Renewable Fuels Module
The NEMS Renewable Fuels Module (RFM) provides natural resources supply
and technology input information for projections of new central-station
U.S. electricity generating capacity using renewable energy resources.
The RFM has seven submodules representing various renewable energy sources,
biomass, geothermal, conventional hydroelectricity, landfill gas, solar
thermal, solar photovoltaics, and wind1.
Some renewables, such as landfill gas (LFG) from municipal solid waste
(MSW) and other biomass materials, are fuels in the conventional sense
of the word, while others, such as water, wind, and solar radiation, are
energy sources that do not involve the production or consumption of a fuel.
Renewable technologies cover the gamut of commercial market penetration,
from hydroelectric power, which was one of the first electric generation
technologies, to newer power systems using biomass, geothermal, LFG, solar,
and wind energy.
The submodules of the RFM interact primarily with the Electricity Market
Module (EMM). Because of the high level of integration with the EMM,
the final outputs (levels of consumption and market penetration over time)
for renewable energy technologies are largely dependent upon the EMM.
Because some types of biomass fuel can be used for either electricity generation
or for the production of liquid fuels, such as ethanol, there is also some
interaction with the Petroleum Market Module (PMM), which contains additional
representation of some biomass feedstocks that are used primarily for liquid
fuels production.
Projections for residential and commercial grid-connected photovoltaic
systems are developed in the end-use demand modules and not in the RFM;
see the Distributed Generation and Combined Heat and Power descriptions
in the “Commercial Demand Module” section of the report.
Key Assumptions
Nonelectric Renewable Energy Uses
In addition to projections for renewable energy used in central station
electricity generation, the AEO2009 contains projections of nonelectric
renewable energy uses for industrial and residential wood consumption,
solar residential and commercial hot water heating, biofuels blending in
transportation fuels, and residential and commercial geothermal (ground-source)
heat pumps. Assumptions for their projections are found in the residential,
commercial, industrial, and petroleum marketing sections of this report.
Additional minor renewable energy applications occurring outside energy
markets, such as direct solar thermal industrial applications or direct
lighting, off-grid electricity generation, and heat from geothermal resources
used directly (e.g., district heating and greenhouses) are not included
in the projections.
Electric Power Generation
The RFM considers only grid-connected central station electricity generation
systems. The RFM submodules that interact with the EMM are the central
station grid-connected biomass, geothermal, conventional hydroelectricity,
landfill gas, solar (thermal and photovoltaic), and wind submodules, which
provide specific data or estimates that characterize that resource. A
set of technology cost and performance values is provided directly to the
EMM and are central to the build and dispatch decisions of the EMM. The
technology cost and performance values are summarized in Table 8.2 in the
chapter discussing the EMM. Overnight capital costs are presented in Table
13.1 and the assumed capacity factors for new plants in Table 13.2.
Capital Costs
Capital costs for renewable technologies are affected by several factors.
Capital costs for technology to exploit some resources, especially geothermal,
hydroelectric, and wind power resources, are assumed to be dependent on
the quality, accessibility, and/or other site-specific factors in the areas
with exploitable resources. These factors can include additional costs
associated with reduced resource quality; need to build or upgrade transmission
capacity from remote resource areas to load centers; or local impediments
to permitting, equipment transport, and construction in good resource areas
due to siting issues, inadequate infrastructure, or rough terrain.
Short-term cost adjustment factors increase technology capital costs as
a result of a rapid U.S. buildup in a single year, reflecting limitations
on the infrastructure (for example, limits on manufacturing, resource assessment,
and construction expertise) to accommodate unexpected demand growth. These
factors, which are applied to all new electric generation capacity, are
a function of past production rates and are further described in The Electricity
Market Module of the National Energy Modeling System: Model Documentation
Report, available at http://www.eia.doe.gov/bookshelf/docs.html.
