***APPENDIX A\--Modeling***

**[Model Description]{.underline}**

[Model Logic]{.underline}

ABB developed the MarketSimulator model to predict the economic and
physical performance of large power networks on an hourly basis. The
application was designed to produce:

-   Market clearing prices -- produces estimated forward price curves
    that vary by location (bus or node), including spot energy and
    shadow transmission price curves

-   Generating resource dispatch -- estimates the lowest cost dispatch
    for the Western Interconnection

-   Estimated congestion -- demonstrates where transmission bottlenecks
    may occur

-   Transmission expansion -- shows system-wide effects of proposed
    transmission development

-   Various sensitivities -- allows the user to examine events/scenarios
    that would introduce volatility in bulk power prices.

For this SSG-WI report, MarketSimulator is used to simulate transmission
congestion and to estimate congestion costs at the nodal level on a
West-wide basis. The model accomplishes this through means of an
algorithm that dispatches generating resources such that total West-wide
production costs are minimized. This dispatch algorithm matches hourly
generation to hourly loads and losses while taking into account:

-   transmission constraints; and

-   capacity, energy constraints (hydro, wind), outages, and minimum up
    and down periods of generating resources.

To minimize system production costs, the model takes into account
variable fuel costs, heat rates (thermal plants), and variable O&M
costs. Production costs and nodal prices are catalogued for each hour of
the study year.

The model yields an optimal dispatch of generation, corresponding power
flows, and resulting nodal price information. Specifically:

-   Hourly dispatch for each generating unit;

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-   Hourly production costs

-   Hourly flows and flow duration curves

-   Net import, load and generation for each area

-   Congested paths/lines

-   Transmission Shadow Prices

-   Locational marginal prices for loads and generators; and

-   Locational shadow prices.

Large amounts of load and resource data are required to model West-wide
system operations on an hourly basis at the nodal level. To keep the
modeling efficient and flexible, certain simplifying assumptions were
made to data inputs and modeling. For

**Figure A-1: MarketSimulator Algorithm** ![](media/image1.wmf)

example, contractual terms and conditions for power purchases and sales
and for wheeling were not taken into account. Simplified heat rate
factors rather than detailed, plant-specific heat curves were applied to
thermal units. Bidding behavior was not modeled. The simplifying
assumptions do not, however, detract from the screening purposes being
served.

As noted earlier, the scope of this SSG-WI study does [not
consider]{.underline} the capital costs of generation or demand-side
alternatives to mitigate congestion. The study also does not evaluate
the risks associated with future fuel prices or environmental
regulation.

Figure A-1 depicts the logic flow of the MarketSimulator algorithm. The
dispatch algorithm solves each hour's dispatch through a technique known
as delayed constraint generation, iterating between a linear programming
(LP) solver and a power flow calculator, as shown. The LP solver
produces a candidate dispatch, which then is evaluated for feasibility
by the power flow calculator. If the associated power flow violates any
transmission constraints, the constraints are added to the LP
formulation, and the process continues until convergence is obtained.

[Model Inputs]{.underline}

Monthly peak and energy forecasts are obtained for each area modeled in
the power flow. Historic hourly load shapes are used to transform the
monthly load data into an hourly loads fit to this peak and energy
forecast. Nodal demand is determined at each hour by imposing/fitting a
set of load distribution factors obtained from a WECC power flow case
onto load shapes selected to describe control area demand patterns.

Economic preference for each thermal generating unit is specified by a
piecewise linear incremental heat rate model, time varying fuel costs
and variable O&M costs. Capacity and outage information for each unit
are also specified as input data. The previous material describes the
economic dispatch capabilities and algorithm of Market Simulator.
Dispatch determines the loading of resources; predicting the on/off
schedule of the thermal units is known as unit commitment. At run time,
the user has two options regarding unit commitment:

-   Disabled: In this mode, all units not on outage are assumed
    available for dispatch. Units on must-run status have dispatch lower
    bounded by the normal unit minimum level. Units on fixed dispatch
    are locked to their assigned schedule. All other thermal units are
    made available for dispatch from 0 MW to normal unit maximum
    capacity.

-   Enforced: The current version of MarketSimulator features a
    multi-area priority list unit commitment method that reflects known
    transmission constraints when the transportation model is invoked to
    model the WECC. Both minimum up- and down-times are considered.

Transmission constraints take the form of thermal limits on AC lines and
bi-directional security constrained flow limits on interfaces.
Interfaces are sums of flows on sets of lines, known elsewhere as branch
groups or nomograms.

[Hydro Modeling]{.underline}

MarketSimulator is limited when it comes to hydro modeling and
optimization. However, the model accepts hourly hydro shapes and treats
them as fixed values. For the SSG-WI studies, an external algorithm was
used to shape hydro.[^1]

The external algorithm used for hydro shaping can be described as a mix
of peak shaving and "pseudo" run-of-the-river. It uses hydro resources
to level the load shape without regards to the existence of other
resources. The run-of-river hydro energy is modeled as base load energy;
whereas the dispatchable "monthly" hydro energy dispatches to shave
system peak load. Hydro power plants are scheduled one at a time over
the horizon of the week, subject to hourly constraints for minimum and
maximum generation, weekly constraints for ramp rates, and total energy.

A price-leveling algorithm is used to schedule pumped storage units
before the economic dispatch algorithm commences. While respecting pond
capacity limits, each pumped storage plant is scheduled in alternating
'blocks' of generation and pumping energy until the expected local
marginal price ratio does not compare favorably with the cycle
efficiency of the unit.

[Wind Modeling]{.underline}

The output of the Foote Creek wind project in Wyoming formed the initial
basis of wind data entered into the model. Based on a statistical
analysis of the wind resource distribution pattern over a typical year
of the project we developed a probability distribution curve showing the
probability of output for each hour, calculated as a percentage of the
wind farm's capacity. In order to reflect inherent electrical and
mechanical system losses the maximum output of the wind plant was
limited to 86% of rated nameplate capacity.

The capacity factor for wind generation is highly site specific.
Therefore, using best available data, each wind plant modeled was
assigned a series of values for its capacity factor, depending on the
diurnal and seasonal variations in the wind resource at that location.
These were defined in a 4 x 4 matrix of values for each plant, detailing
specific values for four time periods during the day (midnight to 6 am,
6 am to noon, noon to 6 pm, and 6 pm to midnight) for each of the four
seasons. Then, based on the characteristics of the standard probability
distribution curve, each of these "average" capacity factors was
randomized to generate a unique hourly time series with 8,760 values per
year, as required for input to the model. In this way, all of the sites
will exhibit a similar shape to their output distribution curve, but
with a temporally and geographically specific average capacity value.
The total hourly output of all wind plants in each geographical region
was aggregated, and interconnected to the grid at a spot that
represented the modelers' views of the "center of gravity" of the
various wind farms in that region.

While this process sounds very precise, it is important to understand
that it is extremely difficult to generalize the behavior of individual
wind farms across [any]{.underline} geographic region, and that the raw
wind resource data used to generate these time series over this broad
geographic scope is not robust. There are several fundamental weaknesses
we have identified in this modeling approach. First, because of the
random way in which hourly output was generated, there is no correlation
between output values from nearby sites or from prior time intervals. In
actuality, the best predictor of wind output in any one hour is the
output in the last hour. Using a random method to determine the hourly
output limits the number of contiguous hours that wind is either at a
high level or low level. It also does not model the likelihood that the
wind output from a wide area may increase or decrease simultaneously
because of synoptic weather patterns. Therefore, the results may show
wind's contribution to congestion to be lower than it actually is at
some times and higher than it actually is at other times.

Second, the probability distribution curve created was based on the wind
characteristics for a single site, and does not necessarily represent
the distribution curve that would be expected at any other location. For
this approach to gain greater validity, additional distribution curves
would have to be developed for each site that is subject to a unique
wind regime.

As the primary goal of this analysis is to identify the impact that wind
generation could have on transmission congestion, we felt that it was
important to in some manner represent the intermittent nature of the
wind resource, rather than using steady-state, average output values.
Given the relative lack of sensitivity of the overall modeling results
to these specific assumptions, this treatment is directionally correct
and suitable for this screening exercise. However, uncritical use of
this data set for more targeted evaluations of specific projects or
follow on detailed planning is not recommended.

[Distributed Generation/Demand Response]{.underline}

Distributed generation and/or demand response is not explicitly modeled.
Non-wires alternatives are considered qualitatively using some of the
studies run for this evaluation.

# [Model Limitations]{.underline}

[LMP Costs may be too Low]{.underline}

In MarketSimulator, the LMP differences become muted when looking across
cases because the program looks only at variable costs and does not
factor in costs associated with bid behavior (e.g., when the snow pack
is low, market prices would likely be more than variable costs). In
addition, the hydro peak shaving algorithm schedules a considerable
percentage of the hydro hours at the minimum output level from the hydro
power plants, which does not typically reflect actual hydro operations.
Thus, peak shaving may underestimate the use of thermal peaking units,
thus lowering peak hour LMP estimates. On the other hand, hard-wiring
hydro generation may underestimate the flexibilities of hydro generation
resulting in LMP costs that are too high.

[Competitive Market Assumption]{.underline}

The model assumes a fully competitive market in which all generators bid
their marginal cost into a market clearing price IFM (Integrated Forward
Market), do not engage in strategic bidding, withholding of any
generator capacity or otherwise exercise market power or influence
prices in the market. Likewise, it is assumed that all demand is price
inelastic, and buyers do not engage in strategic or price influencing
behaviors. Modeling such behavior is beyond the capabilities of
available software, and in any event would be subjective and an
invitation for unnecessary debate.

Never-the-less, it is only reasonable to assume there is or will be some
strategic behavior in the market, which will reduce overall market
efficiency and increase overall market costs. Transmission capacity,
however, is the great equalizer. To the extent there is congestion on
the grid, almost by definition there are opportunities for strategic
behaviors and some inefficiencies that are not modeled. Since the thrust
of the SSG-WI/sub-regional modeling efforts is the evaluation of new
transmission, the construction of which will eliminate or mitigate
congestion to some degree. A more robust transmission will tend to
mitigate strategic behaviors. Therefore, there are benefits of the
transmission upgrades, which are not captured and quantified by the
analysis.

[Must Run Generation Not Modeled]{.underline}

The RMR (Required-Must-Run) generators are not modeled as must-run
generators, which might underestimate the production costs of more
expensive, less efficient generators in an import zone. In other words,
the simulation may over-estimate the amount of more expensive, less
efficient generation that could be displaced by cheaper imports if a new
transmission line were built. The efficient OPF (optimal power flow)
dispatch simulation would dispatch the RMR generation to serve load
whenever the cost of this generation is low enough to include in an
efficient dispatch. However, RMR generation may be required to be
dispatched even when this results in an inefficient dispatch for the
following reasons:

-   They are in an import load pocket or a load pocket that would exist
    after an N-1 contingency;

-   Voltage constraints require that they be operated.

