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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.

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

Comparison of Satellite-Derived Wind Measurements with Other Wind Measurement Sensors

The purpose of this paper is to compare the good data from the Jimsphere launches with the data from the satellite system. By comparing the wind speeds from the Fixed Pedestal System 16 (FPS-16) Radar/Jimsphere Wind System and NASA's 50-MHz Radar Wind Profiler, the validation of winds from Geostationary Operational Environmental Satellite 7 (GOES-7) is performed. This study provides an in situ data quality check for the GOES-7 satellite winds. Comparison was made of the flowfields in the troposphere and the lower stratosphere of case studies of pairs of Jimsphere balloon releases and Radar Wind Profiler winds during Space Shuttle launches. The mean and standard deviation of the zonal component statistics, the meridional component statistics, and the power spectral density curves show good agreement between the two wind sensors. The standard deviation of the u and v components for the STS-37 launch (consisting of five Jimsphere/Radar Wind Profiler data sets) was 1.92 and 1.67 m/s, respectively; for the STS-43 launch (there were six Jimsphere/Wind Profiler data sets) it was 1.39 and 1.44 m/s, respectively. The overall standard deviation was 1.66 m/s for the u component and 1.55 m/s tor the v component, and a standard deviation of 2.27 m/s tor the vector wind difference. The global comparison of satellite with Jimsphere balloon vector winds shows a standard deviation of 3.15 m/s for STS-43 and 4.37 m/s for STS-37. The overall standard deviation of the vector wind was 3.76 m/s, with a root-mean-square vector difference of 4.43 m/s. These data have demonstrated that this unique comparison of the Jimsphere and satellite winds provides excellent ground truth and a frame of reference during testing and validation of satellite data

Susko, Michael↗
DOE OSTI2025

Joint Modeling of Wind Speed and Wind Direction Through a Conditional Approach

Atmospheric near surface wind speed and wind direction play an important role in many applications, ranging from air quality modeling, building design, wind turbine placement to climate change research. It is therefore crucial to accurately estimate the joint probability distribution of wind speed and direction. In this work, we develop a conditional approach to model these two variables, where the joint distribution is decomposed into the product of the marginal distribution of wind direction and the conditional distribution of wind speed given wind direction. To accommodate the circular nature of wind direction, a von Mises mixture model is used; the conditional wind speed distribution is modeled as a directional dependent Weibull distribution via a two-stage estimation procedure, consisting of a directional binned Weibull parameter estimation, followed by a harmonic regression to estimate the dependence of the Weibull parameters on wind direction. A Monte Carlo simulation study indicates that our method outperforms two other approaches in estimation efficiency: one that utilizes periodic spline quantile regression and another that generates data from the commonly used Abe-Ley distribution for cylindrical data. We illustrate our method by using the output from a regional climate model to investigate how the joint distribution of wind speed and direction may change under some future climate scenarios. Our method indicates significant changes in the variation of wind speed with respect to some directions.

17 WIND ENERGY↗
DOE OSTI2022

Comparison of the Gaussian Wind Farm Model with Historical Data of Three Offshore Wind Farms

A recent expert elicitation showed that model validation remains one of the largest barriers for commercial wind farm control deployment. The Gaussian-shaped wake deficit model has grown in popularity in wind farm field experiments, yet its validation for larger farms and throughout annual operation remains limited. This article addresses this scientific gap, providing a model comparison of the Gaussian wind farm model with historical data of three offshore wind farms. The energy ratio is used to quantify the model’s accuracy. We assume a fixed turbulence intensity of $I_∞$ = 6% and a standard deviation on the inflow wind direction of $σ_{wd}$ = 3° in our Gaussian model. First, we demonstrate the non-uniqueness issue of $I_∞$ and $σ_{wd}$, which display a waterbed effect when considering the energy ratios. Second, we show excellent agreement between the Gaussian model and historical data for most wind directions in the Offshore Windpark Egmond aan Zee (OWEZ) and Westermost Rough wind farms (36 and 35 wind turbines, respectively) and wind turbines on the outer edges of the Anholt wind farm (110 turbines). Turbines centrally positioned in the Anholt wind farm show larger model discrepancies, likely due to deep-array effects that are not captured in the model. A second source of discrepancy is hypothesized to be inflow heterogeneity. In future work, the Gaussian wind farm model will be adapted to address those weaknesses.

