SEARCH · Engineering Papers

Results for “wind energy development”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 397 records · Page 22

All sources NASA NTRS DOE OSTI

DOE OSTI2024

MRS Modelling in OpenFAST

Multi-rotor wind turbines, where more than one rotor is connected to a single support structure, are increasing in popularity due to their balance of power generation with component size, weight, and cost. Multi-rotor turbines are also common in marine energy, where deployment sites tend to be depth-constrained, limiting the maximum size of a rotor. To support the industry and research communities in designing and modeling multi-rotor turbines, the open-source turbine modeling tool OpenFAST, developed and supported by the National Renewable Energy Laboratory, is being extended to model multi-rotor wind and marine turbines. This presentation gives an overview of the current state of OpenFAST, planned changes to enable coupled aero-hydro-servo-elastic dynamic modeling of multi-rotor turbines, and examples of the types of turbines that OpenFAST will support.

marine energy↗

DOE OSTI2022

OC6 phase I: Improvements to the OpenFAST predictions of nonlinear, low-frequency responses of a floating offshore wind turbine platform

We report in the OC5 and OC6 projects, the authors observed a persistent underprediction of the nonlinear, low-frequency responses of an offshore wind semisubmersible with many mid-fidelity engineering models, including the OpenFAST tool developed by the National Renewable Energy Laboratory. Both the low-frequency wave excitation in surge and pitch and the resulting resonance motions were severely underpredicted. In response, we developed several modifications to the OpenFAST model from the OC5/6 projects to improve the predictions of the low-frequency wave loads and responses. All modifications are in the modeling of the viscous drag forces. Efforts were made to provide physical justifications to the changes and to limit the number of additional parameters requiring tuning, so that the modified model can be applied to other floating wind systems. With the proposed modifications, the predictions of the low-frequency surge and pitch wave loads on a fixed floater and the resonance responses of a floating structure are both significantly improved with a single set of model coefficients, which leads to good agreement with the measurements from the OC6 wave-basin experimental campaign.

17 WIND ENERGY↗

DOE OSTI2021

Evaluating Terrain as a Turbulence Generation Method

When driving microscale large-eddy simulations with mesoscale model solutions, turbulence will take space to develop, known as fetch, on the microscale domain. To reduce fetch, it is common to add perturbations near the boundaries to speed up turbulence development. However, when simulating domains over complex terrain, it is possible that the terrain itself can quickly generate turbulence within the boundary layer. It is shown here that rugged terrain is able to generate turbulence without the assistance of a perturbation strategy; however, the levels of turbulence generated are improved when adding perturbations at the inlet. Flow over smoothed, but not flat, terrain fails to generate adequate turbulence throughout the boundary layer in all tests conducted herein. Sensitivities to the strength of the mean wind speed and boundary layer height are investigated and show that higher wind speeds produce turbulence over terrain features that slower wind speeds do not. Further, by increasing the height of the capping inversion, the effectiveness of topography alone to generate turbulence throughout the depth of the boundary is diminished. In all cases, the inclusion of a perturbation strategy improved simulation performance with respect to turbulence development.

17 WIND ENERGY↗

DOE OSTI2022

2021 Component Innovation Awardee: Windurance, LLC

Distributed wind turbine manufacturers seeking to enter the market are often hampered by two challenges: not enough capital and no specific expertise in developing certified electronic equipment. A harsh reality is that off-the-shelf power electronics are neither certified nor cost-effective. This lack of certified controller equipment in the distributed wind energy industry adds expense and impedes market penetration related to certification for individual wind turbines, wind system projects, and installations. Normally, these certification costs would be borne repeatedly by individual turbine manufacturers or developers on a model-by-model or project-by-project basis, resulting in cost and time delays as well as uncertainty and risk for project developers and prospective owners. Windurance seeks to eliminate these challenges by developing and obtaining third-party certification of a standardized wind turbine controller. This will facilitate development, certification, and production while supporting efficiencies not easily achievable by individual manufacturers. Windurance's Distributed Wind Industry Turbine Controller will enable manufacturers to apply proprietary turbine- specific configurations and functionality. When applicable, manufacturers can expand on a Windurance-provided software framework to add unique or proprietary functionality.

