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Annual Technology Baseline 2017

National Renewable Energy Laboratory


Recommended Citation:
NREL (National Renewable Energy Laboratory). 2017. 2017 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

Land-Based Wind Power Plants

Representative Technology

Most land-based wind plants in the United States range in capacity from 50 MW to 100 MW (Wiser and Bolinger 2015). Wind turbines installed in the United States in 2015 were, on average, 2-MW turbines with rotor diameters of 102 m and hub heights of 82 m (Moné et al. 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 corresponds to over 3.5 million km2 of potential land area after accounting for standard exclusions 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 packing density of 3MW/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. Five different wind turbines are associated with a range of average annual wind speed based on actual wind plant installations in 2015. This method is described in Moné et al, (2017) and summarized below.

  • The capital expenditures (CAPEX) associated with wind plants installed in 2015 in the interior of the country are used to represent wind plants associated with average annual wind speeds that correspond with the median wind speed for projects installed in 2015. A range of CAPEX across the range of wind speeds 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.
  • The capacity factor is determined for each unique geographic location using the site-specific hourly wind profile and a power curve that corresponds with the five wind turbines defined to represent the range of wind technology installed in the United States in 2015.
  • Average annual operations and maintenance (O&M) costs are assumed equivalent at all geographic locations.
  • LCOE is calculated for each area based on the CAPEX and capacity factor estimated for each area.

For illustration in the ATB, the full resource potential, represented by 130,000 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.

Future year projections are derived from estimated cost reduction potential for land-based wind technologies based on elicitation of over 160 wind industry experts (Wiser et al. 2016). This study produced three different cost reduction pathways, and the median and low estimates for LCOE reduction are used for ATB Mid and ATB Low cost scenarios. Because the overall LCOE reduction was used as the basis for the ATB projections, all three cost elements - CAPEX, O&M, and capacity factor - should be considered together. The individual component projections are illustrative. Three different projections were developed for scenario modeling as bounding levels:

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

chart: CAPEX historical trends, current estimates, and future projections in the 2017 ATB
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.

CAPEX estimates for 2015 correspond well with market data for plants installed in 2015. Projections reflect a continuation of the downward trend observed in the recent past and are anticipated to continue based on preliminary data for 2016 projects.

In the lower wind resource areas represented by TRGs 6-10, CAPEX is likely 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 et al. 2014) is shown in box-and-whiskers format for comparison to the ATB current CAPEX estimates and future projections. Wiser and Bolinger (2014) 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 with 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 table below 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 are associated with TRG 4.

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

Projections of future LCOE were derived from a survey of wind industry experts (Wiser et al. 2016) for scenarios that are associated with 50% and 10% probability levels in 2030 and 2050. Projections of future offshore wind plant CAPEX was determined based on adjustments to CAPEX, fixed O&M (FOM), and capacity factor in each year to result in a predetermined LCOE value based on an expert survey conducted by 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 likely 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.

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

Technology innovations that could impact future CAPEX costs are summarized in LCOE Projections.

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
    • Owner's 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 (^lt;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 EIA (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.

chart: CAPEX definition for land-based wind in the 2017 ATB

Standard Scenarios Model Results

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

Operation and Maintenance (O&M) Costs

Operations and maintenance (O&M) costs represent the annual fixed expenditures (and depend on capacity) required to operate and maintain a wind plant over its technical lifetime of 25 years (the distinction between economic life and technical life is described here), including:

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

chart: base year estimate and future year projections for fixed O&M costs for land-based wind in the 2017 ATB

Base Year Estimates

Due to a lack of 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).

Future Year Projections

Future FOM is assumed to decline 25% by 2050 in Mid cost case and 39% in Low cost wind cases. 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. 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 technical lifetime of the plant (the distinction between economic life and technical life is described here). 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 wind profile, 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 High, Mid, and Low cost scenarios.

chart: capacity factor (annual average energy production over plant lifetime) for land-based onshore in the 2017 ATB
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 specified by 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 (Wiser et al. 2014) 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 2015, shown by year of commercial online date. As reported in the 2015 DOE Wind Technologies Market Report (Wiser and Bolinger 2016), NextEra Energy Resources, in their quarterly earnings reports, estimates that the "wind resource index" for the United States as a whole was 94% in 2015. The generation-weighted average 2015 capacity factors are also shown adjusted upward for a typical wind resource year by 1/0.94.

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.

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

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 well as very low wind resource sites associated with TRGs 8-10 are not as common in the historical 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 from AWS 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. 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 LCOE value.

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

Technology innovations that could impact future capacity factors are summarized in LCOE Projections.

Standard Scenarios Model Results

ATB CAPEX, O&M, and capacity factor assumptions for Base Year and future projections through 2050 for High, Mid, and Low projections 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 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 projections were adapted from the expert survey results for scenario modeling as bounding levels:

  • High Cost: no change in CAPEX, O&M, or capacity factor from 2015 to 2050, consistent across all renewable energy technologies in ATB.
  • Mid cost: LCOE percent reduction from the Base Year equivalent to that corresponding to the Median Scenario (50% probability) in the expert survey (Wiser et al. 2016)
  • Low cost: LCOE percent 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 percent reductions 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 percent 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 35% and for the Low cost scenario is 53%.

A broad sample of cost of wind energy projections are shown to provide context for the ATB High, Mid, and Low cost projections. The ATB Mid cost projection, which corresponds to the Median scenario from the expert survey, results in LCOE reductions that are lower than median scenarios in the literature. The ATB Low cost projection, which corresponds to the Low scenario from the expert survey, is similar to the lower bound of the sample of literature projections.

chart: plant cost and performance projections methodology for land-based wind in the 2017 ATB

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 focus of the ATB is to define the primary cost and performance parameters for use in electric sector modeling or other analysis where more sophisticated comparisons among technologies are made. LCOE captures the energy component of electric system planning and operation, but the electric system also requires capacity and flexibility services to operate reliably. 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 the combined impact of CAPEX, O&M, and capacity factor projections across the range of resources present in the contiguous United States. The Current Market Conditions LCOE demonstrates the range of LCOE based on macroeconomic conditions similar to the present. The Historical Market Conditions LCOE presents the range of LCOE based on macroeconomic conditions consistent with prior ATB editions and Standard Scenarios model results. The Normalized LCOE (all LCOE estimates are normalized with the lowest Base Year LCOE value) emphasizes the effect of resource quality and the relative differences in the three future pathways independent of project finance assumptions. The ATB representative plant characteristics that best align with 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.

Current Market Conditions
Historical Market Conditions
Normalized
The ATB representative plant characteristics that best align with recently installed or anticipated near-term land-based wind plants are associated with TRG 4.

The methodology for representing the CAPEX, O&M, and capacity factor assumptions behind each pathway is discussed in Projections Methodology. The three pathways are generally defined as:

  • High = Base Year (or near-term estimates of projects under construction) equivalent through 2050 maintains current relative technology cost differences
  • Mid = 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 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. For comparison in the ATB, two project finance structures are represented.

  • Current Market Conditions: The values of the production tax credit (PTC) and investment tax credit (ITC) are ramping down by 2020, at which time wind and solar projects may be financed with debt fractions similar to other technologies. This scenario reflects debt interest (4.4% nominal, 1.9% real) and return on equity rates (9.5% nominal, 6.8% real) to represent 2017 market conditions (AEO 2017) and a debt fraction of 60% for all electricity generation technologies. An economic life, or period over which the initial capital investment is recovered, of 20 years is assumed for all technologies. These assumptions are one of the project finance options in the ATB spreadsheet.
  • Long-Term Historical Market Conditions: Historically, debt interest and return on equity were represented with higher values. This scenario reflects debt interest (8% nominal, 5.4% real) and return on equity rates (13% nominal, 10.2% real) implemented in the ReEDS model and reflected in prior versions of the ATB and Standard Scenarios model results. A debt fraction of 60% for all electricity generation technologies is assumed. An economic life, or period over which the initial capital investment is recovered, of 20 years is assumed for all technologies. These assumptions are one of the project finance options in the ATB spreadsheet.

These parameters are held constant for estimates representing the Base Year through 2050. No incentives such as the PTC or ITC are included. 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 and economic life, see Project Finance Impact on LCOE. For LCOE estimates for High, Mid, and Low scenarios for all technologies, see 2017 ATB Cost and Performance Summary.

In general, the degree of adoption of a range of technology innovations distinguishes the High, Mid and Low cost cases. These projections represent the following trends to reduce CAPEX and FOM, and increase O&M.

  • 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 diversity 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
  • 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.

Commercial PV

Representative Technology

For the ATB, commercial PV systems are modeled for a 300-kWDC fixed-tilt (5°), roof-mounted system. Flat-plate PV can take advantage of direct and indirect insolation, so PV modules need not directly face and track incident radiation. This gives PV systems a broad geographical application, especially for commercial PV systems.

Resource Potential

Solar resources across the United States are mostly good to excellent at about 1,000–2,500 kWh)/m2/year. The Southwest is at the top of this range, while only Alaska and part of Washington are at the low end. The range for the contiguous United States is about 1,350–2,500 kWh/m2/year. Nationwide, solar resource levels vary by about a factor of two.

Distributed-scale PV is assumed to be configured as a fixed-axis, roof-mounted system. Compared to utility-scale PV, this reduces both the potential capacity factor and amount of land (roof space) that is available for development. A recent study of rooftop PV technical potential (Gagnon et al. 2016) estimated that as much as 731 GW (926 TWh/yr) of potential exists for small buildings (< 5,000 m2 footprint) and 386 GW (506 TWh/yr) for medium (5,000–25,000 m2) and large buildings (>25,000 m2).

map: mean U.S. solar resource available to PV systems
Map of the mean solar resource available to PV 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 et al. 2012; NREL, "Renewable Energy Technical Potential").

Base Year and Projections Overview

The Base Year estimates rely on modeled CAPEX and O&M estimates benchmarked with industry and historical data. Capacity factor is estimated based on hours of sunlight at latitude for all geographic locations in the United States. Capacity factor is estimated based on hours of sunlight at latitude for three representative geographic locations in the United States.

Future year projections are derived from analysis of published projections of PV CAPEX and bottom-up engineering analysis of O&M costs. Three different projections were developed for scenario modeling as bounding levels:

  • High cost: no change in CAPEX, O&M, or capacity factor from 2016 to 2050; consistent across all renewable energy technologies in the ATB
  • Mid cost: based on the median of literature projections of future CAPEX; O&M technology pathway analysis
  • Low cost: based on low bound of literature projections of future CAPEX; O&M technology pathway analysis.

