Scaled Wind Farm Technology (SWiFT)

Increasing the performance of current wind farms to reduce wind power’s costs

Operations

A significant percentage of wind energy is not effectively harvested in large wind farms because the turbines “shadow” each other and reduce the output of the turbines located in their wake. The wakes also produce increased turbulence and uneven loading on the shadowed turbines, increasing fatigue issues that eventually affect a wind farm’s longevity and reliability. The Scaled Wind Farm Technology (SWiFT) facility is the first public facility to use multiple wind turbines to measure how wind turbine wakes interact with one another in a wind farm.

Contact Us

Tim Crawford
SWiFT Facility Lead
Wind Energy Technologies, Sandia National Laboratories
Mail Stop 1124
PO Box 5800
Albuquerque, NM 87123
office: 505-844-2949
mobile: 505-449-8600

Additional Resources:

Research

The current interest areas for research at SWiFT are:

  • Wake energy loss
  • Wake-induced loads
  • Advanced rotor development
  • Turbine control in wind farms
  • Advanced sensing

View a presentation about the SWiFT facility.

Wind Optimization Projects

The current interest areas for research at SWiFT are:

  • Wake energy loss
  • Wake-induced loads
  • Advanced rotor development
  • Turbine control in wind farms
  • Advanced sensing

View a presentation about the SWiFT facility.

The Department of Energy’s Scaled Wind Farm Technology (SWiFT) facility was commissioned in 2013 in order to provide an experimental site with research-scale wind turbines for studying wind-turbine wakes and turbine–turbine interactions at a realistic scale. The SWiFT site is managed and operated by Sandia National Laboratories for the DOE Wind Program.

As the scale of wind energy installations grows and represents a greater portion of U.S. energy production, it becomes increasingly important to understand the impacts of these complex flow environments on wind turbine operations. The Scaled Wind Farm Technologies (SWiFT) facility was established to experimentally study turbine-turbine wake interactions. Many features of waked operation of a wind turbine, including reduced power and increased loads, are a function of turbine spacing and atmospheric conditions.

An analysis of the atmospheric conditions at the SWiFT site, performed using historical data from Texas Tech University’s 200m meteorological tower, can be used to inform and design experimental campaigns. The analysis provides approximate conclusions about the frequency and magnitude of atmospheric conditions important to wind energy at the SWiFT site and scale. The analysis also enables modelers to simulate the site using probable conditions prior to experimental campaigns based on which conditions are likely to occur.

The analysis summarizes bulk atmospheric conditions–such as variable averages and distributions and determination of the SWiFT turbine IEC design classification. The time dependency of atmospheric conditions at the SWiFT site is also characterized, both seasonally and throughout the day. Correlated atmospheric conditions, such as atmospheric stability and turbulence levels, are also presented from the analyzed data set, which captures the likelihood of being able to operate at combined sets of atmospheric conditions. The final report summarizing the analysis can be downloaded here, SWiFT Site Atmospheric Characterization.

Wakes produced from upstream turbines in wind plants lead to lower power production and increased loads on downstream turbines. The resulting loss of energy capture and increase in maintenance costs represent one of the largest opportunities to reduce cost of energy (COE) at the plant level. Improvements in wind turbine design and plant layout to realize plant-scale COE reductions will require computational simulation and design tools with improved accuracy validated with experimental data.

This project seeks to demonstrate that the Sandia Wake Imaging System (SWIS) is capable of measuring the formation and development of flow structures near the turbine rotor at temporal and spatial scales not accessible by current measurement techniques such as scanning LIDAR or particle image velocimetry (PIV). The technique produces a velocity image of the measurement field by using specialized cameras with a filter and software to measure the Doppler shift of scattered laser light from aerosols tracking the flowfield.

In July of 2015, the SWIS was successfully deployed at the Scaled Wind Farm Technology (SWiFT) facility to demonstrate the tech¬nology in a field application (see image). When deployed as part of future test campaigns, this system will produce a novel experimental data for researchers to better understand fundamental wind-turbine wake phenomena and to validate computational codes and design tools that will be used to improve utility wind plant performance.

SWIS

To establish a baseline with the Texas Tech University (TTU) [Ka-band (link1)] Doppler radar, unique and novel wind farm flow mapping has been performed in either full- or semi-precipitating environments. Preliminary results to date have opened insight to full utility-scale wind-farm performance that have never been seen in any other data set, measured or modeled.

Click to download the FAST model and the associated report.