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Offshore Wind Market Report: 2023 Edition

The Offshore Wind Market Report: 2023 Edition provides detailed information on the U.S. and global offshore wind energy industries to inform policymakers, researchers, and analysts about technology, economic, and market trends. The scope of the report covers the status of over 293 global operating offshore wind energy projects as well as the broader global pipeline of projects in various stages of development through December 31, 2022. To provide up-to-date information and discussion on this emerging industry in the United States, this report tracks the significant U.S. domestic industry progress and events from January 1, 2022, through May 31, 2023. The U.S. offshore wind energy project development pipeline has reached a potential generating capacity of over 52 gigawatts, and the industry has seen strong support from state and federal governments (such as from the Inflation Reduction Act of 2022 and the announced Floating Offshore Wind Shot to reduce the cost of floating wind by 70%). There are contracts for over 17 gigawatts of the electricity from these offshore wind projects and state policies are in place to procure over 42 gigawatts by 2040. Although some projects are facing economic headwinds due to rising costs and higher interest rates (corresponding to project cost increases of 11% - 30% in 2022), there has still been significant investment in a domestic supply chain (including manufacturing facilities, new vessels, and upgraded or planned ports). Technologies continue to evolve as offshore wind turbines in the 15-megawatt class advance towards commercial production. Key offshore wind energy market indicators, such as commercial leasing, state energy planning targets, procurement policies, offtake agreements, and federal support for U.S. jobs and supply chain development, point toward sustained market growth when viewed together, but the macroeconomic hurdles facing the first generation of commercial projects could significantly stunt that growth.

17 WIND ENERGY↗

Wind and Wildlife Co-Exist With Help From ECO Wind

Sustainable deployment of wind energy requires a balance of conservation, energy, and economic goals. The Enabling Coexistence Options for Wind Energy and Wildlife (ECO Wind) program at the U.S. Department of Energy National Renewable Energy Laboratory (NREL) supports efforts to reduce wildlife impacts at land-based and offshore wind energy facilities with monitoring and minimization technology solutions.

50 EE - Wind and Water Power Program - Water (EE-4↗

Proceedings of the 2021 Airborne Wind Energy Workshop

On March 2-3, 2021, the National Renewable Energy Laboratory (NREL) conducted a virtual workshop to evaluate the status, potential development, and technical viability of AWE systems as a source of energy in the United States. Stakeholder input provided at the workshop will contribute to the report to Congress. This report summarizes key workshop findings, current technology research and development activities in the United States, and opportunities and potential modes of collaboration and coordination for future technology research and development activities. The workshop focused on U.S. stakeholders in AWE, with approximately 100 experts and industry stakeholders from AWE technology developers, operators, engineering firms, consultants, government, national laboratories, and university researchers. The workshop began with an explanation from DOE's Wind Energy Technologies Office (WETO) Technology Manager, Ben Hallissy, of the context and purpose of the workshop, including a request from Congress that the U.S. Department of Energy (DOE) deliver a "report on the potential for, and technical viability of, airborne wind energy systems to provide a significant source of energy in the United States, including a summary of research, development, demonstration, and commercialization needs, including an estimate of Federal funding requirements, to further examine and validate the technical and economic viability of airborne wind energy concepts over the 10-year period." The workshop began with brief introductions from attendees who explained their interest in AWE. Nicolas El Hayek of Planair summarized the proceedings from the AWE workshop held in September 2020 by the International Energy Agency (IEA) Wind Task 11. This was followed by a presentation by Roland Schmehl of TU-Delft summarizing European AWE R&D efforts. Chris Vermillion of North Carolina State University and Jason Jonkman of NREL presented an overview of U.S. R&D efforts. Then five panelists discussed AWE markets, sizes of AWE systems, challenges, and opportunities. Panelists included: Cristina Archer, professor at the College of Earth, Ocean, and Environment and associate director at the Center for Research in Wind (CReW) at the University of Delaware; Stephan Brabeck, chief technology officer at SkySails; Thierry Delahave, innovation and technology development lead at Saipem; Rob Creighton, founder and chief executive officer at WindLift; and David Schaefer, founder and chief executive officer at eWind Solutions. The second day of the workshop began with a brief overview of five key topics that are crucial to enabling AWE in the United States. These topics range from estimates of the U.S. wind resource, technical generation potential, economic analysis, environmental challenges, status of current technology and R&D activities, and needed activities to enable commercialization of AWE. This set the stage for a robust discussion in breakout groups where individuals could offer their opinions on the potential opportunities for AWE in the United States. The following topics were discussed in the breakout groups: resource potential and energy output, technical potential, social and environmental impacts, and permitting, techno-economic analysis and markets, technology assessment and upscaling and demonstration and commercialization needs. The second day concluded with reports by the NREL research team, communicating the key themes and outcomes from each of the breakout group discussions.

