plant rather than on a single isolated system. If this is not taken
into account one runs the risk of improving energy/exergy efficiency of a single
process at the expense of overall plant performance.
Capital cost estimates were generated for the two cases and the overnight cost
estimate, which includes hardware, installation, indirect and startup costs, were
estimated to be $333 million (Baseline) and $347 million (Advanced). The largest
portion of the capital costs are associated with hydrogen synthesis and purification
106
(30%), gas cleanup (25-28%), and power production (17%). To improve the
accuracy of economic evaluations, economic assessment methodology needs to be
improved to provide for the reasonable estimation of capital costs for low TRL
technologies. Low TRL technologies have great potential to improve system
performance but are inherently difficult to accurately cost.
The 6010 kgH2/hr produced by these the energy equivalent of approximately
157,322 gallons of gasoline per day. While this is not a huge amount it is enough to
provide 130,000 individuals with the energy equivalent of the average gasoline
energy Americans consume on a daily basis [80, 81]. Each refinery would reduce
the need to import over 8000 barrels of oil every day for the production of gasoline.
To completely eliminate the need to import oil for gasoline production several
thousand biorefineries would need to be built and the vehicle fleet would need to be
converted for hydrogen use. While this is not a reasonable option due to the large
capital costs associated with building refineries/converting the vehicle fleet and the
huge amount biomass that thousands of biorefineries would require, it does show
the impact that employing alternatives to feed such a number of refineries but the
intent of biorefining would not be to be the singular replacement for gasoline. By
increasing domestic energy resources by leveraging alternative technologies,
including thermochemical-based biorefining, the US can make progress in reducing
US foreign oil imports and increasing energy and economic security.
107
CHAPTER 7
FUTURE WORK RECOMMENDATIONS
This work establishes a foundation for modeling and simulation of gasification-
based systems. It provides a framework from which to build higher-fidelity models
for use in future studies and accordingly there are significant opportunities for
future research.
Project 1: Explore the impact of various feedstocks on gasifier performance and
syngas composition
In order to use the gasifier model developed in this work, knowledge about
outlet syngas composition and feedstock characteristics is required. This proves
problematic when trying to simulate variable feedstocks such as municipal waste,
agricultural residues, etc. In reality, gasification-based biorefineries are most likely
to be attractive when they can operate on a variety of different feedstocks. An
improved gasifier model would enable evaluation of the effect of feedstock variation
(e.g. seasonal variation in energy crops) on plant performance and economics
Project 2: Impact of changing biorefinery product
One advantage of gasification of a biomass feedstock is that the syngas produced
can be used as a feedstock to make a wide variety of products. This study was
limited to hydrogen-power production, but fuels such as Fischer-Tropsch liquids,
mixed alcohols, methanol, and dimethyl ether could be produced. Each fuel requires
a different fuel production pathway, and incorporating flexibility of product
produced into the biorefinery model represents a significant modeling effort. Fuel
flexibility in the models would allow for design and optimization of a wide variety of
fuel types and co-products.
Project 3: Impact of advanced technology and process intensification in hydrogen
production and purification
The work performed in this study examined the impact of advanced gas cleanup
technology on biorefinery performance. Only a limited set of gas cleanup options
108
were pursued in this thesis. Preliminary studies suggest that WGSMR technology is
an attractive option that deserves further investigation.
Project 4: Integration of fuel cell technology into biomass gasification plants
Fuel cells present an efficient alternative to traditional power production
technologies such as IGCC technology. Solid oxide fuel cell integration into a
biorefinery provides for highly efficient power production yet requires detailed
consideration of syngas purity, operating temperature and pressure, and thermal
integration.
Project 5: Integrating carbon capture technology in carbon-lite, carbon-neutral,
carbon-negative biorefinery plant configurations
Carbon capture technology is thought to reduce overall plant efficiency due to
the high parasitic loads associated with the compression/dehydration of carbon
dioxide. During the course of this study it was found that employing carbon capture
technology could negate the negative impact of carbon capture parasitic loads by
improving hydrogen recovery rates. More detailed study of such systems is
warranted due to the potential performance gains and potential economic impact
even in the absence of carbon legislation.
Project 6: Life cycle assessment of thermochemical-based biorefineries
To this point full lifecycle assessments of biorefineries are relatively rare.
Incorporating environmental and social impacts of such plants would be very
beneficial in understanding the overall costs and environmental impact of such
systems.
109
REFERENCES CITED
[1] U.S. Energy Information Administration. (2010, October 29). China - Oil.
Available: http://www.eia.doe.gov/cabs/China/Oil.html
[2] U.S. Energy Information Administration. (2010). Petroleum. Available:
http://www.eia.doe.gov/oil_gas/petroleum/info_glance/petroleum.html
[3] U. S. D. o. Energy. (2011, March 26). U.S. Petroleum Reserves. Available:
http://www.fossil.energy.gov/programs/reserves/
[4] U.S. Department of Commerce, "National Income and Product Accounts,"
Bureau of Economic Analysis, Ed., ed, 2009.
[5] Air Transport Association. (2010, April). Annual Crude Oil and Jet Fuel Prices.
Available:
http://www.airlines.org/Economics/DataAnalysis/Pages/AnnualCrudeOilandJetF
uelPrices.aspx
[6] Air Transport Association. (2010, April). U.S. Airline Bankruptcies and Service
Cessations. Available:
http://www.airlines.org/Economics/DataAnalysis/Pages/USAirlineBankruptciesS
erviceCessations.aspx
[7] R. Perlack, L. Wright, A. Turhollow, R. Graham, B. Stokes, and D. Erbach,
"Biomass as Feedstock for a Bioenergy and Bioproducts Industry: The Technical
Feasibility of a Billion-Ton Annual Supply," Oak Ridge National Laboratory,
2005.
[8] G. Gopalakrishnan, M. C. Negri, M. Wang, M. Wu, S. W. Snyder, and L.
