Articles | Volume 10, issue 1
https://doi.org/10.5194/wes-10-41-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-10-41-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
07 Jan 2025
Research article |
| 07 Jan 2025
| 07 Jan 2025
Proof of concept for multirotor systems with vortex-generating modes for regenerative wind energy: a study based on numerical simulations and experimental data
Flavio Avila Correia Martins
CORRESPONDING AUTHOR
Faculty of Aerospace Engineering, Flow Physics and Technology Department, Wind Energy Section, Delft University of Technology, Kluyverweg 1, Delft, the Netherlands
Alexander van Zuijlen
Faculty of Aerospace Engineering, Flow Physics and Technology Department, Wind Energy Section, Delft University of Technology, Kluyverweg 1, Delft, the Netherlands
Faculty of Aerospace Engineering, Flow Physics and Technology Department, Aerodynamics Section, Delft University of Technology, Kluyverweg 1, Delft, the Netherlands
Carlos Simão Ferreira
Faculty of Aerospace Engineering, Flow Physics and Technology Department, Wind Energy Section, Delft University of Technology, Kluyverweg 1, Delft, the Netherlands
Related authors
No articles found.
David Bensason, Jayant Mulay, Andrea Sciacchitano, and Carlos Ferreira
Wind Energ. Sci., 10, 1499–1528, https://doi.org/10.5194/wes-10-1499-2025, https://doi.org/10.5194/wes-10-1499-2025, 2025
Short summary
Short summary
The wake of a scaled vertical-axis wind turbine farm was measured, resulting in the first experimental database of 3D-resolved flow-field measurements. In addition to the baseline operating conditions, two modes of wake control were tested, which involve the passive adjustment of the rotor blade pitch. The results highlight the impacts of these mode adjustments on the trailing vorticity system, wake topology, and affinity towards increasing the rate of wake recovery throughout the farm.
Abhratej Sahoo, Akshay Koodly Ravishankara, Wei Yu, Daniele Ragni, and Carlos Simao Ferreira
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2025-69, https://doi.org/10.5194/wes-2025-69, 2025
Preprint under review for WES
Short summary
Short summary
The paper proposes a new model to include the effects of vortex generators in the fast aerodynamic force calculation methods used for rotor blade sectional load calculations. The model is derived from the effects of vortex generators on turbulent boundary layers. The new model is more accurate than existing models in predicting the parametric impact of various vortex generator geometries on the stall delay and lift increase effects on airfoil aerodynamic polars.
YuanTso Li, Wei Yu, Andrea Sciacchitano, and Carlos Ferreira
Wind Energ. Sci., 10, 631–659, https://doi.org/10.5194/wes-10-631-2025, https://doi.org/10.5194/wes-10-631-2025, 2025
Short summary
Short summary
A novel wind farm concept, called a regenerative wind farm, is investigated numerically. This concept tackles the significant wake interaction losses among traditional wind farms. Our results show that regenerative wind farms can greatly reduce these losses, boosting power output per unit surface. Unlike traditional farms with three-bladed wind turbines, regenerative farms use multi-rotor systems with lifting devices (MRSLs). This unconventional design effectively reduces wake losses.
David Bensason, Andrea Sciacchitano, and Carlos Ferreira
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2025-3, https://doi.org/10.5194/wes-2025-3, 2025
Revised manuscript accepted for WES
Short summary
Short summary
This study experimentally explores the wake of the novel X-Rotor vertical axis wind turbine. Passive blade pitch is used to favorably modify the wake topology and subsequent energy replenishment process. The results demonstrate significant increases in available power for downstream rotors and the underlying mechanisms, highlighting the potential of vertical-axis wind turbines and passive blade pitch control for high-energy-density wind farm applications.
Erik Fritz, Koen Boorsma, and Carlos Ferreira
Wind Energ. Sci., 9, 1617–1629, https://doi.org/10.5194/wes-9-1617-2024, https://doi.org/10.5194/wes-9-1617-2024, 2024
Short summary
Short summary
This study presents results from a wind tunnel experiment on a model wind turbine with swept blades, thus blades curved in the rotor plane. Using a non-intrusive measurement technique, the flow around the turbine blades was measured from which blade-level aerodynamics are derived in post-processing. The detailed experimental database gives insight into swept-blade aerodynamics and has great value in validating numerical tools, which aim at simulating swept wind turbine blades.
Erik Fritz, André Ribeiro, Koen Boorsma, and Carlos Ferreira
Wind Energ. Sci., 9, 1173–1187, https://doi.org/10.5194/wes-9-1173-2024, https://doi.org/10.5194/wes-9-1173-2024, 2024
Short summary
Short summary
This study presents results from a wind tunnel experiment on a model wind turbine. Using a non-intrusive measurement technique, the flow around the turbine blades was measured. In post-processing, the blade-level aerodynamics are derived from the measured flow fields. The detailed experimental database has great value in validating numerical tools of varying complexity, which aim at simulating wind turbine aerodynamics as accurately as possible.
Adhyanth Giri Ajay, Laurence Morgan, Yan Wu, David Bretos, Aurelio Cascales, Oscar Pires, and Carlos Ferreira
Wind Energ. Sci., 9, 453–470, https://doi.org/10.5194/wes-9-453-2024, https://doi.org/10.5194/wes-9-453-2024, 2024
Short summary
Short summary
This paper compares six different numerical models to predict the performance of an X-shaped vertical-axis wind turbine, offering insights into how it works in 3D when its blades are fixed at specific angles. The results showed the 3D models here reliably predict the performance while still taking this turbine's complex aerodynamics into account compared to 2D models. Further, these blade angles caused more complexity in predicting the turbine's behaviour, which is highlighted in this paper.
