A major challenge in turbulence-resolving flow simulations is the generation of unsteady and coherent turbulent inflow conditions. Precursor methods have proven to be reliable inflow generators but are limited in applicability and flexibility especially when attempting to couple boundary-layer dynamics with large-scale temporal variations in the direction of the inflow. Here, we propose a methodology that is capable of providing fully developed turbulent inflow for time-varying mean-flow directions. The method is a generalization of a concurrent precursor inflow technique, in which a fully developed boundary-layer simulation that uses periodic boundary conditions is dynamically rotated with the large-scale wind direction that drives the simulation in the domain of interest. The proposed inflow method is applied to large-eddy simulations of boundary-layer flow through the Horns Rev wind farm when subjected to a sinusoidal variation in wind direction at the hourly time scale.

Turbulent inflow precursor method with time-varying direction for large eddy simulations and applications to wind farms

The numerical study of the wake of full-scale slender devices such as aircraft wings and wind turbine blades requires high-fidelity large eddy simulation tools. The broad spectrum of scales involved entails the use of coarse-grain models for the devices. Actuator disk or line methods have been developed for that purpose, and are to date the most employed in that context. These methods transfer the force from the device to the fluid using 3D mollification functions. A novel immersed lifting and dragging line method is here presented, together with its implementation in a hybrid vortex particle-mesh flow solver. The line models the effect of blades or wings on the flow through the generation of vorticity, in a Lagrangian manner. This has several advantages over the treatment inherent to actuator methods: The absence of mollification in the spanwise direction and the relaxation of the classical Courant–Friedrichs–Lewy condition contribute to keeping the accuracy and the efficiency at a high level. The method is thoroughly verified against theory using results on various airfoils and wings. Finally, the efficiency of the approach is illustrated with the simulation of the wake of an elliptical wing. The role of parasitic drag in the development of wake instabilities is pointed out, by comparing configurations with none, moderate and high profile drag. In the last case, the simulation captures the fine scales vortex dynamics and the establishment of a turbulent wake over a length of 30 wing spans.

An immersed lifting and dragging line model for the vortex particle-mesh method

. This study proposes two methodologies for improving the accuracy of wind
turbine load assessment under wake conditions by combining nacelle-mounted
lidar measurements with wake wind field reconstruction techniques. The first
approach consists of incorporating wind measurements of the wake flow field,
obtained from nacelle lidars, into random, homogeneous Gaussian turbulence
fields generated using the Mann spectral tensor model. The second approach
imposes wake deficit time series, which are derived by fitting a bivariate
Gaussian shape function to lidar observations of the wake field, on the Mann
turbulence fields. The two approaches are numerically evaluated using a
virtual lidar simulator, which scans the wake flow fields generated with the
dynamic wake meandering (DWM) model, i.e., the target fields. The
lidar-reconstructed wake fields are then input into aeroelastic simulations of
the DTU 10  MW wind turbine for carrying out the load validation
analysis. The power and load time series, predicted with lidar-reconstructed
fields, exhibit a high correlation with the corresponding target
simulations, thus reducing the statistical uncertainty
(realization-to-realization) inherent to engineering wake models such as the
DWM model. We quantify a reduction in power and loads' statistical uncertainty
by a factor of between 1.2 and 5, depending on the wind turbine component, when
using lidar-reconstructed fields compared to the DWM model results. Finally,
we show that the number of lidar-scanned points in the inflow and the size of
the lidar probe volume are critical aspects for the accuracy of the
reconstructed wake fields, power, and load predictions.

/pdf/wind-turbine-load-validation-in-wakes-using-wind-field-kefyu1pk96.pdf

Wind turbine load validation in wakes using wind field reconstruction techniques and nacelle lidar wind retrievals

The Actuator Disc/Navier-Stokes (AD/NS) method has played a significant role in wind farm simulations. It is based on the assumption that the flow is azimuthally uniform in the rotor plane, and thus, requires a tip loss correction to take into account the effect of a finite number of blades. All existing tip loss corrections were originally proposed for the Blade-Element Momentum Theory (BEMT), and their implementations have to be changed when transplanted into the AD/NS method. The special focus of the present study is to investigate the performance of tip loss corrections combined in the AD/NS method. The study is conducted by using an axisymmetric AD/NS solver to simulate the flow past the experimental NREL Phase Ⅵ wind turbine and the virtual NREL 5MW wind turbine. Three different implementations of the widely used Glauert tip loss function F are discussed and evaluated. In addition, a newly developed tip loss correction is applied and compared with the above implementations. For both the small and large rotors under investigation, the three different implementations show a certain degree of difference to each other, although the relative difference in blade loads is generally no more than 4%. Their performance is roughly consistent with the standard Glauert correction employed in the BEMT, but they all tend to make the blade tip loads over-predicted. As an alternative method, the new tip loss correction shows superior performance in various flow conditions. A further investigation into the flow around and behind the rotors indicates that tip loss correction has a significant influence on the velocity development in the wake.

