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Annual Technology Baseline 2018

National Renewable Energy Laboratory


Recommended Citation:
NREL (National Renewable Energy Laboratory). 2018. 2018 Annual Technology Baseline. Golden, CO: National Renewable Energy Laboratory. http://atb.nrel.gov/.


Please consult Guidelines for Using ATB Data:
https://atb.nrel.gov/electricity/user-guidance.html

2018 ATB

For each electricity generation technology in the ATB, this website provides:

  • Capital expenditures (CAPEX): the definition of CAPEX used in the ATB and the historical trends, current estimates, and future projections of CAPEX used in the ATB
  • Operations and maintenance (O&M) costs: the definition of O&M and the current estimates and future projections of O&M used in the ATB
  • Capacity factor (CF): the definition of CF and the historical trends, current estimates, and future projections of CF used in the ATB
  • Future cost and performance methods: an outline of the methodology used to make the projections of future cost and performance in the ATB for Constant, Mid, and Low technology cost cases
  • Levelized cost of energy (LCOE): metric that combines CAPEX, O&M, CF, and projections for Constant, Mid, and Low technology cost cases for illustration of the combined effect of the primary cost and performance components and discussion of technology advances that yield future projections
  • Financing Assumptions: Where applicable, development of technology-specific interest rate on debt, return on equity, and debt-to-equity ratios, and their impact on LCOE are documented in each technology section, and summarized here.

Electricity generation technologies are selected on the left side of the screen, and the topics highlighted above can be selected using the drop-down menu at the top-right of the screen.

Guidelines for using and interpreting ATB content and comparisons to other literature are provided. LCOE accounts for many variables important to determining the competitiveness of a building and operating a specific technology (e.g., upfront capital costs, capacity factor, and cost of financing); however, it does not necessarily demonstrate which technology in a given place and time would provide the lowest cost option for the electricity grid. This analysis is performed using electric sector models such as the Regional Energy Deployment Systems (ReEDS) model and corresponding analysis results such as the NREL Standard Scenarios.

The NREL Standard Scenarios, a companion product to the ATB, provides a suite of electric sector scenarios and associated assumptions-including technology cost and performance assumptions from the ATB.

ATB data sources and references are also provided for each technology. All dollar values are presented in 2016 U.S. dollars, unless noted otherwise.

Additional information about the 2018 ATB - available via links in the ATB website footer below - includes:

Land-Based Wind

Representative Technology

Most land-based wind plants in the United States range in capacity from 50 MW to 100 MW (Wiser and Bolinger (2017)). Wind turbines installed in the United States in 2016 were, on average, 2.2-MW turbines with rotor diameters of 108 m and hub heights of 84 m (Wiser and Bolinger (2017)).

Resource Potential

Wind resource is prevalent throughout the United States but is concentrated in the central states. Total land-based wind technical potential exceeds 10,000 GW (almost tenfold current total U.S. electricity generation capacity), which would use the wind resource on 3.5 million km2 of land area but would disrupt or exclude other uses from a fraction of that area. This technical potential does not include standard exclusions-lands such as federally protected areas, urban areas, and water. Resource potential has been expanded from approximately 6,000 GW (DOE (2015)) by including locations with lower wind speeds to provide more comprehensive coverage of U.S. land areas where future technology may improve economic potential).

Renewable energy technical potential, as defined by Lopez et al. 2012, represents the achievable energy generation of a particular technology given system performance, topographic limitations and environmental and land-use constraints. The primary benefit of assessing technical potential is that it establishes an upper-boundary estimate of development potential. It is important to understand that there are multiple types of potential-resource, technical, economic, and market (Lopez et al. 2012; NREL, "Renewable Energy Technical Potential ").

The resource potential is calculated by using over 130,000 distinct areas for wind plant deployment that cover over 3.5 million km2. The potential capacity is estimated to total over 10,000 GW if a power density of 3 MW/km2 is assumed.

map of land-based wind resource in the contiguous United States
Map of the land-based wind resource in the contiguous United States
Source: NREL (2012)

Base Year and Future Year Projections Overview

For each of the 130,000 distinct areas, an LCOE is estimated taking into consideration site-specific hourly wind profiles. Representative wind turbines derived from annual installation statistics are associated with a range of average annual wind speed based on actual historical wind plant installations This method is described in Moné et al. (2017) and summarized below.

  • Capital expenditures (CAPEX) associated with wind plants installed in the interior of the country are used to characterize CAPEX for hypothetical wind plants with average annual wind speeds that correspond with the median conditions for recently installed wind facilities. A range of CAPEX across the full range of observed wind speeds at each site-specific location is developed using engineering models and assumed differences in rotor diameter. Wind turbines at lower wind speed sites have larger rotors and, therefore, higher CAPEX.
  • Capacity factor is determined for each unique location using the site-specific hourly wind profile and a power curve that corresponds with the representative wind turbine defined to represent the annual average wind speed for each site.
  • Average annual operations and maintenance (O&M) costs are assumed to be equivalent at all geographic locations.
  • LCOE is calculated for each area based on the CAPEX and capacity factor estimated for each area.

For representation in the ATB, the full resource potential, reflecting the 130,000 individual areas, was divided into 10 techno-resource groups (TRGs). The capacity-weighted average CAPEX, O&M, and capacity factor for each group is presented in the ATB.

Three different projections were developed for scenario modeling as bounding levels:

  • Constant Technology Cost Scenario: no change in CAPEX, O&M, or capacity factor from 2016 to 2050; consistent across all renewable energy technologies in the ATB
  • Mid Technology Cost Scenario: LCOE percentage reduction from the Base Year equivalent to that corresponding to the Median Scenario (50% probability) from Wiser et al. (2016), an international expert elicitation study
  • Low Technology Cost Scenario: LCOE percentage reduction from the Base Year is derived from a bottom-up analysis of specific wind advancements enabled by additional R&D activities (Dykes et al. (2017)).

More specifically, future year projections for the Mid cost scenario are derived from the estimated cost reduction potential for land-based wind technologies as calculated from an elicitation of over 160 wind industry experts (Wiser et al. (2016)). Their study produced three different cost reduction pathways, and the median estimates for LCOE reduction are used for ATB Mid cost scenario. Future year projections for the Low cost scenario are derived from the estimated cost reduction potential considering a collection of intelligent and novel technologies that comprise next-generation wind turbine and plant technology and characterized as System Management of Atmospheric Resource through Technology, or SMART strategies (Dykes et al. (2017)). In both scenarios, the overall LCOE reductions resulting from these analyses were used as the basis for the ATB projections. Accordingly, all three cost elements - CAPEX, O&M, and capacity factor-should be considered together; individual cost element projections are derived.

CAPital EXpenditures (CAPEX): Historical Trends, Current Estimates, and Future Projections

Capital expenditures (CAPEX) are expenditures required to achieve commercial operation in a given year. These expenditures include the wind turbine, the balance of system (e.g., site preparation, installation, and electrical infrastructure), and financial costs (e.g., development costs, onsite electrical equipment, and interest during construction) and are detailed in CAPEX Definition. In the ATB, CAPEX reflects typical plants and does not include differences in regional costs associated with labor, materials, taxes, or system requirements. The related Standard Scenarios product uses regional CAPEX adjustments. The range of CAPEX demonstrates variation with wind resource in the contiguous United States.

CAPEX Definition

Capital expenditures (CAPEX) are expenditures required to achieve commercial operation in a given year.

For the ATB-and based on EIA (2016a) and the System Cost Breakdown Structure defined by Moné et al. 2015 - the wind plant envelope is defined to include:

  • Wind turbine supply
  • Balance of system (BOS)
  • Turbine installation, substructure supply, and installation
  • Site preparation, installation of underground utilities, access roads, and buildings for operations and maintenance
  • Electrical infrastructure, such as transformers, switchgear, and electrical system connecting turbines to each other and to the control center
  • Project-related indirect costs, including engineering, distributable labor and materials, construction management start up and commissioning, and contractor overhead costs, fees, and profit.
  • Financial costs
  • Owners' costs, such as development costs, preliminary feasibility and engineering studies, environmental studies and permitting, legal fees, insurance costs, and property taxes during construction
  • Onsite electrical equipment (e.g., switchyard), a nominal-distance spur line (< 1 mile), and necessary upgrades at a transmission substation; distance-based spur line cost (GCC) not included in the ATB
  • Interest during construction estimated based on three-year duration accumulated 10%/10%/80% at half-year intervals and an 8% interest rate (ConFinFactor).

CAPEX can be determined for a plant in a specific geographic location as follows:

CAPEX = ConFinFactor × (OCC × CapRegMult + GCC)
(See the Financial Definitions tab in the ATB data spreadsheet.)

Regional cost variations and geographically specific grid connection costs are not included in the ATB (CapRegMult = 1; GCC = 0). In the ATB, the input value is overnight capital cost (OCC) and details to calculate interest during construction (ConFinFactor).

In the ATB, CAPEX represents a typical land-based wind plant and varies with annual average wind speed. Regional cost effects associated with labor rates, material costs, and other regional effects as defined by IEA 2016a, DOE 2015 expand the range of CAPEX. Unique land-based spur line costs for each of the 130,000 areas based on distance and transmission line costs expand the range of CAPEX even further. The figure below illustrates the ATB representative plants relative to the range of CAPEX including regional costs across the contiguous United States. Note that the ATB Base Year estimate for TRG 4 is equivalent to the market data observed capacity-weighted average wind plant CAPEX in the same year. The ATB representative plants are associated with a regional multiplier of 1.0.

R&D Only Financial Assumptions (constant background rates, no tax or tariff changes)

Standard Scenarios Model Results

ATB CAPEX, O&M, and capacity factor assumptions for the Base Year and future projections through 2050 for Constant, Mid, and Low technology cost scenarios are used to develop the NREL Standard Scenarios using the ReEDS model. See ATB and Standard Scenarios.

CAPEX in the ATB does not represent regional variants (CapRegMult) associated with labor rates, material costs, etc., but the ReEDS model does include 134 regional multipliers (EIA 2016a).

The ReEDS model determines the land-based spur line (GCC) uniquely for each of the 130,000 areas based on distance and transmission line cost.

Natural Gas Internal Combustion Engine Vehicle

Operations and maintenance (O&M) costs depend on capacity and represent the annual fixed expenditures required to operate and maintain a wind plant, including:

  • Insurance, taxes, land lease payments, and other fixed costs
  • Present value and annualized large component replacement costs over technical life (e.g., blades, gearboxes, and generators)
  • Scheduled and unscheduled maintenance of wind plant components, including turbines and transformers, over the technical lifetime of the plant.

The following figure shows the Base Year estimate and future year projections for fixed O&M (FOM) costs. Three cost scenarios are represented. The estimate for a given year represents annual average FOM costs expected over the technical lifetime of a new plant that reaches commercial operation in that year.

Base Year Estimates

Due to limited available robust market data, an assumption of FOM of $51/kW-yr was determined to be representative of the range of available data; no variation of FOM with TRG (or wind speed) was assumed (DOE (2015)). The following chart shows sample historical data for reference.

Source: Wiser and Bolinger (2017)

Future Year Projections

Future FOM is assumed to decline by approximately 25% by 2050 in Mid cost case and 35% in Low cost windcases. These values are the result of linear curves fit to the results of the expert survey documented in Wiser et al. (2016).

A detailed description of the methodology for developing future year projections is found in Projections Methodology.

Technology innovations that could impact future O&M costs are summarized in LCOE Projections.

Capacity Factor: Expected Annual Average Energy Production Over Lifetime

The capacity factor represents the expected annual average energy production divided by the annual energy production, assuming the plant operates at rated capacity for every hour of the year. It is intended to represent a long-term average over the lifetime of the plant. It does not represent interannual variation in energy production. Future year estimates represent the estimated annual average capacity factor over the technical lifetime of a new plant installed in a given year.

The capacity factor is influenced by hourly windprofile, expected downtime, and energy losses within the wind plant. The specific power (ratio of machine rating to rotor swept area) and hub height are design choices that influence the capacity factor.

