United States
Environmental Protection
Agency
Air and Energy Engineering
Research Laboratory
Research Triangle Park NC 27711
Research and Development
EPA/600/S7-85/039 Apr. 1986
Project Summary
Computer Economics of Physical
Coal Cleaning and Flue Gas
Desulfurization
C. R. Wright, L Larkin, F. M. Kennedy, and T. W. Tarkington
Under EPA sponsorship, a computer
model has been developed by TV A that
determines process and detailed
economic data for a physical coal-
cleaning process and a limestone or
lime flue gas desulfurization (FGD)
process applied to electric utility
boilers. The model can be used to
determine the economics of either
process used alone or the two in various
combinations, based on user-supplied
data on cleaning requirements, coal
properties, and SO 2 emission
requirements. The model also
determines the indirect economic
benefits and penalties to overall power
plant operation associated with the use
of cleaned coal. The coal-cleaning
process consists of three processing
streams in which coarse, medium, and
fine coal fractions are cleaned by
respectively, dense-medium vessels,
dense-medium cyclones, and froth
flotation. Several variants of the
limestone or lime FGO process and
different waste disposal methods can
be specified for the FGD process. The
model provides an analysis of the
cleaned coal, a list of major FGO
equipment, and detailed capital
investment and operating cost data.
The report provides a general
description of the model, illustrates its
use and potential application, and
summarizes its use in a la.rge number of
simulations. Using a 1,000-MW boiler
as the basis, simulations were made
with four coals at four cleaning levels
and at four emission levels. The effects
of these variables on the economics of
the processes used separately and in
combination are discussed.
This Project Summary was developed
by EPA's Air and Energy Engineering
Research Laboratory, Research Triangle
Park, NC to announce key findings of
the research project that is fully docu-
mented in a separate report of the same
title (see Project Report ordering in-
formation at back).
Introduction
In recent years, coal cleaning has come
to be regarded as a practical alternative in
some cases for the control of SO 2
emissions from coal-fired power plants.
TVA recently completed an economic
evaluation for EPA that illustrated the
potential of coal cleaning in SO 2 emission
control. As a continuation of this
program, a computer model was
developed to model the performance and
economics of full-scale coal cleaning
alone and in combination with limestone
and lime FGD. The model determines the
process design and economics for a
coal-cleaning process or a coal-cleaning
process combined with FGD. It also
determines the economic benefits and
penalties attributable to the use of
cleaned coal instead of raw coal.
The model should be useful in
comparing process designs and
economics of various combinations of
coal-cleaning and lime or limestone FGD
processes. This should be particularly
useful when evaluating processes for
specific applications since the model will
illustrate the effect of changes in process
variables on the cost and design of the
component processes or the entire
system as a whole.
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Model Description
The coal-cleaning/FGD computer
model consists of four computer
programs (written in FORTRAN IV), linked
by common input and output data. The
first program determines process
performance and economics of the
coal-cleaning process from design and
operating specifications; the second and
third determine the FGD process design
and the corresponding capital investment
and annual revenue requirements from
raw or clean coal properties and emission
requirements; and the fourth quantifies
selected economic benefits and penalties
of using cleaned coal. Unlike the first
three programs, which are modified
versions of previously developed
programs, the fourth was created
specifically for this project. The cost
elements that the model calculates
include capital investment, first-year
annual revenue requirements, and
levelized annual revenue requirements:
each can be generated for either a
coal-cleaning process, a combined
coal-cleaning/FGD process, or an FGD
process, depending on user specifica-
tions. For the combined coal-cleaning/
FGD process, the net cost is the sum of
the costs for the coal-cleaning and FGD
processes and the sum of the benefits
and penalties.
Model Input Procedure
To simplify data entry for the combined
model, all data required for its execution
are included as input data to the
coal-cleaning program. The information
required includes power plant data,
emission regulations, coal-cleaning
process specifications, FGD design
specifications, raw coal properties and
washability, and economic data. The flow
of the data throughout the combined
model is shown in Figure 1.
Coal-Cleaning Program
The coal-cleaning program was
adapted from Battelle-Columbus
Laboratories Coal Preparation Simulation
Model (CPSM4), Version 2. The program
required many modifications to conform
to TVA's process design criteria and to
form the combined coal-cleaning/FGD
model. Although many of these changes
were relatively minor and did not alter the
program processing sequence, some
areas required major revisions, requiring
five new subroutines and associated
program rearrangement.
