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At least 1,639 records · Page 91
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Micrometeorological impacts of offshore wind farms as seen in observations and simulations

In Europe, offshore wind farms have a capacity of 16 GW, with 71% installed at the North Sea. These wind farms represent an additional source of turbulence and may influence the stratification of the marine boundary layer. We present aircraft measurements and simulations showing an impact on temperature and humidity at hub height in the order of 0.5 K and 0.5 g kg -1 even 60 km downwind of a wind farm cluster. We extend these simulations to explore a realistic future scenario, suggesting wakes in potential temperature and water vapor propagating more than 100 km downwind. Furthermore, such impacts of wind farms are only observed in case of a strong stable stratification at rotor height, allowing wind farms to mix warmer air downward.

17 WIND ENERGY↗
DOE OSTI2026

Closed-Loop Wind Turbine Controllers for Active Wake Mixing Strategies

Wind turbine active wake mixing (AWM) is an exciting new field of research where dynamic actuation, usually on the blade pitch angles, is used to increase wind farm-wide power production. From a controls perspective, the current state-of-the-art AWM strategies are very simple: a dynamic, usually periodic, reference signal is prescribed to actuators in an open-loop (OL) fashion. The actuation is then presumed to have a certain desired effect on the system, i.e., the wind turbine and the flow it affects. However, this system is highly nonlinear and experiences disturbances in the form of wind variations that are not known a priori. As a result, the OL approach might not yield optimal results. In this article, a novel approach is presented, which closes the loop on AWM controllers. A feedback loop is implemented, which uses measurements of the individual blade bending moments that are widely available on modern wind turbines to determine the individual blade pitch angles. A proof of concept of this implementation is presented in this article, and a thorough comparison with the OL method is executed using high-fidelity flow simulations. These simulations show that the novel closed-loop controller does not substantially increase wake mixing but achieves similar performance as the OL controller while reducing fatigue loads on the controlled turbine.

17 WIND ENERGY↗
DOE OSTI2018

2017 Distributed Wind Market Report

The U.S. Department of Energy’s (DOE’s) annual Distributed Wind Market Report provides stakeholders with market statistics and analysis along with insights into its trends and characteristics. Cumulative U.S. distributed wind installed capacity for 2003 to 2017 now stands at 1,076 MW from over 81,000 wind turbines across all 50 states, Puerto Rico, the U.S. Virgin Islands (USVI), and Guam. In 2017, 21 states added 83.7 MW of new distributed wind capacity, representing 3,311 units and $274 million in investment. 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.

17 WIND ENERGY↗
DOE OSTI2019

Vertical Axis Wind Turbine (VAWT) with Thermoplastic Composite Blades

Rising concerns about global climate change, planet pollution and increasing use of energy have accelerated wider utilization of renewable energy sources. A recent trend in energy system development is decentralization of power generation systems. The opportunity for individuals or organizations to generate electricity locally decreases losses and part of the electricity price caused by the long-distance power transmission. Vertical axis wind turbines (VAWTs) cannot compete with traditional horizontal axis wind turbines (HAWTs) on the basis of aerodynamic performance or maximum power output generated for a given footprint. However, their ability to perform at a wide range of wind speeds, indifference to wind direction, simplicity of fabrication, transportability and maintainability make them ideal candidates for decentralized installations in urban and residential areas. The project team including Steelhead Composites (SHC), Colorado State University (CSU), National Renewable Energy Laboratory (NREL) and Arkema Inc. designed and fabricated a VAWT rotor assembly with thermoplastic composite blades using novel infusion and fabrication techniques. This full-scale VAWT rotor assembly was designed for a rated power output of 0.5-1 kW, as estimated through analytical computational fluid dynamics (CFD) methods. Those CFD simulations were combined with structural finite element analysis (FEA) to optimize the shape and composite layup of the wind blades. Much of the emphasis of this program was to characterize the recyclable thermoplastic material and composite structural design, in order to take full advantage of the material properties of such composites. Additionally, this project examined the potential of thermoplastic resin systems to transform the way VAWT rotor assemblies are joined both in the factory in in the field, by utilizing thermally welded joints to minimize field failure. The infused composite blades manufactured during this program are an excellent example of these benefits made possible by the Arkema thermoplastic resin system. This prototype blade manufacturing also provided the groundwork to inform decisions for larger scale manufacturing techniques applicable to a commercialization strategy. There is specific commercial interest for small scale VAWT’s that are competitively priced, perform to expectations, and have environmentally conscious end-of-life characteristics. Economic analysis was also conducted to compare designs and material usage, providing an estimated levelized cost of energy (LCOE) for the VAWT. The next steps for commercialization would include testing of the rotor assembly to verify predicted performance, specification of the balance of plant components (generator, inverter, etc.), and identification of a manufacturing partner with capability to scale-up production. This program has showed the potential for a commercially viable product through detailed analysis, material characterization and prototype fabrication.

