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All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

The Wind Energy Workforce Gap in the United States

There are more than 100,000 jobs in the U.S. wind industry today, and the second-fastest growing job in the United States in 2017 was wind technician. A vibrant wind industry needs workers, and students who graduate from wind energy education and training programs need jobs. The goal of this research is to better understand the needs of wind-related businesses, education and training requirements, and the make-up of current and future domestic workforces. Educators are developing and training future workers. Educational institutions need to know which courses to provide to connect students with potential employers and to justify their wind energy programs by being able to place graduates into well-paying jobs. In interviews with 250 wind energy firms and 50 educational institutions, many respondents reported difficulty hiring qualified candidates, while many educational institutions reported graduates not finding jobs in the wind industry. We refer to this mismatch as the 'workforce gap.' This conference poster explores this gap.

17 WIND ENERGY↗
DOE OSTI2016

Offshore Wind Energy

In 1991, the Vindeby Offshore Wind Farm, the first offshore wind farm in the world, started feeding electricity to the grid off the coast of Lolland, Denmark. Since then, offshore wind energy has developed from this early experiment to a multibillion dollar market and an important pillar of worldwide renewable energy production. Unit sizes grew from 450 kW at Vindeby to the 7.5 MW-class offshore wind turbines (OWT ) that are currently (by October 2014) in the prototyping phase. This chapter gives an overview of the state of the art in offshore wind turbine (OWT) technology and introduces the principles of modeling and simulating an OWT. The OWT components -- including the rotor, nacelle, support structure, control system, and power electronics -- are introduced, and current technological challenges are presented. The OWT system dynamics and the environment (wind and ocean waves) are described from the perspective of OWT modelers and designers. Finally, an outlook on future technology is provided. The descriptions in this chapter are focused on a single OWT -- more precisely, a horizontal-axis wind turbine -- as a dynamic system. Offshore wind farms and wind farm effects are not described in detail in this chapter, but an introduction and further references are given.

17 WIND ENERGY↗
DOE OSTI2019

Distributed Cooperative Control of Wind Farms with On-Site Battery Energy Storage Systems

This chapter studies the output power regulation in wind farms consisting of doubly-fed induction generator wind turbines, one of the most popular generator configurations in modern multi-MW wind industry, equipped with on-site battery energy storage systems. Traditionally, wind farms were operated as standalone units or were equipped with a central, large-scale, energy storage system. In fact, most of the existing control designs for hybrid wind-storage applications are centralized, where the central unit collects the measured data from all wind turbines and storage systems (if they exist) and compares with the load demand to generate the reference power for each wind turbine controller. Those centralized setups or control structures do not fully exploit the flexibility and locality of the on-site energy storage systems in a wind farm. Moreover, the storage functionality is lost if the central storage system is broken down, while in a distributed architecture, a failure only affects individual on-site storage systems and the others will still operate. Therefore, on-site storage systems and distributed control designs need to be developed for wind farms to provide regulation services for the grid. An approach to tackle that challenge will be presented in this chapter.

17 WIND ENERGY↗
DOE OSTI2017

Emissions and temperature benefits: The role of wind power in China

Background: As a non-fossil technology, wind power has an enormous advantage over coal because of its role in climate change mitigation. Therefore, it is important to investigate how substituting wind power for coal-fired electricity will affect emission reductions, changes in radiative forcing and rising temperatures, particularly in the context of emission limits. Methods: We developed an integrated methodology that includes two parts: an energy-economy-environmental (3E) integrated model and an emission-temperature response model. The former is used to simulate the dynamic relationships between economic output, wind energy and greenhouse gas (GHG) emissions; the latter is used to evaluate changes in radiative forcing and warming. Results: Under the present development projection, wind energy cannot serve as a major force in curbing emissions, even under the strictest space-restraining scenario. China's temperature contribution to global warming will be up to 21.76% if warming is limited to 2 degrees. With the wind-for-coal power substitution, the corresponding contribution to global radiative forcing increase and temperature rise will decrease by up to 10% and 6.57%, respectively. Conclusions: Substituting wind power for coal-fired electricity has positive effects on emission reductions and warming control. However, wind energy alone is insufficient for climate change mitigation. It forms an important component of the renewable energy portfolio used to combat global warming. - Highlights: • We assess the warming benefits associated with substitution of wind power for coal. • The effect of emission space limits on climate responses is deeply examined. • China is responsible for at most 21.76% of global warming given the 2-degree target. • Wind power alone may not be sufficient to face the challenge of climate change. • A fertile policy soil and an aggressive plan are necessary to boost renewables.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Calibration and validation of a spar-type floating offshore wind turbine model using the FAST dynamic simulation tool