The printout is divided into three
segments: the first lists the values of
selected input data to ensure that no
All Input Data
Coal Cleaning
Process Printout
4
Coal Cleaning
Program
1
k
P
I
f
FGD Input Data
Benefits/
Penalties
Input Data
FGD Programs
Benefits/
Penalties Program
Benefits/Penalties
Program Printout
Figure 7. Flow of data through the combined model.
FGD Process
Printout
errors were made during the input
operation; the second (execution)
provides an analysis of internal flow
streams and a performance report for
each equipment unit included in the
coal-cleaning process; and the third
presents the overall results of the
simulation. The tables in this segment
provide the performance data and the
process economics for the coal-cleaning
plant.
The model can simulate many
coal-cleaning processes if equipment
performance, process design
information, and economic data are
available. The base case process design
used in the illustrative runs is felt to be
typical. The flow diagram for this process
design is shown in Figure 2. The process,
as illustrated, separates the raw coal into
three size fractions, each of which is
processed in a different type of separation
equipment: the coarse coal in a
dense-medium vessel, the intermediate
in a dense-medium cyclone, and the fine
in froth flotation cells.
FGD Model
The FGD model is the Shawnee
lime/limestone computer model
developed by Bechtel National, Inc., and
TVA using data obtained from the test
facility at the TVA Shawnee Steam Plant
near Paducah, KY. This model consists of
two programs that produce full-scale
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Coal Receiving
and Storage
Railroad
Car
[L—J| Dump
Raw Coal
Sizing
3/8 in x 20M
Coarse Coal
Cleaning
Intermediate
Coal
Cleaning
Fine Coal
Cleaning
Refuse
Disposal
Clean Coal
Storage
Pre-Wet
Screen
DW
Distributing
Tank
Dense Medium
Dense
3/8 'i'n'x ~2~8M ' 'Me'diu'rrT
yclone
DM Cyclone
Feed Sump
Drain Rinse
Screens
^Bottoms Tops\
i. t
Magnetic
Separator
.(Magnetite)
Flotation
Feed Sump
-» Flotation
Cells
Clarified Water
for Reuse
DM Sump
Dense Medium
Recirculation
System
Refuse Disposal Site
Water Surge Pond
Clean Coal
Stockpile
Coal
Refuse
Dense Medium
Dilute Medium Water
Clean Coal
Shipment
Figure 2. Flow diagram for the coal-cleaning process.
design and economic data for a variety of
limestone or lime FGD systems.
The current model includes options for
limestone or lime scrubbing: a mobile-
bed absorber (TCA), a spray tower or
venturi-spray tower absorbers, and
various waste disposal methods. The
FGD process design used to illustrate the
capabilities of the combined model is
illustrated in Figure 3. The process
employs limestone slurry scrubbing in a
spray tower absorber and the untreated
waste is disposed of in a pond.
Economic Benefits and
Penalties Program
Many differences between cleaned and
raw coal result in economic benefits and
penalties for a power plant other than the
obvious benefit of reduced FGD costs.
This program utilizes appropriate
equations to approximate many of these
benefits and penalties that accrue
because of such differences as a lower
ash content, a higher moisture content,
and generally a higher heating value of
the cleaned coal. Each of the benefits and
penalties calculated by this program is
discussed below.
FGD Costs
The most important effect of coal
cleaning on power plant costs is in the
area of FGD costs; in some cases coal
cleaning or coal cleaning with FGD can be
more economical than FGD alone in
controlling S02 emissions. The ways in
which coal cleaning reduces the FGD
requirement are much the same as the
other benefits. In particular, the reduced
sulfur content and increased heat
content of cleaned coal reduce the
quantity of SO 2 produced in the
combustion process, thus reducing the
SO2 removal requirement of the FGD
process. Sometimes the use of cleaned
coal can even eliminate the need for FGD.
The benefit that is used in this model is
determined by comparing costs required
when FGD is used to control raw coal
combustion emissions with the FGD
costs when the emissions from cleaned
coal combustion are controlled.
Raw Coal Loss
No presently available coal-cleaning
process can achieve 100% separation of
pure coal from its impurities. Some coal is
lost in the cleaning plant refuse, and
some impurities remain in the cleaned
coal. The coal that is lost is an economic
liability for the coal-cleaning plant. This
liability or penalty is quantified as the
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Emergency Bypass
Coa/_
Boiler
Economizer] Electrostaiic
I Precipitator
Scrubber Area
Spray Tower
Steam from
Steam Plant
\Reheater-ff—
''l.D. Fan
Condensate
.Makeup to steam Plant
Water
Absorber
Bleed
Receiving
Tank I—g
Figure 3. Flow diagram for the limestone-scrubbing process.
heat content (Btu's) of the coal that is lost
in the refuse.
