  This paper compares two actuator line methodologies for modelling wind
turbines employing high-order h/p solvers and large-eddy simulations. The
methods combine the accuracy of high-order solvers (in this work the maximum
order is 6) with the computational efficiency of actuator lines to capture the
aerodynamic effects of wind turbine blades.
  Comparisons with experiments validate the actuator line methodologies. We
explore the effects of the polynomial order and the smoothing parameter
associated with the Gaussian regularization function, and use them to blend the
actuator line forcing in the high-order computational mesh, to show that both
parameters influence the distribution of forces along the blades and the
turbine wake. The greatest impact is obtained when the polynomial order is
increased, allowing one to better capture the physics without requiring new
meshes.
  When comparing the actuator line methodologies, we show the advantages of
performing weighted sums, over element averages, to compute the blade
velocities and forces in high-order solvers. For low-order simulations (low
polynomial orders), both methods provide similar results, but as the polynomial
order is increased, the weighted sum method shows smoother thrust/torque
distributions and better wake resolution. Furthermore, cell averaging
introduces nonphysical oscillations when increasing the polynomial order beyond
3 (4th order accuracy).
