bluuebunny/crossref_metadata_2025_split huggingface dataset:
Critical design load case fatigue and ultimate failure simulation for a 10-m H-type vertical-axis wind turbine
Authors: Moore K R , Brownstein I D , Ross H K 
Published: June 2024

Abstract
While previous studies investigating critical vertical-axis wind turbine (VAWT) design load cases have focused on large and relatively flexible Darrieus designs, the bulk of current commercial products seeking certification fall in the relatively small, stiff, H-type configuration. Understanding the critical design load case impacts for both fatigue and ultimate failure for this size and type of VAWT is imperative for certification and to help break the cycle of historical VAWT failures. A reevaluation of each of the design load cases specified in IEC 61400-1 using the Offshore Wind ENergy Simulator (OWENS) validated aero-servo-elastic software is conducted for both fatigue and ultimate failure contributions. Several design load cases previously thought negligible may have high enough fatigue damage rates for H-VAWTs to warrant more careful consideration; these cases include parked, extreme wind shear, and direction change with gust. Additionally, full operation stop-start-stop cycles, which historically have not been a part of the standards, may contribute fatigue damage similar to other normal design load cases. In light of these potentially critical conditions, and the sizes of many of the current H-VAWT designs falling in the IEC 61400-2 small wind turbine standard, the standard may need to be expanded to enable design success of certified H-VAWT systems.
Investigating data-driven surrogates for the Ainslie wake model
Authors: Morabito Niccolò , Quaeghebeur Erik , Bliek Laurens 
Published: June 2024

Abstract
Efficient and accurate calculation of wind turbine wakes are central to the design and analysis of wind farms. We present the promising results of an investigation into machine learning techniques for creating computationally efficient surrogates of the Ainslie wake model, as a computationally accessible stepping stone to more complex models. We have compiled an extensive dataset comprising 8600 wake fields, and explored a diverse range of techniques. Among these, the most promising techniques are regression decision trees (RDTs) and Fourier-expanded multi-layer perceptrons (FEMLPs) which have proven to be very effective for image applications. Even with smaller training sets, acceptable results are achieved, offering a feasible balance between size and performance. Both RDTs and FEMLPs excel in interpolation, while FEMLPs particularly showcase robust extrapolation capabilities. Visual comparisons show that RDTs outperform FEMLPs in terms of the smoothness of the generated wake fields. All techniques create surrogates that are at least six orders of magnitude faster than the Ainslie model implementation. The investigation results in a flexible pair of turbine wake surrogate models which are extremely fast and achieve high performance with a reasonable training time. Their generic nature makes them promising candidates for creating effective surrogates for more complex wake models.
Design for Repowering of Wind Farms: An Initial Framework
Authors: Bouzolin Daniel , Settelmaier Kyle , Todd Griffith D. 
Published: June 2024

Abstract
The need for clean and cost-effective energy sources is more pertinent than ever. Wind energy positions itself as a global contender in this role, offering a cost-effective and environmentally-friendly energy option. Furthermore, the wind energy industry is already starting to see numerous wind farms reaching 20+ years of life that require either repowering or decommissioning decisions to be made. Repowering offers many potential economic and sustainable benefits; however, many operators are faced with challenging decisions regarding whether to repower and how to optimally repower. This paper aims to address these challenges by introducing a novel comprehensive framework, known as “Design for Repowering”. In Design for Repowering, wind farms of the future would be designed with planned repowering in mind. Through integration of multiple criteria, including health monitoring/sensors, digital twins, and social/environmental factors, we aim to address open questions about repowering, such as the optimal timing, strategy, and economics of repowering decisions. Furthermore, the framework is applied to several case studies, illustrating its potential for solving some of the long-term challenges expected in the future of wind energy.
Multidisciplinary Wind Farm Electrical Infrastructure Optimization
Authors: Rodrigues Rafael Valotta , Rua Juan-Andres Perez 
Published: June 2024

Abstract
During the construction stage of a wind farm, it is paramount to consider which layouts are the most efficient. Recent literature has found that optimization of the annual energy production is not necessarily driven by the same factors as other economic metrics, such as the internal rate of return. One parameter that makes this particularly true is the electrical cable length and layout, which affect both the cash flow of the project and the investments. While placing turbines far from each other is beneficial to mitigate the wake effect, the capital expenditures associated with the longer cables affects economic metrics. On the other hand, even though placing turbines close to each other reduces cable expenses, wind turbine mechanical loads are challenging to determine from wake effects. This work investigates trends between annual energy production, internal rate of return, electrical cable layout, and turbine components degradation due to mechanical loads. Results point towards corroborating recent literature, finding financial opportunities to explore tighter layouts with shorter electrical cables.
Vertical axis wind turbine wake steering by pitched struts and blades
Authors: Ribeiro André F. P. , Ferreira Carlos S. , Casalino Damiano 
Published: June 2024

