United States
Environmental Protection
Agency
Air and Energy Engineering
Research Laboratory
Research Triangle Park, NC 27711
Research and Development
EPA/600/SR-94/017 May 1994
EPA Project Summary
State Acid Rain Research and
Screening System Version 1.0
User's Manual
C. A. Bogart, S. J. Epstein, K. S. Piper, and A. S. Taylor
This project summary describes Ver-
sion 1.0 of EPA's STate Acid Rain Re-
search and Screening System
(STARRSS). The system was developed
to assist utility regulatory commissions
in reviewing utility acid rain compliance
plans.
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 infor-
mation at back).
introduction
The acid rain provisions included in Title
IV of the 1990 Clean Air Act Amendments
(CAAA) mandate that many electric utili-
ties substantially curtail their sulfur dioxide
(SO2) emissions by 1995with even more
stringent environmental limits taking effect
in the year 2000. These affected utilities
must file compliance plans with EPA and
state public utility commissions to indicate
how they intend to reduce their SO2 emis-
sions to allowable levels. As they review
these compliance plans, state regulators
will play a critical role in determining the
success of the CAAA. Whether they are
asked to formally preapprove compliance
plans or not, commissions will have con-
siderable influence over utilities' compli-
ance decisions. Therefore, in determining
what constitutes a "good" compliance plan,
commissions will have to address the fol-
lowing questions:
Is the utility's preferred plan the least-
cost solution?
How risky is the utility's preferred plan?
What other compliance strategies
should the utility be considering?
Should the utility be a buyer or a
seller in the SO2 allowance market
and to what extent?
STARRSS is an integrated information/
modelling system that is designed to as-
sist state regulatory commissions and utili-
ties in answering these questions.
A Compliance Planning Model
Funded by EPA's Air and Energy Engi-
neering Research Laboratory (in Research
Triangle Park, NC), STARRSS is a screen-
ing tool that allows analysts to compare
the cost-effectiveness of a wide variety of
acid rain compliance options, including:
Scrubbing
Repowering
Fuel switching/blending
Cofiring
Combustion technologies
(e.g., sorbent injection)
Emissions allowance purchases
Conservation
New, cleaner resources
Improved boiler efficiency
Emissions dispatch
Designed to run quickly on a personal
computer (an IBM PC AT or IBM-compat-
ible PC with an 80286 processor or bet-
ter), STARRSS focuses on the compre-
hensive analysis of many compliance strat-
egies. As a decision support tool,
STARRSS uses a multiple-scenario, risk-
assessment approach. The model uses
three user-specified forecasts (high, me-
dium, and low forecasted values) for most
input data items (e.g., price forecasts, tech-
nology costs, and performance). Through
Printed on Recycled Paper
-------
a Monte Carlo process, STARRSS then
simulates hundreds of different scenarios
for a particular compliance strategy, se-
lecting one of these three values during
each scenario (based on user-specified
probabilities). Therefore, a strategy is ex-
posed to the uncertainties of future events
(e.g., varying allowance prices, fuel prices,
construction costs, generating unit operat-
ing characteristics). These multiple simu-
lations yield a distribution of cost esti-
mates that represent the range of pos-
sible costs for a compliance strategy.
Working with this distribution, the user
can see the level of economic or business
risk that Is inherent in a particular compli-
ance strategy. Just because a strategy
has a low expected cost (as measured by
the average of the cost distribution) does
not necessarily make it a desirable plan.
For example, a STARRSS analysis of
Strategy A may have an expected value
of $2 billion, plus or minus $0.5 billion. In
other words, considering potential fluctua-
tions In the fuel and allowance markets
and other parameters, Strategy A is likely
to cost between $1.5 and $2.5 billion.
Strategy B has a cost of $2.1 billion, plus
or minus $0.1 billion. If one simply chose
the optimal strategy based on a compari-
son of the plans' expected value for com-
pliance costs, then one would pick Strat-
egy A as the better plan. However, Strat-
egy B is less risky, because it has less
variance in its total costs. A utility or state
commission may want to choose Strategy
B, realizing that the likely economic expo-
sure is capped at $2.2 billion, whereas
there may be a substantial probability that
Strategy A could cost as much as $2.5
billion.