The OPF will instead dispatch more efficient resources, some of which
will be imports made possible by the proposed new line, when this would
not actually be acceptable if all operating constraints were taken into
account.

Lower voltage line limits were not active in the model. Activating them
might address part of the problem, but omission of RMR N-1 security and
voltage constraints may still raise questions. However, it is possible
that excess economical power dispatched from import resources would be
present in the base case before addition of the proposed new
transmission line such that the incremental benefits of the new line are
not distorted or over-estimated. It is also possible that the proposed
new lines themselves, or that network upgrades that will be needed to
deliver additional imports associated with the new lines will reduce the
need for RMR contracts and produce an economic benefit that has not been
captured.

[The OPF Dispatch Not Security-Constrained]{.underline}

In California, the Cal ISO's MD02 market is going to use a
security-constrained dispatch and unit commitment. This means the
dispatch will not only be constrained to prevent loading transmission
lines beyond their normal (continuous) rating, but the dispatch will be
constrained to prevent, for example, N-1 contingency loading beyond the
overload (emergency) rating of lines. For example, suppose there are 2
parallel lines with supply at one end and demand at the other. Both
lines are rated 100 MW normal with a 120 MW emergency rating. A dispatch
that is not security-constrained will dispatch the system to send 200 MW
over the parallel lines, if this is the economic solution. A
security-constrained dispatch will only dispatch 120 MW over the
parallel lines since following an N-1 contingency of one of the lines,
this is the maximum that could be reliably carried by the remaining
line.

Although the simulation software does not determine security
constraints, individual path constraints associated with the WECC Path
Ratings (e.g. Path 15, 26, 46, 49, etc), are included in the
simulation\--i.e. the limits of "rated paths" in the model include
dynamic and thermal limits to prevent post contingency conditions from
exceeding safe and reliable operating conditions. Non-rated internal
paths such as those that are known to cause intra-zonal congestion in
the market, such as the West of Devers and North of Miguel systems, are
modeled. Likewise, operating nomograms are included in the simulation.
All critical constraints known to exist at this time have been modeled.

Failure to consider all operating security constraints could cause the
analysis to over- estimate the benefits of import lines since the model
may overestimate the amount of internal, less efficient generation that
would be displaced by imports. However, no omissions are known to exist
at this time, and it is assumed the results are valid in this regard.

[Unit Commitment Module Not Available]{.underline}

Absent unit commitment constraints, the OPF program assumes all
generators are immediately available, and if the output of a unit is
less expensive, it might be dispatched for as few as a couple of MW
and/or for as few as a couple of minutes. In actuality, a generator is
not started to run under these kinds of conditions. Generators take a
finite length of time to start, have a minimum output level, should be
operated a minimum length of time before shutdown and should be shut
down a minimum length of time before restart can be initiated.

While the lack of a unit commitment module causes the program to tend to
underestimate the total cost of production, this does not necessarily
imply that the calculated benefits of proposed transmission projects are
overstated. The incremental benefits of new transmission may be over- or
understated. Hopefully, any error introduced in this way would be
present in both the base case and the case with the proposed new
transmission project so that the calculated incremental benefits are
valid. This problem cannot be corrected given the current software.

[Some Proposed Generation not Included]{.underline}

The addition of new, efficient generators inside an area that is
currently constrained from securing import generation due to
transmission limitations will tend to reduce the benefits of proposed
new import transmission lines. For example, some proposed generation
facilities in California (e.g. Mountain View, Otay Mesa, and the
Pastoria Expansion) did not meet the criteria for inclusion in the
simulation but might have a significant impact on the analysis results,
if constructed. Mountain View, for example, could have an adverse impact
on the economic benefits of the D-PV#2 line. Therefore, sensitivity
studies will need to be performed to evaluate the potential impact of
these generation projects on the economic analysis results.

[Locational gas price differences Included, but Transmission Losses and
Wheeling Charges Not Included]{.underline}

The price of gas to generators inside of import areas such as California
was assumed to be higher than the price to generators at the border or
outside of California and closer to the gas fields. This raises the cost
of power from internal generators relative to external generators and
causes the OPF to dispatch more power from resources external to
California and less from internal generators. Thus, reflecting the
locational price of gas tends to increase the economic benefits of the
proposed new lines. However, transmission loss factors that are around
5% at external locations such as Palo Verde, and which would effectively
raise the cost of generation external to an import area by up to 5%
relative to internal generators was not modeled. Wheeling charges that
could raise the cost of external generation by \$1 or \$2 per MWH were
also not modeled. This would also cause the OPF to dispatch more power
from external resources to meet California load and less from internal
generators, tending to increase the calculated economic benefits of
proposed new transmission lines.

The net effect of these modeling assumptions tends to increase the
incremental benefits of proposed new transmission projects such as those
extending from California to Arizona and Nevada. It might be possible to
add a constraint to the OPF formulation to add a hurtle for use of
designated lines for imports to simulate the effect of these charges
when more detailed studies are performed.

[Similar Generators are assumed to have Similar Cost Curves]{.underline}

In the real world, different generators would likely have different
incremental cost curves. However, the market bid price of generators
cannot really be known, irrespective of actual cost. Therefore, it is
reasonable to assume that similar vintage and technology generators have
identical, flat incremental cost curves because in a competitive market,
actual cost information and biding strategy is not publicly disclosed. A
flat cost curve will tend to result in a step function dispatch of
generators, which is unlikely to occur. A sloped cost curve is perhaps
more realistic. It is difficult to evaluate whether this assumption has
any impact on calculated benefits, but since even a large new 500 kV
line is a marginal change on a system as large as the Western
Interconnection, it might be safe to conclude there would be no
significant impact.

[Transmission Losses are estimated as a Fixed Percentage]{.underline}

In a real alternating current transmission/distribution system, losses
vary with the square of the power transmitted over the line. Although
the sub-regions such as California may estimate energy losses under
different loading conditions and include them with the demand, the model
estimates energy losses by summing up the load at all busses and then
applying a fixed percentage adder. This seems to be a satisfactory
approach from the standpoint of a production cost model.

[Generator Forced Outages Not Modeled]{.underline}

Generator forced outages are not modeled. However, in an incremental
comparison, the difference in costs with and without a transmission
project would tend to cancel out the impact of omitting forced outages.
Thus, this omission should not have much if any impact on the
calculation of incremental benefits associated with a possible new line.

[Phase shifters]{.underline}

Phase shifters in the model will maintain a fixed angle unless they are
activated in the model. For example, the Nelway phase shifter on the
BC-NW East Path was not activated in the 2008 case. Use of this phase
shifter would have shifted the power flows to the west side of the path,
better balancing the flows in the system. However, the representation of
the phase shifters is adequate for a planning study.

[Consumer and Producer Benefits/Losses]{.underline}

The cost of power to consumers is calculated for each of 8760 hours in
the year by summing the LMPs at each bus times the load at each bus in
an area (e.g. Arizona, San Diego, etc). The gross benefits of a new line
to the consumer are deemed to be the cost of power before the upgrade
minus the cost of power after the upgrade project is completed. A
reduction in the cost of power is assumed to be an increase in consumer
benefit. The producer benefit/loss is calculated in a similar fashion by
summing the LMPs at the generator minus the unit production cost of the
generator times the number of MWH of energy production in each hour,
with and without the upgrade project to find the incremental producer
benefit/loss. Consumer benefits may be offset by generator losses when
the generator experiencing the loss is tied to the consumer in an
economic sense (e.g. is in the rate base of the utility serving the
consumer). Thus, it is important that region for which benefits of a new
line are to be determined encompasses economically connected producers
and consumers.

The benefit of most interest is the net consumer benefit in an import
region. If the net benefit that results from a new transmission line is
greater than the cost of the new line, there is an economic case to be
made for proceeding with the line. The cost of constructing generation
resources is ignored in this analysis because it is assumed that such
construction has already occurred thus making the capital cost of
generation a sunk cost. If the construction of new generation is tied to
the construction of new transmission then both sets of capital costs
need to be included in the cost/benefit analysis.

With respect to congestion revenues, the construction of a new
transmission line may reduce or eliminate the flow of congestion
revenues to consumers that existed before the new line was built. Just
as a reduction in supplier benefit is netted against an increase of
consumer benefit in the same region, a reduction in congestion revenue
must also be netted against an increase in consumer benefit, if the
market is set up to pay congestion revenues.

**[Validation of Model Results]{.underline}**

The results of the simulations were validated using the following
approach:

-   A graphical comparison of Path Duration Flows (PDF) comparing the
    results of the SSG-WI to historic flows was done.

-   The objective of this comparison was a matching of trends with
    consideration given to:

    -   Market Simulator models a single control area

    -   A comparison of SSG-WI 2008 to 2002 actual involve different
        load levels; considerable new resource additions; varied
        transmission topology

-   The similar shape of the actual PDFs and the SSG-WI 2008 PDFs help
    to validate the results of the simulations (See Figure A-2).
    Specifically,

    -   CAISO confirmed the SSG-WI result to be consistent with what
        they are seeing for EOR and SCIT. The SSG-WI result for EOR is
        valid when the significant number of additional resources are
        taken into account for the 2008 case (i.e., additions at Panda
        and Gila alone were about 2000 MW; thousands of MWs were added
        in Arizona and in Nevada.)

    -   Path 26 compared favorably.

    -   COI Deviation is due to the fair amount of gas added in the
        Northwest, attempting to move south.

    -   "Idaho -- PNW" and "Montana to PNW" compared incredibly close;
        though, thinking about those areas one can say the profile of
        resources has not changed much. Consistently, the comparison for
        the "West of Hatwai" should have resulted in greater
        correlation. The sensitivity runs performed with reduced DSI
        loads in Montana showed a direct impact to the flows on the
        "WOH" path. This leads to the conclusion that the continued
        discrepancy has to do with the level of loads modeled.

    -   The \"TOT2\" discrepancy has to do with reversed economics
        caused by the glut of generation in Arizona.

**Figure A-2**

![](media/image2.wmf){width="5.9944444444444445in"
height="3.776388888888889in"}

***APPENDIX B---Generation Assumptions***

**[Generation Scenarios]{.underline}**

# [2008 Generation Scenario]{.underline}

The power plants likely to be on line by mid-2004 produce enough power
to meet expected loads plus reserve requirements in 2008. Plants added
between 2000 and mid-2004 are primarily gas-fired.

# [2013 Natural Gas Scenario]{.underline}

#  

The 2013 natural gas scenario adds 18,200 MW of combined-cycle
combustion turbines to the level assumed in 2008. These are located
based on load growth and proximity to gas and electric transmission
lines.

All three 2013 scenarios add 6,500 MW (nameplate) of wind generation.
These wind plants are placed in areas with good resources. These wind
resources are placed closer to loads than the additional 12,000 MW wind
added in the renewable scenario.

