in Group News, Research News

Jun 23: Paper “Wake Effect Parameter Calibration with Large-Scale Field Operational Data using Stochastic Optimization” published in Applied Energy! Here are some highlights:

  • Engineering wake models have parameters that crucially affect their performance.
  • Wake parameters can be calibrated as constants or functions of other wind variables.
  • Stochastic optimization (SO) provides accurate and reliable wake calibrations.
  • Both point and functional calibration of wake parameters can be done well with SO.
  • A derivative-free trust-region SO method provides robust wake calibration.
  • Efficiently implemented trust-region SO uses adaptive sampling and variance reduction.
  • Stratifying data based on wind characteristics effectively reduces variance during SO.
  • Choosing strata of wind data and dynamically sampling from each expedites calibration.
  • Robust wake calibration helps understanding power deficit patterns in wind farms.
  • Good prediction of power deficit due to wake enables optimal design of new wind farms.