bluuebunny/crossref_metadata_2025_split huggingface dataset:
Large Eddy Simulation of Wind Turbine Wakes during the Evening Transition Period
Authors: Chanprasert W. , Sharma R. N. , Cater J. E. , Norris S. E. 
Published: September 2020

Abstract
A transient simulation of a two inline wind turbines during the evening transition period is modelled using Large Eddy Simulation with an actuator disc method. Two inline turbines are placed parallel to the stream-wise direction and the distance between the turbines is seven rotor diameters. The wind profiles and turbulence data are produced by a precursor simulation. The simulation was carried out for four physical hours and the surface heat flux varies with time according to the evening period. The wind profile evolves over the transition period and the atmospheric stability gradually changes from unstable in the late afternoon to a stable condition in the evening. The wake recovers more quickly in the afternoon and it recovers more slowly corresponding to the changes in atmospheric stability. This causes a reduction in the power output and the mean thrust load of the downstream turbine over the period. Additionally, the velocity spectrum displays higher fluctuations at the downstream turbine.
An induction-aware parameterization for wind farms in the WRF mesoscale model
Authors: Mayol M L , Diaz GP Navarro , Saulo AC , Otero AD 
Published: September 2020

Abstract
With the aim of assessing the potential impacts of wind farms on weather and regional climate, in this work an induction-aware modified version of the Wind Farm Parameterization implemented in the WRF model is presented. It uses the undisturbed wind speed, instead of the grid cell velocity, as reference to compute the corresponding momentum sink, source of TKE and power output. The relation between the reference and grid velocity is obtained from a previous calibration process. The modified parameterization is verified by simulating one single wind turbine, showing that the power output becomes independent of the selected horizontal resolution. Finally, the performance of the new parameterization is tested over an utility-scale wind farm. It is applied to compute the wind farm efficiency for different wind directions, under several resolutions and its results compared with former parameterizations.
IEA Wind Task 31: Design of a new comparison metrics simulation challenge for wind resource assessment in complex terrain Stage 1
Authors: Barber S , Buehler M , Nordborg H 
Published: September 2020

Abstract
In wind energy, the accuracy of the estimation of the wind resource has an enormous effect on the expected rate of return of a project. For a given project, the modeller is faced with a difficult choice of a wide range of simulation tools with varying accuracies and costs. In previous work, a new method for estimating the skill and cost scores of different wind modelling tools for a given project has been developed. Although this method worked well, it was shown that further studies are required for a wide range of input conditions and project types in order to develop project-specific transfer functions between the predicted and actual cost and skill scores. In this paper therefore, a new simulation challenge is designed with the goal of collecting comparison metrics data regarding the skill and cost scores of a range of different simulation tools for a complex terrain site, both before and after carrying out the simulations. The complex terrain site Perdigao is chosen for the challenge, due to the volume and quality of available measurement data and the complexity of the terrain. An initial data analysis and WAsP simulations allow mast 29 to be chosen for the input data and masts 7, 10, 20, 22, 25, 27, 34 and 37 for the validation data. The WAsP simulations are compared to previous WRF simulations and are found to capture the main features of the flow over the two ridges. The wind acceleration over the two ridges and the resulting maximum wind speeds at the peak of the ridges as well as the reduced velocity regions in the valley between the ridges are well captured. However, smaller-scale features such as small areas of separated flow seen in the WRF simulations cannot be captured by WAsP. This choice of mast for the challenge will therefore allow the capabilities of different tools for calculating flow in separated regions as well as on top of hills to be assessed.
Wind Tunnel Study of a “Floating” Wind Turbine’s Wake in an Atmospheric Boundary Layer with Imposed Characteristic Surge Motion
Authors: Schliffke Benyamin , Aubrun Sandrine , Conan Boris 
Published: September 2020