# [2013 Coal Scenario]{.underline}

This scenario adds 16,300 MW of coal plants to the level assumed in
2008. These plants are located at or near coal mines. Representatives of
the Western coal industry helped develop this scenario. This scenario
also adds 1,900 MW of combined-cycle gas-fired plants in the Southern
California and Northern Baja Mexico areas.

# [2013 Renewable Scenario]{.underline}

In this scenario, the majority of the new generation in the region is
supplied by renewable energy sources, with 9,500 MW of new
combined-cycle gas-fired generation added as well. By 2013, this
scenario adds 34,300 MW of additional nameplate capacity to the region
above the level assumed in 2008. The renewable generation is assumed to
be composed of the following resources: 18,500 MW is wind, 2,500 MW is
solar and 3,800 MW is baseload biomass and geothermal. This shows 54% of
new capacity additions coming from wind, 18% from the combination of
geothermal, biomass and solar, and the remaining 28% from natural gas.
On an energy basis, this shows wind providing 64,824 GWh/year or 36% of
new supply; geothermal and biomass 29,959 GWh/yr or 17%; solar 4,818
GWh/yr or 3%; and combined-cycle gas 77,395 GWh/yr or 44% of total new
energy.[^2] West-wide, this would increase the percentage of non-hydro
renewable generation capacity from 2.6% of the total resource mix in
2008 to 13.2% in 2013. This is enough renewable energy generation to
meet all of the renewable portfolio standard targets of California,
Arizona, Nevada and New Mexico currently in place.

Representatives of the American Wind Energy Association (AWEA) and
Western Resource Advocates (WRA) participated in developing this
scenario. AWEA took the lead on providing the wind capacity added in the
scenario and WRA provided the inputs on the non-wind renewables based on
the analysis in its forthcoming \" Interior West Clean Energy Plan\".
Many of the performance assumptions for non-wind resources derive from
the Energy Information Administration's Annual Energy Outlook 2002 (AEO
2002) and other publicly available sources. These assumptions were
further refined based on input from the California Energy Commission,
industry experts, and other regional studies.

It proved difficult to establish a clear base-line of the renewable
generation on-line as of 2003, the starting point of the study.
Historically, renewable sources have tended to be smaller and not as
well documented as other types of power plants, which has resulted in
discrepancies in the plant data drawn from different sources. For this
study, the starting values were derived by inventorying incremental
resource additions for 2001 to 2003, and adding them to the year 2000
values listed in WECC's [Existing Generation and Significant Additions
and Changes to System Facilities]{.underline} report (SigAdds). Although
we have not yet been able to reconcile the differences, the values
listed in SigAdds for renewables are somewhat lower than in other
sources. Because of this, we estimate that there may be as much as 800
MW more non-wind renewable generation currently on-line in the region
than is included in this study.

All parties to the Report agreed that the Renewables scenario should
model the addition of 20,000 MW of wind added to the region by 2013. The
first plan developed by AWEA and its member companies showed 8,000 MW
coming on-line in 2002-2007 (with an additional 12,000 MW added
2008-2013). It was later determined that, in addition to currently
operating projects, all wind plants under construction and expected to
be on-line by the end of 2003 should be treated as \"existing\" wind
capacity. This had the effect of reducing the 8,000 MW of AWEA projected
would be developed between 2002 and 2008. The overall result is that the
report now models the addition of 18,500 MW of wind instead of 20,000
MW. This discrepancy is insignificant on a 225,000 MW WECC grid ten
years out.

Wind, geothermal and biomass plants are located in areas where those
resources are prevalent. Given the widespread availability of solar
power across the West, whenever possible solar capacity was located near
transmission capacity or load centers, or ideally both. The additional
gas plants in the renewables scenarios are located near load centers.

In the model the biomass and geothermal plants are run at full output
when not down for maintenance, because of their low variable operating
costs relative to gas and coal units. The variable output of wind and
solar plants is determined outside the model, based on hourly
availability of the resource, while gas and coal-fired plants are
dispatched within the model to follow the remaining loads.

### Wind

Capacity -- Wind generation additions were based on the current AWEA
forecast for the western United States. As shown in the table below,
this projects a total of 20,000 MW of new installed capacity to come
on-line between 2003 and 2014. This estimate is based primarily on
projects planned or proposed by wind development companies to supply
identified customers and markets. This number is consistent with the
amount of wind capacity that will have to be installed to meet the
targets of the state Renewable Portfolio Standards (RPS) now in place in
AZ, CA, NM and NV. This amount of wind saturates no major market in the
region, and represents less than 10% of the wind resource potential in
the WECC that is economic with current technology when gas prices are
\$4/mmbtu or greater.[^3]

Location -- Wind development companies identified the approximate
injection points of their planned or proposed projects onto the grid to
AWEA. The distribution of these projects by state is consistent with RPS
targets, and also shows that each state obtains some wind development.
In the 2003-2008 period, as shown on the table below, wind development
is projected to be quite equally spread throughout the region, with
seven states each receiving 500 MW-800 MW of new projects and three
states 900 MW-1,300 MW of projects. In the 2008-2013 period, the great
majority of wind additions as proposed by developers is projected to be
in MT and WY, with small amounts in the other nine states. In preparing
its overall wind development plan for the WECC, AWEA sought to match
proposed projects to existing transmission, while also recognizing that
development of some resource areas will require new transmission to be
built.

> **WECC Wind Development Plan**
>
> **Nameplate Capacity, MW**

**State On-Line 2002-2007 2008-2013**

> AZ - 200 100
>
> CA 1,716 1,300 500
>
> CO 61 900 100
>
> ID - 500 100
>
> MT - 800 2,900
>
> NV - 500 700
>
> NM 1 800 700
>
> OR 157 800 100
>
> UT - 600 400
>
> WA 178 1,000 100
>
> WY [141]{.underline} [600]{.underline} [6,300]{.underline}
>
> WECC Total 2,254 8,000 12,000

Capacity factor -- projected capacity factor for each new plant was
modeled on an hourly basis, as described in the wind modeling section.
The average annual capacity factor of the plants ranged between 34% in
the coastal/western states (AZ, CA, ID, NV, OR, WA) and 44% in the
Mountain states (CO, MT, NM, UT, WY). Because the largest amount of wind
development is proposed for the windier states, the weighted average
capacity factor of the total proposed new wind capacity is estimated to
be 40%. This notwithstanding, the model runs for this report used an
average wind capacity factor of 34%. This will be corrected in
subsequent model runs.

## Wind Capacity Factor versus Capacity Credit

There is sometimes confusion on the use of the terms capacity factor and
capacity credit as it is applied to intermittent sources of energy, such
as wind power. This section describes the assumptions and methodologies
used to determine these values for the report, and highlights the
differences between the two. Much of the work in this field has been
conducted by Michael Milligan, of the National Renewable Energy
Laboratory. (see Milligan, M. R. (2002). Modeling Utility-Scale Wind
Power Plants, Part 2: Capacity Credit. 67 pp.; NREL Report No.
TP-500-29701)

# WIND CAPACITY FACTOR 

Capacity factor is calculated as the amount of energy actually produced
during a year, divided by the theoretical maximum output that could be
generated over that same period, based on the unit's nameplate rating.
For conventional power plants, this is an historical measure of how
often the plant is shut down for maintenance, either routine or
unplanned, as well as how often the plant's output is reduced because
other lower variable cost generation is available to meet load at any
point in time.

Commercial wind plants typically have annualized capacity factors of
30-40%. From a mechanical standpoint, the availability of individual
wind turbines is warranted by manufacturers to be 95% or greater, and
because wind farms consist of many individual turbines the "wind farm
availability" is even higher. This availability is superior to that of
conventional power plants, reflecting the performance of modern wind
plants as extremely reliable generators. However, wind is an
intermittent resource -- during windy periods there is adequate "fuel"
to produce very low cost energy, but during lulls the output may drop to
zero. Net wind availability has sometimes been represented as an
"Effective Forced Outage Rate," (EFOR) just as mechanical outages are
treated with conventional units. Expressed this way "effective forced
outage rate" is the inverse of capacity factor, or 60-70%. It is,
however, misleading to characterize wind availability as EFOR since the
system reliability impacts of wind variability are very different from
conventional plant forced outages. Modern wind farms are producing at
least some energy over 80% of the time and very, very rarely experience
instantaneous changes in output that rival "routine" startup and shut
down of conventional plants.

# WIND CAPACITY CREDIT 

The capacity credit of a plant is a measure of the increase in load
carrying capability that a given generator can provide to an electrical
system meeting a specific system reliability target. This target can be
specified using alternative measures of reliability, such as loss of
load probability (LOLP) or expected unserved energy (EUE). A standard
criteria in general use is an LOLP of one day in ten years. The capacity
credit represents the generator's contribution to the total portfolio of
all generation resources that must be able to meet minute-by-minute load
requirements as required by the system operator. Therefore, unlike
capacity factor, which simply quantifies the overall average energy
delivery of a plant, capacity credit indicates both the plant's
availability and the correlation of this availability with time
differentiated system requirements for the capacity to deliver energy.
The value depends heavily (but not exclusively) on events during high
load hours for the utility system.

Capacity credit is defined as the change in effective load carrying
capability (ELCC) of the system with the addition of the subject
generator at a given level of system reliability. The ELCC cannot be
calculated simply by specifying the generator average capacity factor or
by measuring the plant output during last year's system peak load hour
-- it must be determined by considering hourly loads and generating
patterns, plus a statistical treatment of other generator forced outage
rates, and the probability of unusual events such as an unseasonal
weather event during e.g. a planned nuclear plant refueling outage,
using an appropriate production-cost or reliability model. Many detailed
studies have found wind to have a higher "capacity value" to the system
during shoulder months of the year when most routine system maintenance
is performed rather than during peak seasons /maximum load levels.
Because ELCC calculations can be very time consuming and data intensive,
it is often estimated by averaging the capacity factor during the top
1,000 load hours during a typical year.

Robust data on which to base a detailed ELCC analysis simply does not
exist on a WECC-wide geographic scale. This report assumes a standard
capacity credit of 20% for each wind plant. This assumption that
capacity credit amount to, on average, roughly 60% of the wind capacity
factor is judged to be conservative. Study results are not sensitive to
precise measurement of wind capacity credit, which is provided only to
ensure the overall "resource adequacy" of the generation portfolios and
some assurance that overall system reliability is comparable between the
various generation scenarios.

## Geothermal

Capacity -- Initial geothermal estimates were based on the NEMS
geothermal resource assessment. The geothermal units include all
potential units with busbar costs of \$60/MWh or less. In order to
reflect environmental and developmental concerns, the projected
geothermal development at each site was limited to those included within
Steps 1 and 2 of the NEMS data, where the four possible steps
demonstrate increasing difficulty in extraction.

Location -- Web-based maps of geothermal resources produced by SMU were
used to correlate the geothermal sites to transmission control areas.

Capacity factor -- Between 80% and 95%, depending on location.
Geothermal plants run at full output when they are not down for routine
or unplanned maintenance.

## Biomass

For this study biomass facilities are broken down into two categories
-- 1) dedicated combined cycle facility and 2) biomass (landfill gas).

