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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Report of the Condition of a General Electric Transportation Systems Gearbox

Wind power plant operations and maintenance (O&M) costs remain an appreciable contributor to the overall cost of wind energy. Premature of wind turbine gearboxes failures are often a result of abrasive wear, micropitting, scuffing, white-etch cracks, and macropitting issues. Micropitting is a fatigue phenomenon that occurs in Hertzian contacts in both gears and rolling-element bearings that operate in mixed or micro elastohydrodynamic lubrication regimes. Micropitting is influenced by and manifests itself in many different ways depending on operating conditions such as load, speed and operating temperature, and on factors such as gear geometry and accuracy, tooth flank roughness, percentage of tooth sliding, and lubricant composition. Despite much research by many investigators, micropitting remains complex, unpredictable, and difficult to control and remains a problem in wind turbine gearboxes. The purpose of this report is to document and describe the micropitting damage observed in a wind turbine gearbox, thereby facilitating further analysis and examination in future reports.

17 WIND ENERGY↗
DOE OSTI2021

Assessing boundary condition and parametric uncertainty in numerical-weather-prediction-modeled, long-term offshore wind speed through machine learning and analog ensemble

To accurately plan and manage wind power plants, not only does the time-varying wind resource at the site of interest need to be assessed but also the uncertainty connected to this estimate. Numerical weather prediction (NWP) models at the mesoscale represent a valuable way to characterize the wind resource offshore, given the challenges connected with measuring hub-height wind speed. The boundary condition and parametric uncertainty associated with modeled wind speed is often estimated by running a model ensemble. However, creating an NWP ensemble of long-term wind resource data over a large region represents a computational challenge. Here, we propose two approaches to temporally extrapolate wind speed boundary condition and parametric uncertainty using a more convenient setup in which a mesoscale ensemble is run over a short-term period (1 year), and only a single model covers the desired long-term period (20 year). We quantify hub-height wind speed boundary condition and parametric uncertainty from the short-term model ensemble as its normalized across-ensemble standard deviation. Then, we develop and apply a gradient-boosting model and an analog ensemble approach to temporally extrapolate such uncertainty to the full 20-year period, for which only a single model run is available. As a test case, we consider offshore wind resource characterization in the California Outer Continental Shelf. Both of the proposed approaches provide accurate estimates of the long-term wind speed boundary condition and parametric uncertainty across the region (R 2 >0.75), with the gradient-boosting model slightly outperforming the analog ensemble in terms of bias and centered root-mean-square error. At the three offshore wind energy lease areas in the region, we find a long-term median hourly uncertainty between 10 % and 14 % of the mean hub-height wind speed values. Finally, we assess the physical variability in the uncertainty estimates. In general, we find that the wind speed uncertainty increases closer to land. Also, neutral conditions have smaller uncertainty than the stable and unstable cases, and the modeled wind speed in winter has less boundary condition and parametric sensitivity than summer.

17 WIND ENERGY↗
DOE OSTI2025

Contextualizing Wind Turbine Blade Waste: Comparison to Other Global Waste Streams

Worldwide wind energy generation capacity has grown rapidly over the past several decades, and wind turbines installed at the beginning of this wave of growth are approaching the end of their design lifetimes. As an increasing number of wind power plants reach their end of life, both decommissioning and repowering (i.e., dismantling or refurbishing existing turbines and commissioning new ones) will produce waste material from the retired wind turbines, foundations, and balance of plant. However, the amount and type of waste, particularly for wind blades, is often mischaracterized. Although wind turbine components are largely recyclable, the blades are typically made of fiberglass composites, which can present challenges for material recovery and reuse. Within the USA, the accumulation of wind turbine blades in landfills has raised questions about whether the continued expansion of wind energy is sustainable if it results in substantial future waste. This study compares the mass and volume of potential global wind blade waste to other waste streams. It also discusses the materials used to manufacture wind turbine blades and summarizes current options for material redesign, recycling (recovery and reuse), repurposing, and disposal of used blades. The analysis indicates that, although wind turbine blades could represent 14% of the composite market by 2027, the potential future mass and volume of wind turbine blade waste is relatively small compared to other industries. These findings suggest that although the development of scalable, economically viable, and environmentally sustainable methods for wind turbine manufacturing, repurposing, and recycling is important, it may make sense to take advantage of synergies among multiple industries in recycling composite waste, rather than focusing solely on wind turbine blades. From a global perspective, larger sustainability, recycling, and waste stream reduction impacts can be made in other industries, such as transportation and construction.

