Annual Technology Baseline 2018
National Renewable Energy Laboratory
Recommended Citation:
NREL (National Renewable Energy Laboratory). 2018. 2018 Annual Technology Baseline. Golden, CO: National Renewable Energy Laboratory. http://atb.nrel.gov/.
Please consult Guidelines for Using ATB Data:
https://atb.nrel.gov/electricity/user-guidance.html
Offshore Wind
Representative Technology
In 2016, the first offshore wind plant commenced commercial operation in the United States near Block Island (Rhode Island). This demonstration project is 30 MW in capacity; in the ATB, cost and performance estimates are made for commercial-scale projects 600 MW in capacity. The ATB Base Year offshore wind plant technology reflects a machine rating of 3.4 MW with a rotor diameter of 115 m and hub height of 85 m, which is typical of European projects installed in 2015-2016.
Resource Potential
Wind resource is prevalent throughout major U.S. coastal areas, including the Great Lakes. The resource potential exceeds 2,000 GW (Musial et al. (2016)), excluding Alaska. Prior estimates of offshore wind resource potential (Schwartz et al. (2010)) were updated in 2016 to extend domain boundaries from 50 nautical miles (nm) to 200 nm, consider turbine hub heights of 100 m (previously 90 m), and assume a capacity array power density of 3 MW/km2 (Musial et al. (2016)). A range of technology exclusions were applied based on maximum water depth for deployment, minimum wind speed, and limits to floating technology in freshwater surface ice. Resource potential was represented by over 7,000 areas for offshore wind plant deployment after accounting for competing use and environmental exclusions, such as marine protected areas, shipping lanes, pipelines, and others.
Source: Musial et al. 2016
Renewable energy technical potential, as defined by Lopez et al. 2012, represents the achievable energy generation of a particular technology given system performance, topographic limitations, and environmental and land-use constraints. The primary benefit of assessing technical potential is that it establishes an upper-boundary estimate of development potential. It is important to understand that there are multiple types of potential-resource, technical, economic, and market (Lopez at al. 2012; NREL, "Renewable Energy Technical Potential").
Base Year and Future Year Projections Overview
Based on the Musial et al. (2016) resource assessment, LCOE was estimated at more than 7,000 areas (with a total capacity of approximately 2,000 GW) in Beiter et al. (2016), taking into consideration a variety of spatial parameters, such as wind speeds, water depth, distance from shore, distance to ports, and wave height. CAPEX, O&M, and capacity factor are calculated for each geographic location using engineering models, hourly wind resource profiles, and representative sea states. The spatial LCOE assessment served as the basis for estimating the ATB baseline LCOE in the Base Year 2016, weighted by the available capacity, for fixed-bottom and floating offshore wind technology.
The Base Year LCOE assumes a 3.4-MW turbine size and long-term average hourly wind profiles and it reflects the least-cost choice among three substructure types (Beiter et al. (2016)):
- Monopile (fixed-bottom)
- Jacket (fixed-bottom)
- Semi-submersible (floating).
The representative offshore wind plant size is assumed to be 600 MW (Beiter et al. (2016)). For illustration in the ATB, the full resource potential, represented by 7,000 areas, was divided into 15 techno-resource groups (TRGs), of which TRGs 1-5 are representative of fixed-bottom wind technology and TRGs 6-15 are representative of floating offshore wind technology. The capacity-weighted average CAPEX, O&M, and capacity factor for each group is presented in the ATB.
Future year projections are derived from estimated cost reduction potential for offshore wind technologies based partially on elicitation of over 160 wind industry experts (Wiser et al. (2016)). Estimates for 2016-2050 were adjusted from the 2016 ATB for inflation (2015$ to $2016$). The specific scenarios are:
- Constant Technology Cost Scenario: no change in CAPEX, O&M, or capacity factor from 2015 to 2050; consistent across all renewable energy technologies in the ATB
- Mid Technology Cost Scenario: LCOE percentage reduction from the Base Year equivalent to that corresponding to the Median Scenario (50% probability) in expert survey (Wiser et al. (2016))
- Low Technology Cost Scenario: LCOE percentage reduction from the Base Year equivalent to that corresponding to the Low scenario (10% probability) in the expert survey (Wiser et al. (2016)).
CAPital EXpenditures (CAPEX): Historical Trends, Current Estimates, and Future Projections
Capital expenditures (CAPEX) are expenditures required to achieve commercial operation in a given year. These expenditures include the wind turbine, the balance of system (e.g., site preparation, installation, and electrical infrastructure), and financial costs (e.g., development costs, onsite electrical equipment, and interest during construction) and are detailed in CAPEX Definition. In the ATB, CAPEX reflects typical plants and does not include differences in regional costs associated with labor, materials, taxes, or system requirements. The related Standard Scenarios product uses regional CAPEX adjustments. The range of CAPEX demonstrates variation with wind resource in the contiguous United States.
The following figure shows the Base Year estimate and future year projections for CAPEX costs. Three cost scenarios are represented: Constant, Mid, and Low technology cost cases. Historical data from land-based wind plants installed in the United States are shown for comparison to the ATB Base Year estimates. The estimate for a given year represents CAPEX of a new plant that reaches commercial operation in that year.
CAPEX estimates for 2016 correspond well with market data for plants installed in 2016. Projections reflect a continuation of the downward trend observed in the recent past and are anticipated to continue based on preliminary data for 2017 projects.
In the lower wind resource areas represented by TRGs 6-10, CAPEX is expected to grow as future wind turbine technology transitions to new platforms, including taller towers, larger rotors, and higher machine ratings. In the higher wind resource areas represented by TRGs 1-5, optimization of current wind turbine platforms will lead to lower CAPEX in future years.
Recent Trends
Actual land-based wind plant CAPEX (Wiser and Bolinger (2017)) is shown in box-and-whiskers format for comparison to the ATB current CAPEX estimates and future projections. provide statistical representation of CAPEX for about 65% of wind plants installed in the United States since 2007. CAPEX estimates should tend toward the low end of observed cost because no regional impacts or spur line costs are included. These effects are represented in the market data.
Base Year Estimates
For illustration in the ATB, all potential land-based wind plant areas were represented in 10 TRGs. These were defined by resource potential (GW) and have higher resolution on the highest-quality TRGs, as these are the most likely sites to be deployed, based on their economics.
TRG 1 represents the best 100 GW of wind, as determined by LCOE. TRG 2 represents the next best 200 GW, while TRG 3 represents the next best 400 GW, and TRG 4 represents the next best 800 GW. TRGs 5-9 all represent 1,600 GW of resource potential. TRG 10 represents the remaining 1,148 GW of available potential. This representation is based on the approach described in DOE (2015) and implemented with 2015 market data in Moné et al. (2017).