Transportation Costs
In most cases coal cleaning produces a
product that has a higher heating value
than the raw coal, thereby reducing the
quantity of coal necessary to satisfy the
heat requirements of a specific power
plant. When coal is cleaned at the mine,
the reduced coal requirement decreases
the cost of transporting the coal, which is
a cost benefit for the utility.
United Mine Workers' Benefits
The 1978 United Mine Workers'
(UMW) contract requires mine operators
to pay $1.385 to the Pensions and Benefit
Trust Fund for every ton of coal shipped to
a consumer. Since coal cleaning
generally reduces the quantity of coal
required by a power plant, the
contribution to the trust fund is also
reduced, resulting in a cost benefit for the
utility.
State Taxes
State-imposed coal taxes, often called
severance taxes, are presently levied by
13 states. Depending on the method of
taxation, coal cleaning can reduce or
increase these taxes, creating a cost
benefit or penalty. At present, there are
four ways to apply these charges:
taxation based on the tonnage of coal
shipped is the most common. For this
reason, it is used in the example runs for
this project. Based on this method, coal
cleaning would generally yield an
economic benefit by reducing the
quantity shipped. On the other hand,
taxation based on the tonnage mined or
value of the coal shipped would produce
an economic penalty for coal cleaning
because of the coal loss in the cleaning
plant refuse.
Size Reduction
In general, at least two and sometimes
three size reductions are performed on
coal as it moves from the ground to the
4
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power plant boiler. For the development
of this program, it was assumed that the
power plant was equipped with
pulverized coal boilers, in which case
three size reductions are necessary. The
first reduction is at the mine: the run-
of-mine (ROM) coal is crushed to the
appropriate topsize. The next two
reductions are at the power plant: the
coal is crushed before being fed to the
pulverizers and then ground into powder
in the pulverizer and fed to the boiler.
When coal cleaning is used, an additional
size reduction is usually included,
resulting in a cost benefit to the utility
because the size reduction requirements
at the power plant are reduced. Coal
cleaning can also produce a benefit in the
size reduction operations at the power
plant by reducing the coal mineral matter,
making the coal easier to grind. Also, the
increased heating value of cleaned coal
decreases the amount to be ground. One
effect of coal cleaning, the increase in
surface moisture, can increase pulverizer
plugging, but it is not considered in the
program because of lack of data on the
effects of moisture.
Maintenance Costs
The quality and quantity of the coal
used in a power plant have long been
recognized as having a direct effect on the
maintenance costs of the plant
equipment. Some of the equipment areas
have been mentioned, but other areas
which must be considered include the
boilers and accessories, coal conveying
and storage equipment, and the air
heaters. Coal cleaning yields an
economic benefit in maintenance costs
for these and other areas of power plant
operation by raising the quality of coal
burned in the plant and by reducing the
ash and sulfur content. To quantify this
benefit, the program uses a relationship
based on the ash and sulfur in the coal
which is derived from actual power plant
maintenance data.
Power Plant Availability
The availability of a power plant for the
production of electricity is another area
that is affected by the use of cleaned coal.
Many of the factors relating to availability
(e.g., tube corrosion, sootblower failure,
slagging, and fouling) are influenced by
power plant age and mineral content of
the coal burned; therefore, they are also
influenced by the use of cleaned coal. It is
difficult to quantify the effects of coal
cleaning on availability because of the
influence of other factors unrelated to
fuel quality. In the program, the
availability benefit is quantified, using a
logarithmic relationship based on the
coal ash content, sulfur content, and
boiler age.
Boiler Efficiency
The efficiency of a power plant boiler is
often expressed in terms of the amount of
heat required to generate 1 kWh of
power. This characteristic of the power
plant is affected by coal cleaning in much
the same manner as availability, except
that: (1) the increased surface moisture,
inherent in cleaned coal, reduces boiler
efficiency, and (2) the coal sulfur content
does not appreciably affect efficiency. Of
the three factors affecting efficiency
(moisture content, ash content, and boiler
age), the coal moisture content effect is
the most pronounced. All of these factors
are included in the equation used by the
model to quantify this benefit (or penalty).