André F. P. Ribeiro, Damiano Casalino, and Carlos S. Ferreira
Wind Energ. Sci., 8, 661–675, https://doi.org/10.5194/wes-8-661-2023, https://doi.org/10.5194/wes-8-661-2023, 2023
Short summary
Short summary
Floating offshore wind turbines move due to not having a rigid foundation. Hence, as the blades rotate they experience more complex aerodynamics than standard onshore wind turbines. In this paper, we show computational simulations of a wind turbine rotor moving in various ways and quantify the effects of the motion in the forces acting on the blades. We show that these forces behave in nonlinear ways in some cases.
Alessandro Bianchini, Galih Bangga, Ian Baring-Gould, Alessandro Croce, José Ignacio Cruz, Rick Damiani, Gareth Erfort, Carlos Simao Ferreira, David Infield, Christian Navid Nayeri, George Pechlivanoglou, Mark Runacres, Gerard Schepers, Brent Summerville, David Wood, and Alice Orrell
Wind Energ. Sci., 7, 2003–2037, https://doi.org/10.5194/wes-7-2003-2022, https://doi.org/10.5194/wes-7-2003-2022, 2022
Short summary
Short summary
The paper is part of the Grand Challenges Papers for Wind Energy. It provides a status of small wind turbine technology in terms of technical maturity, diffusion, and cost. Then, five grand challenges that are thought to be key to fostering the development of the technology are proposed. To tackle these challenges, a series of unknowns and gaps are first identified and discussed. Improvement areas are highlighted, within which 10 key enabling actions are finally proposed to the wind community.
Daan van der Hoek, Joeri Frederik, Ming Huang, Fulvio Scarano, Carlos Simao Ferreira, and Jan-Willem van Wingerden
Wind Energ. Sci., 7, 1305–1320, https://doi.org/10.5194/wes-7-1305-2022, https://doi.org/10.5194/wes-7-1305-2022, 2022
Short summary
Short summary
The paper presents a wind tunnel experiment where dynamic induction control was implemented on a small-scale turbine. By periodically changing the pitch angle of the blades, the low-velocity turbine wake is perturbed, and hence it recovers at a faster rate. Small particles were released in the flow and subsequently recorded with a set of high-speed cameras. This allowed us to reconstruct the flow behind the turbine and investigate the effect of dynamic induction control on the wake.
Carlos Ferreira, Wei Yu, Arianna Sala, and Axelle Viré
Wind Energ. Sci., 7, 469–485, https://doi.org/10.5194/wes-7-469-2022, https://doi.org/10.5194/wes-7-469-2022, 2022
Short summary
Short summary
Floating offshore wind turbines may experience large surge motions that, when faster than the local wind speed, cause rotor–wake interaction.
We derive a model which is able to predict the wind speed at the wind turbine, even for large and fast motions and load variations in the wind turbine.
The proposed dynamic inflow model includes an adaptation for highly loaded flow, and it is accurate and simple enough to be easily implemented in most blade element momentum design models.
G. A. M. van Kuik, J. Peinke, R. Nijssen, D. Lekou, J. Mann, J. N. Sørensen, C. Ferreira, J. W. van Wingerden, D. Schlipf, P. Gebraad, H. Polinder, A. Abrahamsen, G. J. W. van Bussel, J. D. Sørensen, P. Tavner, C. L. Bottasso, M. Muskulus, D. Matha, H. J. Lindeboom, S. Degraer, O. Kramer, S. Lehnhoff, M. Sonnenschein, P. E. Sørensen, R. W. Künneke, P. E. Morthorst, and K. Skytte
Wind Energ. Sci., 1, 1–39, https://doi.org/10.5194/wes-1-1-2016, https://doi.org/10.5194/wes-1-1-2016, 2016
Related subject area
Thematic area: Fluid mechanics | Topic: Wakes and wind farm aerodynamics
Experimental demonstration of regenerative wind farming using a high-density layout of vertical-axis wind turbines
Modeling the effects of active wake mixing on wake behavior through large-scale coherent structures
Wake development in floating wind turbines: new insights and an open dataset from wind tunnel experiments
Spatiotemporal behavior of the far wake of a wind turbine model subjected to harmonic motions: phase averaging applied to stereo particle image velocimetry measurements
Spatial development of planar and axisymmetric wakes of porous objects under a pressure gradient: a wind tunnel study
Numerical investigation of regenerative wind farms featuring enhanced vertical energy entrainment
Convergence and efficiency of global bases using proper orthogonal decomposition for capturing wind turbine wake aerodynamics
Direct integration of non-axisymmetric Gaussian wind-turbine wake including yaw and wind-veer effects
Turbine- and farm-scale power losses in wind farms: an alternative to wake and farm blockage losses
Effect of blockage on wind turbine power and wake development
Comparison of wind-farm control strategies under realistic offshore wind conditions: wake quantities of interest
Introduction and comparison of novel deep learning and optimization approaches to analytical wake modeling of a tilted wind turbine
Hyperparameter tuning framework for calibrating analytical wake models using SCADA data of an offshore wind farm
Synchronised WindScanner field measurements of the induction zone between two closely spaced wind turbines
Wind farm structural response and wake dynamics for an evolving stable boundary layer: computational and experimental comparisons
Improvements to the dynamic wake meandering model by incorporating the turbulent Schmidt number
An actuator sector model for wind power applications: a parametric study
Wind tunnel investigations of an individual pitch control strategy for wind farm power optimization
The near-wake development of a wind turbine operating in stalled conditions – Part 1: Assessment of numerical models
Data-driven optimisation of wind farm layout and wake steering with large-eddy simulations
Floating wind turbine motion signature in the far-wake spectral content – a wind tunnel experiment
Breakdown of the velocity and turbulence in the wake of a wind turbine – Part 1: Large-eddy-simulation study
Breakdown of the velocity and turbulence in the wake of a wind turbine – Part 2: Analytical modelling
Free-vortex models for wind turbine wakes under yaw misalignment – a validation study on far-wake effects
A method to correct for the effect of blockage and wakes on power performance measurements
Vortex model of the aerodynamic wake of airborne wind energy systems
A new RANS-based wind farm parameterization and inflow model for wind farm cluster modeling
Investigating energy production and wake losses of multi-gigawatt offshore wind farms with atmospheric large-eddy simulation
The wind farm as a sensor: learning and explaining orographic and plant-induced flow heterogeneities from operational data
Multi-point in situ measurements of turbulent flow in a wind turbine wake and inflow with a fleet of uncrewed aerial systems
Addressing deep array effects and impacts to wake steering with the cumulative-curl wake model
Actuator line model using simplified force calculation methods
Brief communication: A clarification of wake recovery mechanisms
Predictive and stochastic reduced-order modeling of wind turbine wake dynamics
Wind turbine wake simulation with explicit algebraic Reynolds stress modeling
Including realistic upper atmospheres in a wind-farm gravity-wave model
David Bensason, Jayant Mulay, Andrea Sciacchitano, and Carlos Ferreira
Wind Energ. Sci., 10, 1499–1528, https://doi.org/10.5194/wes-10-1499-2025, https://doi.org/10.5194/wes-10-1499-2025, 2025
Short summary
Short summary
The wake of a scaled vertical-axis wind turbine farm was measured, resulting in the first experimental database of 3D-resolved flow-field measurements. In addition to the baseline operating conditions, two modes of wake control were tested, which involve the passive adjustment of the rotor blade pitch. The results highlight the impacts of these mode adjustments on the trailing vorticity system, wake topology, and affinity towards increasing the rate of wake recovery throughout the farm.