The following table summarizes the annual average wind speed range for each TRG, capacity-weighted average wind speed, cost and performance parameters for each TRG, and resource potential in terms of capacity and energy for each TRG. Typical land-based wind installations in 2015 and 2016 are associated with TRG4.
TRG Definitions for Land-Based Wind
| Techno-Resource Group (TRG) | Wind Speed Range (m/s) | Weighted Average Wind Speed (m/s) | Weighted Average CAPEX ($/kW) | Weighted Average OPEX ($/kW-yr) | Weighted Average Net CF (%) | Potential Wind Plant Capacity (GW) | Potential Wind Plant Energy (TWh) |
|---|---|---|---|---|---|---|---|
| TRG1 | 8.2-13.5 | 8.7 | 1,573 | 51 | 47.4% | 100 | 414 |
| TRG2 | 8.0-10.9 | 8.4 | 1,592 | 51 | 46.2% | 200 | 810 |
| TRG3 | 7.7-11.1 | 8.2 | 1,599 | 51 | 45.0% | 400 | 1,576 |
| TRG4 | 7.5-13.1 | 7.9 | 1,605 | 51 | 43.5% | 800 | 3,050 |
| TRG5 | 6.9-11.1 | 7.5 | 1,616 | 51 | 40.7% | 1,600 | 5,708 |
| TRG6 | 6.1-9.4 | 6.9 | 1,642 | 51 | 36.4% | 1,600 | 5,098 |
| TRG7 | 5.4-8.3 | 6.2 | 1,678 | 51 | 30.8% | 1,600 | 4,320 |
| TRG8 | 4.7-6.9 | 5.5 | 1,708 | 51 | 24.6% | 1,600 | 3,443 |
| TRG9 | 4.0-6.0 | 4.8 | 1,713 | 51 | 18.3% | 1,600 | 2,558 |
| TRG10 | 1.0-5.3 | 4.0 | 1,713 | 51 | 11.1% | 1,148 | 1,116 |
| Total | 10,648 | 28,092 | |||||
Future Year Projections
Mid: Projections of future LCOE were derived from a survey of wind industry experts (Wiser et al. (2016)) for scenarios that are associated with a 50% probability level in 2030 and 2050. Projections of future land-based wind plant CAPEX were determined based on adjustments to CAPEX, fixed O&M (FOM), and capacity factor in each year to result in a predetermined LCOE value derived from Wiser et al. (2016).
In order to achieve the overall LCOE reduction associated with the median and low projections from the expert survey, CAPEX was used to accommodate all improvement aspects other than O&M and capacity factor survey results. In the lower wind resource areas represented by TRGs 6-10, CAPEX is expected to grow as future wind turbine technology transitions to new platforms, including taller towers, larger rotors, and higher machine ratings. In the higher wind resource areas represented by TRGs 1-5, optimization of current wind turbine platforms will lead to lower CAPEX.
Low: Projections of future LCOE for the Low cost scenario were derived from an accelerated development pathway that included incremental improvements to technology through scaling and learning as well as innovation enabled by the DOE's Atmosphere to Electrons research program and anticipated scientific advances (Dykes et al. (2017)). The reductions in turbine and balance-of-system CAPEX were estimated by a survey of wind industry experts (Wiser et al. (2016)) focusing on detailed line item cost reduction potential. The results of the survey show a reduction in turbine and balance-of-system CAPEX by 2030 through turbine scaling with less material use and use of more efficient manufacturing processes. The accelerated decline in CAPEX is expected for all TRGs through 2030 except TRGs 9 and 10, where CAPEX is expected to slightly increase in the near term and then begin to decline at the same rate as the remaining TRGs. After 2030, the rate of CAPEX reduction is expected to continue but at a slower rate. As stated in Dykes et al. (2017), the wind turbine industry is expected to continue trends in scaling seen over the past several decades while learning processes will keep the per-unit power costs of these turbines at or below current levels. In addition, the turbine size increases will lead to economies of scale for the wind power plant through reductions in plant infrastructure and erection costs while science-enabled R&D pathways in turbine design will push materials and manufacturing costs of per-unit power to levels lower than those observed today.
A detailed description of the methodology for developing future year projections is found in Projections Methodology.
Technology innovations that could impact future O&M costs are summarized in LCOE Projections.
CAPEX Definition
Capital expenditures (CAPEX) are expenditures required to achieve commercial operation in a given year.
Based on EIA (2013), Moné et al. (2015), and Beiter et al. (2016), the System Cost Breakdown Structure of the ATB for the wind plant envelope is defined to include:
- Wind turbine supply
- Balance of system (BOS)
- Turbine installation, substructure supply and installation
- Site preparation, port and staging area support for delivery, storage, handling, and installation of underground utilities
- Electrical infrastructure, such as transformers, switchgear, and electrical system connecting turbines to each other (array cable system costs) and to the cable landfall (export cable system costs)
- Development and project management
- Financial costs
- Owners' costs, such as development costs, preliminary feasibility and engineering studies, environmental studies and permitting, legal fees, insurance costs, and property taxes during construction
- Interest during construction estimated based on three-year duration accumulated 40%/40%/20% at half-year intervals and an 8% interest rate (ConFinFactor).
CAPEX can be determined for a plant in a specific geographic location as follows:
Regional cost variations are not included in the ATB (CapRegMult = 1). In the ATB, the input value is overnight capital cost (OCC) and details to calculate interest during construction (ConFinFactor). Because transmission infrastructure between an offshore wind plant and the point at which a grid connection is made onshore is a significant component of the offshore wind plant cost, an offshore spur line cost (OffSpurCost) for each TRG is included in the CAPEX estimate. The offshore spur line cost reflects a capacity-weighted average of all potential wind plant areas within a TRG, similar to OCC.
In the ATB, CAPEX represents the capacity-weighted average values of all potential wind plant areas within a TRG and varies with water depth and distance from shore. Regional cost effects associated with labor rates, material costs, and other regional effects as defined by DOE 2015 expand the range of CAPEX. Unique land-based spur line costs for each of the 7,000 areas based on distance and transmission line costs expand the range of CAPEX even further. The following figure illustrates the ATB representative plants relative to the range of CAPEX including regional costs across the contiguous United States. The ATB representative plants are associated with a regional multiplier of 1.0.
Standard Scenarios Model Results
ATB CAPEX, O&M, and capacity factor assumptions for the Base Year and future projections through 2050 for Constant, Mid, and Low technology cost scenarios are used to develop the NREL Standard Scenarios using the ReEDS model. See ATB and Standard Scenarios.
CAPEX in the ATB does not represent regional variants (CapRegMult) associated with labor rates, material costs, etc., but the ReEDS model does include 134 regional multipliers (EIA (2013)).