Electrostatic Precipitation
The major factor controlling the size
and cost of an electrostatic precipitator
(ESP) is the specific collection area,
which is determined primarily by the fly
ash resistivity and volumetric flow rate of
flue gas. Fly ash resistivity is directly
related to such factors as ash content,
ash composition, and sulfur content of
the coal. Volumetric flow rate is related to
the coal composition: carbon content,
hydrogen content, sulfur content, ash
content, and moisture content. Coal
cleaning, by altering coal properties, also
affects ESP capital and operating costs. In
most cases, the results are detrimental:
an economic penalty is imposed.
Ash Disposal
The costs of transporting and disposing
of the ash are decreased because coal
cleaning reduces the ash content of the
coal and generally increases the heating
value of the coal, both of which decrease
the quantity of ash to be disposed of at the
power plant.
Design and Economic Premises
The design and economic premises for
the combined coal-cleaning/FGD model
are based on premises developed by TV A
for economic evaluations of power plant
emission control processes. The
premises for the benefits and penalties
program were developed especially for
this model.
The base case assumes a new,
midwestern, 1,000-MW, pulverized-
coal-fired power plant supplied by a coal-
cleaning plant at a mine 500 miles* away,
with transportation by unit train. The
design heat rate of the boiler is 9,200
Btu/kWh, and it operates at full load for
5,500 hours a year for 30 years. The coal-
cleaning process incorporates three
cleaning streams: dense-medium vessels
for coarse coal (3 in. x 3/8-in.), dense-
medium cyclones for medium-sized coal
(3/8-in. x 28 mesh), and froth flotation for
fine coal (less than 28 mesh).
The cases studied are based on four
coals, selected characteristics of which
are presented in Table 1 with the
equivalent SO2 contents. Each coal is
cleaned by controlling the specific gravity
of the separating media at 1.40, 1.50,
1.60, and 1.80. The emission standards
evaluated consist of 0.6,1.2, 2.0, and 4.0
Ib SO 2 /106 Btu emission limits and the
1979 new source performance standards
(NSPS).
The economic premises are based on
regulated utility operations. Capital
investments, first-year annual revenue
requirements, and levelized annual
revenue requirements are determined.
The costs are projected to 1982 for the
capital investment and to 1984 for the
annual revenue requirements.
Results and Examples of Model
Use
To test the computational accuracy of
the model, selected results from the
model output have been compared with
the corresponding results obtained from
rrfanual calculations. This comparison
yields a maximum difference of less than
1.5%, which is well within acceptable
limits.
The results obtained from this model
can be used in many different ways,
including:
• To determine the most economical
method of SO 2 control using coal
cleaning, FGD, or a combination of
both.
• To illustrate the effects of changes
in process conditions on the
performance and economics of a
coal-cleaning, an FGD, or a
combined coal-cleaning/FGD
process.
• To analyze the effect of coal
cleaning on power plant operations
by considering various benefits and
penalties attributable to coal
cleaning.
"Readers more familiar with metric units may use the
conversion factors at the back of this Summary.
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• To compare the process
performance and economics for
different coal-cleaning and FGD
process designs.
These do not exhaust all possible uses,
but they do indicate potential uses of the
model.
The main objectives of this report are to
make potential users of this model aware
of its availability and to illustrate some of
its possible uses. To accomplish the
latter, the model was used to simulate a
range of conditions. Eighty runs were
made using the four premise coals, each
cleaned at four specific gravities of
separation, with the flue gas restricted to
five SO 2 emission limits. Other trial runs
of the combined model were made by
varying such conditions as cleaned coal
topsize, power plant megawatt rating,
and the distance from the cleaning plant
to the power plant.
Coal-Cleaning Operating
Performance
In a coal-cleaning plant, the specific
gravity of the medium in the cleaning
vessel is usually controlled to regulate
the properties of the cleaned coal. For this
reason, it is the input variable used in the
model to define the cleaning process
operating conditions. Among the
important plant performance parameters
determined by the specific gravity are the
yield, the reduction in sulfur emission,
and the Btu recovery. The yield (weight of
clean coal product divided by the weight
of raw coal feed) is an indirect measure of
the amount of material which is mined,
processed, and later discarded as refuse.
The reduction in sulfur emission
parameter is a function of the reduction in
ash and pyritic sulfur as determined by
the physical desulfurization (washability)
of each coal. The Btu recovery is the
percentage of the Btu content of the raw
coal that remains when the coal is
cleaned. It is a measure of both the
cleaned coal properties and the
economics of the process since the Btu
loss in the refuse is an important
economic factor in coal cleaning.