Also assumed to affect all new capacity types are costs associated with
construction commodities. Through the middle of this decade, the installed
cost for most new plants was observed to increase. Although several factors
contributed to this cost escalation, some of which may be more or less
important to specific types of new capacity, much of the overall cost increase
was correlated with increases in the cost of construction materials, such
as bulk metals, specialty metals, and concrete. Capital costs in AEO2009 are specifically linked to the projections for the metals producer price
index found in the Macroeconomic Module of NEMS.
Independent of the other two factors, capital costs for all electric generation
technologies, including renewable technologies, are assumed to decline
as a function of growth in installed capacity for each technology.
For a description of NEMS algorithms lowering generating technologies’
capital costs as more units enter service (learning), see “Technological
Optimism and Learning” in the EMM chapter of this report. A detailed description
of the RFM is provided in the EIA publication, Renewable Fuels Module of
the National Energy Modeling System, Model Documentation 2005, DOE/EIA-M069(2005)
(Washington, DC, 2005).
Solar Electric Submodule
Background
The Solar Electric Submodule currently includes both concentrating solar
power (thermal) and photovoltaics, including two solar technologies: 50
megawatt central receiver (power tower) solar thermal (ST) and 5 megawatt
single axis tracking-flat plate photovoltaic (PV) technologies. PV is assumed
available in all thirteen EMM regions, while ST is available only in the
six Western regions with the arid atmospheric conditions that result in
the most cost-effective capture of direct sunlight. Capital costs for both
technologies are determined by EIA using multiple sources, including public
reports of recent solar thermal capacity additions. Most other cost and
performance characteristics for ST are obtained or derived from the August
6, 1993, California Energy Commission memorandum, Technology Characterization
for ER 94; and, for PV, from the Electric Power Research Institute, Technical
Assessment Guide (TAG) 1993. In addition, capacity factors are obtained
from information provided by the National Renewable Energy Laboratory (NREL).
Assumptions
- Capacity factors for solar technologies are assumed to vary by time of
day and season of the year, such that nine separate capacity factors are
provided for each modeled region, three for time of day and for each of
three broad seasonal groups (summer, winter, and spring/fall). Regional
capacity factors vary from national averages. The current reference case
solar thermal annual capacity factor for California, for example, is assumed
to average 40 percent; California’s current reference case PV capacity
factor is assumed to average 24.6 percent.
- Because solar technologies are more expensive than other utility grid-connected
technologies, early penetration will be driven by broader economic decisions
such as the desire to become familiar with a new technology, environmental
considerations, and the availability of limited Federal subsidies. Minimal
early years’ penetration is included by EIA as “floor” additions to new
generating capacity (see “Supplemental and Floor Capacity Additions” below).
- Solar resources are well in excess of conceivable demand for new capacity;
energy supplies are considered unlimited within regions (at specified daily,
seasonal, and regional capacity factors). Therefore, solar resources are
not estimated in NEMS. In the seven regions where ST technology is not
modeled, the level of direct, normal insolation (the kind needed for that
technology) is assumed to be insufficient to make that technology commercially
viable through 2030.
- NEMS represents the Energy Policy Act of 1992 (EPACT92) permanent 10-percent
investment tax credit (ITC) for solar electric power generation by tax-paying
entities. In addition, the current 30-percent ITC scheduled to expire at
the end of 2016, is also represented to qualifying new capacity installations.
Wind-Electric Power Submodule
Background
Because of limits to windy land areas, wind is considered a finite resource,
so the submodule calculates maximum available capacity by Electricity Market
Module Supply Regions. The minimum economically viable average wind speed
is about 14 mph, and wind speeds are categorized by annual average wind
speed based on a classification system originally from the Pacific Northwest
Laboratory. The RFM tracks wind capacity (megawatts) by resource quality,
and costs within a region and moves to the next best wind resource when
one category is exhausted. For AEO2009, wind resource data on the amount
and quality of wind per EMM region come from the National Renewable Energy
Laboratory2 The technological performance, cost, and other wind data used
in NEMS are derived by EIA from available data and from available literature.3 Maximum wind capacity, capacity factors, and incentives are provided to
the EMM for capacity planning and dispatch decisions. These form the basis
on which the EMM decides how much power generation capacity is available
from wind energy. The fossil-fuel heat rate equivalents for wind are used
for energy consumption calculation purposes only.
