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.
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.
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.
| 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.
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.
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.
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.
| 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.
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.
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.
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).
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.
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.
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.
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.
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.
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.
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.
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
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
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.
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 $7,900/kW. The estimates reflect potential sites with 3 feet of head to over 60 feet head and from 1 MW to more than 30 MW of capacity. In general, NSD potential represents smaller-capacity facilities with lower head than most historical data represents. These characteristics lead to higher CAPEX estimates than past data suggests as many of the larger, higher-head sites in the United States have been previously developed.
Base Year Estimates
For illustration in the ATB, all potential NPD and NSD sites were first binned by both head and capacity. Analysis of these bins provided groupings that represent the most realistic conditions for future hydropower deployment. The design values of these four reference NPD and four reference NSD plants are shown below. The full range of resource and design characteristics is summarized in the ATB data spreadsheet.
| Plants | Resource Characteristics Ranges | Weighted Average Values | Calculated Plant Values | ||||
|---|---|---|---|---|---|---|---|
| Plants | Head (feet) | Capacity (MW) | Head (feet) | Capacity (MW) | Capacity Factor | ICC (2015$/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 |
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.
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.
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.
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.
| 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.
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.
Values are in 2015$.
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.
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.
(soon to be set up for cofiring biomass)
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.
Comparison with Other Sources
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.
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.
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.
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.
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").
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.
Comparison with Other Sources
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.
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.
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").
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 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:
- Heat is created: Biomass (sometimes co-fired with 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 reused in the plant.
(a biomass gasifier that operates on wood chips)
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.
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.
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.
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.
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.
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.
References
AWS Truepower. 2012. Wind Resource of the United States: Mean Annual Wind Speed at 200m Resolution. https://www.awstruepower.com/assets/Wind-Resource-Map-UNITED-STATES-11x171.pdf.
B&V (Black & Veatch). 2012. Cost and Performance Data for Power Generation Technologies. Black & Veatch Corporation. February 2012. http://bv.com/docs/reports-studies/nrel-cost-report.pdf.
Danko, Pete. 2015. 'SolarReserve: Crescent Dunes Solar Tower Will Power Up in March: Without Ivanpah's Woes.' Breaking Energy. February 10, 2015. http://breakingenergy.com/2015/02/10/solarreserve-crescent-dunes-solar-tower-will-power-up-in-march-without-ivanpahs-woes/.
DOE (U.S. Department of Energy). 2011. U.S. Billion-Ton Update: Biomass Supply for a Bioenergy and Bioproducts Industry. Perlack, R.D., and B.J. Stokes, eds. Oak Ridge, TN: Oak Ridge National Laboratory. ORNL/TM-2011/224. August 2011. https://www.osti.gov/scitech/biblio/1023318.
DOE (U.S. Department of Energy). 2012. SunShot Vision Study. DOE/GO-102012-3037. February 2012. https://www1.eere.energy.gov/solar/pdfs/47927.pdf.
DOE (U.S. Department of Energy). 2015. Wind Vision: A New Era for Wind Power in the United States. U.S. Department of Energy. DOE/GO-102015-4557. March 2015. http://energy.gov/sites/prod/files/2015/03/f20/wv_full_report.pdf.
DOE (U.S. Department of Energy). 2016. Hydropower Vision: A New Chapter for America's Renewable Electricity Source. Washington, D.C.: U.S. Department of Energy. DOE/GO-102016-4869. July 2016. https://energy.gov/sites/prod/files/2016/10/f33/Hydropower-Vision-10262016_0.pdf.
DOI (U.S. Department of the Interior, Bureau of Reclamation). 2010. Assessment of Potential Capacity Increases at Existing Hydropower Plants: Hydropower Modernization Initiative. Sacramento, CA: U.S. Department of the Interior. October 2010. https://www.usbr.gov/power/AssessmentReport/USBRHMICapacityAdditionFinalReportOctober2010.pdf.
EIA (U.S. Energy Information Administration). 2014. Annual Energy Outlook 2014 with Projections to 2040. Washington, D.C.: U.S. Department of Energy. DOE/EIA-0383(2014). April 2014. http://www.eia.gov/forecasts/aeo/pdf/0383(2014).pdf.