LaFreniere, "Biofuels, Land, and Water: A Systems Approach to Sustainability,"
Environmental Science & Technology, vol. 43, pp. 6094-6100, 2009.
[9] A. Milbrandt, "Geographic Perspective on the Current Biomass Resource
Availability in the United States," National Renewable Energy Lab, Golden,
2005.
[10] National Renewable Energy Laboratory. (2010). Dynamic Maps, GIS Data, &
Analysis Tools. Available: http://www.nrel.gov/gis/biomass.html
[11] C. Higman and M. Van der Burgt, Gasification: Elsevier, 2003.
[12] E. Larson, H. Jin, and F. Celik, "Gasification-based Fuels and Electricity
Production from Biomass, without and with Carbon Capture and Storage,"
Princeton Environmental Institute, Princeton, NJ, 2005.
[13] R. H. Williams, E. D. Larson, R. E. Katofsky, and J. Chen, "Methanol and
hydrogen from biomass for transportation," Energy for Sustainable Development,
vol. 1, pp. 18-34, 1995.
110
[14] P. Spath, A. Aden, T. Eggeman, M. Ringer, B. Wallace, and J. Jechura, "Biomass
to Hydrogen Production Detailed Design and Economics Utilizing the Battelle
Columbus Laboratory Indirectly-Heated Gasifier," NREL/TP-510-37408, 2005.
[15] Energy Research Centre of the Netherlands (ECN). (2009, June). Wood, Hybrid
Poplar ID#806. Available: http://www.ecn.nl/phyllis
[16] J. Dean, R. Braun, D. Munoz, M. Penev, and C. Kinchin, "An Analysis of Hybrid
Hydrogen Production Systems," National Renewable Energy Laboratory,
Golden, 2010.
[17] E. Searcy and P. Flynn, "The Impact of Biomass Availability and Processing
Cost on Optimum Size and Processing Technology Selection," Applied
Biochemistry and Biotechnology, vol. 154, pp. 92-107, 2009.
[18] A. Aden, M. Ruth, K. Ibsen, J. Jechura, K. Neeves, J. Sheehan, B. Wallace, L.
Montague, A. Slayton, and J. Lukas, "Lignocellulosic Biomass to Ethanol
Process Design and Economics Utilizing Co-Current Dilute Acid Prehydrolysis
and Enzymatic Hydrolysis for Corn Stover," NREL/TP-510-32438, 2002.
[19] J. Dean, "Leveling Intermittent Renewable Energy Production Through Biomass
Gasification-Based Hybrid Systesm," M.S., Division of Engineering Colorado
School of Mines, Golden, 2009.
[20] P. Bergman, A. Boersma, J. Kiel, M. Prins, K. Ptasinski, and F. Janssen,
"Torrefaction for entrained-flow gasification of biomass," 2005.
[21] J. Kiel, F. Verhoeff, H. Gerhauser, and B. Meuleman, "BO2-technology for
biomass upgrading into solid fuel - pilot-scale testing and market
implementation," in 16th European Biomass Conference & Exhibition, Valencia,
Spain, 2008, pp. 48-53.
[22] K. R. Cummer and R. C. Brown, "Ancillary equipment for biomass gasification,"
Biomass and Bioenergy, vol. 23, pp. 113-128, 2002.
[23] M. R. Beychok, "Process and environmental technology for producing SNG and
liquid fuels," National Environmental Research Center, 1975.
[24] Gasification Technologies Council. (2010, Nov 29). What is Gasification
Overview. Available: http://www.gasification.org/page_2.asp?a=1
[25] R. Braun, J. Dean, and L. Hanzon, "Modeling and Systems Analyses of
Thermochemical-based Biorefineries - Final Report," Institution of
Transportation StudiesColorado School of Mines, 2009.
[26] F. Lau, D. Bowen, R. Zabransky, R. Remick, R. B. Slimane, and S. Doong,
"Technoeconomic Analysis of Hydrogen Production by Gasification of
Biomass," United States Department of Energy, 2003.
111
[27] R. J. Evans, R. A. Knight, M. Onischak, and S. P. Babu, "Development of
biomass gasification to produce substitute fuels," Pacific Northwest Laboratory,
Richland, Technical Report1 March 1988.
[28] A. der Drift, H. Boerrigter, B. Coda, M. K. Cieplik, and K. Hemmes, "Entrained
flow gasification of biomass: Ash behaviour, feeding issues, system analyses,"
Environmental Center of the Netherlands, 2004.
[29] N. Abatzoglou, N. Barker, P. Hasler, and H. Knoef, "The development of a draft
protocol for the sampling and analysis of particulate and organic contaminants in
the gas from small biomass gasifiers," Biomass and Bioenergy, vol. 18, pp. 5-17,
2000.
[30] T. Milne and R. J. Evans, "Biomass Gasifier "Tars": Their Nature, Formation,
and Conversion," National Renewable Energy Laboratory, Golden, 1998.
[31] M. M. Yung, W. S. Jablonski, and K. A. Magrini-Bair, "Review of Catalytic
Conditioning of Biomass-Derived Syngas," Energy & Fuels, vol. 23, pp. 1874-
1887, 2009.
[32] L. Devi, K. J. Ptasinski, F. J. J. G. Janssen, S. V. B. van Paasen, P. C. A.
Bergman, and J. H. A. Kiel, "Catalytic decomposition of biomass tars: use of
dolomite and untreated olivine," Renewable Energy, vol. 30, pp. 565-587, 2005.
[33] S. Rapagnà, N. Jand, A. Kiennemann, and P. U. Foscolo, "Steam-gasification of
biomass in a fluidised-bed of olivine particles," Biomass and Bioenergy, vol. 19,
pp. 187-197, 2000.
[34] G. Huber, "Breakingthe Chemical and Engineering Barriers to Lignocellulosic
Biofuels: Next Generation Hydrocarbon Biorefineries," University of
Massachusetts-Amherst, Amherst, 2008.