17 WIND ENERGY↗
DOE OSTI2022

Evaluating the effectiveness of a camera-based detection system to support informed curtailment and minimize eagle fatalities at wind energy facilities

The American Wind Wildlife Institute (AWWI – now Renewable Energy Wildlife Institute, REWI) – was appointed prime awardee of DOE award number DE-EE0007880 to lead a team of scientists, wind developers, and technology manufacturers in a collaborative evaluation of the effectiveness of a technology intended to help reduce eagle collisions with wind turbines. IdentiFlight, developed by Renewable Energy Systems (RES) in collaboration with Boulder Imaging, is an autonomous aerial monitoring and detection system. REWI partnered with ecological consultants, Western Ecosystems Technology, Inc. (WEST), to independently evaluate the performance of IdentiFlight reducing eagle collision risk under a suite of environmental conditions relative to the performance of a Biomonitor (human observer-based) Program. The project objectives were to 1) evaluate how IdentiFlight compared to biomonitors in detecting and identifying eagles under a suite of environmental conditions and 2) use the observation data to model how IdentiFlight and biomonitors reduced the eagle fatality prediction through informed curtailment. Field testing was to take place at two geographically distinct wind farms over two field seasons at each wind farm with a study design appropriate for meta-analyses across sites and years.

17 WIND ENERGY↗
DOE OSTI2023

Great Lakes Wind Energy Challenges and Opportunities Assessment

Many issues associated with wind development in the Great Lakes will require solutions different from those developed for offshore wind in ocean states and may not fully benefit from the industry learnings of nearby states. As a result, technology readiness and cost reduction for Great Lakes Wind (GLW) energy generation is likely to be delayed relative to other regions without a substantial, targeted GLW research campaign, and proactive stakeholder engagement in the region at all levels. Failure to conduct the necessary research to lower GLW costs in the near term could limit its contribution to the Nation's decarbonization goals by 2035, and could potentially raise long term energy prices in Great Lakes states if demand for renewable energy continues to accelerate. The overall objective of a research program such as that described in this report would be to enable the realization of commercial GLW before 2035. With the aim of ensuring that prospective development of GLW is conducted efficiently, safely, and coordinated in the best interests of the local residents and stakeholders, the U.S. Department of Energy (DOE) Wind Energy Technologies Office (WETO) tasked the National Renewable Energy Laboratory (NREL) to assist in (a) developing an improved understanding of offshore wind power's development potential in the Great Lakes, (b) identifying the key issues that need to be resolved for this potential to be achieved, and (c) defining a comprehensive research program to address and resolve these issues. This report presents the results of NREL's effort to address these needs.

cost modeling↗
DOE OSTI2023

Setting the Baseline: The Current Understanding of Equity in Land-Based Wind Energy Development and Operation