Capacity -- Capacity additions were based on an analysis of biogas
potential completed by the Tellus Institute, as included in the Interior
West Clean Energy Plan. In addition, 250 MW of landfill gas plants were
included throughout the West.

Location -- The biomass combined cycle facilities were allocated to
transmission service areas on the basis of load.

Capacity factor -- 80% for combined cycle plants, and 90% for landfill
gas plants. Biomass plants run at full output when they are not down for
routine or unplanned maintenance.

Because of their similar capacity factors and operating characteristics
as base-load plants, geothermal and biomass plants were combined and
treated as a single fuel source.

## Solar

Solar estimates were based on an assessment of the economic viability of
two technologies during the study period -- centralized, solar thermal
plants, and distributed photovoltaic arrays. In Arizona, New Mexico, and
Southern Nevada, 40% of solar power comes from solar thermal stations
while 60% comes from photovoltaics. In the rest of the region solar
power is generated exclusively from photovoltaics.

Location -- Plant locations were based on a review of the solar
insolation and the control area maps in the Renewable Energy Atlas of
the West, produced by the WRA and Northwest Sustainable Energy for
Economic Development. Whenever possible, the stations were located near
transmission capacity or load centers, or ideally both.

Capacity Factor -- An 8,760 element time series of capacity factors was
developed to describe operating characteristics of solar systems, based
on input from Frank Vignola of the University of Oregon. The capacity
factor varies daily between 0 and the daily maximum (up to 100%), with
an average annualized capacity factor of 22%.

**[Non-Wires Alternatives]{.underline}**

There are non-wires alternatives for relieving transmission congestion.
Generation, including distributed generation, can be located on the load
side of a transmission constraint; demand-side actions can reduce demand
during periods of transmission congestion; and remedial Action Schemes
(RAS) and new transmission technologies, such as flexible AC
transmission systems (FACTS), can also increase transfer capacity
without requiring the construction of new wires.

[Strategic Importance of Non-wires Alternatives to Transmission
Planners]{.underline}

The future is unknown. New technology, volatile and sustained high fuel
prices, and drought are examples of conditions that could fundamentally
and quickly change how a region chooses to meet load. During the Western
energy crisis of 2000-2001--- under conditions no one in the
interconnection foresaw -- many providers relied on emergency programs
to buy back power from customers, and customers' installed on-site
generation. While the buyback prices were much higher than the price of
power purchased from the utilities, the prices were often much less than
the market prices of the time. One lesson from this period is that
demand reduction programs can reduce demand given sufficient incentives.

A demand response package and a distributed resources strategy that are
a part of every day utility practice could be refined and implemented to
reduce the need for transmission expansion and meet demand during a
crisis. Deferring big transmission investments *without jeopardizing
grid reliability* may lower costs to consumers, as it allows more of the
unknown future to unfold itself. Capital investments in the electric
industry tend to be big, lumpy, and long-lived. There is the risk that
new technologies can turn such investments into "white elephants." New
technologies, such as economical fuel cells, could radically reduce the
presently perceived need for new transmission.

Non-wires solutions allow planners to determine, and in some cases
delay, the need for transmission construction. They also can help to
alleviate "economic congestion" at lower costs than new transmission.
However, load-based generation and demand-side actions are not
substitutes for transmission, which also allows for diversity of
generation sources and the inclusion of resources located remotely from
load centers.

By illustration, the transmission congestion studies for 2008 and 2013
in this report assume a peak load growth rate of approximately 2%
beginning today. If load growth could be reduced to 1%, no additional
transmission would be needed in 2013 beyond that assumed in the 2008
study. That is, the load in 2013 would be equal to the loads assumed in
2008[^4]. A reduction in peak load growth and local generation of the
magnitude required to halve the growth rate of power delivered through
the transmission grid is not infeasible.

The concept of non-wires alternatives is not new. FERC has recognized
the value of non-wires alternatives as complements to transmission
construction and requires equal consideration of non-wires alternatives
in its RTO orders and proposed SMD rule. The California ISO and BPA have
undertaken initiatives to consider non-wires alternatives in-lieu of new
transmission investment. Consideration of non-transmission alternatives
was part of the planning process adopted by former Western regional
transmission groups (NRTA, SWRTA, WRTA). Also, the existing WECC
regional planning process requires the consideration of "alternatives."

There are three groups of non-wires alternatives contemplated here: (1)
location of generation on the load side of a transmission constraint;
(2) demand-side actions; and (3) non-wires transmission options such as
Remedial Action Schemes (RAS) and flexible AC transmission systems
(FACTS).

New generation, including central power plants, combined heat and power
(CHP) and other distributed generation, can be located on the load side
of a constraint and thereby relieve congestion. Existing backup
generation on the load side of a transmission constraint can also be
used (e.g., PGE's Dispatchable Standby Generation Program).

There are a variety of demand-side actions that can reduce the need for
transmission, including more timely and accurate price signals to
consumers that better reflect wholesale market congestion costs, demand
buy-back programs (e.g., price-based dispatch, interruptible/curtailable
and demand response contracts), and certain measures generally
considered only as energy savers[^5].

RAS and new transmission technologies, such as FACTS, can be used to
increase transfer capacity on existing wires and thereby reduce
transmission congestion. RAS schemes are widely used in the Western
Interconnection to increase transfer capacity on transmission paths. The
cost and impacts on reliability must be considered with these
alternatives.

Non-wires alternatives to reduce transmission congestion and help manage
future risks should be considered at all levels of transmission
planning. The specificity of the analysis of non-wires alternatives
should increase as one moves from interconnection-wide planning, to RTO
or sub-regional planning, to planning by load serving entities (LSE). At
SSG-WI's high level of planning it would be very difficult to specify
each of the non-wires alternatives that might be employed to meet
transmission needs. As the planning becomes more specific to regions and
LSEs, specific measures will need to be considered.

However, even at the SSG-WI level of planning some high-level statements
can be made about the impact of non-wires solutions. For example, there
are at least two ways to model the effectiveness of non-wires
alternatives in relieving congestion and delaying construction of wires.

The impact of successful demand-side measures in reducing transmission
congestion can be estimated by extrapolating the lower load in 2008 to
the 2013 scenarios[^6]. This result can be achieved, for example, by
halving the assumed load growth between today and 2013 to 1%. (See
footnote above for calculation.) If demand-side measures were able to
hold 2013 peak load to levels forecasted for 2008, one could conclude
that the same resources[^7] and transmission system that met loads in
2008 would meet loads in 2013.

Another way to measure the effects of non-wires solutions at this high
level of analysis is to model sensitivity to load variations. For
example, one could arbitrarily drop loads by 10% or 20% in an area on
the congested side of a constraint and then estimate changes in
production costs to determine whether the availability of non-wires
solutions is practically and economically feasible. These sensitivities
have not been undertaken here. If performed, such analysis would give
planners at the subregional or LSE levels guidance as to the amount of
non-wires solutions that would have to be available to effectively
manage congestion.

The impact of RAS and FACTS could be estimated by increasing the
carrying capacity of specific paths in the 2013 scenarios that were
modeled and estimating the costs associated with those non-wires
investments.

When planning for western subregions or utilities, standards, criteria
and metrics should be developed to support analysis and comparison of
alternatives. Metrics would include discount rates, assumed facility
lifetimes, and other parameters that can be used to compare alternatives
on a standard basis. One approach to considering non-wires alternatives
on a sub-regional basis has been documented in a report prepared for
BPA, *Kangley Echo Lake Economic Screening and Sensitivity Analysis
Report*, November 8, 2002.

***APPENDIX C***

***Long-term Model Improvements***

The following model improvements have been identified to increase the
accuracy of existing production costing model simulations. The SSG-WI
Modeling Improvements Group will be pursuing the potential solutions
listed below.

**[Modeling Hydro]{.underline}**

**Opportunity for improvement:** Hourly hydro generation is a fixed
input to ABB's optimized power flow program (OPF) and is simply netted
against the hourly bus bar load at each dam site.

Hydro inputs are determined in the following manner:

Step 1. BPA, BCH, WAPA, CEC and PacifiCorp provided monthly average
hydro generation at all major hydro sites assuming high, medium and low
water conditions. BPA's data was derived from "Hydsim", a hydro
regulation model that simulates the monthly average generation at all
federal and Mid-Columbia hydro facilities for various water and load
conditions and subject to system operating constraints.

Step 2. The monthly hydro generation at each dam site was shaped into
hourly data using a peak shaving algorithm that operates within each
dam's minimum and maximum constraint limits to serve the WECC's
system-wide hourly load shape.

This two-step approach tends to flex hydro operations beyond operating
limits, and is for all practical purposes, is blind to transmission
constraints. In addition, this approach creates a "rigid" dispatch
scenario that does not interact in a dynamic manner with hourly OPF
transmission constraints and thermal unit dispatch.

In addition, chain-linking models is time-consuming and prone to error
because the analyst must exercise great care to ensure that Hydsim, the
peak shaving algorithm and ABB's MarketSimulator are consistent with
regard to model assumptions, loads, thermal displacement markets and
transmission constraints.

**Potential Solutions:**

The existing approach can be improved upon by:

1\) Resolving proprietary issues and replacing the peak shaving
algorithm with outputs from BPA's Hourly Operation System Simulator
(HOSS).

2\) \"Tuning\" the peak shaving algorithm, e.g., adjusting the monthly
maximum and minimum limits until the algorithm produces hourly
generation shapes that more accurately reflect actual operations. 

Future improvements might also include:

Incorporating regional cascaded multi-dam hydro regulation logic
directly into the OPF formulation and simulating hydro operations with
historical unregulated inflow data or synthesizing inflows that are
derived from the historical inflow records and correlated across space
and time.

**[Modeling Wind Generation Characteristics]{.underline}**

**Opportunity for improvement:** The temporal characteristics of the
wind resource at geographically specific locations has been poorly
documented, and can not be easily modeled as an hourly time series of
the nature needed for this study. Each hour of the year was treated as a
random event, with no correlation to the changes in wind at nearby
locations or during prior time intervals.

**Potential Solutions:**

Gathering additional historical data on site specific temporal
characteristics of the wind, as well as developing more sophisticated
models to simulate the performance of wind plants on an hourly basis,
which would provide a more meaningful understanding of the impact that a
non-dispatchable resource can have upon transmission congestion.

**[Modeling Uncertainty]{.underline}**

**Opportunity for improvement:** This analysis incorporated uncertainty
by simulating the least cost hourly operation of the Western electrical
system for 2008 and 2013 across a very limited set of pre-configured
outcomes for resources, loads, fuel prices and hydro inflows. While
lacking in sample size, this approach can provide useful insights into
the relative costs and benefits of alternative scenarios.

However, resource allocation decisions are actually based on uncertain
forecasts of these quantities and prices. These forecasts can be
represented mathematically as a continuum of probability distributions
(see diagram below). For example, a LMP forecast is actually a series of
probability distributions, each of which is a function of many uncertain
variables.