[35] Y. G. Pan, X. Roca, E. Velo, and L. Puigjaner, "Removal of tar by secondary air
in fluidised bed gasification of residual biomass and coal," Fuel, vol. 78, pp.
1703-1709, 1999.
[36] L. Devi, K. J. Ptasinski, and F. J. J. G. Janssen, "A review of the primary
measures for tar elimination in biomass gasification processes," Biomass and
Bioenergy, vol. 24, pp. 125-140, 2003.
[37] S. Villano, J. Hoffmann, H.-H. Carstensen, and A. Dean, "Selective Removal of
Ethylene, a Deposit Precursor, from a "Dirty" Synthesis Gas Stream via Gas-
Phase Partial Oxidation," Journal of Physical Chemistry A, vol. 114, pp. 6502-
6514, 2010.
[38] American Water Works Association and American Society of Civil Engineers,
Water Treatment Plant Design, 3rd ed. New York: McGraw Hill, 1997.
[39] A. R. Smith and J. Klosek, "A review of air separation technologies and their
integration with energy conversion processes," Fuel Processing Technology, vol.
70, pp. 115-134, 2001.
112
[40] H. Boerrigter, H. d. Uil, and H.-P. Calis, "Green Diesel from Biomass via
Fischer-Tropsch Synthesis: New Insights in Gas Cleaning and Process Design,"
presented at the Pyrolysis and Gasifciation of Biomass and Waste, Expert
Meeting, Strasbourg, France, 2002.
[41] K. Engelen, Y. Zhang, D. J. Draelants, and G. V. Baron, "A novel catalytic filter
for tar removal from biomass gasification gas: Improvement of the catalytic
activity in presence of H2S," Chemical Engineering Science, vol. 58, pp. 665-
670.
[42] P. Simell, E. Kurkela, P. Ståhlberg, and J. Hepola, "Catalytic hot gas cleaning of
gasification gas," Catalysis Today, vol. 27, pp. 55-62, 1996.
[43] W. Wang, N. Padban, Z. Ye, G. Olofsson, A. Andersson, and I. Bjerle, "Catalytic
Hot Gas Cleaning of Fuel Gas from an Air-Blown Pressurized Fluidized-Bed
Gasifier," Industrial & Engineering Chemistry Research, vol. 39, pp. 4075-4081,
2000.
[44] J. H. Lehr and J. K. Lehr, Standard Handbook of Environmental Science, Health,
and Technology, 1st ed. New York: McGraw-Hill, 2000.
[45] J. Patt, D. Moon, C. Phillips, and L. Thompson, "Molybdenum carbide catalysts
for water–gas shift," Catalysis Letters, vol. 65, pp. 193-195, 2000.
[46] A. V. Bridgwater, "The technical and economic feasibility of biomass
gasification for power generation," Fuel, vol. 74, pp. 631-653, 1995.
[47] D. Cicero, R. Gupta, B. Turk, and D. Simbeck, "A Review of Desulfurization in
Gasification Systems," in 20th Annual International Pittsburgh Coal Conference,
Pittsburgh, Pennsylvania. USA, 2003.
[48] D. Kubek and E. Polla, "Purification and Recovery Options for Gasification," ed.
Des Plaines, Illinois: UOP LLC, 2000.
[49] A. Kohl and R. B. Nielsen, Gas Purification, 5th ed.: Elsevier, 1997.
[50] Merichem Company. (2009, June). LO-CAT(R) Process Spec Sheet. Available:
http://www.gtp-merichem.com/products/lo-cat/process.php
[51] G. Henningsen, S. Katta, and G. Mathur, "Sorbent Testing and
Commercialization of Transport Reactors for Hot Gas Desulfurization," in The
Advanced Coal-Based Power and Environmental Systems '97 Conference,
Pittsburgh, PA, 1997.
[52] U.S. Department of Energy, "Current and Future IGCC Technologies," 2008.
[53] Y. Ohtsuka, N. Tsubouchi, T. Kikuchi, and H. Hashimoto, "Recent progress in
Japan on hot gas cleanup of hydrogen chloride, hydrogen sulfide and ammonia in
coal-derived fuel gas," Powder Technology, vol. 190, pp. 340-347, 2009.
113
[54] S. K. Gangwal and J. W. Portzer, "Advanced Sulfur Control Concepts," in
Advanced Coal-Fired Power Systems '95 Review Meeting, Springfield, BA,
1995.
[55] Nextant, "Preliminary Feasibility Analysis of RTI Warm Gas Cleanup (WGCU)
Technology," Research Triangle Institute InternationalJune 2007.
[56] G. Kolb, Fuel Processing: for Fuel Cells, 1st ed.: Wiley, 2008.
[57] Haldor-Topsoe, "Sulfur tolerance of water gas shift catalysts," J. Dean, Ed., ed,
2009.
[58] Haldor-Topsoe, "SSK Sulphur resistant/sour wager-gas shift catalyst," ed:
Haldor-Topsoe, 2009.
[59] L. Wang, K. Murata, and M. Inaba, "Development of novel highly active and
sulphur-tolerant catalysts for steam reforming of liquid hydrocarbons to produce
hydrogen," Applied Catalysis A: General, vol. 257, pp. 43-47, 2004.
[60] D. Drdar and R. Jones, "GE IGCC Technology and Experience with Advanced
Gas Turbines," General Electric, 2000.
[61] L. Engineering, "Pressure Swing Adsorption Sulfur Tolerance," J. Dean, Ed., ed,
2009.
[62] C. Yang, "Determining the lowest-cost hydrogen delivery mode," International
Journal of Hydrogen Energy, vol. 32, pp. 268-286, 2007.
[63] A. Züttel, "Hydrogen storage methods," Naturwissenschaften, vol. 91, pp. 157-
172, 2004.
[64] R. L. Bain, "Material and Energy Balances for Methanol from Biomass Using
Biomass Gasifiers," National Renewable Energy Laboratory, Golden, 1992.