CIP↗

DOE OSTI2025

Integrating Offshore Wind Into Competitive Renewable Energy Zones (CREZ) for the Philippines

The Philippines is aiming to jumpstart a domestic offshore wind industry and has incorporated offshore wind into several planning efforts. In parallel, the Philippines has also been a leader in incorporating renewable energy zones (REZs) into their power sector development and transmission plans. The objective of this study, conducted by the U.S. Department of Energy's National Renewable Energy Laboratory (NREL) in partnership with the Philippines Department of Energy (PDOE), is to incorporate offshore wind resources into the Philippines' already established competitive renewable energy zones (CREZs) to support national transmission planning, thereby merging these two previously disparate workstreams and implementing a key recommendation from the World Bank's offshore wind roadmap for the Philippines.

17 WIND ENERGY↗

DOE OSTI2025

Integrating Offshore Wind Into Competitive Renewable Energy Zones (CREZ) for the Philippines [Slides]

17 WIND ENERGY↗

DOE OSTI2026

Key Drivers for Offshore Wind Deployment in the Western United States

The western coast of the United States has abundant natural resources, including wind, sun, and water. Despite strong ocean winds, offshore wind energy (OSW) in the Western United States is in the early stages of technology development due largely to the deep water off the coast, which requires floating platforms rather than fixed‐bottom turbines. Floating OSW increases the technical difficulty of installation and thus the cost relative to both fixed‐bottom OSW and land‐based turbines. OSW is a potential generation option to help meet increasing demand on the west coast of the United States because it likely has fewer land‐use conflicts than other technologies and complements sources in the existing electricity supply by providing energy during times of high system stress. This paper examines the possible drivers and barriers to OSW deployment on the West Coast using the National Laboratory of the Rockies' state‐of‐the‐art capacity expansion model and the Regional Energy Deployment System (ReEDS) model. We use ReEDS to explore a multitude of future scenarios looking at key drivers for OSW deployment, including variations on the cost of OSW, electricity demand growth, and the availability of competing technologies to examine the factors that may play a role in OSW growth. Assuming coastal state policies such as renewable portfolio and clean energy standards remain in place, we find that OSW can play a role in meeting electricity demand and provide energy during stressful grid conditions and find that deployment from the least‐cost investment model ranges from 7.6 to 38 GW by 2045.

17 WIND ENERGY↗

DOE OSTI2022

Rating of a Pitch Bearing for a 1.5-Megawatt Wind Turbine

Slew ring or "pitch" bearings are used in wind turbines to connect the blade root to the hub. They support the resulting simultaneous radial, axial, and overturning moment loads while allowing relative rotation of the blade with respect to the hub. NREL has recently begun a research program related to pitch bearing reliability, recognizing its growing importance for wind turbines. The purpose of this first paper is to describe the rating analysis for a reference pitch bearing representative of that used a 1.5-megawatt (MW) wind turbine. The analysis will serve as a baseline for future finite-element analyses and strain and deflection measurements of an installed pitch bearing. If successful, this work will enable the design and specification of more reliable pitch bearings, a key concern in the long-term operation of land-based wind turbines and new development of offshore wind turbines.

17 WIND ENERGY↗

DOE OSTI2024

Experimental trials of species-specific bat flight responses to an ultrasonic deterrent

