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America’s Energy Future: Technology and Transformation - Summary Edition
3
Key Results from Technology Assessments
This chapter summarizes the detailed assessments presented in Part 2 of this report, organized by subject and chapter as follows:
Energy efficiency (Chapter 4)
Alternative transportation fuels (Chapter 5)
Renewable energy (Chapter 6)
Fossil-fuel energy (Chapter 7)
Nuclear energy (Chapter 8)
Electricity transmission and distribution (Chapter 9).
The chapter annex, Annex 3.A, describes the key methods and assumptions that were used to develop the energy supply, savings, and cost estimates in this report. Additional detailed supporting information can be found in Part 2 of this report and in the following National Academies reports derived from this America’s Energy Future (AEF) Phase I study:
Real Prospects for Energy Efficiency in the United States (NAS-NAE-NRC, 2009c; available at http://www.nap.edu/catalog.php?record_id=12621)
Liquid Transportation Fuels from Coal and Biomass: Technological Status, Costs, and Environmental Impacts (NAS-NAE-NRC, 2009b; available at http://www.nap.edu/catalog.php?record_id=12620)
Electricity from Renewable Resources: Status, Prospects, and Impediments (NAS-NAE-NRC, 2009a; available at http://www.nap.edu/catalog.php?record_id=12619).
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ENERGY EFFICIENCY
The potential for increasing energy efficiency—that is, for reducing energy use while delivering the same energy services—in the United States is enormous. Technology exists today, or is expected to be developed over the normal course of business between now and 2030, that could save about 30 percent of the energy used annually in the buildings, transportation, and industrial sectors. These savings could easily repay, with substantial dividends, the investments involved. In particular, if energy prices were high enough to motivate investment in energy efficiency or if public policies had the same effect, energy use could be lower by 15–17 quads (about 15 percent) in 2020 and by 32–35 quads (about 30 percent) in 2030 than the reference case projection of the U.S. Department of Energy’s Energy Information Administration (EIA). The opportunities for achieving these savings reside in hundreds of technologies, many of them already commercially available and others just about to enter the market.
This section summarizes the capability of energy efficiency technologies to reduce energy use or moderate its growth. Technologies that pay for themselves (in reduced energy costs) after criteria have been applied to reflect experience with consumer and corporate decision making are considered cost-effective. For the buildings sector, supply curves were developed that reflect implementation of efficiency technologies in a logical order, starting with lowest-cost technological options. Using discounted cash flow1 and accounting for the lifetimes of technologies and infrastructures involved, the reported efficiency investments in buildings generally pay for themselves in 2–3 years. For the industrial and transportation sectors, the AEF Committee relied on results from the report by the America’s Energy Future Panel on Energy Efficiency Technologies (NAS-NAE-NRC, 2009c).2 For industry, the panel reported industry-wide potential for energy savings reflecting improvements that would offer an internal rate-of-return on the efficiency investment of at least 10 percent. For transportation (which addresses fewer technologies and thus includes more in-depth assessments of each), the panel focused on how the performance and costs of vehicle technologies might evolve relative to one another (and the capability of these technologies to reduce fleet fuel consumption).
1
The discounted cash flow approach describes a method of valuing a project, company, or asset such that all future cash flows are estimated and discounted to give their present values.
2
Further details on these estimates can also be found in Chapter 4 in Part 2 of this report.
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The panel examined the available energy efficiency literature and performed additional analyses. For each sector, comparisons were made to a “baseline” or “business as usual” case to estimate the potential for energy savings. These are described in Annex 3.A.
Buildings Sector
About 40 percent of the primary energy used in the United States, and fully 73 percent of the electricity, is used in residential and commercial buildings. Diverse studies for assessing this sector’s energy-savings potential, although they take many different approaches, are remarkably consistent and have been confirmed by the supply curves developed for this report. The consensus is that savings of 25–30 percent relative to current EIA (2008) reference case projections could be achieved over the next 20–25 years. These savings, which would come principally from technologies that are more efficient for space heating and cooling, water heating, and lighting, could hold energy use in buildings about constant even as population and other drivers of energy use grow. Moreover, the savings could be achieved at a cost per energy unit that would be lower than current average retail prices for electricity and gas.3 For the entire buildings sector, the supply curves in Chapter 2 of this report (Figures 2.5 and 2.6) as well as in the panel report (NAS-NAE-NRC, 2009c) show that a cumulative investment of $440 billion4 in existing technology between 2010 and 2030 could produce an annual savings of $170 billion in reduced energy costs.