In this study, high-quality computer simulations are required when designing floating wind turbines because of the complex dynamic responses that are inherent with a high number of degrees of freedom and variable metocean conditions. In 2007, the FAST wind turbine simulation tool, developed and maintained by the U.S. Department of Energy's (DOE's) National Renewable Energy Laboratory (NREL), was expanded to include capabilities that are suitable for modeling floating offshore wind turbines. In an effort to validate FAST and other offshore wind energy modeling tools, DOE funded the DeepCwind project that tested three prototype floating wind turbines at 1/50 th scale in a wave basin, including a semisubmersible, a tension-leg platform, and a spar buoy. This paper describes the use of the results of the spar wave basin tests to calibrate and validate the FAST offshore floating simulation tool, and presents some initial results of simulated dynamic responses of the spar to several combinations of wind and sea states. Wave basin tests with the spar attached to a scale model of the NREL 5-megawatt reference wind turbine were performed at the Maritime Research Institute Netherlands under the DeepCwind project. This project included free-decay tests, tests with steady or turbulent wind and still water (both periodic and irregular waves with no wind), and combined wind/wave tests. The resulting data from the 1/50th model was scaled using Froude scaling to full size and used to calibrate and validate a full-size simulated model in FAST. Results of the model calibration and validation include successes, subtleties, and limitations of both wave basin testing and FAST modeling capabilities.

17 WIND ENERGY↗
DOE OSTI2015

Variability of interconnected wind plants: correlation length and its dependence on variability time scale

The variability in wind-generated electricity complicates the integration of this electricity into the electrical grid. This challenge steepens as the percentage of renewably-generated electricity on the grid grows, but variability can be reduced by exploiting geographic diversity: correlations between wind farms decrease as the separation between wind farms increases. However, how far is far enough to reduce variability? Grid management requires balancing production on various timescales, and so consideration of correlations reflective of those timescales can guide the appropriate spatial scales of geographic diversity grid integration. To answer 'how far is far enough,' we investigate the universal behavior of geographic diversity by exploring wind-speed correlations using three extensive datasets spanning continents, durations and time resolution. First, one year of five-minute wind power generation data from 29 wind farms span 1270 km across Southeastern Australia (Australian Energy Market Operator). Second, 45 years of hourly 10 m wind-speeds from 117 stations span 5000 km across Canada (National Climate Data Archive of Environment Canada). Finally, four years of five-minute wind-speeds from 14 meteorological towers span 350 km of the Northwestern US (Bonneville Power Administration). After removing diurnal cycles and seasonal trends from all datasets, we investigate dependence of correlation length on time scale by digitally high-pass filtering the data on 0.25–2000 h timescales and calculating correlations between sites for each high-pass filter cut-off. Correlations fall to zero with increasing station separation distance, but the characteristic correlation length varies with the high-pass filter applied: the higher the cut-off frequency, the smaller the station separation required to achieve de-correlation. Remarkable similarities between these three datasets reveal behavior that, if universal, could be particularly useful for grid management. For high-pass filter time constants shorter than about τ = 38 h, all datasets exhibit a correlation length $\xi $ that falls at least as fast as ${{\tau }^{-1}}$ . Since the inter-site separation needed for statistical independence falls for shorter time scales, higher-rate fluctuations can be effectively smoothed by aggregating wind plants over areas smaller than otherwise estimated.

