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DOE OSTI2024

Reference Site Conditions for Floating Wind Arrays in the United States

17 WIND ENERGY↗

DOE OSTI2024

Reference Site Condition Datasets for Floating Wind Arrays in the United States

Floating offshore wind farm design is highly site-specific, requiring detailed information about the specific conditions of a project area for realistic design studies. Unfortunately, publicly available site condition data for potential floating offshore wind project sites in the United States is scarce. To support U.S. offshore wind research, we developed reference site condition datasets, including metocean and seabed information, for four potential floating wind project areas in the U.S.: Humboldt Bay, Morro Bay, the Gulf of Maine, and the Gulf of Mexico. These datasets were compiled using publicly available data. Our metocean analysis, covering wind, waves, and surface currents, utilized measurement data from 2000 to 2020. Sources included the National Renewable Energy Laboratory’s National Offshore Wind Dataset for wind data, National Data Buoy Center buoys for wave data, and the High Frequency Radar Network for surface currents. These data were integrated into hourly time series used to compute extreme return periods up to 500 years, monthly statistics, and joint probability clusters for fatigue analysis. Soil conditions were evaluated using the usSEABED database and bathymetry grids were interpolated from the NCEI Digital Elevation Model Global Mosaic. Further information on the datasets and how they were created can be found in: Biglu, M., M. Hall, E. Lozon, S. Housner. 2024. Reference Site Conditions for Floating Wind Arrays in the United States. Golden, CO: National Renewable Energy Laboratory (NREL). NREL/TP-5000-89897. The data are also available at: https://github.com/FloatingArrayDesign/SiteConditions The content of each dataset is as follows: _NOW23_wind.txt: Hourly NOW-23 wind data up to a height of 400 meter. _metocean_1hr.txt: Hourly time series including wind, wave, surface current and temperature data. _Summary.xlsx: Metocean data, including extreme values, joint probability distributions and monthly statistics. _usSEABED_soil.csv: Extract of the usSEABED database for this specific site. _bathymetry_200m.txt (and 500m, 1000m): Gridded seabed depth data.

16 TIDAL AND WAVE POWER↗

DOE OSTI2026

Unalakleet Microgrid Optimization for Tribal Community Resilience

The Unalakleet Microgrid Optimization Project aimed to strengthen the reliability and efficiency of the isolated electric power system that serves the Tribal community of Unalakleet, Alaska. The community relies entirely on a local wind-diesel microgrid, consisting of four 475 kW diesel generators and six 100 kW wind turbines, to provide electricity to approximately 745 residents and Tribal facilities. Because Unalakleet is not on a road system and is located nearly 400 miles from the nearest major power grid, maintaining a resilient and efficient local energy system is critical. The scope of this project included upgrading a portion of the transmission line between the wind farm and the power plant to increase voltage and reduce line losses, along with modernizing the Supervisory Control and Data Acquisition (SCADA) system to improve monitoring, control, and data management of the power system. These upgrades were designed to increase wind energy utilization, reduce diesel fuel consumption by tens of thousands of gallons annually, and improve overall grid stability. By allowing more of the community’s electricity to be supplied by local renewable wind resources, the project was designed to lower operating costs, reduce dependence on imported fuel, and strengthen the long-term resilience of the power system. These improvements represent an important step toward the community’s long-term energy vision of expanding renewable generation, incorporating energy storage, and eventually achieving “diesels-off” operation, where essential Tribal loads are powered primarily by local renewable resources.

