Offshore Wind Energy - Buoy Lidar Project
A 2014 study estimated that U.S. offshore wind energy could generate enough power for 17 million homes. More than a dozen offshore wind farms are in various stages of development in the United States. The demonstration projects in Virginia and New Jersey receive funding from the U.S. Department of Energy (DOE).Read More
Coastal Wind Profiler
Wind is a variable energy resource. As its proportional contribution to overall electrical power increases, accurate forecasting of wind power production becomes increasingly important to maintain stability in the electrical grid and low power costs. In turn, forecast accuracy depends substantially on data to provide accurate initialization of numerical weather forecast models. The U.S. Department of Energy (DOE), in collaboration with the National Oceanic and Atmospheric Administration (NOAA), recently completed installation of three new wind-profiling radars on the Washington and Oregon coasts to provide data for model initialization.Read More
Improving the Mapping and Prediction of Offshore Wind Resources
With few weather observations over the coastal Atlantic Ocean, atmospheric models are an essential bridge to map offshore wind resources and forecast wind power potential, up to hours or days in advance. Unfortunately, these models have large wind speed uncertainties over the ocean, especially at wind turbine height a few hundred feet above the ocean.Read More
Leading-edge Erosion Study (LEES) Project
Airfoil Performance Degradation due to Roughness and Leading-edge Erosion
Wind farms often underperform predicted power output by 10 to 30 percent relative to manufacturer predictions. A potential aerodynamic explanation is that blade roughness caused by insect impingement and leading-edge erosion decreases lift and drag as opposed to “clean” blades. These effects are difficult to test in the field because aerodynamic performance cannot be measured directly and can be affected by many factors that cannot be controlled in field experiments. This project provides aerodynamic performance data using wind tunnel measurements of representative inboard and outboard blade sections contaminated with various types and levels of roughness and leading-edge erosion. Results include aerodynamic load coefficients and measurements of laminar-to-turbulent transition location as functions of Reynolds number and angle of attack for various roughness configurations.Read More
Lake Michigan Wind Assessment
A study of wind speed and direction over Lake Michigan was conducted to determine if there was sufficient energy potential to justify further work toward wind farm development.Read More
This model performance study features several federally funded U.S. laboratories collaborating on various mesoscale and microscale model simulations and assessments to establish a validated model for the inflow conditions at the Scaled Wind Farm Technology Facility (SWiFT), located at Texas Tech University in Lubbock, Texas. The collected field data observed at SWiFT display ranges of atmospheric behaviors. The project spans March 2015 through September 2018.Read More
Position of Offshore Wind Energy Resources
In response to a request from U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy, NOAA's Office of Oceanic and Atmospheric Research (OAR) and the National Weather Service (NWS) have performed research to provide information about the type and spatial density of observations needed to characterize the wind resource in the offshore environment.Read More
Unsteady Aerodynamics Experiment Phase VI NREL-NASA Ames Wind Tunnel Experiment
The Unsteady Aerodynamics Experiment (UAE) was undertaken to acquire research-grade wind turbine aerodynamics measurements capable of expanding physical comprehension, improving predictive models, and advancing turbine technology and performance. Initiated in 1987 at the National Renewable Energy Laboratory’s (NREL) National Wind Technology Center (NWTC), the UAE evolved through five phases of field experiments during 1987 through 1998.[1-3] Concurrently, analogous wind turbine field experiments aimed at the same objectives were pursued at several laboratories in Europe and Asia.[4,5] Together, these field experiments succeeded in developing procedures and instrumentation for acquiring research-grade measurements in the field test environment and generally confirmed that turbine blades produced flow fields that were highly three-dimensional, strongly separated, and predominantly unsteady.
However, crucial details of the turbine blade flow fields remained obscure, overwhelmed by the temporal and spatial disparities imposed by turbulent atmospheric inflows. To isolate the key blade and rotor fluid mechanics details, atmospheric inflow anomalies needed to be eliminated. Thus, plans were launched simultaneously in the United States and Europe to carry out research-grade turbine aerodynamics experiments in the largest U.S. and EU wind tunnels. Documented and archived in the DAP UAE6 database, the NREL UAE Phase VI experiment was conducted in the National Aeronautics and Space Administration (NASA) 80 ft x 120 ft wind tunnel at the NASA Ames Research Center at Moffett Field, California. The EU Model rotor EXperiment In COntrolled conditions (MEXICO) experiment was carried out in the German-Dutch Wind Tunnels (DNW) Large Low Speed Facility (LLF), located near Marknesse in The Netherlands.