Advanced technologies just emerging or under development promise even greater gains in energy efficiency. They include solid-state lighting (light-emitting diodes); advanced cooling systems that combine measures to reduce cooling requirements with emerging technologies for low-energy cooling, such as evaporative cooling, solar-thermal cooling, and thermally activated desiccants; control sys-
3
The average residential electricity price in the United States in 2007 was 10.65¢/kWh (in the commercial sector, the average price was 9.65¢/kWh). The average residential price for natural gas in the United States in 2007 was $12.70/million Btu (in the commercial sector, the average price was $11/million Btu).
4
The investments include both the full add-on costs of new equipment and measures (such as attic insulation) and the incremental costs of purchasing an efficient technology (e.g., a high-efficiency boiler) compared with purchasing conventional-counterpart technology (e.g., a standard boiler). These investments would be made instance-by-instance by the individuals and public or private entities involved. The costs of policies and programs that would support, motivate, or require these improvements are not included.
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tems for reducing energy use in home electronics; “superwindows” with very low U-values;5 dynamic window technologies that adjust cooling and electric lighting when daylight is available; and very-low-energy houses and commercial buildings that combine fully integrated design with on-site renewable-energy generation.
Transportation Sector
The transportation sector, which is almost solely dependent on petroleum, produces about one-third of the U.S. greenhouse gas emissions6 arising from energy use. The sector is dominated by use of the nation’s highways, for both freight and passengers.
Current technologies offer many potential improvements in fuel economy, and they become increasingly competitive and attractive as fuel prices rise. Reductions in fleet fuel consumption over the next 10–20 years will likely come primarily from improving today’s spark-ignition (SI), diesel, and hybrid vehicles that are fueled with petroleum, biofuels, and other nonpetroleum hydrocarbon fuels.
Over the subsequent decade, plug-in hybrid vehicles (PHEVs) that use electricity plus any of the fuels just mentioned may be deployed in sufficient volume to have a significant effect on petroleum consumption. Longer term, after 2030, major sales of hydrogen fuel-cell vehicles (HFCVs) and battery-electric vehicles (BEVs) are possible.
Light-duty vehicles. Power-train improvements for LDVs offer the greatest potential for increased energy efficiency over the next two decades. Technologies that improve the efficiency of SI engines could reduce average new-vehicle fuel consumption by 10–15 percent by 2020 and a further 15–20 percent by 2030. Turbocharged diesel engines, which are some 10–15 percent more efficient than equal-performance SI engines, could steadily replace nonturbocharged engines in the SI fleet. Improvements in transmission efficiency and reductions in rolling resistance, aerodynamic drag, and vehicle size, power, and weight can all increase vehicle fuel efficiency.
5
U-values represent how well a material allows heat to pass through it. The lower the U-value, the greater a product’s ability to insulate.
6
In this report, the cited quantities of greenhouse gases emitted are expressed in terms of CO2-equivalent (CO2-eq) emissions.
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Currently, corporate average fuel economy (CAFE) standards for new LDVs are targeted to reach 35 miles per gallon by 2020, which would equate to a 40 percent improvement in average new-vehicle fuel efficiency (and a 30 percent reduction in average fuel consumption).7 Achieving this goal, and further improving fuel efficiency after 2020, will require that the historic emphasis on ever-increasing vehicle power and size be reversed in favor of fuel economy.
Gasoline hybrid-electric vehicles (HEVs) currently offer vehicle fuel-consumption savings of as much as 30 percent over SI engines. Thus it is likely that meeting the new CAFE standards by 2020 will require a large fraction of new vehicles to be HEVs or smaller, less powerful vehicles. PHEVs and BEVs could begin to make a large impact beyond 2020; however, the success of these technologies is crucially dependent on the development of batteries with much higher performance capabilities than today’s batteries, and with lower costs. Research and development on battery technology continues to be a high priority.
If they could be equipped with batteries that powered the vehicle for 40–60 miles, gasoline PHEVs could reduce gasoline/diesel consumption by 75 percent. While HEVs mainly improve performance or fuel economy, PHEVs actually get most of their energy from the electric grid.
Improvements in battery and fuel-cell technologies are expected to pave the way for possible large-scale deployments of BEVs and HFCVs in the 2020–2035 period. Because BEVs and HFCVs could reduce and ultimately eliminate the need for petroleum in transportation, they could also reduce and possibly even eliminate LDV tailpipe greenhouse gas emissions.
Freight transportation. Future technologies for heavy-duty trucks include continuously variable transmissions and hybrid-electric systems to modulate auxiliaries (such as air-conditioning and power steering) and reduce idling. Significant reductions in aerodynamic drag are also possible. Reductions in fuel consumption of 10–20 percent in heavy-and medium-duty vehicles appear feasible over the next decade or so.