[65] C. N. Hamelinck, A. P. C. Faaij, H. den Uil, and H. Boerrigter, "Production of
FT transportation fuels from biomass; technical options, process analysis and
optimisation, and development potential," Energy, vol. 29, pp. 1743-1771, 2004.
[66] I. C. Kemp, Pinch Analysis and Process Integration, 2nd ed. Oxford, UK:
Butterworth-Heinemann, 2007.
[67] R. D. Brdar and R. M. Jones, "GE IGCC Technology and Experience with
Advanced Gas Turbines," GE Power Systems, 2000.
[68] M. M. El-Wakil, Powerplant Technology: McGraw-Hill, 2002.
[69] R. H. Perry and D. W. Green, Perry's Chemical Engineers' Handbook, 7th ed.:
McGraw-Hill, 1997.
[70] M. P. Aznar, M. A. Caballero, J. Gil, J. A. Martin, and J. Corella, "Commercial
Steam Reforming Catalysts To Improve Biomass Gasification with
114
Steam−Oxygen Mixtures. 2. Catalytic Tar Removal," Industrial & Engineering
Chemistry Research, vol. 37, pp. 2668-2680, 1998.
[71] E. D. Larson, H. Jin, and F. E. Celik, "Large-scale gasification-based
coproduction of fuels and electricity from switchgrass," Biofuels, Bioproducts
and Biorefining, vol. 3, pp. 174-194, 2009.
[72] R. J. Braun, L. G. Hanzon, and J. H. Dean, "System Analysis of
Thermochemical-Based Biorefineries for Coproduction of Hydrogen and
Electricity," Journal of Energy Resource Technology, vol. 133, 2011.
[73] M. Moran, Availability Analysis: a guide to efficient energy use corrected
edition. New York: ASME, 1989.
[74] M. J. Moran and H. N. Shapiro, Fundamentals of engineering thermodynamics,
1988.
[75] J. Szargut, Exergy Method Technical and Ecological Applications. Ashurst
Lodge, Southhampton: WIT Press, 2005.
[76] J. Szargut, D. R. Morris, and F. R. Steward, Energy analysis of thermal,
chemical, and metallurgical processes, 1988.
[77] M. J. Moran and H. N. Shapiro, Fundamentals of Engineering Thermodynamics,
6th ed. Hoboken, NJ: John Wiley and Sons, Inc., 2008.
[78] P. S. Yong, H. M. Moon, and S. C. Yi, "Exergy Analysis of Cryogenic Air
Separation Process for Generating Nitrogen," Journal of Industrial Engineering
Chemistry, vol. 8, pp. 499-505, September 28 2002.
[79] U. S. D. o. Energy. (2009, March 30). Annual Energy Outlook 2011 Early
Release with Projections to 2035. Available:
http://www.eia.gov/forecasts/aeo/pdf/0383er%282011%29.pdf
[80] U.S. Census Bureau. (2011, April). US & World Population Clocks. Available:
http://www.census.gov/main/www/popclock.html
[81] U.S. Energy Information Administration. (2010, April). Oil: Crude and
Petroleum Products Explained. Available:
http://www.eia.doe.gov/energyexplained/index.cfm?page=oil_home#tab2
[82] C. McGowin and C. Libby, "Engineering and Economic Evaluation of
Renewable Energy Technology," Palo Alto, 2007.
[83] Nexant, "Gasification Plant Cost and Performance Optimization," Septemeber
2003.
[84] M. Peters, K. Timmerhaus, and R. West, Plant Design and Economics for
Chemical Engineers, 5th ed. New York: McGraw-Hill
Science/Engineering/Math, 2003.
115
[85] A. M. Gribik, R. E. Mizia, H. Gatley, and B. Phillips, "Economic and Technical
Assessment of Wood Biomass Guel Gasification for Industrial Gas Production,"
2007.
[86] Nexant, "Equipment Design and Cost Estimation for Small Midular Biomass
Systems, Synthesis Gas Cleanup, and Oxygen Separatoin Equipment," National
Renewable Energy LaboratoryMay 2006.
[87] D. R. Simbeck, "CO2 Mitigation Economics for Existing Coal-Fired Power
Plants," in First National Conference on Carbon Sequestration, Washington DC,
2001.
[88] T. Kreutz, R. Williams, S. Consonni, and P. Chiesa, "Co-production of hydrogen,
electricity and CO2 from coal with commercially ready technology. Part B:
Economic analysis," International Journal of Hydrogen Energy, vol. 30, pp. 769-
784, 2005.
[89] M. McMurry, K. Eurek, Ed., Personal communication via email ed: GE Infra
Energy, 2009.
[90] HP Alloys. (2009, August). INCONEL(R) Alloy 600 (UNS N06600). Product
Brochure
[91] R. A. Newby, M. A. Alvin, G. J. Bruck, T. E. Lippert, E. E. Smeltzer, and M. E.
Stampahar, "Optimization of Advanced Filter Systems - Option I Program -
Bench-Scale Testing for the Resoultion of Technical Issues," Siemens
Westinghouse Power Corporation, Pittsburgh DE-AC26-97FT33007, June 2002.
116
APPENDIX A
BIOREFINERY CAPITAL COSTS [25]
Table A. 1 Capital Costs for Baseline Case
Un
its
SS
oC
oC
os
t Y
ea
rR
20
08
Co
st
I.F
.2
00
8 I
ns
tall
ed
Co
st
Ov
ern
igh
t C
os
tN
ote
Fe
ed
Pre
pa
rati
on
:
Tru
ck
Sc
ale
/Un
loa
de
rto
ns
110
.23
60
100
,00
02
00
60
.717
6,3
32
2.4
7$
43
5,5
39
$5
53
,13
4a
.