Lawrence Cheung, Gopal Yalla, Prakash Mohan, Alan Hsieh, Kenneth Brown, Nathaniel deVelder, Daniel Houck, Marc T. Henry de Frahan, Marc Day, and Michael Sprague
Wind Energ. Sci., 10, 1403–1420, https://doi.org/10.5194/wes-10-1403-2025, https://doi.org/10.5194/wes-10-1403-2025, 2025
Short summary
Short summary
Mitigating turbine wakes is an important aspect to maximizing wind farm energy production but is a challenge to model. We demonstrate a new approach to modeling active wake mixing, which re-energizes turbine wake through periodic blade pitching. The new model divides the wake into separate steady, unsteady, and turbulent components and solves for each in a computationally efficient manner. Our results show that the model can reasonably predict the faster wake recovery due to mixing.
Alessandro Fontanella, Alberto Fusetti, Stefano Cioni, Francesco Papi, Sara Muggiasca, Giacomo Persico, Vincenzo Dossena, Alessandro Bianchini, and Marco Belloli
Wind Energ. Sci., 10, 1369–1387, https://doi.org/10.5194/wes-10-1369-2025, https://doi.org/10.5194/wes-10-1369-2025, 2025
Short summary
Short summary
This paper investigates the impact of large movements allowed by floating wind turbine foundations on their aerodynamics and wake behavior. Wind tunnel tests with a model turbine reveal that platform motions affect wake patterns and turbulence levels. Insights from these experiments are crucial for optimizing large-scale floating wind farms. The dataset obtained from the experiment is published and can aid in developing simulation tools for floating wind turbines.
Antonin Hubert, Boris Conan, and Sandrine Aubrun
Wind Energ. Sci., 10, 1351–1368, https://doi.org/10.5194/wes-10-1351-2025, https://doi.org/10.5194/wes-10-1351-2025, 2025
Short summary
Short summary
The paper aims to study the far wake of a wind turbine under realistic inflow conditions subjected to harmonic floating motions. The present work shows that phase averaging enables the observation of the coherent spatiotemporal wake behaviour in response to the harmonic motions, contrary to previous studies with time averaging, and that the resulting variations in the chosen metrics exhibit an intensity higher than those expected when using basic quasi-steady-state approaches.
Wessel van der Deijl, Martín Obligado, Stéphane Barre, and Christophe Sicot
Wind Energ. Sci., 10, 719–732, https://doi.org/10.5194/wes-10-719-2025, https://doi.org/10.5194/wes-10-719-2025, 2025
Short summary
Short summary
We present a wind tunnel study on the effect of an adverse pressure gradient on wakes from porous discs and cylinders. We quantified the spatial development of turbulent wakes for Reynolds numbers up to 3.9 × 105 and at distances ranging from 1 to 12 diameters downstream, both with and without an adverse pressure gradient. Consistent with previous studies, we find that the pressure gradient has an effect in all cases, resulting in larger velocity deficits and wider wakes.
YuanTso Li, Wei Yu, Andrea Sciacchitano, and Carlos Ferreira
Wind Energ. Sci., 10, 631–659, https://doi.org/10.5194/wes-10-631-2025, https://doi.org/10.5194/wes-10-631-2025, 2025
Short summary
Short summary
A novel wind farm concept, called a regenerative wind farm, is investigated numerically. This concept tackles the significant wake interaction losses among traditional wind farms. Our results show that regenerative wind farms can greatly reduce these losses, boosting power output per unit surface. Unlike traditional farms with three-bladed wind turbines, regenerative farms use multi-rotor systems with lifting devices (MRSLs). This unconventional design effectively reduces wake losses.
Juan Felipe Céspedes Moreno, Juan Pablo Murcia León, and Søren Juhl Andersen
Wind Energ. Sci., 10, 597–611, https://doi.org/10.5194/wes-10-597-2025, https://doi.org/10.5194/wes-10-597-2025, 2025
Short summary
Short summary
Using a global base in a proper orthogonal decomposition provides a common base for analyzing flows, such as wind turbine wakes, across an entire parameter space. This can be used to compare flows with different conditions using the same physical interpretation. This work shows the convergence of the global base, its small error compared to the truncation error in the flow reconstruction, and the insensitivity to which datasets are included for generating the global base.
