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Annual Technology Baseline 2017

National Renewable Energy Laboratory


Recommended Citation:
NREL (National Renewable Energy Laboratory). 2017. 2017 Annual Technology Baseline. Golden, CO: National Renewable Energy Laboratory. http://atb.nrel.gov/.


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

Offshore Wind Power Plants

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.

Resource Potential

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

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

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

Base Year and Future Year Projections Overview

Based on the Musial et al. (2016) resource assessment, LCOE was estimated at more than 7,000 areas (with a total capacity of approximately 2,000 GW) in Beiter et al. (2016), taking into consideration a variety of spatial parameters, such as wind speeds, water depth, distance from shore, distance to ports, and wave height. CAPEX, O&M, and capacity factor are calculated for each geographic location using engineering models, hourly wind resource profiles, and representative sea states. The spatial LCOE assessment served as the basis for estimating the ATB baseline LCOE in the Base Year 2015, 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 sub-structure 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). 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 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 are used for ATB Mid and ATB Low cost scenarios. 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 water depth and distance from shore 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 offshore wind plants installed globally are shown for comparison to the ATB Base Year estimates (TRG 1–5 reflects fixed-bottom offshore wind plants and TRG 6–15 reflect floating offshore wind plants). The estimate for a given year represents CAPEX of a new plant that reaches commercial operation in that year.

chart: CAPEX historical trends, current estimates, and future projections for offshore wind in the 2017 ATB
Historical data shown in box-and-whiskers format where a bar represents the median, a box represents the 20th and 80th percentiles, and whiskers represent the minimum and maximum.
Year represents Commercial Online Date for a past or future plant.

Recent Trends

Actual wind plant CAPEX for European projects installed through 2015 are shown for comparison to the ATB Base Year CAPEX estimates and future projections. NREL's internal offshore wind database provides statistical representation of CAPEX for about 91% of offshore wind plants >100 MW commissioned in Europe and Asia from 2001 to 2015, based on installed capacity. All commercial-scale offshore wind plants installed to date have fixed-bottom substructures.

CAPEX estimates for the Base Year 2015 for TRGs 1–5, fixed-bottom technologies, tend to be lower than CAPEX for projects installed in 2015. The recent project installations represent characteristics in terms of water depth and distance from shore that generally align with those of TRG5. Floating technologies (TRGs 6–15) are not yet commercially deployed and are estimated to be higher cost than today's fixed-bottom project installations.

Base Year Estimates

For illustration in the ATB, offshore wind capacity was represented in 15 techno-resource groups (TRGs). Based on the share of capacity between fixed-bottom and floating technology estimated in Beiter et al. (2016), 5 TRGs were allocated to fixed-bottom technology (TRGs 1–5) (total capacity of 727 GW) and 10 TRGs to floating technology (TRGs 6–15) (total capacity of 1,330 GW). Available capacity for fixed-bottom and floating offshore wind technology was determined based on the least-cost choice between fixed-bottom and floating substructure types at more than 7,000 U.S. coastal areas in Beiter et al. (2016). Offshore wind locations were ranked by the LCOE estimated in Beiter et al. (2016) and binned into TRGs. The table below shows the capacity that was allocated by TRG. TRGs 1–3 (fixed-bottom) and 6–8 (floating) include less capacity than TRGs 4 and 5 (fixed bottom) and TRGs 9–15 to provide higher resolution at low levels of LCOE. The table also includes capacity-weighted average wind speed, water depth, distance from shore, cost and performance parameters, and resource potential in terms of capacity and energy for each TRG. Spatial conditions typically found in existing Bureau of Ocean Energy Management lease areas in the Northeast range from 10 m to 95 m in water depth (average of 32 m) and 3 km to 90 km in distance from shore (average of 22 km), corresponding to the average conditions in TRGs 3–5. Wind speeds found across existing Bureau of Ocean Energy Management lease areas in the Northeast generally tend to be more aligned with TRGs 1 and 2.