As discussions about economic equity and environmental justice have become more prevalent in recent years, the related concepts of "energy justice" or "energy equity" have received increasing attention from policymakers, industry, nonprofits, and academics. According to the Initiative for Energy Justice (2019), energy justice is defined as "The goal of achieving equity in both the social and economic participation in the energy system, while also remediating social, economic, and health burdens on those disproportionately harmed by the energy system" The state of equity as it applies specifically to wind energy, however, remains relatively unexplored and isolated to academia. As a result, the National Renewable Energy Laboratory's Wind Energy Equity Engagement Series aims to better understand equity in wind energy through engagement with experts and communities, including representation in decision-making around new developments, potential impacts to communities near wind energy installations, and community-level distribution of the benefits and burdens of wind energy. This report covers the first three phases of the series.

17 WIND ENERGY↗
DOE OSTI2023

Capacity Density Considerations for Offshore Wind Plants in the United States

The United States is a rapidly emerging market for offshore wind energy, with a project pipeline estimated at over 52 GW as of May 31, 2023 (Musial et al. 2023). The capacity density, measured in megawatts per square kilometer (MW/km 2 ), is a crucial parameter for estimating the magnitude of the development pipeline and the nameplate potential of existing lease areas. The offshore wind energy industry is comprised of diversity of participants, including developers, governmental bodies, investors, environmental advocacy groups, and researchers. These various stakeholders use capacity density in different ways as a key metric for evaluating the potential of individual offshore wind lease area or even a section of ocean space. This report presents our assessment of capacity density values in the current pipeline of emerging U.S. offshore wind farms and a detailed list of the main factors that influence capacity density. This understanding is critical for planning of future lease areas, for estimating the technical resource potential for offshore wind on the U.S. outer continental shelf (OCS), and for estimating ocean space requirements needed for meeting state and national goals for a carbon neutral energy transition.

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 OSTI2021

Deep Reinforcement Learning for Automatic Generation Control of Wind Farms

This paper provides a model-free framework for real-time control of wind farms to accurately track a power reference signal. This problem requires tractable dynamical models for capturing the aerodynamic interaction between wind turbines and controllers that can make decisions in realtime given varying atmospheric conditions. In this paper, we propose a deep reinforcement learning framework to provide real-time yaw control of a wind farm. Modifications have been made to FLOw Redirection and Induction in Steady State (FLORIS), a modeling tool that incorporates transient wake behavior. The control problem is formulated to track a synthetic power reference signal based on historical atmospheric (wind speed and direction) information, price signals, and regulation deployment data from U.S. regional transmission operators. Results indicate that a wind farm, with this control paradigm, can achieve good tracking performance when tested with real atmospheric data.

49 EE - Wind and Water Power Program - Wind (EE-4W↗
DOE OSTI2024

U.S. Wind and Solar PV Supply Curves with Future Land-use Change

This dataset provides future supply curves representing the total resource potential for land-based wind and solar photovoltaic (PV) deployment in the conterminous United States after accounting for the impact of land-use and land-cover change (LULC). We use LULC projections from 2010 to 2050 developed based on the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emission Scenarios. The LULC projections are subsequently fed into the renewable energy potential model (reV), which estimates total available wind and solar capacity after excluding non-developable land. Supply curves are provided for four IPCC scenarios in 2050: A1B, A2, B1, and B2. As a baseline, we also provide the supply curve from the B2 scenario in 2010. In addition to the supply curves, we also provide representative wind and solar generation profiles for each supply curve point. These generation profiles are provided as capacity factors and are based on a 2012 weather year using NSRDB and WindToolkit resource data. For more details on the supply curve and profile datasets included here please refer to README. Additional information on the supply curves and the LULC projections used to generate them, as well as an analysis of their impact on wind and solar deployment under decarbonization can be found in the publication linked below: "U.S. Wind and Solar PV Supply Curves with Future Land-use Change Publication".