Karim Ali, Pablo Ouro, and Tim Stallard
Wind Energ. Sci., 10, 511–533, https://doi.org/10.5194/wes-10-511-2025, https://doi.org/10.5194/wes-10-511-2025, 2025
Short summary
Short summary
We introduce an innovative analytical method to better understand and optimise wind-farm performance by accurately calculating how turbine wakes affect each other. Unlike traditional numerical approaches, our method provides a precise way to measure the impact of upstream wakes on downstream turbines. This new approach, validated through numerical comparisons, enhances optimisation strategies, potentially leading to more efficient wind-farm operations and increased power generation.
Andrew Kirby, Takafumi Nishino, Luca Lanzilao, Thomas D. Dunstan, and Johan Meyers
Wind Energ. Sci., 10, 435–450, https://doi.org/10.5194/wes-10-435-2025, https://doi.org/10.5194/wes-10-435-2025, 2025
Short summary
Short summary
Traditionally, the aerodynamic loss of wind farm efficiency is classified into wake loss and farm blockage loss. This study, using high-fidelity simulations, shows that neither of these two losses is well correlated with the overall farm efficiency. We propose new measures called turbine-scale efficiency and farm-scale efficiency to better describe turbine–wake effects and farm–atmosphere interactions. This study suggests the importance of better modelling farm-scale loss in future studies.
Olivier Ndindayino, Augustin Puel, and Johan Meyers
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2025-6, https://doi.org/10.5194/wes-2025-6, 2025
Revised manuscript accepted for WES
Short summary
Short summary
Our aim is to understand the relationship between flow blockage and improved wind farm efficiency using large-eddy simulations, as well as developing an analytical model that shows promise for improving turbine power predictions under blockage. We found that blockage enhances turbine power and thrust by inducing a favourable pressure drop across the turbine row, while simultaneously inducing an unfavourable pressure increase downstream which has minimal direct impact on far wake development.
Kenneth Brown, Gopal Yalla, Lawrence Cheung, Joeri Frederik, Dan Houck, Nate deVelder, Eric Simley, and Paul Fleming
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-191, https://doi.org/10.5194/wes-2024-191, 2025
Revised manuscript accepted for WES
Short summary
Short summary
This paper presents a one half of a companion-paper series that studies strategies to reduce negative aerodynamic interference (i.e., wake effects) between nearby wind turbines in a wind farm. The approach leverages high-fidelity flow simulations of an open-source design for an offshore wind turbine. Complimenting the companion paper’s analysis of the power and loading effects of the wake-control strategies, this article uncovers the underlying fluid-dynamic causes for these effects.
James Cutler, Christopher Bay, and Andrew Ning
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-172, https://doi.org/10.5194/wes-2024-172, 2025
Revised manuscript accepted for WES
Short summary
Short summary
This study compares two methods for modeling wakes from tilted wind turbines. An optimized analytical model improves accuracy but is limited by assumptions about wake shape. In contrast, a deep learning approach captures complex wake patterns without these constraints, matching high-fidelity simulations with minimal computational effort. The comparison highlights the potential of deep learning to transform wake modeling, offering greater accuracy and efficiency for wind energy optimization.
Diederik van Binsbergen, Pieter-Jan Daems, Timothy Verstraeten, Amir R. Nejad, and Jan Helsen
Wind Energ. Sci., 9, 1507–1526, https://doi.org/10.5194/wes-9-1507-2024, https://doi.org/10.5194/wes-9-1507-2024, 2024
Short summary
Short summary
Wind farm yield assessment often relies on analytical wake models. Calibrating these models can be challenging due to the stochastic nature of wind. We developed a calibration framework that performs a multi-phase optimization on the tuning parameters using time series SCADA data. This yields a parameter distribution that more accurately reflects reality than a single value. Results revealed notable variation in resultant parameter values, influenced by nearby wind farms and coastal effects.
Anantha Padmanabhan Kidambi Sekar, Paul Hulsman, Marijn Floris van Dooren, and Martin Kühn
Wind Energ. Sci., 9, 1483–1505, https://doi.org/10.5194/wes-9-1483-2024, https://doi.org/10.5194/wes-9-1483-2024, 2024
Short summary
Short summary
We present induction zone measurements conducted with two synchronised lidars at a two-turbine wind farm. The induction zone flow was characterised for free, fully waked and partially waked flows. Due to the short turbine spacing, the lidars captured the interaction of the atmospheric boundary layer, induction zone and wake, evidenced by induction asymmetry and induction zone–wake interactions. The measurements will aid the process of further improving existing inflow and wake models.
Kelsey Shaler, Eliot Quon, Hristo Ivanov, and Jason Jonkman
Wind Energ. Sci., 9, 1451–1463, https://doi.org/10.5194/wes-9-1451-2024, https://doi.org/10.5194/wes-9-1451-2024, 2024
Short summary
Short summary
This paper presents a three-way verification and validation between an engineering-fidelity model, a high-fidelity model, and measured data for the wind farm structural response and wake dynamics during an evolving stable boundary layer of a small wind farm, generally with good agreement.
Peter Brugger, Corey D. Markfort, and Fernando Porté-Agel
Wind Energ. Sci., 9, 1363–1379, https://doi.org/10.5194/wes-9-1363-2024, https://doi.org/10.5194/wes-9-1363-2024, 2024
Short summary
Short summary
The dynamic wake meandering model (DWMM) assumes that wind turbine wakes are transported like a passive tracer by the large-scale turbulence of the atmospheric boundary layer. We show that both the downstream transport and the lateral transport of the wake have differences from the passive tracer assumption. We then propose to include the turbulent Schmidt number into the DWMM to account for the less efficient transport of momentum and show that it improves the quality of the model predictions.
