skip to main content

DOE PAGESDOE PAGES

Title: Improving Lidar Turbulence Estimates for Wind Energy

Remote sensing devices (e.g., lidars) are quickly becoming a cost-effective and reliable alternative to meteorological towers for wind energy applications. Although lidars can measure mean wind speeds accurately, these devices measure different values of turbulence intensity (TI) than an instrument on a tower. In response to these issues, a lidar TI error reduction model was recently developed for commercially available lidars. The TI error model first applies physics-based corrections to the lidar measurements, then uses machine-learning techniques to further reduce errors in lidar TI estimates. The model was tested at two sites in the Southern Plains where vertically profiling lidars were collocated with meteorological towers. Results indicate that the model works well under stable conditions but cannot fully mitigate the effects of variance contamination under unstable conditions. To understand how variance contamination affects lidar TI estimates, a new set of equations was derived in previous work to characterize the actual variance measured by a lidar. Terms in these equations were quantified using a lidar simulator and modeled wind field, and the new equations were then implemented into the TI error model.
Authors:
 [1] ;  [1] ;  [1] ;  [2]
  1. National Renewable Energy Lab. (NREL), Golden, CO (United States)
  2. Univ. of Oklahoma, Norman, OK (United States). School of Meteorology
Publication Date:
Report Number(s):
NREL/JA-5000-67547
Journal ID: ISSN 1742-6588
Grant/Contract Number:
AC36-08GO28308
Type:
Accepted Manuscript
Journal Name:
Journal of Physics. Conference Series
Additional Journal Information:
Journal Volume: 753; Journal ID: ISSN 1742-6588
Publisher:
IOP Publishing
Research Org:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Wind and Water Technologies Office (EE-4W)
Country of Publication:
United States
Language:
English
Subject:
17 WIND ENERGY; lidar; turbulence; wind energy; L-TERRA; turbulence intensity
OSTI Identifier:
1335579