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.