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Title: FY17 Accomplishments - Testing Facilities and Capabilities at SWiFT, SNL

Abstract

The Scaled Wind Farm Technologies (SWiFT) facility operated by Sandia National Laboratories (SNL) has, in support of the Atmosphere to electrons (A2e) research program, acquired measurements of wind turbine wake dynamics under various atmospheric conditions and while interacting with a downstream wind turbine. SNL researchers, in collaboration with National Renewable Energy Laboratory (NREL) researchers, installed a customized LIDAR system created by the Technical University of Denmark (DTU) in one of the SWiFT wind turbines (Figure 1) and operated that turbine with intentional yaw-versus-winddirection misalignment to study the behavior of the turbine wake under numerous combinations of atmospheric conditions and turbine yaw offsets. The DTU-customized LIDAR provided detailed measurements of the wake’s shape and location at many distances downwind of the turbine (Figure 2). These measurements will benefit wind energy researchers looking to understand wind turbine wake behavior and improve modeling and simulation of wake dynamics, including the “wake steering” affect that is observed when turbine yaw offset is controlled. During the test campaign, two SWiFT wind turbines were operated at the same time to observe the influence of the turbines on each other as the wake of the upwind turbine was observed sweeping over and interacting with the downwind turbine.

Authors:
 [1]
  1. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Wind and Water Technologies Office (EE-4W)
OSTI Identifier:
1405268
Report Number(s):
SAND-2017-11401R
657992
DOE Contract Number:
AC04-94AL85000
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
17 WIND ENERGY

Citation Formats

Berg, Jonathan Charles. FY17 Accomplishments - Testing Facilities and Capabilities at SWiFT, SNL. United States: N. p., 2017. Web. doi:10.2172/1405268.
Berg, Jonathan Charles. FY17 Accomplishments - Testing Facilities and Capabilities at SWiFT, SNL. United States. doi:10.2172/1405268.
Berg, Jonathan Charles. Sun . "FY17 Accomplishments - Testing Facilities and Capabilities at SWiFT, SNL". United States. doi:10.2172/1405268. https://www.osti.gov/servlets/purl/1405268.
@article{osti_1405268,
title = {FY17 Accomplishments - Testing Facilities and Capabilities at SWiFT, SNL},
author = {Berg, Jonathan Charles},
abstractNote = {The Scaled Wind Farm Technologies (SWiFT) facility operated by Sandia National Laboratories (SNL) has, in support of the Atmosphere to electrons (A2e) research program, acquired measurements of wind turbine wake dynamics under various atmospheric conditions and while interacting with a downstream wind turbine. SNL researchers, in collaboration with National Renewable Energy Laboratory (NREL) researchers, installed a customized LIDAR system created by the Technical University of Denmark (DTU) in one of the SWiFT wind turbines (Figure 1) and operated that turbine with intentional yaw-versus-winddirection misalignment to study the behavior of the turbine wake under numerous combinations of atmospheric conditions and turbine yaw offsets. The DTU-customized LIDAR provided detailed measurements of the wake’s shape and location at many distances downwind of the turbine (Figure 2). These measurements will benefit wind energy researchers looking to understand wind turbine wake behavior and improve modeling and simulation of wake dynamics, including the “wake steering” affect that is observed when turbine yaw offset is controlled. During the test campaign, two SWiFT wind turbines were operated at the same time to observe the influence of the turbines on each other as the wake of the upwind turbine was observed sweeping over and interacting with the downwind turbine.},
doi = {10.2172/1405268},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Sun Oct 01 00:00:00 EDT 2017},
month = {Sun Oct 01 00:00:00 EDT 2017}
}

Technical Report:

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