• Energy Research

The actuator line method is a widely used technique to model wind turbines in computational fluid dynamics, as it significantly reduces the required computational expense in comparison to simulations using geometrically resolved blades. Actuator line coupled to an aeroelastic solver enables not only the study of detailed wake dynamics but also aeroelastic loads, flexible blade deformation and how this interacts with the flow. Validating aeroelastic actuator line predictions of blade loading, deflection and turbine wakes in complex inflow scenarios is particularly relevant for modern turbine designs and wind farm studies involving realistic inflows, wind shear or yaw misalignment. This work first implements a vortex-based smearing correction in an aeroelastic coupled actuator line, and performs a grid resolution and smearing parameter study which demonstrates significant improvement in the blade loading and in the numerical dependencies of predicted thrust and power output. A validation is then performed using a 2.3 MW turbine with R = 40 m radius, comparing against blade resolved fluid-structure interaction simulations and full-scale measurement data, in both laminar and turbulent inflows including both high shear and high yaw misalignment. For an axisymmetric laminar inflow case, the agreement between blade resolved and actuator line simulations is excellent, with prediction of integrated quantities within 0.2%. In more complex flow cases, good agreement is seen in overall trends but the actuator line predicts lower blade loading and flapwise deflection, leading to underpredictions of thrust by between 5.3% and 8.4%. The discrepancies seen can be attributed to differences in wake flow, induction, the reliance of the actuator line on the provided airfoil data and the force application into the computational domain. Comparing the wake between coupled actuator line and blade resolved simulations for turbulent flow cases also shows good agreement in wake deficit and redirection, even under high yaw conditions. Overall, this work validates the implementation of the vortex-based smearing correction and demonstrates the ability of the actuator line to closely match blade loading and deflection predictions of blade resolved simulations in complex flows, at a significantly lower computational cost.

Abstract. In the present work, a consistent method for calculating the lift and drag forces from the 2-D airfoil data for the dihedral or coned horizontal-axis wind turbines when using generalized lifting-line methods is described. The generalized lifting-line methods refer to the models that discretize the blade radially into sections and use 2-D airfoil data, for example, lifting-line (LL), actuator line (AL), blade element momentum (BEM) and blade element vortex cylinder (BEVC) methods. A consistent interpretation of classic unsteady 2-D thin airfoil theory results reveals that it is necessary to use both the relative flow information at one point on the chord and the chordwise gradient of the flow direction to correctly determine the 2-D aerodynamic force and moment. Equivalently, the magnitude of the force should be determined by the flow at the three-quarter-chord point, while the force direction should be determined by the flow at the quarter-chord point. However, this aspect is generally overlooked, and most implementations in generalized lifting-line methods use only the flow information at one calculation point per section for simplicity. This simplification will not change the performance prediction of planar rotors but will cause an error when applied to non-planar rotors. In this work this effect is investigated using the special case, where the wind turbine blade has only out-of-plane shapes (blade dihedral) and no in-plane shapes (blade sweep), operating under steady-state conditions with uniform inflow applied perpendicular to the rotor plane. The impact of the effect is investigated by comparing the predictions of the steady-state performance of non-planar rotors from the consistent approach of the LL method with the simplified one-point approaches. The results are verified using blade-geometry-resolving Reynolds-averaged Navier–Stokes (RANS) simulations. The numerical investigations confirmed that the full method complying with the thin airfoil theory is necessary to correctly determine the magnitude and direction of the sectional aerodynamic forces for non-planar rotors. The aerodynamic loads of upwind- and downwind-coned blades that are calculated using the LL method, the BEM method, the BEVC method and the AL method are compared for the simplified and the full method. Results using the full method, including different specific implementation schemes, are shown to agree significantly better with fully resolved RANS than the often used simplified one-point approaches.

AbstractThe present paper introduces a new, physically consistent definition of effective induction that should be used in engineering models for power kite performance that use aerodynamic coefficients for the wing. It is argued that in such cases it is physically inconsistent to use disc-based induction models – like momentum models – and thus a new, physically consistent induction model using vortex theory methodology is derived. Simulation results using the new induction model are compared to the previously often used momentum method and Actuator Line (AL) CFD simulations. The comparison shows that the new vortex based model is in much better agreement with the AL results than the momentum method. The new model is as computationally light as the momentum induction method.