7
As noted in Chapters 1 and 2, the Obama administration recently announced new policies that will accelerate the implementation of these fuel economy standards.
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Rail is about 10 times more energy-efficient than trucking, so shifting freight from trucks to rail can offer considerable energy savings.
Air transportation. The latest generation of airliners offers a 15–20 percent improvement in fuel efficiency.8 The newer airplanes, however, are likely to do little more than offset the additional fuel consumption caused by projected growth in air travel over the next several decades.
Long-term system-level improvements. Examples of system-level innovations that could substantially improve efficiency include the utilization of intelligent transportation systems to manage traffic flow; better land-use management; and greater application of information technology in place of commuting and long-distance business travel.
Industrial Sector
Estimates from independent studies using different approaches agree that the potential for cost-effective reduction in energy use by industry range from 14 to 22 percent—about 4.9 to 7.7 quads—by 2020, compared with current EIA reference case projections. Most of the gains will occur in energy-intensive industries, notably chemicals and petroleum, pulp and paper, iron and steel, and cement.9 Growth in the energy-efficient option of combined heat and power production is also likely to be significant. Beyond 2020, new technologies such as novel heat and power sources, new products and processes, and advances in recycling could bring about even greater gains in energy efficiency. Important progress might also come from adapting new technology (such as fuel cells for combined heat and power generation) and adopting alternative methods of operation (e.g., “on-demand” manufacturing).
Chemicals and petroleum. Technologies for improving energy efficiency include high-temperature reactors, corrosion-resistant metal- and ceramic-lined reactors, and sophisticated process controls. Cost-effective improvements in efficiency of 10–20 percent in petroleum refining by 2020 are possible.
8
Increases in passenger airliner efficiency will also benefit air freight transport.
9
Further details on the potential improvements in these industries can be found in Chapter 4 in Part 2 of this report and in the report of the America’s Energy Future Panel on Energy Efficiency Technologies (NAS-NAE-NRC, 2009c).
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Pulp and paper. The industry could use more waste heat for drying, advanced water-removal and filtration technologies, high-efficiency pulping processes, and modernized lime kilns. Estimates of cost-effective gains in energy efficiency by 2020 range from 16 to 26 percent.
Iron and steel. Promising advances in technology that could be available by 2020 involve electric-arc furnace (EAF) melting, blast-furnace slag-heat recovery, integration of refining functions, and heat capture from EAF waste gas. The American Iron and Steel Institute recently announced a goal of using 40 percent less energy for iron and steel production by 2025 compared with 2003.
Cement. Major energy savings would require significant upgrades to an advanced dry-kiln process. Efficiency could also be enhanced with advanced control systems, combustion improvements, indirect firing, and optimization of certain components. A combination of these changes could yield a reduction in energy use of about 10 percent. In addition, changing the chemistry of cement to decrease the need for calcination could result in reduced energy use of another 10–20 percent. Advanced technologies for yielding further improvements are under development. Overall savings of 20 percent are possible by 2020.
A set of crosscutting technologies exists that could improve energy efficiency in a wide range of industrial applications. This includes the expansion of combined heat and power systems; separation processes based on membranes and other porous materials; advanced materials that resist corrosion, degradation, and deformation at high temperatures; controls and automation; steam- and process-heating technologies that improve quality and reduce waste; high-efficiency fabrication processes that improve yields and reduce waste; remanufacturing of products for resale; and sensor systems that reduce waste by improving control.
Barriers to Deployment and Drivers of Efficiency
Numerous barriers impede deployment of energy efficiency technologies in each of the sectors previously discussed. In the buildings sector, regulatory policies do not usually reward utility investments in energy efficiency; building owners in rental markets and builders are not responsible for paying energy costs and thus lack incentives to make investments that reduce energy use; information about
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the energy costs of specific appliances and equipment is often not readily available; and access to capital for such investments is limited. Drivers for greater efficiency—that is, for overcoming these barriers—could include rising energy costs, growing environmental awareness, improved and publicized building codes and appliance efficiency standards, and state and local utility programs.
In the transportation sector, barriers that limit energy efficiency include the lack of clear signals about future oil prices (expectations for future prices strongly affect technology and investment decisions) and the lack of sufficient production capability to manufacture energy-efficient vehicles across vehicle platforms.
The barriers to deployment in the industrial sector include the technical risks of adopting a new industrial technology; high investment costs for industrial energy efficiency improvements; intra-firm competition for capital, which may favor improvements in products and processes over energy efficiency; the lack of specialized knowledge about energy efficiency technologies; and unfavorable provisions of the tax code.