Offshore Wind TRG Definition
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 3,891 136 45% 12 49
TRG 2 LCOE <= 149 8.0–8.5 8.4 16 9 3,982 141 43% 25 94
TRG 3 LCOE <= 157 8.0–8.5 8.3 19 15 4,121 143 42% 50 182
TRG 4 LCOE <= 192 8.0–8.5 8.3 26 36 4,657 150 40% 320 1,131
TRG 5 LCOE <= 306 7.5–8.0 7.9 36 72 5,442 157 37% 320 1,023
Floating
TRG 6 LCOE <= 166 9.5–10 9.7 130 24 6,078 105 50% 12 55
TRG 7 LCOE <= 175 9.5–10 9.7 145 40 6,338 106 50% 25 108
TRG 8 LCOE <= 188 9.5–10 9.5 139 50 6,501 110 48% 50 212
TRG 9 LCOE <= 206 9.0–9.5 9.4 136 70 6,816 121 47% 100 414
TRG 10 LCOE <= 229 9.0–9.5 9.1 140 94 7,066 128 45% 200 781
TRG 11 LCOE <= 252 8.5–9.0 8.7 323 118 7,345 132 42% 200 727
TRG 12 LCOE <= 274 8.0–8.5 8.1 404 123 7,351 134 37% 200 651
TRG 13 LCOE <= 299 7.5–8.0 7.8 474 138 7,538 135 35% 200 615
TRG 14 LCOE <= 341 7.0–7.5 7.4 615 130 7,728 130 32% 200 566
TRG 15 LCOE <= 438 7.5–8.0 7.5 797 199 8,331 137 31% 143 390
Total 2,058 6,997

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, 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. Future fixed-bottom offshore wind technology CAPEX is assumed to decline 54% by 2050 in the Mid cost case and 62% in the Low cost wind case. Future floating offshore wind technology CAPEX is assumed to decline 49% by 2050 in the Mid cost case and 58% in the Low cost wind case.

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.

Based on EIA (2013), Moné et al. (2013 ), 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
    • Turbine installation, substructure supply and installation
    • Site preparation, port and staging area support for delivery, storage, handling, 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
    • 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
    • Interest during construction estimated based on three-year duration accumulated 40%/40%/20% at half year intervals and an 8% interest rate (ConFinFactor).

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

CAPEX = ConFinFactor*(OCC*CapRegMult+GCC), where GCC = OnSpurCost + OffSpurCost.

(See the Financial Definitions tab in the ATB data spreadsheet.)

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

In the ATB, CAPEX represents the capacity-weighted average values of all potential wind plant areas within a TRG and varies with water depth and distance from shore. Regional cost effects associated with labor rates, material costs, and other regional effects as defined by EIA (2013) 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.

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

Standard Scenarios Model Results

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

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

Operation and Maintenance (O&M) Costs

Operations and maintenance (O&M) costs represent the annual fixed expenditures 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 (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 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. The range of Base Year O&M estimates reflects distance from shore and metocean conditions.

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

Base Year Estimates

FOM costs vary by distance from shore and metocean conditions. As a result, O&M costs vary from $105/kW-year (TRG 6) to $157/kW-year (TRG 5) in 2015. The capacity-weighted average in the ATB for fixed-bottom offshore technology (TRGs 1-5) is $146/kW-year; the corresponding value for floating offshore wind technology (TRGs 6-15) is $125/kW-year.

Future Year Projections

Future fixed-bottom offshore wind technology O&M is assumed to decline 7.5% 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 7.5% 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 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 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 High, Mid, and Low cost scenarios.

chart: capacity factor (annual average energy production over plant lifetime) for offshore wind in the 2017 ATB
Historical data shown in box and whiskers format where a bar represents the median, a box represents the 20th and 80th percentiles, and whiskers represent the minimum and maximum.
Historical data represent pre-construction capacity factor estimates for plants with Commercial Online Date specified by year.
Projection data represent expected annual average CF for plants with Commercial Online Date specified by year.

Recent Trends

Pre-construction annual energy estimates from 93% of global operating wind capacity in 2015 (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 (see table).

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 CF 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 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 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 the 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 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 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 39% and for the Low cost scenario is 51%.

A broad sample of cost of wind energy projections are shown to provide context for the ATB High, Mid, and Low cost projections. In general, the ATB Mid cost projection reflects median values of the full population of literature; the ATB Low cost projection is similar to the low bound of the literature in the later years. While some published studies as well as recent project announcements for European projects to be installed by 2020 suggest significant near-term cost reduction, it is likely that the United States will lag due to a lack of industry infrastructure. Because the expert survey provided LCOE Projections that are related to each other in terms of probability, these scenarios are used in the ATB to represent two distinct levels of technology improvement pathways.

chart: plant cost and performance projections methodology for offshore wind in the 2017 ATB

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 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 offshore wind plants are associated with TRGs 3-5. Data for all the resource categories can be found in the ATB data spreadsheet.