Re
ce
ivin
g H
op
pe
r/M
ag
ne
tft
314
161
8,5
00
8,0
00
20
06
0.7
13,1
73
2.4
7$
32
,53
7$
41,
32
2a
.
Ro
tary
Dis
c S
cre
en
/Ho
pp
er
ton
s/h
r3
67
.44
20
03
5,0
00
20
06
0.7
61,
716
2.4
7$
152
,43
9$
193
,59
7a
.
Ha
mm
er
Mill
/ H
op
pe
rto
ns
/hr
166
.610
02
30
,00
02
00
60
.73
78
,72
42
.47
$9
35
,44
9$
1,18
8,0
20
a.
RD
S C
on
ve
yor
ton
s/h
r16
6.6
100
45
,00
02
00
60
.77
4,0
98
2.4
7$
183
,02
3$
23
2,4
39
a.
HM
Co
nv
eyo
rto
ns
/hr
183
.72
100
45
,00
02
00
60
.77
9,3
49
2.4
7$
195
,99
3$
24
8,9
10a
.
Do
zer
#1
yd3
18.4
18.4
40
0,0
00
20
06
14
60
,76
92
.47
$1,
138
,09
8$
1,4
45
,38
5a
.
Do
zer
#2
yd3
18.4
18.4
40
0,0
00
20
06
14
60
,76
92
.47
$1,
138
,09
8$
1,4
45
,38
5a
.
Re
cla
im H
op
pe
rto
ns
24
9.9
150
5,5
00
20
06
0.7
9,0
56
2.4
7$
22
,36
9$
28
,40
9a
.
Re
cla
im C
on
ve
yor
ton
s/h
r9
1.8
65
05
0,0
00
20
06
0.7
88
,16
62
.47
$2
17,7
69
$2
76
,56
7a
.
Fe
ed
Bin
ton
s2
75
.58
150
5,5
00
20
06
0.7
9,6
98
2.4
7$
23
,95
5$
30
,42
2a
.
Fe
ed
Co
nv
eyo
rto
ns
/hr
91.
86
50
40
,00
02
00
60
.77
0,5
33
2.4
7$
174
,216
$2
21,
25
4a
.
Lo
ck
Ho
pp
er
ton
s/h
r9
1.8
63
02
,115
,50
02
00
20
.76
,73
6,0
192
.47
$16
,63
7,9
67
$2
1,13
0,2
18b
.
Ga
sif
ica
tio
n a
nd
AS
U
Cry
og
en
ic A
ir S
ep
ara
tio
nk
g/s
95
% O
28
.216
.06
40
,318
,00
02
00
40
.62
53
4,3
16,9
32
Inc
lud
ed
$3
4,3
16,9
32
$4
3,5
82
,50
3c
.
GT
I Ga
sif
ier
ton
ne
s/d
ay
1,8
80
82
95
,85
2,3
30
20
03
0.7
14,8
72
,86
51.
32
$19
,63
2,1
81
$2
5,9
14,4
79
d.
As
h C
yclo
ne
kg
/s g
as
46
.82
1.0
83
99
,60
22
00
70
.67
186
,14
62
.47
$4
59
,78
0$
60
6,9
10e
.
Ga
s C
lea
nu
p
Do
lom
ite
Gu
ard
Be
dk
g/h
r g
as
168
,65
95
7,6
51
219
,28
02
00
50
.75
71,
418
2.4
7$
1,4
11,4
03
$1,
86
3,0
52
f.
Ca
taly
tic
Ta
r C
rac
ke
rft
3/m
in g
as
19,1
52
10,0
00
1,4
04
,28
32
00
70
.72
,42
4,1
78
2.4
7$
5,9
87
,72
0$
7,9
03
,79
1g
.
Syn
ga
s C
oo
ler
(A,B
)M
Wth
46
.57
72
5,4
00
,00
02
00
30
.59
27
,02
3,7
07
1.5
2$
41,
103
,05
9$
54
,25
6,0
37
h.
We
t S
cru
bb
er
m3/s
ga
s4
.09
12.1
3,5
11,2
00
20
02
0.7
2,3
90
,05
72
.47
$5
,90
3,4
41
$7
,79
2,5
42
i.
LO
-CA
T(R
) Oxi
diz
er
Ve
ss
el
kg
/hr
ga
s3
60
23
3.6
1,0
00
,00
02
00
20
.65
1,9
26
,98
52
.47
$4
,75
9,6
53
$6
,28
2,7
42
j.
Zn
O P
olis
hin
g B
ed
k
g/h
r g
as
117
,25
85
7,6
51
219
,28
02
00
50
.67
43
3,7
08
2.4
7$
1,0
71,
25
8$
1,4
14,0
61
k.
Wa
ter
Ga
s S
hif
t
Hig
h T
em
p W
GS
km
ol
(CO
+H2
)/h
r3
,73
58
,819
10,7
00
,00
02
00
20
.65
8,9
04
,38
82
.47
$2
1,9
93
,83
8$
29
,03
1,8
66
l.
Lo
w T
em
p W
GS
km
ol
(CO
+H2
)/h
r3
,73
58
,819
10,7
00
,00
02
00
20
.65
8,9
04
,38
82
.47
$2
1,9
93
,83
9$
29
,03
1,8
67
l.
H2
Pu
rifi
ca
tio
n
PS
A U
nit
km
ol/
s H
2
Re
cyc
le1.
20
59
0.2
94
5,3
70
,00
02
00
20
.74
22
,20
0,1
89
Inc
lud
ed
$2
2,2
00
,18
9$
29
,30
4,2
49
m.
H2 R
ec
ycle
Co
mp
res
so
rM
We
0.0
97
55
104
,74
8,5
82
20
02
0.6
73
10,5
53
Inc
lud
ed
$3
10,5
53
$4
09
,93
0n
.
H2 C
om
pre
ss
or
MW
e3
.54
104
,74
8,5
82
20
02
0.6
73
,44
6,0
76
Inc
lud
ed
$3
,44
6,0
76
$4
,54
8,8
21
o.