Abstract
Floating offshore wind turbines (FOWTs) are a potential source for increased offshore energy production. As the technology is still in a pre-industrial state several questions remain to be addressed where little field data is available. This study uses physical modelling at a reduced scale to investigate the unsteady behaviour and the development of the wake in a simplified FOWT model. A porous disc model is placed in an atmospheric wind tunnel and subjected to a range of different motions. The effects of induced sinusoidal surge motion on the characteristics of the model’s wake at a fixed downstream distance of 4.6D are studied. First results show unchanged mean velocity values but modified turbulence intensity and turbulent kinetic energy profiles. Spectra taken in the wake show shifts to higher frequencies in the longitudinal flow component while the opposite is true for the vertical flow component. Further research into spatial characteristics of the wake are necessary to confirm these results.
POD analysis of the recovery process in wind turbine wakes
Authors: De Cillis G , Cherubini S , Semeraro O , Leonardi S , De Palma P 
Published: September 2020

Abstract
The wake produced by a single three-bladed wind turbine is investigated using the proper orthogonal decomposition (POD) of numerical data obtained by a large eddy simulation. The rotor blades are modeled using the actuator line method, whereas tower and nacelle are simulated through an immersed boundary method. The POD is performed in a three-dimensional subdomain enclosing the wake after conducting a convergence test, which demonstrates that the first ten modes are well converged. Most energetic POD modes identify and isolate different flow features characterising the wake dynamics, such as the tip-vortices spirals, the von Kárman vortices shed by the tower, the Kelvin-Helmholtz instability linked to the wake shear layer. Very low frequency modes are also found, which could be related to the wake meandering phenomenon. Moreover, the wake recovery process is studied by computing the contribution of each POD mode to the mean-kinetic-energy entrainment. This analysis indicates that tip vortices negatively affect the wake recovery, since they provide a negative entrainment. On the contrary, flow structures related to the tower wake are found to be beneficial to wake recovery, demonstrating the importance of including tower and nacelle in numerical simulations.
Increasing turbine dimensions: impact on shear and power
Authors: Barthelmie R.J. , Shepherd T.J. , Pryor S.C. 
Published: September 2020

Abstract
As wind turbine average hub-height (H) and rotor diameter (D) grow, it is assumed that the benefit derived from larger swept areas and higher wind speeds at higher altitudes will outweigh any increase in fatigue loading due to higher shear and manufacturing/installation costs. The impact of increasing wind turbine H and D on power production and the occurrence of extreme positive and negative shear is examined using high-resolution simulations with the Weather Research and Forecasting (WRF) model over Iowa. Three wind turbine scenarios are considered; S#1: H=83m, D=100m; S#2: H=100 m, D=100 m and S#3: H=100 m, D=133 m. Increasing H from 83 m to 100 m while maintaining D=100 m increases power by 16% relative to scenario 1. Increasing D to 133 m from 100 m with H=100 m doubles the power output compared to S#1. Extreme shear across the rotor plane (shear exponent α > 0.2 or α < 0) is frequently observed, but only modestly impacted by the changes in wind turbine dimensions. Thus, the increase in power output from increasing H and D to these levels seems to incur little penalty in terms of increased occurrence of high positive or negative shear.
Evaluation of the WRF model for simulating surface winds and the diurnal cycle of wind speed for the small island state of Fiji
Authors: Dayal K K , Cater J E , Kingan M J , Bellon G D , Sharma R N 
Published: September 2020

