bluuebunny/crossref_metadata_2025 huggingface dataset:
Active Cluster Wake Mixing
Authors: Gutknecht Jonas , Becker Marcus , Taschner Emanuel , Stipa Sebastiano , Allaerts Dries , Viré Axelle , Van Wingerden Jan-Willem
Published: June 2024

In recent years, the relevance of the interaction between neighboring wind farms has grown steadily. As one farm extracts energy from the wind, a downstream one can systematically experience lower wind speeds which threatens the economic viability of the farm. Significant progress has been made in understanding these farm-farm wake interactions, but we still lack methodologies to mitigate their undesired effects. In this study, we introduce Active Cluster Wake Mixing (ACWM). This novel method aims to accelerate the recovery of the cluster wake using dynamic control actions: By exciting the thrust of the individual turbines depending on their relative location, we generate non-uniform patterns of energy extraction. Phase offsets between the individual excitation signals propagate these regions through the wind farm. This results in large-scale velocity gradients inside the farm, which also affect the flow in the cluster wake region. An in-depth exploration and optimization of ACWM requires significant computational effort. Therefore, we compare three different wind farm modeling approaches in Large Eddy Simulations (LES) that differ in their computational costs regarding their suitability for further exploration of ACWM. For this purpose, we use an unoptimized ACWM scheme with two different excitation frequencies. For the first time ever we successfully show that ACWM manipulates the flow inside the wind farm with favorable effects on the wake velocity. We also demonstrate that the modeling of cluster wakes is challenging and has a significant effect on the potential gain.
A blind test on wind turbine wake modelling based on wind tunnel experiments: Phase I – The benchmark case
Authors: Pappa V , Campagnolo F , Tamaro S , Mühle F , Stegmüller J , Croce A , Gromke C , Riziotis V , Bottasso C , Sciacchitano A , Bouris D , Manolesos M
Published: June 2024

Wind turbine wake and modelling is crucial to optimizing future wind farm layouts and hence reducing the cost of energy. This paper presents the first phase of a blind test on modelling controlled and uncontrolled wind turbine wakes. The blind test is based on wind tunnel experiments of two model scale wind turbines (D = 1.1 m) one downstream of the other. The exercise is split into two phases and the first one is presented here, where participants are invited to simulate the baseline case, in which both turbines are aligned with the flow and there is no control on the either turbine. The objective of this phase is to ensure all participants can benchmark their numerical approach against a baseline open data set, where no wake control is applied. Experimental measurements include inflow velocity, turbine power and loads for a range of tip speed ratios. In the second phase, not presented here, the wake of the upstream turbine will be controlled and the performance of the downstream one will be recorded. This will be a blind test with the data not released prior to submissions. The present paper gives an overview of the initial, open benchmark case, including its objectives, methodology and experimental results.
Passive Mooring-based Turbine Repositioning Technique for Wake Steering in Floating Offshore Wind Farms
Authors: Alkarem Yuksel R. , Huguenard Kimberly , Verma Amrit S. , Van Binsbergen Diederik , Bachynski-Polić Erin , Nejad Amir R.
Published: June 2024

Power loss due to wake effects from upstream wind turbines is an important factor in the design of floating wind farms. These wake disturbances also increase fatigue loads on downstream units. Economic-driven wind farm layout optimization may culminate in non-standard, irregular configurations of offshore wind farms that deviate from conventional engineering practices. Consequently, wind farm developers are inclined towards a more geometrically coherent layout that are sub-optimal. Floating wind turbines horizontal offsets can be used to overcome wake losses. In this study, a novel method suggesting various mooring orientation methods to passively reposition the wind turbines in the farm to maximize annual energy yield. Preliminary parametric optimization demonstrates the effectiveness of the proposed method for standard floating wind farm designs to reduce wake effects by as much as 30% at rated wind speed compared to a baseline case, while preserving the farm’s overall uniformity.
Performance comparison of analytical wake models calibrated on a large offshore wind cluster
Authors: Van Binsbergen Diederik , Daems Pieter-Jan , Verstraeten Timothy , Nejad Amir , Helsen Jan
Published: June 2024

This study benchmarks the performance of multiple analytical wake models using a multi-level hyperparameter optimization framework for calibrating models with SCADA data in the Belgian-Dutch offshore zone. The calibration targets wind coming the northwest (300 to 330 degrees) with wind speeds ranging from 7 to 9 m/s, a wind direction where wakes are clustered across Belgian wind farms. Six wake models are evaluated, namely those described by Jensen (1983), Bastankhah (2014), Niayifar (2016), Zong (2020), Nygaard (2020), and Pedersen (2022). Relative and accumulated relative error between the calibrated wake models and SCADA data are analyzed both on turbine, farm, and cluster level. Statistical moments of the residual error between each model and SCADA data for individual turbines are presented in boxplots for each wind farm and are analyzed using kernel density estimates. Additionally, the calibrated tuning parameters are used to calculate wake losses, demonstrating a strong overlap across models. The analysis reveals that the top-hat TurbOpark model shows the best performance, followed by its Gaussian variant. The Gaussian models by Niayifar (2016) and Zong (2020), as well as the top-hat model by Jensen (1983) all show relatively good performance, while the Gaussian model by Bastankhah (2014) has the worst performance after calibration. While some models perform better than other models, all models show similar trends post-calibration, indicating that with proper calibration, any model can be viable, given its inherent limitations are recognized and managed.
Power production and large-scale wake effects of offshore wind turbines with low specific rating
Authors: Paulsen Johannes , Dörenkämper Martin , Steinfeld Gerald
Published: June 2024

