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Offshore Wind

2021 ATB data for offshore wind are shown above. Wind Resource Class 3 is displayed by default as it is most representative of near-term U.S. fixed-bottom offshore wind projects. More details surrounding Wind Resource Classes are provided below in Resource Categorization.

The following chart shows the LCOE scenario results presented above normalized for a comparison with literature projections. 

Future costs for three ATB technology innovation scenarios are derived by modeling initial year costs and then applying temporal cost reductions from experiential learning curves as well as economies of turbine size and plant scale. A learning rate for the supply chain is obtained based on a regression of global offshore wind project data. Separate capital (CAPEX) and operation and maintenance expenditure (OPEX) reduction trajectories are derived for each technology innovation scenario based on the assumed 2030 turbine capacity and level of assumed global offshore wind deployment. 

These cost reduction trajectories are applied to initial cost estimates which were modeled in NREL's Offshore Regional Cost Analyzer (ORCA) tool for thousands of potential offshore wind sites across major U.S. coastal areas (Beiter et al., 2016). Costs are reported for commercial-scale projects of 1,000 MW.  Since those initial modeled estimates were taken as the 2018 values from the 2020 ATB, the baseline offshore wind costs in 2019 (COD—commercial operation date) for the 2021 ATB result from one year of cost reducing learning and upsizing effects relative to that initial modeled year. Future cost scenarios through 2030 (COD) are determined using the same learning curve and economies of size methodology. Higher turbine ratings in future years also reduce wake losses and were modeled to thereby increase the annual energy production of an offshore wind plant. Costs beyond 2030 are obtained by extrapolating the cost trends estimated for 2019–2030 (COD).

The three technology innovation scenarios are centered around turbine rating and globally installed offshore wind capacity:

  • Conservative Technology Innovation Scenario (Conservative Scenario): turbine size remaining at a level consistent with the technology solutions available in today's markets; limited advancements in technology innovation are characteristic of this scenario. Logistical and manufacturing constraints are similar to those today, and they limit turbine size growth. Globally installed wind capacity in 2030 is assumed to be 60% less than under the Moderate Scenario, or 102 GW and 4.9 GW for fixed-bottom and floating respectively.
  • Moderate Technology Innovation Scenario (Moderate Scenario): turbine size increasing at a rate commensurate with growth in recent years; logistical, manufacturing, operating and performance constraints are addressed by technology innovation in turbine, substructure, port and vessel capabilities to enable the next generation of offshore wind technology; these increases in turbine size are accompanied by continued increases in supply chain efficiencies. Global offshore wind deployment in 2030 is assumed to be 204 GW and 9.7 GW, representing averages of literature estimates for fixed-bottom and floating respectively ((Global Wind Energy Council, 2020)(Wood Mackenzie, 2020)(Equinor, 2020)(Hannon et al., 2019)(4C Offshore, 2020)).
  • Advanced Technology Innovation Scenario (Advanced Scenario): turbine size increasing at a rate that is considerably higher than in recent years; accelerated technology innovation enables large turbine systems and fundamentally changes the manufacturing, installation, operation, and performance of a wind plant. Globally installed wind capacity in 2030 is assumed to be 60% more than under the Moderate Scenario, or 305 GW and 14.5 GW for fixed-bottom and floating respectively.

In the following sections, the offshore wind ATB estimates are explored in greater detail. First, the offshore wind resource in the U.S. is categorized and split into different wind classes. Then, the cost reduction pathways are outlined for each of the technology innovation scenarios before the representative turbine technologies are detailed. Finally, the cost modeling methodology is presented via its main components: CAPEX, OPEX, and Annual Energy Production (AEP).

Resource Categorization

The U.S. offshore wind technical resource potential exceeds 2,000 gigawatts (GW) (Musial et al., 2016), after accounting for exclusions that are due to water depth, minimum wind speed, limits to floating technology in freshwater surface ice, competing uses and environmental exclusions, marine protected areas, shipping lanes, pipelines, and other factors.