17 WIND ENERGY↗
DOE OSTI2025

Sea surface warming and ocean-to-atmosphere feedback driven by large-scale offshore wind farms under seasonally stratified conditions

Offshore wind farms may induce changes in the upper ocean and near-surface atmosphere through coupled ocean-atmosphere feedbacks. Yet, the role of air-sea interactions mediated by offshore wind farms remains poorly understood. Using fully coupled ocean-atmosphere-wave model simulations for seasonally stratified conditions along the US East Coast, we show that simulated cumulative reductions in wind stress due to large-scale wind farm clusters lead to sea surface warming of 0.3° to 0.4°C and a shallower mixed layer. This warming drives upward heat fluxes, destabilizing the atmospheric boundary layer and enhancing wind stress, which partially offsets wake-induced wind deficits. These wake-ocean interactions influence near-surface meteorology and air-sea fluxes, suggesting that a coupled modeling approach may be necessary for assessing potential oceanographic impacts of offshore wind developments. However, ocean coupling exerts limited influence on winds at turbine-relevant heights or within downstream wakes, resulting in minimal impact on long-term energy. These findings suggest that models without ocean coupling may be adequate for wind energy applications.

17 WIND ENERGY↗
DOE OSTI2013

The impact of climate change on the U.S. wind energy resource

The growing need for low-carbon emitting electricity sources has resulted in rapid growth in the wind power industry. The size and steadiness of the offshore wind resource has attracted growing investment in the planning of offshore wind turbine installations. Decisions about the location and character of wind farms should be made with an eye not only to present but also future wind resource, which may change as increasing carbon dioxide forces reductions in the poleward temperature gradient, and thus potentially in the mean tropospheric westerly winds. I propose to use the new North American Regional Climate Change Assessment Program climate projections to estimate the change of the wind power resource under various carbon dioxide loading scenarios and for a range of climate models. We will compare our assessment with both our assessment based on the IPCC AR4 model runs, to explore the extent to which improved model resolution changes the prediction for the wind power resource, and with present day estimates from reanalysis and scatterometer winds.

17 WIND ENERGY↗
DOE OSTI2013

Advanced Offshore Wind Turbine/Foundation Concept for the Great Lakes

This project investigated a conceptual 2-bladed rotor wind turbine design and assessed its feasibility for installation in the Great Lakes. The levelized cost of energy was used for this purpose. A location in Lake Erie near the coast of Cleveland, Ohio was selected as the application site. The loading environment was defined using wind and wave data collected at a weather station in Lake Erie near Cleveland. In addition, the probability distributions of the annual significant wave height and wind speed were determined. A model of the dependence of the above two quantities was also developed and used in the study of wind turbine system loads. Loads from ice floes and ridges were also included.The NREL 5 MW 3-bladed rotor wind turbine concept was used as the baseline design. The proposed turbine design employs variable pitch blade control with tip-brakes and a teeter mechanism. The rotor diameter, rated power and the tower dimensions were selected to closely match those of the NREL 5 MW wind turbine.A semi-floating gravity base foundation was designed for this project primarily to adapt to regional logistical constraints to transport and install the gravity base foundation. This foundation consists of, from bottom to top, a base plate, a buoyancy chamber, a taper zone, a column (with ice cone), and a service platform. A compound upward-downward ice cone was selected to secure the foundation from moving because of ice impact.The turbine loads analysis was based on International ElectroTechnical Committee (IEC) Standard 61400-1, Class III winds. The NREL software FAST was the primary computational tool used in this study to determine all design load cases. An initial set of studies of the dynamics of wind turbines using Automatic Dynamic Analysis of Mechanical Systems (ADAMS) demonstrated that FAST and ADAMS load predictions were comparable. Because of its relative simplicity and short run times, FAST was selected for this study. For ice load calculations, a method was developed and implemented in FAST to extend its capability for ice load modeling.Both upwind and downwind 2-bladed rotor wind turbine designs were developed and studied. The new rotor blade uses a new twist angle distribution design and a new pitch control algorithm compared with the baseline model. The coning and tilt angles were selected for both the upwind and downwind configurations to maximize the annual energy production. The risk of blade-tower impact is greater for the downwind design, particularly under a power grid fault; however, this risk was effectively reduced by adjusting the tilt angle for the downwind configuration.