The ReEDS model determines offshore spur line and land-based spur line (GCC) uniquely for each of the 7,000 areas based on distance and transmission line cost.
Natural Gas Internal Combustion Engine Vehicle
Operations and maintenance (O&M) costs represent the annual fixed expenditures required to operate and maintain a wind plant over its lifetime of 30 years, including:
- Insurance, taxes, land lease payments and other fixed costs (e.g., project management and administration, weather forecasting, and condition monitoring)
- Present value and annualized large component replacement costs over technical life (e.g., blades, gearboxes, and generators)
- Scheduled and unscheduled maintenance of wind plant components, including turbines and transformers, over the technical lifetime of the plant.
The following figure shows the Base Year estimate and future year projections for fixed O&M (FOM) costs. Three cost scenarios are represented. The estimate for a given year represents annual average FOM costs expected over the technical lifetime of a new plant that reaches commercial operation in that year. The range of Base Year O&M estimates reflects distance from shore and metocean conditions.
Base Year Estimates
FOM costs vary by distance from shore and metocean conditions. As a result, O&M costs vary from $106/kW-year (TRG 6) to $159/kW-year (TRG 5) in 2016. The capacity-weighted average in the ATB for fixed-bottom offshore technology (TRGs 1-5) is $148/kW-year; the corresponding value for floating offshore wind technology (TRGs 6-15) is $127/kW-year.
Future Year Projections
Future fixed-bottom offshore wind technology O&M is assumed to decline 7% by 2050 in the Mid cost case and 16% in the Low cost wind case, based on the expert survey conducted by Wiser et al. (2016).
Future floating offshore wind technology O&M is assumed to decline 7% by 2050 in the Mid cost case and 16% in the Low cost wind case, based on the expert survey conducted by Wiser et al. (2016).
A detailed description of the methodology for developing future year projections is found in Projections Methodology.
Technology innovations that could impact future O&M costs are summarized in LCOE Projections.
Capacity Factor: Expected Annual Average Energy Production Over Lifetime
The capacity factor represents the expected annual average energy production divided by the annual energy production, assuming the plant operates at rated capacity for every hour of the year. It is intended to represent a long-term average over the lifetime of the plant. It does not represent interannual variation in energy production. Future year estimates represent the estimated annual average capacity factor over the technical lifetime of a new plant installed in a given year.
The capacity factor is influenced by the rotor swept area/generator capacity, hub height, hourly wind profile, expected downtime, and energy losses within the wind plant. It is referenced to 100-m above-water-surface, long-term average hourly wind resource data from Musial et al. (2016).
The following figure shows a range of capacity factors based on variation in the wind resource, water depth, and distance from shore for offshore wind plants in the contiguous United States. Pre-construction estimates for offshore wind plants operating globally in 2015, according to the year in which plants were installed, is shown for comparison to the ATB Base Year estimates. The range of Base Year estimates illustrate the effect of locating an offshore wind plant in a variety of wind resource, water depth, and distance from shore conditions (TRGs 1-5 are fixed-bottom offshore wind plants and TRGs 6-15 are floating offshore wind plants). Future projections are shown for Constant, Mid, and Low technology cost scenarios.
Recent Trends
Pre-construction annual energy estimates from 93% of global operating wind capacity in 2016 (NREL's internal offshore wind database) is shown in a box-and-whiskers format for comparison with the ATB current estimates and future projections. The historical data illustrate pre-construction estimated capacity factors for projects by year of commercial online date. The range of capacity factors defined by the ATB TRGs compared well with the estimated capacity factors for projects installed in 2015.
Base Year Estimates
The capacity factor is determined using a representative power curve for a generic NREL-modeled offshore wind turbine (Beiter et al. (2016)) and includes geospatial estimates of gross capacity factors for the entire resource area (Musial et al. (2016)). The net capacity factor considers spatial variation in wake losses, electrical losses, turbine availability, and other system losses. For illustration in the ATB, all 7,000 wind plant areas are represented in 15 TRGs.
TRG Definitions for Offshore Wind
| TRG | LCOE Range ($/MWh) | Wind Speed Range (m/s) | Weighted Average Wind Speed (m/s) | Weighted Water Depth (m) | Weighted Distance Site to Cable Landfall (km) | Weighted Average CAPEX ($/kW) | Weighted Average OPEX ($/kW/yr) | Weighted Average Net CF (%) | Potential Wind Plant Capacity (GW) | Potential Wind Plant Energy (TWh) |
|---|---|---|---|---|---|---|---|---|---|---|
| Fixed-Bottom | ||||||||||
| TRG 1 | LCOE <= 141 | 8.5–9.0 | 8.6 | 13 | 6 | 3,800 | 137 | 45% | 12 | 49 |
| TRG 2 | LCOE <= 149 | 8.0–8.5 | 8.4 | 16 | 9 | 3,890 | 143 | 43% | 25 | 94 |
| TRG 3 | LCOE <= 157 | 8.0–8.5 | 8.3 | 19 | 15 | 4,027 | 145 | 42% | 50 | 182 |
| TRG 4 | LCOE <= 192 | 8.0–8.5 | 8.3 | 26 | 36 | 4,556 | 152 | 40% | 320 | 1,131 |
| TRG 5 | LCOE <= 306 | 7.5–8.0 | 7.9 | 36 | 72 | 5,333 | 159 | 37% | 320 | 1,023 |
| Floating | ||||||||||
| TRG 6 | LCOE <= 166 | 9.5–10 | 9.7 | 130 | 24 | 5,961 | 105 | 51% | 12 | 55 |
| TRG 7 | LCOE <= 175 | 9.5–10 | 9.7 | 145 | 40 | 6,217 | 108 | 50% | 25 | 108 |
| TRG 8 | LCOE <= 188 | 9.5–10 | 9.5 | 139 | 50 | 6,337 | 111 | 48% | 50 | 212 |
| TRG 9 | LCOE <= 206 | 9.0–9.5 | 9.4 | 136 | 70 | 6,687 | 122 | 47% | 100 | 414 |
| TRG 10 | LCOE <= 229 | 9.0–9.5 | 9.1 | 140 | 94 | 6,931 | 129 | 45% | 200 | 781 |
| TRG 11 | LCOE <= 252 | 8.5–9.0 | 8.7 | 323 | 118 | 7,211 | 134 | 42% | 200 | 727 |
| TRG 12 | LCOE <= 274 | 8.0–8.5 | 8.1 | 404 | 123 | 7,224 | 135 | 37% | 200 | 651 |
| TRG 13 | LCOE <= 299 | 7.5–8.0 | 7.8 | 474 | 138 | 7,411 | 136 | 35% | 200 | 615 |
| TRG 14 | LCOE <= 341 | 7.0–7.5 | 7.4 | 615 | 130 | 7,606 | 131 | 32% | 200 | 566 |
| TRG 15 | LCOE <= 438 | 7.5–8.0 | 7.5 | 797 | 199 | 8,204 | 138 | 31% | 143 | 390 |
| Total | 2,058 | 6,997 | ||||||||
Future Year Projections
Projections of capacity factors for plants installed in future years were determined based on estimates obtained through an expert survey conducted by Wiser et al. (2016) for both fixed-bottom and floating offshore wind technologies. Projections for capacity factors implicitly reflect technology innovations such as larger rotors and taller towers that will increase energy capture at the same geographic location without explicitly specifying tower height and rotor diameter changes.