Abstract
Vertical axis wind turbines (VAWTs) have been identified as a technology that, in association with wake steering, can increase power density of wind farms. In this study, we validate a free wake method for VAWT wake prediction, which leads to satisfactory results. We then use this method to simulate wake steering by means of fixed pitched blades and struts. We demonstrate that combining pitched wakes and struts can lead to very advantageous wake behavior, but only when the interactions between the tip vortices are taken into account. The possibility to inject more high momentum flow into the wake while moving the vortex system away from the next turbine could make pitched blades and struts a powerful tool for future wind farms.
Modeling of Blockage and Wake Effect: Comparison with Field data
Authors: Maheshwari Priyank , Haize Julien , Pallud Maxime 
Published: June 2024

Abstract
We apply engineering approaches for estimating the induction zone in front of a wind turbine and escalating to the global blockage at wind farm and cluster of farms scale as well accounting for wind farm wake. The methods include the vortex cylinder model and the self-similar model for blockage, and Jensen and Eddy-viscosity models for the wake estimation. To calibrate each model, Reynold Average Navier-Stokes with Actuator disc simulations are employed. Every model’s efficacy is assessed in comparison to the validation data of an operated wind farm in Scotland with more than 100 turbines of 10 MW each. We also examine the widely used process within the wind industry for transferring the application of calibrated wake and blockage models from one wind farm. According to our simulation analysis, blockage causes sideways acceleration and upstream slowdown. This also result in a gradient in the power produced by each turbine on the farm, which, if not properly accounted for, appears to be a wake model constraint. Furthermore, the response of different turbine type in another environment is not effectively predicted by the blockage and wake model, which is based on a particular turbine type and environment.
How do wind farm blockage and axial induction control interact?
Authors: Bossanyi Ervin , Bleeg James 
Published: June 2024

Abstract
Wake losses significantly reduce wind farm output, but wind farm flow control (WFFC) can substantially reduce these losses, using wake steering (yawing upstream turbines) and/or axial induction control (reducing turbine power and thrust to weaken their wakes). Previous work shows that ignoring wind farm blockage in traditional wake models represents a prediction bias of similar order to the gains achievable with WFFC. Axial induction control works by changing turbine thrust, which is also the cause of blockage; this raises the question of how the two effects interact. Induction control can more than compensate for any loss due to blockage, but here we investigate the relationship further. Induction control reduces turbine thrust coefficients to reduce wake losses, but this should also reduce blockage, suggesting that induction control might achieve higher gains in practice than predicted with blockage effects ignored. An engineering model for blockage effects was added to the wind farm code LongSim, and steady-state gains calculated for a well-known offshore wind farm, with and without blockage. The results confirm that the power gains are indeed higher if blockage is modelled. These results are corroborated by comparisons against RANS (Reynolds-Averaged Navier Stokes) simulations, in which blockage effects are implicitly modelled.
Graph-based Deep Reinforcement Learning for Wind Farm Set-Point Optimisation
Authors: Sheehan H , Poole D , Silva Filho T , Bossanyi E , Landberg L 
Published: June 2024

Abstract
Wake steering is a form of wind farm control in which upstream turbines are deliberately yawed to misalign with the free-stream wind in order to prevent their wakes from impacting turbines further downstream. This technique can give a net increase in power generated by an array of turbines compared to greedy control, but the optimisation of multiple turbine set-points under varying wind conditions can be infeasibly complex for traditional, white-box models. In this work, a novel deep reinforcement learning method combining the standard Deep Deterministic Policy Gradient algorithm with a graph representation of potential inter-turbine wake connections was trained to apply wake steering to an array of nine turbines under varying wind directions. The method demonstrated strong performance for wind directions with large potential farm power gains. A steady-state wind farm solver was used, employing a “quasi-dynamic” approach to sampling wind directions, to achieve an additional 47 MW (6.5%) power over four wind directions compared to greedy control.
An international benchmark for wind plant wakes from the American WAKE ExperimeNt (AWAKEN)
Authors: Bodini N , Abraham A , Doubrawa P , Letizia S , Thedin R , Agarwal N , Carmo B , Cheung L , Corrêa Radünz W , Gupta A , Goldberger L , Hamilton N , Herges T , Hirth B , Iungo G V , Jordan A , Kaul C , Klein P , Krishnamurthy R , Lundquist J K , Maric E , Moriarty P , Moss C , Newsom R , Pichugina Y , Puccioni M , Quon E , Roy S , Rosencrans D , Sanchez Gomez M , Scott R , Shams Solari M , Taylor T J , Wharton S 
Published: June 2024