17 WIND ENERGY↗
DOE OSTI2013

Assessment of U.S. Manufacturing Capability for Next-Generation Wind Turbine Drivetrains

Robust U.S. wind turbine manufacturing capabilities and supply chains are important for the United States to reduce the cost of electricity generated from wind turbines. These capabilities and supply chains are also critical to the invention and commercialization of new wind turbine technologies while providing high-quality jobs. The development of advanced drivetrain technologies for windturbine applications is advancing the state of the art for drivetrain design by producing higher capacity and operating reliability than conventional drivetrains. Advanced drivetrain technologies such as medium-speed and direct-drive generators, silicon-carbide (SiC) IGBT-based power electronics, and high torque density speed increasers require different manufacturing and supply chaincapabilities that present both risks and opportunities for U.S. wind turbine manufacturers and the wind industry as a whole. The primary objective of this project is to assess how advanced drivetrain technologies and trends will impact U.S. wind turbine manufacturing and its supply chains. The U.S. Department of Energy and other industry participants will use the information from this study toidentify domestic manufacturing gaps, barriers, and opportunities for developing U.S. wind turbine manufacturing capabilities and supply chains for next-generation drivetrain technologies. This report also includes recommendations for prioritizing technology areas for possible investments by public, private, or nonprofit entities that will reduce the cost of wind-generated electricity. Suchinvestments foster opportunities to invent and commercialize new wind turbine technologies, and provide high-quality jobs in the United States.

17 WIND ENERGY↗
DOE OSTI2016

Hurricane Resilient Wind Plant Concept Study Final Report

Hurricanes occur over much of the U.S. Atlantic and Gulf coasts, from Long Island to the U.S.-Mexico border, encompassing much of the nation's primary offshore wind resource. Category 5 hurricanes have made landfall as far north as North Carolina, with Category 3 hurricanes reaching New York with some frequency. Along the US West coast, typhoons strike with similar frequency and severity. At present, offshore wind turbine design practices do not fully consider the severe operating conditions imposed by hurricanes. Although universally applied to most turbine designs, International Electrotechnical Commission (IEC) standards do not sufficiently address the duration, directionality, magnitude, or character of hurricanes. To assess advanced design features that could mitigate hurricane loading in various ways, this Hurricane-Resilient Wind Plant Concept Study considered a concept design study of a 500-megawatt (MW) wind power plant consisting of 10-MW wind turbines deployed in 25-meter (m) water depths in the Western Gulf of Mexico. This location was selected because hurricane frequency and severity provided a unique set of design challenges that would enable assessment of hurricane risk and projection of cost of energy (COE) changes, all in response to specific U.S. Department of Energy (DOE) objectives. Notably, the concept study pursued a holistic approach that incorporated multiple advanced system elements at the wind turbine and wind power plant levels to meet objectives for system performance and reduced COE. Principal turbine system elements included a 10-MW rotor with structurally efficient, low-solidity blades; a lightweight, permanent-magnet, direct-drive generator, and an innovative fixed substructure. At the wind power plant level, turbines were arrayed in a large-scale wind power plant in a manner aimed at balancing energy production against capital, installation, and operation and maintenance (O&M) costs to achieve significant overall reductions in COE.

17 WIND ENERGY↗
DOE OSTI2018

Offshore Wind Energy Resource Assessment for Alaska

This report quantifies Alaska's offshore wind resource capacity while focusing on its unique nature. It is a supplement to the existing U.S. Offshore Wind Resource Assessment, which evaluated the offshore wind resource for all other U.S. states. Together, these reports provide the foundation for the nation's offshore wind value proposition. Both studies were developed by the National Renewable Energy Laboratory. The analysis presented herein represents the first quantitative evidence of the offshore wind energy potential of Alaska. The technical offshore wind resource area in Alaska is larger than the technical offshore resource area of all other coastal U.S. states combined. Despite the abundant wind resource available, significant challenges inhibit large-scale offshore wind deployment in Alaska, such as the remoteness of the resource, its distance from load centers, and the wealth of land available for onshore wind development. Throughout this report, the energy landscape of Alaska is reviewed and a resource assessment analysis is performed in terms of gross and technical offshore capacity and energy potential.