17 WIND ENERGY↗
DOE OSTI2022

Transmission Alternatives for California North Coast Offshore Wind, Volume 4: Cost-Benefit Analysis Report

The purpose of this report is to compare the costs and benefits of installing offshore wind power plants with capacities up to 500 megawatts (MW) in the Humboldt Wind Energy Area offshore California, focusing on identifying the costs related to transmission upgrades and possible alternatives such as energy storage. We identify several options that result in lower costs than upgrading transmission to provide full deliverability. Our estimates of the levelized cost of energy (LCOE) assuming full deliverability range from $80/MWh for a 144-MW plant to $73/MWh for a 480-MW plant with a 2030 commercial operation date; however, the additional cost of transmission upgrades increases these values to between $86/MWh and $98/MWh. Based on curtailment and revenue estimates developed using a production cost model, the LCOEs for plant capacities of 144 MW and 168 MW with Energy Only deliverability are lower than the combined cost of energy and transmission upgrades for full deliverability. The addition of a 4-hour, 15-MW battery energy storage system increases revenue for both plant sizes, with the 144 MW + storage scenario producing the most revenue relative to LCOE.

17 WIND ENERGY↗
DOE OSTI2022

Blackstart Capability and Survivability of Wind Turbines with Fully Rated Converters

We report the blackstart capability of wind turbines is critical for the recovery of wind-dominant power systems from blackouts. If wind power plants are not able to restore a power system, the incorporation of wind resources into electric grids could be limited by blackstart capability. This paper tackles this problem by setting forth a grid-forming controller for Type 4 wind turbines which employ fully rated power converters. To this end, we engineer two-axis anti-windup proportional-integral regulators that serve to ride through restoration disturbances. We also design an active protection system to prevent wind turbines from stalling during recovery from blackouts. We demonstrate in a high-fidelity simulation environment that Type 4 wind turbines with the developed controllers and protection subsystem can: (i) re-energize a notional wind-dominant grid; (ii) ride through asymmetrical faults; and (iii) survive low wind speed events.

17 WIND ENERGY↗
DOE OSTI2022

Comparative Study of Wind Energy Potential Estimation Methods for Wind Sites in Togo and Benin (West Sub-Saharan Africa)

The characterization of wind speed distribution and the optimal assessment of wind energy potential are critical factors in selecting a suitable site for wind power plants (WPP). The Weibull distribution law has been used extensively to analyze the wind characteristics of candidate WPP sites, and to estimate the available and deliverable energy. This paper presents a comparative study of five wind energy resource assessment methods as they applied to the context of wind sites in West Sub-Saharan Africa. We investigated three numerical approaches, namely, the adaptive neuro-fuzzy inference system (ANFIS), the multilayer perceptron method (MLP), and support vector regression (SVR), to derive the distribution law of wind speeds and to optimally quantify the corresponding wind energy potential. Next, we compared these three approaches to two well-known Weibull distribution law-based methods: the empirical method of Justus (EMJ) and the maximum likelihood method (MLM). Case study results indicated that the neural network-based methods, ANFIS and MLP, yielded the most accurate distribution fits and wind energy potential estimates, and consequently, are the most recommended methods for the wind sites in Togo and Benin. The orders of magnitude of the root mean squared error (RMSE) in estimating the recoverable energy using ANFIS were, respectively, 10-4 and 10-5 for Lomé and Cotonou, while MLP achieved an RMSE order of magnitude of 10-3 for both sites.