The relationships between specific
gravity of separation and the resulting
yield reduction in sulfur emission
parameter and Btu recovery are shown in
Table 2. Yield and Btu recovery decrease
as the specific gravity of separation
decreases. This is to be expected because
the amount of ash and pure coal lost to
the cleaning plant refuse increases as the
specific gravity decreases. The sulfur
reduction increases as the specific
Table 1. Selected Characteristics and Equivalent SOz Contents of the Premise Coals
Coal
Illinois No. 6
Pittsburgh
Upper
Freeport
Cedar Grove
Pyritic
Sulfur,
%
3.27
2.15
1.88
N.A.
Total
Sulfur,
%
4.34
3.67
2.32
0.85
Ash.
%
29.39
13.81
16.80
16.04
Moisture.
%
1.36
3.42
5.60
6.60
Heat
Content.
Btu/lb
9.667
12,121
11.668
1 1.680
Equivalent
SOz Content
in Coal. Ib
SO2/ 10* Btu
8.97
6.05
3.97
1.45
Basis: All values are on an as-received basis.
Table 2. Sulfur Reduction and Btu Recovery by Coal Cleaning
Raw
Coal
Coal-Cleaning Operating,
Specific Gravity
1.4
1.5
1.6
1.8
Illinois No. 6 Coal
Yield. %
Ib SOz/10* Btu*
Sulfur reduction. %
Btu recovery, %
Pittsburgh Coal
Yield. %
Ib SOz/'10* Btu*
Sulfur reduction, %
Btu recovery. %
Upper Freeport Coal
Yield. %
Ib SOz/'10s Btu*
Sulfur reduction, %
Btu recovery, %
Cedar Grove Coal
8.97
6.05
3.97
56
3.86
57
78
73
3.79
37
82
67
1.76
56
78
65
4.18
53
88
83
4.18
31
92
78
1.93
51
89
68
4.38
51
92
86
4.37
28
95
82
2.03
49
93
73
5.08
43
96
91
4.68
23
97
88
2.35
41
97
Yield. %
lbSO2/10eBtu*
Sulfur reduction. %
Btu recovery, %
_
1.45
-
-
78
1.17
19
91
80
1.20
17
93
81
1.23
15
95
83
1.25
14
96
"Assuming 100% conversion of sulfur to SOa.
gravity decreases due to the increased
pyritic sulfur removed. The result is a
tradeoff between high-Btu recovery and
high-sulfur removal.
FGD Operating Performance
The FGD process design used in this
illustration removes 90% of the SO2 in
the flue gas that is scrubbed. If the overall
SO 2 removal requirement of the FGD
system is less than 90%, a portion of the
gas is bypassed to allow the scrubber to
operate at the 90% removal level. The
bypassed flue gas is then combined with
the scrubbed flue gas to reduce the steam
requirements for reheating (which is
often the single largest energy
requirement of an FGD process). For this
reason, the amount of bypass is the most
important FGD operating condition
affecting the FGD design. The portion of
flue gas bypassed is determined by the
emission limit, the heating value, the
sulfur content of the fired coal, and the
sulfur content of the ash.
Economics
One possible use of the combined
computer model is to determine the
combination of coal cleaning and FGD
that will meet a specified emission limit at
the minimum overall cost. The operating
conditions for this optimum combination
are not the same for every case because
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they can change with variations in coal
properties, process characteristics (e.g.,
washing equipment efficiencies), and the
particular cost element chosen for the
analysis.
Capital Investment
The changes in capital investment for
coal-cleaning, FGD, and the other
economic benefits and penalties are
shown as a function of Btu recovery in
Figure 4. These cases are for Pittsburgh
coal with a 1.20lb S02/106 Btu
emission limit. In terms of change in
capital investment, coal cleaning has a
large effect on FGD. The net capital
investment, considering all three
components, is lower for the combined
coal-cleaning/FGD process than for FGD
alone over much of the range of coal-
cleaning conditions used. The minimum
in the net capital investment curve
indicates that an optimum set of cleaning
conditions does exist with respect to
capital investment. For the conditions
used in Figure4, the minimum occurs ata
Btu recovery of approximately 75%. The
specific gravity of separation equivalent
to this recovery represents the conditions
at which the system should be designed
to minimize capital investment.