Abstract
Evaluation of the performance of the WRF model is carried out for simulating the surface winds and the diurnal cycle of wind speed for the small island developing state of Fiji at a 1.33 km by 1.33 km grid resolution using 1deg gridded data from NCEP-FNL. Simulations are performed for an austral summer (January 2017) and an austral winter (July 2017) month using the dynamical downscaling and the two-way nested approach. A set of physics parameterization schemes together with topo_wind = 1, 2 and ysu_topdown_pblmix = 1 physics settings associated with YSU PBL scheme are used to correct the surface winds and the diurnal cycle of wind speed. The results reveal that the WRF model is able to capture the surface winds and the diurnal cycle of wind speed on the windward side. Surface winds on the leeward side and the outer islands, show positive bias especially at nighttime for January and at both the day and night time for July. The statistical evaluation of all stations for January (July) showed a bias of 1.16 m/s (1.89 m/s), RMSE of 2.40 m/s (3.14 m/s), STDE of 1.88 m/s (2.08 m/s) and diurnal cycle correlation of 0.74 (0.68) using topo_wind = 2 and ysu_topdown_pblmix = 1.
Lagrangian Vortex computations of turbine wakes: recent improvements using Poletto’s Synthetic Eddy Method (SEM) to account for ambient turbulence
Authors: Bex Camille Choma , Pinon Grégory , Slama Myriam , Gaston Benoist , Germain Grégory , Rivoalen Elie 
Published: September 2020

Abstract
This paper presents possible techniques for modelling ambient turbulence in the Lagrangian Vortex Method formalism. Due to the fact that regular Synthetic Eddy Method (SEM) already presented in previous studies is not divergence free by definition; improvements were necessary to develop a similar SEM method with such a divergence free property. The recent improvements formulated by R. Poletto give the way to such a possibility. This new Divergence Free Synthetic Eddy Method (DFSEM) is presented here in comparison with the regular SEM. Obtained numerical velocity fields are compared in terms of convergence properties, Power Spectral Density and also Taylor macro-scale. Finally, turbine wakes are computed with both the recent Poletto’s DFSEM and the regular Jarrin’s SEM to highlight differences. At this stage of development, the DFSEM seems very promising even though some improvements are still necessary.
Large-scale coherent structures in the atmosphere over a flat terrain
Authors: Alcayaga Leonardo , Larsen Gunner Chr. , Kelly Mark , Mann Jakob 
Published: September 2020

Abstract
Large-scale coherent motions in the atmospheric boundary layer are investigated from field measurements made with two scanning wind lidars over a two-dimensional domain covering approximately 50 km2. The size, isotropy and two-point statistics of the coherent structures, show their influence on wind field homogeneity and local conditions that wind turbines might experience within a wind farm. For neutral atmospheric stability and high wind conditions, most of these structures are observed to be narrow streaks of low streamwise momentum having positive vertical velocity component (ejections), extending several kilometers. The results shown here are consistent with numerical simulations of atmospheric flows under similar conditions, and scale experiments made in laboratories.
Downscaling and improving the wind forecasts from NWP for wind energy applications using support vector regression
Authors: Yakoub Ghali , Mathew Sathyajith , Leal Joao 
Published: September 2020

Abstract
The stochastic nature of wind poses challenges in the large scale integration of wind energy with the grid. Wind characteristics at a site may significantly vary with time. which will be reflected on the wind power production. Understanding and managing such variations could be challenging for wind farm owners. energy traders and grid operators. In this work. we propose models based on support vector regression (SVR) to downscale the speed and direction of wind at a specific site using both historical observed measurements and numerical weather predictions (NWP). Several meteorological variables. considered to have potential influence on the wind. were used in the feature selection for the models. The models are then optimally developed and used to predict the wind speed and direction at the site considered. In view of the two of Nord pool’s energy markets namely the intraday and day ahead markets. approaches for short-term forecasts (t + 1 hours) and medium-term recursive forecasts (t + 36 hours) were developed. The proposed SVR models are found to be accurate and efficient in correcting the NWP information and predicting the wind speed and direction for the short-term forecasts. For medium-term forecasts. the developed models could outperform the NWP. especially for the wind speed predictions.
Wind farm blockage effects: comparison of different engineering models
Authors: Branlard Emmanuel , Quon Eliot , Meyer Forsting Alexander R. , King Jennifer , Moriarty Patrick 
Published: September 2020