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 hardware, 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 or materials. 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 reduction scenarios are represented: High, Mid, and Low. Historical data from commercial PV 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.

chart: CAPEX historical trends, current estimates, and future projections for commercial-scale PV in the 2017 ATB
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.
CAPEX is shown as a single value because it does not vary with solar resource.

Recent Trends

Reported historical commercial-scale PV installation CAPEX (Barbose and Dargouth 2016) is shown in box-and-whiskers format for comparison to the ATB current CAPEX estimates and future projections. The data in Barbose and Dargouth (2016) represent 85% of all U.S. residential and commercial PV capacity installed through 2015 and 82% of capacity installed in 2015.

PV pricing and capacities are quoted in kWDC (i.e., module rated capacity) unlike other generation technologies, which are quoted in kWAC. For PV, this would correspond to the combined rated capacity of all inverters. This is done because kWDC is the unit that the majority of the PV industry uses. Although costs are reported in kWDC, the total CAPEX includes the cost of the inverter, which has a capacity measured in kWAC.

CAPEX estimates for 2015 reflect continued rapid decline in pricing supported by analysis of recent system pricing for projects that became operational in 2015 (Feldman et al. 2016).

The range in CAPEX estimates reflects the heterogeneous composition of the commercial PV market in the United States.

Base Year Estimates

For illustration in the ATB, a representative commercial-scale PV installation is shown. Although the PV technologies vary, typical installation costs are represented with a single estimate because the CAPEX does not vary with solar resource.

Although the technology market share may shift over time with new developments, the typical installation cost is represented with the projections above.

A system price of $2.47/WDC in 2015 represents the median reported price of a utility-scale PV system installed in 2015 reported in Tracking the Sun IX (Barbose and Dargouth 2016) and adjusted to remove regional cost multipliers based on geographic location of projects installed in 2015. The $2.18/WDC in 2016 is based on bottom-up benchmark analysis reported in U.S. Solar Photovoltaic System Cost Benchmark Q1 2016 (adjusted for inflation) (Fu et al. 2016). These figures are in line with other estimated system prices reported in Feldman et al. (2016).

The Base Year CAPEX estimates should tend toward the low end of observed cost because no regional impacts are included. These effects are represented in the historical market data.

Future Year Projections

Projections of future commercial PV installation CAPEX are based on 10 system price projections from 5 separate institutions. We adjusted the "min," "median," and "max" analyst forecasts in a few different ways. All 2015 pricing is based on the 20th percentile, median, and 80th percentile historically reported commercial PV prices reported in Tracking the Sun IX (Barbose and Dargouth 2016). All 2016 pricing is based on the bottom-up benchmark analysis reported in U.S. Solar Photovoltaic System Cost Benchmark Q1 2016 (adjusted for inflation) (Fu et al. 2016). These figures are in line with other estimated system prices reported in Feldman et al. (2016).

We adjusted the Mid and Low projections for 2017–2050 to remove distortions caused by the combination of forecasts with different time horizons and based on internal judgment of price trends. The high projection case is kept constant at the 2016 CAPEX value, assuming no improvements beyond 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.

CAPEX Definition

Capital expenditures (CAPEX) are expenditures required to achieve commercial operation in a given year. For commercial PV, this is modeled for a host-owned business model only with access to debt.

For the ATB - and based on EIA (2016a) and the NREL Solar PV Cost Model (Fu et al. 2016) - the distributed solar PV plant envelope is defined to include:

  • Hardware
    • Module supply
    • Power electronics
    • Racking
    • Foundation
    • AC and DC materials and installation
  • Balance of system (BOS)
    • Site and/or roof preparation
    • Permitting, inspection, and interconnection costs
    • 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
    • Owner's costs, such as development costs, legal fees, insurance costs.
    • Depreciation and interest on debt (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 are not included in the ATB (CapRegMult = 1). Because distributed PV plants are located directly at the end use, there are no grid connection costs (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 distributed residential/commercial PV plant 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 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.

chart: CAPEX definition for commercial-scale PV in the 2017 ATB

Standard Scenarios Model Results

ATB CAPEX, O&M, and capacity factor assumptions for the Base Year and future projections through 2050 for High, Mid, and Low projections 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 dGen does include state-level cost multipliers (EIA 2016a).

Operation and Maintenance (O&M) Costs

Operations and maintenance (O&M) costs represent the annual expenditures required to operate and maintain a solar PV plant over its technical lifetime of 30 years (the distinction between economic life and technical life is described here), including:

  • Insurance, property taxes, site security, legal and administrative fees, and other fixed costs
  • Present value, annualized large component replacement costs over technical life (e.g., inverters at 15 years)
  • Scheduled and unscheduled maintenance of solar PV plants, transformers, etc. over the technical lifetime of the plant (e.g., general maintenance, including cleaning and vegetation removal).

The following figure shows the Base Year estimate and future year projections for fixed O&M (FOM) costs. Three cost reduction 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.

chart: base year estimate and future year projections for fixed O&M costs for commercial-scale PV in the 2017 ATB

Base Year Estimates

FOM is assumed to be $18/kWDC-yr based on Woodhouse et al. (2016). This number is reasonably consistent with the 2013 "empirical O&M costs" reported in Bolinger and Weaver (2014), which indicates O&M costs ranging from $15/kWAC/yr to $25/kWAC/yr for fixed-tilt PV systems (this range would be lower if reported in $kWDC/yr). A wide range in reported prices exists in the market, in part depending on what maintenance practices exist for a particular system. These cost categories include asset management (including compliance and reporting for incentive payments), different insurance products, site security, cleaning, vegetation removal, and failure of components. Not all these practices are performed for each system; additionally, some factors are dependent on the quality of the parts and construction. NREL analysts estimate O&M costs can range between $0 and $40/kWDC-yr.

Future Year Projections

Future FOM is assumed to decline to $7.5/kWDC-yr by 2020 in the Low cost case and by 2025 in the Mid cost case.

There is currently great market variation in what individual companies perform for O&M.

A detailed description of the methodology for developing Future Year Projections is found in Projections Methodology.

Technology innovations that could impact future CAPEX 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 technical lifetime of the plant (the distinction between economic life and technical life is described here). 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.

PV system capacity is not directly comparable to other technologies' capacity factors. Other technologies' capacity factors are represented in exclusively AC units (see Solar PV AC-DC Translation). However, because PV pricing in this ATB documentation is represented in $/WDC, PV system capacity is a DC rating. Because each technology uses consistent capacity ratings, the LCOEs are comparable.

The capacity factor is influenced by the hourly solar profile, technology (e.g., thin-film versus crystalline silicon), axis type (e.g., none, one, or two), expected downtime, and inverter losses to transform from DC to AC power. The DC-AC ratio is a design choice that influences the capacity factor. For the ATB, commercial PV systems are modeled for a 300-kWDC fixed-tilt (5°), roof-mounted system. PV plant capacity factor incorporates an assumed degradation rate of 0.5%/year (Jordan and Kurtz 2013) in the annual average calculation.

The following figure shows a range of capacity factors based on variation in the solar resource in the contiguous United States. The range of the Base Year estimates illustrate the effect of locating a residential PV plant in locations with solar irradiance similar to Seattle, Washington, Kansas City, Missouri, or Daggett, California (estimated first-year operation capacity factors of 11.4%, 14.5%, and 18.7% respectively). Future projections for High, Mid, and Low cost scenarios are unchanged from the Base Year. Technology improvements are focused on CAPEX and O&M cost elements.

chart: capacity factor (annual average energy production over plant lifetime) for commercial-scale solar PV in the ATB
The legend labels refer to the first-year operation capacity factors. The data illustrated modifies the first-year capacity factor by including estimated degradation over the economic life of a PV plant.

Base Year Estimates

For illustration in the ATB, a range of capacity factors is associated with solar irradiance diversity and the range of latitude for three resource locations in the contiguous United States:

  • Low: Seattle, Washington
  • Mid: Kansas City, Missouri
  • High: Daggett, California

First-year operation capacity factors as modeled range from 11.4% to 18.7%, though these depend significantly on geography and system configuration (e.g., fixed-tilt versus single-axis tracking).

Over time, PV installation output is reduced due to degradation in module quality. This degradation is accounted in ATB estimates of capacity factor over the 20-year economic life of the plant (the distinction between economic life and technical life is described here). The adjusted average capacity factor values in the ATB are 11%, 14%, and 18%.

Future Year Projections

Projections of capacity factor for installations installed in future years are unchanged from the Base Year. Solar PV installations have very little downtime, inverter efficiency is already optimized, and improvements in panel density are expected to result in smaller footprints or lower CAPEX, not necessarily increased capacity factor. That said, there is potential for future increases in capacity factor through technological improvements such as less panel reflectivity, lower degradations rates and improved performance in low-light conditions.

Standard Scenarios Model Results

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

dGen does not endogenously consider curtailment from surplus renewable energy generation, though this is a feature of the linked ReEDS-dGen model (Cole et al. 2016), where balancing area-level marginal curtailments can be applied to DPV generation as determined by scenario constraints.

Plant Cost and Performance Projections Methodology

Currently, CAPEX - not LCOE - is the most common metric for PV cost. Due to differing assumptions in long-term incentives, system location and production characteristics, and cost of capital, LCOE can be confusing and often incomparable between differing estimates. While CAPEX also has many assumptions and interpretations, it involves fewer variables to manage. Therefore, PV projections in the ATB are driven entirely by plant and operational cost improvements.

We created High, Mid and Low CAPEX cases to explore the range of possible outcomes of future PV cost improvements. The High cost case represents no CAPEX improvements made beyond today, the Mid cost case represents current expectations of price reductions in a "business-as-usual" scenario, and the Low cost case represents current expectations of potential cost reductions given improved R&D funding and more aggressive global deployment targets.

While CAPEX is one of the drivers to lower costs, R&D efforts continue to focus on other areas to lower the cost of energy from residential PV. While these are not incorporated in the ATB, they include: longer system lifetime, improved performance and reliability, and lower cost of capital.

Projections of future commercial PV installation CAPEX are based on 10 system price projections from 5 separate institutions. Projections included short-term U.S. price forecasts made in the past six months and long-term global and U.S. price forecasts made in the past primarily provided by market analysis firms with expertise in the PV industry, through a subscription service with NREL. The long-term forecasts primarily represent the collection of publicly available, unique forecasts with either a long-term perspective of solar trends or through capacity expansion models with assumed learning by doing.

