Three-dimensional structure of wind turbine wakes as measured by scanning lidar

Bodini, Nicola; Zardi, Dino; Lundquist, Julie K.

doi:10.5194/amt-10-2881-2017

Title: Three-dimensional structure of wind turbine wakes as measured by scanning lidar

Journal Article · Mon Aug 14 00:00:00 EDT 2017 · Atmospheric Measurement Techniques (Online)

DOI:https://doi.org/10.5194/amt-10-2881-2017· OSTI ID:1374921

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The lower wind speeds and increased turbulence that are characteristic of turbine wakes have considerable consequences on large wind farms: turbines located downwind generate less power and experience increased turbulent loads. The structures of wakes and their downwind impacts are sensitive to wind speed and atmospheric variability. Wake characterization can provide important insights for turbine layout optimization in view of decreasing the cost of wind energy. The CWEX-13 field campaign, which took place between June and September 2013 in a wind farm in Iowa, was designed to explore the interaction of multiple wakes in a range of atmospheric stability conditions. Based on lidar wind measurements, we extend, present, and apply a quantitative algorithm to assess wake parameters such as the velocity deficits, the size of the wake boundaries, and the location of the wake centerlines. We focus on wakes from a row of four turbines at the leading edge of the wind farm to explore variations between wakes from the edge of the row (outer wakes) and those from turbines in the center of the row (inner wakes). Using multiple horizontal scans at different elevations, a three-dimensional structure of wakes from the row of turbines can be created. Wakes erode very quickly during unstable conditions and can in fact be detected primarily in stable conditions in the conditions measured here. During stable conditions, important differences emerge between the wakes of inner turbines and the wakes of outer turbines. Further, the strong wind veer associated with stable conditions results in a stretching of the wake structures, and this stretching manifests differently for inner and outer wakes. As a result, these insights can be incorporated into low-order wake models for wind farm layout optimization or for wind power forecasting.

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Research Organization:: National Renewable Energy Laboratory (NREL), Golden, CO (United States)

Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE)

Grant/Contract Number:: APUP UGA-0-41026-22; AC36-08GO28308

OSTI ID:: 1374921

Alternate ID(s):: OSTI ID: 1379466

Report Number(s):: NREL/JA-5000-70056

Journal Information:: Atmospheric Measurement Techniques (Online), Journal Name: Atmospheric Measurement Techniques (Online) Vol. 10 Journal Issue: 8; ISSN 1867-8548

Publisher:: Copernicus Publications, EGUCopyright Statement

Country of Publication:: Germany

Language:: English

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Cited by: 39 works

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