In the 2021 ATB, each of the potential wind sites represented by this technical resource potential is binned into 14 wind resource classes, which are organized by substructure technology type, wind speed, and costs. Wind Resource Classes 1–7 represent fixed-bottom offshore wind technology, and Wind Resource Classes 8–14 represent floating offshore wind technology (see the tables below). Sites are assigned to either fixed-bottom resource if they are located in water depths that are shallower than 60 meters (m) or to floating resource if the water depth exceeds 60 m.

For each substructure type, the break points for the wind resource classes occur at selected percentiles of the total wind resource technical potential. This specification is applied separately for each substructure type. For example, the most favorable resource class (Wind Resource Class 1) is defined to represent the top 2% of all potential wind capacity offshore of the contiguous United States in terms of wind speed and costs. We specify a narrower percentile range for the top classes so that the NREL Regional Energy Deployment System (ReEDS) model has higher-resolution representation for the most favorable sites because they are more likely to be developed in the near-to medium term. In ReEDS, these percentiles are applied to a representation of the wind resource using only the most basic exclusions and based on analysis from the Renewable Energy Potential (reV) model (Maclaurin et al., 2019).

The following tables show the percentile ranges assumed for each resource class and the resulting mean 100 m wind speed ranges that define each class for fixed-bottom (first table) and floating offshore (second table) technologies in ReEDS (Lopez et al.,2021 forthcoming). The annual mean wind speeds, averaged for all years between 2007 and 2013 and by wind resource class, range from 5.9–10.0 m/s for fixed-bottom technology to 6.0–11.3 m/s for floating technology. Because of the different resource potential that each wind resource class represents (e.g., Wind Resource Class 1 represents nearly 2% whereas Wind Resource Class 7 represents 36% of the total resource potential), there is not necessarily a consistent trend in average cost and site parameters from Wind Resource Classes 1–7 (fixed-bottom) and 8–14 (floating). For instance, the average water depth for floating sites does not increase consistently because of the variation in resource potential each wind resource class represents. These wind class categories are consistent with those used to represent the full wind resource in ReEDS (Brown et al., 2020). In previous editions of the ATB, these wind resource classes were referred to as techno-resource groups (TRGs) with the total wind resource technical potential divided into 5 fixed-bottom and 10 floating classes. TRG break points in previous ATB editions are different from the representation of the wind resource classes in the 2021 ATB. The TRG methodology is described in Appendix H of the Wind Vision Study (DOE 2015) and in earlier versions of the ATB documentation.

Fixed-Bottom Offshore Wind Resource Classes

Wind Resource ClassMin. Wind Speed (m/s)Max. Wind Speed (m/s)Average Wind Speed (m/s)Wind Speed Range (m/s)Percentile Range of Total Resource Potential (%)
19.9810.3310.240.35<2%
29.319.989.820.672%–4%
39.139.319.200.184%–8%
48.859.139.000.288%–16%
57.948.858.400.9116%–32%
67.077.937.440.8632%–64%
76.007.076.561.0764%–100%

Floating Offshore Wind Resource Classes

Wind Resource ClassMin. Wind Speed (m/s)Max Wind Speed (m/s)Average Wind Speed (m/s)Wind Speed Range (m/s)Percentile Range of Total Resource Potential (%)
810.3011.4710.571.17<2%
910.1810.3010.230.122%–4%
1010.0110.1810.090.174%–8%
119.6010.019.810.418%–16%
128.849.609.230.7616%–32%
137.438.848.041.4132%–64%
145.987.436.951.4564%–100%

Wind Resource Class 3 best represents the resource characteristics of near-term deployment for fixed-bottom technology along the U.S. East Coast such as Vineyard Wind; Wind Resource Class 12 most closely represents our most recent assessment of the resource characteristics of mid-term deployment for floating technology in the California Call Areas defined by the Bureau of Ocean Energy Management (BOEM) (Beiter et al., 2020). These wind speed classes were determined to be most comparable to the site conditions and cost characteristics of commercial-scale projects with an anticipated COD before 2030.

