bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluation of turbulence characteristics in WRF simulations at WiValdi wind park
Authors: Kilroy Gerard , Englberger Antonia , Wrba Linus , Bührend Lukas , Wildmann Norman
Published: June 2024

In this work we evaluate WRF-LES simulations at the WiValdi wind park at Krummendeich, North Germany. To accurately resolve fine-scale turbulence, we employ a high-resolution nested innermost grid with 5 m horizontal grid spacing. The main aim is to accurately reproduce realistic turbulent characteristics observed in neutral and stable atmospheric boundary layers. The so-called cell-perturbation method to accelerate the development of fine-scale three-dimensional turbulence is tested, and results are compared to in-situ observations and to another highly idealized numerical model running in LES mode.

While WRF without additional modifications is capable of reproducing the mean wind fields at the WiValdi wind park, it is unable to reproduce the turbulent characteristics observed. With the cell-perturbation method included, results are significantly improved, with turbulent characteristics much closer to observations.
Examining relative impacts of atmospheric and oceanic factors on offshore wind farms
Authors: Williams H H , Aiyer A K , Deike L , Mueller M E
Published: June 2024

Accurate understanding and prediction of how ocean waves affect offshore wind farms are critical to their siting, design, and operation. This study presents a computational framework for simulating finite offshore wind farms using Large Eddy Simulation (LES) and a Dynamic Wave Spectrum Model (Dyn-WaSp). Implementation of the Dyn-WaSp with and without a correction for swell modes is compared to a static roughness (wave phase-averaged) model, which has a similar computational cost. Impacts of the different wave models on the wind’s mean velocity and turbulent kinetic energy profiles in the finite offshore wind farm are examined, and ideal available power at hub height is compared. The dynamic wave spectrum model is shown to predict lower mean velocities in comparison to the phase-averaged approach and predicts higher shear and turbulent kinetic energy, suggesting that loading on turbines is greater than would be estimated by a static roughness model.
Surge motion-induced dynamic inflow effects in floating offshore wind turbines: A State Prediction Model
Authors: Meng Qingshen , Yu Wei
Published: June 2024

The impact of surge motion on aerodynamic unsteadiness in modern floating offshore wind turbines (FOWT) is a well-recognized phenomenon. When coupled with advanced controllers integrated into these turbines, it can lead to fluctuations in power output. This paper introduces a state-space model that incorporates dynamic inflow effects resulting from surge motion and a PID pitch controller. Additionally, an observation equation is formulated to predict the system power output. Through time series validations, the proposed state-space model demonstrates its ability to accurately capture power responses influenced by surge motions. The developed model serves as a valuable tool for the comprehensive analysis of FOWT, allowing for the exploration of the intricate interplay between unsteady aerodynamics, advanced control mechanisms, and power output.
Applicability of a Simplified Model of a 15MW Wind Turbine for a Mooring Fatigue Study
Authors: Pergler P. , Potier G. , Barrier P. , Le Guennec S. , Capaldo M. , Féron M.
Published: June 2024

Mooring system of floating wind turbine design, as conditioned by fatigue analysis, requires time-consuming simulations. But to provide relevant solutions for the multiple coming tenders, efficient methodologies need to be developed to design quickly optimal floating platform mooring for specific metocean data and project constraints. This paper presents a comparison between a mooring fatigue assessment calculated with two standard detailed modelling of a 15MW wind turbine and a simplified Drag and Lift Model (DLM) based on global coefficients at hub often used in floating offshore wind preliminary analysis to carry out extreme analysis. The present contribution is here focused on the proper assessment of a quantitative error introduced by the simplified turbine model in the mooring fatigue assessment, and the evaluation of the missing contributions such as 3P excitation or low frequency induced by turbine control. Two different control approaches are assessed here to capture a range of coupled behaviour which have been observed on project. It has been shown that the DLM approach is accurate to carry out analysis under extreme conditions, but also gives relevant fatigue results for the most fatiguing lines. In general, the order of magnitude is consistent even for low damage. All the calculations have been made using DeepLines WindTM software.
CFD simulation of a multi-rotor system using diffuser augmented wind turbines by lattice Boltzmann method
Authors: Watanabe Seiya , Yoshikawa Masaki , Hu Changhong
Published: June 2024