17 WIND ENERGY↗

DOE OSTI2025

A survey on degradation modeling, prognosis, and prognostics-driven maintenance in wind energy systems

Wind energy generation proliferated over the past decades, introducing unique challenges and opportunities for failure prediction, operation and maintenance. Decision-makers are continuously looking into new methods to infer failure mechanisms and behaviors of wind turbine components to detect and intervene in the failures before they happen. Evidently, degradation modeling and prognosis become engaging topics for researchers and practitioners to prevent catastrophic failures. Prognostics-driven approaches predict the time of failure for the components (e.g., predicting remaining useful life), which provides significant insights for scheduling of operations and maintenance activities. Integrating these prognostics-driven insights into wind farm operations and maintenance presents a substantial challenge, demanding careful consideration of numerous factors such as accessibility, crew routing, and spare part logistics. This study provides state-of-the-art review for degradation modeling, prognosis, and prognostics-driven maintenance techniques for wind energy systems. The discussed techniques align with the United Nations' sustainable development goals, in particular Goal 7 (Affordable and Clean Energy), by enhancing effectiveness and sustainability of wind energy operations. This work also showcases open research questions related to degradation modeling, prognosis, and prognostics-driven maintenance.

Altinpulluk, Nur Banu↗

DOE OSTI2026

Block Island Acoustic Data Analysis and Peak Detection Tools

This dataset contains acoustic signal analysis tools and processed datasets for pile driving noise characterization during Block Island Wind Farm construction (October 25, 2015), including peak detection algorithms, signal extraction methods, and visualization products for multi-channel hydrophone array data.

17 WIND ENERGY↗

DOE OSTI2025

Evaluating mesoscale model predictions of diurnal speedup events in the Altamont Pass Wind Resource Area of California

Mesoscale model predictions of wind, turbulence, and wind energy capacity factors are evaluated in the Altamont Pass Wind Resource Area of California (APWRA), where the diurnal regional sea breeze and associated terrain-driven speedup flows drive wind energy production during the summer months. Results from the Weather Research and Forecasting model version 4.4 using a novel three-dimensional planetary boundary layer (3D PBL) scheme, which treats both vertical and horizontal turbulent mixing, are compared to those using a well-established one-dimensional (1D) scheme that treats only vertical turbulent mixing. Each configuration is evaluated over a nearly 3-month-long period during the Hill Flow Study, and due to the recurring nature of the observed speedup flows, diurnal composite averaging is used to capture robust trends in model performance. Both model configurations showed similar overall skill. The general timing and direction of the speedup flows is captured, but their magnitude is overestimated within a typical wind turbine rotor layer. Both also fail to capture a persistent observed near-surface jet-like flow, likely due to the limited grid resolution that is typical of mesoscale models. However, the 3D PBL configuration shows several minor improvements over the 1D PBL configuration, including improved wind speed and turbulence kinetic energy profiles during the accelerating phase of the speedup events, as well as reduced positive wind speed bias at surface stations across the APWRA region. Using a mesoscale wind farm parameterization, modeled capacity factors are also compared to monthly data reported to the US Energy Information Administration (EIA) during the study period. Although the monthly trend in the data is captured, both model configurations overestimate capacity factors by roughly 7 %–11 %. Through model evaluation, this study provides confidence in the 3D PBL scheme for wind energy applications in complex terrain and provides guidance for future testing.

17 WIND ENERGY↗

DOE OSTI2024

Tilted lidar profiling: Development and testing of a novel scanning strategy for inhomogeneous flows

The most common profiling techniques for the atmospheric boundary layer based on a monostatic Doppler wind lidar rely on the assumption of horizontal homogeneity of the flow. This assumption breaks down in the presence of either natural or human-made obstructions that can generate significant flow distortions. The need to deploy ground-based lidars near operating wind turbines for the American WAKE experimeNt (AWAKEN) spurred a search for novel profiling techniques that could avoid the influence of the flow modifications caused by the wind farms. With this goal in mind, two well-established profiling scanning strategies have been retrofitted to scan in a tilted fashion and steer the beams away from the more severely inhomogeneous region of the flow. Results from a field test at the National Renewable Energy Laboratory's 135-m meteorological tower show that the accuracy of the horizontal mean flow reconstruction is insensitive to the tilt of the scan, although higher-order wind statistics are severely deteriorated at extreme tilts mainly due to geometrical error amplification. A numerical study of the AWAKEN domain based on the Weather Research and Forecasting Model and large-eddy simulation are also conducted to test the effectiveness of tilted profiling. It is shown that a threefold reduction of the error on inflow mean wind speed can be achieved for a lidar placed at the base of the turbine using tilted profiling.