With the aim to increase the energy yield of large offshore wind farm clusters, especially during low wind speeds, innovative rotor concepts with low specific ratings are being developed. We use mesoscale simulations, to compare wakes and power production of a wind farm cluster with a rated power of 1.17 GW, equipped with a turbine featuring a low specific rating turbine concept, and the IEA 15 MW offshore reference turbine. While the IEA turbine resembles typical offshore wind turbine concepts, the HL rotor features a very large rotor diameter compared to its rated power, thus resulting in a very low specific rating for an offshore turbine. We simulate two wind farms made up of either of the two turbines that have the same installed capacity and farm layout. We found an improved power production of 86 % to 100 % for the HL wind farm in partial load conditions and comparable power production at rated operation. While the HL wind farm exhibits a more pronounced cluster wake during partial load operation, the IEA wind farm induces a larger wind speed deficit in the wake during rated operation. We discuss observed differences in wake behaviour, attributing them to the larger rotor diameter and lower thrust coefficient of the HL concept.
Validation of induction/steering reserve-boosting active power control by a wind tunnel experiment with dynamic wind direction changes
Authors: Tamaro S , Guilloré A , Anand A , Mühle F V , Campagnolo F , Bottasso C L
Published: June 2024

This paper presents an experimental validation of an active power control methodology that combines induction control and wake steering to maximize the power reserve of the wind turbines in a farm. The experiments are carried out on a cluster of three scaled wind turbines in a boundary-layer wind tunnel, by dynamically varying the wind direction, and by considering a time-varying power tracking signal that mimics secondary frequency control of the grid. The methodology is compared with three active power control algorithms sourced from the literature. Results indicate that the instantaneous power reserves are indeed improved by an appropriate handling of wake effects, achieving a more accurate tracking of the power signal.
Reconstruction of environmental site conditions by the integration of SCADA and reanalysis data
Authors: Vad A , Bottasso C L
Published: June 2024

For the operational optimization of wind farms, AEP estimation and other tasks, high quality data of environmental conditions at the site are necessary. However, such data is often not available or has insufficient quality. This work tries to fill this gap, by integrating two data sources: the (usually available) operational data from the SCADA (Supervisory Control and Data Acquisition) system, and reanalysis data. SCADA data streams contain measurements from each wind turbine in the farm, but they are affected by various sources of uncertainty (including local flow effects, miscalibration, etc.), and might contain gaps. Meteorological reanalysis datasets can be used to fill gaps and complement SCADA data. However, modelled data can contain a wide range of biases and errors, due to limited model fidelity, coarse spatial and temporal resolution, inaccuracies in the input data feeding the model, etc. This study considers various methods to extract and merge wind speed and direction information from these diverse data sources. The analysis is based on field data measured at two experimental test sites, an offshore site equipped with 111 multi-MW turbines and a lidar buoy, and an onshore site equipped with 14 multi-MW wind turbines and a lidar. The methods are evaluated in the spectral and temporal domains by comparing the reconstructed wind characteristics with measurements from the lidars.
Are steady-state wake models and lookup tables sufficient to design profitable wake steering strategies? A Large Eddy Simulation investigation
Authors: Lejeune Maxime , Frère Ariane , Moens Maud , Chatelain Philippe
Published: June 2024

We leverage Large Eddy Simulation (LES) of wind farms to study the performances of an open-loop wake steering controller. This global controller is elaborated based on Lookup Table (LUT) generated using FLORIS. Our objectives are to highlight the potential problems that can arise from model errors due to its steady-state formulation and from difficulties to properly define the ambient flow state. We consider two wind farm configurations: a first theoretical layout of six machines, and a second layout representing a commercial wind farm that is currently studied for wake steering strategy, the King Plains wind farm. We represent our wind farm environment using LES within which the turbines are modeled as actuator disks. In addition to the standard local controller, the wind farm utilizes a LUT to compute the optimal yaw offset angles. Before its integration into the controller, this LUT is first populated using the yaw optimizer integrated into FLORIS. The primary input parameters for the LUT are derived from the freestream atmospheric conditions, which are parametrized in terms of TI, hub height wind speed, and wind direction. In this work, we investigate different strategies for estimating the ambient wind direction fed as input to the LUT during the control and their impact on the dynamics of the yaw actuation. While results confirm the potential of this type of controller, they also highlight the importance of a proper sensing to determine the freestream state.
A numerical analysis of wind farm wake characteristics in the southern part of the North Sea
Authors: Palatos-Plexidas Alexandros , Gremmo Simone , Porchetta Sara , Van Beeck Jeroen , De Cruz Lesley , Munters Wim
Published: June 2024