Blo
we
rm
3/s
air
52
.78
4.7
26
7,0
00
199
70
.64
24
,70
52
.47
$1,
04
9,0
21
$1,
38
4,7
07
p.
Ste
am
an
d P
ow
er:
HR
SG
+ S
tea
m C
ycle
MW
e3
6.3
85
05
0,0
16,0
00
20
08
0.6
43
40
,76
6,7
37
Inc
lud
ed
$4
0,7
66
,73
7$
51,
77
3,7
57
q.
PS
A P
urg
e G
as
Exp
an
de
rM
We
1.7
510
3,1
40
,00
02
00
30
.67
1,3
99
,29
3In
clu
de
d$
1,3
99
,29
3$
1,7
77
,10
2r.
AS
U N
2 E
xpa
nd
er
MW
e3
.110
3,1
40
,00
02
00
30
.67
2,0
52
,511
Inc
lud
ed
$2
,05
2,5
11$
2,6
06
,68
9r.
Co
mb
us
tio
n A
ir C
om
pre
ss
or
MW
e0
.74
104
,74
8,5
82
20
02
0.6
71,
20
7,0
86
Inc
lud
ed
$1,
20
7,0
86
$1,
53
2,9
99
r.
Bo
iler
(C)
m2
613
.43
715
.35
65
1,15
32
00
70
.59
65
1,4
09
2.4
7$
1,6
08
,98
1$
2,0
43
,40
6s
.
Pre
he
ate
r (D
)m
24
47
.62
715
.35
65
1,15
32
00
70
.59
54
0,8
87
2.4
7$
1,3
35
,99
1$
1,6
96
,70
8s
.
Co
nd
en
se
r (E
)m
24
5.3
57
15.3
56
51,
153
20
07
0.5
914
0,0
98
2.4
7$
34
6,0
42
$4
39
,47
3s
.
Co
nd
en
se
r (F
)m
29
8.5
37
15.3
56
51,
153
20
07
0.5
92
21,
45
82
.47
$5
47
,00
0$
69
4,6
90
s.
Co
nd
en
se
r (G
)m
26
1.0
17
15.3
56
51,
153
20
07
0.5
916
6,8
99
2.4
7$
412
,24
1$
52
3,5
47
s.
TIC
20
08
$2
56
,60
2,2
78
$3
33
,45
0,9
93
117
Table Notes:
a. Feed preparation base on a generic biomass feed preparation system from the
Renewable Energy Technology Assessment Guide. Biomass is assumed to be dry
upon delivery. This baseline system provides 50 dry tons of dry biomass per
hour to the gasification plant. In order to scale the system components to the
CSM requirements, ratios between feed equipment capacities are kept constant
based on a Feed Conveyor rate of 91.86 dry tons of biomass per hour. For
instance the ratio between the Feed Bin and Feed Conveyor is 3:1, so the Feed
Bin will store 275.58 tons of biomass which is three times the feed conveyor
rate of 91.86 tph [82].
b. The dual lock hopper cost data is given by T.R. Miles Consultants. The lock
hopper system includes two 15-ton-per-hour lock hoppers each with a meter
bin, injector screw, and inert gas and purge gas compression. Overall the base
system provides 30 tons of dry biomass per hour to the gasifier which is scaled
up to 91.86 tons per hour [52].
c. Nexant/GTI cite an Air Products quote of an ASU with 1530 tpd of 95% pure O2
at 90F, 500 psia. The ASU requires 40.9 MW, 4450 lb/hr psig steam, 9400 gpm
cooling water. Scaling factor has been developed with ASU cost data from
various sources [83].
d. Larson et al. 2005 gives cost data for an oxygen-blown, pressurized GTI gasifier.
The base cost for a gasifier pressurized at 30 bar which processes 1000 tons of
bagasse per day is 6.41 million USD2003. According to Larson a 30 bar GTI
gasifier can process up to 2875 tons per day. The CSM system uses a gasifier
pressurized at 24 bar, so the cost must be scale down to account for the
pressure difference. Using cost factors for internal pressure levels of vessels
from Peter and Timmerhaus, the cost factor (CF) associated with a vessel with
pressure P (bar) is given as CF = 0.0368*P + 1.4363. The CF’s for 24 bar and 30
bar are 2.32 and 2.54 respectively. Therefore a factor of 0.913 (2.32/2.54 =
0.913) is applied to the 30 bar gasifier base cost to give a 24 bar base cost of
5.85 million USD2003. According to Larson, a 24 bar GTI gasifier has a maximum
processing capacity of 2416 tpd [12, 84].
e. Gasifier ash cyclone is given by Gribik et al. 2007. The ash cyclone cited is rated
for temperatures up to 1000 ºF, pressures up to 25 psi, and syngas flow rates of
10,000 scfm. Cost includes 4.8 percent for equipment delivery [85].
f. Dolomite guard bed base cost is given by Nexant. Cost is based on a ZnO bed
which is similar in construction to a dolomite bed. Because the bed is made of
steel the cost will be highly dependent on changes in steel price [86].
g. Tar Cracker cost given by Gribik et al. 2007. The tar cracker is a bubbling
fluidized reactor rated at 96 percent conversion of tars, oils and methane. The
reactor allows for 10,000 scfm of syngas flow, requires inlet gas temperatures of
118
1652 ºF, and has outlet gas temperatures of 1742 ºF. Cost includes 4.8 percent
for equipment delivery [85]
h. Syngas cooler cost is based on a 77 MWth unit given in Simbeck 2004 [87]. The
scaling factor is given by Hamelinck et al. 2004. [65]
i. Wet scrubber cost comes from Hamelick et al. 2004 who cites vendor quotes for
a 29 MWe BIGCC plant requiring 33.48 tonnes wood per day input and
producing 10.55 m3 of fuel gas per second [65].