17 WIND ENERGY↗

Grand Challenges in the Science of Wind Energy

The energy system of the future that depends on 80% or more renewable energy will put new demands on the wind systems that support it. There are significant areas of scientific uncertainly that need to be addressed to enable the innovation required for success. This presentation, based on a 2019 article in Science, lays out those areas of scientific challenges and proposes an integrated wind energy discipline that encompasses the needed research.

49 EE - Wind and Water Power Program - Wind (EE-4W↗

Development of a Metocean Reference Site near the Massachusetts and Rhode Island Wind Energy Areas

This project developed the first long-term U.S.-based offshore MetOcean Reference Site (MORS-1) by capitalizing on a unique combination of one of the few existing publicly available offshore wind energy metocean observational campaigns in the United States and the only existing research-grade offshore fixed tower. Data collected at MORS-1 has facilitated improved wind resource assessments, improved short-term power production estimates, and reduced costs for sensor validation and calibration efforts, which translate into reduced overall wind energy project risk and cost for developers. Now operational, MORS-1 serves the needs of both industry and researchers using a nonprofit, joint industry-academic partnership model. Led by the Woods Hole Oceanographic Institution, the MORS-1 development effort focused on creating both a recognized organizational structure that will ensure support of the MORS-1 by the wider wind energy industry and research community, and a highly validated data collection and sensor validation facility that will serve as the premier location for cost- and uncertainty-reducing resource characterization and research efforts.

17 WIND ENERGY↗

Gearing Up for 2030: Building the Offshore Wind Supply Chain and Workforce Needed to Deploy 30 GW and Beyond

This webinar addresses the current state and future needs of the U.S. offshore wind energy workforce and supply chain. During this webinar, National Renewable Energy Laboratory researchers Matt Shields and Jeremy Stefek will present new research on the challenges of producing thousands of offshore wind energy technology components while creating tens of thousands of U.S. jobs - and the solutions that can help meet those challenges. Topics covered in the webinar include port facilities, vessels, component manufacturing, trades and roles in the industry, workforce development and training, and the coordination of supply chain and workforce efforts between states and regions.

2030↗

WINDPROF: Merged Best-Estimate Wind Profile Data – Block Island (WFIP3 Campaign)

WINDPROF provides 10-minute wind and turbulence profiles, integrating Doppler lidars, wind profiling radars, and sonic anemometers across Northeast U.S. coastal/offshore sites during the WFIP3 campaign. Key data include wind speed, direction, vertical velocity, and turbulence parameters, with standardized quality control (e.g., instrument-specific thresholds and inter-instrument validation). Profiles are interpolated to a height grid (20 m spacing below 100 m; 30 m above) and include comprehensive uncertainty estimates. The Block Island dataset covers February 2024–September 2025, offering reproducible methods for atmospheric research, model validation, and wind energy studies.

17 WIND ENERGY↗

WINDPROF: Merged Best-Estimate Wind Profile Data – Nantucket (WFIP3 Campaign)

WINDPROF provides 10-minute wind and turbulence profiles, integrating Doppler lidars, wind profiling radars, and sonic anemometers across Northeast U.S. coastal/offshore sites during the WFIP3 campaign. Key data include wind speed, direction, vertical velocity, and turbulence parameters, with standardized quality control (e.g., instrument-specific thresholds and inter-instrument validation). Profiles are interpolated to a height grid (20 m spacing below 100 m; 30 m above) and include comprehensive uncertainty estimates. The Nantucket dataset covers February 2024–September 2025, offering reproducible methods for atmospheric research, model validation, and wind energy studies.