17 WIND ENERGY↗
DOE OSTI2020

Power and Wind Shear Implications of Large Wind Turbine Scenarios in the US Central Plains

Continued growth of wind turbine physical dimensions is examined in terms of the implications for wind speed, power and shear across the rotor plane. High-resolution simulations with the Weather Research and Forecasting model are used to generate statistics of wind speed profiles for scenarios of current and future wind turbines. The nine-month simulations, focused on the eastern Central Plains, show that the power scales broadly as expected with the increase in rotor diameter (D) and wind speeds at hub-height (H). Increasing wind turbine dimensions from current values (approximately H = 100 m, D = 100 m) to those of the new International Energy Agency reference wind turbine (H = 150 m, D = 240 m), the power across the rotor plane increases 7.1 times. The mean domain-wide wind shear exponent (α) decreases from 0.21 (H = 100 m, D = 100 m) to 0.19 for the largest wind turbine scenario considered (H = 168 m, D = 248 m) and the frequency of extreme positive shear (α > 0.2) declines from 48% to 38% of 10-min periods. Thus, deployment of larger wind turbines potentially yields considerable net benefits for both the wind resource and reductions in fatigue loading related to vertical shear.

17 WIND ENERGY↗
DOE OSTI2021

A Twenty-Year Analysis of Winds in California for Offshore Wind Energy Production Using WRF v4.1.2

Offshore wind resource characterization in the United States relies heavily on simulated winds from numerical weather prediction (NWP) models, given the lack of hub-height observations offshore. One such NWP data set used extensively by U.S. stakeholders is the Wind Integration National Dataset (WIND) Toolkit, a 7-year time-series data set produced in 2013 by the National Renewable Energy Laboratory. In this study, we present an update to that data set for offshore California that leverages recent advancements in NWP modeling capabilities and extends the period of record to a full 20 years. The data set predicts a significantly larger wind resource (0.25–1.75 m s-1 stronger), including in three Call Areas that the Bureau of Ocean Energy Management is considering for commercial activity. We conduct a set of yearlong simulations to study factors that contribute to this increase in the modeled wind resource. The largest impact arises from a change in the planetary boundary layer parameterization from the Yonsei University scheme to the Mellor-Yamada-Nakanishi-Niino scheme and their diverging wind profiles under stable stratification. Additionally, we conduct a refined wind resource assessment at the three Call Areas, characterizing distributions of wind speed, shear, veer, stability, frequency of wind droughts, and power production. We find that, depending on the attribute, the new data set can show substantial disagreement with the WIND Toolkit, thereby driving important changes in predicted power.

49 EE - Wind and Water Power Program - Wind (EE-4W↗
DOE OSTI2025

Uplifting winds: The surprisingly positive community-wide impact of wind energy installations on property values

A primary concern of stakeholders when considering a new wind project is the potential negative effects wind turbines may have on home values. Yet, what has been surprisingly overlooked in the literature and general discourse around wind energy is that the well-researched positive economic development and fiscal and amenity benefits of wind energy (e.g., increased tax base, tax revenue, better public services and employment gains) might positively affect jurisdiction-wide housing values. With a focus on school districts in the United States, we compare home values in school districts with wind energy installations, before and after a wind energy installation becomes operational, to home values in other school districts located in the same county but without a wind energy installation to provide some of the first causal evidence on the relationship between wind energy projects and district-wide property values. We find that wind projects lead to economically meaningful increases in district-wide housing values of approximately 3 %, when those values are compared to similar homes located in school districts in same-county without wind energy. The effect is strongly correlated with wind project size. The mechanisms, our research suggests, are likely related to relatively large increases in school district per-pupil revenues and expenditures, which are also correlated with wind project size. We suggest other possible mechanisms for the increased values as well.