17 WIND ENERGY↗
DOE OSTI2024

Hybrid power plant design for low-carbon hydrogen in the United States

In this study, we provide a nationwide techno-economic analysis of clean hydrogen production powered by a hybrid renewable energy plant for over 50,000 locations in the United States. We leverage the open-source Hybrid Optimization Performance Platform (HOPP) tool to simulate the hourly performance of an off-grid wind-solar plant integrated with a 1-GW polymer exchange membrane electrolyzer system. The levelized cost of hydrogen is calculated for varying technology costs, and tax credits to explore cost sensitivities independent of plant design, performance, and site selection. Our findings suggest that strategies for cost reduction include selecting sites with abundant wind resources, complementary wind and solar resources, and optimizing the sizing of wind and solar assets to maximize the hybrid plant capacity factor. These strategies are linked to increased hydrogen production and reduced electrolyzer stack replacements, thereby lowering the overall cost of hydrogen.

08 HYDROGEN↗
NASA NTRS1994

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

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

Spera, David A.↗
DOE OSTI2022

Multifidelity multiobjective optimization for wake-steering strategies

Abstract. Wake steering is an emerging wind power plant control strategy where upstream turbines are intentionally yawed out of perpendicular alignment with the incoming wind, thereby “steering” wakes away from downstream turbines. However, trade-offs between the gains in power production and fatigue loads induced by this control strategy are the subject of continuing investigation. In this study, we present a multifidelity multiobjective optimization approach for exploring the Pareto front of trade-offs between power and loading during wake steering. A large eddy simulation is used as the high-fidelity model, where an actuator line representation is used to model wind turbine blades and a rainflow-counting algorithm is used to compute damage equivalent loads. A coarser simulation with a simpler loads model is employed as a supplementary low-fidelity model. Multifidelity Bayesian optimization is performed to iteratively learn both a surrogate of the low-fidelity model and an additive discrepancy function, which maps the low-fidelity model to the high-fidelity model. Each optimization uses the expected hypervolume improvement acquisition function, weighted by the total cost of a proposed model evaluation in the multifidelity case. The multifidelity approach is able to capture the logit function shape of the Pareto frontier at a computational cost only 30 % that of the single-fidelity approach. Additionally, we provide physical insights into the vortical structures in the wake that contribute to the Pareto front shape.

17 WIND ENERGY↗
DOE OSTI2020

Bethel Wind Energy Construction Project. Final report

Final report for the Bethel (Alaska) Wind Construction project. Under this project, Alaska Village Electric Cooperative, Inc. (AVEC) constructed and commissioned one new 900 kW-capacity wind turbine at a site in Bethel about 3.3 miles NE of the diesel-fired prime power plant. The wind generator’s output will augment the prime source generation provided by the diesel-powered generators.

17 WIND ENERGY↗
DOE OSTI2026

Grid and Wind Transient Ride Through Assessment of Type-5 Synchronous Wind Turbine

The integration of the inverter-based renewable energy resources is increasing and replacing conventional synchronous generators in the evolving bulk power system (BPS), impacting the system inertia along the way. Also, the limited over-current capability of power electronic converters continues to deteriorate the grid strength of the evolving power systems. Type-5 wind turbines have the potential to mitigate these problems because this configuration interfaces with the grid through a synchronous generator; hence, its operation and consequent grid impacts might mimic the conventional synchronous generator. The drivetrain of this type of turbines, however, is different from the more common Type-3 and Type-4 turbines. A hydraulic torque converter and gearbox with torque limiting feature are integral parts of a Type-5 wind turbine drivetrain, to isolate the wind speed variations at the wind turbine rotor from the grid connected generator side. This supports the synchronous operation of the generator. However, high fidelity models of Type-5 wind turbine drivetrain including these core components are not openly and widely available for grid integration and transient stability studies. Moreover, Type-5 turbines are not commonly deployed and hence its power generation and frequency stability characteristics are not widely publicized. This hinders appropriate assessment of Type-5 wind power plant's contribution to bulk grid resilience. This work provides transient stability assessment of a standalone Type-5 wind turbine. Normal operation and grid transient studies are performed to see the step load change and wind speed disturbance impacts on the Type-5 drivetrain and generation dispatch. Preliminary results show that Type-5 wind turbines can support load changes of between 0.6 p.u to 1.15 p.u. Beyond this point, the synchronization of the generator starts to deviate from its set point.