The rapid expansion of wind farms in the North Sea requires a better understanding of the wind turbines’ wake effects. In this study, the classification of wake patterns under different atmospheric boundary layer stability conditions is investigated. For this purpose, the Weather Research and Forecast model is utilized to calculate wind farm wake effects over the southern North Sea for a year-long period. The atmospheric stability is characterized by the value of Monin-Obukhov length, and seven different classes are considered. The results have shown that the predominance of the stability condition depends on seasonality. In autumn and winter months very unstable conditions prevail, while in spring and summer periods near-neutral and stable events occur more frequently. The different atmospheric stability conditions have distinct effects on the averaged wind-speed deficits. Specifically, in near-neutral and stable stratification, wakes propagate further downwind of the wind turbines affecting neighboring wind farms, while in the case of unstable conditions, these effects are weaker.
On the impact of different static induction control strategies on a wind turbine wake
Authors: Zúñiga Inestroza Manuel Alejandro , Hulsman Paul , Petrović Vlaho
Published: June 2024

This study provides a wind tunnel investigation to identify effective ways of derating an upstream turbine for mitigating wake-induced power losses. Short-range continuous-wave lidar measurements are used to remotely map the time-averaged wake characteristics of a controllable model wind turbine under uniform inflow with negligible turbulence. The analysis focuses on comparing four distinct static induction control (SIC) strategies, each at targeted derating levels of 5 % and 10 %, against a conventional greedy strategy. The results indicate that pitch-to-feather combined with an increased tip-speed ratio is the most favourable approach for minimising wake losses in a two-turbine setup. Notably, power gains of up to 3.8 % are achieved for partial and full wake overlap conditions at 5 % derating and small turbine spacing. These observations are consistent with previous field experiments, suggesting that SIC may be advantageous in wind farms with closely spaced turbines. Overall, these findings underscore the importance of carefully selecting and understanding the implemented derating strategy for supporting wind farm flow control applications.
Wind tunnel investigation on the recovery and dynamics of the wake of a floating offshore wind turbine subjected to low inflow turbulence
Authors: Messmer Thomas , Peinke Joachim , Hölling Michael
Published: June 2024

Floating offshore wind turbines (FOWT) operate in various turbulent conditions, including low turbulence intensity situations (TI∞
≤ 5%). In this paper, we investigate experimentally the wake of a model floating wind turbine subjected to inflow turbulence up to TI∞
≈ 3%. We consider idealised surge platform motion and analyse wake measurements at different downstream positions x ∈ [4D, 8D]. The results show that rotor movements enhance wake recovery compared to the fixed wind turbine, especially for TI∞
≤ 2%. The recovery of the moving wind turbine wake is progressively less affected by motion with increasing TI∞
. Both amplitude and frequency of motion are key parameters that drive wake recovery and dynamics. We found in the wake large coherent structures induced by the platform movements, which allow a faster transition to the far wake but may cause increased loading on downstream turbines.
The impacts of climate change on offshore wind park projects: from changes in resource to project profitability
Authors: Olivares-Cabello Claudia , López Ana , Gebraad Pieter , Lizcano Gil , Edvaldsson Edvald
Published: June 2024

Offshore wind power generation is projected to increase 15-fold over the next two decades. This generation is, however, weather dependent. The compounding of the anthropogenic climate change signal with high spatial and temporal wind variability can lead to large uncertainties in the projected impacts of climate change on wind resources, and further down the line in the economics of a project. In this study, we showcase a methodology to analyze the impact of climate change on the economic indicators of an offshore wind farm project. Projections of changes in wind resources are obtained using an ensemble of statistically downscaled Coupled Model Intercomparison Project 6 (CMIP6) for different emission scenarios and time periods. A series of assumptions about the features of a representative wind farm and its key economic parameters are made to compute two economic indicators: the Internal Rate of Return (IRR) and the Levelized Cost of Energy (LCOE). The IRR is an estimate of the profitability of potential investments and the LCOE is the cost over the lifetime of an investment compared to the expected energy production. We find that the effect of changes of resource on IRR and LCOE depends on the region, emissions scenario, and projection period. In general, and conditioned on the assumptions underlying this study, impacts on IRR are more significant -i.e., with differences between -0.5% and -1% in Brazil- than on LCOE. We conclude that it is especially important to take into account climate change when making investment decisions based on a project’s expected profitability.
The Influence of Topographical Variations on Wind Turbine Wake Characteristics Using LES
Authors: Patel Jay A. , Maity Ankita , Ghaisas Niranjan S.
Published: June 2024

