Approaches for Predicting Wind Turbine Hub-Height Turbulence Metrics

Hannah Livingston, Nicola Bodini, Julie Lundquist

Research output: Contribution to journalArticle


Hub-height turbulence is essential for a variety of wind energy applications, ranging from wind plant siting to wind turbine control strategies. Because deploying hub-height meteorological towers can be a challenge, alternative ways to estimate hub-height turbulence are desired. In this paper, we assess to what degree hub-height turbulence can be estimated via other hub-height variables or ground-level atmospheric measurements in complex terrain, using observations from three meteorological towers at the Perdigão and WFIP2 field campaigns. We find a large variability across the three considered towers when trying to model hub-height turbulence intensity (TI) and turbulence kinetic energy (TKE) from hub-height or near-surface measurements of either wind speed, TI, or TKE. Moreover, we find that based on the characteristics of the specific site, atmospheric stability and upwind fetch either determine a significant variability in hub-height turbulence or are not a main driver of the variability in hub-height TI and TKE. Our results highlight how hub-height turbulence is simultaneously sensitive to numerous different factors, so that no simple and universal relationship can be determined to vertically extrapolate turbulence from near-surface measurements, or model it from other hub-height variables when considering univariate relationships. We suggest that a multivariate approach should instead be considered, possibly leveraging the capabilities of machine learning nonlinear algorithms.
Original languageAmerican English
Number of pages30
JournalWind Energy Science Discussions
StatePublished - 2021

NREL Publication Number

  • NREL/JA-5000-80288


  • complex terrain
  • extrapolation
  • turbulence
  • turbulence intensity


Dive into the research topics of 'Approaches for Predicting Wind Turbine Hub-Height Turbulence Metrics'. Together they form a unique fingerprint.

Cite this