17 WIND ENERGY↗

DOE OSTI2026

Block Island Project Documentation, Presentations, and Reports

This dataset contains documentation and outreach materials from the RODEO project at the Block Island Wind Farm, including the presentations, report figures, and summary materials produced across the monitoring and modeling effort. It complements the RODEO data datasets (acoustic monitoring, propagation modeling, analysis, environmental, survey, geospatial, bathymetry, and seafloor) and contains documents and figures rather than instrument or model data.

17 WIND ENERGY↗

DOE OSTI2025

Reliability Analysis of Power Grids Considering Component Failures of Variable Energy Resources

This paper proposes an improved model for the reliability assessment of power systems considering component failures of variable energy resources (VER). The inherent intermittency of VER such as solar photovoltaic (PV) and wind farms, along with their susceptibility to component failures, present significant challenges to reliable system operation. These issues, combined with power grid operation and network constraints, complicate the reliable operation of VER-integrated power systems. Here, to address these concerns, this paper introduces a reliability assessment framework that considers VER input variability, its impact on component availability, and their resulting impact on overall system reliability. Stochastic models based on discrete Markov processes are developed to incorporate variable irradiance, wind speeds, and their effects on PV and wind component failure rates. A next-event and state transition-based approach is then developed to integrate the stochastic models into a mixed-timing sequential Monte Carlo simulation framework for composite reliability assessment. Case studies on the RTS-GMLC system demonstrate the effectiveness of the proposed model in evaluating the reliability of VER-integrated systems.

Pandit, Dilip [Sandia National Laboratories (SNL-N↗

DOE OSTI2025

Acoustic Tomography System (CRADA Final Report)

NREL will install the CU/CIRES acoustic tomography array at the National Wind Technology Center (NWTC). The system consists of 9 freestanding towers of 9.1m height that are currently located at the NWTC. On these towers are installed a series of microphones and speakers. One center tower holds a sonic anemometer and temperature probe. The purpose of the acoustic tomography system is to measure complex flow fields surrounding wind turbine arrays that influence wind farm energy production and reliability. There is currently no funding to test and research the system (just install it), but NREL and CU researchers will write proposals that will fund the actual research with this unique measurement technology.

17 WIND ENERGY↗

DOE OSTI2024

Considerations for Offshore-Wind-to-Hydrogen Systems in the United States

This presentation investigates the complexities involved in designing and siting offshore wind-to-hydrogen plants across the United States. It examines the integration of offshore wind farms with electrolysis facilities to produce green hydrogen, highlighting the technical, region-specific characteristics, and economic factors that influence project feasibility and success. The study presents four representative regions around the United States, two fixed-bottom locations and two floating locations: the New York Bight, Gulf of Mexico, Gulf of Maine and off the northern coast of California. Additionally, it assesses two energy transmission configurations - centralized onshore and offshore electrolysis - for the years 2025, 2030, and 2035.

ENERGY PLANNING, POLICY, AND ECONOMY,HYDROGEN,WIND↗

DOE OSTI2024

International Energy Agency 22 MW Offshore Reference Wind Turbine

The presentation will be used in a public webinar to introduce the newly developed 22 megawatt offshore reference wind turbine designed within the International Energy Agency Wind Technology Commercialization Programme Task 55 Reference Wind Turbines and Plants. The turbine was designed collaboratively by two teams at the Denmark Technical University and at the National Renewable Energy Laboratory. Reference turbines serve an important purpose in the wind energy community, since they provide openly available data for models representative of current wind turbine technology, which can be used by practitioners for a variety of modeling purposes, ranging from aerodynamic, structural, and aeroelastic turbine modeling to wind farm flow modeling, across a range of fidelities. The IEA 22 RWT aims to model machines with projected installation in the 2025-2030 time frame. The turbine has a rotor diameter of 284 meters and a hub height of 170 meters. It is a class 1-B machine with a rotor specific power nearing 350 W m-2 and it is mounted on either a fixed-bottom offshore foundation or a semi-submersible floating platform.