These barriers are formidable, and sustained public and private support will be needed to overcome them. Particular attention must be paid to infrastructure, industrial equipment, and other long-lived assets in order to ensure that energy efficiency technologies and systems are put into place when these assets are constructed or renewed.
Meanwhile, there are several drivers for greater efficiency. They include expected increases in energy prices and concern about availability of fuels and electricity; more stringent air-quality standards, which raise the prices of pollution allowances; demand charges and demand-response incentives; collateral benefits such as higher product quality and productivity; and corporate sustainability initiatives.
In general, substantial energy savings in all sectors will be realized only if efficient technologies and practices achieve wide use. Experience demonstrates that these barriers can be overcome with the aid of well-designed policies. Many policy initiatives have been effective, including efficiency standards (vehicle and appliance) combined with U.S. Department of Energy R&D on efficient equipment; promotion of combined heat and power, largely through the Public Utilities Regulatory and Policy Act of 1978; the ENERGY STAR® product-labeling program; building-energy codes; and utility- and state-sponsored end-use efficiency programs. These initiatives have already resulted in a nearly 13-quad-per-year reduction in primary energy use.
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ALTERNATIVE TRANSPORTATION FUELS
The U.S. transportation sector consumed about 14 million barrels of oil per day in 2007, 9 million of which was used in light-duty vehicles. Total U.S. liquid fuels consumption in 2007 was about 21 million barrels per day, about 12 million of which was imported. The nation could reduce its dependence on imported oil by producing alternative liquid transportation fuels from domestically available resources to replace gasoline and diesel, and thereby increase energy security and reduce greenhouse gas emissions.
Two abundant domestic resources with such potential are biomass and coal. The United States has at least 20 years’ worth of coal reserves in active mines and probably sufficient resources to meet the nation’s needs for well over 100 years at current rates of consumption. Biomass can be produced continuously over the long term if sustainably managed, but the amount that can be produced at any given time is limited by the natural resources required to support biomass production. However, a robust set of conversion technologies needs to be developed or demonstrated and brought to commercial readiness to enable those resources to be converted to suitable liquid transportation fuels.
Biomass Supply
Biomass for fuels must be produced sustainably to avoid excessive burdens on the ecosystems that support its growth. Because corn grain is often used for food, feed, and fiber production, and also because corn grain requires large amounts of fertilizer, the committee considers corn grain ethanol to be a transition fuel to cellulosic biofuels or other biomass-based liquid hydrocarbon fuels (for example, biobutanol and algal biodiesel). About 365 million dry tonnes (400 million dry tons) per year of cellulosic biomass—dedicated energy crops, agricultural and forestry residues, and municipal solid wastes—could potentially be produced on a sustainable basis using today’s technology and agricultural practices, and with minimal impact on U.S. food, feed, and fiber production or the environment. By 2020, that amount could reach 500 million dry tonnes (550 million dry tons) annually. A key assumption behind these estimates is that dedicated fuel crops would be grown on idle agricultural land in the Conservation Reserve Program. The size of the facilities for converting biomass to fuel will likely be limited by the supply of biomass available from the surrounding regions.
Producers will likely need incentives to grow biofeedstocks that not only do not compete with other crop production but also avoid land-use practices
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that cause significant net greenhouse gas emissions. Appropriate incentives can encourage lignocellulosic biomass production in particular. To ensure a sustainable biomass supply overall, a systematic assessment of the resource base—which addresses environmental, public, and private concerns simultaneously—is needed.
Conversion Technologies
Two conversion processes can be used to produce liquid fuels from biomass: biochemical conversion and thermochemical conversion.
Biochemical Conversion
Biochemical conversion of starch from grains to ethanol has already been deployed commercially. Grain-based ethanol was important for stimulating public awareness and initiating the industrial infrastructure, but cellulosic ethanol and other advanced cellulosic biofuels have much greater potential to reduce U.S. oil use and CO2 emissions and have minimal impact on the food supply.
Processes for biochemical conversion of cellulosic biomass into ethanol are in the early stages of commercial development. But over the next decade, improvements in cellulosic ethanol technology are expected to come from evolutionary developments gained from commercial experience and economies of scale. Incremental improvements of biochemical conversion technologies can be expected to reduce nonfeedstock costs by about 25 percent by 2020 and about 40 percent by 2035. In terms of transport and distribution, however, an expanded infrastructure will be required because ethanol cannot be transported in pipelines used for petroleum transport.
Studies have to be conducted to identify the infrastructure that will be needed to accommodate increasing volumes of ethanol and to identify and address the challenges of distributing and integrating these volumes into the fuel system. Also, research on biochemical conversion technologies that convert biomass to fuels more compatible with the current distribution infrastructure could be developed over the next 10–15 years.