Attitudes↗
NASA NTRSDate not supplied

AWP: NASA's Aerosol Wind Profiler Coherent Doppler Wind Lidar

A new airborne coherent Doppler Wind Lidar (DWL) instrument has been implemented leveraging NASA's development of the 2-micron Wind-Space Pathfinder (Wind-SP) lidar transceiver. A technology development project, Wind-SP refined and demonstrated numerous components required for a coherent-detection space wind lidar instrument. Aerosol Wind Profiler (AWP) transitioned this transceiver into an airborne wind lidar capable of providing full 3-D wind vector retrievals. AWP operates with laser pulse energy and repetition rate combination required for high spatial and vertical resolution wind profiling from space. Operation from aircraft platforms will yield very strong signal return required for detailed process studies at <2km spatial and <100m vertical resolution under most conditions. AWP will serve as NASA’s wind calibration and validation instrument for future space-based wind observations over the coming decades, while also providing data supporting space wind lidar simulation studies. The AWP instrument is introduced and preliminary results from recent AWP demonstration flights are presented.

AWP↗
DOE OSTI2022

Verification and Validation of Model-Scale Turbine Performance and Control Strategies for the IEA Wind 15 MW Reference Wind Turbine

To enable the fast growth of the floating offshore wind industry, simulation models must be validated with experimental data. Floating wind model-scale experiments in wind–wave facilities have been performed over the last two decades with varying levels of fidelity and limitations. However, the turbine controls in these experiments have considered only limited control strategies and implementations. To allow for control co-design, this research focuses on implementing and experimentally validating more advanced turbine control actions and strategies in a wind–wave basin for a 1:70-scale model of the International Energy Agency’s wind 15 MW reference wind turbine. The control strategies analyzed include torque control, collective pitch control, and transition region control (setpoint smoothing). Our experimental and numerical results include the effects of varying rotor speeds, blade pitches, and wind environments on the turbine thrust and torque. Numerical models from three different software tools are presented and compared to the experimental results. Their ability to effectively represent the aero-dynamic response of the wind turbine to the control actions is successfully validated. Finally, turbine controller tuning parameters based on the derivatives of thrust and torque are derived to allow for improved offshore wind turbine dynamics and to validate the ability of modeling tools to model the dynamics of floating offshore wind turbines with control co-design.

17 WIND ENERGY↗
DOE OSTI2023

Effects of wind field characteristics on pitch bearing reliability: a case study of 5 MW reference wind turbine at onshore and offshore sites; Auswirkungen von Windfeldeigenschaften auf die Zuverlässigkeit von Rotorblattlagern: eine Fallstudie über eine 5-MW-Referenz-Windkraftanlage an Onshore- und Offshore-Standorten

This paper presents a study on pitch bearing basic rating life affected by wind field characteristics at both onshore and offshore wind sites. The National Renewable Energy Laboratory 5 MW reference wind turbine is selected for the study. Wind field characteristics including reference hub height mean wind speed, wind speed distribution, wind shear, and vertical inflow are studied. A decoupled approach is employed where global analysis is performed first. Second, the load effects from the global analysis are applied on a reference pitch bearing designed based on best industrial practices. For the case study onshore site, it is found that the Kernel density estimation best fits the wind distribution, while the International Electrotechnical Commission proposed distribution appears to be not suitable. Moreover, it is shown that the seed number has high effect on the bearing life in turbulence wind and the wind speeds around rated have the highest contribution in both bearing fatigue damage and extreme load failure. The results contribute to better understanding of the wind field characteristics on the pitch bearing life.

17 WIND ENERGY↗
DOE OSTI2023

Wind Fields in Category 1–3 Tropical Cyclones Are Not Fully Represented in Wind Turbine Design Standards

Abstract Offshore wind energy deployment in the U.S. is expected to increase in the years to come, with proposed wind farm sites located in regions with high risk for tropical cyclones. Yet, the wind turbine design criteria outlined by the International Electrotechnical Commission for extreme events may not account for wind field characteristics unique to tropical cyclones. To evaluate if current design standards capture the extreme conditions of these storms, we perform idealized large‐eddy simulations of three tropical cyclones (one Category 1, one Category 2, and one Category 3 storms) using the Weather Research and Forecasting model. Wind conditions near the eyewall of Cat‐1, Cat‐2, and Cat‐3 storms can exceed current design standards for offshore wind turbines. Winds at 90 m can be faster than outlined in the design criteria for Class I and Class T turbines for 50‐year recurrence periods. Wind speed shear across the turbine rotor layer is also larger than assumed in design specifications. Moreover, vertical variations in wind direction across the turbine rotor layer are large for tropical cyclones of all intensity levels, suggesting design standards should include veer, which can amplify loads in wind turbines. The existence of hurricane wind field characteristics that are not represented in design standards does not imply that damage or failure will certainly occur. Engineering safety factors incorporated in the design of the turbine's blades and structural components may prevent damage from occurring.