Array↗
DOE OSTI2025

Wind Turbine Sound Setbacks and Supply Curves: Ordinances and Extrapolated Trends, 110 Hub Height, 130 Rotor Diameter

This dataset provides a comprehensive set of wind turbine sound setbacks from every residential structure in the contiguous United States (CONUS). A sound setback is defined as the minimum required distance between a residential structure and a hypothetical turbine installation site to ensure that modeled sound levels received at the residence do not exceed local sound ordinances, which are commonly expressed in A-weighted decibels (dBA). Therefore, sound setbacks are a local spatial assessment combining multiple factors, including the sound pressure curve as a function of the observer location (distance and direction) relative to the turbine, local sound regulations, and the geographical distribution of residential structures. The dataset is organized into multiple scenario-based products, detailed as follows: 1. Existing and extrapolated sound setbacks. An existing scenario characterizes sound setbacks only in states or counties that have implemented sound regulations as of 2022. The extrapolated scenarios extend a constant sound threshold to counties that lack explicit sound regulations, with thresholds ranging from 35 to 60 dBA, in 5-dBA increments reflecting the variation observed in current sound ordinances. 2. Sound setbacks in directional and worst scenarios. The directional scenario accounts for the distance and orientation of residential structures relative to a hypothetical turbine location, utilizing the turbine's sound emissions in that specific direction. In contrast, the worst scenario takes loudest sound level at each distance step from the turbine, irrespective of directional considerations, which aligns with current industry practice. 3. Supply curves for Open and Reference Access scenarios. This dataset includes supply curves generated by the reV model, which integrates each of the above sound setbacks into both Open and Reference siting scenarios. In addition, two Open and Reference baselines scenarios were included which do not consider sound setbacks for comparative analysis. All sound setback data are stored in TIF files, with partial maps of the data provided in PNG format. The values in the sound setback raster range from 0 to 1, representing the fraction of developable land within a 90 meter by 90 meter pixel due to sound ordinances. A value of 0 indicates areas where wind energy development is prohibited, while a value of 1 signifies areas fully permissible. The wind turbine parameters used in the sound modeling are based on the land-based turbine from International Energy Agency (IEA), featuring a rated electrical power of 3.4 MW, a rotor diameter of 130 meters, and a hub height of 110 meters. The atmospheric conditions, including wind speed/direction, turbulence, air temperature, relative humidity, and air pressure, that drive the sound generation are obtained from the WIND Toolkit dataset.

Array↗
DOE OSTI2021

Spatially-Explicit Prediction of Capacity Density Advances Geographic Characterization of Wind Power Technical Potential

Mounting interest in ambitious clean energy goals is exposing critical gaps in our understanding of onshore wind power potential. Conventional approaches to evaluating wind power technical potential at the national scale rely on coarse geographic representations of land area requirements for wind power. These methods overlook sizable spatial variation in real-world capacity densities (i.e., nameplate power capacity per unit area) and assume that potential installation densities are uniform across space. Here, we propose a data-driven approach to overcome persistent challenges in characterizing localized deployment potentials over broad extents. We use machine learning to develop predictive relationships between observed capacity densities and geospatial variables. The model is validated against a comprehensive data set of United States (U.S.) wind facilities and subjected to interrogation techniques to reveal that key explanatory features behind geographic variation of capacity density are related to wind resource as well as urban accessibility and forest cover. We demonstrate application of the model by producing a high-resolution (2 km × 2 km) national map of capacity density for use in technical potential assessments for the United States. Our findings illustrate that this methodology offers meaningful improvements in the characterization of spatial aspects of technical potential, which are increasingly critical to draw reliable and actionable planning and research insights from renewable energy scenarios.