Assumptions
- Only grid-connected (utility and nonutility) generation is included. Projections
for distributed wind generation are included in the commercial and residential
modules.
- In the wind submodule, wind supply costs are affected by three modeling
measures: addressing (1) average wind speed, (2) distance from existing
transmission lines, and (3) resource degradation, transmission network
upgrade costs, and market factors.
- Available wind resource is reduced by excluding all windy lands not suited
for the installation of wind turbines because of: excessive terrain slope
(greater than 20 percent); reservation of land for non-intrusive uses (such
as National Parks, wildlife refuges, and so forth); inherent incompatibility
with existing land uses (such as urban areas, areas surrounding airports
and water bodies, including offshore locations); insufficient continguous
windy land to support a viable wind plant (less than 5 square kilometers
of windy land in a 100 square kilometer area). Half of the wind resource
located on military reservations, U.S. Forest Service land, state forested
land, and all non-ridge-crest forest areas are excluded from the available
resource base to account for the uncertain ability to site projects at
such locations. These assumptions are detailed in the Draft Final Report
to EIA on Incorporation of Existing Validated Wind Data into NEMS, November
2003.
- Capital costs for wind technologies are assumed to increase in response
to (1) declining natural resource quality, such as terrain slope, terrain
roughness, terrain accessibility, wind turbulence, wind variability, or
other natural resource factors, as the best sites are utilized (2) increasing
cost of upgrading existing local and network distribution and transmission
lines to accommodate growing quantities of remote wind power, and (3) market
conditions, such as the increasing costs of alternative land uses, including
aesthetic or environmental reasons. Capital costs are left unchanged for
some initial share, then increased 20, 50, 100 percent, and finally 200
percent, to represent the aggregation of these factors.
- Proportions of total wind resources in each category vary by EMM region.
For all thirteen EMM regions combined, 1.3 percent of windy land is available
with no cost increase, 5.4 percent is available with a 20 percent cost
increase, 11.2 percent is available with a 50 percent cost increase, 27.3
percent is available with a 100 percent cost increase, and almost 54.8
percent of windy land is assumed to be available with a 200 percent cost
increase.
- Depending on the EMM region, the cost of competing fuels, and other factors,
wind plants can be built to meet system capacity requirements or as a “fuel
saver” to displace generation from existing capacity. For wind to penetrate
as a fuel saver, its total capital and fixed operations and maintenance
costs minus applicable subsidies must be less than the variable operating
costs, including fuel, of the existing (non-wind) capacity. When competing
in the new capacity market, wind is assigned a capacity credit that declines
based on its estimated contribution to regional reliability requirements.
- Because of downwind turbulence and other aerodynamic effects, the model
assumes an average spacing between turbine rows of 5 rotor diameters and
a lateral spacing between turbines of 10 rotor diameters. This spacing
requirement determines the amount of power that can be generated from wind
resources, about 6.5 megawatts per square kilometer of windy land, and
is factored into requests for generating capacity by the EMM.
- Capacity factors are assumed to increase to a 46 percent in the best wind
class resulting from taller towers, more reliable equipment, and advanced
technologies. Capacity factors for each wind class are calculated as a
function of overall wind market growth. The capacity factors are assumed
to be limited to about 48 percent for an average Class 6 site. As better
wind resources are depleted, capacity factors are assumed to go down. By
2030, the typical wind plant build will have a somewhat lower capacity
factor than those found in the best wind resource area.
- AEO2009 does not allow plants constructed after 2009 to claim the Federal
Production Tax Credit (PTC), a 2 cent per kilowatt-hour tax incentive
that is set to expire on December 31, 2009. Wind plants are assumed to
depreciate capital expenses using the Modified Accelerated Cost Recovery
Schedule with a 5-year tax life.
