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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 19 records
All sourcesNASA NTRSDOE OSTI
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 OSTI2022

Offshore Testing Facility – Small Scale Turbine Testing and Development Final Technical Report

In July 2010 funding for an award was made available under contract DE-EE0004200 which is the focus of this report. Under this funding, The U.S. Department of Energy’s (USDOE) designated Florida Atlantic University’s (FAU) state of Florida marine renewable energy focused Center of Excellence for Ocean Energy Technology as the Southeast National Marine Renewable Energy Center (SNMREC). The award was advertised in 2008, when the USDOE Wind and Water Program issued a funding opportunity announcement (DE-PS36-08GO98030) to establish university-led National Marine Renewable Energy Centers (NMRECs). Although FAU was selected for this opportunity, funding did not become available until 2010 at which time three of the original five years of performance remained and scope was adjusted accordingly. This award was divided into two phases. The first phase focused on marine energy turbine system enhancement and research while the second phase aimed to advance offshore capabilities and testing opportunities for small-scale demonstration turbines. The project’s objective was to increase the nation’s capabilities, knowledge, and competitiveness with respect to ocean current energy technology. This project successfully achieved these goals by advancing marine energy technology testing opportunities and capabilities. This report details these accomplishments by phase and task. Descriptions include any relevant results, challenges, achievements, and outcomes. Additional intellectual products and publications are listed in the Appendix where detailed technical explanations can be found. Further, because this award designated SNMREC as a USDOE center, it challenges FAU to continue providing value for the marine energy sector in the long term. The direct accomplishments of this project, though noteworthy, are also the seeds for a greater partnership between the USDOE and FAU. SNMREC, leveraging its designation as an NMREC under this award, will expand these contributions for decades to come as a coordinated sustainable program that can serve the marine energy sector’s needs as they arise.

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

Turbine scale and siting considerations in wind plant layout optimization and implications for capacity density

Improvements in wind energy technology, reduced costs, and ambitious clean energy goals have led to projections of high wind contribution in coming years. Developing methodologies to design wind plants with a variety of siting constraints and turbine sizes helps enable high wind penetration, and gain a better understanding of how wind plants are sensitive to setback constraints and turbine design. In this paper, we present a two-step optimization method to simultaneously determine the optimal number of turbines and their locations in a wind plant domain divided into many small, discrete parcels. We present the optimized performance metrics of a wind plant optimized with different turbine sizes and ratings, and with different siting restrictions within the wind plant. Our results indicate that taller and larger turbines are more sensitive to increasing siting constraints. We also compare the optimal wind plant layouts and performance for wind plants optimized for minimum COE and maximum profit. Wind plants optimized for profit had 130%-190% of the capacity of plants optimized for COE, which demonstrates that the optimal results are greatly affected by the objective function, which should be carefully considered. Finally, in this paper we demonstrate the effect of increasing siting constraints on wind plant capacity density, and how the results change when different land areas are used to calculate capacity density. When using the entire wind plant boundary area to determine capacity density, increasing siting constraints decreases the capacity density. However, when we only use the available area (the area left after removing the siting constraints) to calculate the capacity density, increasing the siting constraints increases capacity density. This is a critical insight because of how capacity density is typically defined and used in research, and has important implications for assessment of technical potential and capacity expansion modeling, as well as future wind deployment potential.

17 WIND ENERGY↗
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 OSTI2020

Validation of FAST.Farm Against Full-Scale Turbine SCADA Data for a Small Wind Farm

FAST.Farm is a new midfidelity engineering tool developed by the National Renewable Energy Laboratory targeted at accurately and efficiently predicting wind turbine power production and structural loading in wind farm settings, including wake interactions between turbines. FAST.Farm is based on some of the principles of the Dynamic Wake Meandering model—including passive tracer modeling of wake meandering—but addresses many of the limitations of previous Dynamic Wake Meandering (DWM) implementations. Previous FAST.Farm verification studies show the similarities and differences between FAST.Farm and large-eddy simulations for rigid and flexible turbines. In this validation study, FAST.Farm turbine responses are compared to multiturbine measurements from a subset of a full-scale wind farm. FAST.Farm predictions of turbine generator power, rotor speed, and blade pitch for five-turbine simulations are compared to supervisory control and data acquisition results. Results reveal that FAST.Farm generator power mean and standard deviation results reasonably match measured data for upstream and downstream turbines, as well as the mean rotor speed and blade pitch above rated wind speeds. However, FAST.Farm generally underpredicts the mean rotor speed and overpredicts the mean blade pitch below rated operation. These errors are likely related to inaccuracies in the generic controller simulated. Despite controller differences, FAST.Farm predicts the same overall relative rotor power trends for all waked turbines at all wind speeds.