Abstract
This article introduces the first benchmark study within the International Energy Agency Wind Task 57 framework, focusing on wind plant wakes. Leveraging data from the American WAKE ExperimeNt (AWAKEN), the benchmark aims to assess the accuracy of simulation tools in modeling wind plant wakes and their impact on the downstream flow under diverse inflow conditions. The AWAKEN field campaign, conducted in Oklahoma from 2022 to 2024, provides unprecedented observations of wind plant-atmosphere interactions, thus offering a large dataset to validate numerical models of different complexity. The benchmark will include three phases—code calibration, blind comparison, and iteration—allowing participants to refine their numerical models based on the feedback from the benchmark team. This article describes the benchmark case study selected from observations providing details on atmospheric conditions, wake evidence, and wind turbine operation. The benchmark’s structure and timeline, along with the expected publication of results, are discussed as well. This collaborative effort aims to enhance the accuracy of wind plant wake simulations, thus contributing to the improvement of wind energy production estimates.
Land-based wind plant wake characterization using dual-Doppler radar measurements at AWAKEN
Authors: Abraham Aliza , Hamilton Nicholas , Bodini Nicola , Hirth Brian , Schroeder John , Letizia Stefano , Krishnamurthy Raghavendra , Newsom Rob , Moriarty Patrick 
Published: June 2024

Abstract
Wind plant wakes have been shown to persist for tens of kilometers downstream in offshore environments, reducing the power output of neighboring plants, but their behavior on land remains relatively unexplored through observation. This study capitalizes on the unique and extensive field data collected for the American WAKE ExperimeNt (AWAKEN) project underway in northern Oklahoma. X-band dual-Doppler radars deployed at this site measure wind speed and direction at 25-m and 2-min resolution within a 30-km range, capturing the interactions between three neighboring wind plants. These measurements show that the wake of one wind plant extends at least 15 km downstream under easterly wind and stable atmospheric conditions. Though the wake wind speed increases within the first 10 km, it plateaus at 90% of the freestream wind speed. The spanwise velocity distribution within the wake initially shows the clear signature of the wind plant layout, which is smoothed as it propagates downstream, indicating spanwise momentum transfer is a key mechanism in wind plant wake development and recovery. These findings have important implications for wind plant siting decisions and resource assessments, and provide insights into atmospheric interactions at the wind plant scale.
LES on wind turbines by comparison of Vortex Particle Method and Finite Volume Method codes
Authors: Roperch M , Mulakaloori V H C , Bénard P , Pinon G 
Published: June 2024

Abstract
The aim of this paper is to compare two different computational methods that analyse the flow around wind turbine using Large-Eddy-Simulations (LES). The first method uses a three-dimensional unsteady Lagrangian Vortex Particle method (VP) associated to a lifting-line (LL) approach providing radial loads, integrated thrust and power coefficients, circulations and angle of attack across the turbine blades. The second method solves the incompressible Navier-Stokes equations with the classical Finite Volume (FV) method coupled to the Actuator Line (AL) method to model the rotor blades. Both methods are compared by means of a benchmark consisting in a single full-scale NREL5MW wind turbine and the results are thus compared to Martínez-Tossas et al (2018). The comparisons involve loads, angle of attack and velocity along the blade. Wakes downstream of the turbine are analysed via the evolution of flow fields as mean velocity and vorticity. Results are found to be in good agreement with the verification case. A comparison is also performed on the evaluation of the numerical cost, precision and efficiency of both computational methods.
Wake Effects in Lower Carbon Future Scenarios
Authors: Lundquist Julie K. , Rosencrans David J. , Roberts Owen , Lopez Anthony , Mai Trieu 
Published: June 2024

Abstract
In August 2022, the U.S. Congress passed the Inflation Reduction Act (IRA), which intended to accelerate U.S. decarbonization, clean energy manufacturing, and deployment of new power and end-use technologies. The National Renewable Energy Laboratory has examined possible scenarios for growth by 2050 resulting from the IRA and other emissions reduction drivers and defined several possible scenarios for large-scale wind deployment. These scenarios incorporate large clusters of turbines operating as wind farms grouped around existing or likely transmission lines which will result in wind farm wakes. Using a numerical weather prediction (NWP) model, we assess these wake effects in a domain in the U. S. Southern Great Plains for a representative year with four scenarios in order to validate the simulations, estimate the internal wake impact, and quantify the cluster wake effect. Herein, we present a validation of the ”no wind farm” scenario and quantify the internal waking effect for the ”ONE” wind farm scenario. Future work will use the “MID” scenario (more than 8000 turbines) and the “HI” scenario (more than 16,000 turbines) to quantify the effect of cluster wakes or inter-farm wakes on power production.
Measurements and modelling of the wind speed profile in the induction zone of an offshore wind turbine
Authors: Cleve Jochen 
Published: June 2024