A detailed description of the methodology for developing future year projections is found in Projections Methodology.
Technology innovations that could impact future O&M costs are summarized in LCOE Projections.
Standard Scenarios Model Results
ATB CAPEX, O&M, and capacity factor assumptions for the Base Year and future projections through 2050 for Constant, Mid, and Low technology cost scenarios are used to develop the NREL Standard Scenarios using the ReEDS model. See ATB and Standard Scenarios.
The ReEDS model output capacity factors for offshore wind can be lower than input capacity factors due to endogenously estimated curtailments determined by scenario constraints.
Plant Cost and Performance Projections Methodology
ATB projections were derived from the results of a survey of 163 of the world's wind energy experts Wiser et al. (2016). The survey was conducted to gain insight into the possible future cost reductions, the source of those reductions, and the conditions needed to enable continued innovation and lower costs (Wiser et al. (2016)). The expert survey produced three cost reduction scenarios associated with probability levels of 10%, 50%, and 90% of achieving LCOE reductions by 2030 and 2050. In addition, the scenario results include estimated changes to CAPEX, O&M, capacity factor, project life, and weighted average cost of capital (WACC) by 2030.
For the ATB, three different technology cost scenarios were adapted from the expert survey results for scenario modeling as bounding levels:
- Constant Technology Cost Scenario: no change in CAPEX, O&M, or capacity factor from 2015 to 2050; consistent across all renewable energy technologies in the ATB
- Mid Technology Cost Scenario: LCOE percentage reduction from the Base Year equivalent to that corresponding to the Median Scenario (50% probability) in the expert survey (Wiser et al. (2016))
- Low Technology Cost Scenario: LCOE percentage reduction from the Base Year equivalent to that corresponding to the Low scenario (10% probability) in the expert survey (Wiser et al. (2016)).
Expert survey estimates were normalized to the ATB Base Year starting point in order to focus on projected cost reduction instead of absolute reported costs. The percentage reduction in LCOE by 2020, 2030, and 2050 from the expert survey's Median and Low scenarios are implemented as the ATB Mid and Low cost scenarios. This is accomplished by utilizing survey estimates for changes to capacity factor and O&M costs by 2030 and 2050. The corresponding CAPEX value to achieve the overall LCOE reduction is computed. The percentage reduction in LCOE by 2030 and by 2050 was applied equally across all TRGs. The overall reduction in LCOE by 2050 for the Mid cost scenario is 39% and for the Low cost scenario is 51%.
A broad sample of cost of offshore wind energy projections provides context for the ATB Constant, Mid, and Low technology cost projections. Based on a TRG4 resource classification,[1] the ATB Mid cost projection, which corresponds to the median scenario from the Wiser et al. (2016) expert survey, results in LCOE reductions that are fairly aligned with the median scenarios of external studies (BNEF (2017c); IRENA (2016b); Catapult (2016); Lazard (2017)). EIA (2017b) estimates higher cost levels in the period 2022-2041, while BNEF (2018) estimates lower cost levels for the U.S by the mid-2020s. These external studies were reviewed to validate the baseline estimates and projections derived for the ATB. Generally, while some published studies as well as recent tender awards for European projects to be installed by the mid-2020s suggest significant near-term cost reduction (see e.g., Musial et al. (2017)), it is likely that the United States will lag due to a different development stage of the U.S. supply chain and port infrastructure.
The relative costs of mid-depth water plants and deep water, or floating, offshore wind plants are maintained constant throughout the scenarios for simplicity. Some hypothesize that unique aspects of floating technologies, such as the ability to assemble and commission turbines at the port, could reduce the cost of floating technologies relative to fixed-bottom technologies.
Levelized Cost of Energy (LCOE) Projections
Levelized cost of energy (LCOE) is a simple metric that combines the primary technology cost and performance parameters: CAPEX, O&M, and capacity factor. It is included in the ATB for illustrative purposes. The ATB focuses on defining the primary cost and performance parameters for use in electric sector modeling or other analysis where more sophisticated comparisons among technologies are made. The LCOE accounts for the energy component of electric system planning and operation. The LCOE uses an annual average capacity factor when spreading costs over the anticipated energy generation. This annual capacity factor ignores specific operating behavior such as ramping, start-up, and shutdown that could be relevant for more detailed evaluations of generator cost and value. Electricity generation technologies have different capabilities to provide such services. For example, wind and PV are primarily energy service providers, while the other electricity generation technologies provide capacity and flexibility services in addition to energy. These capacity and flexibility services are difficult to value and depend strongly on the system in which a new generation plant is introduced. These services are represented in electric sector models such as the ReEDS model and corresponding analysis results such as the Standard Scenarios.
The following three figures illustrate LCOE, which includes the combined impact of CAPEX, O&M, and capacity factor projections for off-shore wind across the range of resources present in the contiguous United States. For the purposes of the ATB, the costs associated with technology and project risk in the U.S. market are represented in the financing costs, not in the upfront capital costs (e.g. developer fees, contingencies). An individual technology may receive more favorable financing terms outside of the U.S., due to less technology and project risk, caused by more project development experience (e.g. offshore wind in Europe), or more government or market guarantees. The R&D Only LCOE sensitivity cases present the range of LCOE based on financial conditions that are held constant over time unless R&D affects them, and they reflect different levels of technology risk. This case excludes effects of tax reform, tax credits, technology-specific tariffs, and changing interest rates over time. The R&D + Market LCOE case adds to these the financial assumptions (1) the changes over time consistent with projections in the Annual Energy Outlook and (2) the effects of tax reform, tax credits, and tariffs. The ATB representative plant characteristics that best align with those of recently installed or anticipated near-term land-based wind plants are associated with TRG 4. Data for all the resource categories can be found in the ATB data spreadsheet.