17 WIND ENERGY↗
DOE OSTI2021

Convection in Scaled Turbine Internal Cooling Passages With Additive Manufacturing Roughness

Abstract Additive manufacturing processes, such as direct metal laser sintering (DMLS), enable the creation of novel turbine cooling internal passages and systems. However, the DMLS method produces a significant and unique surface roughness. Previous work in scaled passages analyzed pressure losses and friction factors associated with the rough surfaces, as well as investigated the velocity profiles and turbulent flow characteristics within the passage. In this study, the heat transfer characteristics of scaled additively manufactured surfaces were measured using infrared (IR) thermography. Roughness panels were CNC machined from plates of aluminum 6061 to create near isothermal roughness elements when heated. Fluid resistance differences between the aluminum roughness panels and roughness panels constructed from ABS plastic using the same roughness patterns from McClain et al. (2020, “Flow in a Simulated Turbine Blade Cooling Channel With Spatially Varying Roughness Caused by Additive Manufacturing Orientation,” ASME Turbo Expo 2020, Turbomachinery Technical Conference and Exposition, Virtual Conference, Sept. 21–25, GT2020-16069) were investigated. Finally, the overall thermal performance enhancements and friction losses were assessed through the calculation of surface averaged “global thermal performance” ratios. The global thermal performance characterizations indicate results in-line with those found for traditional commercial roughness and slightly below traditional internal passage convection enhancement methods such as swirl chambers, dimples, and ribs. The passages investigated in this study do not include compressibility effects or the long-wavelength artifacts and channel geometric deviations observed by Wildgoose et al. (2020, “Impact of Additive Manufacturing on Internal Cooling Channels with Varying Diameters and Build Directions,” ASME Turbo Expo 2020, Turbomachinery Technical Conference and Exposition, Virtual Conference, Sept. 21–25, GT2020-15049). However, the results of this study indicate that, based on the roughness augmentation alone, artificial convective cooling enhancers such as turbulators or dimples may still be required for additively manufactured turbine component cooling.

Engineering↗
DOE OSTI2020

Validation of blade-resolved computational fluid dynamics for a MW-scale turbine rotor in atmospheric flow

In this study, simulation results of two different computational fluid dynamics codes, Nalu-Wind and EllipSys3D, are presented for a wind turbine rotor in complex yawed and sheared inflow. The results are compared to measurements from the DanAero experiments, to validate computed pressures and azimuthal trends. Despite different code methodologies and grid setups, the codes agree well in computed pressures and integrated forces along the blade for all blade azimuthal positions, however with some discrepancy in the very yawed case. Additionally, both codes capture well the azimuthal trends and force levels seen in measurements. Investigation into discrepancies shows that expanding grids before the rotor, lead to smearing of the wind profiles, which is likely the main cause of the differences in the results between the codes. Additionally, omission of the ground constraint cause discrepancies in relative velocity seen by the passing blade, due to an over speeding beneath the rotor.

17 WIND ENERGY↗
DOE OSTI2021

Experimental Investigation of Innovative Cooling Schemes on an Additively Manufactured Engine Scale Turbine Nozzle Guide Vane

This study includes the design, validation, and fabrication via direct metal laser sintering (DMLS) of a gas turbine nozzle guide vanes (NGV) that incorporates three innovative cooling schemes specifically enabled by additive manufacturing. The novel NGV design is the culmination of an extensive research and development effort over a period of 4 years that included low- and high-speed cascade testing coupled with unsteady computational fluid dynamics for numerous candidate innovative cooling architectures. The final vane design (SJ-vane) consists of sweeping jet (SJ) film cooling holes on the suction surface (SS), sweeping jet impingement holes at the leading edge and double-wall partial length triangular pin-fin with impinging jet at the trailing edge. For comparison purposes, a second DMLS enabled vane (777-vane) was designed and fabricated with prototypical cooling circuits to serve as a baseline. This vane consists of a shaped film cooling holes on the suction surface, circular impingement holes at the leading edge, and full-length cylindrical pin-fins at the trailing edge. Experiments with the two DMLS enabled vanes were performed at the Ohio State University Turbine Reacting Flow Rig (TuRFR) at engine-relevant temperature (1375 K) and Mach number conditions. Infrared (IR) thermography was utilized to measure the wall temperature of the pressure and suction surface at several coolant mass flowrates to estimate the overall cooling effectiveness (ϕ). Results showed improved cooling performance for the advanced cooling schemes (sweeping jet film cooling, impingement cooling, and triangular pin-fin cooling) compared with the baseline cooling schemes.