In instances in which literature projections did not include all years, a straight-line change in price was assumed between any two projected values. To generate a High, Mid, and Low cost forecast we took the "min," "median," and "max" of the data sets; however, we only included short-term U.S. forecasts until 2030 as they focus on near-term pricing trends within the industry. Starting in 2030, we include long-term global and U.S. forecasts in the data set, as they focus more on long-term trends within the industry. It is also assumed after 2025 U.S. prices will be on par with global averages; the U.S. federal tax credit for solar assets reverts down to 10% for all projects placed in service after 2023, which has the potential to lower upfront financing costs and remove any distortions in reported pricing, compared to other global markets. Additionally, a larger portion of the United States will have a more mature PV market, which should result in a narrower price range. Changes in price for the High, Mid, and Low cost forecast between 2020 and 2030 are interpolated on a straight-line basis.

We adjusted the "min," "median," and "max" analyst forecasts in a few different ways. All 2015 pricing is based on the 20th percentile, median, and 80th percentile historically reported commercial PV price reported in Tracking the Sun IX (Barbose and Dargouth 2016). All 2016 pricing is based on the bottom-up benchmark analysis reported in U.S. Solar Photovoltaic System Cost Benchmark Q1 2016 (adjusted for inflation) (Fu et al. 2016). These figures are in line with other estimated system prices reported in Feldman et al. (2016).

We adjusted the Mid and Low cost projections for 2017-2050 to remove distortions caused by the combination of forecasts with different time horizons and based on internal judgment of price trends. The High cost projection case is kept constant at the 2016 CAPEX value, assuming no improvements beyond 2016.

chart: system prices, 2015-2050, for commercial-scale solar PV in the ATB
chart: system prices, 2015-2050, for commercial-scale solar PV in the ATB
All prices quoted in euros are converted to USD (1€ = $1.25).
All prices quoted in WAC are converted to WDC (1 WAC=1.2 WDC).

Future FOM is assumed to decline to $7.5/kWDC-yr by 2020 in the Low case and by 2025 in the Mid case through improvements in system operation and more durable, better performing capital equipment (Woodhouse et al. 2016).

Capacity factors are assumed to not increase over time. All PV system efficiency improvements are assumed to result in capital cost reductions rather than capacity factor improvements.

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 focus of the ATB is to define the primary cost and performance parameters for use in electric sector modeling or other analysis where more sophisticated comparisons among technologies are made. LCOE captures the energy component of electric system planning and operation, but the electric system also requires capacity and flexibility services to operate reliably. 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 the combined impact of CAPEX, O&M, and capacity factor projections across the range of resources present in the contiguous United States. The Current Market Conditions LCOE demonstrates the range of LCOE based on macroeconomic conditions similar to the present. The Historical Market Conditions LCOE presents the range of LCOE based on macroeconomic conditions consistent with prior ATB editions and Standard Scenarios model results. The Normalized LCOE (all LCOE estimates are normalized with the lowest Base Year LCOE value) emphasizes the effect of resource quality and the relative differences in the three future pathways independent of project finance assumptions. The ATB representative plant characteristics that best align with recently installed or anticipated near-term commercial PV plants are associated with Comm PV: 14.5%. Data for all the resource categories can be found in the ATB data spreadsheet.

Current Market Conditions
Historical Market Conditions
Normalized
The ATB representative plant characteristics that best align with recently installed or anticipated near-term commercial PV plants are associated with Comm PV: CF 14.5%.

The methodology for representing the CAPEX, O&M, and capacity factor assumptions behind each pathway is discussed in Projections Methodology. The three pathways are generally defined as:

  • High = Base Year (or near-term estimates of projects under construction) equivalent through 2050 maintains current relative technology cost differences
  • Mid = 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 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. For comparison in the ATB, two project finance structures are represented.

  • Current Market Conditions: The values of the production tax credit (PTC) and investment tax credit (ITC) are ramping down by 2020, at which time wind and solar projects may be financed with debt fractions similar to other technologies. This scenario reflects debt interest (4.4% nominal, 1.9% real) and return on equity rates (9.5% nominal, 6.8% real) to represent 2017 market conditions (AEO 2017) and a debt fraction of 60% for all electricity generation technologies. An economic life, or period over which the initial capital investment is recovered, of 20 years is assumed for all technologies. These assumptions are one of the project finance options in the ATB spreadsheet.
  • Long-Term Historical Market Conditions: Historically, debt interest and return on equity were represented with higher values. This scenario reflects debt interest (8% nominal, 5.4% real) and return on equity rates (13% nominal, 10.2% real) implemented in the ReEDS model and reflected in prior versions of the ATB and Standard Scenarios model results. A debt fraction of 60% for all electricity generation technologies is assumed. An economic life, or period over which the initial capital investment is recovered, of 20 years is assumed for all technologies. These assumptions are one of the project finance options in the ATB spreadsheet.

These parameters are held constant for estimates representing the Base Year through 2050. No incentives such as the PTC or ITC are included. 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 and economic life, see Project Finance Impact on LCOE. For LCOE estimates for High, Mid, and Low scenarios for all technologies, see 2017 ATB Cost and Performance Summary.

The LCOE for commercial PV systems is calculated using the same financing parameters as the utility systems. Although we recognize that commercial systems have a wide range of financing options available to them, we represent LCOEs using these utility-based financing calculations in order to allow better comparison against the utility system LCOEs.

In general, the degree of adoption of a range of technology innovations distinguishes the High, Mid and Low cost cases. These projections represent the following trends to reduce CAPEX and FOM.

  • Modules
    • Increased module efficiencies and increased production-line throughput to decrease CAPEX; overhead costs on a per-kilowatt will go down if efficiency and throughput improvement are realized.
    • Reduced wafer thickness or the thickness of thin-film semiconductor layers
    • Development of new semiconductor materials
    • Development of larger manufacturing facilities in low-cost regions
  • Balance of system (BOS)
    • Increased module efficiency, reducing the size of the installation
    • Development of racking systems that enhance energy production or require less robust engineering
    • Integration of racking or mounting components in modules
    • Reduction of supply chain complexity and cost
      • Creation of standard packages system design
      • Improvement of supply chains for BOS components in modules
    • Improved power electronics
      • Improvement of inverter prices and performance, possibly by integrating micro-inverters
    • Decreased installation costs and margins
      • Reduction of supply chain margins (e.g., profit and overhead charged by suppliers, manufacturer, distributors, and retailers); this will likely occur naturally as the U.S. PV industry grows and matures.
      • Streamlining of installation practices through improved workforce development and training, and developing standardized PV hardware
      • Expansion of access to a range of innovative financing approaches and business models
      • Development of best practices for permitting interconnection, and PV installation such as subdivision regulations, new construction guidelines, and design requirements.

FOM cost reduction represents optimized O&M strategies, reduced component replacement costs, and lower frequency of component replacement.

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. In the ATB, CSP plants with 10 hours of TES are illustrated.

The first large molten-salt power tower plant (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 ).

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 is some of the best in the world and ranges from 2,000 to 2,800 kWh/m2/year. The solar resource for the Southwest was found in Ballaben, Poliafico, and Hashem (2015). The raw resource technical potential of seven western states (Arizona, California, Colorado, Nevada, New Mexico, Utah, and Texas) exceeds 11,000 GW (almost tenfold current total U.S. electricity generation capacity), assuming 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 et 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, 15 of the 17 currently operational CSP plants in the United States use parabolic trough technology. And, two power tower facilities - Ivanpah (392 MW) and Crescent Dunes (110 MW), are operational. One small 5-MW linear Fresnel plant is non-operational in California (NREL's Concentrating Solar Power Projects). This 5-MW solar-enhanced oil recovery site was a development site.

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 are determined using manufacturing cost models and are benchmarked with industry data. The 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 by industry input.
  • Capacity factor varies with inclusion of thermal energy storage and solar irradiance. The listed projects assume power towers with 10 hours of thermal energy storage.
    • 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 megawatts electrical (MWe).

The Base Year estimates are made for 2015 (via an updated index of the ATB 2016) and for 2018, which has utilized a recent assessment of the industry and has expected project completion in 2018.

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

  • High cost: no change in CAPEX, O&M, or capacity factor from 2018 to 2050; consistent across all renewable energy technologies in the ATB
  • Mid cost: CAPEX reduced by 25% by 2030 and based on median of literature projections of future CAPEX to 2050; O&M technology pathway analysis.
  • Low cost: technology pathway analysis demonstrating feasibility of achieving SunShot targets by 2030 through reductions to CAPEX and O&M.

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, 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 or materials. 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 reduction scenarios are represented: High, Mid, and Low. The estimate for a given year represents CAPEX of a new plant that reaches commercial operation in that year.

chart: CAPEX historical trends, current estimates, and future projections for solar CSP in the 2017 ATB

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 lowers LCOE for power towers.

The CAPEX estimate (2015) is approximately $8,130/kW. 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 2018, the CAPEX estimate is $7,037/kW.

Future Year Projections

Three cost projections are developed for CSP technologies:

  • High cost: no change in CAPEX, O&M, or capacity factor from 2018 to 2050; consistent across all renewable energy technologies in the ATB
  • Mid cost: CAPEX reduced by 25% by 2030 and based on median of literature projections of future CAPEX to 2050; O&M technology pathway analysis
  • Low cost: technology pathway analysis demonstrating feasibility of achieving SunShot targets by 2030 through reductions to CAPEX and O&M.

Detailed description of the methodology for developing Future Year Projections is found in Projections Methodology.

Technology innovations that could impact future CAPEX 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 EIA (2016a), Turchi (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, cooling system)
    • Thermal energy storage system
    • Installation
  • Balance of system, including installation, land acquisition, electrical infrastructure and project indirect costs
    • Land acquisition, site preparation, 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
    • Owner's 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 an 8% 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.

chart: CAPEX definition for soalr CSP in the 2017 ATB

Standard Scenarios Model Results

ATB CAPEX, O&M, and capacity factor assumptions for the Base Year and future projections through 2050 for High, Mid, and Low projections 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.

Operation and Maintenance (O&M) Costs

Operations and maintenance (O&M) costs represent the annual expenditures required to operate and maintain a solar CSP plant over its technical lifetime of 30 years (the distinction between economic life and technical life is described here), including:

  • Operating and administrative labor, insurance, legal and administrative fees, and other fixed costs
  • Utilities (water, power, 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 reduction 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.

chart: base year estimate and future year projections for fixed O&M costs for solar CSPin the 2017 ATB

Base Year Estimates

FOM is assumed to be $66/kW-yr. Variable O&M is approximately $4/MWh until 2018 and $3.50/MWh after (Kurup and Turchi 2015).

Future Year Projections

Future FOM is assumed to decline to the SunShot target of $50/kW-yr by 2030 in the Mid cost case and $40/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 technical lifetime of the plant (the distinction between economic life and technical life is described here). 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 High, Mid, and Low cost scenarios are unchanged from the Base Year. Technology improvements are focused on CAPEX and O&M cost elements.

chart: capacity factor (annual average energy production over plant lifetime) for geothermal in the 2017 ATB

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:

  • 2015: 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
  • 2018: 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: SunShot targets are met; 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 slightly down-rated from SAM 2015 projections.