In terms of a graphical explanation, Fig-
ure 1 shows the cost distributions for two
hypothetical compliance strategies. While
the Fuel Switch strategy has an expected
(I.e., average) cost that is less than for the
Scrub BlgCoal 1 strategy, it also has
greater cost volatility. Comparisons such
as these allow the user to identify the
cost-versus-risk trade-offs that often arise
in the course of compliance strategy de-
velopment.
Two examples of the many input and
reporting screens in STARRSS follow. Fig-
ure 2 shows one of the input screens in
which the user specifies the following op-
erational information for each of a utility's
affected units: unit capacity, heat rate, and
baseline heat consumption (the average
annual fuel consumption for 1985-1987,
which is used in the CAM as a baseline
for calculating allowance allocations and
bonus allowances). In addition, the user
specifies the number of Phase I and Phase
n Fuel Switch
+ Scrub BigCoal 1
200 I 400 I 600 « 800
100. 300 _., 500 _ _700.^ _
j $ Million '
Figure 1. Comparison of total cost distributions for two compliance strategies.
Unit
Name
BIGCOAL 1
BIGCOAL 2
MEDCOAL 1
MEDCOAL 2
MEDCOAL 3
MEDCOAL 4
SMALLOIL 1
SMALLOIL 2
SMALLOIL 3
i Affentfiri Units snrean 1 nl 1 _ .
Database Name: SULFUR POWER & LIGHT
Baseline Calculated
Capacity
(MW)
650.0
650.0
350.0
350.0
350.0
350.0
50.0
50.0
80.0
Heat
Rate
10000
10000
10500
10600
10400
10400
13800
13600
13500
Heat
(TBTUs)
26.700
27.300
32.320
32.800
32.860
32.260
0.370
0.640
1.040
Enter Text
SO2 Emis.
(tons)
75293
84761
44656
46244
44424
7984
77
115
171
Allowances
Phasel
36500
37000
44000
44500
45000
0
0
o
0
Phasell
14000
14500
17500
18000
18000
17500
200
330
600
F1 Help
Figure 2. Display/edit affected units screen.
II allowances in a unit's basic allocation.
The Calculated |SO2 Emissions field is a
calculated estimate of the unit's current
SO2 emissions and is based on informa-
tion specified on! this and other screens.
To facilitate the process of database
development arjd refinement, databases
have been developed to model all of the
major utilities affected under the CAAA.
These databases contain publicly avail-
able information^ for all of the above gen-
erating unit characteristics and allowance
allocations. Relevant databases will be in-
cluded with each STARRSS delivery to
serve as a starting point for further data-
base development. State commissions will
ESC Menu
receive databases for all utilities within
their jurisdictions, including multi-state
holding companies and power pools.
For any affected unit, the user can
specify that the unit is a candidate for a
limitless range of compliance activities
(e.g., fuel switching, cofiring, repowering).
For any compliance option, the user can
dictate any of the following applicable en-
tries:
New fuel or fuel blend
SO2 removal efficiency of a technol-
ogy
Capital costs
-------
Increased non-fuel variable operating
and maintenance (O&M) costs
Increased fixed O&M costs
Increased non-operating costs
Capacity derations (or capacity in-
creases)
Boiler efficiency improvements or
losses
In-service year and option life
Except for the first and last items, these
data inputs can be entered as triple fore-
casts (high, medium, and low), as dis-
cussed earlier. STARRSS will determine
the cost-effectiveness of different compli-
ance strategies by analyzing each plan's
present value of revenue requirements
over a user-specified time period. Instead
of just calculating a single cost for a plan,
STARRSS will run hundreds of scenarios
using different combinations of each data
item's triple forecasts in order to develop
a full range of costs. This multiple-sce-
nario analysis is important considering that
compliance costs are strongly dependent
on future market conditions, which are
inherently uncertain. STARRSS will ana-
lyze the interaction of different combina-
tions of options with the allowance mar-
ket, bulk power market, and utility energy
conservation efforts.