17 WIND ENERGY↗
DOE OSTI2024

Modeling the effect of wind speed and direction shear on utility‐scale wind turbine power production

Abstract Wind speed and direction variations across the rotor affect power production. As utility‐scale turbines extend higher into the atmospheric boundary layer (ABL) with larger rotor diameters and hub heights, they increasingly encounter more complex wind speed and direction variations. We assess three models for power production that account for wind speed and direction shear. Two are based on actuator disc representations, and the third is a blade element representation. We also evaluate the predictions from a standard power curve model that has no knowledge of wind shear. The predictions from each model, driven by wind profile measurements from a profiling LiDAR, are compared to concurrent power measurements from an adjacent utility‐scale wind turbine. In the field measurements of the utility‐scale turbine, discrete combinations of speed and direction shear induce changes in power production of −19% to +34% relative to the turbine power curve for a given hub height wind speed. Positive speed shear generally corresponds to over‐performance and increasing magnitudes of direction shear to greater under‐performance, relative to the power curve. Overall, the blade element model produces both higher correlation and lower error relative to the other models, but its quantitative accuracy depends on induction and controller sub‐models. To further assess the influence of complex, non‐monotonic wind profiles, we also drive the models with best‐fit power law wind speed profiles and linear wind direction profiles. These idealized inputs produce qualitative and quantitative differences in power predictions from each model, demonstrating that time‐varying, non‐monotonic wind shear affects wind power production.

Energy & Fuels↗
DOE OSTI2021

Power increases using wind direction spatial filtering for wind farm control: Evaluation using FLORIS, modified for dynamic settings

As wind energy plays a growing role in the energy sector, new methods for controlling wind turbines and wind farms to maximize performance are garnering industry interest. A developing body of research treats the entire wind farm as a control system, with individual turbines acting as agents in a network, allowing farm-level objectives to be considered. Two promising developments in this research are wake steering control, which seeks to increase the power generated at a wind farm by directing the wakes of upstream turbines away from downstream ones, and communication-based spatial filtering, which seeks to improve the quality of information used by turbine- and farm-level controllers by combining measurements of the wind field collected at the individual turbines. The latter method has been shown to improve the estimates of wind direction at the turbines; however, the resulting potential for increased power capture warrants further investigation. With this paper, we begin to address this gap by combining wake steering with wind direction spatial filtering. To do so, we present a preliminary method for assessing the power capture of dynamic controllers using wind farm codes designed for time-averaged simulation. This allows us to generate results much more rapidly than would be possible using high-fidelity wind farm simulators and may be useful in many wind farm control design applications.

17 WIND ENERGY↗
DOE OSTI2024

Land-based wind plant wake characterization using dual-Doppler radar measurements at AWAKEN

Wind plant wakes have been shown to persist for tens of kilometers downstream in offshore environments, reducing the power output of neighboring plants, but their behavior on land remains relatively unexplored through observation. This study capitalizes on the unique and extensive field data collected for the American WAKE ExperimeNt (AWAKEN) project underway in northern Oklahoma. X-band dual-Doppler radars deployed at this site measure wind speed and direction at 25-m and 2-min resolution within a 30-km range, capturing the interactions between three neighboring wind plants. These measurements show that the wake of one wind plant extends at least 15 km downstream under easterly wind and stable atmospheric conditions. Though the wake wind speed increases within the first 10 km, it plateaus at 90% of the freestream wind speed. The spanwise velocity distribution within the wake initially shows the clear signature of the wind plant layout, which is smoothed as it propagates downstream, indicating spanwise momentum transfer is a key mechanism in wind plant wake development and recovery. These findings have important implications for wind plant siting decisions and resource assessments, and provide insights into atmospheric interactions at the wind plant scale.

