Articles | Volume 6, issue 3
https://doi.org/10.5194/wes-6-791-2021
© Author(s) 2021. 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-6-791-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Active flap control with the trailing edge flap hinge moment as a sensor: using it to estimate local blade inflow conditions and to reduce extreme blade loads and deflections
Sebastian Perez-Becker
CORRESPONDING AUTHOR
Chair of Fluid Dynamics, Hermann Föttinger Institute, Technische Universität Berlin, Berlin, Germany
David Marten
Chair of Fluid Dynamics, Hermann Föttinger Institute, Technische Universität Berlin, Berlin, Germany
Christian Oliver Paschereit
Chair of Fluid Dynamics, Hermann Föttinger Institute, Technische Universität Berlin, Berlin, Germany
Related authors
Francesco Papi, Giancarlo Troise, Robert Behrens de Luna, Joseph Saverin, Sebastian Perez-Becker, David Marten, Marie-Laure Ducasse, and Alessandro Bianchini
Wind Energ. Sci., 9, 981–1004, https://doi.org/10.5194/wes-9-981-2024, https://doi.org/10.5194/wes-9-981-2024, 2024
Short summary
Short summary
Wind turbines need to be simulated for thousands of hours to estimate design loads. Mid-fidelity numerical models are typically used for this task to strike a balance between computational cost and accuracy. The considerable displacements of floating wind turbines may be a challenge for some of these models. This paper enhances comprehension of how modeling theories affect floating wind turbine loads by comparing three codes across three turbines, simulated in a real environment.
Francesco Papi, Giancarlo Troise, Robert Behrens de Luna, Joseph Saverin, Sebastian Perez-Becker, David Marten, Marie-Laure Ducasse, and Alessandro Bianchini
Wind Energ. Sci., 9, 981–1004, https://doi.org/10.5194/wes-9-981-2024, https://doi.org/10.5194/wes-9-981-2024, 2024
Short summary
Short summary
Wind turbines need to be simulated for thousands of hours to estimate design loads. Mid-fidelity numerical models are typically used for this task to strike a balance between computational cost and accuracy. The considerable displacements of floating wind turbines may be a challenge for some of these models. This paper enhances comprehension of how modeling theories affect floating wind turbine loads by comparing three codes across three turbines, simulated in a real environment.
Robert Behrens de Luna, Sebastian Perez-Becker, Joseph Saverin, David Marten, Francesco Papi, Marie-Laure Ducasse, Félicien Bonnefoy, Alessandro Bianchini, and Christian-Oliver Paschereit
Wind Energ. Sci., 9, 623–649, https://doi.org/10.5194/wes-9-623-2024, https://doi.org/10.5194/wes-9-623-2024, 2024
Short summary
Short summary
A novel hydrodynamic module of QBlade is validated on three floating offshore wind turbine concepts with experiments and two widely used simulation tools. Further, a recently proposed method to enhance the prediction of slowly varying drift forces is adopted and tested in varying met-ocean conditions. The hydrodynamic capability of QBlade matches the current state of the art and demonstrates significant improvement regarding the prediction of slowly varying drift forces with the enhanced model.
Stefano Cioni, Francesco Papi, Leonardo Pagamonci, Alessandro Bianchini, Néstor Ramos-García, Georg Pirrung, Rémi Corniglion, Anaïs Lovera, Josean Galván, Ronan Boisard, Alessandro Fontanella, Paolo Schito, Alberto Zasso, Marco Belloli, Andrea Sanvito, Giacomo Persico, Lijun Zhang, Ye Li, Yarong Zhou, Simone Mancini, Koen Boorsma, Ricardo Amaral, Axelle Viré, Christian W. Schulz, Stefan Netzband, Rodrigo Soto-Valle, David Marten, Raquel Martín-San-Román, Pau Trubat, Climent Molins, Roger Bergua, Emmanuel Branlard, Jason Jonkman, and Amy Robertson
Wind Energ. Sci., 8, 1659–1691, https://doi.org/10.5194/wes-8-1659-2023, https://doi.org/10.5194/wes-8-1659-2023, 2023
Short summary
Short summary
Simulations of different fidelities made by the participants of the OC6 project Phase III are compared to wind tunnel wake measurements on a floating wind turbine. Results in the near wake confirm that simulations and experiments tend to diverge from the expected linearized quasi-steady behavior when the reduced frequency exceeds 0.5. In the far wake, the impact of platform motion is overestimated by simulations and even seems to be oriented to the generation of a wake less prone to dissipation.