EIA (U.S. Energy Information Administration). 2016a. Capital Cost Estimates for Utility Scale Electricity Generating Plants. Washington, D.C.: U.S. Department of Energy. November 2016. https://www.eia.gov/analysis/studies/powerplants/capitalcost/pdf/capcost_assumption.pdf.
EIA (U.S. Energy Information Administration). 2017. Annual Energy Outlook 2017 with Projections to 2050. Washington, D.C.: U.S. Department of Energy. January 5, 2017. http://www.eia.gov/outlooks/aeo/pdf/0383(2017).pdf.
Entergy. 2015. Entergy Arkansas, Inc.: 2015 Integrated Resource Plan. July 15, 2015. http://entergy-arkansas.com/content/transition_plan/IRP_Materials_Compiled.pdf.
Feldman, David, Robert Margolis, Paul Denholm, and Joseph Stekli. 2016. Exploring the Potential Competitiveness of Utility-Scale Photovoltaics plus Batteries with Concentrating Solar Power, 2015–2030. Golden, CO: National Renewable Energy Laboratory. NREL/TP-6A20-66592. August 2016. http://www.nrel.gov/docs/fy16osti/66592.pdf.
Hadjerioua, Boualem, Yaxing Wei, and Shih-Chieh Kao. 2012. An Assessment of Energy Potential at Non-Powered Dams in the United States. Oakridge, TN: Oakridge National Laboratory. GPO DOE/EE-0711. April 2012. http://www1.eere.energy.gov/water/pdfs/npd_report.pdf.
Hall, Douglas G., Richard T. Hunt, Kelly S. Reeves, and Greg R. Carroll. 2003. Estimation of Economic Parameters of U.S. Hydropower Resources. Idaho Falls, ID: Idaho National Laboratory. INEEL/EXT-03-00662. June 2003. http://www1.eere.energy.gov/water/pdfs/doewater-00662.pdf.
IEA (International Energy Agency). 2015a. Projected Costs of Generating Electricity: 2015 Edition. Paris: International Energy Agency. https://www.iea.org/media/presentations/150831_ProjectedCostsOfGeneratingElectricity_Presentation.pdf.
IRENA (International Renewable Energy Agency). 2016. The Power to Change: Solar and Wind Cost Reduction Potential to 2025. June 2016. Paris: International Renewable Energy Agency. http://www.irena.org/DocumentDownloads/Publications/IRENA_Power_to_Change_2016.pdf.
Kao, Shih-Chieh, Ryan A. McManamay, Kevin M. Stewart, Nicole M. Samu, Boualem Hadjerioua, Scott T. DeNeale, Dilruba Yeasmin, M. Fayzul, K. Pasha, Abdoul A. Oubeidillah, and Brennan T. Smith. 2014. New Stream-Reach Development: A Comprehensive Assessment of Hydropower Energy Potential in the United States. Oakridge, TN: Oakridge National Laboratory. April 2014. GPO DOE/EE-1063. http://nhaap.ornl.gov/sites/default/files/ORNL_NSD_FY14_Final_Report.pdf.
Kurup, Parthiv, and Craig S. Turchi. 2015. Parabolic Trough Collector Cost Update for the System Advisor Model (SAM). Golden, CO: National Renewable Energy Laboratory. NREL/TP-6A20-65228. November 2015. http://www.nrel.gov/docs/fy16osti/65228.pdf.
Lazard. 2016. Levelized Cost of Energy Analysis-Version 10.0. December 2016. New York: Lazard. https://www.lazard.com/media/438038/levelized-cost-of-energy-v100.pdf.
Lopez, Anthony, Billy Roberts, Donna Heimiller, Nate Blair, and Gian Porro. 2012. U.S. Renewable Energy Technical Potentials: A GIS-Based Analysis. National Renewable Energy Laboratory. NREL/TP-6A20-51946. http://www.nrel.gov/docs/fy12osti/51946.pdf.
Mehos, Mark, Craig Turchi, Jennie Jorgenson, Paul Denholm, Clifford Ho, and Kenneth Armijo. 2016. On the Path to SunShot: Advancing Concentrating Solar Power Technology, Performance, and Dispatchability. Golden, CO: National Renewable Energy Laboratory. NREL/TP-5500-65688. May 2016. http://www.nrel.gov/docs/fy16osti/65688.pdf.
Moné, C., A. Smith, M. Hand, and B. Maples. 2015. 2013 Cost of Wind Energy Review. Golden, CO: National Renewable Energy Laboratory. http://www.nrel.gov/docs/fy15osti/63267.pdf.