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 High, Mid, and Low projections 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.

chart: ATB cost projections for solar CSP compared with published literaturein the 2017 ATB

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.

Attempts have been made to clarify the specifics of the other published CSP projections (e.g., number of hours of storage and solar multiple). As yet, this has not been possible in detail for the ATB 2017.

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

  • High
    • 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 2015
    • Costs stay the same from the 2018 estimate through 2050, consistent with ATB renewable energy technologies
  • Mid
    • Based on published projections that highlight an overall CSP CAPEX reduction by 25% by 2030 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 depicted for 2018 based on current state of industry
    • CAPEX and O&M both drop by 25% by 2030
  • Low
    • Significant reductions in heliostat and power system cost due to greater deployment volume and R&D depicted for 2018; 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. 2016)
    • Learning rate applied: 9.9% for the solar field and 12% for the turbine based on global projected CSP deployment are applied after 2030
    • SunShot CAPEX and O&M targets are met in 2030, including new, high-efficiency power cycles and low-cost heliostats.

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 focus of the ATB is to define the primary cost and performance parameters for use in electric sector modeling or other analysis where more sophisticated comparisons among technologies are made. LCOE captures the energy component of electric system planning and operation, but the electric system also requires capacity and flexibility services to operate reliably. 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 the combined impact of CAPEX, O&M, and capacity factor projections across the range of resources present in the contiguous United States. The Current Market Conditions LCOE demonstrates the range of LCOE based on macroeconomic conditions similar to the present. The Historical Market Conditions LCOE presents the range of LCOE based on macroeconomic conditions consistent with prior ATB editions and Standard Scenarios model results. The Normalized LCOE (all LCOE estimates are normalized with the lowest Base Year LCOE value) emphasizes the effect of resource quality and the relative differences in the three future pathways independent of project finance assumptions. The ATB representative plant characteristics that best align with 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.

Current Market Conditions
Historical Market Conditions
Normalized
The ATB representative plant characteristics that best align with recently installed or anticipated near-term CSP plants are associated with Tower - Excellent Resource.

The methodology for representing the CAPEX, O&M, and capacity factor assumptions behind each pathway is discussed in Projections Methodology. The three pathways are generally defined as:

  • High = Base Year (or near-term estimates of projects under construction) equivalent through 2050 maintains current relative technology cost differences
  • Mid = 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 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. For comparison in the ATB, two project finance structures are represented.

  • Current Market Conditions: The values of the production tax credit (PTC) and investment tax credit (ITC) are ramping down by 2020, at which time wind and solar projects may be financed with debt fractions similar to other technologies. This scenario reflects debt interest (4.4% nominal, 1.9% real) and return on equity rates (9.5% nominal, 6.8% real) to represent 2017 market conditions (AEO 2017) and a debt fraction of 60% for all electricity generation technologies. An economic life, or period over which the initial capital investment is recovered, of 20 years is assumed for all technologies. These assumptions are one of the project finance options in the ATB spreadsheet.
  • Long-Term Historical Market Conditions: Historically, debt interest and return on equity were represented with higher values. This scenario reflects debt interest (8% nominal, 5.4% real) and return on equity rates (13% nominal, 10.2% real) implemented in the ReEDS model and reflected in prior versions of the ATB and Standard Scenarios model results. A debt fraction of 60% for all electricity generation technologies is assumed. An economic life, or period over which the initial capital investment is recovered, of 20 years is assumed for all technologies. These assumptions are one of the project finance options in the ATB spreadsheet.

These parameters are held constant for estimates representing the Base Year through 2050. No incentives such as the PTC or ITC are included. 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 and economic life, see Project Finance Impact on LCOE. For LCOE estimates for High, Mid, and Low scenarios for all technologies, see 2017 ATB Cost and Performance Summary.

In general, the degree of adoption of a range of technology innovations distinguishes the High, Mid and Low cost cases. These projections represent the following trends to reduce CAPEX and FOM, and increase O&M.

  • 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 700°C and 55% gross efficiency improves cycle efficiency, reduces powerblock cost, and reduces O&M costs
    • Lower-cost heliostats developed due to more efficient designs and automated and high-volume manufacturing
  • General and "soft" costs improvements
    • Expansion of world market leads to greater and more efficient supply chains; 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
    • Development of best practices for permitting interconnection and installation such as subdivision regulations, new construction guidelines, and design requirements.

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.

Hydropower

Note: Pumped-storage hydropower is considered a storage technology in the ATB and will be addressed in future years. It and other storage technologies are represented in Standard Scenarios Model Results from the ReEDS model.

Upgrades to Existing Facilities

Representative Technology

Hydropower technologies have produced electricity in the United States for over a century. Many of these infrastructure investments have potential to continue providing electricity in the future through upgrades of existing facilities (DOE 2016). At individual facilities, investments can be made to improve the efficiency of existing generating units through overhauls, generator rewinds, or turbine replacements. Such investments are known collectively as "upgrades," and they are reflected as increases to plant capacity. As plants reach a license renewal period, upgrades to existing facilities to increase capacity or energy output are typically considered. While the smallest projects in the United States can be as small as 10-100 kW, the bulk of upgrade potential is from large, multi-megawatt facilities.

Resource Potential

The estimated total upgrade potential of 6.9 GW/24 TWh (at about 1,800 facilities) is based on generalizable information drawn from a series of case studies or owner-specific assessments (DOE 2016). Information available to inform the representation of improvements to the existing fleet includes:.

  • A systematic, full-fleet assessment of expansion potential at Reclamation projects performed under the Reclamation Hydropower Modernization Initiative (see U.S. Bureau of Reclamation, "Hydropower Resource Assessment at Existing Reclamation Facilities")
  • Case study reports from the U.S. Army Corps of Engineers (Corps) performed under its Hydropower Modernization Initiative (Montgomery, Watson, and Harza 2009)
  • Case study reports combining assessments of upgrade and unit and plant optimization potential from the U.S. Department of Energy/Oak Ridge National Laboratory Hydropower Advancement Project.
map of total upgrade potential for hydropower facilities in the United States
Map of the hydropower resource 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 et al. 2012; NREL, "Renewable Energy Technical Potential").

Base Year and Future Year Projections Overview

Upgrades are often among the lowest-cost new capacity resource, with the modeled costs for individual projects ranging from $800/kW to nearly $20,000/kW. This differential results from significant economies of scale from project size, wherein larger capacity plants are less expensive to upgrade on a dollar-per-kilowatt basis than smaller projects are. The average cost of the upgrade resource is approximately $1,500/kW.

CAPEX for each existing facility is based on direct estimates (DOI 2010) where available. Costs at non-reclamation plants were developed using Hall et al. (2003).

Cost= (277 × ExpansionMW-0.3) + (2230 × ExpansionMW-0.19)

The capacity factor is based on actual 10-year average energy production reported in EIA 923 forms. Some hydropower facilities lack flexibility and only produce electricity when river flows are adequate. Others with storage capabilities are operated to meet a balance between electric system, reservoir management, and environmental needs using their dispatch capability.

No future cost and performance projections for hydropower upgrades are assumed.

Upgrade cost and performance are not illustrated in this documentation of the ATB for the sake of simplicity.

Standard Scenarios Model Results

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

The ReEDS model times upgrade potential availability with the relicensing date, plant age (50 years), or both.

Powering Non-Powered Dams

report cover: An Assessment of Energy Potential at Non-Powered Dams in the United States

An Assessment of Energy Potential at Non-Powered Dams in the United States

Representative Technology

Non-powered dams (NPD) are classified by energy potential in terms of head. Low-head facilities have design heads below 20 m and typically exhibit the following characteristics (DOE 2016):

  • 1MW to 10 MW
  • New/rehabilitated intake structure
  • Little, if any, new penstock
  • Axial-flow or Kaplan turbines (2-4 units)
  • New powerhouse (indoor)
  • New/rehabilitated tailrace
  • Minimal new transmission (<5 miles, if required)
  • Capacity factor of 35% to 60%.

High-head facilities have design heads above 20 m and typically exhibit the following characteristics (DOE 2016):

  • 5 MW to 30 MW
  • New/rehabilitated intake structure
  • New penstock (typically <500 feet of steel penstock, if required)
  • Francis turbines (1–3 units)
  • New powerhouse (indoor)
  • New/rehabilitated tailrace
  • Minimal new transmission line (up to 15 mw, if required)
  • Capacity factor of 35% to 60%.

Resource Potential

Up to 12 GW of technical potential exists to add power to U.S. NPD. However, when economic decision-making approximating seen in recent development activity is taken into account, the economic potential of NPD may be approximately 5.6 GW at over 54,000 dams in the contiguous United States. The majority of this potential (5 GW or 90% of resource capacity) is associated with less than 700 dams (DOE 2016). These resource considerations are discussed below:

  • According to the National Inventory of Dams, more than 80,000 dams exist that do not produce power. This data set was filtered to remove dams with erroneous flow and geographic data and dams whose data could not be resolved to a satisfactory level of detail (Hadjerioua, Wei, and Kao 2012). This initial assessment of 54,391 dams resulted in 12 GW of capacity.
  • A new methodology for sizing potential hydropower facilities that was developed for the new-stream reach development resource (Kao et al. 2014) was applied to non-powered dams. This resource potential was estimated to be 5.6 GW at over 54,000 dams. In the development of the Hydropower Vision, the NPD resource available to the ReEDS model was adjusted based on recent development activity and limited to only those projects with power potential of 500 kW or more. As the ATB uses the Hydropower Vision supply curves, this results in a final resource potential of 5 GW/29 TWh from 671 dams.
  • For each facility, a design capacity, average monthly flow rate over a 20-year period, and a design flow rate exceedance level of 30% are assumed. The exceedance level represents the fraction of time that the design flow is exceeded. This parameter can be varied and results in different capacity and energy generation for a given site. The value of 30% was chosen based on industry rules of thumb. The capacity factor for a given facility is determined by these design criteria.
  • Design capacity and flow rate dictate capacity and energy generation potential. All facilities are assumed sized for 30% exceedance of flow rate based on long-term, average monthly flow rates.

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 Projections Overview

Site-specific CAPEX, O&M, and capacity factor estimates are made for each site in the available resource potential. CAPEX and O&M estimates are made based on statistical analysis of historical plant data from 1980 to 2015 (O'Connor et al. 2015a). Capacity factors are estimated based on historical flow rates. For presentation in the ATB, a subset of resource potential is aggregated into four representative NPD plants that span a range of realistic conditions for future hydropower deployment.