Mohammad Mehdi Mohammadi, Hugo Olivares-Espinosa, Gonzalo Pablo Navarro Diaz, and Stefan Ivanell
Wind Energ. Sci., 9, 1305–1321, https://doi.org/10.5194/wes-9-1305-2024, https://doi.org/10.5194/wes-9-1305-2024, 2024
Short summary
Short summary
This paper has put forward a set of recommendations regarding the actuator sector model implementation details to improve the capability of the model to reproduce similar results compared to those obtained by an actuator line model, which is one of the most common ways used for numerical simulations of wind farms, while providing significant computational savings. This includes among others the velocity sampling method and a correction of the sampled velocities to calculate the blade forces.
Franz V. Mühle, Florian M. Heckmeier, Filippo Campagnolo, and Christian Breitsamter
Wind Energ. Sci., 9, 1251–1271, https://doi.org/10.5194/wes-9-1251-2024, https://doi.org/10.5194/wes-9-1251-2024, 2024
Short summary
Short summary
Wind turbines influence each other, and these wake effects limit the power production of downstream turbines. Controlling turbines collectively and not individually can limit such effects. We experimentally investigate a control strategy increasing mixing in the wake. We want to see the potential of this so-called Helix control for power optimization and understand the flow physics. Our study shows that the control technique leads to clearly faster wake recovery and thus higher power production.
Pascal Weihing, Marion Cormier, Thorsten Lutz, and Ewald Krämer
Wind Energ. Sci., 9, 933–962, https://doi.org/10.5194/wes-9-933-2024, https://doi.org/10.5194/wes-9-933-2024, 2024
Short summary
Short summary
This study evaluates different approaches to simulate the near-wake flow of a wind turbine. The test case is in off-design conditions of the wind turbine, where the flow is separated from the blades and therefore very difficult to predict. The evaluation of simulation techniques is key to understand their limitations and to deepen the understanding of the near-wake physics. This knowledge can help to derive new wind farm design methods for yield-optimized farm layouts.
Nikolaos Bempedelis, Filippo Gori, Andrew Wynn, Sylvain Laizet, and Luca Magri
Wind Energ. Sci., 9, 869–882, https://doi.org/10.5194/wes-9-869-2024, https://doi.org/10.5194/wes-9-869-2024, 2024
Short summary
Short summary
This paper proposes a computational method to maximise the power production of wind farms through two strategies: layout optimisation and yaw angle optimisation. The proposed method relies on high-fidelity computational modelling of wind farm flows and is shown to be able to effectively maximise wind farm power production. Performance improvements relative to conventional optimisation strategies based on low-fidelity models can be attained, particularly in scenarios of increased flow complexity.
Benyamin Schliffke, Boris Conan, and Sandrine Aubrun
Wind Energ. Sci., 9, 519–532, https://doi.org/10.5194/wes-9-519-2024, https://doi.org/10.5194/wes-9-519-2024, 2024
Short summary
Short summary
This paper studies the consequences of floater motions for the wake properties of a floating wind turbine. Since wake interactions are responsible for power production loss in wind farms, it is important that we know whether the tools that are used to predict this production loss need to be upgraded to take into account these aspects. Our wind tunnel study shows that the signature of harmonic floating motions can be observed in the far wake of a wind turbine, when motions have strong amplitudes.
Erwan Jézéquel, Frédéric Blondel, and Valéry Masson
Wind Energ. Sci., 9, 97–117, https://doi.org/10.5194/wes-9-97-2024, https://doi.org/10.5194/wes-9-97-2024, 2024
Short summary
Short summary
Wind turbine wakes affect the production and lifecycle of downstream turbines. They can be predicted with the dynamic wake meandering (DWM) method. In this paper, the authors break down the velocity and turbulence in the wake of a wind turbine into several terms. They show that it is implicitly assumed in the DWM that some of these terms are neglected. With high-fidelity simulations, it is shown that this can lead to some errors, in particular for the maximum turbulence added by the wake.
Erwan Jézéquel, Frédéric Blondel, and Valéry Masson
Wind Energ. Sci., 9, 119–139, https://doi.org/10.5194/wes-9-119-2024, https://doi.org/10.5194/wes-9-119-2024, 2024
Short summary
Short summary
Analytical models allow us to quickly compute the decreased power output and lifetime induced by wakes in a wind farm. This is achieved by evaluating the modified velocity and turbulence in the wake. In this work, we present a new model based on the velocity and turbulence breakdowns presented in Part 1. This new model is physically based, allows us to compute the whole turbulence profile (rather than the maximum value) and is built to take atmospheric stability into account.
Maarten J. van den Broek, Delphine De Tavernier, Paul Hulsman, Daan van der Hoek, Benjamin Sanderse, and Jan-Willem van Wingerden
Wind Energ. Sci., 8, 1909–1925, https://doi.org/10.5194/wes-8-1909-2023, https://doi.org/10.5194/wes-8-1909-2023, 2023
Short summary
Short summary
As wind turbines produce power, they leave behind wakes of slow-moving air. We analyse three different models to predict the effects of these wakes on downstream wind turbines. The models are validated with experimental data from wind tunnel studies for steady and time-varying conditions. We demonstrate that the models are suitable for optimally controlling wind turbines to improve power production in large wind farms.
Alessandro Sebastiani, James Bleeg, and Alfredo Peña
Wind Energ. Sci., 8, 1795–1808, https://doi.org/10.5194/wes-8-1795-2023, https://doi.org/10.5194/wes-8-1795-2023, 2023
Short summary
Short summary
The power curve of a wind turbine indicates the turbine power output in relation to the wind speed. Therefore, power curves are critically important to estimate the production of future wind farms as well as to assess whether operating wind farms are functioning correctly. Since power curves are often measured in wind farms, they might be affected by the interactions between the turbines. We show that these effects are not negligible and present a method to correct for them.