Unintended consequences of increasing wind energy production include bat mortalities from wind turbine blade strikes. Ultrasonic deterrents (UDs) have been developed to reduce bat mortalities at wind turbines. Our goal was to experimentally assess the species-specific effectiveness of three emission treatments from the UD developed by NRG Systems. We conducted trials in a flight cage measuring approximately 60 m × 10 m × 4.4 m (length × width × height) from July 2020 to May 2021 in San Marcos, Texas, USA. A single UD was placed at either end of the flight cage, and we randomly selected one for each night of field trials. Trials focused on a red bat species group (Lasiurus borealis and Lasiurus blossevillii; n = 46) and four species: cave myotis (Myotis velifer; n = 57), Brazilian free-tailed bats (Tadarida brasiliensis; n = 73), evening bats (Nycteceius humeralis; n = 53), and tricolored bats (Perimyotis subflavus; n = 17). The trials occurred during three treatment emissions: low (emissions from subarrays at 20, 26, and 32 kHz), high (emissions from subarrays at 38, 44, and 50 kHz), and combined (all six emission frequencies). We placed one wild-captured bat into the flight cage for each trial, which consisted of an acclimation period, a control period with the UD powered off, and the three emission treatments (order randomly selected), each interspersed with a control period. We tracked bat flight using four thermal cameras placed outside the flight cage. We quantified the effectiveness of each treatment by comparing the distances each bat flew from the UD during each treatment vs. the control period using quantile regression. Additionally, we conducted an exploratory analysis of differences between sex and season and sex within season using analysis of variance. Broadly, UDs were effective at altering the bats’ flight paths as they flew farther from the UD during treatments than during controls; however, results varied by species, sex, season, and sex within season. For the red bat group, bats flew farther from the UD during all treatments than during the control period at all percentiles (p < 0.001), and treatments were comparable in effectiveness. For cave myotis, all percentile distances were farther from the UD during each of the treatments than during the control, except the 90th percentile distance during high, and low was most effective. For evening bats and Brazilian free-tailed bats, results were inconsistent, but high and low were most effective, respectively. For tricolored bats, combined and low were significant at the 10th–75th percentiles, high was significant at all percentiles, and combined was most effective. Results suggest UDs may be an effective means of reducing bat mortalities due to wind turbine blade strikes. We recommend that continued research on UDs focus on low emission treatments, which have decreased sound attenuation and demonstrated effectiveness across the bat species evaluated in this study.

17 WIND ENERGY↗

DOE OSTI2021

INTEGRATE - Inverse Network Transformations for Efficient Generation of Robust Airfoil and Turbine Enhancements

The INTEGRATE (Inverse Network Transformations for Efficient Generation of Robust Airfoil and Turbine Enhancements) project is developing a new inverse-design capability for the aerodynamic design of wind turbine rotors using invertible neural networks. This AI-based design technology can capture complex non-linear aerodynamic effects while being 100 times faster than design approaches based on computational fluid dynamics. This project enables innovation in wind turbine design by accelerating time to market through higher-accuracy early design iterations to reduce the levelized cost of energy. INVERTIBLE NEURAL NETWORKS Researchers are leveraging a specialized invertible neural network (INN) architecture along with the novel dimension-reduction methods and airfoil/blade shape representations developed by collaborators at the National Institute of Standards and Technology (NIST) learns complex relationships between airfoil or blade shapes and their associated aerodynamic and structural properties. This INN architecture will accelerate designs by providing a cost-effective alternative to current industrial aerodynamic design processes, including: - Blade element momentum (BEM) theory models: limited effectiveness for design of offshore rotors with large, flexible blades where nonlinear aerodynamic effects dominate - Direct design using computational fluid dynamics (CFD): cost-prohibitive - Inverse-design models based on deep neural networks (DNNs): attractive alternative to CFD for 2D design problems, but quickly overwhelmed by the increased number of design variables in 3D problems AUTOMATED COMPUTATIONAL FLUID DYNAMICS FOR TRAINING DATA GENERATION - MERCURY FRAMEWORK The INN is trained on data obtained using the University of Marylands (UMD) Mercury Framework, which has with robust automated mesh generation capabilities and advanced turbulence and transition models validated for wind energy applications. Mercury is a multi-mesh paradigm, heterogeneous CPU-GPU framework. The framework incorporates three flow solvers at UMD, 1) OverTURNS, a structured solver on CPUs, 2) HAMSTR, a line based unstructured solver on CPUs, and 3) GARFIELD, a structured solver on GPUs. The framework is based on Python, that is often used to wrap C or Fortran codes for interoperability with other solvers. Communication between multiple solvers is accomplished with a Topology Independent Overset Grid Assembler (TIOGA). NOVEL AIRFOIL SHAPE REPRESENTATIONS USING GRASSMAN SPACES We developed a novel representation of shapes which decouples affine-style deformations from a rich set of data-driven deformations over a submanifold of the Grassmannian. The Grassmannian representation as an analytic generative model, informed by a database of physically relevant airfoils, offers (i) a rich set of novel 2D airfoil deformations not previously captured in the data , (ii) improved low-dimensional parameter domain for inferential statistics informing design/manufacturing, and (iii) consistent 3D blade representation and perturbation over a sequence of nominal shapes. TECHNOLOGY TRANSFER DEMONSTRATION - COUPLING WITH NREL WISDEM Researchers have integrated the inverse-design tool for 2D airfoils (INN-Airfoil) into WISDEM (Wind Plant Integrated Systems Design and Engineering Model), a multidisciplinary design and optimization framework for assessing the cost of energy, as part of tech-transfer demonstration. The integration of INN-Airfoil into WISDEM allows for the design of airfoils along with the blades that meet the dynamic design constraints on cost of energy, annual energy production, and the capital costs. Through preliminary studies, researchers have shown that the coupled INN-Airfoil + WISDEM approach reduces the cost of energy by around 1% compared to the conventional design approach. This page will serve as a place to easily access all the publications from this work and the repositories for the software developed and released through this pr...