Offshore wind resources are represented as a separate technology from onshore
wind resources. Offshore resources are modeled with a similar model structure
as onshore wind. However, because of the unique challenges of offshore
construction and the somewhat different resource quality, the assumptions
with regard to capital cost, learning-by-doing cost reductions, and variation
of resource exploitation costs and performance differ significantly from
onshore wind.
- Like onshore resources, offshore resources are assumed to have an upwardly
sloping supply curve, in part influenced by the same factors that determine
the onshore supply curve (such as distance to load centers, environmental
or aesthetic concerns, variable terrain/seabed) but also explicitly by
water depth.
- Because of the more difficult maintenance challenge offshore, performance
for given annual average wind power density level is assumed to be somewhat
reduced by reduced turbine availability. Offsetting this, however, is
the availability of resource areas with higher overall power density than
is assumed available onshore. Capacity factors for offshore are limited
to be about 50 percent for a Class 7 site.
- Cost reductions in the offshore technology result in part from learning
reductions in onshore wind technology as well as from cost reductions unique
to offshore installations, such as foundation design and construction techniques.
Because offshore technology is significantly less mature than onshore
wind technology, offshore-specific technology learning occurs at a somewhat
faster rate than on-shore technology.
Geothermal-Electric Power Submodule
Background
The Geothermal-Electric Submodule (GES) estimates the generating capacity
and output potential of 89 hydrothermal sites in the Western United States.
This estimation is based on two studies: New Geothermal Site Identification
and Qualification, prepared by GeothermEx, Inc for the California Public
Utility Commission, and Western Governors’ Association Geothermal Task
Force Report, which was co-authored by several geothermal experts from
the public and private sectors. These studies focus on geothermal resources
with confirmed temperatures greater than 100 Celsius, which is generally
considered the threshold for economically feasible conventional development.
While EIA had previously distinguished between binary and dual flash technologies,
this is no longer an essential component of cost estimates. Instead, these
studies incorporate expected power plant cost and performance based on
each confirmed resource temperature. This enables greater projection precision
relative to a static choice between two technologies. All plants are assumed
to operate at 90 percent capacity factor. Enhanced Geothermal Systems (EGS),
such as hot dry rock, are not included as potential resources since this
technology is still in development and is not expected to be in significant
commercial use within the projection horizon. As part of EPACT 2005,
the U.S. Geological Survey recently completed its comprehensive review
of all domestic hydrothermal resources. While the final data show overall
capacity estimates similar to the ones presented in the above-mentioned
studies, there are undoubtedly distinctions in individual site characterizations
and methods used for estimating capacity. Although the final aggregate
data has been released, the assumptions and individual site estimates have
not. Therefore, the data will not be incorporated into the AEO until 2010.
The two studies off of which EIA estimates are based maintain separate
capital cost components for each site’s development. The GeothermEx study
divided individual site costs into four components: exploration, confirmation,
development, and transmission. Site exploration is a small component of
aggregate costs, oftentimes being zero. Confirmation and transmission
costs may be significant, however the vast majority of capital costs are
classified under site development which includes power plant construction.
The WGA report, which was used to estimate geothermal potential outside
of the GeothermEx database region, did not provide site specific, separate
capital cost components. However, it did provide some sites with two levels
of capital costs, meaning a portion of the resource could be developed
at a lower cost than the remaining potential. Therefore, EIA maintained
two categories of site specific capital development costs, with a cost
premium placed on some sites beyond their most economic resource. Site
specific operation and maintenance costs are also included in the submodule.
As a result of revised supply estimations, the annual site build limit
has been relaxed but still remains. Geothermal development is limited
to 25 MW of generating capacity until 2010, when the 50 MW limit goes into
effect for the remainder of the projection period.
Assumptions
- Existing and identified planned capacity data are obtained directly by
the EMM from Forms EIA-860A (utilities) and EIA-860B (nonutilities) and
from supplemental additions (See Below).
- The permanent investment tax credit of 10 percent available in all projection
years based on the EPACT applies to all geothermal capital costs, except
through December 2010 when the 2-cent production tax credit is available
to this technology and is assumed chosen instead.