Annual Revenue
Requirements
The levelized annual revenue
requirements for the same cases are
shown in Figure 5. Coal cleaning has the
same general effect on FGD annual
revenue requirements as it has on FGD
capital investment—a continuing decline
as the level of coal cleaning increases.
For the other benefits and penalties,
however, there is an initial decline,
followed by rapidly increasing annual
revenue requirements (because of the
Btu loss) as the coal-cleaning level
increases. The combined coal-
cleaning/FGD process thus has lower
annual revenue requirements than FGD
alone only for a certain range of coal-
cleaning conditions—in this case from
about 80% to near 100% Btu recovery.
Thus, the decision to use coal cleaning
with FGD often depends on the other
economic benefits and penalties that are
associated with coal cleaning.
Comparing the curves in Figures 4 and
5, each curve has a minimum cost point,
but these minimums do not exist at the
same Btu recovery. The curve for the net
capital investment has a minimum at
approximately 75% Btu recovery, while
the net annual revenue requirements
curve has a minimum at 93% Btu
recovery. The shift in minimum cost point
for the annual revenue requirements is
largely due to the large effect of Btu loss
on annual revenue requirements as Btu
recovery decreases. The minimum point
depends on the value assigned to the coal
lost in the refuse: in this example, a cost
of $20.81/ton was used; a different cost
would correspondingly shift the
minimum point toward a lower or higher
Btu recovery.
Figure 6 illustrates the reduction in
levelized annual revenue requirements
for the four coals at different SO2
emission limits as compared to sulfur
removal with FGD alone. Significant
differences in levelized annual revenue
requirements result from differences in
coal washability. Also, the economics
generally become more favorable as the
SO 2 emission limits become less
stringent; however, the curves for the
Cedar Grove and Upper Freeport coals do
have a maximum point beyond which the
economics become less favorable. These
maximums are at the points where the
optimum pollution control process
changes from a combined coal-
cleaning/FGD process to a coal-cleaning
process, alone. The curves for the Illinois
No. 6 and Pittsburgh coals did not reach
the point at which coal cleaning could
provide the most economical pollution
control process without some degree of
FGD being necessary.
Project Conclusions and
Recommendations
A computer model able to calculate the
economics of coal-cleaning processes
alone and combined with FGD in utility
applications has been developed.
Selected values from the model agreed
closely with those from manual
calculations.
The illustrative runs using four premise
coals had coal-cleaning sulfur removals
from 14% to 57% and met some less
stringent emission limits without FGD.
The combined coal-cleaning/FGD
process for each coal had a specific
gravity of separation at which costs were
at a minimum. Coal cleaning reduced the
FGD costs in all cases, primarily by
allowing more flue gas to be bypassed. In
some cases, this reduction in FGD costs
offsets the costs of coal cleaning. Case-
by-case comparisons must be made to
determine the most economical
approach.
For the cases studied, it was found that
the use of coal cleaning in combination
with FGD can have a varied effect on the
levelized annual cost of power
i
60-
40-
20-
0--,
.? -20-
I -40-
-60-
Coal Cleaning
Net
'OtHeT
Benefits andPenalties
70
Figure 4.
80 90
% Btu Recovery
100
Effect of Btu recovery on the net
total capital investment. Pitts-
burgh coal at 1.20 emission
limit.
production. This effect, which depends on
the coal and the specific operating
conditions, ranges from a 0.5% increase
to a 22.6% decrease.
The methods used to determine many
of the other economic benefits and
penalties of coal cleaning are necessarily
Coal Cleaning
Other Benefits
and Penalties
80 90
% Btu Recovery
100
Figure 5.
Effect of Btu recovery on the net
levelized annual revenue require-
ments. Pittsburgh coal at 1.20
emission limit.
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general in nature because detailed data
relating specific coal properties to boiler
performance and operating costs are
scarce. Thus, development and
incorporation of more detailed and
quantitative data in the model would
greatly increase the usefulness of the
model in assessing overall economic
effects of coal cleaning. Similarly, the
scope of the model could be increased by
incorporating other coal-cleaning
processes and alternate emission control
processes such as fabric filter baghouses
and spray dryer FGD and by modifying the
functions to allow multiple simultaneous
simulations. The economics of retrofit
situations should also be considered.
Conversion Factors
Readers more familiar with the metric
system may use the following to convert
the nonmetric units used in the
Summary:
Nonmetric
Times Yields Metric
Btu
in.
Ib
mi
ton
1.055
2.54
0.454
1.609
907.2
kJ
cm
kg
km
kg
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