Filippo Trevisi, Carlo E. D. Riboldi, and Alessandro Croce
Wind Energ. Sci., 8, 999–1016, https://doi.org/10.5194/wes-8-999-2023, https://doi.org/10.5194/wes-8-999-2023, 2023
Short summary
Short summary
Modeling the aerodynamic wake of airborne wind energy systems (AWESs) is crucial to properly estimating power production and to designing such systems. The velocities induced at the AWES from its own wake are studied with a model for the near wake and one for the far wake, using vortex methods. The model is validated with the lifting-line free-vortex wake method implemented in QBlade.
Maarten Paul van der Laan, Oscar García-Santiago, Mark Kelly, Alexander Meyer Forsting, Camille Dubreuil-Boisclair, Knut Sponheim Seim, Marc Imberger, Alfredo Peña, Niels Nørmark Sørensen, and Pierre-Elouan Réthoré
Wind Energ. Sci., 8, 819–848, https://doi.org/10.5194/wes-8-819-2023, https://doi.org/10.5194/wes-8-819-2023, 2023
Short summary
Short summary
Offshore wind farms are more commonly installed in wind farm clusters, where wind farm interaction can lead to energy losses. In this work, an efficient numerical method is presented that can be used to estimate these energy losses. The novel method is verified with higher-fidelity numerical models and validated with measurements of an existing wind farm cluster.
Peter Baas, Remco Verzijlbergh, Pim van Dorp, and Harm Jonker
Wind Energ. Sci., 8, 787–805, https://doi.org/10.5194/wes-8-787-2023, https://doi.org/10.5194/wes-8-787-2023, 2023
Short summary
Short summary
This work studies the energy production and wake losses of large offshore wind farms with a large-eddy simulation model. Therefore, 1 year of actual weather has been simulated for a suite of hypothetical 4 GW wind farm scenarios. The results suggest that production numbers increase significantly when the rated power of the individual turbines is larger while keeping the total installed capacity the same. Also, a clear impact of atmospheric stability on the energy production is found.
Robert Braunbehrens, Andreas Vad, and Carlo L. Bottasso
Wind Energ. Sci., 8, 691–723, https://doi.org/10.5194/wes-8-691-2023, https://doi.org/10.5194/wes-8-691-2023, 2023
Short summary
Short summary
The paper presents a new method in which wind turbines in a wind farm act as local sensors, in this way detecting the flow that develops within the power plant. Through this technique, we are able to identify effects on the flow generated by the plant itself and by the orography of the terrain. The new method not only delivers a flow model of much improved quality but can also help in understanding phenomena that drive the farm performance.
Tamino Wetz and Norman Wildmann
Wind Energ. Sci., 8, 515–534, https://doi.org/10.5194/wes-8-515-2023, https://doi.org/10.5194/wes-8-515-2023, 2023
Short summary
Short summary
In the present study, for the first time, the SWUF-3D fleet of multirotors is deployed for field measurements on an operating 2 MW wind turbine (WT) in complex terrain. The fleet of multirotors has the potential to fill the meteorological gap of observations in the near wake of WTs with high-temporal and high-spatial-resolution wind vector measurements plus temperature, humidity and pressure. The flow up- and downstream of the WT is measured simultaneously at multiple spatial positions.
Christopher J. Bay, Paul Fleming, Bart Doekemeijer, Jennifer King, Matt Churchfield, and Rafael Mudafort
Wind Energ. Sci., 8, 401–419, https://doi.org/10.5194/wes-8-401-2023, https://doi.org/10.5194/wes-8-401-2023, 2023
Short summary
Short summary
This paper introduces the cumulative-curl wake model that allows for the fast and accurate prediction of wind farm energy production wake interactions. The cumulative-curl model expands several existing wake models to make the simulation of farms more accurate and is implemented in a computationally efficient manner such that it can be used for wind farm layout design and controller development. The model is validated against high-fidelity simulations and data from physical wind farms.
Gonzalo Pablo Navarro Diaz, Alejandro Daniel Otero, Henrik Asmuth, Jens Nørkær Sørensen, and Stefan Ivanell
Wind Energ. Sci., 8, 363–382, https://doi.org/10.5194/wes-8-363-2023, https://doi.org/10.5194/wes-8-363-2023, 2023
Short summary
Short summary
In this paper, the capacity to simulate transient wind turbine wake interaction problems using limited wind turbine data has been extended. The key novelty is the creation of two new variants of the actuator line technique in which the rotor blade forces are computed locally using generic load data. The analysis covers a partial wake interaction case between two wind turbines for a uniform laminar inflow and for a turbulent neutral atmospheric boundary layer inflow.
Maarten Paul van der Laan, Mads Baungaard, and Mark Kelly
Wind Energ. Sci., 8, 247–254, https://doi.org/10.5194/wes-8-247-2023, https://doi.org/10.5194/wes-8-247-2023, 2023
Short summary
Short summary
Understanding wind turbine wake recovery is important to mitigate energy losses in wind farms. Wake recovery is often assumed or explained to be dependent on the first-order derivative of velocity. In this work we show that wind turbine wakes recover mainly due to the second-order derivative of the velocity, which transport momentum from the freestream towards the wake center. The wake recovery mechanisms and results of a high-fidelity numerical simulation are illustrated using a simple model.
Søren Juhl Andersen and Juan Pablo Murcia Leon
Wind Energ. Sci., 7, 2117–2133, https://doi.org/10.5194/wes-7-2117-2022, https://doi.org/10.5194/wes-7-2117-2022, 2022
Short summary
Short summary
Simulating the turbulent flow inside large wind farms is inherently complex and computationally expensive. A new and fast model is developed based on data from high-fidelity simulations. The model captures the flow dynamics with correct statistics for a wide range of flow conditions. The model framework provides physical insights and presents a generalization of high-fidelity simulation results beyond the case-specific scenarios, which has significant potential for future turbulence modeling.