A detailed understanding of the characteristics of wind-turbine wakes over complex terrain is crucial for designing efficient wind farms. Complexity of the terrain can be due to changes in elevation (due to, e.g., hills/valley/cliffs), and changes in the surface roughness (due to land types, e.g. fallow/cultivated/forested). We employ large-eddy simulations to study the evolution of a wind-turbine wake sited at different locations on a gradual two-dimensional hill with and without an abrupt transition in its surface aerodynamic roughness. A turbine placed at the foot of the hill, midway between the foot and the peak, and at the hill peak behave very differently when compared against each other. For a homogeneously rough surface, the profile of the velocity deficit normalized by the inflow velocity at the hill peak height shows that the wake recovers fastest for a turbine placed at the midway location. For a heterogeneously rough surface, however, the wake recovery for a turbine at the midway location is not significantly faster than that for a turbine at the hill-foot. The surface heterogeneity accelerates the flow downstream, which affects the wake recovery, due to which the deficits over heterogeneously rough surfaces are typically larger than for homogeneous surfaces. The turbulence intensity as well as the turbulence intensity added due to the presence of the turbine are affected by the position of the turbine as well as the surface roughness heterogeneity. The observed differences between the rates of wake recovery are only partly explained by the pressure gradient of the background flow over the hill in the absence of the wind turbine. The pressure drop over a region from one diameter upstream to five diameters downstream of the turbine explains the wake recovery for the turbines sited on homogeneously rough surface but not on a heterogeneously rough surface.
Wake steering experiments in onshore and offshore wind farms
Authors: Pena Martinez Juan Jose , Coussy Juliette
Published: June 2024

Over the past years, wake steering has been the subject of much research in the wind industry. Multiple academic publications have shown results from high fidelity simulations (such as SOWFA), engineering simulations (such as FLORIS) or from field tests. Most of this research is focused on the power increase as it is the main goal of wake steering. However, other key topics need to be covered upfront. Wake Adapt is the product developed by Siemens Gamesa Renewable Energy that applies wake steering at commercial level. As presented in this paper, some prerequisites are needed before Wake Adapt installation to ensure the wind turbines are calibrated to apply the optimum yaw offsets. The increase in energy is not without costs: yaw activity is increasing which impacts the maintenance costs. Wake Adapt loads must be assessed, and it has been shown that Wake Adapt loads cases are covered by design loads of the turbines. On the modelling side, the Wake Adapt yaw offsets are generated using some engineering models well known by the scientific community. Some robustness is added to the Yaw Offset Lookup Table to ensure that the optimum yaw offsets calculated in steady-state conditions are still optimum with unsteady conditions. Finally, in order to measure the Wake Adapt benefit, a Swap Test can be conducted where wind farm power output with and without Wake Adapt are compared following a certain procedure, especially if the predicted and measured power benefit needs to be compared. The last section of this paper shows some first tests in an onshore wind farm, as well as the results of a full Swap Test in an offshore wind farm, where the measured gain and the predicted gain shows very similar values.
Wind turbine power extraction under partial wake operations, a CFD study using ALM.
Authors: Campaña-Alonso Guillén , Ferrer Esteban , Méndez-López Beatriz
Published: June 2024

This study focuses on the intricate interplay between large wind turbines and their wake effects on neighboring turbines. We specifically investigate the influence in power production and aerodynamic loads when a turbine operates under the influence of upstream turbine wakes. The analysis has been performed by means of Computational Fluid Dynamic simulations using OpenFOAM, while wind turbines are modelled with an Actuator Line Model approach. Two large IEA 15 MW reference wind turbines, with one turbine partially affected by the other’s wake, are analyzed. The research assesses the influence of turbine spacing on aerodynamic torque and blade loads. The study shows that the CP
may suffer oscillations 2 orders of magnitude greater than the ones observed at the reference cases. For the most affected case, the torque experiences oscillations of a 5.46 % w.r.t. to the averaged torque over the last ten revolutions. The influence of operating in partial wake conditions is specially relevant on the blade root loads that are found to suffer an increase of ∼ 20 % and a decrease of ∼ 30 % over one revolution as the blade is affected by the highly sheared flow resulting from the upstream wake.
Exploring the impact of different inflow conditions on wind turbine wakes using Large-Eddy Simulations
Authors: Parinam Anand , Benard Pierre , Von Terzi Dominic , Viré Axelle
Published: June 2024

The ever-growing demand for renewable energy, driven by cost-effectiveness and minimal ecological impacts, has resulted in the deployment of larger wind turbines with rotor diameters surpassing 200 m. This underscores the importance of a thorough understanding of flow dynamics to optimize operational efficiency in diverse atmospheric inflow scenarios. Understanding the intricate impact of atmospheric conditions, including wind shear and turbulence, on wind turbine wakes is crucial for optimizing wind farm layouts and performance, influencing wake evolution, turbine loads, and power output. This research focuses on bridging the gap between idealized inflow scenarios and real-world atmospheric inflow conditions by systematically integrating linear shear, turbulence and the logarithmic wind shear profile into the uniform inflow conditions and analyzing the wake behind the IEA-15 MW wind turbine. To specifically examine inflow effects, a constant hub height wind speed was maintained through a velocity controller. The study focuses on analyzing the wake’s flow field and providing insights into its recovery process. It was found that turbulence plays a critical role in a faster wake recovery as well as increasing the power production of the turbine for sheared inflows and the wind speed selected.
CFD wind farm evaluation in complex terrain under free and wake induced flow conditions
Authors: Bretos David , Campaña-Alonso Guillén , Méndez-López Beatriz , Cantero-Nouqueret Elena
Published: June 2024