17 WIND ENERGY↗

WINDPROF: Merged Best-Estimate Wind Profile Data – Site A1 (AWAKEN Campaign)

WINDPROF provides 10-minute wind and turbulence profiles, integrating Doppler lidars and anemometers during the AWAKEN campaign. Key data include wind speed, direction, vertical velocity, and turbulence parameters, with standardized quality control (e.g., instrument-specific thresholds and inter-instrument validation). Profiles are interpolated to a height grid (20 m spacing below 100 m; 30 m above) and include uncertainty estimates, offering reproducible methods for atmospheric research, model validation, and wind energy studies.

17 WIND ENERGY↗

WINDPROF: Merged Best-Estimate Wind Profile Data – Site A2 (AWAKEN Campaign)

WINDPROF provides 10-minute wind and turbulence profiles, integrating Doppler lidars and anemometers during the AWAKEN campaign. Key data include wind speed, direction, vertical velocity, and turbulence parameters, with standardized quality control (e.g., instrument-specific thresholds and inter-instrument validation). Profiles are interpolated to a height grid (20 m spacing below 100 m; 30 m above) and include uncertainty estimates, offering reproducible methods for atmospheric research, model validation, and wind energy studies.

17 WIND ENERGY↗

WINDPROF: Merged Best-Estimate Wind Profile Data – Site H (AWAKEN Campaign)

WINDPROF provides 10-minute wind and turbulence profiles, integrating Doppler lidars and anemometers during the AWAKEN campaign. Key data include wind speed, direction, vertical velocity, and turbulence parameters, with standardized quality control (e.g., instrument-specific thresholds and inter-instrument validation). Profiles are interpolated to a height grid (20 m spacing below 100 m; 30 m above) and include uncertainty estimates, offering reproducible methods for atmospheric research, model validation, and wind energy studies.

17 WIND ENERGY↗

A Study of Wake Characteristics of Marine Turbine Arrays: Preprint

As the marine energy industry continues to develop and installations grow from single turbines to small arrays and larger farms, understanding and predicting wake behavior using modeling tools is necessary for array design and optimization. The wake characteristics of upstream turbines, including velocity deficit, wake swirling, tip vortices, wake shape and direction, and flow recovery, influence the inflow conditions experienced by downstream turbines in an array and, subsequently, affect the individual turbine loading and power generated by the array. These wake characteristics are influenced by many factors, including site geography, inflow shear profile, turbulence, waves, the strength of the current resource, gravitational forces, storm surges, and seasonal effects like temperature and wind conditions. Efficient array modeling tools that capture these wake effects and resulting turbine-to-turbine interactions need to be developed to optimize farm layouts and design individual turbines for operation within arrays. Unlike the wind industry, the marine energy research community is largely limited to the use of either numerical tools or tank/flume testing to understand marine turbine wake interactions. This paper will investigate recent advances in numerical and experimental marine turbine wake modeling, with a focus on recent publications and on both axial-flow and cross-flow marine turbines. A summary of recent research on these topics is provided. Additionally, a demonstration of turbine wake interactions using computational fluid dynamics is presented.

marine hydrokinetic turbine↗

Wind Turbine Drivetrain Reliability and Wind Plant Operations and Maintenance Research and Development Opportunities

The Drivetrain Reliability Collaborative holds annual meetings convened by the National Renewable Energy Laboratory, Argonne National Laboratory, and the U.S. Department of Energy to bring researchers and stakeholders throughout the wind turbine drivetrain supply, operations, and sustainment chain together to explore the state of the art in mechanical system reliability and operations and maintenance challenges that if solved could have significant benefits. Identification of these research and development opportunities are a prime focus of the meetings and are summarized in this report.

17 WIND ENERGY↗

Biases in preconstruction estimates of wind plant annual energy production

Estimating the energy yield of a wind plant during the preconstruction phase is a historically difficult task, even with industry improvements in these estimations. We build on prior research comparing the realized energy production of wind plants and their estimated annual energy production P50 values (median energy production), using owner-provided energy production and losses. We produced similar results to prior studies but with a slightly increasing bias of overestimating median energy production (a bias between realized and estimated energy production of −7.4 % to −6.6 %, depending on the scenario, as opposed to −6.7 % to −5.5 % from earlier studies). In addition to assessing annual energy production P50 bias, we compared both the 1-year and the long-term annual energy production P90 and uncertainty energy yield assessment estimates to the observed long-term-corrected energy production. We found that neither the energy yield assessment uncertainty nor the P90 is conservative enough compared to the observed distribution of prediction errors, suggesting significant room for improvement in the energy yield assessment process.