Projections developed for the Hydropower Vision study (DOE 2016) using technological learning assumptions and bottom-up analysis of process and/or technology improvements provide a range of future cost outcomes. Three different projections were developed for scenario modeling as bounding levels:

  • High cost: no change in CAPEX, O&M, or capacity factor from 2015 to 2050; consistent across all renewable energy technologies in the ATB
  • Mid cost: incremental technology learning, consistent with Reference in Hydropower Vision (DOE 2016); CAPEX reductions for new stream-reach development (NSD) only
  • Low cost: gains that are achievable when pushing to the limits of potential new technologies, such as modularity (in both civil structures and power train design), advanced manufacturing techniques, and materials, consistent with Advanced Technology in Hydropower Vision (DOE 2016); both CAPEX and O&M cost reductions implemented.

Standard Scenarios Model Results

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

ReEDS Version 2017.1 standard scenario model results restrict the resource potential to sites greater than 500 kW consistent with the Hydropower Vision, which results in 5 GW/29 TWh at 671 dams.

New Stream-Reach Development

map of new stream-reach development potential in the United States
Source: ORNL NSD resource assessment

Representative Technology

Greenfield or new stream-reach development (NSD) sites are defined as new hydropower developments along previously undeveloped waterways and typically exhibit the following characteristics (DOE 2016):

  • 1 MW to 100 MW
  • New diversion/intake structure
  • New penstock
  • Steel with length being head/terrain dependent
  • Various turbine selections
  • Impulse/Francis are common for recently completed projects
  • New powerhouse (indoor)
  • New tailrace
  • New transmission line (up to 15 miles for new projects)
  • Capacity factor of 30% to 80%.

Resource Potential

The resource potential is estimated to be 53.2 GW/301 TWh at nearly 230,000 individual sites (Kao et al. 2014) after accounting for locations statutorily excluded from hydropower development such as national parks, wild and scenic rivers, and wilderness areas.

  • About 8,500 stream reaches were evaluated to assess resource potential (i.e., capacity) and energy generation potential (i.e., capacity factor). For each stream reach, a design capacity, average monthly flow rate over a 20-year period, and design flow rate exceedance level of 30% are assumed. The exceedance level represents the fraction of time that the design flow is exceeded. This parameter can be varied and results in different capacity and energy generation for a given site. The value of 30% was chosen based on industry rules of thumb. The capacity factor for a given facility is determined by these design criteria. Plant sizes range from kilowatt-scale to multi-megawatt scale (Kao et al. 2014).
  • The resource assessment approach is designed to minimize the footprint of a hydropower facility by restricting inundation area to the FEMA 100-year floodplain.
  • New hydropower facilities are assumed to apply run-of-river operation strategies. Run-of-river operation means that the flow rate into a reservoir is equal to the flow rate out of the facility. These facilities do not have dispatch capability.
  • Design capacity and flow rate dictate capacity and energy generation potential. All facilities are assumed sized for 30% exceedance of flow rate based on long-term, average monthly flow rates.

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").

Base Year and Future Year Projections Overview

Site-specific CAPEX, O&M, and capacity factor estimates are made for each site in the available resource potential. CAPEX and O&M estimates are made based on statistical analysis of historical plant data from 1980 to 2015 (O'Connor et al. 2015a). Capacity factors are estimated based on historical flow rates. For presentation in the ATB, a subset of resource potential is aggregated into four representative NSD plants that span a range of realistic conditions for future hydropower deployment.

Projections developed for the Hydropower Vision study (DOE 2016) using technological learning assumptions and bottom-up analysis of process and/or technology improvements provide a range of future cost outcomes. Three different projections were developed for scenario modeling as bounding levels:

  • High cost: no change in CAPEX, O&M, or capacity factor from 2015 to 2050; consistent across all renewable energy technologies in the ATB
  • Mid cost: incremental technology learning, consistent with Reference in Hydropower Vision (DOE 2016); CAPEX reductions for NSD only
  • Low cost: gains that are achievable when pushing to the limits of potential new technologies, such as modularity (in both civil structures and power train design), advanced manufacturing techniques, and materials, consistent with Advanced Technology in Hydropower Vision (DOE 2016); both CAPEX and O&M cost reductions implemented.

Standard Scenarios Model Results

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

ReEDS Version 2017.1 standard scenario model results restrict the resource potential to sites greater than 1 MW, which results in 30.1 GW/176 TWh on nearly 8,000 reaches.

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 hydropower generation plant, 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 or materials. 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 reduction scenarios are represented: High, Mid, and Low. Historical data from actual and proposed non-powered dam (NPD) and new stream-reach development (NSD) plants installed in the United States from 1981 to 2014 are shown for comparison to the ATB Base Year. The estimate for a given year represents CAPEX of a new plant that reaches commercial operation in that year.

chart: CAPEX historical trends, current estimates, and future projections for hydropower in the 2017 ATB
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 CAPEX estimates represent actual and proposed projects from 1981 to 2014.
Year represents Commercial Online Date for a past or future plant.

Recent Trends

Actual and proposed NPD and NSD CAPEX from 1981 to 2014 (from O'Connor et al. 2015a) are shown in box-and-whiskers format for comparison to the ATB current CAPEX estimates and future projections.

The higher-cost ATB sites generally reflect small-capacity, low-head sites that are not comparable to the historical data sample's generally larger-capacity and higher-head facilities. These characteristics lead to higher ATB Base Year CAPEX estimates than past data suggest. For example, the NSD projects that became commercially operational in this period are dominated by a few high-head projects in the mountains of the Pacific Northwest or Alaska.

The Base Year estimates of CAPEX for NPDs in the ATB range from $3,800/kW to $6,000/kW. These estimates reflect facilities with 3 feet of head to over 60 feet head and from 0.5 MW to more than 30 MW of capacity. In general, the higher-cost sites reflect much smaller-capacity (<10 MW), low-head (<30 ft.) sites that have fewer analogues in the historical data, but these characteristics result in higher CAPEX.

The Base Year estimates of CAPEX for NSD range from $5,500/kW to $7,900/kW. The estimates reflect potential sites with 3 feet of head to over 60 feet head and from 1 MW to more than 30 MW of capacity. In general, NSD potential represents smaller-capacity facilities with lower head than most historical data represents. These characteristics lead to higher CAPEX estimates than past data suggests as many of the larger, higher-head sites in the United States have been previously developed.

Base Year Estimates

For illustration in the ATB, all potential NPD and NSD sites were first binned by both head and capacity. Analysis of these bins provided groupings that represent the most realistic conditions for future hydropower deployment. The design values of these four reference NPD and four reference NSD plants are shown below. The full range of resource and design characteristics is summarized in the ATB data spreadsheet.

Representative Hydropower Plants
Plants Resource Characteristics Ranges Weighted Average Values Calculated Plant Values
Plants Head (feet) Capacity (MW) Head (feet) Capacity (MW) Capacity Factor ICC (2015$/kW) O&M (2015$/kW)
NPD 1 3-30 0.5-10 15.4 4.8 0.62 $6,169 $112
NPD 2 3-30 10+ 15.9 82.2 0.64 $5,615 $31
NPD 3 30+ 0.5-10 89.6 4.2 0.60 $4,131 $119
NPD 4 30+ 10+ 81.3 44.7 0.60 $3,895 $41
NSD 1 3-30 1-10 15.7 3.7 0.66 $7,270 $125
NSD 2 3-30 10+ 19.6 44.1 0.66 $6,490 $41
NSD 3 30+ 1-10 46.8 4.3 0.62 $6,357 $118
NSD 4 30+ 10+ 45.3 94.0 0.66 $5,722 $29
Reference plants are representative of the range of resource potential shown in the columns to the right.
30+ represents head >= 30 ft.; similarly 10+ represents capacity >= 10 MW.

The reference plants shown above were developed using the average characteristics (weighted by capacity) of the resource plants within each set of ranges. For example, NPD 1 is constructed from the capacity-weighted average values of NPD sites with 3-330 feet of head and 0.5-30 MW of capacity.

The weighted-average values were used as input to the cost formulas (O'Connor et al. 2015a) in order to calculate site CAPEX and O&M costs.

CAPEX for each plant is based on statistical analysis of historical plant data from 1980 to 2015 as a function of key design parameters, plant capacity, and hydraulic head (O'Connor et al. 2015a).

NPD CAPEX = (11,489,245 × P0.976 × H-0.24) + (310,000 × P0.7)
NSD CAPEX = (9,605,710 × P0.977 × H-0.126) + (610,000 × P0.7)

Where P is capacity in megawatts, and H is head in feet. The first term represents the initial capital costs, while the second represents licensing.

Future Projections

Projections developed for the Hydropower Vision study (DOE 2016) using technological learning assumptions and bottom-up analysis of process and/or technology improvements provide a range of future cost outcomes. Three different CAPEX projections were developed for scenario modeling as bounding levels:

  • High cost:
    • NPD and NSD CAPEX unchanged from the Base Year; consistent across all renewable energy technologies in the ATB
  • Mid cost: consistent with Reference in Hydropower Vision:
    • NSD CAPEX reduced 5% in 2035 and 8.6% in 2050
    • NPD CAPEX unchanged from the Base Year
  • Low cost: consistent with Advanced Technology in Hydropower Vision:
    • Low head NPD/All NSD CAPEX reduced 30% in 2035 and 35.3% in 2050. Low Head NPD is NPD-1 and NPD-2.
    • High head NPD CAPEX reduced 25% in 2035 and 32.7% in 2050. High head NPD is NPD-3 and NPD-4.

Detailed description of the methodology for developing Future Year Projections is found in Projections Methodology.

Technology innovations that could impact future CAPEX costs are summarized in LCOE Projections.

Standard Scenarios Model Results

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

ReEDS Version 2017.1 standard scenario model results use resource/cost supply curves representing estimates at each individual facility (~700 NPD and ~8,000 NSD).

The ReEDS model represents cost and performance for NPD and NSD potential in 5 bins for each of 134 geographic regions, which results in CAPEX ranges of $2,750/kW-$9,000/kW for NPD resource and $5,200/kW-$15,600/kW for NSD.

The ReEDS model represents cost and performance for NPD and NSD potential in 5 bins for each of 134 geographic regions, which results in capacity factor ranges of 38%-80% for NPD resource and 53%-81% for NSD.