R&D Only | R&D + Market
The methodology for representing the CAPEX, O&M, and capacity factor assumptions behind each pathway is discussed in Projections Methodology. In general, the degree of adoption of technology innovation distinguishes the Constant, Mid, and Low technology cost scenarios. These projections represent trends that reduce CAPEX and improve performance. Development of these scenarios involves technology-specific application of the following general definitions:
- Constant Technology = Base Year (or near-term estimates of projects under construction) equivalent through 2050 maintains current relative technology cost differences
- Mid Technology Cost Scenario = technology advances through continued industry growth, public and private R&D investments, and market conditions relative to current levels that may be characterized as "likely" or "not surprising"
- Low Technology Cost Scenario = Technology advances that may occur with breakthroughs, increased public and private R&D investments, and/or other market conditions that lead to cost and performance levels that may be characterized as the " limit of surprise" but not necessarily the absolute low bound.
- To estimate LCOE, assumptions about the cost of capital to finance electricity generation projects are required, and the LCOE calculations are sensitive to these financial assumptions. Three project finance structures are used within the ATB:
- R&D Only Financial Assumptions: This sensitivity case allows technology-specific changes to debt interest rates, return on equity rates, and debt fraction to reflect effects of R&D on technological risk perception, but it holds background rates constant at 2016 values from AEO 2018 and excludes effects of tax reform, tax credits, and tariffs.
- R&D Only + Market Financial Assumptions: This sensitivity case retains the technology-specific changes to debt interest, return on equity rates, and debt fraction from the R&D Only case and adds in the variation over time consistent with AEO 2018, as well as effects of tax reform, tax credits, and technology-specific tariffs. For a detailed discussion of these assumptions, see Changes from 2017 ATB to 2018 ATB.
- ReEDS Financial Assumptions: ReEDS uses the R&D Only + Market Financial Assumptions for the "Mid" technology cost scenario.
- A constant cost recovery period -over which the initial capital investment is recovered-is assumed for all technologies throughout this website, and can be varied in the ATB data spreadsheet.
- The equations and variables used to estimate LCOE are defined on the equations and variables page. For illustration of the impact of changing financial structures such as WACC, see Project Finance Impact on LCOE. For LCOE estimates for the Constant, Mid, and Low technology cost scenarios for all technologies, see 2018 ATB Cost and Performance Summary.
- In general, differences among the technology cost cases reflect different levels of adoption of innovations. Reductions in technology costs reflect the cost reduction opportunities that are listed below.
- Continued turbine scaling to larger-megawatt turbines with larger rotors such that swept area/megawatt capacity decreases resulting in higher capacity factors for a given location
- Greater market competition in the production of primary components (e.g., turbines, support structure), and installation services
- Economy-of-scale and productivity improvements in manufacturing, including mass production of substructure component and optimized installation strategies
- Improved plant siting and operation to reduce plant-level energy losses, resulting in higher capacity factors
- More efficient O&M procedures combined with more reliable components to reduce annual average FOM costs
- Adoption of a wide range of innovative control, design, and material concepts that facilitate the high-level trends described above.
Geothermal
Geothermal technology cost and performance projections will be more extensively updated upon completion of the Geothermal Vision Study. Until then, the projections are based on those documented in 2017 ATB - Geothermal, with the following changes:
- The dollar year was updated from 2015 to 2016 with 1.3% inflation.
- Technology-specific financial assumptions are included, as for other technologies in 2018 ATB, using data from Wall 2017.
Reference: Wall, A. M., Pl Dobson, H. Thomas (2017). "Geothermal Costs of Capital: Relating Market Valuation to Project Risk and Technology." Geothermal Resources Council Transactions, v. 41. https://www.geothermal-library.org/index.php?mode=pubs&action=view&record=1033704.
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, and battery storage technologies are shown in the associated portion of the ATB.
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 (2015)). 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.
https://nhaap.ornl.gov/2016-national-hydropower-map.
Renewable energy technical potential, as defined by Lopez et al. 2012, represents the achievable energy generation of a particular technology given system performance, topographic limitations, and environmental and land-use constraints. The primary benefit of assessing technical potential is that it establishes an upper-boundary estimate of development potential. It is important to understand that there are multiple types of potential-resource, technical, economic, and market (Lopez at al. 2012; NREL, "Renewable Energy Technical Potential").
Base Year and Future Year Projections Overview
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).
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
ATB CAPEX, O&M, and capacity factor assumptions for the Base Year and future projections through 2050 for Constant, Mid, and Low technology cost scenarios are used to develop the NREL Standard Scenarios using the ReEDS model. See ATB and Standard Scenarios.
The ReEDS model 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)):
- 1 MW 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, based on financial decisions in recent development activity, 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 30-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 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 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:
- Constant Technology Cost Scenario: no change in CAPEX, O&M, or capacity factor from 2015 to 2050; consistent across all renewable energy technologies in the ATB
- Mid Technology Cost Scenario: incremental technology learning, consistent with Reference in Hydropower Vision (DOE (2016)); CAPEX reductions for new stream-reach development (NSD) only
Standard Scenarios Model Results
ATB CAPEX, O&M, and capacity factor assumptions for the Base Year and future projections through 2050 for Constant, Mid, and Low technology cost scenarios are used to develop the NREL Standard Scenarios using the ReEDS model. See ATB and Standard Scenarios.
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)
- 30% to 80% capacity factor.
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 30-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 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 at 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:
- Constant Technology Cost Scenario: no change in CAPEX, O&M, or capacity factor from 2015 to 2050; consistent across all renewable energy technologies in the ATB
- Mid Technology Cost Scenario: incremental technology learning, consistent with Reference in Hydropower Vision (DOE (2016)); CAPEX reductions for NSD only
- Low Technology Cost Scenario: 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 the Base Year and future projections through 2050 for Constant, Mid, and Low technology cost scenarios are used to develop the NREL Standard Scenarios using the ReEDS model. See ATB and Standard Scenarios.
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, materials, taxes, or system requirements. The related Standard Scenarios product uses regional CAPEX adjustments. The range of CAPEX demonstrates variation with resource in the contiguous United States.
The following figure shows the Base Year estimate and future year projections for CAPEX costs. Three cost scenarios are represented: Constant, Mid, and Low technology cost. 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 of 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), lower 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 $7,900/kW. The estimates reflect potential sites with 3 feet of head to over 60 feet head and from 1 MW to more than 30 MW of capacity. In general, NSD potential represents smaller-capacity facilities with lower head than most historical data represent. These characteristics lead to higher CAPEX estimates than past data suggest, as many of the larger, higher head sites in the United States have been previously developed.
Base Year Estimates
For illustration in the ATB, all potential NPD and NSD sites were first binned by both head and capacity. Analysis of these bins provided groupings that represent the most realistic conditions for future hydropower deployment. The design values of these four reference NPD and four reference NSD plants are shown below. The full range of resource and design characteristics is summarized in the ATB data spreadsheet.