j. The LO-CAT system is described by Spath et al 2005. The system consists of a
venturi, absorber, oxidizer, air blower, solution circulation pump and solution
cooler [14].
k. ZnO bed cost is given by Nexant. Because the bed is made of steel the cost will
be dependent on steel price [86].
l. Water Gas Shift Reactor cost given by Hamelinck et al. 2004 as 10.7 million
USD2002. Scaling is based on 8819 kmol of CO + H2 per hour.
m. PSA cost given by Kreutz et al 2005. The PSA base unit is rated to 85 percent
recovery rate of hydrogen. Scaling is based on a purge gas flow rate of 0.294
kmol/s. Indirect costs and engineering costs are factored out [88].
n. Recycle gas compressor given by Kreutz et al 2005 as 6.28 million USD2002, which
includes engineering and contingencies. Removing indirect costs yields 4.749
million USD2002 for a 10 MWe compressor [88].
o. The hydrogen compressor is assumed similar to a recycle gas compressor given
by Kreutz et al 2005 [88]. See note (n).
p. Perry gives 1997 cost data for a centrifugal blower excluding the motor with a
scaling factor of R= 0.60. Scaling is based on normal cubic meters per second of
air [69].
q. The HRSG and steam cycle system was provided by Michael McMurray of GE
Infra, Energy. Cost data was generated from a General Electric cost estimation
program for power plants from 25 MW to 200 MW. A scaling factor of 0.634 was
calculated for this MW range [89].
r. Both the purge gas expander and the N2 expander are considered to be similar
to the syngas expander described by Kreutz et al 2005 [88]. This gives a base
cost of 3.14 million for a 10 MW expander.
s. Original installed cost for a 715.35 m2 heat exchanger is 0.651 million USD2007.
The heat exchanger is described by Gribik et al 2007 as a compact type made
from a high temperature alloy (Inconel) which is rated for temperatures up to
1800°F. Inconel is a sulfur tolerant and resistant to hydrogen embrittlement
which will protect the heat exchanger from the corrosive makeup of the syngas
[85, 90].
119
Table A. 2 Capital Costs for Advanced Case
Un
its
SS
oC
oC
os
t Y
ea
rR
20
08
Co
st
I.F
.2
00
8 I
ns
tall
ed
Co
st
Ov
ern
igh
t C
os
tN
ote
Fe
ed
Pre
pa
rati
on
:
Tru
ck
Sc
ale
/Un
loa
de
rto
ns
110
.23
60
100
,00
02
00
60
.717
6,3
32
2.4
7$
43
5,5
39
$5
53
,13
4a
.
Re
ce
ivin
g H
op
pe
r/M
ag
ne
tft
314
161
8,5
00
8,0
00
20
06
0.7
13,1
73
2.4
7$
32
,53
7$
41,
32
2a
.
Ro
tary
Dis
c S
cre
en
/Ho
pp
er
ton
s/h
r3
67
.44
20
03
5,0
00
20
06
0.7
61,
716
2.4
7$
152
,43
9$
193
,59
7a
.
Ha
mm
er
Mill
/ H
op
pe
rto
ns
/hr
166
.610
02
30
,00
02
00
60
.73
78
,72
42
.47
$9
35
,44
9$
1,18
8,0
20
a.
RD
S C
on
ve
yor
ton
s/h
r16
6.6
100
45
,00
02
00
60
.77
4,0
98
2.4
7$
183
,02
3$
23
2,4
39
a.
HM
Co
nv
eyo
rto
ns
/hr
183
.72
100
45
,00
02
00
60
.77
9,3
49
2.4
7$
195
,99
3$
24
8,9
10a
.
Do
zer
#1
yd3
18.4
18.4
40
0,0
00
20
06
14
60
,76
92
.47
$1,
138
,09
8$
1,4
45
,38
5a
.
Do
zer
#2
yd3
18.4
18.4
40
0,0
00
20
06
14
60
,76
92
.47
$1,
138
,09
8$
1,4
45
,38
5a
.
Re
cla
im H
op
pe
rto
ns
24
9.9
150
5,5
00
20
06
0.7
9,0
56
2.4
7$
22
,36
9$
28
,40
9a
.
Re
cla
im C
on
ve
yor
ton
s/h
r9
1.8
65
05
0,0
00
20
06
0.7
88
,16
62
.47
$2
17,7
69
$2
76
,56
7a
.
Fe
ed
Bin
ton
s2
75
.58
150
5,5
00
20
06
0.7
9,6
98
2.4
7$
23
,95
5$
30
,42
2a
.
Fe
ed
Co
nv
eyo
rto
ns
/hr
91.
86
50
40
,00
02
00
60
.77
0,5
33
2.4
7$
174
,216
$2
21,
25
4a
.
Lo
ck
Ho
pp
er
ton
s/h
r9
1.8
63
02
,115
,50
02
00
20
.76
,73
6,0
192
.47
$16
,63
7,9
67
$2
1,13
0,2
18a
.
Ga
sif
ica
tio
n a
nd
AS
U
Cry
og
en
ic A
ir S
ep
ara
tio
nk
g/s
95
% O
28
.216
.06
40
,318
,00
02
00
40
.62
53
4,3
16,9
32
Inc
lud
ed
$3
4,3
16,9
32
$4
3,5
82
,50
3a
.
GT
I Ga
sif
ier
ton
ne
s/d
ay
dry
fe
ed
1,8
80
82
95
,85
2,3
30
20
03
0.7
14,8
72
,86
51.
32
$19
,63
2,1
81
$2
5,9
14,4
79
a.
As
h C
yclo
ne
kg
/s g
as
46
.82
1.0
83
99
,60
22
00
70
.67
186
,14
62
.47
$4
59
,78
0$
60
6,9
10a
.
Ga
s C
lea
nu
p
Do
lom
ite
Gu
ard
Be
dk
g/h
r g
as
168
,65
95
7,6
51
219
,28
02
00
50
.75
71,
418
2.4
7$
1,4
11,4
03
$1,
86
3,0
52
a.