The DAP UAE6 database contains the measurements acquired via experiments in the NASA Ames 80 ft x 120 ft during 2000. The UAE Phase VI wind tunnel experiment objectives were to: 1) acquire research grade aerodynamic and structural measurements 2) on a subscale wind turbine geometrically/dynamically similar to full scale, 3) operating in a controlled, low-turbulence inflow environment.Read More
Wake Steering Experiment
Planned for May through September 2016, Sandia National Laboratories and the National Renewable Energy Laboratory will execute a joint experimental campaign examining wind farm control at the Scaled Wind Farm Technology (SWiFT) facility, hosted at Texas Tech University in Lubbock, Texas. The experimental campaign will be conducted in two phases. In Phase I, an Offset Controller (OC) will be applied to the upwind wind turbine. This controller applies an offset to a nacelle-based wind direction sensor used for aligning the turbine to the wind direction to achieve a prescribed misalignment to the wind. In Phase II, the controller will be replaced by a Wake Steering Controller (WSC) that uses a look-up table based on the FLOw Redirection and Induction in Steady-state (FLORIS) model to find offsets that produce a desired amount of wake steering. The data collected during both phases will be used to perform initial verification and validation studies on controls-oriented models, such as FLORIS, as well as higher-fidelity wind plant analysis models, such as Simulator fOr Wind Farm Applications (SOWFA). Target data include inflow, wake, and turbine performance and loads.Read More
Wind Forecast Improvement Project 1
The National Oceanic and Atmospheric Administration (NOAA) led this observational, data assimilation, and modeling study that was designed to demonstrate improvements in the accuracy of short-term (0-6 hour) wind forecasts for wind energy.Read More
Wind Forecast Improvement Project 2
The Wind Forecast Improvement Project in Complex Terrain, or WFIP2, field campaign officially ended on March 31, 2017. However, some instruments continued to collect data in the field after this date. In general, the data collected after March 31, 2017 have not been quality controlled (QC) and exist on the DAP as z0 data. These data should only be used after discussions with the instrument owners. If any of these data have undergone QC, they will exist as b0 data.
The WFIP2 has maintained two overarching scientific goals:
- To improve the physical understanding of atmospheric processes that directly affect wind energy forecasts in areas of complex terrain.
- To incorporate the new understanding into a foundational weather forecasting model that improves wind energy forecasts.
The Wind Integration National Dataset (WIND) Toolkit
The WIND Toolkit is a combination of three datasets that reflect the ramping characteristics, spatial and temporal correlations, capacity factors of simulated wind plants, and are time synchronized with available load profiles. The datasets include a meteorological dataset based on mesoscale Numerical Weather Prediction model data, a wind power production dataset based on mesoscale model data, and a power and wind speed forecast dataset. These sets were created using the Weather Research and Forecasting Model run on a 2-km grid over 126,000 locations across the contiguous United States at a five-minute resolution with accuracy mimicked by reforecasting the years 2007–2013 using industry-standard techniques. This combination offers vast improvement to existing wind datasets by significantly expanding the geographic area considered, the number of sites included, and the temporal resolution of the data to aid in subhourly modeling of power system operations. Moreover, the WIND Toolkit's creation also followed the latest wind energy research science and current industry standards.Read More
Wind Plant Performance Prediction (WP3) Benchmarking Project
The Wind Plant Performance Prediction (WP3) Benchmark project is a validation exercise for wind farm pre-construction energy assessments. This project represents an unprecedented platform for data sharing and wind industry advancement including preconstruction and operational data from up to 100 or more modern operational wind projects.
- Generate accurate, independent benchmarks of pre-construction energy assessments
- Improve accuracy and reduce uncertainty in pre-construction energy estimates
- Create a platform for sharing data to advance the state-of-the-science for pre-construction energy assessments
Experimental Planetary Boundary Layer Instrumentation Assessment
Multiple remote sensing devices were compared to reference measurements mounted on the National Oceanic and Atmospheric Administration (NOAA) Boulder Atmospheric Observatory (BAO) near Erie, Colorado. XPIA’s primary data collection period was run for a five-week period from March 2–April 6, 2015.Read More