17 WIND ENERGY↗
DOE OSTI2023

From Hydrometeor Size Distribution Measurements to Projections of Wind Turbine Blade Leading-Edge Erosion

Wind turbine blade leading-edge erosion (LEE) is a cause of increased operation and maintenance costs and decreased annual energy production. Thus, detailed, site-specific quantification of likely erosion conditions are critically needed to inform wind plant owner/operator decisions regarding mitigation strategies. Estimating the damage potential at a wind plant site requires accurate measurement of precipitation intensity, phase, droplet size distributions, wind speeds and their joint statistics. The current work quantifies the effect of disdrometer type on the characterization of LEE potential at a site in the US Southern Great Plains. using observations from three co-located disdrometers (an optical, an impact and a video disdrometer), along with hub-height wind-speed observations from a Doppler lidar and two LEE models: a kinetic energy model and the Springer model. Estimates of total kinetic energy of hydrometeor impacts over the four-year study period vary by as much as 38%, and coating lifetime derived from accumulated distance-to-failure estimates from the Springer model differ by an even greater amount, depending on disdrometer type. Damage potential at this site is concentrated in time, with 50% of impact kinetic energy occurring in 6–12 h per year, depending on which set of disdrometer observations is used. Rotor-speed curtailment during the most erosive 0.1–0.2% of 10 min periods is found to increase blade lifetimes and lead to the lowest levelized cost of energy.

17 WIND ENERGY↗
DOE OSTI2026

Reference floating wind array designs for three representative regions

This work presents the systematic development of three open-source reference floating wind array designs. The designs are tailored to representative site conditions for three regions of the United States: Humboldt Bay off the coast of California, the Gulf of Maine, and the Gulf of America. We adopted existing reference designs for the individual 15 MW turbines, semisubmersible floating platforms, substations, mooring systems, and power cables – integrating and adapting them as needed for each location. We adapted existing dynamic cable designs to use larger conductor sizes to meet the arrays' power transmission requirements, and we set up redundant mooring systems for each substation. The layout of each array is a uniform-grid design optimized to approximately minimize the levelized cost of energy (LCOE) within a square lease area while satisfying spatial constraints. These constraints ensure adequate clearances between adjacent turbines and between underwater components during the layout optimization to prevent clashing and ensure that all components reside within the lease boundaries. Substations are included to allow accounting for intra-array cable costs. They are placed within the uniform grid to maintain the navigability of the arrays. For each feasible layout considered, annual energy production and cable routing costs are calculated and updated in the LCOE objective function. After the optimization, we refined the cable routing with a mix of algorithmic and manual methods to ensure that the cables avoid mooring system components and approach the substation with adequate clearances. We confirmed the suitability of each reference array's layout by comparing the wake losses at each wind heading angle to the wind rose, observing that the optimized layouts largely avoid wake losses in the predominant wind directions. These reference arrays provide open-source baseline designs to enable future research and innovation of floating wind technology at the array scale.

17 WIND ENERGY↗
DOE OSTI2018

Large-Eddy Simulation Sensitivities to Variations of Configuration and Forcing Parameters in Canonical Boundary-Layer Flows for Wind Energy Applications

Here, the sensitivities of idealized Large-Eddy Simulations (LES) to variations of model configuration and forcing parameters on quantities of interest to wind power applications are examined. Simulated wind speed, turbulent fluxes, spectra and cospectra are assessed in relation to variations of two physical factors, geostrophic wind speed and surface roughness length, and several model configuration choices, including mesh size and grid aspect ratio, turbulence model, and numerical discretization schemes, in three different code bases. Two case studies representing nearly steady neutral and convective atmospheric boundary layer (ABL) flow conditions over nearly flat and homogeneous terrain were used to force and assess idealized LES, using periodic lateral boundary conditions. Comparison with fast-response velocity measurements at five heights within the lowest 50 m indicates that most model configurations performed similarly overall, with differences between observed and predicted wind speed generally smaller than measurement variability. Simulations of convective conditions produced turbulence quantities and spectra that matched the observations well, while those of neutral simulations produced good predictions of stress, but smaller than observed magnitudes of turbulence kinetic energy, likely due to tower wakes influencing the measurements. While sensitivities to model configuration choices and variability in forcing can be considerable, idealized LES are shown to reliably reproduce quantities of interest to wind energy applications within the lower ABL during quasi-ideal, nearly steady neutral and convective conditions over nearly flat and homogeneous terrain.