If all the necessary conversion and distribution infrastructure were in place, 500 million dry tonnes of biomass could be used to produce up to 30 billion gallons of gasoline-equivalent fuels per year (or 2 million barrels per day [bbl/d]). However, potential fuel supply does not translate to amount of actual supply. When the production of corn grain ethanol was commercialized, U.S. production capacity grew by 25 percent each year over a 6-year period. Assuming that the
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rate of building cellulosic ethanol plants would exceed that of building corn grain ethanol plants by 100 percent, up to 0.5 million bbl/d of gasoline-equivalent cellulosic ethanol (1 barrel of oil produces about 0.85 barrel of gasoline equivalent) could be added to the fuels portfolio by 2020. By 2035, up to 1.7 million bbl/d of gasoline equivalent could be produced in this manner, resulting in about a 20 percent reduction in oil used for LDVs at current consumption levels.
Thermochemical Conversion
Without geologic CO2 storage, technologies for the indirect liquefaction of coal to transportation fuels could be commercially deployable today, but life-cycle greenhouse gas emissions would be more than twice the CO2 emissions of petroleum-based fuels. Requiring geologic CO2 storage with these processes would have a relatively small impact on engineering costs and efficiency. However, the viability of geologic CO2 storage has yet to be adequately demonstrated on a large scale in the United States, and unanticipated costs could occur. Although enhanced oil recovery could present an opportunity for early demonstrations of carbon capture and storage (CCS), that storage would be small compared with the large amounts of CO2 that would be captured if coal-to-liquid fuels production became widely deployed, potentially in the gigatonne-per-year range.
Liquid fuels produced from thermochemical plants that use only biomass feedstock are more costly than fuels produced from coal, but biomass-derived fuels can have life-cycle CO2 emissions that are near zero without geologic CO2 storage or highly negative emissions with geologic CO2 storage. To make such fuels competitive, the economic incentive for reducing CO2 emissions has to be sufficiently high.
When biomass and coal are co-fed in thermochemical conversion to produce liquid fuels, the process allows a larger scale of operation and lower capital costs per unit of capacity than would be possible with biomass alone. If 500 million dry tonnes of biomass were combined with coal (60 percent coal and 40 percent biomass on an energy basis), production of 60 billion gallons of gasoline-equivalent fuels per year (4 million bbl/d) would be technically feasible. That amount of fuel represents about 45 percent of the current volume (140 billion gal/yr or 9 million bbl/d) of liquid fuel used annually in the United States for LDVs. Moreover, when biomass and coal are co-fed, the overall life-cycle CO2 emissions are reduced because the CO2 emissions from coal are countered by the CO2 uptake by biomass during its growth. Combined coal-and-biomass-to-liquid fuels without geologic
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CO2 prices represent potential future costs to operators for emitting CO2 to the atmosphere from energy production. A base-case CO2 price of $0 per tonne was assumed for all of the energy supply cost estimates presented in this report; prices of $50 and $100 per tonne were also considered in the fossil energy and alternative liquid fuels estimates in order to assess the sensitivity of energy supply costs to CO2 prices for a future in which climate change is taken seriously.
Financing period is the length of time that capital borrowed for constructing the energy supply plant would be financed. The financing periods used in this report reflect current industry practices, which vary across technology classes.
Debt/equity indicates the ratio of borrowed capital to equity capital in financing the construction of the energy supply plant. The ratios used in this report reflect current industry practices, which vary across technology classes. In some cases ranges were used.
Before-tax discount rate was used to convert future energy supply costs into present values. The ratios used in this report reflect standard industry practice.
Overnight costs represent the present-value costs, paid as a lump sum, for building an energy supply plant. The overnight costs do not include any costs associated with the acquisition of capital, the acquisition of land on which the plant would be built, or site improvements such as new or upgraded transmission equipment. In some cases, overnight costs are given as ranges. For the fossil-fuel estimates, however, 10 percent of the capital costs were added to account for owners’ costs.
Source of supply estimates describe the methodologies that were used by the AEF Committee to estimate the supply of electricity and liquid fuels. Many factors can affect deployment rates of a technology beyond its readiness for deployment. Consequently, it was not possible to develop a single methodology for estimating deployment rates for all of the energy supply technologies considered in this report. The committee’s estimates of deployment rates were instead based on expert judgment informed by historical rates of technology deployments or by current deployment trends. The supply estimates represent new electricity or liquid fuel supplies and do not account for possible future supply reductions arising from retirements of existing assets.
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Build time is the estimated time required to construct a new energy supply plant. This estimate represents actual construction time; it does not include the time required to acquire a site, to design the plant, and to obtain any needed licenses, permits, or other approvals. The build times used in this report reflect current industry practices, which vary across technology classes.