Hence, a more thorough treatment of uncertainty would incorporate these
distributions directly into the decision logic of our models, (e.g.,
decision logic that affects unit commitment, reservoir management and
resource/transmission acquisitions.

**Potential Solutions:**

It would improve the usefulness of the current approach to:

1\) Simulate sufficient numbers of scenarios that more adequately
represent the range of future possibilities.

2\) Create scenarios that are based on consistent input data, e.g.,
heating and cooling loads that are correlated to snow-pack and runoff.

3\) Streamline the entire study process of running a study, from data
collection through the report-writing phase.

However, these are quick fixes and of limited value. A more useful
approach would be to incorporate uncertainty directly into the decision
logic of our models, which may be beyond the capabilities of many
existing tools. Hence, we may want to investigate and consider other
modeling techniques and formulations.

**[Modeling New Resource Acquisitions]{.underline}**

**Opportunity for improvement:** Transmission and generation are both
substitutes and complements. The economic factors and reliability issues
that drive transmission acquisition decisions will also affect resource
acquisition decisions, and vice versa, so both strategies should be
developed in a consistent manner so as to not introduce a bias in study
results.

For example, it is extremely difficult to "manually" create a consistent
set of resource and transmission acquisition scenarios for a multiple
scenario study in which fuel prices, capital costs, hydro inflows and
load growth trajectories are continually varying over time.

**Potential solutions:**

Hardwiring new resource capacity is a viable option when analyzing only
a few scenarios and when the simulation is limited to a single year.
However, this approach becomes unwieldy and probably infeasible when the
study horizon spans more than a single year or if we adopt a Monte Carlo
approach in simulating uncertainty. A more practical solution may be to
allow the model to acquire new resource capacity based on long run
system economics, maintaining a minimum reliability standard and
resource operating and supply curve data.

**[Modeling Bus Bar Loads]{.underline}**

**Opportunity for improvement:** The existing methodology for estimating
hourly bus bar loads is a complicated and arcane process that fails to
capture the temporal and spatial variability we would actually expect to
see over time horizons of up to 20 years. In addition, no attempt is
made to correlate bus bar load data to weather related hydro inflow and
runoff data.

The existing methodology is also inflexible in that it is ill-suited for
studying specific "events" such as extreme heat wave or cold wave
scenarios.

And to complicate things further, historical load data is proprietary
and access is usually restricted.

**Potential solutions:**

Bus bar loads are an important part of the dispatch equation so it is
important that these data be modeled with the same degree of precision
used in modeling transmission flows and hydro-thermal dispatch. Hence we
may want to explore the possibility of:

1\) Improving access to historical data.

2\) Utilizing historical hydro inflow data and bus bar loadings that are
synthesized from chronologically consistent historical
weather/temperature year data.

3\) Stochastically synthesizing hourly bus bar loads and hydro inflows
such that they are correlated across space and time.

**[Modeling Game Theory and Market Behavior]{.underline}**

**Opportunity for improvement:** Most existing models simulate perfect
competition, which maximizes total social benefits. However, in reality,
prices can exhibit much greater price volatility when firms attempt to
maximize profits by withholding generation.

**Potential solutions:** Develop a better understanding of how economic
equilibrium concepts such as proposed by Cournot and Nash work and
incorporate these features into future models.

**[Modeling Marginal Losses]{.underline}**

**Opportunity for improvement:** Marginal losses can create large LMP
differentials that, when ignored, lead to inefficient dispatch and
resource siting decisions.

**Potential solution:** Incorporate marginal loss methodologies within
the OPF formulation.

**[Modeling Transmission and Generation Rights/Ownership]{.underline}**

**Opportunity for improvement:** Most existing OPF models do not have
the capability to disaggregate area and nodal costs and benefits to the
level of the individual market participants who own or lease property
rights to existing and new generation and transmission assets.

This means decision makers are limited in their ability to answer one of
the most important questions being asked, i.e., *Who are the winners and
losers and how much are they impacted by any given resource allocation
or operating decision?*

However, tracking the flow of dollars with this level of precision
significantly increases data collection efforts, proprietary data
issues, modeling complexity and run times.

**Potential solutions:** The most commonly used approach for assigning
costs and benefits to individual market participants is to make
after-the-fact allocations of area or nodal benefits based on simple
approximations and rules of thumb.

However this approach often leads to inaccurate and misleading
conclusions. Hence, we may want to identify the technical requirements
and weigh the costs against the benefits of adding an ownership
"dimension" to OPF modeling.

**[Modeling: The "Curse" of Dimensionality]{.underline}**

**Opportunity for improvement:** Some existing modeling algorithms may
be challenged by the huge dimensionality of the problem of
simultaneously modeling large nodal networks of thermal generators,
hydro plants, loads, transmission elements and storage reservoirs and
their ownership, with hourly detail over periods of up to twenty years
while representing all of the uncertain variables across many possible
future scenarios.

**Potential solutions:** To overcome this challenge several techniques
are commonly employed:

1\. Reducing or "equivalencing" the electrical grid into a simpler
representation. This technique allows the analyst to aggregate
transmission lines, nodes, loads, generators as well as ownership.

2\. Reducing the number of future outcomes or scenarios to a manageable
number that can be analyzed with existing software and computer
processing capabilities.

3\. Aggregating time intervals into fewer periods or blocks.

However, these techniques invariably reduce the resolution or precision
of the results and compromise our ability to answer the detailed
questions decision makers are asking.

Hence, we may need to conduct a thorough review of the underlying
methodologies and formulations, especially with respect to their
practical ability to handle the huge dimensionality of this problem.

***APPENDIX E---WGA & SSG-WI Studies***

# 

# [Conclusions from the WGA Technical Study]{.underline}

Two bookend generation 2010 expansion scenarios were reviewed and
transmission

expansion plans proposed for both.

-   If generation expansion results in mostly gas-fired generation
    located in or close to loads, transmission expansion that is already
    under construction or committed to be on line in by 2004 is probably
    adequate. This conclusion is highly dependent on the assumptions
    made for gas prices.

-   If generation expansion includes significant new coal, wind, hydro,
    and geothermal resources that are typically located in the more
    electrically remote regions of the system, \$8 to \$12 billion (in
    2010 dollars) of new main grid transmission infrastructure and
    generation integration transmission may be needed. However, fuel
    savings and reductions in market clearing prices as compared with
    the gas case may justify the additional transmission, depending on
    assumptions of delivered gas prices, the capital cost of generation,
    and coal price assumptions. The difference in annual average
    variable cost savings between the Gas scenario and the
    Other-Than-Gas scenario is approximately \$3 billion to \$4 billion.
    In the high gas price sensitivity study, these annual savings jumped
    to over \$5 billion.

-   The initial cost of the Other-Than-Gas case transmission expansion
    could be reduced by \$1 billion to \$4 billion (all 2010 dollars)
    with further study or if main grid transmission plans influence
    optimum location of generation expansion.

-   Capital costs of new generation were analyzed briefly in the
    spreadsheet study, but were not factored into the production cost
    model results. Depending on the treatment of capital costs and other
    fixed costs, including the capital costs of pipelines and fuel
    delivery systems, either "bookend" generation and transmission
    expansion scenario appears to be economical.

-   Mitigation of market power and policy choices such as decreasing
    reliance on gas or developing indigenous renewable or coal resources
    will be important in deciding how much transmission expansion is
    needed.

# [WGA Study Recommendation for Additional Work]{.underline}

The WGA study recommended that additional work should be completed to
refine the modeling analysis by:

1)  Evaluating alternative load growth scenarios that reflect
    implementation of end-use load management, energy efficiency and
    distributed generation resulting from consumers receiving
    closer-to-real-time signals on electricity price;

2)  Expanding the sensitivity analysis to examine the impacts of natural
    gas prices on electricity prices and load growth;

3)  Conducting an incremental transmission addition study to better
    quantify transmission levels and costs;

4)  Expanding the analysis by including DC transmission options;

5)  Evaluating the market power mitigation and operational flexibility
    benefits of either (a) additional generation in
    transmission-constrained areas or (b) the addition of more
    transmission; and

6)  Evaluating additional generation scenarios including combinations of
    wind and peaking resources.

7)  Evaluate the use of additional emerging technology-based solutions
    in increasing transfer capacity in the existing transmission system
    where applicable.

# 

# [Comparison of WGA and SSG Technical Studies]{.underline}

+------------+----------------------------+---------------------------+
|            | ## WGA Study               | > [Proposed SSG           |
|            |                            | > Study]{.underline}      |
+------------+----------------------------+---------------------------+
| Scenarios  | 1.  All-Gas (25,000 MW)    | 1.  Gas Scenario          |
| Studied    |                            |                           |
|            | 2.  Other than Gas (18,000 | 2.  Coal Scenario         |
|            |     MW of coal, 4,000 MW   |                           |
|            |     of wind, and 1,500 MW  | 3.  Renewables Scenario   |
|            |     of geothermal)         |                           |
+------------+----------------------------+---------------------------+
| Years      | 2004 and 2010              | 2008 and 2013             |
| Studied    |                            |                           |
+------------+----------------------------+---------------------------+
| Analysis   | GE MAPS                    | ABB Market Simulator      |
| Tool       |                            |                           |
+------------+----------------------------+---------------------------+
| Hydro      | Yes -- high, average, and  | Yes -- high, average, and |
| Sen        | low                        | low                       |
| sitivities |                            |                           |
+------------+----------------------------+---------------------------+
| Gas Price  | Yes -- high, average, and  | Yes -- high, average, and |
| Sen        | low                        | low                       |
| sitivities |                            |                           |
+------------+----------------------------+---------------------------+

[Benefits of SSG Study over WGA:]{.underline}

1)  Additional scenario that studies large amounts of wind generation

2)  Updated load, generation, and gas price assumptions

3)  Updated estimate of future congested interfaces.

4)  More refined and better optimized transmission expansion plans
    (consideration of DC)

***APPENDIX F---Sub-regional Planning Groups***

Subregional Planning Groups (SPG), working in cooperation with the
SSG-WI Planning Work Group, will play a significant role in Planning of
the Western Interconnection transmission system. It is envisioned these
groups will be a key part of the RTO planning processes once they form.
Through SPGs, stakeholders will evaluate, coordinate, and plan their
future transmission needs. The SPGs as well as SSG-WI will also work to
facilitate the development of future transmission projects.

SSG-WI and the SPGs will develop a cooperative, supportive and
complementary working relationship. Both SSG-WI and the SPGs will work
together to develop models and databases for production costing planning
studies. SSG-WI will focus on interconnection wide needs. Results of
SSG-WI studies will provide important data and information to SPGs for
further economic analysis and detailed planning studies.

The SPGs are involving transmission providers, generation developers,
marketers, local entities and other stakeholders. The processes are open
to all stakeholders. The SPGs will also work with other SPGs on projects
that are of concern or impact them. Results of SPG studies will feed
into SSG-WI to facilitate its process. SSG-WI focus will be to evaluate
interconnection wide benefits beyond the local level.