- Plants are not assumed to retire unless their retirement is reported to
EIA. Geysers units are not assumed to retire but instead are assigned
the 35 percent capacity factors reported to EIA reflecting their reduced
performance in recent years.
- Capital and operating costs vary by site and year; values shown in Table
8.3 in the EMM chapter are indicative of those used by EMM for geothermal
build and dispatch decisions.
Biomass Electric Power Submodule
Background
Biomass consumed for electricity generation is modeled in two parts in
NEMS. Capacity in the wood products and paper industries, the so-called
captive capacity, is included in the industrial sector module as cogeneration.
Generation by the electricity sector is represented in the EMM, with capital
and operating costs and capacity factors as shown in Table 8.2 in the EMM
chapter, as well as fuel costs, being passed to the EMM where it competes
with other sources. Fuel costs are provided in sets of regional supply
schedules. Projections for ethanol are produced by the Petroleum Market
Module (PMM), with the quantities of biomass consumed for ethanol decremented
from, and prices obtained from, the EMM regional supply schedules.
Assumptions
- Existing and planned capacity data are obtained from Form EIA-860.
- The conversion technology represented, upon which the costs in Table 8.3
in the EMM chapter are based, is an advanced gasification-combined cycle
plant that is similar to a coal-fired gasifier. Costs in the reference
case were developed by EIA to be consistent with coal gasifier costs.
Short-term cost adjustment factors are used.
- Biomass cofiring can occur up to a maximum of 15 percent of fuel used in
coal-fired generating plants.
Fuel supply schedules are a composite of four fuel types: forestry materials,
wood residues, agricultural residues and energy crops. Energy crop data
are presented in yearly schedules from 2010 to 2030 in combination with
the other material types for each region. The forestry materials component
is made up of logging residues, rough rotten salvageable dead wood, and
excess small pole trees.4 The wood residue component consists of primary
mill residues, silvicultural trimmings, and urban wood such as pallets,
construction waste, and demolition debris that are not otherwise used.5 Agricultural residues are wheat straw, corn stover, and a number of other
major agricultural crops.6 Energy crop data are for hybrid poplar, willow,
and switchgrass grown on crop land, pasture land, or on Conservation Reserve
Program lands. In AEO2009, agricultural residues and energy crops are
combined into a single "agricultural sector."7 The maximum amount of resources
in each supply category is shown in Table 13.3.
Landfill-Gas-to-Electricity Submodule
Background
Landfill-gas-to-electricity capacity competes with other technologies using
supply curves that are based on the amount of “high”, “low”, and “very
low” methane producing landfills located in each EMM region. An average
cost-of-electricity for each type of landfill is calculated using gas collection
system and electricity generator costs and characteristics developed by
EPA’s “Energy Project Landfill Gas Utilization Software” (E-PLUS).8
Assumptions
- Gross domestic product (GDP) and population are used as the drivers in
an econometric equation that establishes the supply of landfill gas.
- Recycling is assumed to account for 35 percent of the total waste stream
by 2005 and 50 percent by 2010 (consistent with EPA’s recycling goals).
- The waste stream is characterized into three categories: readily, moderately,
and slowly decomposable material.
- Emission parameters are the same as those used in calculating historical
methane emissions in the EIA’s Emissions of Greenhouse Gases in the United
States 2003.9
- The ratio of “high”, “low”, and “very low” methane production sites to
total methane production is calculated from data obtained for 156 operating
landfills contained in the Government Advisory Associates METH2000 database.10
- Cost-of-electricity for each site was calculated by assuming each site
to be a 100-acre by 50-foot deep landfill and by applying methane emission
factors for “high”, “low”, and “very low” methane emitting wastes.