17 WIND ENERGY↗
DOE OSTI2018

Wind Vision Detailed Roadmap Actions: 2017 Update

In March 2015, the U.S. Department of Energy (DOE) released Wind Vision: A New Era for Wind Power in the United States, which explores and quantifies the economic and environmental costs and benefits of a scenario in which wind provides 10% of U.S. electrical demand in 2020, 20% in 2030, and 35% in 2050. The Wind Vision report also includes a Roadmap that describes actions stakeholders can pursue to achieve the vision and its underlying wind deployment scenario. The Wind Vision and its Roadmap were compiled by representatives from DOE and its national laboratories in consultation with the wind industry, trade associations, academia, environmental organizations, and other stakeholders. When the Wind Vision was released in 2015, DOE announced its intention to engage the wind community from time to time to track progress and update the Roadmap periodically.

17 WIND ENERGY↗
DOE OSTI2019

Wind Energy Instrumentation Atlas

The US Department of Energy (DOE) A2e program is focused on developing the next generation of predictive tools to better understand wind plant performance and help industry lower the overall cost of energy. A formal verification and validation process is required to demonstrate improved accuracy of these new models beyond those currently employed. And a critical part of model validation is utilization of a diverse set of accurate observations of atmospheric forcing and wind plant response. A number of existing data sets that will be used for this purpose, as highlighted by Schreck and Maniaci (2017) but A2e researchers also realize that new datasets will be required to meet validation objectives. As such, plans for new experiments based on model validation priorities (NALU validation plan, 2017) are currently being developed. This document is intended to serve as a reference to experimental study planners that describes the capability, accuracy and resolution of existing and developing measurement technologies to observe quantities of interest for wind plant model validation. Such systems can be broken into two major categories: those that measure the flow field and surrounding atmosphere around and within a wind plant and those that measure the turbine response within the wind plant. The A2e validation team will use this catalogue of instrument capability in conjunction with the validation plan, to choose the optimal set of instruments to be deployed, inform instrument placement and operation and estimate the types of validation that may be gathered through new field campaigns. Where existing instrumentation is deficient, the document will also help guide DOE towards potential areas where instrumentation development is required to meet validation objectives and A2e technology development funding may be required. The domain of interest is the wind plant microscale, within and surrounding a single wind plant, typically, tens of kilometers on a side in horizontal directions and to the top of the atmospheric boundary layer (about 1km) in the vertical. Some observations of dominant mesoscale forcing phenomena are required, with the highest resolution measurements occurring in the wind turbine wakes and on the turbines themselves. The simulation tools to be validated are mesoscale driven large-eddy simulations of the atmosphere with full aeroelastic response of individual turbines within the plant. Use cases vary slightly among tool users, but should focus on the primary end customers of the simulations and research insights, which would be turbine manufacturers, wind plant developers and owners. Broadly speaking their interests are maximizing energy output, while maintaining turbine reliability and lifetime.