Mads Baungaard, Stefan Wallin, Maarten Paul van der Laan, and Mark Kelly
Wind Energ. Sci., 7, 1975–2002, https://doi.org/10.5194/wes-7-1975-2022, https://doi.org/10.5194/wes-7-1975-2022, 2022
Short summary
Short summary
Wind turbine wakes in the neutral atmospheric surface layer are simulated with Reynolds-averaged Navier–Stokes (RANS) using an explicit algebraic Reynolds stress model. Contrary to standard two-equation turbulence models, it can predict turbulence anisotropy and complex physical phenomena like secondary motions. For the cases considered, it improves Reynolds stress, turbulence intensity, and velocity deficit predictions, although a more top-hat-shaped profile is observed for the latter.
Koen Devesse, Luca Lanzilao, Sebastiaan Jamaer, Nicole van Lipzig, and Johan Meyers
Wind Energ. Sci., 7, 1367–1382, https://doi.org/10.5194/wes-7-1367-2022, https://doi.org/10.5194/wes-7-1367-2022, 2022
Short summary
Short summary
Recent research suggests that offshore wind farms might form such a large obstacle to the wind that it already decelerates before reaching the first turbines. Part of this phenomenon could be explained by gravity waves. Research on these gravity waves triggered by mountains and hills has found that variations in the atmospheric state with altitude can have a large effect on how they behave. This paper is the first to take the impact of those vertical variations into account for wind farms.
Cited articles
Abbes, M. and Allagui, M.: Centralized control strategy for energy maximization of large array wind turbines, Sustain. Cities Soc., 25, 82–89, 2016. a
Abkar, M. and Porté-Agel, F.: The effect of free-atmosphere stratification on boundary-layer flow and power output from very large wind farms, Energies, 6, 2338–2361, 2013. a
Ahmad, T., Basit, A., Anwar, J., Coupiac, O., Kazemtabrizi, B., and Matthews, P. C.: Fast processing intelligent wind farm controller for production maximisation, Energies, 12, 544, https://doi.org/10.3390/en12030544, 2019. a
Bader, S. H., Inguva, V., and Perot, J. B.: Improving the efficiency of wind farms via wake manipulation, Wind Energy, 21, 1239–1253, https://doi.org/10.1002/we.2226, 2018. a
Bartl, J. and Sætran, L.: Experimental testing of axial induction based control strategies for wake control and wind farm optimization, J. Phys. Conf. Ser., 753, 032–035, 2016. a
Bensason, D., Sciacchitano, A., and Ferreira, C.: Experimental study of the impact of blade-tip mounted rotors on the X-Rotor vertical-axis wind turbine, J. Phys. Conf. Ser., 2767, 072016, https://doi.org/10.1088/1742-6596/2767/7/072016, 2024. a, b, c, d
Broertjes, T., Bensason, D., Sciacchitano, A., and Ferreira, C.: Lift-induced wake re-energization for a vawt-based multi-rotor system, J. Phys. Conf. Ser., 2767, 072012, https://doi.org/10.1088/1742-6596/2767/7/072012, 2024. a, b
Darwish, M. and Moukalled, F.: The finite volume method in computational fluid dynamics: an advanced introduction with OpenFOAM® and Matlab®, Springer International Publishing, Cham, 103–135, ISBN 978-3-319-16874-6, https://doi.org/10.1007/978-3-319-16874-6_5, 2016. a
Dilip, D. and Porté-Agel, F.: Wind turbine wake mitigation through blade pitch offset, Energies, 10, 757, https://doi.org/10.3390/en10060757, 2017. a
Ferreira, C., Bensason, D., Broertjes, T. J., Sciacchitano, A., Martins, F. A., and Ajay, A. G.: Enhancing Wind Farm Efficiency Through Active Control of the Atmospheric Boundary Layer's Vertical Entrainment of Momentum, J. Phys. Conf. Ser., 2767, 092107, https://doi.org/10.1088/1742-6596/2767/9/092107, 2024. a
Ferreira, C. S.: The near wake of the VAWT, PhD Thesis, TU Delft, the Netherlands, 2009. a
Frederik, J. A., Weber, R., Cacciola, S., Campagnolo, F., Croce, A., Bottasso, C., and van Wingerden, J.-W.: Periodic dynamic induction control of wind farms: proving the potential in simulations and wind tunnel experiments, Wind Energ. Sci., 5, 245–257, https://doi.org/10.5194/wes-5-245-2020, 2020. a, b
Gargallo-Peiró, A., Avila, M., Owen, H., Prieto-Godino, L., and Folch, A.: Mesh generation, sizing and convergence for onshore and offshore wind farm Atmospheric Boundary Layer flow simulation with actuator discs, J. Comput. Phys., 375, 209–227, 2018. a
Gebraad, P., Thomas, J. J., Ning, A., Fleming, P., and Dykes, K.: Maximization of the annual energy production of wind power plants by optimization of layout and yaw-based wake control, Wind Energy, 20, 97–107, https://doi.org/10.1002/we.1993, 2017. a
Greenshields, C.: OpenFOAM v11 User Guide, The OpenFOAM Foundation, London, UK, https://doc.cfd.direct/openfoam/user-guide-v11 (last access: 1 March 2024), 2023. a
Hornshøj-Møller, S. D., Nielsen, P. D., Forooghi, P., and Abkar, M.: Quantifying structural uncertainties in Reynolds-averaged Navier–Stokes simulations of wind turbine wakes, Renew. Energ., 164, 1550–1558, 2021. a
Houck, D. R.: Review of wake management techniques for wind turbines, Wind Energy, 25, 195–220, 2022. a
Howland, M. F., Lele, S. K., and Dabiri, J. O.: Wind farm power optimization through wake steering, P. Natl. Acad. Sci. USA, 116, 14495–14500, 2019. a