Conventional Hydroelectricity
The conventional hydroelectricity submodule represents U.S. potential for
new conventional hydroelectric capacity 1 megawatt or greater from new
dams, existing dams without hydroelectricity, and from adding capacity
at existing hydroelectric dams. Summary hydroelectric potential is derived
from reported lists of potential new sites assembled from Federal Energy
Regulatory Commission (FERC) license applications and other survey information,
plus estimates of capital and other costs prepared by the Idaho National
Engineering and Environmental Laboratory (INEEL).11 Annual performance
estimates (capacity factors) were taken from the generally lower but site
specific FERC estimates rather than from the general estimates prepared
by INEEL, and only sites with estimated costs 10 cents per kilowatthour
or lower are included in the supply. Pumped storage hydro, considered a
nonrenewable storage medium for fossil and nuclear power, is not included
in the supply; moreover, the supply does not consider offshore or in-stream
hydro, efficiency or operational improvements without capital additions,
or additional potential from refurbishing existing hydroelectric capacity.
In the hydroelectricity submodule, sites are first arrayed by NEMS region
from least to highest cost per kilowatthour. For any year’s capacity decisions,
only those hydroelectric sites whose estimated levelized costs per kilowatthour
are equal to or less than an EMM determined avoided cost (the least cost
of other technology choices determined in the previous decision cycle)
are submitted. Next, the array of below-avoided cost sites is parceled
into three increasing cost groups, with each group characterized by the
average capacity-weighted cost and performance of its component sites.
Finally, the EMM receives from the conventional hydroelectricity submodule
the three increasing-cost quantities of potential capacity for each region,
providing the number of megawatts potential along with their capacity-weighted
average overnight capital cost, operations and maintenance cost, and average
capacity factor. After choosing from the supply, the EMM informs the hydroelectricity
submodule, which decrements available regional potential in preparation
for the next capacity decision cycle.
Legislation and Regulations
Energy Policy Act of 1992 (EPACT92) and 2005 (EPACT05)
The RFM includes the investment and energy production tax credits codified
in the Energy Policy Act of 1992 (EPACT 92) as amended. The investment
tax credit established by EPACT 92 provides a credit to Federal income
tax liability worth 10 percent of initial investment cost for a solar,
geothermal, or qualifying biomass facility. This credit was raised to 30
percent through 2016 for some solar projects and extended to residential
projects. This change is reflected in the utility, commercial and residential
modules. The production tax credit, as established by EPACT 92, applied
to wind and certain biomass facilities. As amended, it provides a 2 cent
tax credit for every kilowatt-hour of electricity produced for the first
10 years of operation for a wind facility constructed by December 31, 2009
or by December 31, 2010 for other eligible facilities. The value of the
credit, originally 1.5 cents, is adjusted annually for inflation. With
the various amendments, the production tax credit is available for electricity
produced from qualifying geothermal, animal waste, certain small-scale
hydroelectric, landfill gas, municipal solid waste, and additional biomass
resources. Wind, poultry litter and geothermal, and "closed loop"12 biomass
resources receive a 2 cent tax credit for the first 10 years of facility
operations. All other renewable resources receive a 1 cent tax credit
for the first 10 years of facility operations. EIA assumes that biiomass
facilities obtaining the PTC will use "open-loop" fuels, as "closed-loop"
fuels are assumed to be unavailable and/or too expensive for widespread
use during the period that the tax credit is available. The investment
and production tax credits are exclusive of one another, and may not both
be claimed for the same geothermal facility (which is eligible to receive
either).
Alternative Renewable Cases
Renewable Technology Cases
Two cases examine the effect on energy supply using alternative assumptions
for cost and performance of non-hyrdo, non-landfill gas renewable energy
technologies. The High Renewable Cost case examines the effect if technology
costs were to remain at current levels. The Low Renewable Cost case examines
the effect if technology energy costs were reduced by 2030 to 25 percent
below Reference case values.
The High Renewable Cost case does not allow “learning-by-doing” effects
to reduce the capital cost of biomass, geothermal, solar, or wind technologies
or to improve wind capacity factor beyond 2009 levels. The construction
of the first four units of biomass integrated gasification combined cycle
units are still assumed to reduce the technological optimism factor associated
with this technology. Although the cost of biiomass fuels is assumed to
remain the same in this case as in the Reference case, this case assumes
that no energy crops will be available through 2030, consistent with the
"frozen technology" assumptions for the other technologies. All other parameters
remain the same as in the Reference case.
