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Modal dynamics of wind turbine wake meandering from lidar observations

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  • Hamilton, Nicholas
  • Doubrawa, Paula
  • Moriarty, Patrick
  • Letizia, Stefano
  • Thedin, Regis

Abstract

Horizontal scans from nacelle-mounted lidars provide time series measurements of wind turbine wakes across diverse atmospheric conditions, enabling analysis of coherent turbulent structures that influence wake meandering through proper orthogonal decomposition (POD). While low-order modes capture the most energetic turbulent structures, our analysis reveals that they do not necessarily dominate wake meandering dynamics. We evaluate more than 16,000 combinatorial reconstructions of the flow field for each inflow case, demonstrating that mode relevance depends on mode symmetry, turbulent kinetic energy content, and inflow characteristics. Cases with low turbulence intensity and large integral timescales show stronger correlations between POD modes and wake meandering, whereas higher turbulence conditions (turbulence intensity > 7%) are less effectively described by reduced-order models. However, the qualitative similarity of POD modes across varied atmospheric conditions suggests the potential existence of a semi-universal basis for representing wind turbine wakes, with implications for improving engineering wake models.

Suggested Citation

  • Hamilton, Nicholas & Doubrawa, Paula & Moriarty, Patrick & Letizia, Stefano & Thedin, Regis, 2025. "Modal dynamics of wind turbine wake meandering from lidar observations," Renewable Energy, Elsevier, vol. 254(C).
    • Handle: RePEc:eee:renene:v:254:y:2025:i:c:s0960148125012170
    DOI: 10.1016/j.renene.2025.123555
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    References listed on IDEAS

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    1. Sadek, Zein & Scott, Ryan & Hamilton, Nicholas & Cal, Raúl Bayoán, 2023. "A three-dimensional, analytical wind turbine wake model: Flow acceleration, empirical correlations, and continuity," Renewable Energy, Elsevier, vol. 209(C), pages 298-309.
    2. Mathieu Pichault & Claire Vincent & Grant Skidmore & Jason Monty, 2021. "Short-Term Wind Power Forecasting at the Wind Farm Scale Using Long-Range Doppler LiDAR," Energies, MDPI, vol. 14(9), pages 1-21, May.
    3. Keane, Aidan, 2021. "Advancement of an analytical double-Gaussian full wind turbine wake model," Renewable Energy, Elsevier, vol. 171(C), pages 687-708.
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