17 WIND ENERGY↗
DOE OSTI2023

Grand challenges in the design, manufacture, and operation of future wind turbine systems

Abstract. Wind energy is foundational for achieving 100 % renewable electricity production, and significant innovation is required as the grid expands and accommodates hybrid plant systems, energy-intensive products such as fuels, and a transitioning transportation sector. The sizable investments required for wind power plant development and integration make the financial and operational risks of change very high in all applications but especially offshore. Dependence on a high level of modeling and simulation accuracy to mitigate risk and ensure operational performance is essential. Therefore, the modeling chain from the large-scale inflow down to the material microstructure, and all the steps in between, needs to predict how the wind turbine system will respond and perform to allow innovative solutions to enter commercial application. Critical unknowns in the design, manufacturing, and operability of future turbine and plant systems are articulated, and recommendations for research action are laid out. This article focuses on the many unknowns that affect the ability to push the frontiers in the design of turbine and plant systems. Modern turbine rotors operate through the entire atmospheric boundary layer, outside the bounds of historic design assumptions, which requires reassessing design processes and approaches. Traditional aerodynamics and aeroelastic modeling approaches are pressing against the limits of applicability for the size and flexibility of future architectures and flow physics fundamentals. Offshore wind turbines have additional motion and hydrodynamic load drivers that are formidable modeling challenges. Uncertainty in turbine wakes complicates structural loading and energy production estimates, both around a single plant and for downstream plants, which requires innovation in plant operations and flow control to achieve full energy capture and load alleviation potential. Opportunities in co-design can bring controls upstream into design optimization if captured in design-level models of the physical phenomena. It is a research challenge to integrate improved materials into the manufacture of ever-larger components while maintaining quality and reducing cost. High-performance computing used in high-fidelity, physics-resolving simulations offer opportunities to improve design tools through artificial intelligence and machine learning, but even the high-fidelity tools are yet to be fully validated. Finally, key actions needed to continue the progress of wind energy technology toward even lower cost and greater functionality are recommended.

17 WIND ENERGY↗
DOE OSTI2024

Investigating the interactions between wakes and floating wind turbines using FAST.Farm

As floating offshore wind progresses to commercial maturity, wake and array effects across a farm of floating offshore wind turbines (FOWTs) will become increasingly important. While wakes of land-based and bottom-fixed offshore wind turbines have been extensively studied, only recently has this topic become relevant for floating turbines. This work presents an investigation of the mutual interaction between the motions of floating wind turbines and wakes using FAST.Farm. While FAST.Farm has been extensively validated across a wide range of conditions, it has never been validated for FOWT applications. Hence, in the first part of this work, we validate FAST.Farm by comparing simulations of a single FOWT against high-fidelity results from large-eddy simulations available in the literature. The validation is based on wake meandering, mean wake deflection, and velocity deficit at different downstream locations. This validation showed that the original axisymmetric (polar) wake model of FAST.Farm overpredicts the vertical wake deflection induced by shaft tilt and floater pitch, while the new curled wake model is capable of properly capturing the vertical wake deflection. In the second part, we use FAST.Farm to analyze a small three-unit array of FOWTs with a spacing of 7 diameters across a wide range of environmental conditions. The same National Renewable Energy Laboratory 5 MW reference wind turbine atop the OC4-DeepCwind semisubmersible is adopted for the three FOWTs and for the validation against high-fidelity simulations. To assess the effect of the floating substructure, we compare the power production, tower-base moments, and blade-root moments obtained for the floating turbines with the results obtained in a fixed-bottom configuration. The main differences introduced by the floating substructure are the motions induced by the waves, the change in the natural frequencies of the tower caused by differences in the boundary condition at its base, and the larger vertical deflection of the wake deficit due to the mean pitch of the platform. The impact of these differences, as well as other minor effects, are analyzed in detail.

16 TIDAL AND WAVE POWER↗