A diffuser-augmented wind turbine (DAWT) achieves greater power generation efficiency by increasing wind speed through the diffuser. Nevertheless, scaling up this technology is difficult because of the considerable amount of wind drag on the diffusers. To overcome this difficulty, a multi-rotor system with two or more wind turbines on the same structure is one approach to increasing wind turbine power output. This research proposes a computational fluid dynamics (CFD) method to evaluate the hydrodynamic performance of a large-scale multi-rotor system of DAWTs. Compared to conventional wind turbines, CFD simulations of DAWTs necessitate higher computational costs because of the need of high-resolution meshes for the diffuser. Furthermore, the computational cost of a multi-rotor system increases with the number of rotors. To address the issue of high computational cost, we use the Lattice Boltzmann Method (LBM), which is well suited to large-scale CFD simulations. A wind turbine is modeled as an actuator line model and a diffuser as a wall boundary. An adaptive mesh refinement approach generates higher resolution meshes near the rotor and diffuser. LBM simulations were conducted for a single DAWT and a multi-rotor system with five DAWTs. The LBM results of the wake velocity and pressure distributions were in agreement with those obtained from wind tunnel experiments and general CFD methods in earlier studies. To investigate the diffuser gap effects, we simulated five DAWTs with diffuser gaps of 5%–25% of the diffuser diameter. The power gain of each DAWT was assessed. Great performance improvements were found with diffuser gaps of 20% and 25% of the diffuser diameter. On average, the five DAWTs achieved a power gain of more than 10%. These findings confirmed the accurate evaluation capability of the proposed CFD method for hydrodynamic characteristics of multi-rotor systems using DAWTs.
Impact of rotational direction on wake replenishment mechanisms of counter-rotating paired vertical-axis wind turbines
Authors: Talamalek Ayoub , Runacres Mark C. , De Troyer Tim
Published: June 2024

Recent studies have shown that the placement of paired vertical-axis wind turbines (VAWTs) in close proximity is a promising approach to design efficient VAWT farm layouts, mainly due to the increased power output. This study aims to experimentally investigate the impact of the rotational direction of paired counter-rotating VAWTs on their wake characteristics and replenishment mechanisms through a quantitative analysis using the momentum balance equation. The results of this study enhance our understanding of the effect of rotational direction on wake dynamics of counter-rotating paired VAWTs and offer valuable insights for optimising the design of VAWT farm configurations.
Lessons learned from 10 years of wind tunnel tests on small wind turbines designed by students
Authors: Schepers J.G. , Adema N.C. , Lipian M. , Kulak M. , Shahid A. , Best A. , Bendre T. , Gallicchio I. , Elsabbagh A. , Mostafa A. , Kim T. , Mikkelsen R. , Gaunaa M. , Teuwen J.J.E. , Rudolf R.T. , Wood D. , Holierhoek J.G.
Published: June 2024

This article discusses results from an international contest, open for university student teams (bachelor and master), involving the design, construction, and testing of small wind turbines in a large wind tunnel. The wind tunnel has an outlet of 2.85 x 2.85 m allowing a maximum rotor swept area of 2 m2 without significant tunnel effects. Both horizontal and vertical axis wind turbines are part of the competition. The turbines are evaluated by an external jury of industry experts based on criteria such as Annual Energy Production, cut-in wind speed, innovations, design, and sustainability. Although the contest has been initiated in 2013 with an educational focus, it has also evolved into a valuable database for scientific purposes by providing a decade worth of performance measurements for roughly 9-10 various turbine concepts each year. The collected data may serve as a unique validation resource for assessing the accuracy of design codes in modelling diverse turbine concepts thanks to detailed design reports with model descriptions accompanying each turbine (such turbine descriptions are often considered confidential for field measurements). The paper aims to explore the scientific value of this database by comparing calculations with measurements, offering explanations where possible, and reporting intriguing findings on unconventional concepts’ performance. Even though not all observations could be explained fully they provide food for thought. Recommendations are provided for both students to enhance their designs and for contest organizers to elevate the scientific value of the measurements in future contests.
Enhancing Power Output of Ducted Wind Turbines through Flow Control
Authors: Akhter M Z , Shaaban A , Marini A
Published: June 2024

This study focuses on the performance enhancement of a ducted small-scale National Renewable Energy Laboratory (NREL) Phase VI wind turbine, utilizing a Wind Lens diffuser. The investigation is conducted at the critical cut-in wind speed of 5 m/s. The research evaluates the integration of passive flow control devices, including Vortex Generators, Microtab, and Slot, strategically positioned across the Wind Lens to augment the mass flow through the rotor. The results indicate significant amplifications in the turbine output of up to 127%, attributable to airflow manipulation across the diffuser, resulting in increased torque and power output. The study highlights the effectiveness of employed flow control devices in managing turbulence and/or flow separation, thereby enhancing aerodynamics, particularly under low wind conditions. A comprehensive analysis of various parameters such as pressure and flow fields, turbulence, and other relevant metrics is conducted to ascertain their collective influence on rotor aerodynamics. The results demonstrate the potential of these passive flow control devices in advancing small-scale wind turbine technology, especially in regions with low wind potential. Moreover, the design simplicity and cost-effectiveness of these passive flow control devices suggest wider applicability in the renewable energy sector, contributing to the reduction of carbon-intensive energy reliance.
Investigation of the effect of free-stream turbulence on paired vertical-axis wind turbines using wind tunnel testing and an actuator-line model
Authors: Talamalek Ayoub , Damiola Luca , Runacres Mark C. , De Troyer Tim
Published: June 2024