Ca
taly
tic
Ta
r C
rac
ke
rft
3/m
in g
as
19,1
52
10,0
00
1,4
04
,28
32
00
70
.72
,42
4,1
78
2.4
7$
5,9
87
,72
0$
7,9
03
,79
1a
.
Syn
ga
s C
oo
ler
(A,B
)M
Wth
28
77
25
,40
0,0
00
20
03
0.5
92
0,0
34
,15
01.
52
$3
0,4
71,
94
2$
40
,22
2,9
64
a.
Ca
taly
tic
Ca
nd
le F
ilte
rm
3/h
r3
78
20
518
40
8,3
71,
00
019
99
0.6
79
,98
4,6
98
2.4
7$
24
,66
2,2
03
$3
2,5
54
,10
8b
.
Ho
t G
as
De
su
lfu
riza
tio
nlb
mo
l/h
r18
88
02
120
84
,15
8,2
88
199
60
.75
,77
9,4
87
Inc
lud
ed
$5
,77
9,4
87
$7
,62
8,9
23
c.
Zn
O P
olis
hin
g B
ed
k
g/h
r g
as
117
,36
05
7,6
51
219
,28
02
00
50
.67
43
3,9
61
2.4
7$
1,0
71,
88
2$
1,4
14,8
85
a.
Wa
ter
Ga
s S
hif
t
Hig
h T
em
p W
GS
km
ol (
CO
+H2
)/h
r3
,718
8,8
1910
,70
0,0
00
20
02
0.6
58
,87
8,2
75
2.4
7$
21,
92
9,3
38
$2
8,9
46
,72
6a
.
Lo
w T
em
p W
GS
km
ol (
CO
+H2
)/h
r3
,717
8,8
1910
,70
0,0
00
20
02
0.6
58
,87
7,4
36
2.4
7$
21,
92
7,2
68
$2
8,9
43
,99
3a
.
H2
Pu
rifi
ca
tio
n
PS
A U
nit
km
ol/
s H
2 R
ec
ycle
1.2
06
90
.29
45
,37
0,0
00
20
02
0.7
42
2,2
13,8
10In
clu
de
d$
22
,213
,810
$2
9,3
22
,23
0a
.
H2 R
ec
ycle
Co
mp
res
so
rM
We
0.0
97
55
104
,74
8,5
82
20
02
0.6
73
10,5
53
Inc
lud
ed
$3
10,5
53
$4
09
,93
0a
.
H2 C
om
pre
ss
or
MW
e3
.54
104
,74
8,5
82
20
00
0.6
73
,44
6,0
76
Inc
lud
ed
$3
,44
6,0
76
$4
,54
8,8
21
a.
Blo
we
rm
3/s
air
52
.78
4.7
26
7,0
00
199
70
.64
24
,70
52
.47
$1,
04
9,0
21
$1,
38
4,7
07
a.
Ste
am
an
d P
ow
er:
HR
SG
+ S
tea
m C
ycle
MW
e3
6.3
85
05
0,0
16,0
00
20
08
0.6
43
40
,76
6,7
37
Inc
lud
ed
$4
0,7
66
,73
7$
51,
77
3,7
57
a.
PS
A P
urg
e G
as
Exp
an
de
rM
We
1.7
510
3,1
40
,00
02
00
30
.67
1,3
99
,29
3In
clu
de
d$
1,3
99
,29
3$
1,7
77
,10
2a
.
AS
U N
2 E
xpa
nd
er
MW
e3
.110
3,1
40
,00
02
00
30
.67
2,0
52
,511
Inc
lud
ed
$2
,05
2,5
11$
2,6
06
,68
9a
.
Co
mb
us
tio
n A
ir C
om
pre
ss
or
MW
e0
.74
104
,74
8,5
82
20
02
0.6
71,
20
7,0
86
Inc
lud
ed
$1,
20
7,0
86
$1,
53
2,9
99
a.
Bo
iler
(C)
m2
36
5.1
47
15.3
56
51,
153
20
07
0.5
94
79
,64
52
.47
$1,
184
,72
3$
1,5
04
,59
9a
.
Pre
he
ate
r (D
)m
24
25
.57
15.3
56
51,
153
20
07
0.5
95
24
,95
52
.47
$1,
29
6,6
38
$1,
64
6,7
30
a.
Pre
he
ate
r (E
)m
24
98
.06
715
.35
65
1,15
32
00
70
.59
57
6,0
60
2.4
7$
1,4
22
,86
8$
1,8
07
,04
2a
.
Co
nd
en
se
r (F
)m
213
9.9
57
15.3
56
51,
153
20
07
0.5
92
72
,39
52
.47
$6
72
,816
$8
54
,47
6a
.
Co
nd
en
se
r (G
)m
29
4.8
97
15.3
56
51,
153
20
07
0.5
92
16,5
85
2.4
7$
53
4,9
66
$6
79
,40
6a
.
Co
nd
en
se
r (H
)m
26
6.5
17
15.3
56
511
53
20
07
0.5
917
56
22
2.4
7$
43
3,7
87
$5
50
,90
9a
.
TIC
20
08
$2
66
,92
8,4
76
$3
47
,016
,79
7
120
Table Notes:
a. See corresponding note shown in previous table.
b. Cost data for a candle filter is discussed by Newby et al 2002. The hot gas filter
design is rated for 542ºC, 2620kPa, 19727 ppmw inlet dust load. Cost data is
based on volumetric flow rate of syngas [91].
c. Installed cost for an Advanced Hot Gas Process (AHGP) for Desulfurization.
Equipment includes: Desulfurization transport reactor, 3-stage bubbling bed
regeneration reactor, compressor, condenser, demister, heat exchanger, tanks
and pipes. Reactor costs are based on a bench-scale system given by Gangwal et
al 1998. Costs are dependent on reactor size which is dependent on steel price
[54].