17 - WIND ENERGY↗
DOE OSTI2023

2022 Cost of Wind Energy Review [Slides]

The 12th annual Cost of Wind Energy Review, now presented in slide deck format, uses representative utility-scale and distributed wind energy projects to estimate the levelized cost of energy (LCOE) for land-based and offshore wind power plants in the United States.

17 WIND ENERGY↗
DOE OSTI2023

Machine Learning–Adjusted WRF Forecasts to Support Wind Energy Needs in Black Start Operations

Abstract The push for increased capacity of renewable sources of electricity has led to the growth of wind-power generation, with a need for accurate forecasts of winds at hub height. Forecasts for these levels were uncommon until recently, and that, combined with the nocturnal collapse of the well-mixed boundary layer and daytime growth of the boundary layer through the levels important for energy generation, has contributed to errors in numerical modeling of wind generation resources. The present study explores several machine learning algorithms to both forecast and correct standard WRF Model forecasts of winds and temperature at hub height within wind turbine plants over several different time periods that are critical for the anticipation of potential blackouts and aiding in black start operations on the power grid. It was found that mean square error for day-2 wind forecasts from the WRF Model can be improved by over 90% with the use of a multioutput neural network, and that 60-min forecasts of WRF error, which can then be used to adjust forecasts, can be made with an LSTM with great accuracy. Nowcasting of temperature and wind speed over a 10-min period using an LSTM produced very low error and especially skillful forecasts of maximum and minimum values over the turbine plant area.

17 WIND ENERGY↗
DOE OSTI2023

Chapter 14 - Reliability of Wind Turbines

The global wind energy industry has grown at a fast pace during the past half-decade. Advancements from design and manufacturing to operation and maintenance have led to reduced capital and maintenance costs, which make wind power an indispensable source for a comprehensive solution to global electricity needs. Once wind turbines are installed, the opportunity to lower wind power costs is mainly through improved operation and maintenance practices. Modern wind turbines are equipped with tens or hundreds of measurement channels and are generating an abundance of data, with lot of efforts being put into data analysis by both the research community and the industry. One type of analysis is through the exploration of reliability engineering methods based on readily available data or maintenance records collected at typical wind power plants. If adopted and conducted appropriately, these analyses can quickly save operation and maintenance costs in a potentially impactful manner. The wind industry has adopted this discipline more broadly in recent years. This chapter discusses wind turbine reliability by highlighting the methodology of reliability engineering life data analysis. It first briefly discusses the fundamentals of wind turbine reliability and the current industry status. Then, the reliability engineering method for life analysis, including data collection, model development, and forecasting, is presented in detail and illustrated through two case studies. The chapter concludes with some remarks on potential opportunities to improve wind turbine reliability. An owner and operator's perspective is taken and mechanical components are used to exemplify the potential benefits of reliability engineering analysis to improve wind turbine reliability and availability.

