Multi-Fidelity Active Subspaces for Wind Farm Uncertainty Quantification

Research output: Contribution to conferencePaperpeer-review

2 Scopus Citations


Wind plants operate in stochastic environments characterized by complex turbulent flow dynamics and high-dimensional random variables. A key step in uncertainty quantification studies is sensitivity analysis and dimension reduction that can facilitate the development of surrogate models to be used for forward and inverse propagation or optimization under uncertainty. Prior work has shown active subspaces are an effective tool for identifying important directions in the space of stochastic inputs; however, they have only been applied to single-fidelity wind plant models. In this study, we investigate the efficacy of a multi-fidelity active subspace method for analysing the uncertainty in wind plant power output. The multifidelity active subspace estimator offers the promise of increased accuracy in identifying active subspaces as compared to a single-fidelity estimator for the same computational cost, or a reduction in cost for the same accuracy. This makes the study of uncertainty in larger wind plants and with higher fidelity physics tractable. The multi-fidelity active subspace method is applied to gridded and existing wind plant layouts with single and multiple inflow conditions and its performance for surrogate modeling and uncertainty propagation is compared against a single-fidelity active subspace method. This multi-fidelity approach yields substantial computational speedups of 2× − 3.4× across the test cases along with acceptable accuracy in surrogate modeling and computing statistical moments.

Original languageAmerican English
Number of pages19
StatePublished - 2021
EventAIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2021 - Virtual, Online
Duration: 11 Jan 202115 Jan 2021


ConferenceAIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2021
CityVirtual, Online

Bibliographical note

Publisher Copyright:
© 2021, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

NREL Publication Number

  • NREL/CP-2C00-78323


  • active subspace
  • CFD
  • dimension reduction
  • Monte Carlo
  • multi-fidelity
  • surrogate modeling
  • uncertainty quantification
  • wind


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