Several SPGs have already formed and others are in the formative stages.
The following is a brief summary of those SPGs.

**Central Arizona Transmission System (CATS)**

The CATS SPG initially focused on development of the transmission system
between the Phoenix and Tucson areas in Arizona. It addressed
transmission concerns related to load growth in this area and proposed
generation additions in this area of approximately 10,000 MW. The first
participants included Arizona Public Service, Salt River Project, Tucson
Electric Company, Southwest Transmission Cooperative, Citizens
Communications Company, WAPA, and the Arizona Corporation Commission
staff. Early on, participation in CATS was opened up to all
stakeholders, which widened the interest and scope of the work.

CATS is also working with the STEP SPG to explore transmission
alternatives that go from Arizona to Southern California.

Through 2003, the CATS study area encompassed an area bounded by the
Phoenix Metropolitan area to the north, the Tucson Metropolitan area to
the south, the Palo Verde Generating Station to the west and the
Arizona/New Mexico border to the east. During this period a transmission
long range plan was developed, a State wide coordinated 10 year study
was completed, an ACC "Reliability Must Run" study was coordinated among
the stakeholders, and several new transmission projects facilitated by
the CATS work were started and are in various stages of development.

The initial CATS meeting was held in March 2000. Reports documenting the
long range transmission plan for central and southern Arizona (Phase 1),
the integration of several Phase I alternatives and proposed
transmission projects in Arizona that were not included in first CATS
phase (Phase II), and the 10 year coordinated plans of the transmission
entities within Arizona (Phase III), were prepared after each phase was
completed. Each study phase took about 1 year.

Discussion are underway to explore the possibility of expanding the CATS
study area to include western Arizona, New Mexico, and west Texas for
2004.

Web Site for the CATS Subregional Planning Group is
<http://www.azpower.org/>.

**Southwest Transmission Expansion Plan (STEP)**

STEP is a collaborative ad-hoc sub-regional planning group that was
formed in October of 2002 to meet the following goal:

> *To provide a forum where all interested parties are encouraged to
> participate in the planning, coordination, and implementation of a
> robust transmission system between the Arizona, Nevada, Mexico, and
> southern California areas that is capable of supporting a competitive,
> efficient, and seamless west-wide wholesale electricity market while
> meeting established reliability standards. The wide participation
> envisioned in this process is intended to result in a plan that meets
> a variety of needs and has a broad basis of support.*

STEP is an ad-hoc voluntary organization whose membership is open to all
interested stakeholders. STEP has no staff and utilizes its members
(stakeholders, project sponsors, transmission owners, regulatory
agencies, and RTO/ISO's) to complete the required work. Generally,
members that want specific studies conducted are responsible for the
completion of the work. STEP's focus is on economically driven expansion
projects that support the development of seamless west-wide markets
while satisfying established reliability standards. In evaluating the
economic benefits of transmission projects, STEP considers all potential
aspects of economic benefits including the potential for mitigating
market power. In addition, when requested, STEP will work with project
sponsors to help assess the benefits (connecting generation, serving
load, marketing power, etc.) of their independent transmission
proposals.

STEP contains the following planning functions:

1.  STEP has developed a biennial planning process that will produce a
    long-term bulk transmission expansion plan.

2.  STEP identifies current and future transmission congestion that is
    an impediment to the efficient operation of the western market. In
    addition, the impacts on congestion of potential new generation
    facilities or new transmission projects will be considered.
    Generation currently developing in California, Mexico, Nevada and
    Arizona is expected to heavily congest the transmission facilities
    into those areas.

3.  STEP is developing, through a collaborative process, strategic
    transmission options and specific alternative plans for reinforcing
    the transmission system and for reducing or eliminating congestion.
    This information is being provided to the marketplace. Specific
    projects that are being evaluated include:

    a.  Upgrading the series compensation in the existing 500 kV
        transmission lines between California and Arizona.

    b.  A new line between Imperial Valley and Rainbow

    c.  A second Palo Verde-Devers Line

    d.  A second Southwest Power Link (SWPL) line between Hassayampa and
        Imperial Valley and possibly on to Miguel.

    e.  Upgrading the Mead-Phoenix-Adelanto Project to DC.

    f.  A new line from the Eldorado Valley (Mead, Marketplace,
        Eldorado) to southern California (Lugo, Victorville, Adelanto).

    g.  A Palo Verde-Mead line

4.  STEP will review project sponsor studies if requested by the project
    sponsor. The review may include:

    a.  Assessing the technical system impacts of the proposed project
        (transmission and non-transmission).

    b.  Assessing the projects cost and benefits

5.  STEP will rely as much as possible on the technical studies
    conducted by project sponsors and studies conducted in other forums
    (primarily CATS, and the ISO Control Area Study).

6.  The studies completed for STEP will:

    a.  Focus on regional needs.

    b.  Consider a variety of alternatives.

    c.  Consider the flexibility of alternatives.

    d.  Comply with established standards, guidelines, procedures and
        policies (primarily NERC and WECC).

    e.  Be made available to all STEP members following applicable data
        availability guidelines.

    f.  Utilize an economic methodology that has been adopted by STEP to
        evaluate the economic benefits of transmission system additions
        such as the one under development at the California ISO.

    g.  Consider viable non-transmission alternatives

7.  STEP will perform technical study work that is not duplicative of
    work done by others. Technical studies done by STEP shall be
    identified in an approved study plan that will include items, such
    as:

    a.  Purpose and need

    b.  Objectives

    c.  Development of base cases and other data

    d.  Methodology

    e.  Schedule

    f.  Assignment of study work

8.  Members of STEP will share the study work. In general, members will
    study the areas where they have an interest. The results of the
    individual work will be shared with STEP and will normally be
    documented in a STEP report.

9.  STEP will provide a forum to facilitate stakeholder development of
    projects through the planning effort. It will be up to those
    participating in a project to determine the specifics of a project
    such as the scope of the project, lead entity or entities, project
    participants, and funding for a project.

10. Once the long-range transmission expansion plan is developed, the
    focus of STEP will temporarily shift to facilitating the phased
    implementation of the plan. Implementation may involve a variety of
    short-term projects that will ultimately support the development of
    the long-term plan. The long-term plan will be periodically revised
    as desired by STEP.

11. STEP works closely with regulatory and governmental agencies (CEC,
    CPUC, ACC, etc.) in developing facility plans, in order to:

    a.  Gain their input and insights concerning energy policy and other
        issues.

    b.  Provide input to the various regulatory and governmental
        agencies primarily through the involvement of the regulatory and
        governmental personnel who participate in the STEP processes.

    c.  Enhance and streamline the permitting of these facilities and
        help reduce the amount of analysis required by siting agencies.

12. STEP closely coordinates with the following planning and
    coordination functions:

    a.  The west-wide expansion planning function that is being filled
        by the SSG-WI-PWG.

    b.  The planning functions and responsibilities of the individual
        RTOs. Specifically, this activity will take advantage of the
        work products produced in the annual grid expansion planning
        processes that are in place at the California ISO and in other
        entities (i.e., STEP could use base cases that are jointly
        developed by CATS and the California ISO).

    c.  The planning functions and responsibilities of coordination
        activities such as CATS and WATS.

    d.  The planning coordination function of the WECC.

STEP provides a forum for the discussion of different approaches for
funding potential transmission projects.

Additional information on STEP is available at the web site
<http://www1.caiso.com/docs/2002/11/04/2002110417450022131.html>.

**Rocky Mountain Subregional Planning Group**

The Rocky Mountain SPG is an effort initiated by the Governors or the
states of Wyoming and Utah. The Goal is: "To identify in an open and
public process, the most critical electric transmission and generation
project needs in the Rocky Mountain subregion, and with broad
stakeholder involvement provide a framework for regional collaboration
to improve the Western interconnection with technical, financial and
environmentally viable projects identified for developmental
consideration.

Electric transmission in the rocky Mountain region is constrained and as
a result, the region's vast wind, natural gas and coal resources are
underutilized. RTOs are years from effective operation and there is no
current collaborative Rocky Mountain planning g effort to consider
transmission expansion from a holistic perspective.

Those to be involved include Western Interconnection electric utilities,
IPPs, rural electric generation and transmission cooperatives,
municipalities, federal power, transmission and marketing agencies,
project developers, entrepreneurs, power brokers, state and federal
regulators, state energy office representatives and anyone interested in
regional electric generation and transmission planning.

Additional information on the Rocky Mountain Subregional Planning Group
may be found at their web site
<http://psc.state.wy.us/htdocs/subregional/home.htm>.

**Northwest Sub-regional Planning Group (NTAC)**

####### Following is the agreed upon scope of work for ntac: 

**[Mission]{.underline}**

NTAC will be the open forum to address forward looking planning and
development for robust and cost effective NWPP area transmission system.

**[Background]{.underline}**

The electric utility industry continues to change with new issues,
proposed regulations, new forums, and an emerging market influence.
However, with all these changes the fundamental needs of end-use
customers remain the same. Utilities serving these customers struggle to
address their individual requirements as well as to analyze and address
reliability needs.

Discussion during various meetings have identified a view that the NWPP
geographic area is lacking a forum to address the further planning and
development of a robust NWPP area transmission system. This planning and
development would identify future transmission needs by performing
studies to identify solutions. The forum will consider transmission and
non-transmission alternatives. This would mean more than reliability
planning or maintaining current capability. To fill the existing void in
the geographic area of the NWPP associated with the planning of a robust
transmission system, the NWPP TPC has broadened its scope of activities
to include expansion planning dealing with commercial issues. This forum
would need to exist until its functions were assumed by a different
forum or through a comprehensive RTO planning function. The goal is to
avoid duplication now and into the future.

This Scope of Work outlines a forum and structure where participants can
engage in regular and detailed discussions about the further planning
and development of a robust NWPP area transmission system.

**[Goals and Objectives]{.underline}**

The overall goals of this effort are:

1.  To provide necessary information to maintain and/or enhance the
    reliability of the transmission system under the operation and
    planning control of the NWPP area participants.

2.  To develop a transmission assessment that identifies transmission
    constraints under a range of scenarios and suggests possible
    solutions to relieve those constraints, including alternatives such
    as transmission additions, DSM, distributed generation, Special
    Protection Systems (safety nets such as load shedding, Remedial
    Action Schemes) provided by NTAC participants, or through other
    transmission planning efforts.

3.  To provide information to identify the options to support the
    continual electric requirements including load growth of the end use
    customers within the area of the NWPP.

4.  To develop a transmission assessment that will also identify options
    to increase the competitive supply of electricity.

5.  To coordinate with other transmission planning efforts within the
    Western Interconnection.

6.  To use an open and transparent process. The transmission assessment
    will be available to any interested party.

**[General Approach]{.underline}**

In order to meet the goals of this effort, the planning process must
integrate the planning activities that provide for ongoing load growth,
interconnecting new generation, and ensuring reliability standards are
met. The goals look forward into the future, the process must be
proactive in nature.