Abstract Energy losses due to wind farm clustering and wind farm interaction are rarely well represented in the wind farm design process because of the lack of fast models that can accurately account for neighboring wind farm wakes. A recently developed solution is the actuator wind farm (AWF) model, which is a Reynolds-averaged Navier-stokes (RANS) based wind farm parametrization that models a wind farm as a distributed thrust force and applies a global wind farm thrust coefficient controller. We propose an improved version of the AWF model, where each turbine employs a local thrust force controller and uses turbine thrust and power coefficients as input to better handle inhomogeneous inflow conditions. The proposed AWF model shows improved performance compared to the original AWF model in terms of predicted wind turbine power of a downstream wind farm that operates in a partial wake of an upstream wind farm, without significantly increasing the computational effort. However, the annual energy production (AEP) wake losses of a large wind farm cluster are nearly unaffected by using local or global control and input because the largest impact is found near the cut-in wind speed, which does not contribute much to the AEP wake losses.

Abstract A new wake surrogate model based on Reynolds-averaged Navier-Stokes (RANS) single rotor simulations is presented. The model relies on a series of three-dimensional pre-calculated deficit and added turbulence intensity flow fields, stored in a look-up table (LUT) as a function of the thrust coefficient and the ambient turbulence intensity. For any combination of these parameters, the flow around a wind turbine can be predicted by linearly interpolating within the look-up table. Furthermore, the resulting three-dimensional flow fields from different turbine sources can be superposed linearly to calculate the total wind farm flow. The model is implemented in PyWake and benchmarked against other, commonly employed engineering wake models, namely the Gaussian-Bastankhah, the N. O. Jensen and the Zong models, where RANS wind farm simulations are used as reference. In both full and partial wake cases, the surrogate model achieves a higher accuracy than any other model. Besides providing an accuracy comparable to a full RANS solution, the model can compute a flow case in the order of 1 s on a single processor. The main disadvantage is that the generation of the look-up table is time consuming, computationally expensive and can be memory demanding (especially if more inputs, such as the yaw misalignment angle, stability, etc. are added). Nevertheless, generating the LUT only has to be done once per wind turbine type.

Abstract. The actuator line (AL) was intended as a lifting line (LL) technique for computational fluid dynamics (CFD) applications. In this paper we prove – theoretically and practically – that smearing the forces of the actuator line in the flow domain forms a viscous core in the bound and shed vorticity of the line. By combining a near-wake representation of the trailed vorticity with a viscous vortex core model, the missing induction from the smeared velocity is recovered. This novel dynamic smearing correction is verified for basic wing test cases and rotor simulations of a multimegawatt turbine. The latter cover the entire operational wind speed range as well as yaw, strong turbulence and pitch step cases. The correction is validated with lifting line simulations with and without viscous core, which are representative of an actuator line without and with smearing correction, respectively. The dynamic smearing correction makes the actuator line effectively act as a lifting line, as it was originally intended.

Abstract. Leading-edge erosion (LEE) can significantly impact the aerodynamic performance of wind turbines and thereby the overall efficiency of a wind farm. Typically, erosion is modeled for individual turbines where aerodynamic effects only impact the energy production through degraded power curves. For wind farms, aerodynamic deficiency has the potential to also alter wake dynamics, which will affect the overall energy production. The objective of this study is to demonstrate this combined effect by coupling LEE damage prediction and aerodynamic loss modeling with steady-state wind farm flow modeling. The modeling workflow is used to simulate the effect of LEE on the Horns Rev 1 wind farm. Based on a 10-year simulation, the aerodynamic effect of LEE was found to be insignificant for the first few years of operation but rapidly increases and reaches a maximum annual energy production (AEP) loss of 2.9 % in the last year for a single turbine. When including the impact of LEE to the wakes behind eroded turbines, the AEP loss is seen to reduce to 2.7 % at the wind farm level, i.e., corresponding to an overestimation of the AEP loss of up to 7 % when only considering a single wind turbine. In addition, it was demonstrated that the modeling framework can be used to prioritize turbines for an optimal repairing strategy.