The aerodynamic interaction of vertical-axis wind turbines (VAWTs) in paired configurations can be advantageous in wind farms. However, these turbines operate in the atmospheric boundary layer which is characterised by high turbulence and may also face high-turbulence levels associated with downstream wakes. Therefore, the main goal of this study is to explore the impact of turbulence intensity on the efficiency of paired VAWTs, employing a combination of wind tunnel experiments and an actuator-line model (ALM) integrated in a URANS-based OpenFOAM solver. The present ALM employs aerodynamic coefficients derived from experimental dynamic measurements conducted on a pitching aerofoil. The wind tunnel tests suggest that paired VAWTs operating in turbulent inflow can experience advantages arising from both the mutual aerodynamic interaction between them and the effect of turbulence on the aerodynamic conditions on their aerofoils. Additionally, the ALM sheds light on the mechanisms that contribute to the enhanced power output of isolated and paired VAWTs in turbulent inflow conditions.
Sensitivity analysis of parameters impacting the performance of an energy ship using airborne wind energy
Authors: Frommer Nicole , Cheng Po Wen
Published: June 2024

This study assesses the impact of different model parameters on the power performance of energy ship systems using point-mass models, focusing on two operational modes. The first mode involves a kite operating in a pumping mode with adjustable tether lengths, aided by additional propellers for ship propulsion. It utilizes a quasi-steady kite model coupled with ship motion’s drag force and velocity triangles. The second mode features a kite pulling the ship, while underwater hydraulic turbines harness energy from ship velocity. Derived from a sail-based model, calculations deploy the force balance equation in line with ship motion, considering the drag forces of the ship and hydraulic turbines, alongside the propulsive force resulting from the kite’s interaction with the ship. The investigated parameters influencing the power performance include kite surface, ship length, wind speed, the angle between the ship’s motion direction and wind direction, and, for the pumping mode, ship speed. The power production of the propulsion mode is generally lower, with differences of at least 72%, depending on the combination of considered parameters.
Design, Analysis, and Wind Tunnel Evaluation of Novel Fabric-Covered Rotor Blades in Wind Energy Generation
Authors: Jelili Fatma , Beyer Michael , Ritschel Uwe
Published: June 2024

This paper investigates the performance of a novel fabric-covered rotor blade. The study aims to address the need for cost-effective wind turbine blades by exploring the potential of textile-based materials. The research includes a comprehensive wind tunnel experiment to evaluate the aerodynamic response of the fabric-covered blade, compared to a traditional hard-shell blade. The experimental data are systematically processed and corrected for wind tunnel effects, providing valuable insights into the aerodynamic behavior of the novel blade. The results show that the fabric-covered blade, constructed from PTFE-coated fiberglass fabric, exhibits promising aerodynamic characteristics, with potential applications in reducing manufacturing expenses and enhancing power generation. The study concludes by proposing a novel control strategy leveraging the natural deformation of blades at high wind speeds, suggesting potential applications in limiting power output at high wind speeds. Overall, these findings contribute to the ongoing efforts in developing innovative and cost-efficient solutions for wind energy generation.
Impact of Blade Pitch Actuation System on Wind Turbine Cost and Energy Production
Authors: Pusch Manuel , Phadnis Mandar , Jeong Michael , Qin Chao , Loth Eric , Pao Lucy
Published: June 2024

To minimize the levelized cost of energy (LCOE) of wind turbines, advanced co-design strategies are required that also consider the contribution of active blade pitch control to overall energy production and wind turbine cost. Thereby, the demanded closed-loop performance drives the requirements on the blade pitch actuation system, which needs to be carefully balanced. To enable this, an extended LCOE measure is developed in this paper using stochastic estimates for quantifying pitch actuation cost in terms of pitch power and closed-loop performance in terms of net energy production. Additionally, the impact of blade pitch deflections on structural loads and hence cost is evaluated considering both collective and individual pitch control. The interdependencies between the different design objectives are revealed in a case study carried out on a 25MW wind turbine, demonstrating the guidance for engineers toward cost-effective and efficient wind turbine designs.
Conceptual Design of Offshore Jacket Substructures Using Machine Learning
Authors: Qian Han , Bartels Jan-Hauke , Marx Steffen
Published: June 2024

The offshore wind sector is mature and has led to standardized design methods for offshore substructures. The conceptual design phase is critical for efficiency and cost-effectiveness and forms the basis for further design iterations. As turbine capacity increases, so does the complexity of offshore substructures, making design more challenging. However, the design process still relies on the expertise of the design engineers. These engineers rely heavily on their experience and intuition when designing, which can lead to biases due to limited information. To address this problem, Machine Learning (ML) techniques offer a promising way to improve the accuracy and efficiency of the conceptual design of offshore substructures. The current study is limited to the conceptual design of jacket substructures and was conducted on a self-developed global dataset of real jackets. The ML-based approach proposed in this study is capable of learning from existing data, recognizing intricate relationships between design variables, and potentially providing more accurate estimates for the initial conceptual design of offshore jacket substructures.
Towards a general tool chain integration platform for multi-disciplinary analysis and optimization in wind energy
Authors: Feng Ju , Sørensen Jens Nørkær
Published: June 2024