Capacity factor is the ratio (expressed as a percent) of the energy output of a plant over its lifetime to the energy that could be produced by that plant if it was operated at its nameplate capacity. Some capacity factors are expressed as ranges. The capacity factors used in this report reflect current experience and projected future improvements, both of which vary across technology classes.
Near-term build-rate limitations identifies important factors that could limit the rates of plant deployments between 2009 and 2020. These limitations arise from a lack of experience in deploying new technologies (e.g., CCS), bottlenecks in obtaining critical plant components (e.g., large forgings for nuclear plants), and reduced availabilities of other materials and personnel. Most of these bottlenecks are expected to be temporary and should not present major impediments to deployment after 2020.
Resource limitations are factors that could restrict the supply of energy obtained from the deployment of existing and new technologies. These limitations relate mainly to the availability of feedstocks and fuels that are needed to operate the energy supply plants.
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TABLE 3.A.1 Sources and Key Assumptions Used to Develop Cost and Energy Supply Estimates in This Report
Fossil-Fuel Energy (Chapter 7)
Nuclear Energy (Chapter 8)
Renewable Energy (Chapter 6)
Reference scenario
EIA (2008)
EIA (2008)
EIA (2009)
COST ESTIMATES: SOURCES AND KEY ASSUMPTIONS
Source of cost estimates
Committee-derived model estimates
Committee-derived model estimates
Critical assessment of the literaturea
Models used to obtain estimates
NETL (2007) and Princeton Environmental Instituteb
Keystone (2007) model for LCOEc
Monte Carlo for sensitivity analysis
NEMS model for EIA (2009) cost estimates
MERGE model for EPRI (2007) cost estimates
Other literature estimates are not model based
Cost estimate limitations
IGCC, USPC, and CCS technologies are not yet mature and have not been deployed
Geologic storage of CO2 has not been demonstrated on a commercial scale
Evolutionary nuclear technologies are mature but plants have not yet been deployed in the United States.
Solar technologies are undergoing rapid technological improvements that could bring down future costs.
Plant maturity
Nth plant for pulverized coal
3 percent premium on capital costs added for IGCC, PC-CCS, and IGCC-CCS to account for immaturity of technologies
20 percent premium on CCS capital costs added for CCS 2020 estimates to account for immaturity of technologies
Nth plant
Nth plant
Plant size
500 MW (coal and gas)
1.35 GW, based on weighted average of current plant license applications
Variable
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Alternative Transportation Fuels (Chapter 5)
Cellulosic Ethanol
Coal to Liquid
Coal + Biomass to Liquid
EIA (2008)
EIA (2008)
EIA (2008)
Committee-derived model estimates
Committee-derived model estimates
Committee-derived model estimates
See NAS-NAE-NRC (2009), Appendix I
Princeton Environmental Instituteb
Princeton Environmental Instituteb
Cellulosic technologies are not yet mature and have not been deployed
Geologic storage of CO2 has not been demonstrated on a commercial scale
Geologic storage of CO2 has not been demonstrated on a commercial scale
Intermediate plant
No capital cost contingency included in estimate for CCS
Intermediate plant
No capital cost contingency included in estimate for CCS
Intermediate plant
No capital cost contingency included in estimate for CCS
4,000 bbl/d
50,000 bbl/d
10,000 bbl/d
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Fossil-Fuel Energy (Chapter 7)
Nuclear Energy (Chapter 8)
Renewable Energy (Chapter 6)
Reference scenario
EIA (2008)
EIA (2008)
EIA (2009)
COST ESTIMATES: SOURCES AND KEY ASSUMPTIONS
Plant life (yr)
20
40
Variable
Feedstock and fuel costs
Coal: $1.71/GJ ($46/tonne)
Gas: $6/GJ, $16/GJ
Average: 1.25¢/kWh
Range: 0.8–1.7¢/kWh
Biomass: $15–35/MWh
Others: $0
CO2 prices ($/tonne)
0, 50,100
0
0
Financing period (yr)
20
Average: 40
Range: 30–50
Variable
Debt/equity
55/45
IPP: Average 60/40 Range: 50/50 to 70/30
IOU: Average 50/50 Range: 45/55 to 55/45
Also considered: 80/20 for IPP and IOU with federal loan guarantees
Variable
Before-tax discount rate (percent/yr)
7
IOU: 6.9
IPP: 7.7
Variable
Overnight costs (Millions of 2007$/kW) (Millions of 2007$/bbl)
PC: 1625
PC+CCS: 2961
IGCC: 1865
IGCC+CCS: 2466
NGCC: 572
NGCC+CCS: 1209
–20%/+30% uncertainty
Average: 4500
Range: 3000–6000
Biopower: 3390
Traditional geothermal: 1585