Engineering↗
DOE OSTI2020

A gravo-aeroelastically scaled wind turbine rotor at field-prototype scale with strict structural requirements

A new sub-scale field-prototype design solution is developed to realize the dynamics, structural response, and distributed loads (gravitational, aerodynamic, centrifugal) that are characteristic of a full-scale large, modern wind turbine rotor. Prior work in sub-scale wind turbine testing has focused on matching aerodynamic/aero-elastic characteristics of full-scale rotors at wind tunnel scale. However, large-scale rotor designs must expand beyond this limited set of scaling parameters for cost-effective prototyping and meet strict requirements for structural safety for field testing. Here, the challenge lies in producing a structural design meeting two competing objectives: novel scaling objectives that prescribe the sub-scale blade to have low mass and stiffness; and traditional structural safety objectives that drive the design to have higher stiffness and mass. A 20% gravo-aeroelastically scaled wind turbine blade is developed successfully that satisfies these competing objectives. First, it achieved close agreement for non-dimensional tip deflection and flap-wise blade frequency (both within 2.1%) with a blade mass distribution constrained to produce target gravitational and centrifugal loads. Second, the entire blade structure was optimized to ensure a safe, manufacturable solution meeting strict strength requirements for a testing site that can experience up to 45 m/s wind gusts. The prototype-scale blade was fabricated and successfully proof-load tested.

17 WIND ENERGY↗
DOE OSTI2021

Considerations for testing full-scale wind turbine nacelles with hardware-in-the-loop

In this paper, pole placement control techniques are utilized to compensate for variations in the torsional dynamics resulting from the different boundary conditions experienced by a wind turbine nacelle when mounted on a test bench. Simulation case studies are used to understand the baseline torsional characteristics of the nacelle coupled to the test bench versus that coupled to the rotor. It was found that the frequency shifts by up to 200% and 400% for the first and second torsional modes, respectively. The feasibility of utilizing pole placement technique to match the torsional characteristics of the turbine on the test bench is investigated using PI and PID controllers. Here, the performance of the tuned controller is then verified under two test scenarios: Low Voltage Ride Through (LVRT), and a highly dynamic turbulent wind input. It is demonstrated that tuning the test bench speed controller can effectively shift the poles of the closed-loop system to match the desired first and second modes of the full turbine and replicate transient field events on the test bench.

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

Loads Response That is Due to Wake Steering on a Pair of Utility-Scale Wind Turbines

The goal of this report is to present the resulting turbine loads of a full-scale wind turbine wake steering field campaign. In this experiment, wake steering controls were applied to an upwind turbine (T2) and the downwind turbine (T3) was instrumented to measure mechanical loads. The test subjects (T2 & T3) were GE 1.5SLE CWE turbines located on a wind farm with a prevailing wind direction coming from the northwest. The data collection strategy involved toggling the wake steering controls of T2 between on and off. This resulted in two databases (baseline and wake steered) with similar turbulence intensities. Valid data was extracted and processed. The analysis involved scaling data to engineering units, applying coordinate transformations where applicable, calculating 10-minutes statistics, and calculating damage equivalent loads (DELs) to assess fatigue. Figures are shown as statistics and DELs binned by wind speed with supplemental scatter plots provided in the appendices. Results between the baseline and wake steered databases were compared. Overall, the binned statistics showed minimal differences in loading between the two cases. However, the DELs of the wake steered case were observed to be consistently smaller than the baseline for most of the turbine components. A potential for future work was recognized based on the findings of this report. Some areas of further study include an analysis for more granular loads sensitivity to different yaw offset angles and rotor wake overlap, an in-depth comparison of loads between the upwind and downwind turbines, and further fatigue analysis to quantify differences observed in this experiment.

17 WIND ENERGY↗
DOE OSTI2022

Toward control co-design of utility-scale wind turbines: Collective vs. individual blade pitch control

A large-eddy simulation framework has been coupled with controller modules to systematically investigate the impacts of collective (CPC) and individual (IPC) pitch control strategies on utility-scale wind turbine energy production and fatigue loads. Wind turbine components were parameterized using an actuator surface model to simulate the rotor blades and the turbine nacelle. The baseline CPC and IPC algorithms, consisting of single-input single-output proportional–integral controllers and two integral controllers, respectively, were incorporated into the numerical framework. A series of simulations were carried out to investigate the relative performance of the two controllers under various turbulent inflow conditions, spanning hub-height velocities of 7 to 14 m/s. The numerical simulation results of this study showed that, in comparison to the CPC, the IPC controller could successfully reduce the damage equivalent loads of utility-scale turbines at regions 2 and 3 of turbine operation by about 3% and 40%, respectively, without any penalty on the power production of the turbine. It was also shown that, despite its minor impact on the turbulence kinetic energy of the wake, the IPC controller did not influence the recovery of the turbine wake.