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 described by O'Connor et al. (2015b) - the hydropower plant envelope is defined to include:

  • Hydropower generation plant
    • Civil works, such as site preparation, dams and reservoirs, water conveyances, and powerhouse structures
    • Equipment, such as the powertrain and ancillary plant electrical and mechanical systems
  • Balance of system
    • Installation and O&M infrastructure
    • Electrical infrastructure, such as transformers, switchgear, and electrical system connecting turbines to each other and to the control center
    • Project indirect costs, including costs related to environmental mitigation and regulatory compliance, engineering, distributable labor and materials, construction management start up and commissioning, and contractor overhead costs, fees, and profit
  • Financial costs
    • Owner's costs, such as development costs, preliminary feasibility and engineering studies, environmental studies and permitting, legal fees, insurance costs, and property taxes during construction
    • Electrical interconnection and 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 is shown for four representative non-powered dam plants and four representative new stream-reach development plants. CAPEX estimates for all identified hydropower potential (~700 NPD and ~8,000 NSD) results in a CAPEX range that is much broader than that shown in the ATB. It is unlikely that all of the resource potential will be developed due to the very high costs for some sites. Regional cost effects and distance-based spur line costs are not estimated.

chart: CAPEX definition for hydropower in the 2017 ATB

Standard Scenarios Model Results

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

CAPEX in ATB do not represent regional variants (CapRegMult) associated with labor rates, material costs, etc., and neither does ReEDS.

CAPEX in ATB do not include geographically determined spur line (GCC) from plant to transmission grid, and neither does ReEDS.

Operation and Maintenance (O&M) Costs

Operations and maintenance (O&M) costs represent average annual fixed expenditures (and depend on rated capacity) required to operate and maintain a hydropower plant over its technical lifetime of 50 years (the distinction between economic life and technical life is described here), including:

  • Insurance, taxes, land lease payments, and other fixed costs
  • Present value and annualized large component overhaul or replacement costs over technical life (e.g., rewind stator, patch cavitation damage, and replace bearings)
  • Scheduled and unscheduled maintenance of hydropower plant components, including turbines, generators, etc. 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 reduction 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.

chart: base year estimate and future year projections for fixed O&M costs for hydropower in the 2017 ATB

Base Year Estimates

A statistical analysis of long-term plant operation costs from FERC Form-1 resulted in a relationship between annual, FOM costs, and plant capacity (updated to 2015$ from O'Connor et al. 2015a).

Lesser of (Annual O&M (in 2015$)=227,000xP0.547) or (2.5% of CAPEX)

Future Year Projections

Projections developed for the Hydropower Vision study (DOE 2016) using technological learning assumptions and bottom-up analysis of process and/or technology improvements provide a range of future cost outcomes. Three different O&M projections were developed for scenario modeling as bounding levels:

  • High cost: FOM costs unchanged from the Base Year to 2050; consistent with all ATB technologies
  • Mid cost: FOM costs for both NPD and NSD plants are unchanged from 2015 to 2050; consistent with Reference in Hydropower Vision
  • Low cost: FOM costs for both NPD and NSD plants are reduced by 50% in 2035 and 54% in 2050, consistent with Advanced Technology in Hydropower Vision.

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 technical lifetime of the plant (the distinction between economic life and technical life is described here). 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 site hydrology, design factors (e.g., exceedance level), and operation characteristics (e.g., dispatch or run of river). Capacity factors for all potential NPD sites and NSDs are estimated based on design criteria, long-term monthly flow rate records, and run-of-river operation.

The following figure shows a range of capacity factors based on variation in the resource for hydropower plants in the contiguous United States. Historical data from run of river hydropower plants operating in the United States from 2003 through 2012 are shown for comparison with the Base Year estimates. The range of the Base Year estimates illustrates the effect of resource variation. Future projections for High, Mid and Low cost scenarios are unchanged from the Base Year. Technology improvements are focused on CAPEX and O&M cost elements.

chart: capacity factor (annual average energy production over plant lifetime) for hydropower in the 2017 ATB
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 energy production from about 200 run-of-river plants operating in the United States from 2003 through 2012 where Year represents calendar year.
Projection data represent expected annual average CF for plants with Commercial Online Date specified by Year.

Recent Trends

Actual energy production from about 200 run-of-river plants operating in the United States from 2003 to 2012 (EIA 2016a) is shown in box-and-whiskers format for comparison with current estimates and future projections. This sample includes some very old plants that may have lower availability and efficiency losses. It also includes plants that have been relicensed and may no longer be optimally designed for current operating regime (e.g., a peaking unit now operating as run of river). This contributes to the broad range, particularly on the low end.

Interannual variation of hydropower plant output for run-of-river plants may be significant due to hydrological changes such as drought. This impact may be exacerbated by climate change over the long term.

Current and future estimates for new hydropower plants are within the range of observed plant performance. These potential hydropower plants would be designed for specific site conditions, which would indicate operation toward the high end of the range.

Base Year Estimates

For illustration in the ATB, all potential NPD and NSD sites are represented with four reference plants, each as described below.

Representative Hydropower Plants
Plants Resource Characteristics Ranges Weighted Average Values Calculated Plant Values
Plants Head (feet) Capacity (MW) Head (feet) Capacity (MW) Capacity Factor ICC (2014$/kW) O&M (2014$/kW)
NPD 1 3-30 0.5-10 15.4 4.8 0.62 $6,169 $112
NPD 2 3-30 10+ 15.9 82.2 0.64 $5,615 $31
NPD 3 30+ 0.5-10 89.6 4.2 0.60 $4,131 $119
NPD 4 30+ 10+ 81.3 44.7 0.60 $3,895 $41
NSD 1 3-30 1-10 15.7 3.7 0.66 $7,270 $125
NSD 2 3-30 10+ 19.6 44.1 0.66 $6,490 $41
NSD 3 30+ 1-10 46.8 4.3 0.62 $6,357 $118
NSD 4 30+ 10+ 45.3 94.0 0.66 $5,722 $29

Future Year Projections

The capacity factor remains unchanged from the Base Year through 2050. Technology improvements are focused on CAPEX and O&M costs.

Standard Scenarios Model Results

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

ReEDS Version 2017.1 standard scenario model results use resource/cost supply curves representing estimates at each individual facility (~700 NPD and ~8,000 NSD).

The ReEDS model represents cost and performance for NPD and NSD potential in 5 bins for each of 134 geographic regions, which results in capacity factor ranges of 38%-80% for the NPD resources and 53%-81% for NSD.

Existing hydropower facilities in the ReEDS model provide dispatch capability such that their annual energy production is determined by the electric system needs by dispatching generators to accommodate diurnal and seasonal load variations and output from variable generation sources (e.g., wind and solar PV).

Plant Cost and Performance Projections Methodology

Projections developed for the Hydropower Vision study (DOE 2016) using technological learning assumptions and bottom-up analysis of process and/or technology improvements provide a range of future cost outcomes. Three different projections were developed for scenario modeling as bounding levels:

  • High cost: no change in CAPEX or OPEX from 2015 to 2050; consistent across all renewable energy technologies in the ATB
  • Mid cost: incremental learning, consistent with Reference in the Hydropower Vision study (DOE 2016); CAPEX reductions for NSD only
  • Low cost: gains that are achievable when pushing to the limits of potential new technologies, such as modularity (in both civil structures and power train design), advanced manufacturing techniques, and materials, consistent with Advanced Technology in Hydropower Vision (DOE 2016); both CAPEX and O&M cost reductions implemented.
chart: cost and performance projections methodology for hydropower in the 2017 ATB

The Mid and Low cost cases use a mix of inputs based on EIA technological learning assumptions, input from a technical team of Oak Ridge National Laboratory researchers, and the experience of expert hydropower consultants. Estimated 2035 cost levels are intended to provide magnitude of order cost reductions deemed to be at least conceptually possible, and they are meant to stimulate a broader discussion with the hydropower industry and its stakeholders that will be necessary to the future of cost reduction in the industry. Cost projections were derived independently for NPD and NSD technologies.

For context, ATB cost projections are compared to the literature, which represents 7 independent published studies and 11 cost projection scenarios within these studies. Cost reduction literature for hydropower is limited with several studies projecting no change through 2050. It is unclear whether (1) this represents a deliberate estimate of no future change in cost or (2) no estimate has been made.

Hydropower investment costs are very site specific and vary with type of technology. Literature was reviewed to attempt to isolate perceived CAPEX reduction for resources of similar characteristics over time (e.g., estimated cost to develop the same site in 2015, 2030, and 2050 based on different technology, installation, and other technical aspects). Some studies reflect increasing CAPEX over time. These studies were excluded from the ATB based on the interpretation that rising costs reflect a transition to less attractive sites as the better sites are used earlier.

Literature estimates generally reflect hydropower facilities of sizes similar to those represented in U.S. resource potential (i.e., they exclude estimates for very large facilities). Due to limited sample size, all projections are analyzed together without distinction between types of technology. Note that although declines are shown on a percentage basis, the reduction is likely to vary with initial capital cost. Large reductions for moderately expensive sites may not scale to more expensive sites or to less expensive sites. Projections derived for the Hydropower Vision study for different technologies (Low Head NPD, High Head NPD, and NSD) address this simplification somewhat.

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 focus of the ATB is to define the primary cost and performance parameters for use in electric sector modeling or other analysis where more sophisticated comparisons among technologies are made. LCOE captures the energy component of electric system planning and operation, but the electric system also requires capacity and flexibility services to operate reliably. 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 the combined impact of CAPEX, O&M, and capacity factor projections across the range of resources present in the contiguous United States. The Current Market Conditions LCOE demonstrates the range of LCOE based on macroeconomic conditions similar to the present. The Historical Market Conditions LCOE presents the range of LCOE based on macroeconomic conditions consistent with prior ATB editions and Standard Scenarios model results. The Normalized LCOE (all LCOE estimates are normalized with the lowest Base Year LCOE value) emphasizes the effect of resource quality and the relative differences in the three future pathways independent of project finance assumptions. The ATB representative plant characteristics that best align with recently installed or anticipated near-term hydropower plants are associated with NPD 4. Data for all the resource categories can be found in the ATB data spreadsheet.

Current Market Conditions
Historical Market Conditions
Normalized

Values are in 2015$.

The ATB representative plant characteristics that best align with recently installed or anticipated near-term hydropower plants are associated with NPD 4.

The methodology for representing the CAPEX, O&M, and capacity factor assumptions behind each pathway is discussed in Projections Methodology. The three pathways are generally defined as:

  • High = Base Year (or near-term estimates of projects under construction) equivalent through 2050 maintains current relative technology cost differences
  • Mid = 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 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. For comparison in the ATB, two project finance structures are represented.