To enable easier uptake and flexible usage for the wind energy community, a general tool chain integration platform for multi-disciplinary analysis and optimization, TopDesign, is proposed and developed. This work describes its concept and the initial implementation. The platform is written in Python and provided as an open source framework. The design of this platform puts emphasis on flexibility, usability and extensibility. General model classes with standard interfaces, which can wrap custom tools/models in different formats based on different programming languages, will be provided together with examples that are easy to understand and modify. Coupling tools/models into a system thus becomes an easy task of connecting models by inputs and outputs and defining workflow with a directed graph. To demonstrate the usage of the proposed platform, we implement a wind farm evaluation system by coupling the PyWake model, the FLORIS model and self-written constraint models in the platform and apply it in solving wind farm layout optimization problems with two algorithms, as implemented in an in-house optimization Python library. A case study for a wind farm composed of 9 turbines shows the potential of the proposed platform and methodology.
GNN-based surrogate modeling for collection systems costs
Authors: Souza De Alencar M , Göçmen T , Cutululis N A
Published: June 2024

There are no known polynomial-time algorithms to perform the cable layout optimization (CLO) for the electrical network within a wind power plant (WPP). This means the computational cost for solving the CLO problem grows exponentially with plant size, which often postpones its solution to until after most design decisions are made, thus forgoing some trade-offs that would be beneficial to the plant’s goal. This work presents a method to obtain a fast estimate of the CLO that can be performed at each iteration of the broader optimization framework. The proposed surrogate model comprises of a graph neural network (GNN) regression model, as this architecture resembles the graph nature of the CLO problem. The GNN is trained with a dataset of procedurally generated site instances that are optimized by costly solving an integer linear programming model. While the inference time for GNNs is constant, the features calculation proposed has time complexity O(N log N) (where N is the number of wind turbines). This still means a major speed up for problems of non-trivial size when compared to exact CLO. A simpler feed-forward neural network (FNN) was trained on the same dataset and used as baseline. Both GNN and FNN achieved r
2 scores of 0.997 for the regression on unseen data of actual WPP, with standard deviations of the relative errors of 1.59% for the FNN and 1.66% for the GNN. Although the GNN did not improve on the performance of the FNN, the latter is an original contribution to the state of the art and an useful tool for the integrated optimization of WPP. This work looked only into a sliver of what is possible with GNNs, leaving ample space for improvements in applying that architecture to the CLO problem.
Dynamic interaction of inflow and rotor time scales and impact on single turbine wake recovery
Authors: Andersen S J , Hodgson E L , Aa Madsen M H
Published: June 2024

The entrainment and recovery of wind turbine wakes are highly dependent on atmospheric inflow conditions, which has typically been quantified through the turbulent intensity. However, recent studies have shown that the integral time scales of the inflow has significant impact on the wake recovery. Concurrently, increased power production can also be achieved through intentionally introducing beneficial time scales by altering the control of the individual wind turbines. This study studies the combined impact of the dynamic interaction between dominant inflow and rotor time scales. The results show increased power production of a downstream wind turbine of more than 50% for the largest thrust coefficients and tip-speed ratios (TSR). However, the peak power gain occurs at different downstream positions indicating that combinations of inflow time scales and TSR = 6 result in faster near wake breakdown compared to the same inflow time scales combined with higher thrust coefficient of TSR = 8.
A two-step topology and layout wind farm optimization approach
Authors: Pollini Nicolò
Published: June 2024

A novel two-step approach is presented to optimize the placement of wind turbines within a wind farm. The goal is to maximize the annual energy production, while the topology and layout of the wind turbines are optimized in sequence with a two-step procedure using gradient-based algorithms. In particular, in the first step the topology of the wind farm is optimized. A grid of potential wind turbine locations is defined, and continuous density variables ranging from zero to one are assigned to each location. The variables indicate the presence or absence of a wind turbine. Throughout the topology optimization process, we penalize the intermediate values of these variables, implicitly pushing the algorithm towards crisp 0-1 final layouts. Constraints are imposed on the minimum and maximum number of wind turbines and the spacing between them. Subsequently, in the second step, we refine the wind farm layout by optimizing the coordinates (x, y) of the wind turbines, which are initialized based on the optimal topology obtained in the first step. Numerical findings demonstrate the capability of the proposed approach to identify non-intuitive optimized wind farm layouts, with reasonable computational resources and time.
Resource Assessment for Distributed Wind Energy: An Evaluation of Best-Practice Methods in the Continental US
Authors: Phillips Caleb , Duplyakin Dmitry , Sheridan Lindsay , Ruzekowicz Jenna , Nelson Matthew , Fytanidis Dimitrios , Linn Rod , Kotamarthi Rao , Tinnesand Heidi
Published: June 2024