Representative Hydropower Plants
| Resource Characteristics Ranges | Weighted Average Values | Calculated Plant Values | |||||
|---|---|---|---|---|---|---|---|
| Plants | Head (feet) | Capacity (MW) | Head (feet) | Capacity (MW) | Capacity Factor | ICC (2014$/kW) | O&M (2014$/kW) |
| NPD 1 | 3-30 | 0.5-10 | 15.4 | 4.8 | 0.62 | 5,969.33 | 111.73 |
| NPD 2 | 3-30 | 10+ | 15.9 | 82.2 | 0.64 | 5,433.24 | 30.74 |
| NPD 3 | 30+ | 0.5-10 | 89.6 | 4.2 | 0.60 | 3,997.79 | 118.67 |
| NPD 4 | 30+ | 10+ | 81.3 | 44.7 | 0.60 | 3,769.22 | 40.54 |
| NSD 1 | 3-30 | 1-10 | 15.7 | 3.7 | 0.66 | 7,034.81 | 125.01 |
| NSD 2 | 3-30 | 10+ | 19.6 | 44.1 | 0.66 | 6,280.15 | 40.76 |
| NSD 3 | 30+ | 1-10 | 46.8 | 4.3 | 0.62 | 6,151.05 | 117.61 |
| NSD 4 | 30+ | 10+ | 45.3 | 94.0 | 0.66 | 5,537.34 | 28.93 |
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)).
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:
- Constant Technology Cost Scenario:
- NPD and NSD CAPEX unchanged from the Base Year; consistent across all renewable energy technologies in the ATB
- Mid Technology Cost Scenario: 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 Technology Cost Scenario: 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
A detailed description of the methodology for developing future year projections is found in Projections Methodology.
Technology innovations that could impact future O&M costs are summarized in LCOE Projections.
Standard Scenarios Model Results
ATB CAPEX, O&M, and capacity factor assumptions for the Base Year and future projections through 2050 for Constant, Mid, and Low technology cost scenarios are used to develop the NREL Standard Scenarios using the ReEDS model. See ATB and Standard Scenarios.
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 (BOS)
- 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
- Owners' 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:
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 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 Constant, Mid, and Low technology cost scenarios are used to develop the NREL Standard Scenarios using the ReEDS model. See ATB and Standard Scenarios.
CAPEX in the ATB does not represent regional variants (CapRegMult) associated with labor rates, material costs, etc., and neither does the ReEDS model.
CAPEX in the ATB does not include geographically determined spur line (GCC) from plant to transmission grid, and neither does the ReEDS model.
Natural Gas Internal Combustion Engine Vehicle
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 lifetime of 30 years, 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 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.
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:
- Constant Technology Cost Scenario: FOM costs unchanged from the Base Year to 2050; consistent with all ATB technologies
- Mid Technology Cost Scenario: FOM costs for both NPD and NSD plants are unchanged from 2015 to 2050; consistent with Reference in Hydropower Vision
- Low Technology Cost Scenario: 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 lifetime of the plant. It does not represent interannual variation in energy production. Future year estimates represent the estimated annual average capacity factor over the technical lifetime of a new plant installed in a given year.
The capacity factor is influenced by 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 the Constant, Mid, and Low technology cost scenarios are unchanged from the Base Year. Technology improvements are focused on CAPEX and O&M cost elements.
Recent Trends
Actual energy production from about 200 run-of-river plants operating in the United States from 2003 to 2012 (EIA 2016a) is shown in box-and-whiskers format for comparison with current estimates and future projections. This sample includes some very old plants that may have lower availability and efficiency losses. It also includes plants that have been relicensed and may no longer be optimally designed for current operating regime (e.g., a peaking unit now operating as run of river). This contributes to the broad range, particularly on the low end.
Interannual variation of hydropower plant output for run-of-river plants may be significant due to hydrological changes such as drought. This impact may be exacerbated by climate change over the long term.
Current and future estimates for new hydropower plants are within the range of observed plant performance. These potential hydropower plants would be designed for specific site conditions, which would indicate operation toward the high end of the range.
Base Year Estimates
For illustration in the ATB, all potential NPD and NSD sites are represented with four reference plants, each as described below.
Representative Hydropower Plants
| 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 | 5,969.33 | 111.73 |
| NPD 2 | 3-30 | 10 + | 15.9 | 82.2 | 0.64 | 5,433.24 | 30.74 |
| NPD 3 | 30 + | 0.5-10 | 89.6 | 4.2 | 0.60 | 3,997.79 | 118.67 |
| NPD 4 | 30 + | 10 + | 81.3 | 44.7 | 0.60 | 3,769.22 | 40.54 |
| NSD 1 | 3-30 | 1-10 | 15.7 | 3.7 | 0.66 | 7,034.81 | 125.01 |
| NSD 2 | 3-30 | 10 + | 19.6 | 44.1 | 0.66 | 6,280.15 | 40.76 |
| NSD 3 | 30 + | 1-10 | 46.8 | 4.3 | 0.62 | 6,151.05 | 117.61 |
| NSD 4 | 30 + | 10 + | 45.3 | 94.0 | 0.66 | 5,537.34 | 28.93 |
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 Constant, Mid, and Low technology cost scenarios 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:
- Constant Technology Cost Scenario: no change in CAPEX or OPEX from 2015 to 2050; consistent across all renewable energy technologies in the ATB
- Mid Technology Cost Scenario: incremental learning, consistent with Reference in the Hydropower Vision study (DOE (2016)); CAPEX reductions for NSD only
- Low Technology Cost Scenario: 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 ATB focuses on defining the primary cost and performance parameters for use in electric sector modeling or other analysis where more sophisticated comparisons among technologies are made. The LCOE accounts for the energy component of electric system planning and operation. The LCOE uses an annual average capacity factor when spreading costs over the anticipated energy generation. This annual capacity factor ignores specific operating behavior such as ramping, start-up, and shutdown that could be relevant for more detailed evaluations of generator cost and value. Electricity generation technologies have different capabilities to provide such services. For example, wind and PV are primarily energy service providers, while the other electricity generation technologies such as hydropower can provide capacity and flexibility services in addition to energy. These capacity and flexibility services are difficult to value and depend strongly on the system in which a new generation plant is introduced. These services are represented in electric sector models such as the ReEDS model and corresponding analysis results such as the Standard Scenarios.