Huang, M.: Wake and wind farm aerodynamics of vertical axis wind turbines, Dissertation (TU Delft), Delft University of Technology, https://doi.org/10.4233/uuid:14619578-e44f-45bb-a213-a9d179a54264, 2023. a
Huang, M., Sciacchitano, A., and Ferreira, C.: Experimental and numerical study of the wake deflections of scaled vertical axis wind turbine models, J. Phys. Conf. Ser., 2505, 012019, https://doi.org/10.1088/1742-6596/2505/1/012019, 2023. a
Jadeja, A.: Wake Deflection Technique for Vertical Axis Wind Turbines using Actuator Line Model in OpenFOAM, Master's thesis, Delft University of Technology, 2018. a
Kheirabadi, A. C. and Nagamune, R.: A quantitative review of wind farm control with the objective of wind farm power maximization, J. Wind Eng. Ind. Aerod., 192, 45–73, 2019. a
Lignarolo, L. E., Ragni, D., Krishnaswami, C., Chen, Q., Ferreira, C. J. S., and van Bussel, G. J.: Experimental analysis of the wake of a horizontal-axis wind-turbine model, Renew. Energ., 70, 31–46, https://doi.org/10.1016/j.renene.2014.01.020, 2014. a
Martins, F. A., Ferreira, C. S., and Van Zuijlen, A.: Numerical investigation of atmospheric boundary layer control in wind farms with multirotor systems, J. Phys. Conf. Ser., 2767, 072006, https://doi.org/10.1088/1742-6596/2767/7/072006, 2024. a
Martins, F. A. C.: My Research Software, Zenodo [software], https://doi.org/10.5281/zenodo.11615669, 2024. a, b
McKenna, R. v., Hollnaicher, S., vd Leye, P. O., and Fichtner, W.: Cost-potentials for large onshore wind turbines in Europe, Energy, 83, 217–229, 2015. a
Menter, F. R., Kuntz, M., and Langtry, R.: Ten years of industrial experience with the SST turbulence model, Turbulence, Heat and Mass Transfer, 4, 625–632, 2003. a
Munters, W. and Meyers, J.: Towards practical dynamic induction control of wind farms: analysis of optimally controlled wind-farm boundary layers and sinusoidal induction control of first-row turbines, Wind Energ. Sci., 3, 409–425, https://doi.org/10.5194/wes-3-409-2018, 2018. a
Parekh, J. and Verstappen, R.: Uncertainty quantification analysis for simulation of wakes in wind-farms using a stochastic RANS solver, compared with a deep learning approach, Comput. Fluids, 257, 105867, https://doi.org/10.1016/j.compfluid.2023.105867, 2023. a
Rezaeiha, A., Kalkman, I., and Blocken, B.: CFD simulation of a vertical axis wind turbine operating at a moderate tip speed ratio: Guidelines for minimum domain size and azimuthal increment, Renew. Energ., 107, 373–385, 2017. a
Ryan, K. J., Coletti, F., Elkins, C. J., Dabiri, J. O., and Eaton, J. K.: Three-dimensional flow field around and downstream of a subscale model rotating vertical axis wind turbine, Exp. Fluids, 57, 1–15, 2016. a
Sadorsky, P.: Wind energy for sustainable development: Driving factors and future outlook, J. Clea. Prod., 289, 125779, https://doi.org/10.1016/j.jclepro.2020.125779, 2021. a
Simley, E., Fleming, P., and King, J.: Design and analysis of a wake steering controller with wind direction variability, Wind Energ. Sci., 5, 451–468, https://doi.org/10.5194/wes-5-451-2020, 2020. a, b
Tescione, G., Ragni, D., He, C., Ferreira, C. S., and Van Bussel, G.: Near wake flow analysis of a vertical axis wind turbine by stereoscopic particle image velocimetry, Renew. Energ., 70, 47–61, 2014. a
van den Berg, D., de Tavernier, D., and van Wingerden, J.-W.: The dynamic coupling between the pulse wake mixing strategy and floating wind turbines, Wind Energ. Sci., 8, 849–864, https://doi.org/10.5194/wes-8-849-2023, 2023. a
Wang, C., Campagnolo, F., and Bottasso, C. L.: Does the use of load-reducing IPC on a wake-steering turbine affect wake behavior?, J. Phys. Conf. Ser., 1618, 022–035, https://doi.org/10.1088/1742-6596/1618/2/022035, 2020. a
Wei, N. J., Brownstein, I. D., Cardona, J. L., Howland, M. F., and Dabiri, J. O.: Near-wake structure of full-scale vertical-axis wind turbines, J. Fluid Mech., 914, A17, https://doi.org/10.1017/jfm.2020.578, 2021. a
Weller, H. G., Tabor, G., Jasak, H., and Fureby, C.: A tensorial approach to computational continuum mechanics using object-oriented techniques, Comput. Phys., 12, 620–631, 1998. a
Wu, Y.-T. and Porté-Agel, F.: Large-eddy simulation of wind-turbine wakes: evaluation of turbine parametrisations, Bound.-Lay. Meteorol., 138, 345–366, 2011. a
Zerrahn, A.: Wind power and externalities, Ecol. Econ., 141, 245–260, 2017. a
Short summary
This study examines regenerative wind farming with multirotor systems fitted with atmospheric boundary layer control (ABL-control) wings near the rotor's wake. These wings create vortices that boost vertical momentum transfer and speed up wake recovery. Results show that ABL-control wings can restore 95 % of wind power within six rotor diameters downstream, achieving a recovery rate nearly 10 times faster than that without ABL control.
This study examines regenerative wind farming with multirotor systems fitted with atmospheric...
Altmetrics
Final-revised paper
Preprint