The following figure shows a range of capacity factors based on variation in the resource for wind plants in the contiguous United States. Historical data from wind plants operating in the United States in 2015, according to the year in which plants were installed, is shown for comparison to the ATB Base Year estimates. The range of Base Year estimates illustrate the effect of locating a wind plant in sites with high wind speeds (TRG 1) or low wind speeds (TRG 10). Future projections are shown for Constant, Mid, and Low technology cost scenarios.

Historical data shown in box-and-whiskers format where a bar represents the median, a box represents the 20th and 80th percentiles, and whiskers represent the minimum and maximum.
Historical data represent capacity factor for plants operating in 2015 with Commercial Online Date specifiedby year. Projection data represent expected annual average capacity factor for plants with Commercial Online Date specified by year.

Recent Trends

Actual energy production from about 90% of wind plants operating in the United States since 2007 () is shown in box-and-whiskers format for comparison with the ATB current estimates and future projections. The historical data illustrate capacity factor for projects operating in 2016, shown by year of commercial online date. As reported in the 2016 DOE Wind Technologies Market Report (Wiser and Bolinger (2017)), NextEra Energy Resources, in their quarterly earnings reports, estimates that the "wind resource index" for the United States as a whole was 99% in 2016. The generation-weighted average 2016 capacity factors are also shown adjusted upward for a typical wind resource year by 1/0.99.

Base Year Estimates

For illustration in the ATB, all potential land-based wind plant areas were represented in 10 TRGs. The capacity-weighted average CAPEX, capacity factor, and resource potential are shown in the table below.

The majority of installed U.S. wind plants generally align with ATB estimates for performance in TRGs 5-7. High wind resource sites associated with TRGs 1 and 2 as wellas very low wind resource sites associated with TRGs 8-10 are not as common in thehistorical data, but the range of observed data encompasses ATB estimates.

The capacity factor is referenced to an 80-m, above-ground-level, long-term average hourly wind resource data fromAWS Truepower (2012).

Future Year Projections

Projections for capacity factors implicitly reflect technology innovations such as larger rotors and taller towers that will increase energy capture at the same location without specifying precise tower height or rotor diameter changes. Improvements in plant performance through lower losses and increased availability are also included implicitly.

  • Mid: Projections of capacity factor for plants installed in future years were determined based on adjustments to CAPEX, FOM, and capacity factor in each year to result in a predetermined LCOEvalue.
  • Low: Projections of capacity factor for plants installed in future years were determined based on the work conducted in the SMART wind power plant (Dykes et al. (2017)). The two primary factors influencing wind plant capacity factor are increased energy capture through turbine scaling and wind plant optimization. The introduction of novel control mechanisms will continue to increase energy capture with more precise control of the flow through the entire wind plant. These technology advancements are expected to increase capacity factor for all TRGs with the more aggressive increases in capacity factor happening through 2030 and then gradually becoming less aggressive through 2050.

A detailed description of the methodology for developing future year projections is found in Projections Methodology.

Technology innovations that could impact future O&M costs are summarized in LCOE Projections.

Standard Scenarios Model Results

ATB CAPEX, O&M, and capacity factor assumptions for the Base Year and future projections through 2050 for Constant, Mid, and Low technology cost scenarios are used to develop the NREL Standard Scenarios using the ReEDS model. See ATB and Standard Scenarios.

The ReEDS model output capacity factors for wind and solar PV can be lower than input capacity factors due to endogenously estimated curtailments determined by scenario constraints.

Plant Cost and Performance Projections Methodology

ATB projections were derived from two different sources for the Mid and Low cases.

  • Mid: A survey of 163 of the world's wind energy experts was conducted to gain insight into possible future cost reductions, the source of those reductions, and the conditions needed to enable continued innovation and lower costs (Wiser et al. (2016)). This expert survey produced three cost reduction scenarios associated with probability levels of 10%, 50%, and 90% of achieving LCOE reductions by 2030 and 2050. In addition, the scenario results include estimated changes to CAPEX, O&M, capacity factor, project life, and weighted average cost of capital (WACC) by 2030.
  • For the Mid case, the LCOE percentage reduction from the Base Year was equivalent to that corresponding to the Median Scenario (50% probability) in the expert survey (Wiser et al. (2016)).
  • Expert survey estimates were normalized to the ATB Base Year starting point in order to focus on projected cost reduction instead of absolute reported costs. The percentage reductions in LCOE by 2020, 2030, and 2050 from the expert survey's Median scenario were implemented as the ATB Mid case. This is accomplished by using survey estimates for changes to capacity factor and O&M costs by 2030 and 2050. The corresponding CAPEX value to achieve the overall LCOE reduction is computed. The percentage reduction in LCOE by 2030 and by 2050 was applied equally across all TRGs. The overall reduction in LCOE by 2050 for the Mid cost scenario is approximately 31%.
  • Low Technology Cost Scenario: A study conducted by NREL (Dykes et al. (2017)) assessed a variety of intelligent and novel technologies that comprise of next-generation wind plant technologies in order to estimate the LCOE of a SMART wind plant in 2030. The study used a bottom-up approach informed by research programs such as the DOE's Atmosphere to Electrons (A2e) program and input from wind energy experts to determine a future wind plant's potential LCOE impacts from enhanced power production, more efficient materials and manufacturing capabilities, lower O&M and servicing costs, lower project risks for investors, increased wind plant life, and an array of grid control and reliability features. Considering the technology advantages of the SMART wind plant, the potential for LCOE reduction is nearly doubled by 2030 compared to the Mid cost scenario derived from the expert survey, and it results in just over a 60% reduction in LCOE by 2050.

A broad sample of cost of wind energy projections is shown to provide context for the ATB Constant, Mid, and Low technology cost projections. The ATB Mid cost projection, which corresponds to the Median scenario from the expert survey, results in LCOE reductions that are slightly lower than other median scenarios in the literature (ARUP (2011); BNEF (2015); E3 (2014); EIA (2014); EPA (2015); GWEC (2014); IEA (2015c); IRENA (2016a); Teske et al. (2015)). The ATB Low cost projection, which corresponds to the NREL bottom-up cost analysis, is similar to the lower bound of the sample of literature projections (BNEF (2016); IEA (2015c); MAKE (2015)).

  • Mid case projection institutions: Ove Arup & Partners Ltd., Bloomberg New Energy Finance, Energy and Environmental Economics, U.S. Energy Information Administration, United States Environmental Protection Agency, Global Wind Energy Council, International Energy Agency, International Renewable Energy Agency, and Greenpeace.
  • Low case projection institutions: Bloomberg New Energy Finance, International Energy Agency, and MAKE Consulting.

Levelized Cost of Energy (LCOE) Projections

Levelized cost of energy (LCOE) is a simple metric that combines the primary technology cost and performance parameters: CAPEX, O&M, and capacity factor. It is included in the ATB for illustrative purposes. The ATB focuses on defining the primary cost and performance parameters for use in electric sector modeling or other analysis where more sophisticated comparisons among technologies are made. The LCOE accounts for the energy component of electric system planning and operation. The LCOE uses an annual average capacity factor when spreading costs over the anticipated energy generation. This annual capacity factor ignores specific operating behavior such as ramping, start-up, and shutdown that could be relevant for more detailed evaluations of generator cost and value. Electricity generation technologies have different capabilities to provide such services. For example, wind and PV are primarily energy service providers, while the other electricity generation technologies provide capacity and flexibility services in addition to energy. These capacity and flexibility services are difficult to value and depend strongly on the system in which a new generation plant is introduced. These services are represented in electric sector models such as the ReEDS model and corresponding analysis results such as the Standard Scenarios.

The following three figures illustrate LCOE, which includes the combined impact of CAPEX, O&M, and capacity factor projections for land-based wind across the range of resources present in the contiguous United States. For the purposes of the ATB, the costs associated with technology and project risk in the U.S. market are represented in the financing costs, not in the upfront capital costs (e.g. developer fees, contingencies). An individual technology may receive more favorable financing terms outside of the U.S., due to less technology and project risk, caused by more project development experience (e.g. offshore wind in Europe), or more government or market guarantees. The R&D Only LCOE sensitivity cases present the range of LCOE based on financial conditions that are held constant over time unless R&D affects them, and they reflect different levels of technology risk. This case excludes effects of tax reform, tax credits, technology-specific tariffs, and changing interest rates over time. The R&D + Market LCOE case adds to these the financial assumptions (1) the changes over time consistent with projections in the Annual Energy Outlook and (2) the effects of tax reform, tax credits, and tariffs. The ATB representative plant characteristics that best align with those of recently installed or anticipated near-term land-based wind plants are associated with TRG 4. Data for all the resource categories can be found in the ATB data spreadsheet.

R&D Only | R&D + Market

R&D Only
The ATB representative plant characteristics that best align with those of recently installed or anticipated near-term land-based wind plants are associated with TRG 4.
R&D Only Financial Assumptions (constant background rates, no tax or tariff changes)
R&D + Market
The ATB representative plant characteristics that best align with those of recently installed or anticipated near-term land-based wind plants are associated with TRG 4.
R&D Only + Market Financial Assumptions (dynamic background rates, taxes, and tariffs)

The methodology for representing the CAPEX, O&M, and capacity factor assumptions behind each pathway is discussed in Projections Methodology. In general, the degree of adoption of technology innovation distinguishes the Constant, Mid, and Low technology cost scenarios. These projections represent trends that reduce CAPEX and improve performance. Development of these scenarios involves technology-specific application of the following general definitions:

  • Constant Technology = Base Year (or near-term estimates of projects under construction) equivalent through 2050 maintains current relative technology cost differences
  • Mid Technology Cost Scenario = technology advances through continued industry growth, public and private R&D investments, and market conditions relative to current levels that may be characterized as "likely" or "not surprising"
  • Low Technology Cost Scenario = Technology advances that may occur with breakthroughs, increased public and private R&D investments, and/or other market conditions that lead to cost and performance levels that may be characterized as the " limit of surprise" but not necessarily the absolute low bound.

To estimate LCOE, assumptions about the cost of capital to finance electricity generation projects are required, and the LCOE calculations are sensitive to these financial assumptions. Three project finance structures are used within the ATB:

  • R&D Only Financial Assumptions: This sensitivity case allows technology-specific changes to debt interest rates, return on equity rates, and debt fraction to reflect effects of R&D on technological risk perception, but it holds background rates constant at 2016 values from AEO 2018 and excludes effects of tax reform, tax credits, and tariffs.
  • R&D Only + Market Financial Assumptions: This sensitivity case retains the technology-specific changes to debt interest, return on equity rates, and debt fraction from the R&D Only case and adds in the variation over time consistent with AEO 2018, as well as effects of tax reform, tax credits, and technology-specific tariffs. For a detailed discussion of these assumptions, see Changes from 2017 ATB to 2018 ATB.
  • ReEDS Financial Assumptions: ReEDS uses the R&D Only + Market Financial Assumptions for the "Mid" technology cost scenario.

A constant cost recovery period -over which the initial capital investment is recovered-is assumed for all technologies throughout this website, and can be varied in the ATB data spreadsheet.

In general, differences among the technology cost cases reflect different levels of adoption of innovations. Reductions in technology costs reflect the cost reduction opportunities that are listed below.

  • Continued turbine scaling to larger-megawatt turbines with larger rotors such that the swept area/megawatt capacity decreases, resulting in higher capacity factors for a given location
  • Continued diversification of turbine technology whereby the largest rotor diameter turbines tend to be located in lower wind speed sites, but the number of turbine options for higher wind speed sites increases
  • Taller towers that result in higher capacity factors for a given site due to the wind speed increase with elevation above ground level
  • Improved plant siting and operation to reduce plant-level energy losses, resulting in higher capacity factors
  • Wind turbine technology and plants that are increasingly tailored to and optimized for local site-specific conditions
  • More efficient O&M procedures combined with more reliable components to reduce annual average FOM costs
  • Continued manufacturing and design efficiencies such that capital cost/kilowatt decreases with larger turbine components
  • Adoption of a wide range of innovative control, design, and material concepts that facilitate the above high-level trends.

Offshore Wind

Representative Technology

In 2016, the first offshore wind plant commenced commercial operation in the United States near Block Island (Rhode Island). This demonstration project is 30 MW in capacity; in the ATB, cost and performance estimates are made for commercial-scale projects 600 MW in capacity. The ATB Base Year offshore wind plant technology reflects a machine rating of 3.4 MW with a rotor diameter of 115 m and hub height of 85 m, which is typical of European projects installed in 2015-2016.