The Low Renewable Cost case assumes that the non-hydro, non-landfill gas
renewable technologies are able to reduce their overall cost-of-energy
produced in 2030 by 25 percent from the Reference case. Because the cost
of supply of renewable resources is assumed to increase with increasing
utilization (that is, the renewable resource supply curves are upwardly
sloping), the cost reduction is achieved by targeting the reduction on
the “marginal” unit of supply for each technology in 2030 for the Reference
case (that is, the next resource available to be utilized in the Reference
case in 2030). This has the effect of reducing costs for the entire supply
(that is, shifting the supply curve downward by 25 percent). As a result
of the overall reduction in costs, more supply may be utilized, and a unit
from higher on the supply curve may result in being the marginal unit of
supply. Thus the actual market-clearing cost-of-energy for a given renewable
technology may not differ by much from the Reference case, although that
resource contributes more energy supply than in the Reference case. These
cost reductions are achieved gradually through "learning-by-doing”, and are only fully realized by 2030.
For wind, biomass, geothermal, and solar technologies, this cost reduction
is achieved by a reduction in overnight capital costs sufficient to achieve
the 10 percent targeted reduction in cost-of-energy. As a result, the
supply of biomass fuel is increased by 10 percent at every price level.
For geothermal, the capital cost of the lowest-cost site available in
the year 2005 is reduced such that if it were available for construction
in 2030, it would have a 10 percent lower cost-of-energy in the High Renewable
case than the cost-of-energy it would have in 2030 were it available for
construction in the Reference case. For solar technologies (both photovoltaic
and solar thermal power), the resource is assumed to be unlimited and the
reductions in cost-of-energy are achieved strictly through capital cost
reduction. Biomass prices is assumed to be reduced 25 percent by 2030 for
a given quantity of fuel supplied. Other assumptions within NEMS are unchanged
from the Reference case.
For the Low Renewable Cost case, demand-side improvements are also assumed
in the renewable energy technology portions of residential and commercial
buildings, industrial processes, and refinery fuels modules. Details on
these assumptions can be found in the corresponding sections of this report.
State RPS Programs
EIA represents various state-level policies generally referred to as Renewable
Portfolio Standards (RPS). These policies vary significantly among states,
but typically require the addition of renewable generation to meet a specified
share of state-wide generation. Any non-discretionary limitations on meeting
the generation or capacity target are modeled to the extent possible.
However, because of the complexity of the various requirements, the regional
target aggregation (described below), and nature of some of the limitations
(also described below), measurement of compliance is assumed to be approximate.
For the AEO2009, regional renewable generation targets were estimated using
the renewable generation targets in each state within the region. In many
cases, regional boundaries intersect state boundaries; in these cases states
were assigned to be within a single region, based on EIA expert judgment
of factors such as predominant load locations and location of renewable
resources eligible for that state’s RPS program. Using state-level RPS
compliance schedules and preliminary estimates of projected sales growth,
EIA estimated the amount of renewable generation required in each state
within a region. Required generation in each state was then summed to the
regional level for each year, and a regional renewable generation share
of total sales was determined, as shown in Table 13.5.
Only targets with established enforcement provisions or established state
funding mechanisms were included in the calculation; goals, provisional
RPS requirements, or requirements lacking established funding were not
included. The California and New York programs require state funding, and
these programs are assumed to be complied with only to the extent that
state funding allows. Compliance enforcement provisions vary significantly
among states and most states have established procedures for waiving compliance
through the use of “alternative compliance” payments, penalty payments,
discretionary regulatory waivers, or retail price impact limits. Because
of the variety of mechanisms, even within a given electricity market region,
these limits are not modeled.
Supplemental and Floor Capacity Additions
For AEO2009, has estimated near-term additions of renewable operating capacity.
These estimates are based on a number of public and proprietary databases
of new project capacity, and provide a plant-specific accounting of new
capacity in 2008 and subsequent years. Because of the significant growth
in this sector during 2008 specific plants are not listed Table 13.6.
Renewable Fuels Module Notes |