17 WIND ENERGY↗
DOE OSTI2020

The Cost of Floating Offshore Wind Energy in California Between 2019 and 2032

California’s energy planning is centered around meeting the emissions reduction and renewable energy requirements of Senate Bill 350 by 2030. However, state power system planning is expected to eventually address California’s requirement to achieve 100% of total retail electricity sales from renewable energy and zero-carbon resources by 2045, as mandated by Senate Bill 100. To comply with these directives, California needs to investigate the further development of energy efficiency, storage, and a diverse range of renewable energy, zero-carbon emission, and transmission resources, including offshore wind. Wind resources off the coast of California have the potential to generate a significant portion of the state’s electric energy as it moves toward a zero-carbon economy and can help diversify its energy mix. Floating offshore wind technology, which is suitable for the deep waters along the California coast, is currently in a precommercial phase, with approximately 84 megawatts (MW) installed worldwide at the end of 2019. Globally there are over 7,000 MW in planning and permitting phases of development, with the first commercial-scale projects expected to be operational in 2024. This study provides site-specific cost and performance data for floating offshore wind to inform California’s long-term energy planning. The identification of new resources to meet California’s policy goals at least cost is part of the Integrated Resource Planning (IRP) process, which is coordinated by the California Public Utilities Commission (CPUC). In 2019–2020 IRP modeling, offshore wind was included for the first time as a candidate resource in some sensitivity cases (CPUC 2019). The data and information presented in this report can be used to update offshore wind inputs in future IRP cycles. The authors conducted a geospatial cost analysis over portions of the offshore wind resource area of California. The analyzed spatial domain includes sites with a mean wind speed of at least 7 meters per second and water depths between 40 meters (m) and 1,300 m. Costs and energy production vary across this analysis domain. We calculated these parameters on a grid layout with over 750 sites, with each site representing a 1,000-MW commercial offshore wind power plant. Levelized cost of energy (LCOE) was calculated at each site over the analysis domain. The resulting variation in LCOE across the analysis domain is illustrated through heat maps in this report. Five study areas were selected within the analysis domain where more detailed cost analysis was conducted and cost parameters, such as annual energy production, capital cost expenditures (CapEx), operational cost expenditures (OpEx), and net capacity factors are reported. These five study areas include Morro Bay, Diablo Canyon, Humboldt, Cape Mendocino and Del Norte.

17 WIND ENERGY↗
DOE OSTI2021

Atlantic Offshore Wind Transmission Literature Review and Gaps Analysis

In support of the national goal to deploy 30 gigawatts of offshore wind by 2030, DOE’s Wind Energy Technologies Office has published an Atlantic Offshore Wind Transmission Literature Review and Gaps Analysis. Transmission constraints— including both land-based transmission interconnections and offshore transmission—are expected to be one of the central challenges to meeting offshore wind deployment goals. Given current trends in offshore wind development, available technology, and state-level procurement goals, most of the first 30 GW of offshore wind are anticipated to be developed along the East Coast. This report summarizes current publicly available transmission analyses along the Atlantic Coast, as well as gaps in existing analyses. Improving understanding of offshore wind transmission options, establishing coordination and aligning processes among states and regions, and quantifying the long-term impacts of offshore wind transmission options will catalyze offshore wind energy’s growth and ensure adequate transmission and a reliable grid.

17 WIND ENERGY↗
DOE OSTI2023

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↗
DOE OSTI2024

WTK-LED: The WIND Toolkit Long-Term Ensemble Dataset

To satisfy a wide group of stakeholders across various wind energy disciplines, including but not limited to stakeholders in the distributed and utility scale wind industry, the new emerging airborne wind energy field, grid integration, power systems modeling, environmental modeling, and researchers in academia, and to close some of the gaps that current public datasets have, we aimed at developing an updated version of the meteorological WIND Toolkit, named WIND Toolkit Long-term Ensemble Dataset (WTK-LED), which is a meteorological dataset providing time series every 5 min and 2 km, including model uncertainty of wind speed at every modeling grid point so that users are provided with a range of possible wind speeds every 2 km. The data were produced using the Weather Research and Forecasting Model (WRF). The vertical grid used in WTK-LED includes many vertical layers in the atmospheric boundary layer to provide information of atmospheric quantities across the rotor layer of utility scale and distributed wind turbines. The WTK-LED includes: 1) Numerical simulations covering the continental United States, Alaska, and Hawaii, with high-resolution data being available for 3 years (2018-2020). 2) Climate simulations from Argonne National Laboratories covering the North American continent, including Alaska, Canada, and most of Mexico and the Caribbean Islands. These simulations complement the new WTK-LED to offer a 4-km dataset covering 20 years, from 2001-2020. 3) Specific long-term,high-resolution offshore simulations have been conducted separately for the US coasts, Hawaii, and the Great Lakes, leading to the 2023 National Offshore Wind data set. This report focuses on a description of the land-based WTK-LED for CONUS, Hawaii, and Alaska, for the 3-year 2-km/5-min dataset and the 20-year 4-km/hourly dataset, as well as the uncertainty quantification method. We also provide limited validation results. Based on our results to date, we suggest use cases and applications for each dataset of the WTK-LED.

17 WIND ENERGY↗