A three-dimensional dynamic mode decomposition analysis of wind farm flow aerodynamics

Xuan Dai, Da Xu, Mengqi Zhang*, Richard J.A.M. Stevens

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

16 Citations (Scopus)
128 Downloads (Pure)

Abstract

High-fidelity large-eddy simulations are suitable to obtain insight into the complex flow dynamics in extended wind farms. In order to better understand these flow dynamics, we use dynamic mode decomposition (DMD) to analyze and reconstruct the flow field in large-scale numerically simulated wind farms by large-eddy simulations (LES). Different wind farm layouts are considered, and we find that a combination of horizontal and vertical staggering leads to improved wind farm performance compared to traditional horizontal staggering. We analyze the wind farm flows using the amplitude selection (AP) and sparsity-promoting (SP method) DMD approach. We find that the AP method tends to select modes with a small length scale and a high frequency, while the SP method selects large coherent structures with low frequency. The latter are somewhat reminiscent of modes obtained using proper orthogonal decomposition (POD). We find that a relatively limited number of SP-DMD modes is sufficient to accurately reconstruct the flow field in the entire wind farm, whereas the AP-DMD method requires more modes to achieve an accurate reconstruction. Thus, the SP-DMD method has a smaller performance loss compared to the AP-DMD method in terms of the reconstruction of the flow field.
Original languageEnglish
Pages (from-to)608-624
Number of pages17
JournalRenewable energy
Volume191
Early online date7 Apr 2022
DOIs
Publication statusPublished - May 2022

Keywords

  • wind turbine
  • wind farm
  • turbulence
  • renewable energy
  • large eddy simulation
  • large eddy simulations
  • wind energy
  • Wind farms
  • Dynamic mode decomposition
  • 22/2 OA procedure

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