17 WIND ENERGY↗

DOE OSTI2025

Wind Supply Chain Security: Hardware Enumeration and Analysis

This project, undertaken by Idaho National Laboratory (INL) for the Department of Energy (DOE) Wind Energy Technologies Office (WETO), focused on the enumeration and analysis of six key devices important to wind technologies. The devices analyzed included Beckhoff Bus Terminal Controllers (BK1120 and BC9000), a Beckhoff Economy Built-in Panel PC (CP6231), an N-Tron Managed Industrial Ethernet Switch (711FX3), a Bachmann M1 Gateway, and a Bachmann Smart Power Plant Controller. Device selection was driven by availability and budget constraints, with several components sourced from existing wind farms and others procured through a co-agreement with another WETO-funded project. The project's primary objective was to create a hardware bill of materials (HBOM) for each device, identifying and documenting all components to assess potential security and supply chain risks. A detailed analysis revealed over 750 unique components across the six devices, with 80% successfully identified and accompanied by datasheets. Notably, Texas Instruments emerged as the leading supplier, providing over 16% of the components, followed by ON Semiconductor at 11.3%, Analog Devices at 5.3%, and Renesas Electronics Corp at 4.1%. Other notable vendors included Toshiba Corporation, iC-Haus Corporation, Atmel, Vishay, and STMicroelectronics. The enumeration process involved thorough documentation of each component, including its designation, quantity, identifiers, pin package, description, vendor, model, and country of origin. This process provided valuable insights into the complexity and diversity of the electronic systems within these wind devices. It also highlighted the distinct separation of components between vendors, suggesting a trend of vendor-specific component usage. Key findings from the project emphasized the importance of broadening the scope of vendor analysis in future research to gain a comprehensive understanding of component distribution and commonality. The identification of vendor-specific component usage patterns offers new avenues for research and underscores the significance of continued investigation in this field. Overall, this project provides critical insights into the component composition of wind devices, aiding in the development of improved supply chain management and component sourcing strategies. The results contribute valuable knowledge to the wind technology sector, laying the groundwork for enhanced security and resilience in wind energy systems.

17 - WIND ENERGY↗

DOE OSTI2025

Stabilizing dynamic subsea power cables using Bi-stable nonlinear energy sinks

This study investigates vibration mitigation of dynamic subsea cables through passive bi-stable nonlinear energy sinks (B-NESs). These devices suppress vibration energy in a broadband way, and can be regarded as extensions of classical linear tuned mass dampers (TMDs) which are narrowband devices. Through the open-source MoorDyn library, we simulated the vibrations of a vertical subsea cable equipped with a set of B-NESs. Multi-objective optimization was performed to detect the B-NES parameters for optimal mitigation of the cable vibrations. Advanced signal processing verified the efficacy of the optimized B-NESs not only to rapidly absorb and locally dissipate vibration energy, but also to nonlinearly scatter vibration energy from low to high frequencies within the cable itself. This last feature is especially beneficial for vibration mitigation of the undersea cable, as at higher frequencies the cable vibrations exhibit drastically reduced amplitudes and are more effectively dissipated by inherent structural damping and hydrodynamic radiation damping. This contrasts with traditional TMDs which can mitigate vibration only at a single frequency. Furthermore, our robustness study confirms the B-NES's effectiveness under even varying environmental conditions. Overall, the B-NES's capacity for broadband vibration mitigation renders it a promising retrofit solution for improving the performance and operational safety of dynamic power cables in offshore wind farms and other marine applications.