Roger Bergua, Amy Robertson, Jason Jonkman, Emmanuel Branlard, Alessandro Fontanella, Marco Belloli, Paolo Schito, Alberto Zasso, Giacomo Persico, Andrea Sanvito, Ervin Amet, Cédric Brun, Guillén Campaña-Alonso, Raquel Martín-San-Román, Ruolin Cai, Jifeng Cai, Quan Qian, Wen Maoshi, Alec Beardsell, Georg Pirrung, Néstor Ramos-García, Wei Shi, Jie Fu, Rémi Corniglion, Anaïs Lovera, Josean Galván, Tor Anders Nygaard, Carlos Renan dos Santos, Philippe Gilbert, Pierre-Antoine Joulin, Frédéric Blondel, Eelco Frickel, Peng Chen, Zhiqiang Hu, Ronan Boisard, Kutay Yilmazlar, Alessandro Croce, Violette Harnois, Lijun Zhang, Ye Li, Ander Aristondo, Iñigo Mendikoa Alonso, Simone Mancini, Koen Boorsma, Feike Savenije, David Marten, Rodrigo Soto-Valle, Christian W. Schulz, Stefan Netzband, Alessandro Bianchini, Francesco Papi, Stefano Cioni, Pau Trubat, Daniel Alarcon, Climent Molins, Marion Cormier, Konstantin Brüker, Thorsten Lutz, Qing Xiao, Zhongsheng Deng, Florence Haudin, and Akhilesh Goveas
Wind Energ. Sci., 8, 465–485, https://doi.org/10.5194/wes-8-465-2023, https://doi.org/10.5194/wes-8-465-2023, 2023
Short summary
Short summary
This work examines if the motion experienced by an offshore floating wind turbine can significantly affect the rotor performance. It was observed that the system motion results in variations in the load, but these variations are not critical, and the current simulation tools capture the physics properly. Interestingly, variations in the rotor speed or the blade pitch angle can have a larger impact than the system motion itself.
Jörg Alber, Marinos Manolesos, Guido Weinzierl-Dlugosch, Johannes Fischer, Alexander Schönmeier, Christian Navid Nayeri, Christian Oliver Paschereit, Joachim Twele, Jens Fortmann, Pier Francesco Melani, and Alessandro Bianchini
Wind Energ. Sci., 7, 943–965, https://doi.org/10.5194/wes-7-943-2022, https://doi.org/10.5194/wes-7-943-2022, 2022
Short summary
Short summary
This paper investigates the potentials and the limitations of mini Gurney flaps and their combination with vortex generators for improved rotor blade performance of wind turbines. These small passive add-ons are installed in order to increase the annual energy production by mitigating the effects of both early separation toward the root region and surface erosion toward the tip region of the blade. As such, this study contributes to the reliable and long-term generation of renewable energy.
Rodrigo Soto-Valle, Stefano Cioni, Sirko Bartholomay, Marinos Manolesos, Christian Navid Nayeri, Alessandro Bianchini, and Christian Oliver Paschereit
Wind Energ. Sci., 7, 585–602, https://doi.org/10.5194/wes-7-585-2022, https://doi.org/10.5194/wes-7-585-2022, 2022
Short summary
Short summary
This paper compares different vortex identification methods to evaluate their suitability to study the tip vortices of a wind turbine. The assessment is done through experimental data from the wake of a wind turbine model. Results show comparability in some aspects as well as significant differences, providing evidence to justify further comparisons. Therefore, this study proves that the selection of the most suitable postprocessing methods of tip vortex data is pivotal to ensure robust results.
Sirko Bartholomay, Tom T. B. Wester, Sebastian Perez-Becker, Simon Konze, Christian Menzel, Michael Hölling, Axel Spickenheuer, Joachim Peinke, Christian N. Nayeri, Christian Oliver Paschereit, and Kilian Oberleithner
Wind Energ. Sci., 6, 221–245, https://doi.org/10.5194/wes-6-221-2021, https://doi.org/10.5194/wes-6-221-2021, 2021
Short summary
Short summary
This paper presents two methods on how to estimate the lift force that is created by a wing. These methods were experimentally assessed in a wind tunnel. Furthermore, an active trailing-edge flap, as seen on airplanes for example, is used to alleviate fluctuating loads that are created within the employed wind tunnel. Thereby, an active flow control device that can potentially serve on wind turbines to lower fatigue or lower the material used for the blades is examined.
Rodrigo Soto-Valle, Sirko Bartholomay, Jörg Alber, Marinos Manolesos, Christian Navid Nayeri, and Christian Oliver Paschereit
Wind Energ. Sci., 5, 1771–1792, https://doi.org/10.5194/wes-5-1771-2020, https://doi.org/10.5194/wes-5-1771-2020, 2020
Short summary
Short summary
In this paper, a method to determine the angle of attack on a wind turbine rotor blade using a chordwise pressure distribution measurement was applied. The approach used a reduced number of pressure tap data located close to the blade leading edge. The results were compared with the measurements from three external probes mounted on the blade at different radial positions and with analytical calculations.