Current wind resources within the United States (US) indicate a potential to profitably install nearly 1,400 gigawatts of distributed wind (DW) capacity. This amount is equivalent to over half of the United States’ current energy demand from electricity, making it enough to power millions of homes and businesses and replace countless fossil fuel-based generating plants. Despite the potential growth of DW in the US, deployments are presently hindered by a lack of confidence in resource estimation methods. One potential challenge is that smaller-scale turbines, with hub heights of 40 meters or less, are disproportionately impacted by obstacles such as buildings and vegetation. These obstacles may produce complex wake effects, best modeled with high-fidelity complex fluid dynamics (CFD) models that are too computationally expensive to use for routine siting and resource assessment. Thus, installers today make use of heuristics and simple equations to approximate the impact of obstacles while also leveraging long-term resource data from commercial or publicly available atmospheric models. This study evaluates these historical and commonly used methods alongside new lower-order obstacle models produced from CFD simulations and measurement-based bias correction. The preliminary results from this study show the importance of taking care in the choice and application of mesoscale atmospheric models and the significant value of bias correction using measurements from nearby meteorological towers. Detailed obstacle modeling provides only modest additional gains in performance and, in some cases, can add error, especially at sites where turbines have already been located to avoid obvious impact from upwind obstacles. These findings reinforce the importance of collecting in situ measurements and suggest that obstacle models may be better applied in practice to automated or computer-aided siting, rather than in economic wind resource assessments.
Uncertainty Quantification for an Automatised RANS-Based Wind Resource Assessment Approach
Authors: Remmler Sebastian , Langner Judith , Letzel Marcus O.
Published: June 2024

In order to assess the model uncertainty of our RANS-based tool chain for wind-resource assessment “E-Wind”, we have simulated a large number of real wind farm projects with multiple measurement locations. Using one measurement location as reference and all others as target position, we systematically evaluated and analysed the horizontal extrapolation error for the annual mean wind speed introduced by the RANS method. Similar to previous studies, we found the model error to be strongly correlated with the simulated speed-up factor between two locations. We derived a method for site-specific prediction of the model uncertainty based on terrain complexity, simulated speed-up and distance between the measurement location and the turbine.
Assessing canopy models across forest edges on flat terrain
Authors: Monteiro J R , Batista V T P , Palma J M L M
Published: June 2024

Computational modelling of atmospheric flows in forested areas is crucial for wind resource assessment, wind farm design and turbine siting, enabling the identification of low wind speed and high turbulence regions. However, when setting up a RANS simulation in a forested area, the question arises: what is the most appropriate canopy model? In this study, employing VENTOS-2D (RANS with k-ε turbulence model), we identified the most suitable of seven canopy models to simulate the mean flow characteristics (wind speed) and second-order flow statistics (turbulent kinetic energy and shear stress) of the flow over a forest edge at the Island of Falster, by comparing against anemometer measurements and LES results. All models exhibited similar profiles for the mean wind speed, with a normalised RMSE of approximately 0.300. Regarding turbulent kinetic energy, the Lopes model outperformed the others, achieving an RMSE of 0.002. Lastly, for the Reynolds shear stress, Liu and Svensson’s models showed the lowest RMSE values (1.756 and 1.609), while others were over 4× larger (RMSE > 7). In summary, the performance of each model varies with the variable in focus, which is related to the model’s derivation method. However, considering all three analysed variables, Liu emerged as the most effective.
Power prediction using high-resolution SCADA data with a farm-wide deep neural network approach
Authors: Daenens Simon , Vervlimmeren Ivo , Verstraeten Timothy , Daems Pieter-Jan , Nowé Ann , Helsen Jan
Published: June 2024

Accurate loss estimation methods with a high level of temporal granularity are necessary to enable the implementation of efficient and adaptable control strategies for wind farms. Predictive models for the power of wind turbines within a wind farm are investigated using high-resolution SCADA data and deep learning methodologies. Traditional physical models offer detailed insights but are computationally expensive. Statistical models face limitations in handling wind energy variability. In this study, deep learning models are explored to capture spatial and temporal dynamics, with four models developed: Multi-Layer Perceptron (MLP), Convolutional Neural Network (CNN), Long Short-Term Memory network (LSTM), and a hybrid CNN-LSTM model. SCADA data from an offshore wind farm is preprocessed, anomalies removed, and annotated based on operational regions. The models are trained, validated, and tested, demonstrating improved accuracy over baseline methods. The hybrid model, incorporating spatial and temporal information, yields the highest predictive performance, showcasing the significance of these dimensions in wind power prediction.
Analytical Wake Modeling in Atmospheric Boundary Layers: Accounting for Wind Veer and Thermal Stratification
Authors: Narasimhan Ghanesh , Gayme Dennice F. , Meneveau Charles
Published: June 2024