  • Current Market Conditions: The values of the production tax credit (PTC) and investment tax credit (ITC) are ramping down by 2020, at which time wind and solar projects may be financed with debt fractions similar to other technologies. This scenario reflects debt interest (4.4% nominal, 1.9% real) and return on equity rates (9.5% nominal, 6.8% real) to represent 2017 market conditions (AEO 2017) and a debt fraction of 60% for all electricity generation technologies. An economic life, or period over which the initial capital investment is recovered, of 20 years is assumed for all technologies. These assumptions are one of the project finance options in the ATB spreadsheet.
  • Long-Term Historical Market Conditions: Historically, debt interest and return on equity were represented with higher values. This scenario reflects debt interest (8% nominal, 5.4% real) and return on equity rates (13% nominal, 10.2% real) implemented in the ReEDS model and reflected in prior versions of the ATB and Standard Scenarios model results. A debt fraction of 60% for all electricity generation technologies is assumed. An economic life, or period over which the initial capital investment is recovered, of 20 years is assumed for all technologies. These assumptions are one of the project finance options in the ATB spreadsheet.

These parameters are held constant for estimates representing the Base Year through 2050. No incentives such as the PTC or ITC are included. 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 and economic life, see Project Finance Impact on LCOE. For LCOE estimates for High, Mid, and Low scenarios for all technologies, see 2017 ATB Cost and Performance Summary.

Areas identified as having potential cost reduction opportunities associated with the Low cost projection include:

  • Widespread implementation of value engineering and design/construction best practices
  • Modular "drop-in" systems that minimize civil works and maximize ease of manufacture reduce both capital investment and O&M expenditures
  • Use of alternative materials in place of steel for water diversion (e.g., penstocks)
  • Implementation of standardized "smart" automation and remote monitoring systems to optimize scheduling of maintenance
  • Research and development on environmentally enhanced turbines to improve performance of the existing hydropower fleet
  • Efficient, certain, permitting, licensing, and approval procedures.

The Hydropower Vision study (DOE 2016) includes roadmap actions that result in lower-cost technology.

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.

chart: Current estimates and future projections calculated from EIA (2017), modified as described in the CAPEX section.
Current estimates and future projections calculated from EIA (2017), modified as described in the CAPEX section.

Comparison with Other Sources

chart:
Data sources include the ATB, B&V (2012), Brattle (2014), Entergy (2015), E3 (2014), IEA (2015), 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 the 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 EIA's 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.

chart: CAPEX range for ATB representative plant and regional costs across U.S. for natural gas plants

Operation and Maintenance (O&M) Costs

Operations and maintenance (O&M) costs represent the annual expenditures required to operate and maintain a plant over its technical lifetime (the distinction between economic life and technical life is described here), 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.

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
chart: Natural gas plant fixed O&M projections.

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 (2016c, 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.

chart: Current estimates and future projections calculated from EIA (2017) and modified.
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 focus of the ATB is to define the primary cost and performance parameters for use in electric sector modeling or other analysis where more sophisticated comparisons among technologies are made. LCOE captures the energy component of electric system planning and operation, but the electric system also requires capacity and flexibility services to operate reliably. 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 the combined impact of CAPEX, O&M, and capacity factor projections across the range of resources present in the contiguous United States. The Current Market Conditions LCOE demonstrates the range of LCOE based on macroeconomic conditions similar to the present. The Historical Market Conditions LCOE presents the range of LCOE based on macroeconomic conditions consistent with prior ATB editions and Standard Scenarios model results. The Normalized LCOE (all LCOE estimates are normalized with the lowest Base Year LCOE value) emphasizes the relative effect of fuel price and heat rate independent of project finance assumptions. The ATB representative plant characteristics that best align with 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.

Current Market Conditions
Historical Market Conditions
Normalized
The ATB representative plant characteristics that best align with recently installed or anticipated near-term natural gas plants are associated with Gas-CC-HighCF.

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 EIA's Annual Energy Outlook 2017 (EIA 2017).

To estimate LCOE, assumptions about the cost of capital to finance electricity generation projects are required. For comparison in the ATB, two project finance structures are represented.

  • Current Market Conditions: The values of the production tax credit (PTC) and investment tax credit (ITC) are ramping down by 2020, at which time wind and solar projects may be financed with debt fractions similar to other technologies. This scenario reflects debt interest (4.4% nominal, 1.9% real) and return on equity rates (9.5% nominal, 6.8% real) to represent 2017 market conditions (AEO 2017) and a debt fraction of 60% for all electricity generation technologies. An economic life, or period over which the initial capital investment is recovered, of 20 years is assumed for all technologies. These assumptions are one of the project finance options in the ATB spreadsheet.
  • Long-Term Historical Market Conditions: Historically, debt interest and return on equity were represented with higher values. This scenario reflects debt interest (8% nominal, 5.4% real) and return on equity rates (13% nominal, 10.2% real) implemented in the ReEDS model and reflected in prior versions of the ATB and Standard Scenarios model results. A debt fraction of 60% for all electricity generation technologies is assumed. An economic life, or period over which the initial capital investment is recovered, of 20 years is assumed for all technologies. These assumptions are one of the project finance options in the ATB spreadsheet.

These parameters are held constant for estimates representing the Base Year through 2050. No incentives such as the PTC or ITC are included. 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 and economic life, see Project Finance Impact on LCOE. For LCOE estimates for High, Mid, and Low scenarios for all technologies, see 2017 ATB Cost and Performance Summary.

Coal

In a coal power plant:

  • Heat is created: Coal is pulverized, mixed with hot air, and burned in suspension.
  • Water turns to steam: The heat turns purified water into steam, which is piped to the turbine.
  • Steam turns the turbine: The pressure of the steam pushes the turbine blade, turns the shaft in the generator, and creates power.
  • Steam is turned back into water: Cool water is drawn into a condenser where the steam turns back into water that can be used over again in the plant.

The process outlined above is adapted from Duke Energy ("How Energy Works"). Coal plant emissions and performance are also impacted by the kind of coal (coal rank) that the plant burns. Lignite, subbituminous, bituminous, and anthracite coal are all of varying quality. The amount of moisture, sulfur, and ash in a particular type of coal can have significant influence on coal plant operation, design, and cost.

Niagara Mohawk's Dunkirk steam station in New York (soon to be set up for cofiring biomass)
Niagara Mohawk's Dunkirk steam station in New York (soon to be set up for cofiring biomass)
Niagara Mohawk's Dunkirk steam station in New York
(soon to be set up for cofiring biomass)
Photo by David Parsons, NREL 06705
Electrical transmission lines in front of coal-fired power plant
Electrical transmission lines in front of coal-fired power plant
Photo by Warren Getz, NREL 10933

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. Coal reserves in the United States are assessed by the United States Geological Survey (USGS, "Coal Assessments").

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

Technology cost and performance projections are taken the EIA Annual Energy Outlook Reference Scenario (EIA 2017). Because little-to-no coal is built in the Reference Scenario, coal capital expenditures (CAPEX) decline according to the minimum learning rate. Pulverized coal is a relatively mature technology, and therefore has a low minimum learning rate. Integrated gasification combined cycle (IGCC) technology, where the coal is gasified and then fed into a combined cycle turbine, is less mature and is assumed to have a slightly higher minimum learning rate. Coal with carbon capture and storage (CCS) is also a newer technology with a higher minimum learning rate.

chart: Current estimates and future projections calculated from EIA (2017), modified as described in the CAPEX section.
Current estimates and future projections calculated from EIA (2017), modified as described in the CAPEX section.

Comparison with Other Sources

chart: Coal plant overnight capital cost comparison by data source.
Data sources include the ATB, B&V (2012), Lazard (2016), NETL (2015), and Rubin et al. (2015).

Lazard (2016) does not explicitly define their ranges with and without CCS; thus, the high end of their pulverized coal and IGCC ranges and the low end of their IGCC-CCS range are assumed to be the middle of the full reported range. All sources have been normalized to the same dollar year. Costs vary due to differences in system design (e.g., coal rank), methodology, and plant cost definitions.

CAPEX Definition

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

For coal power plants, CAPEX equals interest during construction (ConFinFactor) times the overnight capital cost (OCC).

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, which are just passed through to end user, are taken from EIA (2017).

For the ATB, coal-CCS technology is ultra-supercritical pulverized coal technology fitted with CCS. Both 30% capture and 90% capture options are included for the coal-CCS technology. 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)
Coal-new: Ultra-supercritical pulverized coal with SO2 and NOx controls $3,559 1.084 $3,859
Coal-IGCC: Integrated gasification combined cycle (IGCC) $3,819 1.084 $4,141
Coal-CCS: Ultra-supercritical pulverized coal with carbon capture and sequestration (CCS) options (30% / 90% capture) $4,927 / $5,448 1.084 $5,341 / $5,906

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 a coal 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.

chart: CAPEX range for ATB representative plant and regional costs across U.S. for coal plants.

Operation and Maintenance (O&M) Costs

Operations and maintenance (O&M) costs represent the annual expenditures required to operate and maintain a plant over its technical lifetime (the distinction between economic life and technical life is described here), 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.

Cherokee Generating Station, a coal-powered plant in Denver, Colorado
Cherokee Generating Station, a coal-powered plant in Denver, Colorado
Photo by Warren Getz, NREL 06393
chart: Coal plant fixed O&M projections.

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 coal plants, the capacity factors are typically lower than their availability factors. Coal plant availability factors have a wide range depending on system design and maintenance schedules.

The capacity factor 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).

Coal power plants have typically been operated as baseload units, although that has changed in many locations due to low natural gas prices and increased penetration of variable renewable technologies. The average capacity factor used in the ATB is the fleet-wide average reported by EIA for 2015. The high capacity factor represents a new plant that would operate as a baseload unit.

Even though IGCC and coal with CCS have experienced limited deployment in the United States, it is expected that their performance characteristics would be similar to new coal power plants.

chart: Coal net capacity factor.
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 focus of the ATB is to define the primary cost and performance parameters for use in electric sector modeling or other analysis where more sophisticated comparisons among technologies are made. LCOE captures the energy component of electric system planning and operation, but the electric system also requires capacity and flexibility services to operate reliably. 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 the combined impact of CAPEX, O&M, and capacity factor projections across the range of resources present in the contiguous United States. The Current Market Conditions LCOE demonstrates the range of LCOE based on macroeconomic conditions similar to the present. The Historical Market Conditions LCOE presents the range of LCOE based on macroeconomic conditions consistent with prior ATB editions and Standard Scenarios model results. The Normalized LCOE (all LCOE estimates are normalized with the lowest Base Year LCOE value) emphasizes the relative effect of fuel price and heat rate independent of project finance assumptions. The ATB representative plant characteristics that best align with recently installed or anticipated near-term coal plants are associated with Coal-New-HighCF. Data for all the resource categories can be found in the ATB data spreadsheet.

Current Market Conditions
Historical Market Conditions
Normalized
The ATB representative plant characteristics that best align with recently installed or anticipated near-term coal plants are associated with Coal-New-HighCF.

The LCOE of coal power plants is directly impacted by multiple coal fuel cost scenarios. It is also impacted by variations in the heat rate, O&M costs, and assumed capacity factor. For a given year, the LCOE assumes that the fuel prices from that year continue throughout the lifetime of the plant.