Current Market Conditions
Historical Market Conditions
Normalized

The ATB representative plant characteristics that best align with recently installed or anticipated near-term offshore wind plants are associated with TRGs 3-5.

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

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

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

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

These parameters are held constant for estimates representing the Base Year through 2050. No incentives such as the PTC or ITC are included. The equations and variables used to estimate LCOE are defined on the equations and variables page. For illustration of the impact of changing financial structures such as WACC and economic life, see Project Finance Impact on LCOE. For LCOE estimates for High, Mid, and Low scenarios for all technologies, see 2017 ATB Cost and Performance Summary.

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.

Natural Gas Plants

A gas-fired combustion turbine involves:

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

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

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

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

Cutaway of combustion gas turbine

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

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

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

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

Comparison with Other Sources

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

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

CAPEX Definition

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

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

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

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

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

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

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

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

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

Operation and Maintenance (O&M) Costs

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

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

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

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

Capacity Factor: Expected Annual Average Energy Production Over Lifetime

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

The capacity factors of dispatchable units is typically a function of the unit's marginal costs and local grid needs (e.g., need for voltage support or limits due to transmission congestion). The average capacity factor is the average fleet-wide capacity factor for these plant types in 2015. The high capacity factor is taken from EIA (2016c, Table 1a) for a new power plant and represents a high bound of operation for a plant of this type.

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

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

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

Levelized Cost of Energy (LCOE) Projections

Levelized cost of energy (LCOE) is a simple metric that combines the primary technology cost and performance parameters, CAPEX, O&M, and capacity factor. It is included in the ATB for illustrative purposes. The focus of the ATB is to define the primary cost and performance parameters for use in electric sector modeling or other analysis where more sophisticated comparisons among technologies are made. LCOE captures the energy component of electric system planning and operation, but the electric system also requires capacity and flexibility services to operate reliably. Electricity generation technologies have different capabilities to provide such services. For example, wind and PV are primarily energy service providers, while the other electricity generation technologies provide capacity and flexibility services in addition to energy. These capacity and flexibility services are difficult to value and depend strongly on the system in which a new generation plant is introduced. These services are represented in electric sector models such as the ReEDS model and corresponding analysis results such as the Standard Scenarios.

The following three figures illustrate the combined impact of CAPEX, O&M, and capacity factor projections across the range of resources present in the contiguous United States. The Current Market Conditions LCOE demonstrates the range of LCOE based on macroeconomic conditions similar to the present. The Historical Market Conditions LCOE presents the range of LCOE based on macroeconomic conditions consistent with prior ATB editions and Standard Scenarios model results. The Normalized LCOE (all LCOE estimates are normalized with the lowest Base Year LCOE value) emphasizes the relative effect of fuel price and heat rate independent of project finance assumptions. The ATB representative plant characteristics that best align with recently installed or anticipated near-term natural gas plants are associated with Gas-CC-HighCF. Data for all the resource categories can be found in the ATB data spreadsheet.

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

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

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

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

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

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

These parameters are held constant for estimates representing the Base Year through 2050. No incentives such as the PTC or ITC are included. The equations and variables used to estimate LCOE are defined on the equations and variables page. For illustration of the impact of changing financial structures such as WACC and economic life, see Project Finance Impact on LCOE. For LCOE estimates for High, Mid, and Low scenarios for all technologies, see 2017 ATB Cost and Performance Summary.

Biopower Plants

In a biopower plant:

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

Renewable energy technical potential, as defined by Lopez et al. (2012), represents the achievable energy generation of a particular technology given system performance, topographic limitations, and environmental and land-use constraints. Technical resource potential for biopower is based on estimated biomass quantities from the Billion Ton Update study (DOE 2011).