Massive deployment of wind energy is critical to achieving the renewable energy production targets. This requires the development and improvement of models and tools for the optimal exploitation of high altitude and complex terrain sites for wind energy installations. Predicting the wind resource assessment of these sites is very challenging, as is predicting the interaction of wind farms in complex terrain with neighbouring installations, which is necessary to maximise the efficiency of wind energy. To address these challenges, the use of high-fidelity Computational Fluid Dynamics (CFD) models is recommended. In this study, the wind resource at the complex terrain site of the CENER experimental wind farm (Alaiz) is evaluated using steady-state RANS CFD simulations performed with OpenFOAM v2212, taking into account the effects of terrain topography and vegetation. Furthermore, a virtual wind farm located at Alaiz is modelled with the Actuator Disk (AD) method to analyse the effect of topography on the the wake evolution.
Comparison of horizontal wind speed and direction measurements from dual-Doppler radar and profiling lidars
Authors: Vöhringer A L , Gottschall J , Hirth B D , Hung L-Y , Lundquist J K , Schneemann J , Schroeder J L , Theuer F , Kühn M
Published: June 2024

Dual-Doppler radar is a relatively new technology in the wind energy community and thus not yet studied vastly. This paper aims to compare horizontal wind speed and direction data retrieved from dual-Doppler radar and profiling lidars within the American WAKE experimeNt (AWAKEN) to investigate the influence of measurement height, wind direction and speed on the comparison. The 10-min averaged data show a better agreement of the measurements for higher altitudes, especially at faster wind speeds. For the wind direction, two sectors of larger differences in the measurements were detected: around 270° transient winds occur with a higher frequency than in other sectors. To explain the different measurement values in the wind direction sector around 90°, further studies, e.g. on the influence of atmospheric stability, are necessary.
Exploring the Power & Loads Paradigm: Tocha Farm Case Study
Authors: Lucas Frutuoso T R , Marante Pereira M , Santos Pereira R B , Madeira J F A , Cintra João
Published: June 2024

Wind energy plays a vital role in the European Union’s decarbonization and electrification efforts. The present study addresses wind farm control strategies exploring the design space of optimal solutions and understanding how these solutions vary when different objectives and meteorological scenarios are considered. The goal is to bridge the gap in existing literature by avoiding the simplification of the multi-objective optimization problem into single-objective using the weights method. This method was not chosen due to its various limitations, particularly its inability to deal with non-convex Pareto fronts. Instead, in this work, a multiobjective optimization method is adopted that overcomes these constraints and offers a set of solutions (the Pareto front) where the decision maker selects the most suitable solution. The methodology involves four main steps: flow calculation using FLORIS, aerodynamic load calculation with CCBlade, conversion of loads into damage equivalent moments (DEM), and multi-objective optimization using a direct multi-search (DMS) algorithm. By exploring various objectives, such as power and fatigue loads at different components, and different wind turbines, this study aims to explore the design space and quantify the potential improvement in terms of the defined cost-functions. The study utilizes data from Tocha Wind Farm in Portugal, that comprises five VESTAS wind turbines. Strain gauges, accelerometers, and meteorological measurements are used for data collection. Simulations under ‘greedy control’, where a turbine is affected by a wake, are compared with campaign data, considering a fixed wind speed and varying turbulence intensity. The optimization reveals Pareto-optimal strategies and the respective optimal yaw angles. Considering a wind velocity of 8 m.s
−1 and a wind direction of 308°, power may improve up to 4.6%, and the blade root DEM and tower base DEM up to 5.7% and 84%, respectively. The study highlights the impact of considering multiple objectives and supports the selection of wind farm control strategies to effectively manage critical structural components, thereby extending the lifespan of the wind farm.
Investigation of far-wake models coupled with yaw-induction control for power optimization
Authors: Heck Kirby S. , Liew Jaime , Howland Michael F.
Published: June 2024

Combined wake steering and induction control is a promising strategy for increasing collective wind farm power production over standard turbine control. However, computationally efficient models for predicting optimal control set points still need to be tested against high-fidelity simulations, particularly in regimes of high rotor thrust. In this study, large eddy simulations (LES) are used to investigate a two-turbine array using actuator disk modeling in conventionally neutral atmospheric conditions. The thrust coefficient and yaw-misalignment angle are independently prescribed to the upwind turbine in each simulation while downwind turbine operation is fixed. Analyzing the LES velocity fields shows that near-wake length decreases and wake recovery rate increases with increasing thrust. We model the wake behavior with a physics-based near-wake and induction model coupled with a Gaussian far-wake model. The near-wake model predicts the turbine thrust and power depending on the wake steering and induction control set point. The initial wake velocities predicted by the near-wake model are validated against LES data, and a calibrated far-wake model is used to estimate the power maximizing control set point and power gain. Both model-predicted and LES optimal set points exhibit increases in yaw angle and thrust coefficient for the leading turbine relative to standard control. The model-optimal set point predicts a power gain of 18.1% while the LES optimal set point results in a power gain of 20.7%. In contrast, using a tuned cosine model for the power-yaw relationship results in a set point with a lower magnitude of yaw, a thrust coefficient lower than in standard control, and predicts a power gain of 13.7%. Using the physics-based, model-predicted set points in LES results in a power within 1.5% of optimal, showing potential for joint yaw-induction control as a method for predictably increasing wind farm power output.
A simple RANS closure for wind-farms under neutral atmospheric conditions: Preliminary findings
Authors: Jigjid Kherlen , Dwight Richard , Allaerts Dries , Steiner Julia
Published: June 2024

