Power Production and Blade Fatigue of a Wind Turbine Array Subjected to Active Yaw Control

Mou Lin and Fernando Porté-Agel ()
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Mou Lin: Wind Engineering and Renewable Energy Laboratory (WiRE), École Polytechnique Fédérale de Lausanne (EPFL), EPFL-ENAC-IIE-WIRE, 1015 Lausanne, Switzerland
Fernando Porté-Agel: Wind Engineering and Renewable Energy Laboratory (WiRE), École Polytechnique Fédérale de Lausanne (EPFL), EPFL-ENAC-IIE-WIRE, 1015 Lausanne, Switzerland

Energies, 2023, vol. 16, issue 6, 1-17

Abstract: This study investigated the power production and blade fatigue of a three-turbine array subjected to active yaw control (AYC) in full-wake and partial-wake configurations. A framework of a two-way coupled large eddy simulation (LES) and an aeroelastic blade simulation was applied to simulate the atmospheric boundary layer (ABL) flow through the turbines and the structural responses of the blades. The mean power outputs and blade fatigue loads were extracted from the simulation results. By exploring the feasible AYC decision space, we found that in the full-wake configuration, the local power-optimal AYC strategy with positive yaw angles endures less flapwise blade fatigue and more edgewise blade fatigue than the global power-optimal strategy. In the partial-wake configuration, applying positive AYC in certain inflow wind directions achieves higher optimal power gains than that in the full-wake scenario and reduces blade fatigue from the non-yawed benchmark. Using the blade element momentum (BEM) theory, we reveal that the aforementioned differences in flapwise blade fatigue are due to the differences in the azimuthal distributions of the local relative velocity on blade sections, resulting from the vertical wind shear and blade rotation. Furthermore, the difference in the blade force between the positively and negatively yawed front-row turbine induces different wake velocities and turbulence distributions, causing different fatigue loads on the downwind turbine exposed to the wake.

Keywords: wind power; wind turbine fatigue; active yaw control (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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