Resource Potential

Wind resource is prevalent throughout major U.S. coastal areas, including the Great Lakes. The resource potential exceeds 2,000 GW (Musial et al. (2016)), excluding Alaska. Prior estimates of offshore wind resource potential (Schwartz et al. (2010)) were updated in 2016 to extend domain boundaries from 50 nautical miles (nm) to 200 nm, consider turbine hub heights of 100 m (previously 90 m), and assume a capacity array power density of 3 MW/km2 (Musial et al. (2016)). A range of technology exclusions were applied based on maximum water depth for deployment, minimum wind speed, and limits to floating technology in freshwater surface ice. Resource potential was represented by over 7,000 areas for offshore wind plant deployment after accounting for competing use and environmental exclusions, such as marine protected areas, shipping lanes, pipelines, and others.

Offshore wind resource data (100 m) used for 2016 offshore wind resource assessment
Map of the offshore resource in the United States
Source: Musial et al. 2016

Renewable energy technical potential, as defined by Lopez et al. 2012, represents the achievable energy generation of a particular technology given system performance, topographic limitations, and environmental and land-use constraints. The primary benefit of assessing technical potential is that it establishes an upper-boundary estimate of development potential. It is important to understand that there are multiple types of potential-resource, technical, economic, and market (Lopez at al. 2012; NREL, "Renewable Energy Technical Potential").

Base Year and Future Year Projections Overview

Based on the Musial et al. (2016) resource assessment, LCOE was estimated at more than 7,000 areas (with a total capacity of approximately 2,000 GW) in Beiter et al. (2016), taking into consideration a variety of spatial parameters, such as wind speeds, water depth, distance from shore, distance to ports, and wave height. CAPEX, O&M, and capacity factor are calculated for each geographic location using engineering models, hourly wind resource profiles, and representative sea states. The spatial LCOE assessment served as the basis for estimating the ATB baseline LCOE in the Base Year 2016, weighted by the available capacity, for fixed-bottom and floating offshore wind technology.

The Base Year LCOE assumes a 3.4-MW turbine size and long-term average hourly wind profiles and it reflects the least-cost choice among three substructure types (Beiter et al. (2016)):

  • Monopile (fixed-bottom)
  • Jacket (fixed-bottom)
  • Semi-submersible (floating).

The representative offshore wind plant size is assumed to be 600 MW (Beiter et al. (2016)). For illustration in the ATB, the full resource potential, represented by 7,000 areas, was divided into 15 techno-resource groups (TRGs), of which TRGs 1-5 are representative of fixed-bottom wind technology and TRGs 6-15 are representative of floating offshore wind technology. The capacity-weighted average CAPEX, O&M, and capacity factor for each group is presented in the ATB.

Future year projections are derived from estimated cost reduction potential for offshore wind technologies based partially on elicitation of over 160 wind industry experts (Wiser et al. (2016)). Estimates for 2016-2050 were adjusted from the 2016 ATB for inflation (2015$ to $2016$). The specific scenarios are:

  • Constant Technology Cost Scenario: no change in CAPEX, O&M, or capacity factor from 2015 to 2050; consistent across all renewable energy technologies in the ATB
  • Mid Technology Cost Scenario: LCOE percentage reduction from the Base Year equivalent to that corresponding to the Median Scenario (50% probability) in expert survey (Wiser et al. (2016))
  • Low Technology Cost Scenario: LCOE percentage reduction from the Base Year equivalent to that corresponding to the Low scenario (10% probability) in the expert survey (Wiser et al. (2016)).

CAPital EXpenditures (CAPEX): Historical Trends, Current Estimates, and Future Projections

Capital expenditures (CAPEX) are expenditures required to achieve commercial operation in a given year. These expenditures include the wind turbine, the balance of system (e.g., site preparation, installation, and electrical infrastructure), and financial costs (e.g., development costs, onsite electrical equipment, and interest during construction) and are detailed in CAPEX Definition. In the ATB, CAPEX reflects typical plants and does not include differences in regional costs associated with labor, materials, taxes, or system requirements. The related Standard Scenarios product uses regional CAPEX adjustments. The range of CAPEX demonstrates variation with wind resource in the contiguous United States.

The following figure shows the Base Year estimate and future year projections for CAPEX costs. Three cost scenarios are represented: Constant, Mid, and Low technology cost cases. Historical data from land-based wind plants installed in the United States are shown for comparison to the ATB Base Year estimates. The estimate for a given year represents CAPEX of a new plant that reaches commercial operation in that year.

Historical data shown in box-and-whiskers format where a bar represents the median, a box represents the 20th and 80th percentiles, and whiskers represent the minimum and maximum.
Year represents Commercial Online Date for a past or future plant. TRG is defined below.
R&D Only Financial Assumptions (constant background rates, no tax or tariff changes)

CAPEX estimates for 2016 correspond well with market data for plants installed in 2016. Projections reflect a continuation of the downward trend observed in the recent past and are anticipated to continue based on preliminary data for 2017 projects.

In the lower wind resource areas represented by TRGs 6-10, CAPEX is expected to grow as future wind turbine technology transitions to new platforms, including taller towers, larger rotors, and higher machine ratings. In the higher wind resource areas represented by TRGs 1-5, optimization of current wind turbine platforms will lead to lower CAPEX in future years.

Recent Trends

Actual land-based wind plant CAPEX (Wiser and Bolinger (2017)) is shown in box-and-whiskers format for comparison to the ATB current CAPEX estimates and future projections. provide statistical representation of CAPEX for about 65% of wind plants installed in the United States since 2007. CAPEX estimates should tend toward the low end of observed cost because no regional impacts or spur line costs are included. These effects are represented in the market data.

Base Year Estimates

For illustration in the ATB, all potential land-based wind plant areas were represented in 10 TRGs. These were defined by resource potential (GW) and have higher resolution on the highest-quality TRGs, as these are the most likely sites to be deployed, based on their economics.

TRG 1 represents the best 100 GW of wind, as determined by LCOE. TRG 2 represents the next best 200 GW, while TRG 3 represents the next best 400 GW, and TRG 4 represents the next best 800 GW. TRGs 5-9 all represent 1,600 GW of resource potential. TRG 10 represents the remaining 1,148 GW of available potential. This representation is based on the approach described in DOE (2015) and implemented with 2015 market data in Moné et al. (2017).

The following table summarizes the annual average wind speed range for each TRG, capacity-weighted average wind speed, cost and performance parameters for each TRG, and resource potential in terms of capacity and energy for each TRG. Typical land-based wind installations in 2015 and 2016 are associated with TRG4.

TRG Definitions for Land-Based Wind

Techno-Resource Group (TRG) Wind Speed Range (m/s) Weighted Average Wind Speed (m/s) Weighted Average CAPEX ($/kW) Weighted Average OPEX ($/kW-yr) Weighted Average Net CF (%) Potential Wind Plant Capacity (GW) Potential Wind Plant Energy (TWh)
TRG1 8.2-13.5 8.7 1,573 51 47.4% 100 414
TRG2 8.0-10.9 8.4 1,592 51 46.2% 200 810
TRG3 7.7-11.1 8.2 1,599 51 45.0% 400 1,576
TRG4 7.5-13.1 7.9 1,605 51 43.5% 800 3,050
TRG5 6.9-11.1 7.5 1,616 51 40.7% 1,600 5,708
TRG6 6.1-9.4 6.9 1,642 51 36.4% 1,600 5,098
TRG7 5.4-8.3 6.2 1,678 51 30.8% 1,600 4,320
TRG8 4.7-6.9 5.5 1,708 51 24.6% 1,600 3,443
TRG9 4.0-6.0 4.8 1,713 51 18.3% 1,600 2,558
TRG10 1.0-5.3 4.0 1,713 51 11.1% 1,148 1,116
Total 10,648 28,092

Future Year Projections

Mid: Projections of future LCOE were derived from a survey of wind industry experts (Wiser et al. (2016)) for scenarios that are associated with a 50% probability level in 2030 and 2050. Projections of future land-based wind plant CAPEX were determined based on adjustments to CAPEX, fixed O&M (FOM), and capacity factor in each year to result in a predetermined LCOE value derived from Wiser et al. (2016).

In order to achieve the overall LCOE reduction associated with the median and low projections from the expert survey, CAPEX was used to accommodate all improvement aspects other than O&M and capacity factor survey results. In the lower wind resource areas represented by TRGs 6-10, CAPEX is expected to grow as future wind turbine technology transitions to new platforms, including taller towers, larger rotors, and higher machine ratings. In the higher wind resource areas represented by TRGs 1-5, optimization of current wind turbine platforms will lead to lower CAPEX.

Low: Projections of future LCOE for the Low cost scenario were derived from an accelerated development pathway that included incremental improvements to technology through scaling and learning as well as innovation enabled by the DOE's Atmosphere to Electrons research program and anticipated scientific advances (Dykes et al. (2017)). The reductions in turbine and balance-of-system CAPEX were estimated by a survey of wind industry experts (Wiser et al. (2016)) focusing on detailed line item cost reduction potential. The results of the survey show a reduction in turbine and balance-of-system CAPEX by 2030 through turbine scaling with less material use and use of more efficient manufacturing processes. The accelerated decline in CAPEX is expected for all TRGs through 2030 except TRGs 9 and 10, where CAPEX is expected to slightly increase in the near term and then begin to decline at the same rate as the remaining TRGs. After 2030, the rate of CAPEX reduction is expected to continue but at a slower rate. As stated in Dykes et al. (2017), the wind turbine industry is expected to continue trends in scaling seen over the past several decades while learning processes will keep the per-unit power costs of these turbines at or below current levels. In addition, the turbine size increases will lead to economies of scale for the wind power plant through reductions in plant infrastructure and erection costs while science-enabled R&D pathways in turbine design will push materials and manufacturing costs of per-unit power to levels lower than those observed today.

A detailed description of the methodology for developing future year projections is found in Projections Methodology.

Technology innovations that could impact future O&M costs are summarized in LCOE Projections.

CAPEX Definition

Capital expenditures (CAPEX) are expenditures required to achieve commercial operation in a given year.

Based on EIA (2013), Moné et al. (2015), and Beiter et al. (2016), the System Cost Breakdown Structure of the ATB for the wind plant envelope is defined to include:

  • Wind turbine supply
  • Balance of system (BOS)
    • Turbine installation, substructure supply and installation
    • Site preparation, port and staging area support for delivery, storage, handling, and installation of underground utilities
    • Electrical infrastructure, such as transformers, switchgear, and electrical system connecting turbines to each other (array cable system costs) and to the cable landfall (export cable system costs)
    • Development and project management
  • Financial costs
    • Owners' costs, such as development costs, preliminary feasibility and engineering studies, environmental studies and permitting, legal fees, insurance costs, and property taxes during construction
    • Interest during construction estimated based on three-year duration accumulated 40%/40%/20% at half-year intervals and an 8% interest rate (ConFinFactor).

CAPEX can be determined for a plant in a specific geographic location as follows:

CAPEX = ConFinFactor × (OCC × CapRegMult + GCC), where GCC = OnSpurCost + OffSpurCost
(See the Financial Definitions tab in the ATB data spreadsheet.)

Regional cost variations are not included in the ATB (CapRegMult = 1). In the ATB, the input value is overnight capital cost (OCC) and details to calculate interest during construction (ConFinFactor). Because transmission infrastructure between an offshore wind plant and the point at which a grid connection is made onshore is a significant component of the offshore wind plant cost, an offshore spur line cost (OffSpurCost) for each TRG is included in the CAPEX estimate. The offshore spur line cost reflects a capacity-weighted average of all potential wind plant areas within a TRG, similar to OCC.

In the ATB, CAPEX represents the capacity-weighted average values of all potential wind plant areas within a TRG and varies with water depth and distance from shore. Regional cost effects associated with labor rates, material costs, and other regional effects as defined by DOE 2015 expand the range of CAPEX. Unique land-based spur line costs for each of the 7,000 areas based on distance and transmission line costs expand the range of CAPEX even further. The following figure illustrates the ATB representative plants relative to the range of CAPEX including regional costs across the contiguous United States. The ATB representative plants are associated with a regional multiplier of 1.0.

