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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 OSTI2020

Multiscale Framework Simulates Utility-Scale Wind Plant in Its Natural Environment. First-ever simulation could lead to a vital understanding of wind plant performance

Wind plant performance depends on local environmental conditions—and understanding those conditions is crucial to research on wind plant dynamics. Factors such as sloping terrain, surface type and cover, atmospheric heating and cooling, and weather events all play a role in determining the winds that turbines convert into power. However, most models used for wind plant design and operation do not sufficiently account for environmental effects. This can limit our understanding of wind plant dynamics and, thus, our ability to design, site, and operate wind plants for maximum power production and reliability. To meet this challenge, Arthur and other LLNL researchers partnered with scientists at the National Center for Atmospheric Research; the University of California, Berkeley; the University of Colorado, Boulder; and Texas Tech University to develop and demonstrate a novel, mesoscale-tomicroscale wind plant modeling framework.

17 WIND ENERGY↗
NASA NTRS1977

Implementation of wind performance studies for large antenna structures

Structural design procedures are described for a large antenna system to meet performance requirements under gravity and wind loading. A computational method is shown for the evaluation of performance in response to wind loading. Cumulative probability distribution curves for wind loading gain reductions for 100-m-diameter antennas are developed to compare a relatively heavy baseline reflector backup structure with two lighter-weight structures; all have equivalent, acceptable performance for gravity loading.

Levy, R.↗
DOE OSTI2018

Analyzing the Energy Performance, Wind Loading, and Costs of Photovoltaic Slat Modules on Commercial Rooftops

NREL studied a new type of photovoltaic (PV) module configuration wherein multiple narrow, tilted slats are mounted in a single frame. Each slat of the PV slat module contains a single row of cells and is made using ordinary crystalline silicon PV module materials and processes, including a glass front sheet and weatherproof polymer encapsulation. Compared to a conventional ballasted system, a system using slat modules offer higher energy production and lower weight at lower LCOE. The key benefits of slat modules are reduced wind loading, improved capacity factor and reduced installation cost. First, the individual slats allow air to flow through, which reduce wind loading. Using PV performance modeling software, we compared the performance of an optimized installation of slats modules to a typical installation of conventional modules in a ballasted rack mounting system. Based on the results of the performance modeling two different row tilt and spacing were tested in a wind tunnel. Scaled models of the PV Slat modules were wind tunnel tested to quantify the wind loading of a slat module system on a commercial rooftop, comparing the results to conventional ballasted rack mounted PV modules. Some commercial roofs do not have sufficient reserve dead load capacity to accommodate a ballasted system. A reduced ballast system design could make PV system installation on these roofs feasible for the first time without accepting the disadvantages of penetrating mounts. Finally, technoeconomic analysis was conducted to enable an economic comparison between a conventional commercial rooftop system and a reduced-ballast slat module installation.

14 SOLAR ENERGY↗
DOE OSTI2017

Effect of Surface Roughness on Wind Turbine Performance

Wind farm operators observe production deficits as machines age. Quantifying deterioration on individual components is difficult, but one potential explanation is accumulation of blade surface roughness. Historically, wind turbine airfoils were designed for lift to be insensitive to roughness by simulating roughness with trip strips. However, roughness was still shown to negatively affect performance. Furthermore, experiments illustrated distributed roughness is not properly simulated by trip strips. To understand how real-world roughness affects performance, field measurements of turbine-blade roughness were made and simulated on a NACA 63 3 -418 airfoil in a wind tunnel. Insect roughness and paint chips were characterized and recreated as distributed roughness and a forward-facing step. Distributed roughness was tested in three heights and five density configurations. The model chord Reynolds number was varied between 0.8 to 4.8 x 10 6 . Measurements of lift, drag, pitching moment, and boundary-layer transition were completed. Results indicate minimal effect from paint-chip roughness. As distributed roughness height and density increase, lift-curve slope, maximum lift, and lift-to-drag ratio decrease. As Reynolds number increases, bypass transition occurs earlier. The critical roughness Reynolds number varies between 178 to 318, within the historical range. Little sensitivity to pressure gradient is observed. At a chord Reynolds number of 3.2 x 10 6 , the maximum lift-to-drag ratio decreases 40% for 140 m roughness, corresponding to a 2.3% loss in annual energy production. Simulated performance loss compares well to measured performance loss on an in-service wind turbine.