Moné, Christopher, Maureen Hand, Mark Bolinger, Joseph Rand, Donna Heimiller, and Jonathan Ho. 2017. 2015 Cost of Wind Energy Review. Golden, CO: National Renewable Energy Laboratory. NREL/TP-6A20-66861. http://www.nrel.gov/docs/fy17osti/66861.pdf.
Montgomery, Watson, and Harza. 2009. Hydropower Modernization Initiative, Phase I, Needs and Opportunities Evaluation and Ranking. Prepared for the U.S. Army Corps of Engineers Northwest Division Hydroelectric Design Center. Contract No. W9127N-08-D-0003. Task Order 001.
NETL (National Energy Technology Laboratory: Tim Fout, Alexander Zoelle, Dale Keairns, Marc Turner, Mark Woods, Norma Kuehn, Vasant Shah, Vincent Chou, Lora Pinkerton). 2015. Fossil Energy Plants: Volume 1a: Bituminous Coal (PC) and Natural Gas to Electricity, Revision 3. DOE/NETL-2015/1723. http://www.netl.doe.gov/File%20Library/Research/Energy%20Analysis/Publications/Rev3Vol1aPC_NGCC_final.pdf.
O'Connor, Patrick W., Qin Fen (Katherine) Zhang, Scott T. DeNeale, Dol Raj Chalise, and Emma Centurion. 2015. Hydropower Baseline Cost Modeling. Oak Ridge, TN: Oak Ridge National Laboratory. ORNL/TM-2015/14. January 2015. http://info.ornl.gov/sites/publications/files/Pub53978.pdf.
O'Connor, Patrick W., Scott T. DeNeale, Dol Raj Chalise, Emma Centurion, and Abigail Maloof. 2015. Hydropower Baseline Cost Modeling, Version 2. Oak Ridge, TN: Oak Ridge National Laboratory. ORNL/TM-2015/471. September 2015. http://info.ornl.gov/sites/publications/files/Pub58666.pdf.
Rubin, Edward S., Inês M.L. Azevedo, Paulina Jaramillo, and Sonia Yeh. 2015. 'A Review of Learning Rates for Electricity Supply Technologies.' Energy Policy 86 (November 2015): 198–218. http://www.sciencedirect.com/science/article/pii/S0301421515002293.
Taylor, Phil. 2016. 'Nev. Plant Solves Quandary of How to Store Sunshine.' E&E News. March 29, 2016. http://www.eenews.net/stories/1060034748.
Turchi, C. 2010. Parabolic Trough Reference Plant for Cost Modeling with the Solar Advisor Model (SAM). Golden, CO: National Renewable Energy Laboratory. NREL/TP-550-47605. July 2010. http://www.nrel.gov/docs/fy10osti/47605.pdf.
Turchi, Craig S., and Garvin A. Heath. 2013. Molten Salt Power Tower Cost Model for the System Advisor Model (SAM). Golden, CO: National Renewable Energy Laboratory. NREL/TP-5500-57625. February 2013. http://www.nrel.gov/docs/fy13osti/57625.pdf.
Wiser, Ryan, and Mark Bolinger. 2016. 2015 Wind Technologies Market Report. August 2016. https://emp.lbl.gov/sites/default/files/2015-windtechreport.final_.pdf.
Wiser, Ryan, Karen Jenni, Joachim Seel, Erin Baker, Maureen Hand, Eric Lantz, and Aaron Smith. 2016. Forecasting Wind Energy Costs and Cost Drivers: The Views of the World's Leading Experts. Berkeley, CA: Lawrence Berkeley National Laboratory. LBNL-1005717. June 2016. https://emp.lbl.gov/publications/forecasting-wind-energy-costs-and.
Wiser, Ryan, Mark Bolinger, Galen Barbose, Naïm Darghouth, Ben Hoen, Andrew Mills, Samantha Weaver, Kevin Porter, Michael Buckley, Frank Oteri, and Suzanne Tegen. 2014. 2013 Wind Technologies Market Report. Washington, D.C.: U.S. Department of Energy. DOE/GO-102014-4459. August 2014. https://energy.gov/sites/prod/files/2014/08/f18/2013%20Wind%20Technologies%20Market%20Report_1.pdf.