R&D Only Financial Assumptions (constant background rates, no tax or tariff changes)

Standard Scenarios Model Results

ATB CAPEX, O&M, and capacity factor assumptions for the Base Year and future projections through 2050 for Constant, Mid, and Low technology cost scenarios are used to develop the NREL Standard Scenarios using the ReEDS model. See ATB and Standard Scenarios.

CAPEX in the ATB does not represent regional variants (CapRegMult) associated with labor rates, material costs, etc., but the ReEDS model does include 134 regional multipliers (EIA (2013)).

The ReEDS model determines offshore spur line and land-based spur line (GCC) uniquely for each of the 7,000 areas based on distance and transmission line cost.

Natural Gas Internal Combustion Engine Vehicle

Operations and maintenance (O&M) costs represent the annual fixed expenditures required to operate and maintain a wind plant over its lifetime of 30 years, including:

  • Insurance, taxes, land lease payments and other fixed costs (e.g., project management and administration, weather forecasting, and condition monitoring)
  • Present value and annualized large component replacement costs over technical life (e.g., blades, gearboxes, and generators)
  • Scheduled and unscheduled maintenance of wind plant components, including turbines and transformers, over the technical lifetime of the plant.

The following figure shows the Base Year estimate and future year projections for fixed O&M (FOM) costs. Three cost scenarios are represented. The estimate for a given year represents annual average FOM costs expected over the technical lifetime of a new plant that reaches commercial operation in that year. The range of Base Year O&M estimates reflects distance from shore and metocean conditions.

Base Year Estimates

FOM costs vary by distance from shore and metocean conditions. As a result, O&M costs vary from $106/kW-year (TRG 6) to $159/kW-year (TRG 5) in 2016. The capacity-weighted average in the ATB for fixed-bottom offshore technology (TRGs 1-5) is $148/kW-year; the corresponding value for floating offshore wind technology (TRGs 6-15) is $127/kW-year.

Future Year Projections

Future fixed-bottom offshore wind technology O&M is assumed to decline 7% by 2050 in the Mid cost case and 16% in the Low cost wind case, based on the expert survey conducted by Wiser et al. (2016).

Future floating offshore wind technology O&M is assumed to decline 7% by 2050 in the Mid cost case and 16% in the Low cost wind case, based on the expert survey conducted by Wiser et al. (2016).

A detailed description of the methodology for developing future year projections is found in Projections Methodology.

Technology innovations that could impact future O&M costs are summarized in LCOE Projections.

Capacity Factor: Expected Annual Average Energy Production Over Lifetime

The capacity factor represents the expected annual average energy production divided by the annual energy production, assuming the plant operates at rated capacity for every hour of the year. It is intended to represent a long-term average over the lifetime of the plant. It does not represent interannual variation in energy production. Future year estimates represent the estimated annual average capacity factor over the technical lifetime of a new plant installed in a given year.

The capacity factor is influenced by the rotor swept area/generator capacity, hub height, hourly wind profile, expected downtime, and energy losses within the wind plant. It is referenced to 100-m above-water-surface, long-term average hourly wind resource data from Musial et al. (2016).

The following figure shows a range of capacity factors based on variation in the wind resource, water depth, and distance from shore for offshore wind plants in the contiguous United States. Pre-construction estimates for offshore wind plants operating globally in 2015, according to the year in which plants were installed, is shown for comparison to the ATB Base Year estimates. The range of Base Year estimates illustrate the effect of locating an offshore wind plant in a variety of wind resource, water depth, and distance from shore conditions (TRGs 1-5 are fixed-bottom offshore wind plants and TRGs 6-15 are floating offshore wind plants). Future projections are shown for Constant, Mid, and Low technology cost scenarios.

Historical data shown in box-and-whiskers format where a bar represents the median, a box represents the 20th and 80th percentiles, and whiskers represent the minimum and maximum.
Historical data represent pre-construction capacity factor estimates for plants with Commercial Online Date specified by year.
Projection data represent expected annual average capacity factor for plants with Commercial Online Date specified by year.

Recent Trends

Pre-construction annual energy estimates from 93% of global operating wind capacity in 2016 (NREL's internal offshore wind database) is shown in a box-and-whiskers format for comparison with the ATB current estimates and future projections. The historical data illustrate pre-construction estimated capacity factors for projects by year of commercial online date. The range of capacity factors defined by the ATB TRGs compared well with the estimated capacity factors for projects installed in 2015.

Base Year Estimates

The capacity factor is determined using a representative power curve for a generic NREL-modeled offshore wind turbine (Beiter et al. (2016)) and includes geospatial estimates of gross capacity factors for the entire resource area (Musial et al. (2016)). The net capacity factor considers spatial variation in wake losses, electrical losses, turbine availability, and other system losses. For illustration in the ATB, all 7,000 wind plant areas are represented in 15 TRGs.

TRG Definitions for Offshore Wind

TRG LCOE Range ($/MWh) Wind Speed Range (m/s) Weighted Average Wind Speed (m/s) Weighted Water Depth (m) Weighted Distance Site to Cable Landfall (km) Weighted Average CAPEX ($/kW) Weighted Average OPEX ($/kW/yr) Weighted Average Net CF (%) Potential Wind Plant Capacity (GW) Potential Wind Plant Energy (TWh)
Fixed-Bottom
TRG 1LCOE <= 1418.5–9.08.61363,80013745%1249
TRG 2LCOE <= 1498.0–8.58.41693,89014343%2594
TRG 3LCOE <= 1578.0–8.58.319154,02714542%50182
TRG 4LCOE <= 1928.0–8.58.326364,55615240%3201,131
TRG 5LCOE <= 3067.5–8.07.936725,33315937%3201,023
Floating
TRG 6LCOE <= 1669.5–109.7130245,96110551%1255
TRG 7LCOE <= 1759.5–109.7145406,21710850%25108
TRG 8LCOE <= 1889.5–109.5139506,33711148%50212
TRG 9LCOE <= 2069.0–9.59.4136706,68712247%100414
TRG 10LCOE <= 2299.0–9.59.1140946,93112945%200781
TRG 11LCOE <= 2528.5–9.08.73231187,21113442%200727
TRG 12LCOE <= 2748.0–8.58.14041237,22413537%200651
TRG 13LCOE <= 2997.5–8.07.84741387,41113635%200615
TRG 14LCOE <= 3417.0–7.57.46151307,60613132%200566
TRG 15LCOE <= 4387.5–8.07.57971998,20413831%143390
Total2,0586,997
Offshore Wind TRG Definition

Future Year Projections

Projections of capacity factors for plants installed in future years were determined based on estimates obtained through an expert survey conducted by Wiser et al. (2016) for both fixed-bottom and floating offshore wind technologies. Projections for capacity factors implicitly reflect technology innovations such as larger rotors and taller towers that will increase energy capture at the same geographic location without explicitly specifying tower height and rotor diameter changes.

A detailed description of the methodology for developing future year projections is found in Projections Methodology.

Technology innovations that could impact future O&M costs are summarized in LCOE Projections.

Standard Scenarios Model Results

ATB CAPEX, O&M, and capacity factor assumptions for the Base Year and future projections through 2050 for Constant, Mid, and Low technology cost scenarios are used to develop the NREL Standard Scenarios using the ReEDS model. See ATB and Standard Scenarios.

The ReEDS model output capacity factors for offshore wind can be lower than input capacity factors due to endogenously estimated curtailments determined by scenario constraints.

Plant Cost and Performance Projections Methodology

ATB projections were derived from the results of a survey of 163 of the world's wind energy experts Wiser et al. (2016). The survey was conducted to gain insight into the possible future cost reductions, the source of those reductions, and the conditions needed to enable continued innovation and lower costs (Wiser et al. (2016)). The expert survey produced three cost reduction scenarios associated with probability levels of 10%, 50%, and 90% of achieving LCOE reductions by 2030 and 2050. In addition, the scenario results include estimated changes to CAPEX, O&M, capacity factor, project life, and weighted average cost of capital (WACC) by 2030.

For the ATB, three different technology cost scenarios were adapted from the expert survey results for scenario modeling as bounding levels:

  • Constant Technology Cost Scenario: no change in CAPEX, O&M, or capacity factor from 2015 to 2050; consistent across all renewable energy technologies in the ATB
  • Mid Technology Cost Scenario: LCOE percentage reduction from the Base Year equivalent to that corresponding to the Median Scenario (50% probability) in the expert survey (Wiser et al. (2016))
  • Low Technology Cost Scenario: LCOE percentage reduction from the Base Year equivalent to that corresponding to the Low scenario (10% probability) in the expert survey (Wiser et al. (2016)).

Expert survey estimates were normalized to the ATB Base Year starting point in order to focus on projected cost reduction instead of absolute reported costs. The percentage reduction in LCOE by 2020, 2030, and 2050 from the expert survey's Median and Low scenarios are implemented as the ATB Mid and Low cost scenarios. This is accomplished by utilizing survey estimates for changes to capacity factor and O&M costs by 2030 and 2050. The corresponding CAPEX value to achieve the overall LCOE reduction is computed. The percentage reduction in LCOE by 2030 and by 2050 was applied equally across all TRGs. The overall reduction in LCOE by 2050 for the Mid cost scenario is 39% and for the Low cost scenario is 51%.

A broad sample of cost of offshore wind energy projections provides context for the ATB Constant, Mid, and Low technology cost projections. Based on a TRG4 resource classification,[1] the ATB Mid cost projection, which corresponds to the median scenario from the Wiser et al. (2016) expert survey, results in LCOE reductions that are fairly aligned with the median scenarios of external studies (BNEF (2017c); IRENA (2016b); Catapult (2016); Lazard (2017)). EIA (2017b) estimates higher cost levels in the period 2022-2041, while BNEF (2018) estimates lower cost levels for the U.S by the mid-2020s. These external studies were reviewed to validate the baseline estimates and projections derived for the ATB. Generally, while some published studies as well as recent tender awards for European projects to be installed by the mid-2020s suggest significant near-term cost reduction (see e.g., Musial et al. (2017)), it is likely that the United States will lag due to a different development stage of the U.S. supply chain and port infrastructure.

The relative costs of mid-depth water plants and deep water, or floating, offshore wind plants are maintained constant throughout the scenarios for simplicity. Some hypothesize that unique aspects of floating technologies, such as the ability to assemble and commission turbines at the port, could reduce the cost of floating technologies relative to fixed-bottom technologies.

Levelized Cost of Energy (LCOE) Projections

Levelized cost of energy (LCOE) is a simple metric that combines the primary technology cost and performance parameters: CAPEX, O&M, and capacity factor. It is included in the ATB for illustrative purposes. The ATB focuses on defining the primary cost and performance parameters for use in electric sector modeling or other analysis where more sophisticated comparisons among technologies are made. The LCOE accounts for the energy component of electric system planning and operation. The LCOE uses an annual average capacity factor when spreading costs over the anticipated energy generation. This annual capacity factor ignores specific operating behavior such as ramping, start-up, and shutdown that could be relevant for more detailed evaluations of generator cost and value. Electricity generation technologies have different capabilities to provide such services. For example, wind and PV are primarily energy service providers, while the other electricity generation technologies provide capacity and flexibility services in addition to energy. These capacity and flexibility services are difficult to value and depend strongly on the system in which a new generation plant is introduced. These services are represented in electric sector models such as the ReEDS model and corresponding analysis results such as the Standard Scenarios.

The following three figures illustrate LCOE, which includes the combined impact of CAPEX, O&M, and capacity factor projections for off-shore wind across the range of resources present in the contiguous United States. For the purposes of the ATB, the costs associated with technology and project risk in the U.S. market are represented in the financing costs, not in the upfront capital costs (e.g. developer fees, contingencies). An individual technology may receive more favorable financing terms outside of the U.S., due to less technology and project risk, caused by more project development experience (e.g. offshore wind in Europe), or more government or market guarantees. The R&D Only LCOE sensitivity cases present the range of LCOE based on financial conditions that are held constant over time unless R&D affects them, and they reflect different levels of technology risk. This case excludes effects of tax reform, tax credits, technology-specific tariffs, and changing interest rates over time. The R&D + Market LCOE case adds to these the financial assumptions (1) the changes over time consistent with projections in the Annual Energy Outlook and (2) the effects of tax reform, tax credits, and tariffs. The ATB representative plant characteristics that best align with those of recently installed or anticipated near-term land-based wind plants are associated with TRG 4. Data for all the resource categories can be found in the ATB data spreadsheet.

