Effect of tip spacing, thrust coefficient and turbine spacing in multi-rotor wind turbines and farms

Large eddy simulations (LESs) are performed to study the wakes of a multi-rotor wind turbine configuration comprising four identical rotors mounted on a single tower. The multi-rotor turbine wakes are compared to the wake of a conventional turbine comprising a single rotor per tower with the same frontal area, hub height and thrust coefficient. The multi-rotor turbine wakes are found to recover faster, while the turbulence intensity in the wake is smaller, compared to the wake of the conventional turbine. The differences with the wake of a conventional turbine increase as the spacing between the tips of the rotors in the multi-rotor configuration increases. The differences are also sensitive to the thrust coefficients used for all rotors, with more pronounced differences for larger thrust coefficients. The interaction between multiple multi-rotor turbines is contrasted with that between multiple single-rotor turbines by considering wind farms with five turbine units aligned perfectly with each other and with the wind direction. Similar to the isolated turbine results, multi-rotor wind farms show smaller wake losses and smaller turbulence intensity compared to wind farms comprised of conventional single-rotor turbines. The benefits of multi-rotor wind farms over single-rotor wind farms increase with increasing tip spacing, irrespective of the axial spacing and thrust coefficient. The mean velocity profiles and relative powers of turbines obtained from the LES results are predicted reasonably accurately by an analytical model assuming Gaussian radial profiles of the velocity deficits and a hybrid linear-quadratic model for the merging of wakes. These results show that a larger power density can be achieved without significantly increased fatigue loads by using multi-rotor turbines instead of conventional, single-rotor turbines

Optimal closed-loop wake steering – Part 2: Diurnal cycle atmospheric boundary layer conditions

Abstract. The magnitude of wake interactions between individual wind turbines depends on the atmospheric stability. We investigate strategies for wake loss mitigation through the use of closed-loop wake steering using large eddy simulations of the diurnal cycle, in which variations in the surface heat flux in time modify the atmospheric stability, wind speed and direction, shear, turbulence, and other atmospheric boundary layer (ABL) flow features. The closed-loop wake steering control methodology developed in Part 1 (Howland et al., 2020c, https://doi.org/10.5194/wes-5-1315-2020) is implemented in an example eight turbine wind farm in large eddy simulations of the diurnal cycle. The optimal yaw misalignment set points depend on the wind direction, which varies in time during the diurnal cycle. To improve the application of wake steering control in transient ABL conditions with an evolving mean flow state, we develop a regression-based wind direction forecast method. We compare the closed-loop wake steering control methodology to baseline yaw-aligned control and open-loop lookup table control for various selections of the yaw misalignment set-point update frequency, which dictates the balance between wind direction tracking and yaw activity. In our diurnal cycle simulations of a representative wind farm geometry, closed-loop wake steering with set-point optimization under uncertainty results in higher collective energy production than both baseline yaw-aligned control and open-loop lookup table control. The increase in energy production for the simulated wind farm design for closed- and open-loop wake steering control, compared to baseline yaw-aligned control, is 4.0 %–4.1 % and 3.4 %–3.8 %, respectively, with the range indicating variations in the energy increase results depending on the set-point update frequency. The primary energy increases through wake steering occur during stable ABL conditions in our present diurnal cycle simulations. Open-loop lookup table control decreases energy production in the example wind farm in the convective ABL conditions simulated, compared to baseline yaw-aligned control, while closed-loop control increases energy production in the convective conditions simulated. </jats:p