The 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).

To estimate LCOE, assumptions about the cost of capital to finance electricity generation projects are required. For comparison in the ATB, two project finance structures are represented.

  • Current Market Conditions: The values of the production tax credit (PTC) and investment tax credit (ITC) are ramping down by 2020, at which time wind and solar projects may be financed with debt fractions similar to other technologies. This scenario reflects debt interest (4.4% nominal, 1.9% real) and return on equity rates (9.5% nominal, 6.8% real) to represent 2017 market conditions (AEO 2017) and a debt fraction of 60% for all electricity generation technologies. An economic life, or period over which the initial capital investment is recovered, of 20 years is assumed for all technologies. These assumptions are one of the project finance options in the ATB spreadsheet.
  • Long-Term Historical Market Conditions: Historically, debt interest and return on equity were represented with higher values. This scenario reflects debt interest (8% nominal, 5.4% real) and return on equity rates (13% nominal, 10.2% real) implemented in the ReEDS model and reflected in prior versions of the ATB and Standard Scenarios model results. A debt fraction of 60% for all electricity generation technologies is assumed. An economic life, or period over which the initial capital investment is recovered, of 20 years is assumed for all technologies. These assumptions are one of the project finance options in the ATB spreadsheet.

These parameters are held constant for estimates representing the Base Year through 2050. No incentives such as the PTC or ITC are included. 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 and economic life, see Project Finance Impact on LCOE. For LCOE estimates for High, Mid, and Low scenarios for all technologies, see 2017 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's Watts Bar Nuclear Power Plant
TVA's 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.

chart: Current estimates and future projections calculated from EIA (2017), modified as described in the CAPEX section.
Current estimates and future projections calculated from EIA (2017), modified as described in the CAPEX section.

Comparison with Other Sources

chart: Coal plant overnight capital cost comparison by data source.
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 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.

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.

chart: CAPEX range for ATB representative plant and regional costs across U.S. for nuclear plants.

Operation and Maintenance (O&M) Costs

Operations and maintenance (O&M) costs represent the annual expenditures required to operate and maintain a plant over its technical lifetime (the distinction between economic life and technical life is described here), 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.

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/
chart: Nuclear plant O&M projections.

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").

chart: Coal net capacity factor.
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 focus of the ATB is to define the primary cost and performance parameters for use in electric sector modeling or other analysis where more sophisticated comparisons among technologies are made. LCOE captures the energy component of electric system planning and operation, but the electric system also requires capacity and flexibility services to operate reliably. 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 the combined impact of CAPEX, O&M, and capacity factor projections across the range of resources present in the contiguous United States. The Current Market Conditions LCOE demonstrates the range of LCOE based on macroeconomic conditions similar to the present. The Historical Market Conditions LCOE presents the range of LCOE based on macroeconomic conditions consistent with prior ATB editions and Standard Scenarios model results. The Normalized LCOE (all LCOE estimates are normalized with the lowest Base Year LCOE value) emphasizes the relative effect of fuel price and heat rate independent of project finance assumptions.

Current Market Conditions
Historical Market Conditions
Normalized

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 EIA's Annual Energy Outlook 2017 (EIA 2017).

To estimate LCOE, assumptions about the cost of capital to finance electricity generation projects are required. For comparison in the ATB, two project finance structures are represented.

  • Current Market Conditions: The values of the production tax credit (PTC) and investment tax credit (ITC) are ramping down by 2020, at which time wind and solar projects may be financed with debt fractions similar to other technologies. This scenario reflects debt interest (4.4% nominal, 1.9% real) and return on equity rates (9.5% nominal, 6.8% real) to represent 2017 market conditions (AEO 2017) and a debt fraction of 60% for all electricity generation technologies. An economic life, or period over which the initial capital investment is recovered, of 20 years is assumed for all technologies. These assumptions are one of the project finance options in the ATB spreadsheet.
  • Long-Term Historical Market Conditions: Historically, debt interest and return on equity were represented with higher values. This scenario reflects debt interest (8% nominal, 5.4% real) and return on equity rates (13% nominal, 10.2% real) implemented in the ReEDS model and reflected in prior versions of the ATB and Standard Scenarios model results. A debt fraction of 60% for all electricity generation technologies is assumed. An economic life, or period over which the initial capital investment is recovered, of 20 years is assumed for all technologies. These assumptions are one of the project finance options in the ATB spreadsheet.

These parameters are held constant for estimates representing the Base Year through 2050. No incentives such as the PTC or ITC are included. 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 and economic life, see Project Finance Impact on LCOE. For LCOE estimates for High, Mid, and Low scenarios for all technologies, see 2017 ATB Cost and Performance Summary.

Biopower Plants

In a biopower plant:

  1. Heat is created: Biomass (sometimes co-fired with coal) is pulverized, mixed with hot air, and burned in suspension.
  2. Water turns to steam: The heat turns purified water into steam, which is piped to the turbine.
  3. Steam turns the turbine: The pressure of the steam pushes the turbine blade, turns the shaft in the generator, and creates power.
  4. Steam is turned back into water: Cool water is drawn into a condenser where the steam turns back into water that can be reused in the plant.
Joseph C. McNeil Generating Station in Burlington, Vermont (a biomass gasifier that operates on wood chips)
Joseph C. McNeil Generating Station in Burlington, Vermont
(a biomass gasifier that operates on wood chips)
Photo by David Parsons, NREL 06905
NIPSCO generating station
NIPSCO generating station
Photo by Kevin Craig, NREL 08928

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 for biopower is based on estimated biomass quantities from the Billion Ton Update study (DOE 2011).

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

Because biopower 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.

The exception is new biomass cofiring, which is expected to have costs that decline a bit more than existing cofiring project technologies.

chart: Current estimates and future projections calculated from EIA (2017), modified as described in the CAPEX section.
Current estimates and future projections calculated from EIA (2017), modified.

CAPEX Definition

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

Overnight capital costs are modified from EIA (2014). Capital costs include overnight capital cost plus defined transmission cost, and it removes a material price index. The overnight capital costs for cofired units are not the cost of upgrading a plant but the total cost of the plant after the upgrade.

Fuel costs are taken from the Billion Ton Update study (DOE 2011).

Overnight Capital Cost ($/kW) Construction Financing Factor (ConFinFactor) CAPEX ($/kW)
Dedicated: Dedicated biopower plant $3,737 1.041 $3,889
CofireOld: Pulverized coal with sulfur dioxide (SO2) scrubbers and biomass co-firing $3,856 1.041 $4,013
CofireNew: Advanced supercritical coal with SO2 and NOx controls and biomass co-firing $3,856 1.041 $4,013

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 biopower 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.

chart: CAPEX range for ATB representative plant and regional costs across U.S. for biopower plants.

Operation and Maintenance (O&M) Costs

Operations and maintenance (O&M) costs represent the annual expenditures required to operate and maintain a plant over its technical lifetime (the distinction between economic life and technical life is described here), 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.

Joseph C. McNeil Generating Station in Burlington, Vermont (a biomass gasifier that operates on wood chips)
Joseph C. McNeil Generating Station in Burlington, Vermont (a biomass gasifier that operates on wood chips)
Photo by Warren Gretz, NREL 06382
chart: Coal plant fixed O&M projections.

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 biopower plants, the capacity factors are typically lower than their availability factors. Biopower plant availability factors have a wide range depending on system design, fuel type and availability, and maintenance schedules.

Biopower plants are typically baseload plants with steady capacity factors. For the ATB, the biopower capacity factor is taken as the average capacity factor for biomass plants for 2015, as reported by EIA.

Biopower capacity factors are influenced by technology and feedstock supply, expected downtime, and energy losses.

chart: Biopower net capacity factor (dedicated and cofire).
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 focus of the ATB is to define the primary cost and performance parameters for use in electric sector modeling or other analysis where more sophisticated comparisons among technologies are made. LCOE captures the energy component of electric system planning and operation, but the electric system also requires capacity and flexibility services to operate reliably. 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 the combined impact of CAPEX, O&M, and capacity factor projections across the range of resources present in the contiguous United States. The Current Market Conditions LCOE demonstrates the range of LCOE based on macroeconomic conditions similar to the present. The Historical Market Conditions LCOE presents the range of LCOE based on macroeconomic conditions consistent with prior ATB editions and Standard Scenarios model results. The Normalized LCOE (all LCOE estimates are normalized with the lowest Base Year LCOE value) emphasizes the relative effect of fuel price and heat rate independent of project finance assumptions. Data for all the resource categories can be found in the ATB data spreadsheet.

Current Market Conditions
Historical Market Conditions
Normalized
The ATB representative plant characteristics that best align with recently installed or anticipated near-term biopower plants are associated with Dedicated.

The LCOE of biopower plants is directly impacted by the differences in CAPEX (installed capacity costs) as well as by heat rate differences. For a given year, the LCOE assumes that the fuel prices from that year continue throughout the lifetime of the plant.

Regional variations will ultimately impact biomass feedstock costs, but these are not included in the ATB.

The projections do not include any cost of carbon.

Fuel prices are based on the EIA's Annual Energy Outlook 2017 (EIA 2017).

To estimate LCOE, assumptions about the cost of capital to finance electricity generation projects are required. For comparison in the ATB, two project finance structures are represented.

  • Current Market Conditions: The values of the production tax credit (PTC) and investment tax credit (ITC) are ramping down by 2020, at which time wind and solar projects may be financed with debt fractions similar to other technologies. This scenario reflects debt interest (4.4% nominal, 1.9% real) and return on equity rates (9.5% nominal, 6.8% real) to represent 2017 market conditions (AEO 2017) and a debt fraction of 60% for all electricity generation technologies. An economic life, or period over which the initial capital investment is recovered, of 20 years is assumed for all technologies. These assumptions are one of the project finance options in the ATB spreadsheet.
  • Long-Term Historical Market Conditions: Historically, debt interest and return on equity were represented with higher values. This scenario reflects debt interest (8% nominal, 5.4% real) and return on equity rates (13% nominal, 10.2% real) implemented in the ReEDS model and reflected in prior versions of the ATB and Standard Scenarios model results. A debt fraction of 60% for all electricity generation technologies is assumed. An economic life, or period over which the initial capital investment is recovered, of 20 years is assumed for all technologies. These assumptions are one of the project finance options in the ATB spreadsheet.

These parameters are held constant for estimates representing the Base Year through 2050. No incentives such as the PTC or ITC are included. 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 and economic life, see Project Finance Impact on LCOE. For LCOE estimates for High, Mid, and Low scenarios for all technologies, see 2017 ATB Cost and Performance Summary.

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