STARRSS can be run in one of two
operating modes: evaluation or optimiza-
tion. In an evaluation run, the user speci-
fies one or more compliance strategies to
be evaluated and compared. In an optimi-
zation run, the user lets STARRSS de-
velop its own compliance strategies. How-
ever, no single strategy can be declared
optimal since exact future costs and per-
formance are uncertain. Therefore, the
STARRSS optimization approach involves
the selection of a set of top plans from a
list of potentially billions of compliance
strategies. The number of plans in this set
is determined by the user. STARRSS then
evaluates these top plans under a range
of economic and operational uncertainties
(e.g., changing fuel prices, allowance
prices, generating unit operations).
That STARRSS ranks the plans based
on the expected value of compliance costs
does not imply that the least-cost plan is
best. The risks that STARRSS quantifies
(i.e., the cost ranges) also must be taken
into consideration in determining the best
strategy. The level of risk that a utility is
willing to bear is a major factor in the
decision to adopt an emissions reduction
option. Therefore, STARRSS' No. 1 plan
may not be the appropriate choice if the
strategy's risks are too great.
Figure 3 is an example of a STARRSS
output report. The Compliance Strategies
Detail Report shows the expected value
of the costs and SO2 emissions reduction
impacts for the compliance options in all
of the top strategies. The first column of
f numbers displays the total present value
costs over the life of each option. The
second column reports the average an-
nual emissions reduction impact (or bo-
nus allowance allocation) that is attribut-
able to each compliance option. The final
column is a measure of each option's $/
ton cost (on a levelized basis; therefore, it
is not merely the first column's numbers
divided by the second).
Other reports show the range (and sta-
tistical standard deviation) of the costs
and impacts of compliance options and
overall strategies. These statistics allow
the user to assess the relative economic
and performance risks among different
compliance options and strategies.
STARRSS also includes graphical report-
ing features similar to those shown in Fig-
ure 1 that displays the cost profiles and
allowance trading activity of selected com-
pliance strategies.
Conclusion
STARRSS is an acid rain compliance
planning modelling system that provides
decision-makers with a means of compar-
ing the range of outcomes for a variety of
utility compliance strategies. The central
objective of the STARRSS system is not
to identify the best compliance strategy
for decision-makers, but to provide a deci-
sion-support screening tool that will help
organizations identify good strategies (i.e.,
low cost, combined with acceptable levels
of risk) that deserve further detailed analy-
sis.
Compliance
SULFUR POWER & LIGHT
Evaluated 7/30/1992 at 14:15; Phase I
Strategies
1: SCRUB BIGCOAL1 &2
BIGCOAL 1 WETFGD1
bonus allowances
BIGCOAL 2 WETFGD1
bonus allowances
Link BCOAL 1&2 GROUPFGD1
Base Conservation
bonus allowances
Allowance purchases (sales)
Totals for strategy 1 :
strategies ueiail hepon 1
Target Reduction 79809 Tons
run with 250 iterations
Total
Cost ($M)
315
315
(44)
(211)
376
Impact (tons)
63136
6695
63136
6695
266
45
(60165)
79809
Average
$/ton
477
477
375
495
* - Allowance transactions meet or exceed user-specified limits
ESC Main Menu
PgUp/PgDn View Report
F3 Print Report
Figure 3. Compliance strategies detail report screen.
ku.S. GOVERNMENT PRINTING OFFICE: 1*94 - 5M467/M2M
-------
C. A. Bogart, S. J. Epstein, K. S. Piper, and A. S. Taylor are with RCG/Hagler, Bailly,
Inc., Boulder, CO 80306.
Christopher D. Geron is the EPA Project Officer (see belo\v).
The complete report, entitled "State Acid Rain Research and Screening System
Version 1.0 User's Manual," (Order No. PB94-152550; Cost: $36.50, subject to
change) will be available only from: I
National Technical Information Service '<
5285 Port Royal Road I
Springfield, VA 22161
Telephone: 703-487-4650
The EPA Project Officer can be contacted at:
Air and Energy Engineering Research Laboratory!
U.S. Environmental Protection Agency \
Research Triangle Park, NC27711
United States
Environmental Protection Agency
Center for Environmental Research Information
Cincinnati, OH 45268
Official Business
Penalty for Private Use $300
EPA/600/SR-94/017
BULK RATE
POSTAGE & FEES PAID
EPA
PERMIT No. G-35
------- |