R&D Only | R&D + Market

R&D Only
The ATB representative plant characteristics that best align with those of recently installed or anticipated near-term offshore wind plants are associated with TRGs 3-5.
R&D Only Financial Assumptions (constant background rates, no tax or tariff changes)
R&D + Market
The ATB representative plant characteristics that best align with those of recently installed or anticipated near-term offshore wind plants are associated with TRGs 3-5.
R&D Only + Market Financial Assumptions (dynamic background rates, taxes, and tariffs)

The methodology for representing the CAPEX, O&M, and capacity factor assumptions behind each pathway is discussed in Projections Methodology. In general, the degree of adoption of technology innovation distinguishes the Constant, Mid, and Low technology cost scenarios. These projections represent trends that reduce CAPEX and improve performance. Development of these scenarios involves technology-specific application of the following general definitions:

  • Constant Technology = Base Year (or near-term estimates of projects under construction) equivalent through 2050 maintains current relative technology cost differences
  • Mid Technology Cost Scenario = technology advances through continued industry growth, public and private R&D investments, and market conditions relative to current levels that may be characterized as "likely" or "not surprising"
  • Low Technology Cost Scenario = Technology advances that may occur with breakthroughs, increased public and private R&D investments, and/or other market conditions that lead to cost and performance levels that may be characterized as the " limit of surprise" but not necessarily the absolute low bound.
  • To estimate LCOE, assumptions about the cost of capital to finance electricity generation projects are required, and the LCOE calculations are sensitive to these financial assumptions. Three project finance structures are used within the ATB:
  • R&D Only Financial Assumptions: This sensitivity case allows technology-specific changes to debt interest rates, return on equity rates, and debt fraction to reflect effects of R&D on technological risk perception, but it holds background rates constant at 2016 values from AEO 2018 and excludes effects of tax reform, tax credits, and tariffs.
  • R&D Only + Market Financial Assumptions: This sensitivity case retains the technology-specific changes to debt interest, return on equity rates, and debt fraction from the R&D Only case and adds in the variation over time consistent with AEO 2018, as well as effects of tax reform, tax credits, and technology-specific tariffs. For a detailed discussion of these assumptions, see Changes from 2017 ATB to 2018 ATB.
  • ReEDS Financial Assumptions: ReEDS uses the R&D Only + Market Financial Assumptions for the "Mid" technology cost scenario.
  • A constant cost recovery period -over which the initial capital investment is recovered-is assumed for all technologies throughout this website, and can be varied in the ATB data spreadsheet.
  • The equations and variables used to estimate LCOE are defined on the equations and variables page. For illustration of the impact of changing financial structures such as WACC, see Project Finance Impact on LCOE. For LCOE estimates for the Constant, Mid, and Low technology cost scenarios for all technologies, see 2018 ATB Cost and Performance Summary.
  • In general, differences among the technology cost cases reflect different levels of adoption of innovations. Reductions in technology costs reflect the cost reduction opportunities that are listed below.
  • Continued turbine scaling to larger-megawatt turbines with larger rotors such that swept area/megawatt capacity decreases resulting in higher capacity factors for a given location
  • Greater market competition in the production of primary components (e.g., turbines, support structure), and installation services
  • Economy-of-scale and productivity improvements in manufacturing, including mass production of substructure component and optimized installation strategies
  • Improved plant siting and operation to reduce plant-level energy losses, resulting in higher capacity factors
  • More efficient O&M procedures combined with more reliable components to reduce annual average FOM costs
  • Adoption of a wide range of innovative control, design, and material concepts that facilitate the high-level trends described above.

Concentrating Solar Power

Representative Technology

Concentrating solar power (CSP) technology is assumed to be molten-salt power towers. Thermal energy storage (TES) is accomplished by storing hot molten salt in a two-tank system, which includes a hot-salt tank and a cold-salt tank. Stored hot salt can be dispatched to the power block as needed, regardless of solar conditions, to continue power generation and allow for electricity generation after sunlight hours. In the ATB, CSP plants with 10 hours of TES are illustrated. Ten hours is the amount of storage at the Crescent Dunes CSP plant in Nevada, which is representative of most new molten-salt power tower projects.

Molten-salt power towers (with 10 hours of storage) were selected as the representative technology over the parabolic trough with synthetic oil-heat transfer fluid for two main reasons. First, most new global capacity of CSP plants in development or under construction are molten-salt power towers. From 2015, 3.7 GWe of molten-salt power towers were in development or under construction (IRENA 2018 and SolarReserve 2018), compared to 1.3 GWe of parabolic trough (IRENA 2018). Second, current indications are that molten-salt power towers have the greatest cost reduction potential, in terms of both CAPEX and LCOE, and they are part of the U.S. DOE Generation 3 (Gen3) roadmap for the next generation of commercial CSP plants (Mehos et al. (2017)).

The first large molten-salt power tower plant in the United States, Crescent Dunes (110 MWe with 10 hours of storage) was commissioned in 2015 with a reported installed CAPEX of $8.96/WAC (Danko (2015); Taylor (2016)). No new molten salt storage CSP plants were commissioned in the United States in 2017 or 2018. Molten-salt power tower plants are being bid and built in Australia, Chile, and Dubai (NREL n.d.). The United States currently has only one announced project; for the Sandstone project, it has been announced that up to 2 GWe consisting of up to 10 molten-salt power tower systems could be built, each with approximately 10 hours of storage (SolarReserve 2018).

Resource Potential

Solar resource is prevalent throughout the United States, but the Southwest is particularly suited to CSP plants. The direct normal irradiance (DNI) resource across the Southwest, which is some of the best in the world, ranges from 6.0 to over 7.5 kWh/m2/day (NREL 2018). The raw resource technical potential of seven western states (Arizona, California, Colorado, Nevada, New Mexico, Utah, and Texas) exceeds 11,000 GW-which is almost tenfold current total U.S. electricity generation capacity-considering regions in these states with an annual average resource > 6.0 kWh/m2/day and after accounting for exclusions such as land slope (> 1%), urban areas, water features, and parks, preserves, and wilderness areas (Mehos, Kabel, and Smithers (2009)).

map: mean U.S. solar resource available to CSP systems
Map of mean solar resource available to CSP systems in the United States

Renewable energy technical potential, as defined by Lopez et al. 2012, represents the achievable energy generation of a particular technology given system performance, topographic limitations, and environmental and land-use constraints. The primary benefit of assessing technical potential is that it establishes an upper-boundary estimate of development potential. It is important to understand that there are multiple types of potential-resource, technical, economic, and market (Lopez at al. 2012; NREL, Renewable Energy Technical Potential").

The Solar Programmatic Environmental Impact Statement identified 17 solar energy zones for priority development of utility-scale solar facilities in six western states. These zones total 285,000 acres and are estimated to accommodate up to 24 GW of solar potential. The program also allows development, subject to a more rigorous review, on an additional 19 million acres of public land. Development is prohibited on approximately 79 million acres.

According to NREL's Concentrating Solar Power Projects website and the CSP Today Global Projects Tracker (New Energy Update 2018), 12 of the 14 currently operational CSP plants greater than 5 MWe in the United States use parabolic trough technology, and two are power tower facilities-Ivanpah (392 MWe) and Crescent Dunes (110 MWe).

Base Year and Future Year Projections Overview

For the ATB, three representative sites were chosen based on resource class to demonstrate the range of cost and performance across the United States:

  • CAPEX is determined using manufacturing cost models and is benchmarked with industry data. CSP performance and cost are based on the molten-salt power tower technology with dry-cooling to reduce water consumption.
  • O&M cost is benchmarked against industry data.
  • Capacity factor varies with inclusion of TES and solar irradiance. The listed projects assume power towers with 10 hours of TES at these locations:
  • Fair resource (e.g., Abilene Regional Airport, Texas 5.59 kWh/m2/day based on the site TMY3 file)
  • Good resource (e.g., Las Vegas, Nevada 7.1 kWh/m2/day based on the site TMY3 file)
  • Excellent resource (e.g., Daggett, California 7.46 kWh/m2/day based on the site TMY3 file).
  • Representative CSP plant size is net 100 MWe.

The CSP costs originated from a NREL survey leading to updated cost estimates in SAM 2017.09.05. These 2017 costs were deflated to the ATB Base Year of 2016 via the consumer price index. The SAM 2017 costs translate to costs in 2020 in the ATB due to the three-year construction period. (SAM costs are based on the project announcement year, while the ATB is based on the plant commissioning year).

Future year projections are informed by published literature and technology pathway assessments for CAPEX and O&M cost reductions. Three different projections were developed for scenario modeling as bounding levels:

  • Constant Technology Cost Scenario: no change in CAPEX, O&M, or capacity factor from current estimates (2020 for CSP) to 2050; consistent across all renewable energy technologies in the ATB
  • Mid Technology Cost Scenario: the median of published literature projections for future CAPEX; it is expected based on literature that there could be a 25% CAPEX reduction by 2030 from the 2015 costs (Feldman et al. 2016). From 2030 to 2050, a further 20% reduction in CAPEX is assumed.
  • Low Technology Cost Scenario: originates from the lowest CAPEX projections in literature to 2025 (IRENA 2016) and is extended to later years based on DOE research targets.

CAPital EXpenditures (CAPEX): Historical Trends, Current Estimates, and Future Projections

Capital expenditures (CAPEX) are expenditures required to achieve commercial operation in a given year. These expenditures include the generation plant, the balance of system (e.g., site preparation, installation, and electrical infrastructure), and financial costs (e.g., development costs, and interest during construction) and are detailed in CAPEX Definition. In the ATB, CAPEX reflects typical plants and does not include differences in regional costs associated with labor, materials, taxes, or system requirements. The related Standard Scenarios product uses regional CAPEX adjustments. The range of CAPEX demonstrates variation with resource in the contiguous United States.

The following figure shows the Base Year estimate and future year projections for CAPEX costs. Three cost scenarios are represented: Constant, Mid, and Low. The estimate for a given year represents CAPEX of a new plant that reaches commercial operation in that year.

R&D Only Financial Assumptions (constant background rates, no tax or tariff changes)

Base Year Estimates

CAPEX is unchanged for resource class because the same plant is assumed to be built in each location. The capacity factor will change with resource.

TES increases plant CAPEX but also increases capacity factor and annual efficiency. TES generally lowers LCOE for power towers.

The CAPEX estimate (with a base year of 2016) is approximately $7,870/kWe in $2016. It is for a representative power tower with 10 hours of storage and a solar multiple of 2.4. Based on recent assessment of the industry and expected project completion in 2020, the CAPEX estimate for 2020 is $6,640/kWe in $2016 .

Future Year Projections

Three cost projections are developed for CSP technologies:

  • Constant Technology Cost Scenario: no change in CAPEX, O&M, or capacity factor from current estimates (2020 for CSP) to 2050; consistent across all renewable energy technologies in the ATB
  • Mid Technology Cost Scenario: the median of published literature projections for future CAPEX; it is expected based on literature that there could be a 25% CAPEX reduction by 2030 from the 2015 costs (Feldman et al. (2017)). From 2030 to 2050, a further 20% reduction in CAPEX is assumed
  • Low Technology Cost Scenario: originates from the lowest CAPEX projections to 2025 (IRENA 2016) and is extended to later years based on DOE research targets.

A detailed description of the methodology for developing future year projections is found in Projections Methodology.

Technology innovations that could impact future O&M costs are summarized in LCOE Projections.

CAPEX Definition

Capital expenditures (CAPEX) are expenditures required to achieve commercial operation in a given year.

The ATB represents the year in which a plant starts commercial operation. Accordingly, for plants whose construction duration exceeds one year, CAPEX costs will represent technology costs that are lagging current-year estimates by at least one year. For CSP plants, the construction period is typically three years.