CSP: 2860–4130
PV: 2547–5185
Onshore wind: 916–1896
Offshore wind: 2232–3552
ELECTRICITY OR LIQUID FUELS SUPPLY ESTIMATES: SOURCES AND KEY ASSUMPTIONS
Source of supply estimates
Committee-generated, based on historical build rates of plants in the United States
Committee-generated, based on historical build rates of plants in the United States
Committee-generated, based on an examination of natural resource base and other factorsd
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Alternative Transportation Fuels (Chapter 5)
Cellulosic Ethanol
Coal to Liquid
Coal + Biomass to Liquid
EIA (2008)
EIA (2008)
EIA (2008)
20
20
20
$111/tonne dry biomass
$46/tonne coal
$46/tonne coal
$111/tonne dry biomass
0, 50
0, 50
0, 50
20
20
20
70/30
55/45
55/45
7
7
7
349
4000–5000 (with CCS) (0.08–0.09/bbl per day)
1340 (with CCS) (0.134/bbl per day)
Committee-generated, based partly on corn-ethanol plant build rates in the United Statese
Committee-generated, based on historical build rates of plants in the United States
Committee-generated, based partly on corn-ethanol plant build rates in the United Statesf
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Fossil-Fuel Energy (Chapter 7)
Nuclear Energy (Chapter 8)
Renewable Energy (Chapter 6)
Reference scenario
EIA (2008)
EIA (2008)
EIA (2009)
ELECTRICITY OR LIQUID FUELS SUPPLY ESTIMATES: SOURCES AND KEY ASSUMPTIONS
Build time (yr)g
3h
Average: 5.5
Range: 4–7
1–2 for solar and wind
Longer for biopower and hydrothermal
Capacity factor (percent)
85
Average: 90
Range: 75–95
Biopower: 83–85
Traditional geothermal: 90
CSP: 31–65
PV: 21–32
Wind: 32.5–52
Near-term build-rate limitations
Learning curve for CCS slows build rate before 2025
Build rates slowed before 2020 by:
Time to acquire license and construct plants
Lack of domestic experience
Potential bottlenecks in obtaining plant components
Barriers to reach 20 percent renewables generation:
Availability of raw materials
Manufacturing capacity
Availability of personnel
Resource limitations
Historical resources limits considered
None
None for wind and solar; limited resource bases forbiomass, traditional hydropower, hydrokinetic, and traditional geothermal
Note: CCS = carbon capture and storage; CSP = concentrating solar power (i.e., solar thermal); IGCC = integrated gasification combined cycle; IOU = investor-owned utility; IPP = independent power producer; MERGE = Model for Evaluating Regional and Global Effects [of greenhouse gases]; NEMS = National Energy Modeling System; NGCC = natural gas combined cycle; PC = pulverized coal; PV = photovoltaics; USPC = ultrasupercritical pulverized coal.
aThe following studies were used to “bookend” the renewable energy cost estimates: ASES (2007), EIA (2008, 2009), EPRI (2007), and NREL (2007).
bSee Kreutz et al. (2008) and Larson et al. (2008).
cThis model was run using committee-developed assumptions as described in Chapter 8 in Part 2 of this report.
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Alternative Transportation Fuels (Chapter 5)
Cellulosic Ethanol
Coal to Liquid
Coal + Biomass to Liquid
EIA (2008)
EIA (2008)
EIA (2008)
1
3
3
90
90
90
None
None
None
Biomass availability
Coal extraction rates
Biomass availability
dThese additional factors included manufacturing and materials constraints, employment and capital requirements, and necessary deployment rates. The committee also considered current growth rates of renewables technologies and historical build rates of other types of plants.
eThe committee assumed twice the capacity achieved for corn grain ethanol.
fThe committee assumed a build-out rate slightly slower than that for corn grain ethanol because of issues involving accessing sites with about 1.0 million tonnes of biomass per year and a similar availability of coal.
gEstimates do not include the time required for permitting and other approvals.
hThis estimate does not account for differences in complexity of different types of coal and natural gas plants.
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Energy Savings and Cost Estimates
The methodologies and assumptions used to develop the energy savings and cost estimates are provided in Table 3.A.2. Each row in the table is described in the following bulleted list:
Reference scenarios. The reference case for 2006 (EIA 2007) was used for the buildings and industrial sector estimates, but these were adjusted in some cases to reflect the 2007 reference case provided in EIA (2008). The transportation estimates were based on a committee-derived, no-change baseline.