Abstract
The work presents four engineering methods to estimate the induction zone in front of a wind turbine and account for the wind farm blockage effect. The methods comprise the vortex cylinder model, vortex dipole model, self-similar model, and wake projection model. The majority of the models presented account for yaw misalignments and ground effect. Actuator disk simulations are used to verify the individual models. The performance of each model is evaluated both in terms of precision and computational time. The induction models are coupled to wake models within the FLOw Redirection and Induction in Steady State framework to provide the full velocity field within a wind farm. Sample wind farm computations are presented, and the impact of including induction effects into wind farm performance predictions is reported. The different codes are publicly available online.
Wind turbine wake characterization using the SpinnerLidar measurements
Authors: Conti Davide , Dimitrov Nikolay , Peña Alfredo , Herges Thomas 
Published: September 2020

Abstract
We analyze SpinnerLidar measurements of a single wind turbine wake collected at the SWiFT facility and investigate the wake behaviour under different atmospheric turbulence conditions. The derived wake characteristics include the wake deficit, wake-added turbulence and wake meandering in both lateral and vertical directions. The atmospheric stability at the site is characterized using observations from a sonic anemometer. A wake-tracking technique, based on a bi-variate Gaussian wake shape, is implemented to monitor the wake center dis-placements in time to derive quasi-steady wake deficit and turbulence profiles in a meandering frame of reference. The analysis demonstrates the influence of atmospheric stability on the wake behaviour; a faster wake deficit recovery and a higher level of turbulence mixing are observed under unstable compared to stable atmospheric conditions. We also show that the wake me-andering is driven by large-scale turbulence structures, which are characterized by increasing energy content as the atmosphere becomes more unstable. These results suggest the suitability of the dataset for wake-model calibration and provide statistics of the wake deficit, turbulence levels, and meandering, which are key aspects for load validation studies.
Code-to-code-to-experiment validation of LES-ALM wind farm simulators
Authors: Wang C , Muñóz-Simon A , Deskos G , Laizet S , Palacios R , Campagnolo F , Bottasso C L 
Published: September 2020

Abstract
The aim of this work is to present a detailed code-to-code comparison of two Large-Eddy Simulation (LES) solvers. Corresponding experimental measurements are used as a reference to validate the quality of the CFD simulations. The comparison highlights the effects of solver order on the solutions, and it tries to answer the question of whether a high order solver is necessary to capture the main characteristics of a wind farm. Both solvers were used on different grids to study their convergence behavior. While both solvers show a good match with experimental measurements, it appears that the low order solver is more accurate and substantially cheaper in terms of computational cost.
Quantifying the Predictability of a ‘Dunkelflaute’ Event by Utilizing a Mesoscale Model
Authors: Li Bowen , Basu Sukanta , Watson Simon J. , Russchenberg Herman W. J. 
Published: September 2020

Abstract
In the coming decades, both wind and solar power production will be playing increasingly important roles in Europe’s energy economy. It is absolutely essential that power grids are resilient against any unusual weather phenomena. One such meteorological phenomenon, “Dunkelflaute”, is causing serious concern to the renewable energy industry, which is primarily characterized by calm winds and overcast conditions. For example, a Dunkelflaute event happened in the Netherlands on 30th April 2018 leading to a significant shortfall in renewable energy generation requiring emergency intervention by the system operator. By analyzing this case, this paper investigates the performance of a state-of-the-art mesoscale model, Weather Research and Forecasting (WRF), in forecasting a Dunkelflaute event. Multiple WRF simulations are driven using real-time Global Forecast System (GFS) operational data over a range of prediction horizons. For comparison, a benchmark run is carried out using ERA5 reanalysis data as boundary conditions. Through validation using a variety of measured data covering onshore and offshore areas, wind speed is shown to be more predictable than cloud-cover in this particular case study.
Yaw induced wake deflection-a full-scale validation study
Authors: Larsen G.C. , Ott S. , Liew J. , van der Laan M.P. , Simon E. , Thorsen G.R. , Jacobs P. 
Published: September 2020