For the ATB-and based on based on EIA 2016a, Turchi et al 2010, and Turchi and Heath 2013 - the CSP generation plant envelope is defined to include:

  • CSP generation plant
  • Solar collectors
  • Solar receiver
  • Piping and heat-transfer fluid system
  • Power block (heat exchangers, power turbine, generator, and cooling system)
  • Thermal energy storage system
  • Installation
  • Balance of system, including installation, land acquisition, electrical infrastructure, and project indirect costs
  • Land acquisition, site preparation, and installation of underground utilities, access roads, fencing, and buildings for operations and maintenance
  • Electrical infrastructure, such as transformers, switchgear, and electrical system connecting modules to each other and to control the center; the generator voltage is 13.8 kV, the step-up transformer is 13.8/230kV, and the transmission tie line is 230 kV
  • Project indirect costs, including costs related to engineering, distributable labor and materials, construction management start up and commissioning, and contractor overhead costs, fees, and profit
  • Financial costs
  • Owners' costs, such as development costs, preliminary feasibility and engineering studies, environmental studies and permitting, legal fees, insurance costs, and property taxes during construction
  • Onsite electrical equipment (e.g., switchyard), a nominal-distance spur line (< 1 mile), and necessary upgrades at a transmission substation; distance-based spur line cost (GCC) not included in the ATB
  • Interest during construction estimated based on three-year duration accumulated 80%/10%/10% at half-year intervals and a nominal interest rate (ConFinFactor).

CAPEX can be determined for a plant in a specific geographic location as follows:

CAPEX = ConFinFactor × (OCC × CapRegMult + GCC)
(See the Financial Definitions tab in the ATB data spreadsheet)

Regional cost variations and geographically specific grid connection costs are not included in the ATB (CapRegMult = 1; GCC = 0). In the ATB, the input value is overnight capital cost (OCC) and details to calculate interest during construction (ConFinFactor).

In the ATB, CAPEX represents a typical solar-CSP plant with 10 hours of thermal storage and does not vary with resource. Regional cost effects associated with labor rates, material costs, and other regional effects as defined by EIA 2016a expand the range of CAPEX. Unique land-based spur line costs based on distance and transmission line costs expand the range of CAPEX even further. The following figure illustrates the ATB representative plant relative to the range of CAPEX including regional costs across the contiguous United States. The ATB representative plants are associated with a regional multiplier of 1.0.

R&D Only Financial Assumptions (constant background rates, no tax or tariff changes)

Standard Scenarios Model Results

ATB CAPEX, O&M, and capacity factor assumptions for the Base Year and future projections through 2050 for Constant, Mid, and Low technology cost scenarios are used to develop the NREL Standard Scenarios using the ReEDS model. See ATB and Standard Scenarios.

CAPEX in the ATB does not represent regional variants (CapRegMult) associated with labor rates, material costs, etc., but the ReEDS model does include 134 regional multipliers (EIA 2016a).

The ReEDS model determines the land-based spur line (GCC) uniquely for each potential CSP plant based on distance and transmission line cost.

Natural Gas Internal Combustion Engine Vehicle

Operations and maintenance (O&M) costs represent the annual expenditures required to operate and maintain a solar CSP plant over its lifetime of 30 years, including:

  • Operating and administrative labor, insurance, legal and administrative fees, and other fixed costs
  • Utilities (water, power, and natural gas) and mirror washing
  • Scheduled and unscheduled maintenance, including replacement parts for solar field and power block components over the technical lifetime of the plant.

The following figure shows the Base Year estimate and future year projections for fixed O&M (FOM) costs. Three cost scenarios are represented. The estimate for a given year represents annual average FOM costs expected over the technical lifetime of a new plant that reaches commercial operation in that year.

Base Year Estimates

FOM is assumed to be $67/kW-yr until 2020. Variable O&M is approximately $4.1/MWh until 2020 and $3.50/MWh after that (Kurup and Turchi (2015)).

Future Year Projections

Future FOM is assumed to decline to $50/kW-yr by 2030 in the Mid cost case (i.e., approximately a 25% drop) and the SunShot target of approximately $41/kW-yr by 2030 in the Low cost case (DOE (2012)).

A detailed description of the methodology for developing future year projections is found in Projections Methodology.

Technology innovations that could impact future O&M costs are summarized in LCOE Projections.

Capacity Factor: Expected Annual Average Energy Production Over Lifetime

The capacity factor represents the expected annual average energy production divided by the annual energy production, assuming the plant operates at rated capacity for every hour of the year. It is intended to represent a long-term average over the lifetime of the plant. It does not represent interannual variation in energy production. Future year estimates represent the estimated annual average capacity factor over the technical lifetime of a new plant installed in a given year.

Capacity factors are influenced by power block technology, storage technology and capacity, the solar resource, expected downtime, and energy losses. The solar multiple is a design choice that influences the capacity factor.

The following figure shows a range of capacity factors based on variation in the resource for CSP plants in the contiguous United States. The range of the Base Year estimates illustrates the effect of locating a CSP plant at a site with fair, good, or excellent solar resource. The future projections for the Constant, Mid, and Low technology cost scenarios are unchanged from the Base Year. Technology improvements are focused on CAPEX and O&M cost elements.

Base Year Estimates

For illustration in the ATB, a range of capacity factors is associated with three resource locations in the contiguous United States, as represented in the ReEDS model for three classes of insolation:

  • Fair resource: Abilene, Texas: 5.59 kWh/m2/day based on the site TMY3 file equals 42% capacity factor
  • Good resource: Las Vegas, Nevada: 7.1 kWh/m2/day based on the site TMY3 file equals 56% capacity factor
  • Excellent resource: Daggett, California: 7.46 kWh/m2/day based on the site TMY3 file equals 59% capacity factor.

Future Year Projections

The CSP technologies are assumed to be power towers, but with different power cycles and operating conditions as time passes:

  • 2016: a molten-salt (sodium nitrate/potassium nitrate, aka, solar salt) power tower with direct two-tank TES combined with a steam-Rankine power cycle running at 574° C and 41.2% gross efficiency
  • 2020: similar design with identified near-term reductions in heliostat and power system costs
  • 2030 Mid: longer-term reductions (e.g., in the heliostats and power system)
  • 2030 Low: molten-salt power tower with direct two-tank TES combined with a power cycle running at 700° C and 55% gross efficiency.

Over time, CSP plant output may decline. Capacity factor degradation due to mirror and other component degradation is not accounted for in ATB estimates of capacity factor or LCOE.

The ATB capacity factors are generated from Constant, Mid and Low technology cost plant simulations in SAM 2017.09.05.

Estimates of capacity factors for CSP in the ATB represent typical operation. The dispatch characteristics of these systems are valuable to the electric system to manage changes in net electricity demand. Actual capacity factors will be influenced by the degree to which system operators call on CSP plants to manage grid services.

Standard Scenarios Model Results

ATB CAPEX, O&M, and capacity factor assumptions for the Base Year and future projections through 2050 for Constant, Mid, and Low technology cost scenarios are used to develop the NREL Standard Scenarios using the ReEDS model. See ATB and Standard Scenarios.

CSP plants with TES can be dispatched by grid operators to accommodate diurnal and seasonal load variations and output from variable generation sources (wind and solar PV). Because of this, their annual energy production and the value of that generation are determined by the electric system needs and capacity and ancillary services markets.

Plant Cost and Performance Projections Methodology

When comparing the ATB projections with other projections, note that there are major differences in technology assumptions, radiation conditions, field sizes, storage configurations, and other factors.

The Low ATB projection is based on the SunShot Vision Study (DOE (2012); Mehos et al. (2016)) and has been vetted with solar industry representatives.

Projections of future utility-scale CSP plant CAPEX and O&M are based on three different technology cost scenarios were developed for scenario modeling as bounding levels:

  • Constant cost
    • Modeled as molten-salt (sodium nitrate/potassium nitrate, aka, solar salt) power tower with direct two-tank TES combined with a steam-Rankine power cycle running at 574° C and 41.2% gross efficiency in 2016
    • Costs stay the same from the 2020 estimate through 2050, consistent with ATB renewable energy technologies
  • Mid cost
    • Based on published projections that highlight an overall CSP CAPEX reduction of 25% by 2030 compared to 2015 costs, and which represent a potential median compared to other published CSP projections until 2050 (Feldman et al. 2016; IRENA 2016)
    • Gradual reductions in heliostat and power system cost due to greater deployment volume assumed for 2020 and onwards based on current state of industry
    • CAPEX and O&M both drop by 25% by 2030, relative to 2015 costs
    • A further 20% overall CAPEX decrease is assumed from 2030 to 2050. All three components of the CSP CAPEX (the turbine, storage, and the solar field), decrease proportionately by 20% from 2030 to 2050.
  • Low cost
    • Significant reductions in heliostat and power system cost due to greater deployment volume and R&D are used for 2020; the plant was modeled as an advanced molten-salt power tower with direct two-tank TES combined with a power cycle running at 700° C and 55% gross efficiency in 2030 (Mehos et al. (2017)).
    • SunShot CAPEX and O&M targets are approximately met in 2030, including new high-efficiency power cycles and low-cost heliostats.
    • A further 20% overall CAPEX decrease is assumed from 2030 to 2050 based on potential deployment in the United States. The 20% decrease in overall CSP CAPEX is split over the three components: the turbine, storage, and the solar field. It can be expected that greater cost reductions could be achieved for the power block/turbine and the solar field than for the storage.

Levelized Cost of Energy (LCOE) Projections

Levelized cost of energy (LCOE) is a simple metric that combines the primary technology cost and performance parameters: CAPEX, O&M, and capacity factor. It is included in the ATB for illustrative purposes. The ATB focuses on defining the primary cost and performance parameters for use in electric sector modeling or other analysis where more sophisticated comparisons among technologies are made. The LCOE accounts for the energy component of electric system planning and operation. The LCOE uses an annual average capacity factor when spreading costs over the anticipated energy generation. This annual capacity factor ignores specific operating behavior such as ramping, start-up, and shutdown that could be relevant for more detailed evaluations of generator cost and value. Electricity generation technologies have different capabilities to provide such services. For example, wind and PV are primarily energy service providers, while the other electricity generation technologies such as CSP can provide capacity and flexibility services in addition to energy. These capacity and flexibility services are difficult to value and depend strongly on the system in which a new generation plant is introduced. These services are represented in electric sector models such as the ReEDS model and corresponding analysis results such as the Standard Scenarios.

The following three figures illustrate LCOE, which includes the combined impact of CAPEX, O&M, and capacity factor projections for power-tower CSP across the range of resources present in the contiguous United States. For the purposes of the ATB, the costs associated with technology and project risk in the U.S. market are represented in the financing costs, not in the upfront capital costs (e.g. developer fees, contingencies). An individual technology may receive more favorable financing terms outside of the U.S., due to less technology and project risk, caused by more project development experience (e.g. offshore wind in Europe), or more government or market guarantees. The R&D Only LCOE sensitivity cases present the range of LCOE based on financial conditions that are held constant over time unless R&D affects them, and they reflect different levels of technology risk. This case excludes effects of tax reform, tax credits, technology-specific tariffs, and changing interest rates over time. The R&D + Market LCOE case adds to these the financial assumptions (1) the changes over time consistent with projections in the Annual Energy Outlook and (2) the effects of tax reform, tax credits, and tariffs. For example, the projected LCOE could potentially increase from the end of 2020 due to the decreasing levels of the ITC. The ATB representative plant characteristics that best align with those of recently installed or anticipated near-term CSP plants are associated with Tower-Excellent Resource. Data for all the resource categories can be found in the ATB data spreadsheet. Note: the future projection of the " good resource" (i.e. for a CSP plant built in Las Vegas, Nevada) is not shown in the figures to simplify the figures and because the projection lies between the Excellent and the Fair Resource projections.