Abstract
Large wind turbine rotors require the measurement of the wind speed profile across the whole rotor for accurate performance and load assessments. Acquiring these measurements close to the rotor - in the induction zone - has the advantage of high correlation between the wind at the measurement location and the wind that acts on the rotor. In this paper measurements of the wind speed field upstream of a multi-megawatt wind turbine are presented and compared with a simple model of the deceleration of wind speeds in the induction zone. The measurements are taken at several distances in front of the rotor and include the full shear profile across the rotor, which is incorporated into the model by scaling the radial induction field with a free stream shear profile. The model captures the observations very accurately if a mirror turbine is included to model the effect of the ground plane. This model validation provides further evidence of the feasibility to conduct power curve verifications with measurements in the induction zone.
Further improvements to the double-Gaussian wake model
Authors: Zengler C P , Braunbehrens R , Tamaro S 
Published: June 2024

Abstract
In onshore wind farms, the turbine-to-turbine distance can be in the order of three diameters or less. In these circumstances, traditional wake models, developed for the far wake region, lose accuracy. The double-Gaussian wake model is an approach to extend algebraic wake modelling to the near wake region, where the wake is not yet self-similar. In this work, the double-Gaussian wake model is advanced by performing large eddy simulations of a reference wind turbine and a scaled wind turbine model to investigate how the thrust coefficient and the turbulence intensity influence the near wake and wake recovery. Results show that in the near wake the maximum velocity deficits move towards the outer part of the rotor with an increasing thrust coefficient. Thus, a thrust coefficient dependent position of the double-Gaussian peaks is proposed. In addition, a wake expansion function including turbulence intensity and thrust coefficient is tuned. The new model proves to be capable of predicting the wake of different turbine models under various ambient conditions and operational states.
Profit-optimal data-driven operation of a hybrid power plant participating in energy markets
Authors: Anand A , Petzschmann J , Strecker K , Braunbehrens R , Kaifel A , Bottasso C L 
Published: June 2024

Abstract
An energy management system (EMS) is formulated for a hybrid power plant (HPP), consisting of a wind power plant and battery storage plant, participating in bidding stages in the German energy market. The EMS utilizes supervisory control and data acquisition (SCADA) measurements from the site to improve power forecast from the wind power plant. First, the measurement data are used together with numerical weather prediction data to accurately forecast local wind conditions. Second, the measurement data are used to adapt a baseline engineering wake model that gives the total wind power generation for a given input wind condition. The EMS also uses an online cyclic damage minimization approach to accurately balance the battery damage cost against the revenue obtained by market bidding. An HPP controller is formulated to ensure proper tracking of optimal set-points. When compared with standard formulations, the proposed approach shows an accurate estimation and balancing of revenue and costs and a significant reduction in the power deviation penalty, which leads to significantly higher overall profit.
Effects of wind turbine rotor tilt on large-scale wind farms
Authors: Kasper Jens H. , Stevens Richard J.A.M. 
Published: June 2024

Abstract
Recent studies have explored the use of rotor tilt adjustments to reduce wake losses in wind farms. While downward wake deflection in aligned wind farms has shown promise for significant power gains, the impact of wind farm layout on the effectiveness of tilt strategies is not yet fully understood. Additionally, the effect on downstream farms remains unclear. Our large eddy simulations reveal that a rotor tilt of 20 degrees significantly reduces wake losses in aligned wind farms. For wind farms with 8 turbine rows, we observe an overall increase in wind farm productivity of up to 11%. However, tilting the rotors may decrease power production in staggered wind farms, where wake losses are inherently lower due to the increased spacing between turbines. Our findings also suggest that a downstream wind farm might benefit from an upstream farm implementing rotor tilt, although this advantage is primarily observed in the first row of the downstream farm.
Gust-detection from velocity azimuth display Doppler wind lidar profiling at the WiValdi research park.
Authors: Wildmann N , Thayer J D , Detring C , Päschke E 
Published: June 2024

Abstract
This study presents a new retrieval for gusts from Doppler wind lidar (DWL) velocity azimuth display (VAD) scans. The scanning mode which is presented allows for retrieval of mean wind speed, vertical wind speed, turbulence kinetic energy and peak gust speed with a single strategy. It is validated against sonic anemometer measurements at 90 m above ground and a reference DWL gust mode with faster scanning speed at the boundary-layer field site Falkenberg of the DWD. The new algorithm is then run on a multi-year dataset to obtain statistics of gusts at the WiValdi research park. It enables analyses not only at hub height, but also up to 500 m aloft with a reasonable availability above 60%. A case study of a convective cold pool shows the potential of the method to detect and analyze the vertical and horizontal structure of gusts with the proposed method. It highlights the importance of measurements throughout the boundary layer to understand the related physical processes to wind ramps and gusts.