aerodynamics↗

DOE OSTI2025

Using system identification in modeling the yaw response of tail fins for small wind turbines with bearing friction

Here, we describe three main developments of our previous study of the nonlinear yaw dynamics of the tail fins for small wind turbines [Khedr et al., J. Renewable Sustainable Energy 16, 053305 (2024)]. First, the model constants derived from archived computational and experimental studies are adjusted by employing system identification (SI) to maximize the model's agreement with wind tunnel tests. This adjustment was done for high wind speeds, where yaw bearing friction can be ignored. When starting a turbine at low wind speed, however, friction can become important. Our second development is to implement a model for the frictional resistive torque and use SI to maximize its accuracy. These developments used wind tunnel experiments on generic delta, elliptical, and rectangular planforms that were described by Khedr et al. [J. Renewable Sustainable Energy 16, 053305 (2024)]. Since the aerodynamic and friction models employ a large number of constants, we describe ways to constrain the values using linearized solutions of the response equations for small and large yaw angles. Third, we test the generality of the aerodynamic and friction modeling using the complex planform from a commercial small turbine, for which limited theoretical and computational guidance is available in selecting the model constants. The model implemented with SI is shown to provide an accurate description of the yaw response of the complex planform. Guidelines are given for the use of wind tunnel tests to determine the model constants for tail fins of any planform.

17 WIND ENERGY↗

DOE OSTI2025

A Regional Approach to Offshore Wind Energy Manufacturing in the Central Atlantic: Supply Chain

Growth of the offshore wind industry in the United States is likely to require growth in the nation's manufacturing capacity and additional resources and investments to meet energy project demands. Such growth has the potential to provide positive economic impacts for local communities, workers, and entire states. To realize the benefits of developing a domestic offshore wind supply chain, the states of Maryland, North Carolina and Virginia are working together under the Southeast and Mid-Atlantic Regional Transformative Partnership for Offshore Wind Resources (SMART-POWER) regional collaboration to advance the industry, with Delaware as a supporting state. This report is part of the SMART-POWER Workforce and Supply Chain Analysis study, funded by the National Offshore Wind Research and Development Consortium. The study assesses challenges and opportunities for the four Central Atlantic states to understand key regional strengths and identify supply chain investments that could effectively leverage their resources and provide benefits to both the member states and the offshore wind sector as a whole.

17 WIND ENERGY↗

DOE OSTI2022

Sandia Wind Energy Program: FY21 Accomplishments

This report summarizes Fiscal Year 2021 accomplishments from Sandia National Laboratories Wind Energy Program. The portfolio consists of funding provided by the DOE EERE Wind Energy Technologies Office (WETO), Advanced Research Projects Agency-Energy (ARPA-E), DOE Small Business Innovation Research (SBIR), and the Sandia Laboratory Directed Research and Development (LDRD) program. These accomplishments were made possible through capabilities investments by WETO, internal Sandia investment, and partnerships between Sandia and other national laboratories, universities, and research institutions around the world.