The following three figures illustrate LCOE, which includes the combined impact of CAPEX, O&M, and capacity factor projections for hydropower across the range of resources present in the contiguous United States. For the purposes of the ATB, the costs associated with technology and project risk in the U.S. market are represented in the financing costs, not in the upfront capital costs (e.g. developer fees, contingencies). An individual technology may receive more favorable financing terms outside of the U.S., due to less technology and project risk, caused by more project development experience (e.g. offshore wind in Europe), or more government or market guarantees. The R&D Only LCOE sensitivity cases present the range of LCOE based on financial conditions that are held constant over time unless R&D affects them, and they reflect different levels of technology risk. This case excludes effects of tax reform, tax credits, technology-specific tariffs, and changing interest rates over time. The R&D + Market LCOE case adds to these the financial assumptions (1) the changes over time consistent with projections in the Annual Energy Outlook and (2) the effects of tax reform, tax credits, and tariffs. The ATB representative plant characteristics that best align with those of recently installed or anticipated near-term hydropower plants are associated with NPD 4. Data for all the resource categories can be found in the ATB data spreadsheet.
R&D Only | R&D + Market
The methodology for representing the CAPEX, O&M, and capacity factor assumptions behind each pathway is discussed in Projections Methodology. In general, the degree of adoption of technology innovation distinguishes the Constant, Mid, and Low technology cost scenarios. These projections represent trends that reduce CAPEX and improve performance. Development of these scenarios involves technology-specific application of the following general definitions:
- Constant Technology Cost Scenario = Base Year (or near-term estimates of projects under construction) equivalent through 2050 maintains current relative technology cost differences
- Mid Technology Cost Scenario = technology advances through continued industry growth, public and private R&D investments, and market conditions relative to current levels that may be characterized as "likely" or "not surprising"
- Low Technology Cost Scenario = Technology advances that may occur with breakthroughs, increased public and private R&D investments, and/or other market conditions that lead to cost and performance levels that may be characterized as the " limit of surprise" but not necessarily the absolute low bound.
To estimate LCOE, assumptions about the cost of capital to finance electricity generation projects are required, and the LCOE calculations are sensitive to these financial assumptions. Three project finance structures are used within the ATB:
- R&D Only Financial Assumptions: This sensitivity case allows technology-specific changes to debt interest rates, return on equity rates, and debt fraction to reflect effects of R&D on technological risk perception, but it holds background rates constant at 2016 values from AEO 2018 and excludes effects of tax reform, tax credits, and tariffs.
- R&D Only + Market Financial Assumptions: This sensitivity case retains the technology-specific changes to debt interest, return on equity rates, and debt fraction from the R&D Only case and adds in the variation over time consistent with AEO 2018, as well as effects of tax reform, tax credits, and technology-specific tariffs. For a detailed discussion of these assumptions, see Changes from 2017 ATB to 2018 ATB.
- ReEDS Financial Assumptions: ReEDS uses the R&D Only + Market Financial Assumptions for the "Mid" technology cost scenario.
A constant cost recovery period -over which the initial capital investment is recovered-is assumed for all technologies throughout this website, and can be varied in the ATB data spreadsheet.
- The equations and variables used to estimate LCOE are defined on the equations and variables page. For illustration of the impact of changing financial structures such as WACC, see Project Finance Impact on LCOE. For LCOE estimates for the Constant, Mid, and Low technology cost scenarios for all technologies, see 2018 ATB Cost and Performance Summary.
In general, differences among the technology cost cases reflect different levels of adoption of innovations. Reductions in technology costs reflect the cost reduction opportunities that are listed below.
- 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.
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").
DOE ("Nuclear Reactor Technologies")
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 givenyear.
Overnight capital costs are modified from EIA (2017). Capital costs include overnight capital cost plus defined transmission cost, and it removes a material price index.
| Overnight Capital Cost ($/kW) | Construction Financing Factor (ConFinFactor) | CAPEX ($/kW) | |
|---|---|---|---|
| Nuclear: Advanced nuclear power generation | $5,515 | 1.084 | $5,979 |
CAPEX can be determined for a plant in a specific geographic location as follows:
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.
Natural Gas Internal Combustion Engine Vehicle
Operations and maintenance (O&M) costs represent the annual expenditures required to operate and maintain a plant over its lifetime, including:
- Insurance, taxes, land lease payments, and other fixed costs
- Present value and annualized large component replacement costs over technical life
- Scheduled and unscheduled maintenance of power plants, transformers, and other components over the technical lifetime of the plant.
Market data for comparison are limited and generally inconsistent in the range of costs covered and the length of the historical record.
Capacity Factor: Expected Annual Average Energy Production Over Lifetime
The capacity factor represents the assumed annual energy production divided by the total possible annual energy production, assuming the plant operates at rated capacity for every hour of the year. For nuclear plants, the capacity factor is typically the same as (or very close to) their availability factor.
The capacity factor of nuclear units is generally very high (> 85%) as they are typically always online except when undergoing maintenance or refueling (NEI "US Nuclear Capacity Factors").
In the United States, nuclear power plants are baseload plants with steady capacity factors. They need to change out their uranium fuel rods about every 24 months. After 18-36 months, the used fuel is removed from the reactor (World Nuclear Association "The Nuclear Fuel Cycle"). The average fueling outage duration in 2013 was 41 days; from 1990 to 1997, the refueling days ranged from 66 to 106, so improvements have helped capacity factors (NEI, "US Nuclear Refueling Outage Days"). See also NEI ("US Nuclear Power Plants: General U.S. Nuclear Info").
Levelized Cost of Energy (LCOE) Projections
Levelized cost of energy (LCOE) is a simple metric that combines the primary technology cost and performance parameters: CAPEX, O&M, and capacity factor. It is included in the ATB for illustrative purposes. The ATB focuses on defining the primary cost and performance parameters for use in electric sector modeling or other analysis where more sophisticated comparisons among technologies are made. The LCOE accounts for the energy component of electric system planning and operation. The LCOE uses an annual average capacity factor when spreading costs over the anticipated energy generation. This annual capacity factor ignores specific operating behavior such as ramping, start-up, and shutdown that could be relevant for more detailed evaluations of generator cost and value. Electricity generation technologies have different capabilities to provide such services. For example, wind and PV are primarily energy service providers, while the other electricity generation technologies provide capacity and flexibility services in addition to energy. These capacity and flexibility services are difficult to value and depend strongly on the system in which a new generation plant is introduced. These services are represented in electric sector models such as the ReEDS model and corresponding analysis results such as the Standard Scenarios.