Abstract
Aerodynamic wake interactions between turbines located in wind power plants cause both a loss in power production and an increase in fatigue loading of the wind farm turbines. Yaw induced active wake deflection is one possible wind farm control strategy, which can be applied to mitigate wake effects on nearby downstream located wind turbines. In the present study three flow models of different fidelities are applied to mimic a full-scale study of wake deflection recorded by an advanced synchronised setup of two long-range pulsed scanning lidars. The investigated case studies encompass a base case with (approximately) zero yaw setting supplemented by two non-zero yaw cases of 17.5° and -14.5°, respectively. The model results are compared mutually as well as with the result of the full-scale measurement campaign.
Effect of conventionally neutral boundary layer height on turbine performance and wake mixing in offshore windfarms
Authors: Sood Ishaan , Munters Wim , Meyers Johan 
Published: September 2020

Abstract
In this study, we investigate the effect of conventionally neutral boundary layer height and capping inversion strength on wind farm performance. An aeroelastic multibody solver coupled with a pseudo-spectral large eddy simulation code is used to investigate the structural and aerodynamic output of wind turbines in 4 different inflow types. Farm layouts comprising of turbines in both aligned and staggered arrangements are studied. It is found that the shallower boundary layers with strong capping inversions are characterized by oscillatory structures in turbine wakes, leading to increased structural damage in downstream wind turbines due to fatigue. The power output is also observed to decrease due to poorer wake mixing.
Data-driven turbulence modeling for wind turbine wakes under neutral conditions
Authors: Steiner Julia , Dwight Richard , Viré Axelle 
Published: September 2020

Abstract
Currently, the state of the art in wind farm flow physics modeling are Large Eddy Simulations (LES) which resolve a large part of the spectra of the turbulent fluctuations. But this type of model requires extensive computational resources. One wind speed and direction simulation of the Lillgrund wind farm can take between 160k and 3000k processor hours depending on how the turbines are modeled [1, 2]. The next-fidelity model types are Reynolds-Averaged Navier-Stokes (RANS) models which resolve only the mean quantities and model the effect of turbulence fluctuations. These models require about two orders of magnitude less computational time, but generally do not produce accurate predictions of the mean flow field. Proposed modifications made to these models so far do not generalize well and there is room for improvement. Hence, we present the first steps towards using a data-driven approach to aid in deriving new RANS models that generalize well to different turbine types, varying atmospheric stability, and farm layouts. To do so, time-averaged LES data is used to derive corrections to existing RANS models. The approach uses a deterministic symbolic regression method to infer algebraic correction terms to the RANS turbulence transport equations. Optimal correction terms to the RANS equations are derived using a frozen approach where time-averaged flow fields from LES are injected into the RANS equations. The potential of the approach is demonstrated under neutral conditions for multi-turbine constellations at wind-tunnel scale. The results show promise, but more work is necessary to realize the full potential of the approach.
The effect of dynamic near-wake modulation on utility-scale wind turbine wake development
Authors: Abraham Aliza , Martínez-Tossas Luis A , Hong Jiarong 
Published: September 2020

Abstract
High-resolution field-scale experiments using flow visualization with natural snowfall and high-fidelity large eddy simulations are combined to investigate the effect of dynamic turbine operation and atmospheric conditions on wind turbine wake mixing and recovery in the wake of a 2.5 MW wind turbine. Instantaneous near-wake expansion and deflection in response to changes in blade pitch and wind direction, termed dynamic wake modulation, is quantified using both techniques, demonstrating excellent agreement. The simulations are used to extend these results by calculating the energy flux into the wake 7 rotor diameters downstream, showing that dynamic turbine-atmospheric interactions enhance mixing in the far-wake. This finding is exhibited under both uniform and turbulent inflow conditions. Under turbulent flow, a synergistic relationship is also observed between dynamic wake modulation and wake meandering, as wake recovery can be further accelerated when the two phenomena occur together. The results of this study have implications for the development of more realistic far-wake models that include the significant impact of dynamic wake modulation on wake mixing and development. Additionally, the findings from the current study can be used to develop advanced control algorithms to speed up wake breakdown and recovery, further improving wind farm efficiency.