Scenario Descriptions

Various technology innovations and cost drivers are considered in the ATB cost projection scenarios. Future cost changes represented in the 2021 ATB scenarios are attributed to changes in turbine size, size-agnostic innovations, and increased supply chain efficiencies and learning. The technology innovations listed in the following table are structured around the assumed turbine trajectory for the 2021 ATB. The effects from turbine size increases are estimated from techno-economic cost models. Changes in the supply chain and from the introduction of size-agnostic innovations are captured in the learning curve effects.

Summary of Technology Innovation by Scenario (2030)

ScenarioTurbine SizeSupply ChainSize-Agnostic Innovations
Conservative Scenario

Technology Description: Turbines are rated at 12 MW. Moderate retooling of blade manufacturing facilities is needed. Projects rely on existing and announced wind turbine installation vessels.

Justification: This turbine size is currently tested as a prototype (Haliade-X), and these turbines are available for purchase in global markets. The technological and logistical challenges associated with a 12-MW turbine and strategies to overcome them are fairly well understood. Adjustments to U.S. port and vessel infrastructure are underway to accommodate this turbine size. So far only two Jones Act compliant wind turbine installation vessels have been announced. There remains uncertainty as to whether future global vessel demand can be met with existing and announced wind turbine installation vessels, given the volume of scheduled offshore wind projects. U.S. project developers have ordered 12-MW turbine ratings, and it is expected they will be deployed in the early- to mid-2020s.

Technology Description: This scenario assumes a supply chain that generates efficiency gains below the levels of the past few years. Under this scenario, the 12-MW turbine would be mounted on a monopile or jacket substructure using existing technology/materials. The turbine system is installed and operated using moderately enhanced port infrastructure and vessel capabilities.

Justification: The U.S. port infrastructure and vessel fleet is currently being developed with 12-MW turbine designated as the anticipated near-term technology by most original equipment manufacturers (OEMs), manufacturers, and project developers. The Charybdis, the first Jones Act-compliant wind turbine installation vessel, is already under construction for Dominion Energy and is expected to be completed in 2023.

Technology Description: There is limited integration of high-fidelity modeling and advanced controls.

Justification: Sustained wind plant technology that would be in operation today with only incremental improvements provide the justification.

 

Moderate Scenario

Technology Description: Turbines are rated at 15 MW. Major retooling of blade manufacturing facilities is needed, and major adjustments must be made to drivetrain and control technologies. Also, a 15-MW turbine is expected to require large generator bearings and pitch/yaw drive actuators.

Justification: 15 MW have been announced by major turbine OEMs. Vestas aims to have its V236 15.0-MW turbine commercially available in 2024—the same year Siemens Gamesa aims to have the SG 14-222 DD (15-MW with Power Boost option) on the market. The technological and logistical challenges of these turbines are somewhat understood. It is expected that 15-MW turbines might be paired with floating substructures, which might be able to overcome some of the logistical and port constraints in installation and maintenance. Although this turbine rating is expected to be market ready before 2030, there is some uncertainty whether these turbines will widely be operating in U.S. markets by this date; this uncertainty stems in part from limitations in current blade design and the procurement of turbine installation vessels or alternative installation strategies.

Technology Description: This scenario assumes a supply chain that generates efficiency gains commensurate with the levels of the past few years. Under this scenario, the 15-MW turbine would be mounted on a fixed-bottom or floating substructure using improved and highly tailored technology/materials. The turbine system is installed and operated using greatly enhanced port infrastructure and vessel capabilities relative to what exists today.

 

Justification: This scenario would necessitate a growth rate in installed global offshore wind capacity commensurate with the rate in the last few years. In the U.S. this means Efficiency gains are achieved through standardization, economies of scale, and increased competition.

Technology Description: High levels of integration of high-fidelity modeling, measurement, and advanced control strategies. These are used for better site understanding and optimization of operation and maintenance (O&M) strategies at the turbine, plant and fleet levels.

Justification: Increasing digitization and analysis of operational data is already a trend in the offshore wind industry. It is expected that these tools will be widely adopted in combination with a 15-MW turbine by 2030.

Advanced Scenario

Technology Description: Turbines are rated at 18 MW. Next-generation drivetrain and blade materials need to be combined with new turbine installation and maintenance methods.