R&D Only | R&D + Market

R&D Only
The ATB representative plant characteristics that best align with those of recently installed or anticipated near-term CSP plants are associated with Tower - Excellent Resource.
R&D Only Financial Assumptions (constant background rates, no tax or tariff changes)
R&D + Market
The ATB representative plant characteristics that best align with those of recently installed or anticipated near-term CSP plants are associated with Tower - Excellent Resource.
R&D Only + Market Financial Assumptions (dynamic background rates, taxes, and tariffs)

The methodology for representing the CAPEX, O&M, and capacity factor assumptions behind each pathway is discussed in Projections Methodology. In general, the degree of adoption of technology innovation distinguishes the Constant, Mid, and Low technology cost scenarios. These projections represent trends that reduce CAPEX and improve performance. Development of these scenarios involves technology-specific application of the following general definitions:

  • Constant Technology Cost Scenario = Base Year (or near-term estimates of projects under construction) equivalent through 2050 maintains current relative technology cost differences
  • Mid Technology Cost Scenario = technology advances through continued industry growth, public and private R&D investments, and market conditions relative to current levels that may be characterized as "likely" or "not surprising"
  • Low Technology Cost Scenario = Technology advances that may occur with breakthroughs, increased public and private R&D investments, and/or other market conditions that lead to cost and performance levels that may be characterized as the " limit of surprise" but not necessarily the absolute low bound.

To estimate LCOE, assumptions about the cost of capital to finance electricity generation projects are required, and the LCOE calculations are sensitive to these financial assumptions. Three project finance structures are used within the ATB:

  • R&D Only Financial Assumptions: This sensitivity case allows technology-specific changes to debt interest rates, return on equity rates, and debt fraction to reflect effects of R&D on technological risk perception, but it holds background rates constant at 2016 values from AEO 2018 and excludes effects of tax reform, tax credits, and tariffs.
  • R&D Only + Market Financial Assumptions: This sensitivity case retains the technology-specific changes to debt interest, return on equity rates, and debt fraction from the R&D Only case and adds in the variation over time consistent with AEO 2018, as well as effects of tax reform, tax credits, and technology-specific tariffs. For a detailed discussion of these assumptions, see Changes from 2017 ATB to 2018 ATB.
  • ReEDS Financial Assumptions: ReEDS uses the R&D Only + Market Financial Assumptions for the "Mid" technology cost scenario.

A constant cost recovery period -over which the initial capital investment is recovered-is assumed for all technologies throughout this website, and can be varied in the ATB data spreadsheet.

In general, differences among the technology cost cases reflect different levels of adoption of innovations. Reductions in technology costs reflect the cost reduction opportunities that are listed below.

  • Power tower improvements
    • Better and longer-lasting selective surface coatings improve receiver efficiency and reduce O&M costs.
    • New salts allow for higher operating temperatures and lower-cost TES.
    • Development of the power cycle running at approximately 700° C and 55% gross efficiency improves cycle efficiency, reduces powerblock cost, and reduces O&M costs.
    • Lower-cost heliostats developed due to design changes and automated and high-volume manufacturing.
  • General and " soft" costs improvements
    • Expansion of world market leads to greater and more efficient supply chains, and reduction of supply chain margins (e.g., profit and overhead charged by suppliers, manufacturer, distributors, and retailers).
    • Expansion of access to a range of innovative financing approaches and business models

The LCOE range shown is based on locations with fair (Abilene, Texas), good (Las Vegas, Nevada), and excellent (Daggett, California) resources. The CAPEX is the same at each resource as the same plant is used. Future-year projections for the " good" case are not shown to simplify the figure.

Geothermal

Geothermal technology cost and performance projections will be more extensively updated upon completion of the Geothermal Vision Study. Until then, the projections are based on those documented in 2017 ATB - Geothermal, with the following changes:

  1. The dollar year was updated from 2015 to 2016 with 1.3% inflation.
  2. Technology-specific financial assumptions are included, as for other technologies in 2018 ATB, using data from Wall 2017.

Reference: Wall, A. M., Pl Dobson, H. Thomas (2017). "Geothermal Costs of Capital: Relating Market Valuation to Project Risk and Technology." Geothermal Resources Council Transactions, v. 41. https://www.geothermal-library.org/index.php?mode=pubs&action=view&record=1033704.

Natural Gas Plants

A gas-fired combustion turbine involves:

  • An air compressor compresses air and feeds it into the combustion chamber at hundreds of miles per hour.
  • In a combustion system, a ring of fuel injectors inject fuel into combustion chambers where it mixes with the air and is combusted. The resulting high-temperature, high-pressure gas stream enters and expands through the turbine.
  • A turbine has alternate stationary and rotating airfoil-section blades that are driven by expanding hot combustion gas. The rotating blades drive the compressor and spin a generator to produce electricity.

Simple-cycle gas turbines can achieve 20%-35% energy conversion efficiency depending on the type and design of the system. Aeroderivative turbines are typically more flexible but more expensive than their industrial gas turbine counterparts. Combined-cycle natural gas plants include a heat recovery steam generator that uses the hot exhaust from the combustion turbine to generate steam. That steam can then be used to generate additional electricity using a steam turbine. Combined-cycle natural gas plants typically have efficiencies ranging from 50%-60%, and R&D targets have been set to achieve even higher efficiencies. Combined-cycle plants can be built using a variety of configurations, such as a single combustion turbine and steam turbine connected to a single generator (1x1) or two combustion turbines coupled with one steam turbine (2x1) (DOE "How Gas Turbine Power Plants Work").

Renewable energy technical potential, as defined by Lopez et al. 2012, represents the achievable energy generation of a particular technology given system performance, topographic limitations, and environmental and land-use constraints. Technical resource potential corresponds most closely to fossil reserves, as both can be characterized by the prospect of commercial feasibility and depend strongly on available technology at the time of the resource assessment. Natural gas reserves in the United States are assessed by the United States Geological Survey (USGS, National Oil and Gas Assessment).

This section focuses on large, utility-scale natural gas plants. Distributed-scale turbines may be included in a future version of the ATB.

Cutaway of combustion gas turbine
Source: DOE ("How Gas Turbine Power Plants Work")

CAPital EXpenditures (CAPEX): Historical Trends, Current Estimates, and Future Projections

Because natural gas plants are well-known and perform close to their optimal performance, the EIA capital expenditures (CAPEX) projections decline at the minimum learning rate for the gas-fired technologies, resulting in incremental improvement over time that progresses slightly more quickly than inflation.

The one exception is natural gas combined cycle (CC) with carbon capture and storage (CCS). The DOE Office of Fossil Energy and the National Energy Technology Laboratory conduct research on reducing the costs and increasing the performance of CCS technology, and costs are expected to decline over time at a higher learning rate than the more mature gas-CT and gas-CC technologies.

Current estimates and future projections calculated from EIA (2017), modified as described in the CAPEX section.
R&D Only Financial Assumptions (constant background rates, no tax or tariff changes)

Comparison with Other Sources

Data sources include the ATB, B& V (2012), Newell et al. (2014), Entergy (2015), E3 (2014), IEA (2015a), ISO-NE (2016), Lazard (2016), NETL (2015), PGE (2015), PSE (2016), and Rubin et al. (2015).

Costs vary due to differences in configuration (e.g., 2x1 versus 1x1), turbine class, and methodology. All costs were converted to the same dollar year.

CAPEX Definition

Capital expenditures (CAPEX) are expenditures required to achieve commercial operation in a given year.

Overnight capital costs are modified from EIA (2017). Capital costs include overnight capital cost plus defined transmission cost, and it removes a material price index.

Fuel costs are taken from EIA (2017). EIA reports two types of gas-CT and gas-CC technologies in EIA's Annual Energy Outlook: advanced (H-class for gas-CC, F-class for gas-CT) and conventional (F-class for gas-CC, LM-6000 for gas-CT). Because we represent a single gas-CT and gas-CC technology in the ATB, the characteristics for the ATB plants are taken to be the average of the advanced and conventional systems as reported by EIA. For example, the OCC for the gas-CC technology in the ATB is the average of the capital cost of the advanced and conventional combined cycle technologies from the Annual Energy Outlook. Future work aims to improve the representation of the various natural gas technologies in the ATB. The CCS plant configuration includes only the cost of capturing and compressing the CO2. It does not include CO2 delivery and storage.

Overnight Capital Cost ($/kW)Construction Financing Factor (ConFinFactor)CAPEX ($/kW)
Gas-CT:Conventional combustion turbine $864 1.021 $882
Gas-CC:Conventional combined cycle $1,010 1.021 $1,032
Gas-CC-CCS:Combined cycle with carbon capture sequestration $2,109 1.021 $2,154

CAPEX can be determined for a plant in a specific geographic location as follows:

CAPEX = ConFinFactor × (OCC × CapRegMult + GCC)
See the Financial Definitions tab in the ATB data spreadsheet.

Regional cost variations and geographically specific grid connection costs are not included in the ATB (CapRegMult = 1; GCC = 0). In the ATB, the input value is overnight capital cost (OCC) and details to calculate interest during construction (ConFinFactor).

In the ATB, CAPEX represents each type of gas plant with a unique value. Regional cost effects associated with labor rates, material costs, and other regional effects as defined by EIA 2016a expand the range of CAPEX. Unique land-based spur line costs based on distance and transmission line costs are not estimated. The following figure illustrates the ATB representative plant relative to the range of CAPEX including regional costs across the contiguous United States. The ATB representative plants are associated with a regional multiplier of 1.0.

R&D Only Financial Assumptions (constant background rates, no tax or tariff changes)

Natural Gas Internal Combustion Engine Vehicle

Duke Energy's H.F. Lee Plant 1 (natural gas) in Goldsboro, North Carolina
Photo taken September 24, 2013. https://www.flickr.com/photos/dukeenergy/11441374433

Operations and maintenance (O&M) costs represent the annual expenditures required to operate and maintain a plant over its lifetime, including:

  • Insurance, taxes, land lease payments, and other fixed costs
  • Present value and annualized large component replacement costs over technical life
  • Scheduled and unscheduled maintenance of power plants, transformers, and other components over the technical lifetime of the plant.

Market data for comparison are limited and generally inconsistent in the range of costs covered and the length of the historical record.

Capacity Factor: Expected Annual Average Energy Production Over Lifetime

The capacity factor represents the assumed annual energy production divided by the total possible annual energy production, assuming the plant operates at rated capacity for every hour of the year. For natural gas plants, the capacity factor is typically lower (and, in the case of combustion turbines, much lower) than their availability factor. Natural gas plants have availability factors approaching 100%.

The capacity factors of dispatchable units is typically a function of the unit's marginal costs and local grid needs (e.g., need for voltage support or limits due to transmission congestion). The average capacity factor is the average fleet-wide capacity factor for these plant types in 2015. The high capacity factor is taken from EIA (2018, Table 1a) for a new power plant and represents a high bound of operation for a plant of this type.

Gas-CT power plants are less efficient than gas-CC power plants, and they tend to run as intermediate or peaker plants.

Gas-CC with CCS has not yet been built. It is expected to be a baseload unit.

Current estimates and future projections calculated from EIA (2017) and modified.

Levelized Cost of Energy (LCOE) Projections

Levelized cost of energy (LCOE) is a simple metric that combines the primary technology cost and performance parameters: CAPEX, O&M, and capacity factor. It is included in the ATB for illustrative purposes. The ATB focuses on defining the primary cost and performance parameters for use in electric sector modeling or other analysis where more sophisticated comparisons among technologies are made. The LCOE accounts for the energy component of electric system planning and operation. The LCOE uses an annual average capacity factor when spreading costs over the anticipated energy generation. This annual capacity factor ignores specific operating behavior such as ramping, start-up, and shutdown that could be relevant for more detailed evaluations of generator cost and value. Electricity generation technologies have different capabilities to provide such services. For example, wind and PV are primarily energy service providers, while the other electricity generation technologies provide capacity and flexibility services in addition to energy. These capacity and flexibility services are difficult to value and depend strongly on the system in which a new generation plant is introduced. These services are represented in electric sector models such as the ReEDS model and corresponding analysis results such as the Standard Scenarios.

The following three figures illustrate LCOE, which includes the combined impact of CAPEX, O&M, and capacity factor projections for natural gas across the range of resources present in the contiguous United States. For the purposes of the ATB, the costs associated with technology and project risk in the U.S. market are represented in the financing costs, not in the upfront capital costs (e.g. developer fees, contingencies). An individual technology may receive more favorable financing terms outside of the U.S., due to less technology and project risk, caused by more project development experience (e.g. offshore wind in Europe), or more government or market guarantees. The R&D Only LCOE sensitivity cases present the range of LCOE based on financial conditions that are held constant over time unless R&D affects them, and they reflect different levels of technology risk. This case excludes effects of tax reform, tax credits, technology-specific tariffs, and changing interest rates over time. The R&D + Market LCOE case adds to these the financial assumptions (1) the changes over time consistent with projections in the Annual Energy Outlook and (2) the effects of tax reform, tax credits, and tariffs. The ATB representative plant characteristics that best align with those of recently installed or anticipated near-term natural gas plants are associated with Gas-CC-HighCF. Data for all the resource categories can be found in the ATB data spreadsheet.