Source of cost estimates describes the methodologies that were used to estimate energy savings costs. As shown in the table, these estimates were derived from critical assessments of the literature.
Source of savings estimates describes the methodologies that were used to estimate energy savings. As shown in the table, these estimates were derived from critical assessments of the literature and, for buildings and transportation, committee-derived analyses.
Key cost-effectiveness criteria describes the criteria that were used to determine which energy savings were cost-effective. Different criteria were used in the buildings, transportation, and industrial sectors, as described in the table.
Technology lifetimes are average useful lifetimes of the technologies used to obtain energy savings. These estimates are highly technology specific.
Before-tax discount rate was used to convert future energy supply costs into present values. The ratios used in this report reflect standard industry practice.
Other considerations describe other factors that were considered in developing the energy-savings cost and supply estimates.
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TABLE 3.A.2 Sources and Key Assumptions Used to Develop Energy Savings and Cost Estimates
Buildings Sector
Transportation Sector
Industry Sectora
Reference scenario
EIA (2007, 2008)
Developed by committeeb
EIA (2007, 2008)
Source of cost estimates
Critical assessment of the literature
Critical assessment of the literature
Critical assessment of the literature
Source of savings estimates
Critical assessment of the literature on individual technologies and committee-derived conservation supply-curve analysis
Critical assessment of the literature on specific technologies
For light-duty vehicles (LDVs), committee-derived illustrative scenario analysis of overall savings in fuel consumption
Critical assessment of the literature on industry-wide savings, industry-specific savings, and savings from specific crosscutting technologies
Key cost-effectiveness criteria
Levelized cost of energy savings is less than the average national electricity and natural gas prices
Recovery of discounted costs of energy savings over the life of the vehicle
Energy savings provide an internal rate of return on investment of at least 10 percent or exceed the company’s cost of capital by a risk premium
Technology lifetimes
Technology specific
Average vehicle lifetime
Technology specific
Before-tax discount rate (percent/yr)
7
7
15
Other considerations
Assessment accounts for stock turnover in buildings and equipment
For LDVs, assessment considers how the distribution of specific vehicle types in the new-vehicle fleet affects the on-the-road fleet
Assessment of savings in specific industries used to confirm industry-wide estimates
aManufacturing only.
bThis is a “no-change” baseline in which, beyond 2020 (when Energy Independence and Security Act targets are met), any efficiency improvements are fully offset by increases in vehicle performance, size, and weight.
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References for Annex 3.A
ASES (American Solar Energy Society). 2007. Tracking Climate Change in the U.S.: Potential Carbon Emissions Reductions from Energy Efficiency and Renewable Energy by 2030. Washington, D.C.
EIA (Energy Information Administration). 2007. Annual Energy Outlook 2007. DOE/EIA-0383(2007). Washington, D.C.: U.S. Department of Energy, Energy Information Administration.
EIA. 2008. Annual Energy Outlook 2008. DOE/EIA-0383(2008). Washington, D.C.: U.S. Department of Energy, Energy Information Administration.
EIA. 2009. Annual Energy Outlook 2009. DOE/EIA-0383(2009). Washington, D.C.: U.S. Department of Energy, Energy Information Administration.
EPRI (Electric Power Research Institute). 2007. The Power to Reduce CO2 Emissions: The Full Portfolio. Palo Alto, Calif.
Keystone Center. 2007. Nuclear Power Joint Fact-Finding. Keystone, Colo.
Kreutz, T.G., E.D. Larson, G. Liu, and R.H. Williams. 2008. Fischer-Tropsch fuels from coal and biomass. In 25th Annual International Pittsburgh Coal Conference. Pittsburgh, Pa.
Larson, E.D., G. Fiorese, G. Liu, R.H. Williams, T.G. Kreutz, and S. Consonni. 2008. Coproduction of synthetic fuels and electricity from coal + biomass with zero carbon emissions: An Illinois case study. In 9th International Conference on Greenhouse Gas Control Technologies. Washington, D.C.
NAS-NAE-NRC (National Academy of Sciences-National Academy of Engineering-National Research Council). 2009. Liquid Transportation Fuels from Coal and Biomass: Technological Status, Costs, and Environmental Impacts. Washington, D.C.: The National Academies Press.
NETL (National Energy Technology Laboratory). 2007. Cost and Performance Baseline for Fossil Energy Plants. DOE/NETL-2007/1281, Revision 1, August. U.S. Department of Energy, National Energy Technology Laboratory.
NREL (National Renewable Energy Laboratory). 2007. Projected Benefits of Federal Energy Efficiency and Renewable Energy Programs. NREL/TP-640-4137. Golden, Colo. March.