17 WIND ENERGY↗
DOE OSTI2021

Mechanisms of Dynamic Near-Wake Modulation of a Utility-Scale Wind Turbine

The current study uses large eddy simulations to investigate the transient response of a utility-scale wind turbine wake to dynamic changes in atmospheric and operational conditions, as observed in previous field-scale measurements. Most wind turbine wake investigations assume quasi-steady conditions, but real wind turbines operate in a highly stochastic atmosphere, and their operation (e.g. blade pitch, yaw angle) changes constantly in response. Furthermore, dynamic control strategies have been recently proposed to optimize wind farm power generation and longevity. Therefore, improved understanding of dynamic wake behaviours is essential. First, changes in blade pitch are investigated and the wake expansion response is found to display hysteresis as a result of flow inertia. The time scales of the wake response to different pitch rates are quantified. Next, changes in wind direction with different time scales are explored. Under short time scales, the wake deflection is in the opposite direction of that observed under quasi-steady conditions. Finally, yaw changes are implemented at different rates, and the maximum inverse wake deflection and time scale are quantified, showing a clear dependence on yaw rate. To gain further physical understanding of the mechanism behind the inverse wake deflection, the streamwise vorticity in different parts of the wake is quantified. The results of this study provide guidance for the design of advanced wake flow control algorithms. The lag in wake response observed for both blade pitch and yaw changes shows that proposed dynamic control strategies must implement turbine operational changes with a time scale of the order of the rotor time scale or slower.

flow-structure interactions↗
DOE OSTI2020

Wake Statistics of Different-Scale Wind Turbines under Turbulent Boundary Layer Inflow

Subscale wind turbines can be installed in the field for the development of wind technologies, for which the blade aerodynamics can be designed in a way similar to that of a full-scale wind turbine. However, it is not clear whether the wake of a subscale turbine, which is located closer to the ground and faces different incoming turbulence, is also similar to that of a full-scale wind turbine. In this work we investigate the wakes from a full-scale wind turbine of rotor diameter 80 m and a subscale wind turbine of rotor diameter of 27 m using large-eddy simulation with the turbine blades and nacelle modeled using actuator surface models. The blade aerodynamics of the two turbines are the same. In the simulations, the two turbines also face the same turbulent boundary inflows. The computed results show differences between the two turbines for both velocity deficits and turbine-added turbulence kinetic energy. Such differences are further analyzed by examining the mean kinetic energy equation.

17 WIND ENERGY↗
DOE OSTI2020

How wind speed shear and directional veer affect the power production of a megawatt-scale operational wind turbine

Most megawatt-scale wind turbines align themselves into the wind as defined by the wind speed at or near the center of the rotor (hub height). However, both wind speed and wind direction can change with height across the area swept by the turbine blades. A turbine aligned to hub-height winds might experience suboptimal or superoptimal power production, depending on the changes in the vertical profile of wind, also known as shear. Using observed winds and power production over 6 months at a site in the high plains of North America, we quantify the sensitivity of a wind turbine's power production to wind speed shear and directional veer as well as atmospheric stability. We measure shear using metrics such as α (the log-law wind shear exponent), β bulk (a measure of bulk rotor-disk-layer veer), β total (a measure of total rotor-disk-layer veer), and rotor-equivalent wind speed (REWS; a measure of actual momentum encountered by the turbine by accounting for shear). We also consider the REWS with the inclusion of directional veer, REWS θ , although statistically significant differences in power production do not occur between REWS and REWS θ at our site. When REWS differs from the hub-height wind speed (as measured by either the lidar or a transfer function-corrected nacelle anemometer), the turbine power generation also differs from the mean power curve in a statistically significant way. This change in power can be more than 70 kW or up to 5 % of the rated power for a single 1.5 MW utility-scale turbine. Over a theoretical 100-turbine wind farm, these changes could lead to instantaneous power prediction gains or losses equivalent to the addition or loss of multiple utility-scale turbines. At this site, REWS is the most useful metric for segregating the turbine's power curve into high and low cases of power production when compared to the other shear or stability metrics. Therefore, REWS enables improved forecasts of power production.

17 WIND ENERGY↗
DOE OSTI2022

Evaluation of dynamic testing of full-scale wind turbine drivetrains with hardware-in-the-loop

Dynamometer testing of full-scale wind turbine drivetrains involves subjecting integrated components to extreme static loads, fatigue loads, or dynamic loads to replicate field conditions. This paper provides a detailed evaluation of the uncertainty and errors in applied loads and measured responses, and their magnitude relative to established repeatability bounds for a drivetrain subjected to static and dynamic loads on the 7.5 MW test bench at the Clemson University Wind Turbine Drivetrain Testing Facility. An ideal drivetrain simulation model is utilized to isolate the influence of load tracking errors on test article responses. It is shown that the test article response variations are mainly driven by run out and clearances inherent to the drivetrain. For the dynamic profiles, the load tracking errors are within acceptable limits. Furthermore, a frequency analysis is used to show that the test bench controller tracking performance is acceptable for profiles with frequency content up to 1.5 Hz.

17 WIND ENERGY↗