R&D Only | R&D + Market

R&D Only
The ATB representative plant characteristics that best align with those of recently installed or anticipated near-term natural gas plants are associated with Gas-CC-HighCF.
R&D Only Financial Assumptions (constant background rates, no tax or tariff changes)
R&D + Market
The ATB representative plant characteristics that best align with those of recently installed or anticipated near-term natural gas plants are associated with Gas-CC-HighCF.
R&D Only + Market Financial Assumptions (dynamic background rates, taxes, and tariffs)

The LCOE of natural gas plants is directly impacted by the price of the natural gas fuel, so we include low, median, and high natural gas price trajectories. The LCOE is also impacted by variations in the heat rate and O&M costs. Because the reference and high natural gas price projections from AEO 2017 are rising over time, the LCOE of new natural gas plants can actually increase over time if the gas prices rise faster than the capital costs decline. For a given year, the LCOE assumes that the fuel prices from that year continue throughout the lifetime of the plant.

These projections do not include any cost of carbon, which would influence the LCOE of fossil units. Also, for CCS plants, the potential revenue from selling the captured carbon is not included (e.g., enhanced oil recovery operation may purchase CO2 from a CCS plant).

Fuel prices are based on the AEO 2017 (EIA 2017).

To estimate LCOE, assumptions about the cost of capital to finance electricity generation , and the LCOE calculations are sensitive to these financial assumptions. Three project finance structures are used within the ATB:

  • R&D Only Financial Assumptions: This sensitivity case allows technology-specific changes to debt interest rates, return on equity rates, and debt fraction to reflect effects of R&D on technological risk perception, but it holds background rates constant at 2016 values from AEO 2018 and excludes effects of tax reform, tax credits, and tariffs. A constant cost recovery period-or period over which the initial capital investment is recovered-of 30 years is assumed for all technologies.
  • R&D Only + Market Financial Assumptions: This sensitivity case retains the technology-specific changes to debt interest, return on equity rates, and debt fraction from the R&D Only case and adds in the variation over time consistent with AEO 2018, as well as effects of tax reform, tax credits, and tariffs. As in the R&D Only case, a constant cost recovery period-or period over which the initial capital investment is recovered-of 30 years is assumed for all technologies. For a detailed discussion of these assumptions, see Changes from 2017 ATB to 2018 ATB.
  • ReEDS Financial Assumptions: ReEDS uses the R&D Only + Market Financial Assumptions for the "Mid" technology cost scenario.

These parameters are allowed to vary by year. The equations and variables used to estimate LCOE are defined on the equations and variables page. For illustration of the impact of changing financial structures such as WACC, see Project Finance Impact on LCOE. For LCOE estimates for the Constant, Mid, and Low technology cost scenarios for all technologies, see 2018 ATB Cost and Performance Summary.

Nuclear

Nuclear power contributed about 20% of U.S. electricity generation over the past two decades (DOE "Light Water Reactor Sustainability Program").

Nuclear power plants generate electricity in the same way as any other steam-electric power plant. Water is heated, and steam from the boiling water turns turbines and generates electricity. The main difference is that heat from a self-sustaining chain reaction boils the water in a nuclear power plant, as opposed to burning fuels in fossil fuel plants (DOE Office of Nuclear Energy "History").

TVA Watts Bar Nuclear Power Plant
Photo from Tennessee Valley Authority and
DOE ("Nuclear Reactor Technologies")
Photo by David Parsons, NREL 06705

Renewable energy technical potential, as defined by Lopez et al. 2012, represents the achievable energy generation of a particular technology given system performance, topographic limitations, and environmental and land-use constraints. Technical resource potential corresponds most closely to fossil reserves, as both can be characterized by the prospect of commercial feasibility and depend strongly on available technology at the time of the resource assessment. Uranium reserves in the United States are assessed by the United States Geological Survey (USGS, "Uranium Resources and Environmental Investigations").

CAPital EXpenditures (CAPEX): Historical Trends, Current Estimates, and Future Projections

Because nuclear plants are well-known and perform close to their optimal performance, EIA expects capital expenditures (CAPEX) will incrementally improve over time and slightly more quickly than inflation.

Current estimates and future projections calculated from EIA (2017) and modified.
R&D Only Financial Assumptions (constant background rates, no tax or tariff changes)

Comparison with Other Sources

ATB cost numbers are for a brownfield nuclear facility.
Data sources include the ATB, B& V (2012), Entergy (2015), IEA (2015), and Lazard (2016).
All sources have been normalized to the same dollar year. Costs vary due to differences in system design, methodology, and plant cost definitions.

CAPEX Definition

Capital expenditures (CAPEX) are expenditures required to achieve commercial operation in a givenyear.

Overnight capital costs are modified from EIA (2017). Capital costs include overnight capital cost plus defined transmission cost, and it removes a material price index.

Overnight Capital Cost ($/kW) Construction Financing Factor (ConFinFactor) CAPEX ($/kW)
Nuclear: Advanced nuclear power generation $5,515 1.084 $5,979

CAPEX can be determined for a plant in a specific geographic location as follows:

CAPEX = ConFinFactor × (OCC × CapRegMult + GCC)
See the Financial Definitions tab in the ATB data spreadsheet.

Regional cost variations and geographically specific grid connection costs are not included in the ATB (CapRegMult = 1; GCC = 0). In the ATB, the input value is overnight capital cost (OCC) and details to calculate interest during construction (ConFinFactor).

In the ATB, CAPEX represents each type of nuclear plant with a unique value. Regional cost effects associated with labor rates, material costs, and other regional effects as defined by EIA 2016a expand the range of CAPEX (Plant × Region). Unique land-based spur line costs based on distance and transmission line costs are not estimated. The following figure illustrates the ATB representative plant relative to the range of CAPEX including regional costs across the contiguous United States. The ATB representative plants are associated with a regional multiplier of 1.0.

R&D Only Financial Assumptions (constant background rates, no tax or tariff changes)

Natural Gas Internal Combustion Engine Vehicle

Nuclear operating crews running simulations with the Human System Simulator Laboratory research team at Idaho National Laboratory
Nuclear operating crews running simulations with the Human System Simulator Laboratory research team at Idaho National Laboratory
Photo taken November 7, 2012 https://www.flickr.com/photos/inl/9420873449/

Operations and maintenance (O&M) costs represent the annual expenditures required to operate and maintain a plant over its lifetime, including:

  • Insurance, taxes, land lease payments, and other fixed costs
  • Present value and annualized large component replacement costs over technical life
  • Scheduled and unscheduled maintenance of power plants, transformers, and other components over the technical lifetime of the plant.

Market data for comparison are limited and generally inconsistent in the range of costs covered and the length of the historical record.

Capacity Factor: Expected Annual Average Energy Production Over Lifetime

The capacity factor represents the assumed annual energy production divided by the total possible annual energy production, assuming the plant operates at rated capacity for every hour of the year. For nuclear plants, the capacity factor is typically the same as (or very close to) their availability factor.

The capacity factor of nuclear units is generally very high (> 85%) as they are typically always online except when undergoing maintenance or refueling (NEI "US Nuclear Capacity Factors").

In the United States, nuclear power plants are baseload plants with steady capacity factors. They need to change out their uranium fuel rods about every 24 months. After 18-36 months, the used fuel is removed from the reactor (World Nuclear Association "The Nuclear Fuel Cycle"). The average fueling outage duration in 2013 was 41 days; from 1990 to 1997, the refueling days ranged from 66 to 106, so improvements have helped capacity factors (NEI, "US Nuclear Refueling Outage Days"). See also NEI ("US Nuclear Power Plants: General U.S. Nuclear Info").

Current estimates and future projections calculated from EIA (2017) and modified.

Levelized Cost of Energy (LCOE) Projections

Levelized cost of energy (LCOE) is a simple metric that combines the primary technology cost and performance parameters: CAPEX, O&M, and capacity factor. It is included in the ATB for illustrative purposes. The ATB focuses on defining the primary cost and performance parameters for use in electric sector modeling or other analysis where more sophisticated comparisons among technologies are made. The LCOE accounts for the energy component of electric system planning and operation. The LCOE uses an annual average capacity factor when spreading costs over the anticipated energy generation. This annual capacity factor ignores specific operating behavior such as ramping, start-up, and shutdown that could be relevant for more detailed evaluations of generator cost and value. Electricity generation technologies have different capabilities to provide such services. For example, wind and PV are primarily energy service providers, while the other electricity generation technologies provide capacity and flexibility services in addition to energy. These capacity and flexibility services are difficult to value and depend strongly on the system in which a new generation plant is introduced. These services are represented in electric sector models such as the ReEDS model and corresponding analysis results such as the Standard Scenarios.

The following three figures illustrate LCOE, which includes the combined impact of CAPEX, O&M, and capacity factor projections for nuclear across the range of resources present in the contiguous United States. For the purposes of the ATB, the costs associated with technology and project risk in the U.S. market are represented in the financing costs, not in the upfront capital costs (e.g. developer fees, contingencies). An individual technology may receive more favorable financing terms outside of the U.S., due to less technology and project risk, caused by more project development experience (e.g. offshore wind in Europe), or more government or market guarantees. The R&D Only LCOE sensitivity cases present the range of LCOE based on financial conditions that are held constant over time unless R&D affects them, and they reflect different levels of technology risk. This case excludes effects of tax reform, tax credits, technology-specific tariffs, and changing interest rates over time. The R&D + Market LCOE case adds to these the financial assumptions (1) the changes over time consistent with projections in the Annual Energy Outlook and (2) the effects of tax reform, tax credits, and tariffs.

R&D Only | R&D + Market

R&D Only
R&D Only Financial Assumptions (constant background rates, no tax or tariff changes)
R&D + Market
R&D Only + Market Financial Assumptions (dynamic background rates, taxes, and tariffs)

The LCOE of nuclear power plants is directly impacted by the cost of uranium, variations in the heat rate, and O&M costs, but the biggest factor is the capital cost (including financing costs) of the plant. The LCOE can also be impacted by the amount of downtime from refueling or maintenance. For a given year, the LCOE assumes that the fuel prices from that year continue throughout the lifetime of the plant.

Fuel prices are based on the AEO 2017 (EIA 2017).

To estimate LCOE, assumptions about the cost of capital to finance electricity generation projects are required, and the LCOE calculations are sensitive to these financial assumptions. Three project finance structures are used within the ATB:

  • R&D Only Financial Assumptions: This sensitivity case allows technology-specific changes to debt interest rates, return on equity rates, and debt fraction to reflect effects of R&D on technological risk perception, but it holds background rates constant at 2016 values from AEO 2018 and excludes effects of tax reform, tax credits, and tariffs. A constant cost recovery period-or period over which the initial capital investment is recovered-of 30 years is assumed for all technologies.
  • R&D Only + Market Financial Assumptions: This sensitivity case retains the technology-specific changes to debt interest, return on equity rates, and debt fraction from the R&D Only case and adds in the variation over time consistent with AEO 2018, as well as effects of tax reform, tax credits, and tariffs. As in the R&D Only case, a constant cost recovery period-or period over which the initial capital investment is recovered-of 30 years is assumed for all technologies. For a detailed discussion of these assumptions, see Changes from 2017 ATB to 2018 ATB.
  • ReEDS Financial Assumptions: ReEDS uses the R&D Only + Market Financial Assumptions for the "Mid" technology cost scenario.

These parameters are allowed to vary by year. The equations and variables used to estimate LCOE are defined on the equations and variables page. For illustration of the impact of changing financial structures such as WACC, see Project Finance Impact on LCOE. For LCOE estimates for the Constant, Mid, and Low technology cost scenarios for all technologies, see 2018 ATB Cost and Performance Summary.

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