17 WIND ENERGY↗
NASA NTRS1993

Software For Analyzing Performances Of Wind Tunnels

Subsonic Wind Tunnel Performance Analysis computer program developed as aid in design and analysis of subsonic wind tunnels. Brings together and refines previously scattered and oversimplified techniques used for design of, and prediction of losses in, components of subsonic wind tunnels. Implements system of equations for determining total pressure losses and provides general guidelines for design of diffusers, contractions, corners, and inlets and exits of nonreturn tunnels. Written in FORTRAN and BASIC.

Decker, C.↗
DOE OSTI2025

Influence of simple terrain on the spatial variability of a low-level jet and wind farm performance in the AWAKEN field campaign

In wind energy research, scientific challenges are often associated with complex terrain sites, where orography, vegetation, and buildings disrupt flow uniformity. However, even sites characterized as simple terrain can exhibit significant spatial variability in wind speed, particularly during stable boundary layers (SBLs) and low-level jets (LLJs). This study investigates these terrain interactions using both simulations and observations from the American WAKe ExperimeNt (AWAKEN). We employ a multiscale Weather Research and Forecasting (WRF) model simulation, integrating mesoscale forcing in the coarse domains and representing three rows of turbines from the King Plains wind farm as generalized actuator disks (GAD) in the large-eddy simulation (LES) domains. During a nocturnal LLJ event on 3 April 2023, the downstream, wake-affected turbine rows outperformed the upstream, unwaked row by 25 %–51 %. This counterintuitive result arises from terrain-induced streamwise variations in hub-height wind speed of approximately 4 m s −1 over 5 km – equivalent to ∼50 % of the upstream reference speed. This enhancement outweighs the wake-induced reduction in mean wind speed (∼12 %) and global blockage effects reported in the literature (∼1 %–3.4 %). The multiscale simulations capture the intra-farm spatial variability in power performance observed in SCADA data. Terrain-induced vertical displacement of the LLJ, coupled with large wind shear below the jet maximum, drives the substantial streamwise acceleration within the wind farm. These findings underscore the importance of accounting for spatial variability related to terrain, even in simple landscapes, particularly during LLJ conditions. Incorporating such effects into reduced-order modeling frameworks for wind farm design and control could significantly enhance their effectiveness.

17 WIND ENERGY↗
DOE OSTI2025

Large-eddy simulation of an atmospheric bore and associated gravity wave effects on wind farm performance in the southern Great Plains

Gravity waves are a common occurrence in the atmosphere, with a variety of generation mechanisms. Their impact on wind farms has only recently gained attention, with most studies focused on wind farm-induced gravity waves. In this study, the interaction between a wind farm and gravity waves generated by an atmospheric bore event is assessed using multiscale large-eddy simulations. The atmospheric bore is created by a thunderstorm downdraft from a nocturnal mesoscale convective system (MCS). The associated gravity waves impact the wind resource and power production at a nearby wind farm during the American Wake Experiment (AWAKEN) in the US southern Great Plains. A two-domain nested setup (Δx=300 and 20 m) is used in the Weather Research and Forecasting (WRF) model, forced with data from the High-Resolution Rapid Refresh model, to capture both the formation of the bore and its interaction with individual wind turbines. The MCS is resolved on the large outer domain, where the structure of the bore and the associated gravity waves are found to be especially sensitive to parameterized microphysics processes. On the finer inner domain, gravity wave interactions with individual wind turbines are resolved; wake dynamics are captured using a generalized actuator disk parameterization in WRF. The gravity waves are found to have a strong effect on the atmosphere above the wind farm; however, the effect of the waves is more nuanced closer to the surface where there is additional turbulence, both ambient and wake-generated. Notably, the gravity waves modulate the mesoscale environment by weakening and dissipating the preexisting low-level jet, which reduces hub-height wind speed and hence the simulated power output, which is confirmed by the observed supervisory control and data acquisition (SCADA) power data. Additionally, the gravity waves induce local wind direction variations correlated with fluctuations in pressure, which lead to fluctuations in the simulated power output as various turbines within the farm are subjected to waking from nearby turbines.