Accurately predicting wind turbine wake effects is essential for optimizing wind-farm performance and minimizing maintenance costs. This study explores the applicability of the Sparse Regression of Turbulent Stress Anisotropy (SpaRTA) framework to develop a simple yet robust Reynolds-averaged Navier-Stokes (RANS) model for wake prediction in wind energy contexts. The framework introduces two correction terms into two-equation models, with k − ε model being utilized in the current study. One correction term resembles the residual of the Turbulent Kinetic Energy (TKE) equation, and the other corrects the deviatoric part of the Reynolds Stress Tensor (RST). The terms are calculated from high-fidelity measurement or simulation data, and symbolic regression is used to determine the model for these terms.

In this study, Large Eddy Simulation (LES) data from a single turbine is used as the training dataset, and a sample pre-selection process is employed to discover a correction model efficiently. The derived model incorporates two terms based on Pope’s basis tensors and their invariants. The expression of the obtained model shows that it functions as a modification to the constant Cµ
in the k − ε model. The model is evaluated by comparing its predicted velocity and TKE fields with the LES data used for the training. The model showed satisfactory performance in predicting both fields. Additionally, its generalizability is evaluated by testing it against a more complex six-turbine unseen case. The results indicate that the model effectively captures the velocity field and power output, but it tends to overpredict TKE, especially in the wake region.
Sensitivity of the Prediction of Wind Turbine Wakes to the Sub-Grid Scale Model
Authors: Ghobrial Mina , Stallard Tim , Schultz David M. , Ouro Pablo
Published: June 2024

In a large-eddy simulation (LES) approach, the sub-grid scale (SGS) model accounts for the contribution of eddies and their fluxes whose length scales are smaller than the filter width. In wind turbine and farm simulations, different SGS models have been adopted, but their impact on turbine performance and wake prediction remains unknown for non-neutrally stable atmospheric boundary layers. Here, large-eddy simulations of an NREL–5MW wind turbine in stable atmospheric conditions are performed with six SGS models: standard Smagorinsky, Lagrangian-Averaged Scale-Dependent Dynamic (LASDD), Wall-Adapting Local Eddy-Viscosity, Turbulent Kinetic Energy, Stability Dependent Smagorinsky, and Anisotropic Minimum-Dissipation (AMD) models. The resolved flow field and turbine loading have shown limited sensitivity to the SGS model with some deviations from the LASDD in wind speed and turbulence intensity at the turbine elevation. This limited sensitivity is owed to the adopted high-resolution grid necessary to provide an acceptable resolution for the actuator-line method. Regarding the computational costs, the LASDD model has the highest compute overhead to the LES compared to the other five SGS models. The AMD model is simple to implement and provides three-dimensional variation of the SGS eddy-viscosity without any parameter tuning, thus it has the highest potential to be used in LES of wind turbines and farms operating in stable conditions.
Turbulence coherence in wind farms: The role of turbines
Authors: Liu Yang , Stevens Richard J. A. M.
Published: June 2024

Models for wind farm power fluctuations primarily focus on the impact of atmospheric turbulence. We employ large eddy simulations (LES) to demonstrate that dynamic changes in thrust (CT
) and power (CP
) coefficient affect the coherence of power fluctuations in turbine pairs. We consider various inflow wind speeds to examine the velocity and power coherence between consecutive turbine rows under three scenarios: (I) a fully developed region where all turbines operate below rated power, (II) the front row operates above rated power while the downstream row operates below rated power, and (III) both rows operate above rated power. In scenario I, the random sweeping hypothesis turbulence model by Tobin and Chamorro, JFM 855, 1116-1129 (2018) can effectively predict the coherence between the turbines. However, in scenarios II and III, the model fails to capture the simulation results. This discrepancy arises due to the operation of above-rated turbines, with dynamically varying CT
and CP
, which have a distinctly different effect on the flow than turbines operating with fixed CT
and CP
.
Assessment of synthetic turbulence of stably stratified atmospheric boundary layers for LES
Authors: Olivares-Espinosa Hugo , Arnqvist Johan
Published: June 2024