17 WIND ENERGY↗

Loss Factors for Small Distributed Wind Turbines Based on Field Data in the United States

While wind energy production loss due to unavailability, environmental impacts, curtailment, and other causes has been studied and characterized at the utility-scale wind farm level, observation-based characterization of project loss is lacking for distributed wind energy, particularly for projects involving small wind turbines. Contemporary tools and research that support pre-construction distributed wind energy characterization present a wide range of default loss factors to convert gross energy estimates to net: 7-18%. We hypothesize that we can use generation observations from operational distributed wind projects to develop more accurate representations of loss. Using a density-based filtering technique on distributed wind power generation timeseries, we determine periods of typical performance and use them with regression algorithms in a measure-correlate-predict fashion to simulate what the generation would have been during periods of atypical or unreported performance. From there, the actual versus predicted generation leads to the establishment of observation-informed loss factors (median = 17%) for small, single turbine installation distributed wind projects.

17 WIND ENERGY↗

Equations for Estimating the Strength of TV Signals Scattered by Wind Turbines

During the late 1970's and early 1980's, concerns about the potential interference of wind turbine generators with electromagnetic communication signals led to a series of research studies, both in the laboratory and in the field, conducted by the staff of the University of Michigan Radiation Laboratory. These studies were sponsored by organizations such as the U.S. Department of Energy, the Solar Energy Research Institute, and private developers of wind power stations. Research objectives were to identify the mechanisms by which wind turbines might adversely affect communication signals, estimate the severity of these effects for different types of signals (e.g. television, radio, microwave, and navigation), and formulate mathematical models with which to predict the sizes of potential interference zones around wind turbines and wind power plants. This work formed the basis for preliminary standards on assessing electromagnetic interference (EMI) by wind turbines. With the current renewal of interest in wind energy projects, it is appropriate that the many experimental and analytical aspects of this pioneering work be reviewed and correlated. The purpose of this study is to combine test data and theory from previously published and unpublished research reports into a unified and consistent set of equations which are useful for estimating potential levels of television interference from wind turbines. To be comprehensive, these equations will include both horizontal-axis and vertical-axis wind turbines (HAWT's and VAWT's), blade configuration parameters (e.g. number, size, material, twist, and coning), signal frequency and power, and directional characteristics of the receiving antenna. The approach that is followed in this report is as follows. First, some basic equations that describe electromagnetic signals with interference are presented without detailed derivations, since the latter are available in the references. Minor changes in terminology are made for purposes of consistency. Next, the concept of a signal scatter ratio is introduced, which defines the fraction of the signal impinging on a wind turbine that is scattered by its blades onto a nearby receiver. Equations from references are modified for the calculation of experimental scatter ratios (from measured signals containing interference) and idealized scatter ratios (from rotor characteristics and relative locations of the transmitter, the turbine, and the receiver). Experimental and idealized scatter ratios are then calculated and compared for 75 cases from the literature, in which TVI measurements were made around a variety of wind turbines. An empirical equation is then defined for estimating the probability that an actual scatter ratio will differ from an idealized ratio by a given amount. Finally a sample calculation of the size of a potential TV interference zone around a hypothetical wind power station is presented.

Spera, David A.↗

Offshore Wind Market Report: 2023 Edition [Slides]

The Offshore Wind Market Report: 2023 Edition provides detailed information on the U.S. and global offshore wind energy industries to inform policymakers, researchers, and analysts about technology, economic, and market trends. This presentation highlights the main points of the report to help provide a summary.

17 WIND ENERGY↗

Dynamometer Facts

The National Renewable Energy Laboratory's (NREL's) Flatirons Campus features four dynamometers that can perform research validation on wind turbine systems and ocean energy devices. These dynamometers can validate wave and water power systems over capacity ratings ranging from 1 kilowatt (kW) to 5 megawatts (MW) by replacing water with a controllable, electric motor. By combining these capabilities with other tools, such as the controllable grid interface (https://www.nrel.gov/grid/controllable-grid-interface.html), researchers can verify how their device interacts with the grid or integrates with other technologies.

16 TIDAL AND WAVE POWER↗