The following three figures illustrate LCOE, which includes the combined impact of CAPEX, O&M, and capacity factor projections for nuclear across the range of resources present in the contiguous United States. For the purposes of the ATB, the costs associated with technology and project risk in the U.S. market are represented in the financing costs, not in the upfront capital costs (e.g. developer fees, contingencies). An individual technology may receive more favorable financing terms outside of the U.S., due to less technology and project risk, caused by more project development experience (e.g. offshore wind in Europe), or more government or market guarantees. The R&D Only LCOE sensitivity cases present the range of LCOE based on financial conditions that are held constant over time unless R&D affects them, and they reflect different levels of technology risk. This case excludes effects of tax reform, tax credits, technology-specific tariffs, and changing interest rates over time. The R&D + Market LCOE case adds to these the financial assumptions (1) the changes over time consistent with projections in the Annual Energy Outlook and (2) the effects of tax reform, tax credits, and tariffs.
R&D Only | R&D + Market
The LCOE of nuclear power plants is directly impacted by the cost of uranium, variations in the heat rate, and O&M costs, but the biggest factor is the capital cost (including financing costs) of the plant. The LCOE can also be impacted by the amount of downtime from refueling or maintenance. For a given year, the LCOE assumes that the fuel prices from that year continue throughout the lifetime of the plant.
Fuel prices are based on the AEO 2017 (EIA 2017).
To estimate LCOE, assumptions about the cost of capital to finance electricity generation projects are required, and the LCOE calculations are sensitive to these financial assumptions. Three project finance structures are used within the ATB:
- R&D Only Financial Assumptions: This sensitivity case allows technology-specific changes to debt interest rates, return on equity rates, and debt fraction to reflect effects of R&D on technological risk perception, but it holds background rates constant at 2016 values from AEO 2018 and excludes effects of tax reform, tax credits, and tariffs. A constant cost recovery period-or period over which the initial capital investment is recovered-of 30 years is assumed for all technologies.
- R&D Only + Market Financial Assumptions: This sensitivity case retains the technology-specific changes to debt interest, return on equity rates, and debt fraction from the R&D Only case and adds in the variation over time consistent with AEO 2018, as well as effects of tax reform, tax credits, and tariffs. As in the R&D Only case, a constant cost recovery period-or period over which the initial capital investment is recovered-of 30 years is assumed for all technologies. For a detailed discussion of these assumptions, see Changes from 2017 ATB to 2018 ATB.
- ReEDS Financial Assumptions: ReEDS uses the R&D Only + Market Financial Assumptions for the "Mid" technology cost scenario.
These parameters are allowed to vary by year. The equations and variables used to estimate LCOE are defined on the equations and variables page. For illustration of the impact of changing financial structures such as WACC, see Project Finance Impact on LCOE. For LCOE estimates for the Constant, Mid, and Low technology cost scenarios for all technologies, see 2018 ATB Cost and Performance Summary.
References
2H 2017 Offshore Wind Market Outlook. Presentation by Tom Harries, accessed through BNEF subscription services.
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.
Innovation Outlook: Off shore Wind. Abu Dhabi: International Renewable Energy Agency.
Lazard's Levelized Cost of Energy Analysis: Version 11.0. November 2017. New York: Lazard. https://www.lazard.com/perspective/levelized-cost-of-energy-2017.
Levelized Cost and Levelized Avoided Cost of New Generation Resources in the Annual Energy Outlook 2017.
U.S. Offshore Wind. Presentation by Tom Harries, accessed through BNEF subscription services.
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.
Beiter, Philipp, Walter Musial, Aaron Smith, Levi Kilcher, Rick Damiani, Michael Maness, Senu Sirnivas, Tyler Stehly, Vahan Gevorgian, Meghan Mooney, and George Scott. 2016. A Spatial-Economic Cost-Reduction Pathway Analysis for U.S. Offshore Wind Energy Development from 2015-2030. Golden, CO: National Renewable Energy Laboratory. NREL/TP-6A20-66579. September 2016. http://www.nrel.gov/docs/fy16osti/66579.pdf.
Catapult. 2016. Cost Reduction Monitoring Framework. Quantitative Assessment Report. 19 December 2016.
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.
Dykes, K., M. Hand, T. Stehly, P. Veers, M. Robinson, E. Lantz. 2017. Enabling the SMART Wind Power Plant of the Future Through Science-Based Innovation (Technical Report), NREL/TP-5000-68123. National Renewable Energy Laboratory (NREL). Golden, CO (US). https://www.nrel.gov/docs/fy17osti/68123.pdf.
EIA (U.S. Energy Information Administration). 2013. Updated Capital Cost Estimates for Utility Scale Electricity Generating Plants. Washington, D.C.: U.S. Department of Energy, U.S. Energy Information Administration. https://www.eia.gov/outlooks/capitalcost/pdf/updated_capcost.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). 2018. Annual Energy Outlook 2018 with Projections to 2050. Washington, D.C.: U.S. Department of Energy. February 6, 2018. https://www.eia.gov/outlooks/aeo/pdf/AEO2018.pdf.
Entergy. 2015. Entergy Arkansas, Inc.: 2015 Integrated Resource Plan. July 15, 2015. http://entergy-arkansas.com/content/transition_plan/IRP_Materials_Compiled.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.
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.
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.
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.
Musial, W., P. Beiter, P. Schwabe, T. Tian, T. Stehly, P. Spitsen. 2017. 2016 Offshore Wind Technologies Market Report. U.S. Department of Energy Office of Energy Efficiency and Renewable Energy. DOE/GO-102017-5031. August 2017. https://www.energy.gov/sites/prod/files/2018/08/f35/2016%20Offshore%20Wind%20Technologies%20Market%20Report.pdf
Musial, Walt, Donna Heimiller, Philipp Beiter, George Scott, and Caroline Draxl. 2016. 2016 Offshore Wind Energy Resource Assessment for the United States. Golden, CO: National Renewable Energy Laboratory. NREL/TP-5000-66599. September 2016. http://www.nrel.gov/docs/fy16osti/66599.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.
ORNL (Oakridge National Laboratory). n.d. "New Stream-Reach Development Resource Assessment." National Hydropower Asset Assessment Program (NHAAP). http://nhaap.ornl.gov/nsd.
Schwartz, Marc, Donna Heimiller, Steve Haymes, and Walt Musial. 2010. Assessment of Offshore Wind Energy Resources for the United States. Golden, CO: National Renewable Energy Laboratory. NREL/TP-500-45889. June 2010. http://www.nrel.gov/docs/fy10osti/45889.pdf.
Wiser, Ryan, and Mark Bolinger. 2014. 2014 Wind Technologies Market Report. U.S. Department of Energy. DOE/GO-102015-4702. https://energy.gov/sites/prod/files/2015/08/f25/2014-Wind-Technologies-Market-Report-8.7.pdf.
Wiser, Ryan, and Mark Bolinger. 2017. 2016 Wind Technologies Market Report. https://www.energy.gov/sites/prod/files/2017/10/f37/2016_Wind_Technologies_Market_Report_101317.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.