17 WIND ENERGY↗

DOE OSTI2024

Ultrasonic Deterrents To Reduce Bat Mortality at Wind Turbines - Short Science Summary

In North America, several bat species commonly collide with operating turbines. Though the ultimate driver of collisions is unknown, studies suggest that bats may be attracted to turbines because they often approach and spend extended periods of time (seconds to minutes) interacting with turbine structures. To reduce bat mortality at wind farm operators, seek to reduce mortality rates by reducing the amount of time that bats interact with spinning turbine blades (or exposure). Current approaches to reduce exposure include curtailment, whereby turbine operators stop turbine rotors from spinning during periods when bats are expected to be at the highest risk of collision, and deterrent technologies that seek to discourage bats from entering/ limit the amount of time spent within the rotor swept area. We briefly describe the state of the science on ultrasonic deterrent technology, highlight potential drivers of variable efficacy for bat mortality reduction, and suggest next steps focus on identifying the driver(s) of such variability.

bats↗

DOE OSTI2026

Evaluation of a high-resolution regional climate simulation for surface and hub-height wind climatology over North America

Assessing the availability of key wind resources requires augmenting observations to support the implementation of wind energy infrastructure. However, observations are limited, necessitating the development of high-resolution, long-term gridded datasets. This study presents a robust, dynamically downscaled climatological dataset, offering 20 years of hourly wind data at a 4 km spatial resolution across North America, and evaluates its performance against observations, including meteorological towers and automated surface-observing system (ASOS) stations, as well as coarse-resolution reanalysis data (the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis version 5 (ERA5)). Results demonstrate that the downscaled high-resolution wind data outperform ERA5 in regions of complex terrain and coastal areas, with improved overlap coefficients for wind data distributions and reduced root mean square errors (RMSEs) for hub-height and near-surface diurnal wind patterns. The downscaled simulation also captures the synoptic drivers of seasonal wind direction patterns reasonably well, indicated by high wind rose similarity indices. This study also provides an analysis of interannual variability, utilizing the dataset's full 20-year period, and model uncertainty, generated by varying model initial conditions and physics parameterizations across 1-year ensemble members, which are key considerations for wind resource assessment in wind farm development.

17 WIND ENERGY↗

DOE OSTI2024

Modification of wind turbine wakes by large-scale, convective atmospheric boundary layer structures

In this study, we consider the impact of large-scale, convective structures in an unstable atmospheric boundary layer on wind turbine wakes. Simulation data from a high-fidelity large-eddy simulation (LES) of the AWAKEN wind farm site matching unstable atmospheric conditions were analyzed, and both turbine performance and wake behavior were affected based on their location relative to the convective structures. Turbines located in updraft regions of the flow experienced lower inflow velocity and generated less power, but their wakes were observed to recover faster and saw greater turbulent kinetic energy mixing higher in the boundary layer. The opposite effect was found for turbines in the downdraft regions of the convective structures. A simplified model of this wake behavior was also developed based on a two-dimensional k–ε Reynolds-Averaged Navier–Stokes formulation. This simplified model included the effects of vertical transport, but could be efficiently solved as a parabolic system, and was found to capture similar wake modifications observed in the high-fidelity LES computations.

16 TIDAL AND WAVE POWER↗

DOE OSTI2026

Emerging mobile lidar technology to study boundary layer winds influenced by operating turbines

The development of a microjoule-class pulsed Doppler lidar and deployment of this compact system on mobile platforms such as aircraft, ships, or trucks have opened a new opportunity to characterize the dynamics of complex mesoscale wind flows. The PickUp-based Mobile Atmospheric Sounder (PUMAS) truck-based lidar system was recently used during the American Wake Experiment (AWAKEN) to assess the general structure of boundary layer (BL) wind and turbulence around wind turbines in central Oklahoma. Wind speed profiles averaged over PUMAS transects influenced by the operating turbines (waked flow) show a 1–2 m s −1 reduction compared to mean undisturbed (free flow) wind speed profiles. Spatial variability in wind speed was observed in time–height cross-sections at different distances from turbines. The wind speeds were about 9–12 m s −1 at 6 km distance compared to 5–7 m s −1 at the transects near the turbines. The PUMAS dataset from AWAKEN demonstrated the capability of the mobile Doppler lidar system to document spatial variability in wind flows at different distances from wind turbines and obtain quantitative estimates of wind speed reduction in the waked flow. The high-frequency, simultaneous measurements of the horizontal and vertical winds provide a new approach for characterizing dynamic processes critical for wind farm wake analyses.

17 WIND ENERGY↗