*The NTAC will develop and publish an annual Transmission Expansion
Assessment for the NWPP region for the 10 year planning horizon.* The
Transmission Expansion Assessment will identify costs, benefits,
impacts, and other relevant information regarding transmission expansion
for reliability, transmission for new resources, and additional
expansion to support a competitive supply of electricity for the NWPP
region. The NTAC will not allocate benefits and/or costs of the
Transmission Expansion Assessment. The Transmission Expansion Assessment
will be a unified regional transmission plan ("one utility concept") and
will not replace or supercede existing tariffs or other existing legal
obligations.

All participants are expected to provide necessary information (studies,
options, expansion plans, etc.) to NTAC on a sufficient and timely
basis, including issues that may have potential effects on the
transmission system.

NTAC will use consensus to identify necessary and feasible studies to be
performed. The studies performed will be completed within the
limitations of resources provided by the participants. If additional
funds or resources are requested by NTAC from the TPC in order to
perform these studies then TPC will have the responsibility of approving
or disapproving that funding. The TPC admits new members who are willing
to share the TPC's costs on a pro rata basis.

The following are the responsibilities of the participants in this
process:

-   **NWPP TPC** -- oversight, review, and funding. The TPC will select
    the NTAC Chairman.

-   **NTAC** -- NTAC participants will provide input and resources to
    perform all the necessary studies, work and analyses necessary to
    develop the annual Transmission Expansion Assessment. NTAC will
    select the Vice Chairman.

-   **NWPP Staff** -- provide facilitation, coordination, and
    dissemination of information.

-   **Transmission Providers** -- retain local planning responsibilities
    within the NWPP area to ensure reliability of their systems.

# NTAC Expected Duties

1.  The NTAC will coordinate the development of a consistent Load and
    Resource database in cooperation with other related groups such as
    CREPC's WRAT, PNUCC, and the NWPCC.

2.  The NTAC will provide a list of committed transmission additions in
    its Transmission Expansion Assessment.

3.  The NTAC will coordinate the development of a consistent database
    and methods to support economic and production cost studies and
    resource adequacy. This will include data support for northwest
    hydro modeling.

4.  The NTAC will refine Northwest data used in the SSG-WI path
    utilization report, and suggest/develop improvements or enhancements
    to the report to ensure understanding of uses of the Northwest
    transmission system.

5.  Represent the NW Sub-Regional study effort at the SSG-WI PWG.
    Information submitted for support of the SSG-WI studies will be
    derived from NTAC's methods and database.

6.  The NTAC will perform annual assessment of the NWPP transmission
    system by performing studies to:

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a.  Estimate future transmission usage and congestion patterns with new
    resources and load growth scenarios. A broad participant involvement
    process will be used to identify the necessary scenarios.

b.  Estimate the costs of expansion and assess effects of proposed
    transmission and resource expansion scenarios on future transmission
    use patterns and congestion.

c.  Evaluate additional transmission expansion options and other
    alternatives proposed by participants.

**[Process]{.underline}**

Define existing System - Capability

Base Case

-   Decide Base Year

-   Committed Transmission Projects

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```
-   Committed Resource Additions

-   Common Load Forecast

-   Established a Capacity Floor

-   Is the System Adequate

-   Identify existing desired interconnection points for new generation

Problems/Needs

-   Existing Transmission Constraints and Needs

-   Potential Resources to Loads (IRP)

-   Solicit Resource Plans

-   SSG-WI Planning Group Needs

-   Northern California

-   Rocky Mountain

-   IPPs to potential Loads

-   Renewables

Solutions/Ideas

-   Solicit Transmission Plans

-   Solicit Alternatives including non-wires

-   Renewables

Audience

-   PNUCC-TIG

-   SSG-WI

-   RRG/RTO West

-   Regulatory Bodies

-   Individual Participants

-   WGA

**[Schedule]{.underline}**

To be determined.

Additional information on the Northwest Sub-regional Planning Group will
be posted under the Northwest Power Pool's web site at
[http://www.nwpp.org](http://www.nwpp.org/).

***APPENDIX G---Glossary of Terms***

Ancillary Services Interconnected Operations Services identified by the
Federal Energy of electricity between purchasing and selling entities
and which a transmission provider must include in an open access
transmission tariff.

Available Transfer Capability (ATC) A measure of the transfer capability
remaining in the physical transmission network for further commercial
activity over and above already committed uses.

Biomass Any organic material not derived from conventional fossil fuels.
Examples are animal waste, agricultural or forest by-products, and
municipal refuse.

Capability The maximum load which a generator, turbine, transmission
circuit, apparatus, stations, or system can supply under specified
conditions for a given time interval, without exceeding approved limits
of temperature and stress.

Capacity Capacity is the maximum load of electricity that equipment can
carry. Synonymous with capability.

Capacity Factor The ratio of the total energy generated by a generating
unit for a specified period to the maximum possible energy it could have
generated if operated at the maximum capacity rating for the same
specified period, expressed as a percent.

Combined-cycle combustion turbine (CCCT) A electrical generation device
powered by fossil fuel (natural gas), that combines a combustion turbine
with a steam turbine to produce electrical generation.

Combined Heat and Power (CHP) The use of a single prime fuel source such
as reciprocating engine or gas turbine to generate both electrical and
thermal energy to optimize fuel efficiency. Also known as cogeneration.

Congestion Refers to when transmission paths are constrained, which
limits power transactions because of insufficient capacity. Congestion
can be relieved by increasing generation or by reducing load.

Congestion Costs Costs that arise from re-dispatching thermal generation
to enforce transmission constraints.

Control Area A geographical area in which a utility is responsible for
balancing generation and load.

Daily Peak The daily peak is the greatest amount of electricity demanded
during a one-hour period in a day.

Demand The rate at which electric energy is required by a system, part
of a system, or a piece of equipment expressed in megawatts,
megavolt-amperes, or other suitable unit at a given instant or averaged
over any designated period of time.

Average The demand on, or the power output of, an electric system or any
of its parts over any interval of time, as determined by dividing the
total number of kilowatt-hours by the number of units of time in the
interval.

Coincident The sum of two or more demands that occur in the same demand
interval.

Firm The maximum 60-minutes coincident load for the month specified. It
includes transmission system losses and standby demand, and excludes
station service, self load, load management, and interruptible loads.

Maximum (Peak) The greatest of a particular type of demand occurring
within a specified period.

Demand-side Management (DSM) Methods of managing electrical resources
that affect use, rather than generation, of electricity, e.g., energy
efficiency or load control measures.

Discount rate An interest rate that reflects the value of money over
time. In comparing alternatives for a decision, a discount rate is
applied to make different monetary stream flows equivalent, in terms of
a present value or a levelized value.

Distributed generation Locating of small amounts of generation located
on a distribution system for the purpose of meeting local peak loads,
and/or displacing the need to build/upgrade larger-scale, centralized
generation facilities.

EHV Extra-high voltage. Refers to transmission lines with voltage levels
higher than high voltage (HV) but lower than ultra-high voltage (UHV)
levels, and generally considered to range from the 345 kV class through
the 800 kV class of voltages.

Electric demand The instantaneous electric requirement of a power
system, usually expressed in units such as megawatts (MW) or kilowatts
(kW).

Energy Electric energy is usually measured in gigawatt hours.

Generation The act or process of producing electric energy from other
forms of energy; also the amount of energy so produced.

Gross Generation The total amount of electric energy produced by a
generating station or stations, measured at the generator terminals.

Hydro A term used to identify a type of electric generating station,
capacity, or capability, or output in which the source of energy for the
prime mover is falling water.

Net Generation Gross generation less station use.

Independent Power Producer Generation (IPP) A general term embracing
facilities named in the Public Utility Regulatory Policies Act
(cogenerators and small power producers) and any other independent power
producer generating facilities connected to the utility system
(excluding self generation). External IPP resources are those which are
located outside of the service area of the utility purchasing the
generation. A wheeling utility provides transmission service for the
external IPP. Internal IPP resources are those which are located within
the service area of the utility purchasing the generation or are
radially connected to the purchasing utility and do not require wheeling
by another utility.

Pumped Storage Plant A power plant utilizing an arrangement whereby
electric energy is generated for peak load use by utilizing water pumped
into a storage reservoir usually during off-peak periods. A pumped
storage plant may also be used to provide reserve generating capacity.

Thermal A term used to identify a type of electric generating station,

capacity, or capability, or output in which the source of energy for the
prime mover is heat.

Cogeneration Equipment used to produce electric energy and forms of
useful thermal energy, such as heat or steam, used for industrial,
commercial, heating or cooling purposes, through sequential use of
energy. Combined Cycle generation is not considered cogeneration.

Gigawatt 1000 Megawatt

Grid The grid is the network of transmission facilities over which
electricity travels.

Heat rate (Average) Measure of generating station thermal efficiency,
generally expressed as Btu per (net) kWh. Computed by dividing total Btu
content of fuel burned (or heat released from a nuclear reaction) by the
resulting net kWh generated.

Incremental heat rate Amount of thermal energy needed to produce the
next kilowatt-hour of electric energy for any given level of electric
power generation.

Integrated Gasification Combined Cycle (IGCC) Power generation
technology that produces electrical power by combusting coal in the
absence of sufficient oxygen to produce a low-Btu fuel gas, which is
burned in a combined cycle combustion turbine.

Kilowatt A kilowatt is a measure of electrical power equal to 1,000
watts. A watt is the rate at which electricity is generated or consumed.
Ten 100-watt bulbs use one kilowatt of electricity.

Kilowatt --hour A kilowatt-hour is a basic unit of electricity equal to
one kilowatt or 1,000 watts of power used for one hour.

Levelized costs The expression of costs on an equal, per-unit basis,
taking into account an appropriate interest rate. A home mortgage
payment is an example of a levelized cost.

Line loss The electric energy lost (dissipated) in transmission and
distribution lines and their associated equipment, usually through heat
and vibration. Varies with the current (amperes) of the line. If the
current doubles, the losses will increase by a factor of four.

LMP Locational Marginal Price. The marginal cost of supplying the next
increment of demand. Also: shadow price of hourly load resource balance
operating constraint.

Load The amount of electric power delivered or required at any specified
point or points on a system. Load originates primarily at the power
consuming equipment of the customers. See DEMAND.

Firm Load Electric power load (including standby demand) intended to be
served at all times during the period covered by a commitment, even
under adverse conditions.

Interruptible Demand (Load) Electric power load (including load
management) which may be curtailed at the supplier's discretion, or in
accordance with a contractual agreement. In some instances, the demand
reduction may be affected by direct action of the system operator
(remote tripping) after notice to the customer in accordance with
contractual provisions. For example, demands that can be interrupted to
fulfill planning or operating reserve requirements normally should be
reported as interruptible demand.

