bluuebunny/crossref_metadata_2025_split huggingface dataset:
Recommendations on setup in simulating atmospheric gravity waves under conventionally neutral boundary layer conditions
Authors: Khan Mehtab A , Watson Simon J , Allaerts Dries J N , Churchfield Matthew 
Published: June 2024

Abstract
Wind farm-induced atmospheric gravity waves have been the subject of recent research as they can impact wind farm performance. Pressure variations associated with gravity waves can contribute to the global blockage effect and wind farm wake recovery. Therefore, accurate numerical simulation of flow fields, where wind-farm-induced gravity waves may be produced, is important. Three main considerations in such simulations are the overall domain size, the use of Rayleigh damping near domain boundaries to dampen gravity waves, and advection damping at the inlet to prevent spurious oscillations. Often these considerations are treated ad hoc rather than systematically. This work aims to test and extend the systematic modelling of internal gravity waves proposed in a preliminary investigation to modelling of both internal and trapped gravity waves. The preliminary study identifies the length scales to set the domain and damping layer sizes and the time scale to configure the Rayleigh damping coefficient but under linearly stratified conditions. Large eddy simulations of flow through a wind farm canopy are performed under conventionally neutral boundary layer (CNBL) conditions to test the validity of proposed setups for CNBL conditions. Background atmospheric parameters, such as Froude number (Fr), inversion height (Hi
), and inversion layer Froude number (Fri
) control most of the atmospheric gravity wave characteristics. We validated for CBNL conditions that the effective wavelengths of the internal gravity waves are the correct length scale to configure the domain size and damping layer thickness. Likewise, the optimum damping coefficient to dampen the internal gravity waves relates to the free atmosphere’s buoyancy frequency or buoyant perturbations’ time scale. We infer that the damping coefficient in the inversion layer may relate to the inversion buoyancy frequency to effectively dampen the trapped gravity waves. Moreover, the advection damping length is linked to the horizontal wavelength of the trapped gravity waves in the inversion layer to prevent spurious waves at the inlet by retaining wave energy accumulation.
An open-source framework for the development, deployment and testing of wind farm control strategies
Authors: Sucameli C R , Campagnolo F , Petrović V , Hulsman P , Bottasso C L 
Published: June 2024

Abstract
Recent advances in wind farm control, particularly in wake steering strategies, have attracted significant interest from both academia and industry. Wake steering consists in misaligning an upstream turbine to redirect its wake, mitigating its impact on downstream turbines. Implementing these strategies on real-time systems presents challenges, especially in collaborative research projects, for example because of the handling of confidential operational data and the complexity of deploying source code on proprietary hardware. This paper introduces a MATLAB-based framework designed to facilitate the development, deployment, and testing of wake steering strategies on real-time Bachmann PLC systems. The modular architecture of the framework is designed to address common challenges in research projects, such as model deployment, data confidentiality, adaptability to runtime changes, and more in general for the facilitation of multi-partner collaborations. The framework was used to perform multiple wake steering experiments on two 3.5 MW turbines.
Ranking multi-fidelity model performances in reproducing internal and external wake impacts at neighbouring offshore wind farms
Authors: Freitas S , Rowen M , Navarro Diaz G , Erbslöh S 
Published: June 2024

Abstract
Performances of multi-fidelity numerical models in reproducing the impacts of internal and external wakes on power production are evaluated against SCADA data from two operational offshore wind farms in the North Sea. Results obtained for two engineering wake models, Jensen and Cumulative Curl (default and tuned settings), and a higher-fidelity Reynolds-averaged Navier-Stokes (RANS) setup are presented here. Tuned engineering models were configured against RANS results for an idealized wind farm layout consisting of several turbine setups. Input data for the model evaluation scenarios was obtained from a met mast located between the wind farms and binned according to atmospheric stability, wind speed and direction, and turbulence intensity. Results show that the higher fidelity of RANS is most advantageous for inflows that generate more complex internal wakes (e.g., deep array effects) and in replicating external wake impacts. The tuned setups of the engineering models, modified according to stability, outperform their default setups. Default model properties are defined in accordance with developer recommendations. One of the tuned models shows close farm-level agreements with RANS and even exceeds its performances in some of the cases of lower flow complexity.
Wind Turbine Loads in the Near Wake
Authors: Alletto Michael , Woesmann Jan , Letzel Marcus O. , Heyen Malte 
Published: June 2024

Abstract
This work is analyzing the the engineering wake models Frandsen and TNO for small inter-turbine distances. Therefore, loads generated by actuator line LES (AL-LES) wind fields will be compared with the loads generated by the mentioned engineering models. The results are checked for plausibility by comparing the current results with the available literature. Load comparisons for non-dimensional distances x/D ranging from 1.75 to 4 and for seven different wind speeds in order to consider the influence of the thrust coefficient were made. For each speed a low and a high turbulence intensity case is considered. Two latest generation turbines are investigated (one with a diameter of 138 m and one with a diameter of 175 m).Our studies reveal that the fatigue loads computed with the Frandsen and TNO model are conservative compared to the loads generated by AL-LES wind fields. The Wöhler averaged (m=10 and a sector of 120°) flap wise blade root bending moments are at least 150% higher for the TNO and Frandsen model compared to the loads generated by AL-LES wind fields for distances lower than 2.3D and C

T
values higher than 0.7. This indicates that current sector management rules applied by means of the results of the Frandsen and TNO model are too restrictive. A possible way to decrease the conservatism without posing at risk the structural integrity of the turbines is the following: The wake added turbulence intensity can be kept constant for regions in the parameter space with very high conservatism (e.g. for distances smaller than 2.3D and C

T
values higher than 0.7).
A Machine Learning Approach to Correct Turbulence Intensity measured by Floating Lidars
Authors: Rapisardi Giacomo , Araújo Da Silva Marcos Paulo , Miquel Adrià 
Published: June 2024

Abstract
In this work we introduce a supervised Machine Learning (ML) model to correct the Turbulence Intensity (TI) measured by Floating LiDAR Systems (FLS) in offshore environment. The model was developed using data from 46 EOLOS-FLS200 validation campaigns (≈ 4.6 years) carried out at three reference sites in the North Sea. It is based on Gradient Boosting Decision Tree (GBDT) and accounts for wind characteristics, atmospheric conditions, buoy motion, and wave features. Numerical analyses pronounced a consistent improvement in both coefficient of determination (R
2) and Mean Bias Error yielded by the ML-corrected TI. In addition, TI estimates in accordance with the state-of-the-art best practices were successfully obtained, even when evaluating the ML model in a site out of the training dataset, which demonstrates the model’s robustness.
Active Cluster Wake Mixing
Authors: Gutknecht Jonas , Becker Marcus , Taschner Emanuel , Stipa Sebastiano , Allaerts Dries , Viré Axelle , Van Wingerden Jan-Willem 
Published: June 2024

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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.