17 WIND ENERGY↗
DOE OSTI2020

Large-Eddy Simulations of Idealized Atmospheric Boundary Layers Using Nalu-Wind

Accurate prediction of wind-plant performance relies, in part, on properly characterizing the turbulent atmospheric boundary layer (ABL) flow in which wind turbines operate. Large-eddy simulation (LES) is a powerful tool for simulating ABLs because it resolves the largest, most energetic scales of three-dimensional turbulent motions. Yet LES predictions are well known to depend on modeling choices such as grid resolution, numerical discretization schemes, and closures for unresolved scales of turbulence. Here, we evaluate how these choices influence predictions of ABL winds using Nalu-Wind, a wind-specific fork of the open-source, generalized, unstructured, massively parallel flow solver NaluCFD/Nalu.

17 WIND ENERGY↗
DOE OSTI2021

Integration of Storage in the DC Link of a Full Converter-Based Distributed Wind Turbine

Energy storage is known to support the dispatchability of variable renewable resources. In this paper, we model a battery energy storage system (BESS) integrated with the DC link of a Type IV full converter-based wind turbine and the necessary controls to achieve efficient dispatch. To support the validation of control methodologies, we build a detailed model of a Type IV research wind turbine at the National Renewable Energy Laboratory (NREL), the Controls Advanced Research Turbine (CART 3), and we integrated a lithium-ion BESS model in grid-following mode into the model. The simulation results illustrate the sizing and control of the DC link-integrated BESS for a given variable wind resource and varying dispatch strategies (i.e., under constant, uncertain, and ramping wind scenarios). The integrated storage can smooth variabilities in distributed wind output, hedge against uncertainties, provide the ramping capability, as well as support stability under voltage and frequency transients. All of these have been illustrated in MATLAB/Simulink.

DC-link voltage↗
DOE OSTI2022

Advanced Distributed Wind Turbine Controls Series: Part 2-Wind Energy in Isolated Grids – Microgrids, Infrastructure Resilience, and Advanced Controls Launchpad (MIRACL)

In an isolated grid, wind turbines are typically deployed to provide energy to maximize energy production, reduce diesel-fuel consumption, reduce carbon emissions, and reduce costs for energy and fuel transportation. However, in addition to solely providing energy to the power system, wind turbines contain rotating masses and inverter-based controls that can enable various reliability and resilience services through advance controls. As part of the Microgrids, Infrastructure Resilience, and Advanced Controls Launchpad (MIRACL) this paper demonstrates, through desktop simulations, advanced wind turbine controls that can be employed to support higher contributions of wind in isolated grids, and to demonstrate ways that wind can play a role in supporting stability of an isolated grid. This isolated grid used in these desktop simulations is comprised of a wind turbine (600 kW), solar PV (430 kW), battery energy storage system (1 MW/1MWh), a simulated diesel generator (2 MW) and various types of loads (critical, dynamic). We developed a model of the subsystems in MATLAB/Simulink and validated them with available data from real-world components on NREL's Flatirons Campus. These validated models are then configured for various case studies. We compare the output of the desktop simulation with a baseline case with the diesel generator. Active and reactive power control of the wind turbine can help improve frequency and voltage responses in the isolated grid, respectively. By utilizing a small integrated battery energy storage system in the DC-link of the wind turbine, we also demonstrate that wind turbines can help blackstart a critical load comparable to its rated power and support other renewables (e.g. solar PV) come online and pick up an additional load. This report illustrates some of these reliability and resilience services a wind turbine can provide in an isolated grid.

17 WIND ENERGY↗
DOE OSTI2021

Estimation of the Ambient Wind Field From Wind Turbine Measurements Using Gaussian Process Regression

In the search for a lower levelized cost of wind energy, one approach is to increase the accuracy of wind turbine measurements such as wind speed and wind direction. The sensors available on wind turbines are susceptible to local turbulence and measurement bias, which can result in suboptimal turbine performance. As an alternative, recent research has considered using the sensor measurements in a coordinated manner. With such a cooperative approach, the local wind conditions can be estimated more accurately and reliably without the need for additional measurement equipment. In this paper, a novel wind field estimation approach is presented that estimates the local wind conditions based on turbine measurements using Gaussian processes. We show that the estimation framework is able to improve the accuracy of the wind direction estimate both in an offline and online manner, as well as identify possible biases in the sensors and reduce unnecessary wind turbine yaw activity.

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