Justification: Although an 18-MW prototype might be available by the early 2030s, it remains questionable whether turbines of this size will be commercially operating widely by 2030. New testing capacity would have to be developed and next-generation materials and installation/operation regimes would be required to enable these turbines. These enhanced capabilities are not yet well understood.

Technology Description: This scenario assumes a supply chain that generates efficiency gains above the level of the past few years.

Justification: This scenario would necessitate a growth rate in installed global offshore wind capacity above the rate of the last few years. Under this scenario, the 18-MW turbine would be mounted on a fixed-bottom or floating substructure using next-generation technology/materials, and port infrastructure and vessel capabilities. Efficiency gains are achieved through accelerated standardization, large economies of scale and fiercely increased competition.

 

Technology Description: Next-generation plant optimization, high-fidelity modeling and advanced controls are available. These capabilities are needed to better understand atmospheric sciences and forecasting and make use of novel sensing technologies and measurement techniques, computational sciences, digitalization, big data, and information/data science.

Justification: Though next generation tools and methods are not yet well understood, they are explored in research settings and might be available in combination with an 18-MW turbine rating by 2030.

Impacts
  • CAPEX and OPEX reductions from economies of scale
  • Capacity factor increases through reduced wake losses with higher rated turbine capacity
  • CAPEX and OPEX reductions from lower fabrication and maintenance costs.
  • CAPEX and OPEX reductions from lower fabrication and maintenance costs; capacity factor increases through improved understanding, measurement and response of wind regimes
References

Representative Technology

Cost and performance estimates in the Base Year are intended to represent a commercial-scale project of 1,000 MW in capacity. The Base Year technology reflects a machine rating of 6 MW with a rotor diameter of 150 m and hub height of 100 m, which is typical of European projects installed in 2019 and the turbine rating installed at the Block Island Wind Farm (GE Haliade 150-6MW). For the 2021 ATB cost projections, this representative technology evolves to a 15-MW turbine (Moderate Scenario), 12-MW (Conservative Scenario), and 18-MW (Advanced Scenario) turbine rating by 2030. Four substructure types are represented in the cost estimates: jacket and monopile (fixed-bottom) and semi-submersible and spar (floating technology). The table below summarizes key technology details for each technology innovation scenario.

Turbine Technology Details by Scenario

Methodology

This section describes the methodology to develop assumptions for CAPEX, O&M, and capacity factor. For standardized assumptions, see labor costregional cost variationmaterials cost indexscale of industrypolicies and regulations, and inflation.

The first step involves taking the Base Year values from the 2020 ATB and then applying learning and scaling cost reductions to bring forward these values from 2018 to 2019. The 2018 baseline costs were estimated at more than 7,000 potential offshore wind sites using an updated version of NREL's Offshore Regional Cost Analyzer (ORCA) (Beiter et al., 2016). ORCA considers various spatial parameters, including wind speeds, water depth, distance from shore, distance to ports, and wave height. CAPEX, O&M, and capacity factor are calculated for each location using (bottom-up) techno-economic models, hourly wind resource profiles, and representative sea states. Only sites that exceed a distance to cable landfall of 30 kilometers (km) and a water depth of 10 meters (m) are included in this spatial assessment because these are more likely to be developed in the near-to-medium term. ORCA determines the least-cost substructure appropriate for the water depth from four options: monopile (fixed-bottom), jacket (fixed-bottom), semi-submersible (floating), and spar (floating) (Beiter et al., 2016).

Next, cost projections between the Base Year and 2030 (COD) are derived from a combination of cost reductions from learning and economies of size and scale stemming from future technology. For quantifying future costs in the Moderate Scenario between 2019 and 2030, the cost modeling focuses on the impact of:

  • Turbine and Plant Upsizing: NREL's Offshore Renewable Balance-of-system Installation Tool (ORBIT) is used to assess the impacts of turbine and plant upsizing. The impact from greater turbine size reflects in lower CAPEX and O&M costs and higher annual energy production because of reduce wake losses (when turbine spacing is held constant).
  • Supply Chain Efficiencies and Learning: An analysis is conducted to assess the learning rate of the supply chain using empirical project data from (Musial et al., 2019) and NREL's FORCE model. The FORCE model is a regression based tool used to calculate the learning rate for offshore wind CAPEX while controlling for exogenous variables such as water depth, distance to shore, project country, plant capacity, and rated turbine capacity. This learning rate is then translated into cost reductions using the methodology (Beiter et al., 2020) based on assumed levels of global offshore wind deployment in 2030 COD associated with the different ATB technology and innovation scenarios. Because empirical data for OPEX are unavailable to derive a learning curve, the learning rate is assumed to be the same as that of CAPEX.
  • The technology innovation scenarios are distinguished using different assumptions about turbine ratings in 2030. The Moderate Scenario reflects a turbine rating of 15 MW, the Advanced Scenario an 18-MW turbine rating, and the Conservative Scenario a 12-MW turbine rating. The wind plant size is held constant at 1,000 MW in all future years considered, which is consistent with the Base Year assumptions.

Finally, the cost reductions for all scenarios between 2030 and 2050 are extrapolated (i.e., logarithmic fit) based on the estimated trend between 2019 and 2030 (COD). The resulting cost and performance assumptions are validated using an assessment of the first commercial-scale offshore wind projects announced in the United States (e.g., (Beiter et al., 2019)). For instance, Wind Resource Class 3 is assessed to represent the cost and performance characteristics of near-term project deployments of fixed-bottom technology, such as Vineyard Wind.

Capital Expenditures (CAPEX)

Definitions: Capital expenditures (CAPEX) are expenditures required to achieve commercial operation in a given year. In the ATB, CAPEX reflects typical plants and does not include differences in regional costs associated with labor, materials, taxes, or system requirements. The range of CAPEX demonstrates variation with spatial site parameters in the contiguous United States.

Based on (Moné et al., 2015) and (Beiter et al., 2016), the CAPEX of the 2021 ATB for the wind plant envelope is defined to include items noted in the Summary of Technology Innovation by Scenario table above. CAPEX within the ATB represents the capacity-weighted average values of all potential wind plant areas within a wind resource class and varies with water depth, metocean conditions, and distance from shore.

Base Year: 2021 ATB estimates for CAPEX in the Base Year are derived by using the learning curve methodology described above to bring forward the 2020 ATB Base Year (2018) values, which were calculated using an updated version of NREL's Offshore Regional Cost Analyzer (ORCA) (Beiter et al., 2016)

ORCA calculates CAPEX based on various spatial parameters including water depth, distance from shore, distance to ports, and wave height. Array cable, export cable, and an onshore spur line to the nearest grid feature are accounted for in the CAPEX costs. CAPEX estimates are calibrated to correspond to the latest cost and technology trends observed in the U.S. and European offshore wind markets, including:

  • Turbine CAPEX: CAPEX of approximately $1,300/kW are assumed for the Base Year to account for decreases in turbine CAPEX that are observed in global offshore wind markets.
  • Turbine Rating: Turbine technology trends of 8 MW (Base Year), 10 MW (2022 COD), 12 MW (2027 COD), and 15 MW (2030 COD) are assumed to correspond to recent technology trends in the Moderate Scenario.
  • Cost Reduction Trajectory: Recent literature is surveyed to identify the most up-to-date cost reduction trends expected for U.S. and European offshore wind projects; cost reduction trajectories are estimated with the learning curve methodology described above as well as turbine and plant upsizing impacts.

Future Years: CAPEX improvements are driven by an increase in turbine rating, learning from enhanced supply chain efficiencies, and size-agnostic technology innovations.

The following chart illustrates the current scenarios along with historical CAPEX data for offshore wind.

To better illustrate the cost categories included in CAPEX, the following table outlines line items unique to offshore wind as well as those included across with technologies.

CAPEX Breakdown

The following chart indicated how major CAPEX line items change with foundation technology in the Base Year scenarios. Costs are broken into broad categories. The balance of system (BOS) covers the upfront CAPEX for installing the wind plant and its components except for the turbine. Soft costs include insurance, project financing, construction contingency costs, and decommisioning costs.

Operation and Maintenance (O&M) Costs

Definition: O&M costs represent the annual fixed expenditures required to operate and maintain a wind plant over its lifetime, including items noted in the Summary of Technology Innovation by Scenario table above.