Reliable characterization of wind turbine wakes in the presence of Atmospheric Boundary Layer (ABL) flows is crucial to accurately predict wind farm performance. Wind veering in the ABL shears the wake in the lateral direction, and wind veer strength depends on the thermal stability of the ABL. Analytical wake modeling approaches must capture these ABL effects to ensure correct prediction of the wake structure under varied atmospheric conditions. To this end, a new physics-based analytical wake model is developed in this study that is capable of predicting the shape of wakes influenced by wind veer and thermal stratification effects. This model combines a novel ABL wind field model with the Gaussian wake model. The new ABL wind model is capable of predicting both the streamwise and spanwise velocity components in conventionally neutral (CNBL) and stable (SBL) ABL flows. The analytical expressions for both of these horizontal velocity components adhere to Monin-Obukhov Similarity Theory (MOST) in the surface layer, while capturing wind veering in the outer layer of the ABL. Incorporating this ABL model with the Gaussian wake model predicts laterally deflected wake shapes in a fully predictive and self-consistent fashion for a wide range of atmospheric conditions. The results also demonstrate that the enhanced wake model gives improved predictions relative to Large Eddy Simulations of power losses due to wake interactions under strongly stably stratified atmospheric conditions, where wind veer effects are dominant.
Optimizing Wind Farm Efficiency through Active Yaw Control: A Neural Network-Aided Game Theory Approach
Authors: Abedi H , Sarkar S , Wickström A
Published: June 2024

This research investigates the potential of a game-theoretic-based Active Yaw Control (AYC) strategy to enhance power generation in wind farms. The proposed AYC strategy in this study replaces traditional look-up tables with a trained Artificial Neural Network (ANN) that determines the optimal yaw misalignment for turbines under time-varying atmospheric conditions. The study examines a hypothetical 3x2 rectangular arrangement of NREL 5-MW wind turbines. The FAST.Farm simulation tool, utilizing the dynamic wake meandering (DWM) model, is employed to assess both the power performance and structural load on the wind turbines. When tested with two different inflow directions and ambient turbulence (10%), the AYC strategy demonstrated a maximum increase in total power output of 2.6%, although it affected individual turbines differently. It also exhibits an increase in some structural loads, such as tower-top torque, while some components experience a slight reduction in load. The results underscore the effectiveness of the ANN-guided game-theoretic algorithm in improving wind farm power generation by mitigating the negative impact of wake interference, offering a scalable and efficient method for optimizing large-scale wind farm. However, it is essential to evaluate the overall impact of AYC on wind farm efficiency in terms of both Annual Energy Production (AEP) and structural loading under various atmospheric conditions.
Extension and Validation of Minimalistic Prediction Model to Determine the Energy Production of Offshore Wind Farms
Authors: Sørensen Jens N. , Garcia Ariadna M. I. , Larsen Gunner C. , Pedersen Mads M. , Fournely David
Published: June 2024

Calculations of annual energy productions of wind farms are normally very computing demanding as they require simulations of the wind flow field inside the wind farms for a range of ambient wind conditions and directions. Although there exists many advanced computing tools for atmospheric flows, which, in principle, cope with all flow situations, most wind power developers rely their work on simplified engineering models based on analytical approaches and superposition of the flow behind a single row of wind turbines. An alternative to wake modeling is the fully developed wind farm array boundary layer model, which assumes that the wind farm is so large, that the wind field inside the wind farm is in equilibrium with the flow field of the ambient atmospheric boundary layer. Such a model was recently further developed by the authors using a simple correction for coping with finite-sized wind farms. The purpose of the present work is to extend further the finiteness correction formula and validate the model by comparing results to actual production data and to results from other simulation models, such as the Jensen, Gaussian and TurbOPark engineering models. In spite of the simplicity of the proposed model, it outperforms the other models, achieving results within 5% accuracy as compared with full-scale data from existing wind farms.
BladedFarmWake: A framework for evaluating the influence of upstream wakes on turbine loads using Bladed
Authors: Bangga G. , Bossanyi E.
Published: June 2024

A new framework “BladedFarmWake” to include the upstream wake effects into a wind turbine design tool Bladed was developed in the present work. The effects of neighboring turbines in a wind farm are extracted from a wind farm flow solver LongSim, which has been developed for designing wind farm controllers and evaluating wind farm performance, taking account of atmospheric conditions and wake effects including the importance of turbine layouts and individual turbine or wind farm control strategies. These wind farm effects are incorporated into Bladed simulations to obtain time accurate load analyses. BladedFarmWake is designed to work with less human interaction as much as possible, allowing the tool to be adopted in large scale load analyses within the wind turbine design load cases (DLCs). It is demonstrated that the timeseries of the wind flow field and the wake meandering effects are successfully modelled in the framework. The effects of velocity deficit and the wake added turbulence are well captured in the generated turbulent data. As a consequence of the velocity deficit from the upstream turbine, the hub load changes considerably due to the wake meandering effects. The newly developed integrated framework will be of value for wind turbine engineers to incorporate wind farm effects in the design process.
Wake structure analysis of a wind turbine under various atmospheric flow conditions and its application for mid-fidelity calibration
Authors: Euzenat F. , Baiza Martinez L. A. , Yu W. , Maheshwari P. , Pallud M.
Published: June 2024

