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Dynamic-mode-decomposition of the wake of the NREL-5MW wind turbine impinged by a laminar inflow

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  • De Cillis, Giovanni
  • Semeraro, Onofrio
  • Leonardi, Stefano
  • De Palma, Pietro
  • Cherubini, Stefania

Abstract

Dynamic mode decomposition (DMD) has been applied to the wake of the NREL-5MW wind turbine invested by a uniform inflow, to identify the most dynamically relevant coherent structures characterizing this flow. The decomposition has been applied on a snapshot dataset obtained by Large-Eddy Simulation of the flow impinging on the wind turbine, whose tower and nacelle are modeled by the immersed boundary method, whereas rotor blades are modeled using the actuator line method. The Sparsity-Promoting DMD algorithm allows one to select a limited number of dynamic modes optimally reconstructing the snapshot sequence. Among the largest-amplitude selected modes, we found the tip vortices, oscillating at an angular frequency equal to three times the rotational frequency of the turbine. Interestingly, the remaining selected modes are characterized by low frequencies and large-scale spatial structures, reaching the frequency range of the wake meandering. This small set of dynamic modes is highly relevant for the formulation of accurate reduced-order models, which would eventually lead to the design of optimized wind farms layout and control to increase the energy density produced.

Suggested Citation

  • De Cillis, Giovanni & Semeraro, Onofrio & Leonardi, Stefano & De Palma, Pietro & Cherubini, Stefania, 2022. "Dynamic-mode-decomposition of the wake of the NREL-5MW wind turbine impinged by a laminar inflow," Renewable Energy, Elsevier, vol. 199(C), pages 1-10.
    • Handle: RePEc:eee:renene:v:199:y:2022:i:c:p:1-10
    DOI: 10.1016/j.renene.2022.08.113
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    References listed on IDEAS

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    1. De Cillis, Giovanni & Cherubini, Stefania & Semeraro, Onofrio & Leonardi, Stefano & De Palma, Pietro, 2022. "Stability and optimal forcing analysis of a wind turbine wake: Comparison with POD," Renewable Energy, Elsevier, vol. 181(C), pages 765-785.
    2. Liu, Ming & Tan, Lei & Cao, Shuliang, 2019. "Dynamic mode decomposition of gas-liquid flow in a rotodynamic multiphase pump," Renewable Energy, Elsevier, vol. 139(C), pages 1159-1175.
    3. Han, Yadong & Tan, Lei, 2020. "Dynamic mode decomposition and reconstruction of tip leakage vortex in a mixed flow pump as turbine at pump mode," Renewable Energy, Elsevier, vol. 155(C), pages 725-734.
    4. Liu, Ming & Tan, Lei & Cao, Shuliang, 2020. "Method of dynamic mode decomposition and reconstruction with application to a three-stage multiphase pump," Energy, Elsevier, vol. 208(C).
    5. Soledad Le Clainche & Luis S. Lorente & José M. Vega, 2018. "Wind Predictions Upstream Wind Turbines from a LiDAR Database," Energies, MDPI, vol. 11(3), pages 1-15, March.
    6. Ryan Wiser & Joseph Rand & Joachim Seel & Philipp Beiter & Erin Baker & Eric Lantz & Patrick Gilman, 2021. "Expert elicitation survey predicts 37% to 49% declines in wind energy costs by 2050," Nature Energy, Nature, vol. 6(5), pages 555-565, May.
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