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.
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.
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").
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):
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:
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.
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.
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.
|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)|
|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|
|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|
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.
Capital expenditures (CAPEX) are expenditures required to achieve commercial operation in a given year.
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.
ATB CAPEX, O&M, and capacity factor assumptions for the Base Year and future projections through 2050 for High, Mid, and Low projections are used to develop the NREL Standard Scenarios using the ReEDS model. See ATB and Standard Scenarios.
The ReEDS model 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.
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:
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.
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 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.
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.
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.
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).
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.
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.
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:
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.
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) 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.
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:
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.
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.
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.
EIA (U.S. Energy Information Administration). 2016a. Capital Cost Estimates for Utility Scale Electricity Generating Plants. Washington, D.C.: U.S. Department of Energy. November 2016. https://www.eia.gov/analysis/studies/powerplants/capitalcost/pdf/capcost_assumption.pdf.
EIA (U.S. Energy Information Administration). 2017. Annual Energy Outlook 2017 with Projections to 2050. Washington, D.C.: U.S. Department of Energy. January 5, 2017. http://www.eia.gov/outlooks/aeo/pdf/0383(2017).pdf.
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.
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.
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.