A coupled Actuator Line Method (ALM) Large Eddy Simulation (LES) is used to simulate the wake structure of an isolated wind turbine. The wake centre position, boundary, and dynamics downstream of the wind turbine is determined under different atmospheric flow conditions, including neutral, stable, and unstable stratification. The wake centre lateral displacement and autocorrelation are seen to be affected by the atmospheric flow conditions. Finally, the instantaneous wake structure is then used as reference to improve the accuracy of mid-fidelity approach.
Dynamic response of a wind turbine wake subjected to surge and heave step motions under different inflow conditions
Authors: Hubert Antonin , Conan Boris , Aubrun Sandrine
Published: June 2024

The development of floating offshore wind turbines poses new challenges since the floating platform introduces complex dynamics in the wind turbine wake. These wake dynamics are intricately tied to the advection velocity, referring to the velocity of the downstream propagation of the air flow, and used in the context of wind farm modelling. The present article investigates the far-wake dynamic response of a wind turbine model subjected to heave (up-down translation) and surge (fore-aft translation) step motions under two distinct inflow conditions. Wind tunnel experiments were conducted with hot-wires in a realistic turbulent inflow and a low shear and no ground effect inflow, achieved by varying the hub height of the wind turbine model in the atmospheric boundary layer developed in the test section. The results show that the dynamic response of the wake under the low shear and no ground effect inflow conditions aligns with a second-order system with the presence of undershoots and overshoots. In contrast, under realistic conditions, it appears like a first-order system with undershoots and overshoots less evident in most cases. Despite these variations the determined advection velocity remains roughly the same and consistent with the literature for both heave and surge step motions, regardless of the inflow conditions.
Wind tunnel inflow data assimilation in an LES digital twin for improving validation against an experimental wind turbine wake
Authors: Gillyns E. , Buckingham S. , Van Beeck J. , Winckelmans G.
Published: June 2024

Wind energy is playing an essential role in the energy transition towards a carbon-neutral system, for which wind turbine wakes are one of the most important aspects. By extracting energy from the flow, the turbine generates power but also decreases the production and increases the loading of downstream wind turbines; and potentially affects nearby structures.

To better understand the physical phenomenon, Large Eddy Simulation (LES) offers scale-resolving capabilities and a physical insight into complex turbulence flows. The state of the art in terms of high-fidelity wake simulations consists in combining LES with an Actuator Line Model in order to capture the tip vortices and detailed wake dynamics.

This paper focuses on the comparison between such simulation, with experiments in the controlled environment of a wind tunnel, in order to assess the performance and limitations of the model. A large part is dedicated to reproducing a developing flow, with a controlled level of turbulence. The Recycle and Rescale Method is used to provide the mean inflow profile, while a novel approach using controlled volume forces allows to improve the turbulence level of the flow. With the proposed methodology, the mean profile is properly imposed, while the associated turbulence characteristics is improved by roughly 50 %.
Influence of platform motion on the energy production of a floating wind farm
Authors: De Pascali M. , Fontanella A. , Muggiasca S. , Belloli M.
Published: June 2024

This study investigates the dynamics of energy production in floating wind farms. Unlike their bottom-fixed counterparts, floating wind turbines experience large-amplitude, low-frequency movements affecting the rotor response and the wake development. We employed the multi-physics simulator FAST.Farm to study a seven-turbine wind farm, comparing conventional monopile foundations with semi-submersibles. Results show that, under undisturbed wind conditions, floating turbines exhibit a lower power-conversion efficiency due to platform tilt and the use of a thrust clipping controller. Conversely, waked turbines in a floating configuration have a higher power output than with a bottom-fixed foundation. This is attributed to the higher wind speed in their wake which is due to the lower thrust set point of the floating controller, the vertical deflection of the wake and the dynamic conditions at rotor created by motion.
Influence of wake meandering path on floater motions
Authors: Eliassen Lene Vien , Arreba Irene Rivera , De Vaal Jacobus , Panjwani Balram
Published: June 2024

This study shows how different versions of the dynamic wake meandering (DWM) model will result in different dynamic behaviour of a floating wind turbine. In this study, different softwares as well as different input wind boxes are applied. The effect of these variations were studied using statistics from both the meandering behaviour of the wake and the response of a floating wind turbine. The yaw response is the most sensitive, and this study shows that the standard deviation of the yaw response is between 10% to 60%, depending on the DWM options used when generating the wake wind field.
The effect of nacelle-to-rotor size on the wake of a miniature wind turbine
Authors: Dar Arslan Salim , Majzoub Rim , Porté-Agel Fernando
Published: June 2024