database↗
DOE OSTI2023

Yaw-Augmented Control for Wind Farm Power Tracking: Preprint

This paper presents an inner-outer control loop structure which uses wake steering (yaw control) to augment pitch control for wind farms to track a power reference signal. The outer-loop yaw controller employs a recently proposed dynamic yaw model with a time-varying graph structure that accounts for dynamic changes in the farm wake interactions due to the yaw action of upstream turbines. The wake interactions within the model include the physics of the streamwise and lateral wake evolution, which collectively determine its impact on downstream turbines. The inner-loop employs a compensation scheme to account for the slow timescale effects of the yaw control actions within the faster timescale pitch control. The controller is applied to track two power trajectories (typical of secondary frequency regulation signals) using a large eddy simulation wind farm plant. The results demonstrate that the additional control authority from yaw provides some added benefit in reducing the required turbine derates needed for wind farms to track transient power increases in the proposed setting. However, the benefit decreases and pitch control alone is sufficient when the turbines are derated beyond a certain level. These findings suggest that augmenting pitch control with yaw may provide financial incentives in terms of allowing wind farms to maximize power supply to the bulk power market while still providing regulation services. Further work is needed analyze the costs versus benefits of the additional control complexity versus bandwidth in augmenting pitch control with wake steering offers in these applications.

active power control↗
NASA NTRS1973

Economic considerations of utilizing small wind generators

The economic feasibility of small wind generators is compared to that of solar cells, primary batteries, thermoelectric generators, and engine generators. It is shown that small wind generator plants offer an attractive alternative to primary battery systems and constantly running engines to generate power in remote areas. The limitation is an annual average wind velocity of at least 9 to 10 mph. Presently available units are most useful in the average load range of 10 to 1000 watts.

Dodge, R.↗
DOE OSTI2022

Stochastic agent-based model for predicting turbine-scale raptor movements during updraft-subsidized directional flights

Rapid expansion of wind energy development across the world has highlighted the need to better understand turbine-caused avian mortality. The risk to golden eagles (Aquila chrysaetos) is of particular concern due to their small population size and conservation status. Golden eagles subsidize their flight in part by soaring in orographic updrafts, which can place them in conflict with wind turbines utilizing the same low-altitude wind resource. Understanding the behavior of soaring raptors in varying atmospheric conditions can therefore be relevant to predicting and mitigating their risk of collision. We present a predictive movement model that simulates individual paths of golden eagles during directional flight (such as migration) that is subsidized by orographic updraft. We modeled eagles in a 50 km by 50 km study area in Wyoming containing three wind power plants with documented golden eagle collisions with turbines. The movement model is applicable to any region where ground elevation is known at turbine scale (50 m) and wind conditions are known at facility scale (3 km). For a given set of atmospheric conditions, the model simulates movements of thousands of orographic soaring eagles to produce a density map quantifying the relative probability of eagle presence. We validated the simulated tracks with GPS telemetry data showing four directional tracks made by golden eagles transiting through the area in 2019 and 2020. For each eagle track, validation was performed using the ratio of the model-simulated eagle presence likelihood with uniform eagle presence and the presence computed using directed random-walk movements. We found that the predictive performance of the model was significantly better (likelihood ratio 1) for low-altitude movements than high-altitude movements that can involve thermal-soaring. We employed the model to produce seasonal presence maps for migrating golden eagles. We found significant turbine-level variations in eagle presence between northerly and southerly migration routes through the study area. Overall, the proposed model offers a generalizable, probabilistic, and predictive tool to assist wind energy developers, ecologists, wildlife managers, and industry consultants in estimating the potential for conflict between soaring birds and wind turbines, thereby reducing the need for site-specific data on golden eagle movements.

17 WIND ENERGY↗
DOE OSTI2025

Control Design and EMT Simulation Toward the Restoration of Faulted Wind-Dominant Grids

Present power engineers have been challenged to employ electromagnetic transient (EMT) simulations to study the restoration of wind-dominant grids. This paper addresses this hurdle by developing strategies to: (i) reliably control the dc-link voltage of grid-forming wind turbines with dc-coupled batteries, (ii) tune controllers to stably interconnect wind power plants into a grid under recovery, and (iii) autonomously make restoration decisions if transmission faults occur during restoration. These contributions are assessed via EMT simulations of wind-dominant versions of the WSCC 9-bus grid and a 22-bus power system. Furthermore, this paper is significant to address recommendations by the North American Electric Reliability Corporation.

17 WIND ENERGY↗