17 WIND ENERGY↗

DOE OSTI2025

A perspective on lessons learned and future needs for wind energy field campaigns

This perspective paper provides motivation and guidance to the wind energy community for suggested future investments and a long-term strategy for wind-energy-related field campaigns that will provide much-needed observations for improving wind energy science and model validation. We synthesize key lessons learned from past field campaigns, identify critical science gaps that we think should drive future field efforts, and provide a suggested pipeline on how future endeavors should be developed. When considering future grand field campaigns, we stress the need for international cooperation across funding bodies, research institutes, and industry partners to collect observations to overcome current and future grand challenges for wind energy.

17 WIND ENERGY↗

DOE OSTI2021

A Review of Coastal Fog Microphysics During C-FOG

The goal of this paper is to provide an overview the coastal fog microphysical measurements and to evaluate microphysical parameterizations based on the C-FOG (Toward Improving Coastal Fog Prediction) field project. C-FOG is designed to advance understanding of liquid fog formation, development, and dissipation over coastal environments to improve fog predictability and monitoring. The project took place in Eastern Canada (Nova Scotia, NS and Newfoundland, NL) coastlines and open water environments during August-October of 2018 where environmental conditions play an important role for late season’s fog formation. Visibility (Vis), wind speed (Uh), and turbulence along coastlines are the most critical weather- related parameters affecting marine transportation and aviation. In the analysis, microphysical observations are summarized first and then they are, together with 3D wind components, used for fog intensity (visibility) evaluation. Results suggest that detailed microphysical observations collected at the supersites and aboard Research Vessel (RV) Hugh R. Sharp are useful to develop microphysical parameterizations. The fog life cycle and turbulence kinetic energy dissipation rate were strongly related to each other. The magnitude of 3D wind fluctuations was higher during the formation and dissipation stages. An array of cutting-edge instruments used for data collection provided new insight into the variability and intensity of fog (visibility) and microphysics. It is concluded that further improvements in microphysical observations and parameterizations are needed to improve fog predictability of NWP (Numerical Weather Prediction) models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Offshore Wind to Hydrogen - Modeling, Analysis, Testing and International Collaboration Work

This project explores electrolytic hydrogen production from an offshore wind turbine by: Modeling: Simulate an offshore wind turbine and generate power output profiles; Analysis: Analyze offshore conditions and determine operational modes of the stack; Testing: Perform hardware testing to evaluate dynamic characteristics; and International Collaboration Work: Share learnings and publish. Potential Outcomes: Accelerate development of an integrated, in-turbine offshore wind hydrogen system; and Support two DOE Energy Earthshots - Hydrogen and Floating Offshore Wind.

electrolyzer↗

DOE OSTI2020

Adversarial super-resolution of climatological wind and solar data

Accurate and high-resolution data reflecting different climate scenarios are vital for policy makers when deciding on the development of future energy resources, electrical infrastructure, transportation networks, agriculture, and many other societally important systems. However, state-of-the-art long-term global climate simulations are unable to resolve the spatiotemporal characteristics necessary for resource assessment or operational planning. We introduce an adversarial deep learning approach to super resolve wind velocity and solar irradiance outputs from global climate models to scales sufficient for renewable energy resource assessment. Using adversarial training to improve the physical and perceptual performance of our networks, we demonstrate up to a 50 × resolution enhancement of wind and solar data. In validation studies, the inferred fields are robust to input noise, possess the correct small-scale properties of atmospheric turbulent flow and solar irradiance, and retain consistency at large scales with coarse data. An additional advantage of our fully convolutional architecture is that it allows for training on small domains and evaluation on arbitrarily-sized inputs, including global scale. We conclude with a super-resolution study of renewable energy resources based on climate scenario data from the Intergovernmental Panel on Climate Change’s Fifth Assessment Report.

14 SOLAR ENERGY↗

DOE OSTI2021

Distributed Wind Market Report: 2021 Edition

The U.S. Department of Energy’s annual Distributed Wind Market Report provides stakeholders with market statistics and analysis along with insights into market trends and characteristics. By providing a comprehensive overview of the distributed wind market, this report can help guide future investments and decisions by industry, utilities, federal and state agencies, and other interested parties. This report provides key information to help stakeholders understand and access market opportunities and inform distributed wind industry research and development needs.

17 WIND ENERGY↗