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

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

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

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

CAPEX Definition

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

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

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

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

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

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

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

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

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

Operation and Maintenance (O&M) Costs

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

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

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

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

Capacity Factor: Expected Annual Average Energy Production Over Lifetime

The capacity factor represents the assumed annual energy production divided by the total possible annual energy production, assuming the plant operates at rated capacity for every hour of the year. For biopower plants, the capacity factors are typically lower than their availability factors. Biopower plant availability factors have a wide range depending on system design, fuel type and availability, and maintenance schedules.

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

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

chart: Biopower net capacity factor (dedicated and cofire).
Current estimates and future projections calculated from EIA (2017) and modified.

Levelized Cost of Energy (LCOE) Projections

Levelized cost of energy (LCOE) is a simple metric that combines the primary technology cost and performance parameters, CAPEX, O&M, and capacity factor. It is included in the ATB for illustrative purposes. The focus of the ATB is to define the primary cost and performance parameters for use in electric sector modeling or other analysis where more sophisticated comparisons among technologies are made. LCOE captures the energy component of electric system planning and operation, but the electric system also requires capacity and flexibility services to operate reliably. Electricity generation technologies have different capabilities to provide such services. For example, wind and PV are primarily energy service providers, while the other electricity generation technologies provide capacity and flexibility services in addition to energy. These capacity and flexibility services are difficult to value and depend strongly on the system in which a new generation plant is introduced. These services are represented in electric sector models such as the ReEDS model and corresponding analysis results such as the Standard Scenarios.

The following three figures illustrate the combined impact of CAPEX, O&M, and capacity factor projections across the range of resources present in the contiguous United States. The Current Market Conditions LCOE demonstrates the range of LCOE based on macroeconomic conditions similar to the present. The Historical Market Conditions LCOE presents the range of LCOE based on macroeconomic conditions consistent with prior ATB editions and Standard Scenarios model results. The Normalized LCOE (all LCOE estimates are normalized with the lowest Base Year LCOE value) emphasizes the relative effect of fuel price and heat rate independent of project finance assumptions. Data for all the resource categories can be found in the ATB data spreadsheet.

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

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

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

The projections do not include any cost of carbon.

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

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

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

These parameters are held constant for estimates representing the Base Year through 2050. No incentives such as the PTC or ITC are included. The equations and variables used to estimate LCOE are defined on the equations and variables page. For illustration of the impact of changing financial structures such as WACC and economic life, see Project Finance Impact on LCOE. For LCOE estimates for High, Mid, and Low scenarios for all technologies, see 2017 ATB Cost and Performance Summary.

References

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.

Brattle Group (Samuel A. Newell, J. Michael Hagerty, Kathleen Spees, Johannes P. Pfeifenberger, Quincy Liao, Christopher D. Ungate, and John Wroble). 2014. Cost of New Entry Estimates for Combustion Turbine and Combined Cycle Plants in PJM. The Brattle Group. http://www.brattle.com/system/publications/pdfs/000/005/010/original/Cost_of_New_Entry_Estimates_for_Combustion_Turbine_and_Combined_Cycle_Plants_in_PJM.pdf.

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.

E3 (Energy and Environmental Economics). 2014. Capital Cost Review of Power Generation Technologies: Recommendations for WECC's 10- and 20-Year Studies. Prepared for the Western Electric Coordinating Council. https://www.wecc.biz/Reliability/2014_TEPPC_Generation_CapCost_Report_E3.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). 2015. Annual Energy Outlook with Projections to 2040. Washington, D.C.: U.S. Department of Energy. DOE/EIA-0383(2015). April 2015. http://www.eia.gov/outlooks/aeo/pdf/0383(2015).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). 2016c. Levelized Cost and Levelized Avoided Cost of New Generation Resources in the Annual Energy Outlook 2017. Washington, D.C.: U.S. Department of Energy. April 2017. https://www.eia.gov/outlooks/aeo/pdf/electricity_generation.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.

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., et al. 2013. Reference to come.

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.

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.

PGE (Portland General Electric). 2015. Integrated Resource Plan 2016. July 16, 2015. https://www.portlandgeneral.com/-/media/public/our-company/energy-strategy/documents/2015-07-16-public-meeting.pdf.

PSE (Puget Sound Energy). 2016. 2017 IRP Supply-Side Resource Advisory Committee: Thermal. July 25, 2016. https://pse.com/aboutpse/EnergySupply/Documents/IRP_07-25-2016_Presentations.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.

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.