This work studies the evolution of turbulence in a Stable Boundary Layer (SBL) in Large-Eddy Simulations (LES) when a synthetic turbulence field of velocity and temperature is used as initial condition and as well as precursor. Following common approaches found in the literature, initial fields of different characteristics are created and their evolution in the LES is evaluated in order to assess the ability of the synthetically generated turbulence to represent a snapshot of SBL turbulence. The study is carried out with two modelling cases, a forested site as well as the GABLS benchmark [4]. In both cases, the usage of a turbulent SBL as an initial condition proved advantageous to reach a faster convergence presenting an opportunity for computational savings. Yet, the very different turbulence conditions of the modelling setups produce varying results with regard to the type of velocity and temperature fluctuations. Likewise, the usage of a precursor was shown able to represent the flow in a successor LES although with varying reliability, dependent on the background turbulence and the stratification level, that suppresses velocity fluctuations and could lead to the misrepresentation of turbulence level.
Estimating Uncertainties from Dual-Doppler Radar Measurements of Onshore Wind Plants Using LES
Authors: Brown K. , Cheung L. , Develder N. , Herges T. , Hsieh A. , Blaylock M. , Yalla G. , Knaus R. , Maniaci D. , Hirth B.
Published: June 2024

Towards the ongoing work of improving the capability of flow modeling within and around wind plants, an onshore model validation benchmark campaign is underway based on a field experiment involving multiple wind plants in Oklahoma, U.S.A. Dual-Doppler radar is being leveraged to provide flowfield information for the benchmarking owing to the unparalleled capability of such radar to capture minute-by-minute horizontal wind fields over a scale of tens of kilometers. However, dual-Doppler radar exhibits sampling artifacts that must be considered during model validation, and these are due to probe-volume averaging, coarse azimuthal/elevational resolution, non-ideal stereo angles, and coarse temporal sampling. Such sources of error in radar-reconstructed flowfields can be quantified using virtual radar sampling in the high-fidelity simulation environment (i.e., large-eddy simulation (LES)) where the true velocity field is known with confidence, and this is the uncertainty quantification approach adopted in this article. We leverage a virtual radar tool designed to replicate the specific sampling strategy of the X-band dual-Doppler instrument installed in the field campaign. This tool is featured in LES of an expansive 100 km by 100 km region of Oklahoma including hundreds of wind turbines modeled as actuator disks. In agreement with the sampling principles of radar, the results show that large-scale flow structures are qualitatively well-resolved by the instrument, though more simulation time and analysis are needed to determine the accuracy of the radar’s integral lengthscale estimates. At the turbine scale, the radar struggles to capture all of the features of the turbine wakes. The process of probe-volume averaging, as well as the subsequent interpolation to a Cartesian grid, biases the reconstruction of the peak near-wake deficit by an average of 2 m/s, or around 20% of the freestream velocity. Errors in this quantity of interest, as well as one characterizing the magnitude of the free-flow wind speed around the wakes, are found to be sensitive to the radar beam-crossing angle and beam range.
Development and physiochemical assessment of graphene-bioactive glass-P(3HB-co-4HB) composite scaffold as prospect biomaterial for wound healing
Authors: Abdul Rahim Mohd Aiman Hakimi , Samsurrijal Siti Fatimah , Abdullah Amirul Al-Ashraf , Mohd Noor Siti Noor Fazliah
Published: June 2024

The clinical management of wounds presents a considerable challenge because dressing selection must prioritise the provision of appropriate barrier and the healing properties, consider patient’s compliance factors such as comfort, functionality and practicality. This study primarily aimed to develop a composite scaffold patch for potential application in wound healing. Poly(3-hydroxybutyrate-co-4-hydroxybutyrate) [P(3HB-co-4HB)] is a biopolymer that originated from bacteria. It is well-recognised owing to its distinctive mechanical and physical characteristics suitable for biomedical applications. Graphene (G) and bioactive glass (BG) are biocompatible towards humans, and enhanced properties are achievable by adding biopolymer. In this study, composite scaffolds were developed by combining P(3HB-co-4HB) at a distinct proportion of 4HB monomer reinforced with G (3.0 wt.%) and BG (2.5 wt.%) by using solvent casting, resulting in two types of composite scaffolds: P(3HB-co-25%4HB)/G/BG and P(3HB-co-37%4HB)/G/BG. A successful composite scaffold as a unified structure was achieved based on chemical assessments of organic and inorganic elements within the composites. The pure polymer displayed a smooth surface, and the BG and G addition into the composite scaffolds increased surface roughness, forming irregular pores and protuberances. The wettability and hydrophilicity of the composites significantly improved up to 40% in terms of water uptake. An increment in crystallisation temperature diminished the flexibility of the composite’s scaffolds. Evaluation of Presto Blue biocompatibility demonstrated nontoxic behaviour with a dosage of less than 25.00 mg ml−1 of composite scaffold-conditioned media. The L929 fibroblast cells displayed excellent adhesion to both types of composite scaffolds, as evidenced by the increased percentage of cell viability observed throughout 14 d of exposure. These findings demonstrate the importance of optimising each component within the composite scaffolds and their interrelation, paving the way for excellent material properties and enhancing the potential for wound healing applications.
Whey protein-loaded 3D-printed poly (lactic) acid scaffolds for wound dressing applications
Authors: Kayadurmus Hanne Meryem , Rezaei Azadeh , Ilhan Elif , Cesur Sumeyye , Sahin Ali , Gunduz Oguzhan , Kalaskar Deepak M , Ekren Nazmi
Published: June 2024