Base Year: Fixed operation and maintenance (FOM) costs vary by distance from shore and metocean conditions.

Future Years: OPEX change from experiential learning and from an increase in turbine rating.

Use the following table to view the cost components of O&M.

OPEX Breakdown

Capacity Factor

Definition: 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).

Base Year: The capacity factor for the Base Year is also determined by bringing the 2020 ATB Base Year (2018) values forward one year to 2019. They were originally developed using a representative power curve for a generic NREL-modeled 6-MW offshore wind turbine (Beiter et al., 2016), and they include 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. Each wind resource class represents the capacity weighted average of its resource potential.

In the following chart, preconstruction annual energy estimates from publicly available global operating wind capacity in 2018 (Musial et al., 2019) are shown in a box-and-whiskers format for comparison. The range of capacity factors is estimated based on variation in the wind resource for offshore wind plants in the contiguous United States. The range of Base Year estimates illustrates the effect of locating an offshore wind plant in a variety of wind resources.

Future Years: Projections of capacity factors for plants installed in future years are determined based on increasing turbine size and size-agnostic innovations. Under constant turbine spacing, these yield reduced wake losses and thereby, higher annual energy production. Advanced controls are assumed to be partially responsible for improvements in future turbine performance.

References

The following references are specific to this page; for all references in this ATB, see References.

Hannon, Dr. Matthew, Eva Topham, James Dixon, Dr. David McMillian, and Dr. Maurizio Collu. “Offshore Wind, Ready to Float? Global and UK Trends in the Floating Offshore Wind Market,” 2019. https://brandcentral.dnvgl.com/fr/gallery/10651/others/694b3feb674e460198df6db6ba003861/694b3feb674e460198df6db6ba003861_low.pdf?utm_campaign=EN_Publication_Autoresponder_V2_PDF&utm_medium=email&utm_source=Eloqua.

4C Offshore. “4C Offshore Wind Farms Intelligence,” 2020. http://www.4coffshore.com/windfarms/request.aspx?id=owfdb.

Wood Mackenzie. “Foresight 20/20: Onshore & Offshore Wind.” Foresight 20/20: Onshore & Offshore Wind, 2020. https://www.woodmac.com/our-expertise/focus/Power--Renewables/wind-foresight-2020/?utm_source=gtm&utm_medium=article&utm_campaign=wmpr_fs2020wind.

Global Wind Energy Council. “Global Offshore Wind Report 2020.” Global Offshore Wind Report 2020, August 2020. https://gwec.net/wp-content/uploads/2020/12/GWEC-Global-Offshore-Wind-Report-2020.pdf.

Beiter, Philipp, Walter Musial, Aaron Smith, Levi Kilcher, Rick Damiani, Michael Maness, Senu Sirnivas, et al. “A Spatial-Economic Cost-Reduction Pathway Analysis for U.S. Offshore Wind Energy Development from 2015-2030.” Technical Report. Golden, CO: National Renewable Energy Laboratory, 2016. https://doi.org/10.2172/1324526.

Beiter, Philipp, Walt Musial, Patrick Duffy, Aubryn Cooperman, Matt Shields, Donna Heimiller, and Mike Optis. “The Cost of Floating Offshore Wind Energy in California between 2019 and 2032.” NREL Technical Report. Golden, CO, November 2020. https://www.nrel.gov/docs/fy21osti/77384.pdf.

Brown, Maxwell, Wesley Cole, Kelly Eurek, Jon Becker, David Bielen, Ilya Chernyakhovskiy, Stuart Cohen, et al. “Regional Energy Deployment System (ReEDS) Model Documentation: Version 2019.” Technical Report. National Renewable Energy Laboratory, March 2020. https://doi.org/10.2172/1606151.

Maclaurin, Galen, Nick Grue, Anthony Lopez, and Donna Heimiller. “The Renewable Energy Potential (ReV) Model: A Geospatial Platform for Technical Potential and Supply Curve Modeling.” Technical Report. National Renewable Energy Laboratory, September 2019. https://doi.org/10.2172/1563140.