https://www.mdpi.com/2076-3417/9/22/4919/pdf

Evaluation of Tip Loss Corrections to AD/NS Simulations of Wind Turbine Aerodynamic Performance

. This article investigates the far wake response of a yawing upstream wind turbine and its impact on the global load variation in a downstream wind turbine. In order to represent misalignment and realignment scenarios, the upstream wind turbine was subjected to positive and negative yaw maneuvers. Yaw maneuvers could be used to voluntarily misalign wind turbines when wake steering control is targeted. The aim of this wind farm control strategy is to optimize the overall production of the wind farm and possibly its lifetime, by mitigating wake interactions. While wake flow and wind turbine load modifications during yaw maneuvers are usually described by quasi-static approaches, the present study aims at quantifying the main transient characteristics of these phenomena. Wind tunnel experiments were conducted in three different configurations, varying both scaling and flow conditions, in which the yaw maneuver was reproduced in a homogeneous turbulent flow at two different scales and in a more realistic flow such as a modeled atmospheric boundary layer. The effects of yaw control on the wake deviation were investigated by the use of stereo particle imaging velocimetry while the load variation on a downstream wind turbine was measured through an unsteady aerodynamic load balance. While overall results show a nondependence of the wake and load dynamics on the flow conditions and Reynolds scales, they highlight an influence of the yaw maneuver direction on their temporal dynamics.

/pdf/experimental-investigation-of-wind-turbine-wake-and-load-3dr92y3k0f.pdf

Experimental investigation of wind turbine wake and load dynamics during yaw maneuvers

An actuator disk method with tip‐loss correction based on local effective upstream velocities

We investigate several algorithms to detect the centerline of a wind turbine wake. First, we apply these methods during Large Eddy Simulations of an isolated wind turbine subject to a uniform (TI = 0%) and a synthetic turbulent inflow (TI = 10%). The simulations are performed using a vortex-particle mesh method with the blades modeled using immersed lifting lines. The most robust algorithm is then applied to investigate the wakes positions inside a wind farm. At wind farm scale, the simulations are performed with a fourth-order finite difference code inside which the wind turbines are accounted for through advanced actuator disks.

https://iopscience.iop.org/article/10.1088/1742-6596/1037/7/072024/pdf

Development of wake meandering detection algorithms and their application to large eddy simulations of an isolated wind turbine and a wind farm

http://absimage.aps.org/image/DFD19/MWS_DFD19-2019-002009.pdf

Data Assimilation for the Prediction of Wake Trajectories Within Wind Farms

This paper aims at the better understanding of the correlations between rotor loads and the wake meandering inside a wind farm. The flow rotor dynamics are simulated by means of Large Eddy Simulations coupled to Actuator Disk models. The wake meandering is captured through a centerline tracking, itself based on the available power in the flow. Two turbulence intensities are investigated, TIs = 6% and 10%. Results show that the yawing moment is very well correlated to the wake movement, even for wind turbines located deeper into the the wind farm. Correlations can also be found between the wake oscillation and the root bending moments. Wake signatures can also be identified from the amplitude of the high-frequency oscillations of the root bending moments; however, the correlation is sometimes less visible, and deviations can be correlated to wind events or wake decay.

A numerical study of correlations between wake meandering and loads within a wind farm

Large eddy simulations coupled to Actuator Disks are used to investigate wake effects in wind farms. An effort is made on the wind turbine model: it uses the prevailing velocities at each point of the disk to estimate the aerodynamic loads and is improved using a tip-loss correction and realistic control schemes. This accurate and efficient tool is used to study the wind farm response in terms of flow and power production during an unsteady scenario: this work focuses on an emergency shutdown of one rotor inside a wind farm.

https://iopscience.iop.org/article/10.1088/1742-6596/753/3/032053/pdf

Maud Moens

Papers

An actuator disk method with tip‐loss correction based on local effective upstream velocities

Development of wake meandering detection algorithms and their application to large eddy simulations of an isolated wind turbine and a wind farm

Data Assimilation for the Prediction of Wake Trajectories Within Wind Farms

A numerical study of correlations between wake meandering and loads within a wind farm

LES of wind farm response to transient scenarios using a high fidelity actuator disk model