17 WIND ENERGY↗
NASA NTRS1978

Wind tunnel performance tests of coannular plug nozzles

Wind tunnel performance test results and data analyses are presented for dual-flow plug nozzles applicable to supersonic cruise aircraft during takeoff and low-speed flight operation. Outer exhaust stream pressure ratios from 1.5 to 3.5 were tested; inner exhaust stream conditions were varied from very low, or bleed flow rates, up to a pressure ratio of 3.5. Mach numbers tested ranged from zero to 0.45. Measured thrust coefficients for the eight model configurations, operating at an external Mach number of 0.36 and an outer flow pressure ratio of 2.5, varied from 0.95 to 0.974 for high inner flow rates. At low inner flow, the performance ranged from 0.88 to 0.97 for the same operating conditions. The primary design variables influencing the performance levels were the annular height of the inner and outer nozzle throats (denoted by radius ratio - the ratio of inner-to-outer flowpath diameter at the nozzle throat), the plug geometry, and the inner stream flow rate.

Staid, P. S.↗
NASA NTRS1985

Effect of precipitation on wind turbine performance

The effects of precipitation on wind turbine power output was analyzed. The tests were conducted on the two bladed Mod-0 horizontal axis wind turbine with three different rotor configurations. Experimental data from these tests are presented which clearly indicate that the performance of the Mod-0 wind turbine is affected by rain. Light rainfall degraded performance by as much as 20 percent while heavy rainfall degraded performance by as much as 30 percent. Snow mixed with drizzle degraded performance by as much as 36 percent at low windspeeds. Also presented are the results of an analysis to predict the effect of rain on wind turbine performance. This analysis used a blade element/momentum code with modified airfoil characteristics to account for the effect of rain and predicted a loss in performance of 31 percent in high winds with moderate rainfall rates. These predicted results agreed well with experimental data.

Corrigan, R. D.↗
DOE OSTI2020

An Evaluation of Advanced Tools for Distributed Wind Turbine Performance Estimation

We evaluate various classes of distributed wind turbine performance tools across two sites in the United States. The class of tools ranges from the simple mass conservation model to the coupled Reynolds-averaged Navier-Stokes model, all initiated by the WIND Toolkit data set. The resource estimation at the site is evaluated against measured data at the mast location. Taking a sample 100-kW wind turbine and constant losses, we evaluate Openwind, Continuum, and WindNinja tools and document annual energy production (AEP) and time-series statistics associated with the performance estimation of the wind turbine. Using a methodology that is consistent and unbiased across the three options currently available in the industry, we elaborate results at the two sample locations and discuss the probable sources of discrepancy in the AEP estimates. Two main sources of the discrepancy come from the input WIND Toolkit data and the spatial modeling techniques of the tools to capture atmospheric physics. The discussion includes additional values that these tools may bring into the energy assessment process to enhance the owners' confidence over the distributed wind power systems.

17 WIND ENERGY↗
DOE OSTI2014

Reference Manual for the System Advisor Model's Wind Power Performance Model

This manual describes the National Renewable Energy Laboratory's System Advisor Model (SAM) wind power performance model. The model calculates the hourly electrical output of a single wind turbine or of a wind farm. The wind power performance model requires information about the wind resource, wind turbine specifications, wind farm layout (if applicable), and costs. In SAM, the performance model can be coupled to one of the financial models to calculate economic metrics for residential, commercial, or utility-scale wind projects. This manual describes the algorithms used by the wind power performance model, which is available in the SAM user interface and as part of the SAM Simulation Core (SSC) library, and is intended to supplement the user documentation that comes with the software.

