Optimization Under Uncertainty for Wake Steering Strategies

Julian Quick, Ryan King, Paul Fleming, Andrew Ning, Katherine Dykes

Research output: NRELPresentation


Offsetting turbines' yaw orientations from incoming wind is a powerful tool that may be leveraged to reduce undesirable wake effects on downstream turbines. First, we examine a simple two-turbine case to gain intuition as to how inflow direction uncertainty affects the optimal solution. The turbines are modeled with unidirectional inflow such that one turbine directly wakes the other, using ten rotor diameter spacing. We perform optimization under uncertainty (OUU) via a parameter sweep of the front turbine. The OUU solution generally prefers less steering. We then do this optimization for a 60-turbine wind farm with unidirectional inflow, varying the degree of inflow uncertainty and approaching this OUU problem by nesting a polynomial chaos expansion uncertainty quantification routine within an outer optimization. We examined how different levels of uncertainty in the inflow direction effect the ratio of the expected values of deterministic and OUU solutions for steering strategies in the large wind farm, assuming the directional uncertainty used to reach said OUU solution (this ratio is defined as the value of the stochastic solution or VSS).
Original languageAmerican English
Number of pages23
StatePublished - 2017

Publication series

NamePresented at the Wind Energy Science Conference (WESC) 2017, 26-29 June 2017, Lyngby, Denmark

NREL Publication Number

  • NREL/PR-5000-68865


  • optimization
  • optimization under uncertainty
  • systems engineering
  • wake steering
  • wind energy


Dive into the research topics of 'Optimization Under Uncertainty for Wake Steering Strategies'. Together they form a unique fingerprint.

Cite this