Chronic skin wounds pose a global clinical challenge, necessitating effective treatment strategies. This study explores the potential of 3D printed Poly Lactic Acid (PLA) scaffolds, enhanced with Whey Protein Concentrate (WPC) at varying concentrations (25, 35, and 50% wt), for wound healing applications. PLA’s biocompatibility, biodegradability, and thermal stability make it an ideal material for medical applications. The addition of WPC aims to mimic the skin’s extracellular matrix and enhance the bioactivity of the PLA scaffolds. Fourier Transform Infrared Spectroscopy results confirmed the successful loading of WPC into the 3D printed PLA-based scaffolds. Scanning Electron Microscopy (SEM) images revealed no significant differences in pore size between PLA/WPC scaffolds and pure PLA scaffolds. Mechanical strength tests showed similar tensile strength between pure PLA and PLA with 50% WPC scaffolds. However, scaffolds with lower WPC concentrations displayed reduced tensile strength. Notably, all PLA/WPC scaffolds exhibited increased strain at break compared to pure PLA. Swelling capacity was highest in PLA with 25% WPC, approximately 130% higher than pure PLA. Scaffolds with higher WPC concentrations also showed increased swelling and degradation rates. Drug release was found to be prolonged with increasing WPC concentration. After seven days of incubation, cell viability significantly increased in PLA with 50% WPC scaffolds compared to pure PLA scaffolds. This innovative approach could pave the way for personalized wound care strategies, offering tailored treatments and targeted drug delivery. However, further studies are needed to optimize the properties of these scaffolds and validate their effectiveness in clinical settings.
Optimizing decellularization protocols for human thyroid tissues: a step towards tissue engineering and transplantation
Authors: Karabıyık Acar Özge , Bozdağ Gülnihal , Hacıhasanoğlu Ezgi , Tuncer A Alperen , Aysan Erhan , Torun Köse Gamze
Published: June 2024

Hypothyroidism is caused by insufficient stimulation or disruption of the thyroid. However, the drawbacks of thyroid transplantation have led to the search for new treatments. Decellularization allows tissue transplants to maintain their biomimetic structures while preserving cell adhesion, proliferation, and differentiation. This study aimed to decellularize human thyroid tissues using a structure-preserving optimization strategy and present preliminary data on recellularization. Nine methods were used for physical and chemical decellularization. Quantitative and immunohistochemical analyses were performed to investigate the DNA and extracellular matrix components of the tissues. Biomechanical properties were determined by compression test, and cell viability was examined after seeding MDA-T32 papillary thyroid cancer (PTC) cells onto the decellularized tissues. Decellularized tissues exhibited a notable decrease (<50 ng mg−1 DNA, except for Groups 2 and 7) compared to the native thyroid tissue. Nonetheless, collagen and glycosaminoglycans were shown to be conserved in all decellularized tissues. Laminin and fibronectin were preserved at comparatively higher levels, and Young’s modulus was elevated when decellularization included SDS. It was observed that the strain value in Group 1 (1.63 ± 0.14 MPa) was significantly greater than that in the decellularized tissues between Groups 2–9, ranging from 0.13 ± 0.03–0.72 ± 0.29 MPa. Finally, viability assessment demonstrated that PTC cells within the recellularized tissue groups successfully attached to the 3D scaffolds and sustained metabolic activity throughout the incubation period. We successfully established a decellularization optimization for human thyroid tissues, which has potential applications in tissue engineering and transplantation research. Our next goal is to conduct recellularization using the methods utilized in Group 1 and transplant the primary thyroid follicular cell-seeded tissues into an in vivo animal model, particularly due to their remarkable 3D structural preservation and cell adhesion-promoting properties.
A multi-level network tool to trace wasted water from farm to fork and backwards
Authors: Semeria Francesco , Ridolfi Luca , Tuninetti Marta
Published: June 2024

Food loss and waste (FLW) is an issue of great public concern, due to its major impact on food security and on the social, economic and environmental resources involved in food production, trade and consumption. In this work, we put the lens on water resources, as those lost in the different stages of FLW represent about a quarter of the total freshwater resources used in food crop production. To this end, we propose the NETFLOW model (Network-based Evaluation Tool for Food LOss and Waste) as an innovative tool capable of reconstructing, for each commodity, the complex global multi-layered network linking FLW at each stage of the value chain with the corresponding wasted water resources. Food re-exports, nested supply chains, telecoupling of food markets, and different levels of food transformation are taken into account. Focusing on the emblematic case of wheat and its derived food commodities (e.g. flour, bread, pasta), we show the complexity and extent of the FLW-linked water network. For example, in 2016, more than 100 countries used their water resources (almost 3 km3) to produce wheat which was ultimately lost or wasted along the food consumption value chain in Italy, with almost half of this amount being directly attributable to the bread value chain. On the supply side, we show that about 18.3 km3 of water resources in the U.S. were lost through wheat-related FLW in 144 countries, about 40% for flour, 27% for raw wheat (mainly used for feed), and 24% for bread. The NETFLOW model proves useful in unravelling the complex links between (i) product-specific global trade networks, (ii) primary and derived products, (iii) country- and stage-dependent FLW, and (iv) country- and product-specific virtual water content.