Wind tunnel experiments are performed to investigate the effect of nacelle-to-rotor size on the wake of a wind turbine under different Reynolds numbers. Four different turbine configurations are tested, which vary in the rotor diameter and nacelle length and diameter. The near wake region is observed to be significantly affected by the nacelle-to-rotor size of the turbine. The difference in the averaged streamwise velocity and streamwise turbulence intensity is affected more by the change in the rotor diameter than by the change in the nacelle diameter. This is likely due to the change in the nacelle length to rotor diameter ratio, and the change in the distance between the ground and rotor lower tip. The differences in the near wake characteristics are reduced by the increase in the Reynolds number. The onset of the far wake is unaffected by the nacelle-to-rotor size, and consequently, the far wake modeling can be performed with good accuracy using existing analytical models. The power coefficient values show an improvement with the increase in the Reynolds number due to the higher efficiency of the rotor and motor.
Experimental and numerical investigation on the potential of wake mixing by dynamic yaw for wind farm power optimization
Authors: Mühle F V , Tamaro S , Klinger F , Campagnolo F , Bottasso C L
Published: June 2024

This study investigates open-loop dynamic yaw control as a strategy for enhancing wind farm performance through wake mixing. The focus is on understanding the potential for enhanced wake mixing under different turbulence intensities, and the mechanisms triggering mixing. Experimental tests are conducted using scaled wind tunnel experiments with two model wind turbines. The wake flow is analysed by large eddy simulations (LES). Dynamic yawing is prescribed by sinusoidally varying the yaw angle at different excitation frequencies. The study reveals that dynamic yaw control, particularly at low inflow turbulence, leads to increased wake mixing. The resulting enhanced wind farm power capture has a rather flat maximum around an optimal Strouhal number. This is in contrast to high inflow turbulence, where the effectiveness of the control strategy is significantly reduced. The meandering motion of the wake induced by dynamic yaw excitation is identified as the key mechanism for improved wake recovery.
Dynamic individual pitch control for wake mitigation: Why does the helix handedness in the wake matter?
Authors: Coquelet M , Gutknecht J , Van Wingerden JW , Duponcheel M , Chatelain P
Published: June 2024

Wind farm flow control aims at mitigating wake effects in order to maximize power production in wind farms. This work mostly focuses on the Helix strategy, which relies on individual pitch control to radially offset the application point of the thrust force from the rotor center and to dynamically change its azimuthal position. Previous studies have shown that power gains for a downstream turbine are higher for a counter-clockwise (CCW) rotation of the application point than for a clockwise (CW) one. In the CCW case, the wake develops as a right-handed helix, while in the CW case, a left-handed helix is observed. Using Large Eddy Simulations, this paper shows that the helix handedness in the wake matters due to its interaction with the wake swirl. Results of the CCW and CW helix first highlight the formation of streamwise vorticity in the near wake, which is transformed into strong coherent vortices in the far wake. Those vortex structures, to some extent similar to the counter-rotating vortex pair in the wake of yawed wind turbines, are responsible for (i) displacing the wake thanks to their induced velocities and (ii) deforming the shape of the wake.
A new RANS-based added turbulence intensity model for wind-farm flow modelling.
Authors: Delvaux T , Van Der Laan M P , Terrapon V E
Published: June 2024

This work aims to alleviate the memory requirements of the recent wake engineering model described in Criado Risco et al. [1]. The original model relies on a RANS-based look-up table of three-dimensional velocity deficit and added turbulence intensity fields computed for a stand-alone turbine under a wide variety of conditions. The objective is to develop an alternative to the model of Criado Risco et al. [1], particularly in terms of added turbulence intensity, for which little research has been carried out to date. To achieve this, a one-dimensional analytical expression is fitted to the look-up table and generalized to higher dimensions. The turbulence intensity model is then coupled to a velocity deficit model and implemented in PyWake, an open-source wake engineering software. Overall, the new turbulence intensity model is found to provide a reliable description of the RANS look-up table data while reducing by half the memory requirements of the original model. This conclusion is extended to multiple wake situations, for which this work also establishes a direct link between the adequate superposition method and the definition chosen to describe the added turbulence intensity in the wake.
Near-wake measurements and simulations of a floating wind turbine using a four-beam nacelle-based lidar
Authors: Özinan Umut , Gräfe Moritz , Schulz Christian W. , Cheng Po Wen
Published: June 2024

Recent advances in lidar technology have expanded the possibilities for measuring full-scale wind turbine wakes within the atmospheric boundary layer. This study utilizes a four-beam pulsed lidar installed on the nacelle of a floating turbine to measure the near-wake. The wake measurement campaign was conducted on the Floatgen, with lidar measurements reaching up to 2.5 times the rotor diameter distance. These measurements are presented as 10-minute average radial wind speeds. The focus of this study is on the below rated wind speed of 7 m/s. Free flow conditions were assumed at the farthest measurement points, which are located ±0.9 times the rotor diameter from to the rotor center. The sensitivity of lidar measurements to turbulence intensity, vertical wind shear, and significant wave height was investigated. The environmental conditions were categorized into five cases, considering turbulence, vertical shear, and yaw misalignment as well as waves. Two simulation models with different fidelity levels are used to simulate these cases, and the beam-wise radial wind speed predictions are compared with the measurements. A maximum mean absolute error of 11.3% between the measurements and simulations is observed.