Direct Control Load Management A procedure in which customer demand can
be controlled through the direct action of the system operator through
actual interruption of power supply to individual appliances or
equipment on the customer's premises. This type of control usually
reduces the demand of residential customers.

load factor The ratio of average load to the peak load during a
specified period of time; expressed in percent.

Load Management The management of load patterns in order to better
utilize the facilities of the system. Generally, load management
attempts to shift load from peak use periods to other periods of the day
or year.

Losses The general term applied to energy (kilowatt-hours) and power
(kilowatts) lost when operating an electric system, occurring mainly as
energy turns to waste heat in electrical conductors and apparatus.

LSE Load Serving Entity

Marginal cost The cost of producing the marginal, or next, unit of power
to be generated.

Marginal cost pricing As applied in the utility industry, a method of
pricing whereby the price for each unit of energy is set equal to the
cost of producing the next or most recent unit.

Marginal energy costs 1) The cost of producing or saving the last unit
of energy; 2) For a generating resource, the cost to produce one more
kilowatt-hour of electricity.

Megawatt A megawatt is one million watts or 1,000 kilowatts.

Nameplate rating The full-load electrical quantities assigned by the
designer to a generator and its prime mover or other piece of electrical
equipment, such as transformers and circuit breakers, under standardized
conditions, expressed in amperes, kilovoltamperes, kilowatts, volts, or
other appropriate units. Usually indicated on a nameplate attached to
the individual machine or device.

Net The gross capacity of a generating unit as measured at the generator
terminals less the power required for the auxiliary equipment (such as
fan motors, pump motors, and other station service equipment essential
to operate the unit).

Net Dependable Capability (Net Capability) The maximum load which a
generating unit, power plant, or system can supply under specified
conditions for a given interval, without exceeding approved limits of
temperature and stress. When used in reference to a system or plant,
capability includes all generating units except those whose sole
function is to supply emergency power for startup and shutdown. It
includes the capability of units that may be temporarily inoperable
because of maintenance, forced outage, or other reasons, or only
operable at less than full output. It excludes power required for plant
operation.

Net energy The electric energy requirements of a system. It is defined
as system net generation plus energy received from others less energy
delivered to others. It includes system losses but excludes energy
required for "pumping up" pumped storage plants.

Network A network is a system of transmission and distribution lines
cross-connected to provide multiple power feeds to an area. A network is
usually installed in urban areas. Networks make it possible to restore
power quickly to customers by switching them to another circuit.

Nominal discount rate An interest rate that includes inflation

Nomogram Graph for displaying data (i.e., transfer capability) based
upon certain variable values such as temperature, loads, generation, and
line conditions.

Outage The period during which a generating unit, transmission line, or
other facility is out-of-service.

Forced outage The shutting down of a generating unit, transmission line,
or other facility, for emergency reasons.

Scheduled outage The shutdown of a generating unit, transmission line,
or other facility, for inspection or maintenance, in accordance with an
advance schedule.

Peak demand Peak demand is the maximum amount of electricity necessary
to supply customers. Peak periods fluctuate by season. Peak demand
generally occurs in the morning during the winter and in the afternoon
during the summer.

Phase shifter Piece of electrical equipment that acts as a \"one-way
valve\" for electricity, allowing it to pass along a conductor in one
direction but increasing the resistance to flows in the other.

Planning Margin The Planning Margin selected is 15% of the annual peak
hour when the loads plus long-term firm sales minus long-term firm
purchases result in the largest requirement on the system. This target
reserve level assumed to provide sufficient future resources to cover
forced outages, provide operating reserves regulatory margin, and demand
growth uncertainty.

Power pool Two or more interconnected power systems operated as a system
and pooling their resources to supply the power and energy requirements
of the systems in a reliable and economical manner.

Present value 1) The value of current dollars of a flow of cash over
time; 2) In bond financing, the value in current dollars of debt service
payments or reductions over the remaining life of the bonds.

Real discount rate An interest rate adjusted to remove the effect of
inflation

Reliability Reliability is the assurance of a continuous supply of
electricity for customers at the proper voltage and frequency.

Reserve margin For a power plant or transmission facility, extra
capacity above the amount projected to be needed, to allow for
unanticipated demand for power, equipment failure, or other unforeseen
events. Measured as percentage of peak load, or simply a megawatt
number.

Resource adequacy The sufficiency of generation/demand-side management
(DSM) resources to serve loads and meet operating reserve requirements
within the constraints of the transmission system and the operation of
the generating resources. The timeframe for a resource adequacy standard
generally needs to be two to three years out because the construction of
new generation generally requires a two, or more, year timeframe.

RPS Renewable Portfolio Standards. RPS seeks to ensure that a minimum
amount of renewable energy is included in the portfolio of electricity
resources serving a state or country. Portfolio standards have been
primarily a result of state-based electric restructuring efforts. Texas,
Arizona Nevada and California have adopted various non-mandatory
standards.

Series capacitor bank An installation of capacitors with fuses and
associated equipment in series with a line. Generally located near the
center of a line (but can be located at any point). Used to increase the
capability of interconnections and in some cases to achieve the most
advantageous and economical division of loading between lines operating
in parallel.

Shadow Price The shadow price of a constraint (e.g., a transmission
capacity constraint) is the dollar amount by which the optimal objective
function (e.g., minimizing total production costs of the system) is
improved when the constraint limit is increased by one unit. Synonymous
with marginal price, marginal cost, or opportunity cost.

Simple-Cycle Combustion Turbine (SCCT) A combustion turbine, fueled with
fossil fuel(natural gas) used for the generation of electricity without
the recovery of waste heat.

Spot Market As conventionally defined, the spot market refers to
day-ahead and real-time purchases and sales of electricity. .The IRP
defines spot market more broadly to include market purchases and sales,
outside of existing long-term contracts and pursuant to the model
dispatch logic.

SSG-WI Seams Steering Group--Western Interconnection

> SSG-WI serves as the discussion forum for facilitating the creation of
> a Seamless Western Market and for proposing resolutions for issues
> associated with differences in RTO practices and procedures.

Substation A substation is a facility, generally a small building with a
fenced-in yard containing switches, transformers and other equipment
used to adjust voltages and monitor circuits.

Summer peak period The summer peak period begins on June 1 and runs
through September 30.

System The physically connected generation, transmission, distribution
and other facilities operated as an integral unit under one control,
management or operating supervision, often referred to as "electric
system," "electric power system" or "power system."

System peak The System peak is the maximum load on an electrical system
during a given period of time.

Thermal Rating The maximum amount of electrical current that a
transmission line or electrical facility can conduct over a specified
time period before it sustains permanent damage by overheating or before
it violates public safety requirements.

Transfer The transfer of electrical energy across a point or points of
interconnection during a stated period.

Transmission lines Transmission lines are heavy wires that carry large
amounts of electricity over long distances from generating stations to
substations. Transmission lines are held high above the ground on tall
structures called transmission towers.

Transmission access Rights granted to non-owners and non-operators of
transmission facilities to deliver energy along transmission lines to
wholesale customers.

Transmission congestion Condition that exists when market participants
seek to dispatch generation in a pattern which would result in power
flows that cannot be physically accommodated by the transmission system.

Transmission congestion contract Financial instrument that provides a
hedge against congestion price differences between zones.

Transmission interconnection 1) A system consisting of two or more
individual power systems operating with connecting lines to make a
larger system, thus permitting the sharing of generation reserves and
providing alternative transmission paths to serve customers during line
outages; 2) The connection between two power systems.

WGA Western Governor's Association. WGA addresses important policy and
governance issues in the West, advances the role of the Western states
in the federal system, and strengthens the social and economic fabric of
the region. WGA develops policy and carries out programs in the areas of
natural resources, the environment, human services, economic
development, international relations and state governance. WGA acts as a
center of innovation and promotes shared development of solutions to
regional problems.

Water Conditions (as defined in the SSG-WI study)

Low Hydro Runoff and storage regulation which reflects operation under
the lowest quartile of streamflow conditions that have occurred during a
specified period, usually the period of historical record. 1930 inflows
were used for the PNW system.

Medium Hydro Runoff and storage regulation which reflects operation
under average streamflow conditions across all four quartiles and that
have occurred during a specified period, usually the period of
historical record. 1953 inflows were used for PNW inflows.

High Hydro Runoff and storage regulation which reflects operation under
the highest quartile of streamflow conditions that have occurred during
a specified period, usually the period of historical record. 1948
inflows were used for PNW inflows.

Watt A watt is the measure of work that electricity can do. Watts are
commonly used to rate appliances.

WECC Western Electricity Coordinating Council (formerly known as the
Western Systems Coordinating Council, or WSCC); an organization that
works with its members to assess and enforce compliance with established
criteria and policies for ensuring the reliability of the region's
electric service.

[^1]: Simulating the dispatch of hydro units on cascaded river systems
    is significantly more difficult than predicting thermal system
    operation for several reasons. First, the pondage storage capability
    and low incremental cost result in a scarcity of energy and not
    capacity. Market Simulator solves each hour's dispatch sequentially
    and independently. To properly account for the load leveling
    capabilities of the river units, require linking the dispatch
    problems from multiple periods. Further, run-of-river simulation
    requires that water time delay effects be predicted. Finally,
    exogenous factors such as fish, recreation and irrigation place
    demands on hydro dispatch that are not directly associated with
    power market economics. For all these reasons, and because good
    historical/forecasted dispatch data for large WECC river systems is
    available, Market Simulator requires that hourly dispatch for hydro
    units be specified as input.

[^2]: Wind plant capacity factors are estimated to average 42% in the
    Mountain states (MT, WY) and 34% in the coastal states (WA, CA, NV),
    with approximately 80% of new capacity additions planned in the
    Mountain states to 2013. This equiates to an average wind capacity
    factor of 40% across the entire WECC region.

[^3]: Testimony of James H. Caldwell, AWEA, to the U.S. Senate Committee
    on Energy and Natural Resources, Subcommittee on Water and Power,
    August 7, 2001.

[^4]: Current (mid-2003) WECC peak summer loads are approximately
    138,000 GWe. Peak summer loads in 2008 and 2013 are assumed in the
    modeling to be approximately 150,000 and 167,000 GWe, respectively.
    Thus, the assumed load growth from now until 2013 is 2%. If the load
    growth instead were 1%, today's load of 138,000 GWe would grow to
    152,000 GWe by 2013, approximately the assumed load for 2008.

[^5]: For example, compact fluorescent lights reduce peak loads at a
    fraction of the cost of serving peak loads with gas-fired
    generation, and they save energy at less than a penny per kWh.

[^6]: A downside of this approach is that the difference between 2008
    and 2013 is only one possible result. Non-wires alternatives may be
    available to meet this difference and more. However, the appropriate
    level of non-wire alternatives cannot be determined in this way. At
    this high level of SSG-WI planning one can gain insight by doing
    this analysis, and possibly create a target for non-wires
    contributions between now and 2013.

[^7]: Some resources would have been retired and replaced by other,
    perhaps more efficient resources, but the total number of GWe would
    be the same.