17 WIND ENERGY↗
DOE OSTI2019

An Evaluation of Advanced Tools for Distributed Wind Turbine Performance Estimation: Preprint

We evaluate various classes of distributed wind turbine performance tools across two sites in the USA. The tools class ranges from the simple mass conservation model to coupled Reynolds Averaged Navier-Stokes (RANS) model, all initiated by the WIND Toolkit dataset. The resource estimation at the site is evaluated against measured data at the mast location. Taking a sample 100 kW wind turbine and constant losses, we evaluate Openwind, Continuum, and WindNinja tools and document Annual Energy Production (AEP) and time series statistics associated with the performance estimation of the wind turbine. Using a methodology that is consistent and unbiased across the three advance options currently available in the industry, we elaborate results at the two sample locations and discuss the probable sources of discrepancy in the AEP estimates. The discussion includes additional values these tools may bring into the energy assessment process to enhance the owners' confidence over the distributed wind power systems.

17 WIND ENERGY↗
DOE OSTI2019

Wind Plant Performance Prediction (WP3) Benchmark Introduction

This presentation outlines the results from the Wind Plant Performance Prediction (WP3) Benchmarking group, which is concentrated on predicted versus actual wind plant performance, honing in on the variables that can cause over-estimation of power generation and subsequent 'under performance.'

17 WIND ENERGY↗
NASA NTRS1978

DOE/NASA Mod-0A wind turbine performance

Design and operation of a large wind turbine at Clayton, New Mexico is reported. This is the first of three identical 200 kW wind turbines to be operated on electric utility networks. A comparison between its predicted and measured power versus wind speed performance is presented.

Richards, T. R.↗
DOE OSTI2021

Wind Plant Performance Prediction Benchmark Phase 1 (Technical Report)

Financial risk resulting from the uncertainty associated with developing, owning, and operating wind power plants remains a barrier to reducing the levelized cost of energy (LCOE). On average, modern wind power plants in the U.S. underperform their expected annual energy output by 3.5-4.5% , with many underperforming by over 10%. To compensate for this uncertainty, investors require a larger return on investment (ROI) and apply "knock-down" factors that mask much of the underlying sources of uncertainty. Wind energy projects thus have reduced access to low-cost capital. Furthermore, operating wind plants often take a simple approach to estimating operations & maintenance (O&M) costs (e.g. straight-line estimates based on similar plants), which can eat into profits. To overcome these issues, the wind industry must improve the models they use for estimating wind plant performance and operations. An industry consortium (IC) requested that the National Renewable Energy Laboratory (NREL) lead a Department of Energy (DOE) working group to benchmark the accuracy of wind power plant energy predictions against real operational data. The IC was also motivated by DOE and NREL's potential to characterize systematic energy underperformance, identify sources of uncertainty, and explore root causes. The Wind Plant Performance Prediction (WP3) project was created out of this request, and this report represents the successful completion of Phase 1 of the WP3 project. During the project, wind plant owners provided both pre-construction and operational data to NREL. The pre-construction data was provided to wind resource assessment (WRA) consultants so they could conduct energy yield assessments (EYA). NREL took all of the completed EYAs, along with the operational data, and conducted an operational assessment to benchmark the EYA results against actual operational data. Given the large amounts of sensitive data required for this effort, as well as historical opposition to sharing data within industry, successful completion of Phase 1 represents an unprecedented milestone for industry data sharing. To improve the accuracy and confidence of pre-construction EYAs, wind plant owners and investors need better, more certain, energy yield predictions. The WP3 Benchmark Project is an industry-driven response to this reality. For the first time, industry has taken the important step of working together at scale, sharing valuable operational data with DOE and NREL in order to investigate the sources of bias and uncertainty in these energy estimates. This IC provides wind plant preconstruction and operational data to NREL in an organized and documented fashion and provides guidance and feedback as needed. The IC also provides introspection of the design of experiment, key metrics of success, data challenges, analysis best practices, and quality of results.

17 WIND ENERGY↗