Musial, Walt, Donna Heimiller, Philipp Beiter, George Scott, and Caroline Draxl. “2016 Offshore Wind Energy Resource Assessment for the United States.” Technical Report. Golden, CO: National Renewable Energy Laboratory, September 2016. https://doi.org/10.2172/1324533.

Lloyd’s Register. “LR and NETSCo to Develop Jones Act Compliant Wind Turbine Installation Vessel,” December 16, 2020. https://www.lr.org/en-gb/latest-news/1217-lr-and-netsco-to-develop-jones-act-compliant-wind-turbine-installation-vessel/.

Dominion Energy. “Dominion Energy Continues Development of First Jones Act Compliant Offshore Wind Turbine Installation Vessel,” December 16, 2020. https://news.dominionenergy.com/2020-12-16-Dominion-Energy-Continues-Development-of-First-Jones-Act-Compliant-Offshore-Wind-Turbine-Installation-Vessel.

Rystad Energy. “The World May Not Have Enough Heavy Lift Vessels to Service the Offshore Wind Industry Post 2025,” November 25, 2020. https://www.rystadenergy.com/newsevents/news/press-releases/the-world-may-not-have-enough-heavy-lift-vessels-to-service-the-offshore-wind-industry-post-2025/.

Siemens Gamesa Renewable Energy. “Powered by Change: Siemens Gamesa Launches 14 MW Offshore Direct Drive Turbine with 222-Meter Rotor,” May 19, 2020. https://www.siemensgamesa.com/en-int/newsroom/2020/05/200519-siemens-gamesa-turbine-14-222-dd.

Vestas Wind Systems A/S. “Vestas Launches the V236-15.0 MW to Set New Industry Benchmark and Take next Step towards Leadership in Offshore Wind,” February 10, 2020. https://www.vestas.com/en/media/company-news?l=42&n=3886820#!NewsView.

Musial, Walter, Philipp Beiter, Paul Spitsen, and Jake Nunemaker. “2018 Offshore Wind Technologies Market Report.” Technical Report. Golden, CO: National Renewable Energy Laboratory, December 2019. https://doi.org/10.2172/1226783.

Gaertner, Evan, Jennifer Rinker, Latha Sethuraman, Frederik Zahle, Benjamin Anderson, Garrett Barter, Nikhar Abbas, et al. “IEA Wind TCP Task 37:  Definition of the IEA 15-Megawatt Offshore Reference Wind.” Technical Report. Golden, CO: National Renewable Energy Laboratory, March 2020. https://doi.org/10.2172/1603478.

Hundleby, Giles, Kate Freeman, Andy Logan, and Ciaran Frost. “Floating Offshore: 55 Technology Innovations That Will Have Greater Impact on Reducing the Cost of Electricity from European Floating Offshore Wind Farms.” KiC InnoEnergy, and BVG Associates, 2017. http://www.innoenergy.com/new-floating-offshore-wind-report-55-technology-innovations-that-will-impact-the-lcoe-in-floating-offshore-wind-farms/.

Valpy, Bruce, Giles Hundleby, Kate Freeman, Alun Roberts, and Andy Logan. “Future Renewable Energy Costs: Offshore Wind: 57 Technology Innovations That Will Have Greater Impact on Reducing the Cost of Electricity From European Offshore Wind Farms.” KiC InnoEnergy, and BVG Associates, 2017. https://bvgassociates.com/wp-content/uploads/2017/11/InnoEnergy-Offshore-Wind-anticipated-innovations-impact-2017_A4.pdf.

Beiter, Philipp, Paul Spitsen, Walter Musial, and Eric Lantz. “The Vineyard Wind Power Purchase Agreement: Insights for Estimating Costs of U.S. Offshore Wind Projects.” Technical Report. Golden, CO: National Renewable Energy Laboratory, 2019. https://doi.org/10.2172/1495385.

Moné, C., A. Smith, B. Maples, and M. Hand. “2013 Cost of Wind Energy Review.” Technical Report. Golden, CO: National Renewable Energy Laboratory, February 2015. https://doi.org/10.2172/1172936.


Developed with funding from the U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy.

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