Jörg Alber, Rodrigo Soto-Valle, Marinos Manolesos, Sirko Bartholomay, Christian Navid Nayeri, Marvin Schönlau, Christian Menzel, Christian Oliver Paschereit, Joachim Twele, and Jens Fortmann
Wind Energ. Sci., 5, 1645–1662, https://doi.org/10.5194/wes-5-1645-2020, https://doi.org/10.5194/wes-5-1645-2020, 2020
Short summary
Short summary
The aerodynamic impact of Gurney flaps is investigated on the rotor blades of the Berlin Research Turbine. The findings of this research project contribute to performance improvements of different-size rotor blades. Gurney flaps are considered a worthwhile passive flow-control device in order to alleviate the adverse effects of both early separation in the inner blade region and leading-edge erosion throughout large parts of the blade span.
Matthew Lennie, Johannes Steenbuck, Bernd R. Noack, and Christian Oliver Paschereit
Wind Energ. Sci., 5, 819–838, https://doi.org/10.5194/wes-5-819-2020, https://doi.org/10.5194/wes-5-819-2020, 2020
Short summary
Short summary
This study presents a marriage of unsteady aerodynamics and machine learning. When airfoils are subjected to high inflow angles, the flow no longer follows the surface and the flow is said to be separated. In this flow regime, the forces experienced by the airfoil are highly unsteady. This study uses a range of machine learning techniques to extract infomation from test data to help us understand the flow regime and makes recomendations on how to model it.
Sebastian Perez-Becker, Francesco Papi, Joseph Saverin, David Marten, Alessandro Bianchini, and Christian Oliver Paschereit
Wind Energ. Sci., 5, 721–743, https://doi.org/10.5194/wes-5-721-2020, https://doi.org/10.5194/wes-5-721-2020, 2020
Short summary
Short summary
Aeroelastic design load calculations play a key role in determining the design loads of the different wind turbine components. This study compares load estimations from calculations using a Blade Element Momentum aerodynamic model with estimations from calculations using a higher-order Lifting-Line Free Vortex Wake aerodynamic model. The paper finds and explains the differences in fatigue and extreme turbine loads for power production simulations that cover a wide range of turbulent wind speeds.
Annette Claudia Klein, Sirko Bartholomay, David Marten, Thorsten Lutz, George Pechlivanoglou, Christian Navid Nayeri, Christian Oliver Paschereit, and Ewald Krämer
Wind Energ. Sci., 3, 439–460, https://doi.org/10.5194/wes-3-439-2018, https://doi.org/10.5194/wes-3-439-2018, 2018
Short summary
Short summary
The paper describes the experimental and numerical investigation of a model wind turbine with a diameter of 3.0 m in a narrow wind tunnel. The objectives of the study are the provision of validation data, the comparison and evaluation of methods of different fidelity, and the assessment of the influence of wind tunnel walls. It turned out that the accordance between the experimental and numerical results is good, but the wind tunnel walls have to be taken into account for the present setup.
Matthew Lennie, David Marten, George Pechlivanoglou, Christian Navid Nayeri, and Christian Oliver Paschereit
Wind Energ. Sci., 2, 671–683, https://doi.org/10.5194/wes-2-671-2017, https://doi.org/10.5194/wes-2-671-2017, 2017
Short summary
Short summary
Floating platform wind turbines present a challenge for engineers to simulate. This paper explores some better methods for simulating the aerodynamics of wind turbines as they move about on a floating platform. We also derived a new way of investigating whether the aerodynamics of the wind turbine rotor help it stay stable.
Related subject area
Control and system identification
Load reduction for wind turbines: an output-constrained, subspace predictive repetitive control approach
A reference open-source controller for fixed and floating offshore wind turbines
Experimental results of wake steering using fixed angles
Results from a wake-steering experiment at a commercial wind plant: investigating the wind speed dependence of wake-steering performance
Model-based design of a wave-feedforward control strategy in floating wind turbines
Wind inflow observation from load harmonics: initial steps towards a field validation
Control-oriented model for secondary effects of wake steering
Condition monitoring of roller bearings using acoustic emission
Model-free estimation of available power using deep learning
Automatic controller tuning using a zeroth-order optimization algorithm
Integrated wind farm layout and control optimization
Full-scale deformation measurements of a wind turbine rotor in comparison with aeroelastic simulations
Optimal closed-loop wake steering – Part 1: Conventionally neutral atmospheric boundary layer conditions
Grid-forming control strategies for black start by offshore wind power plants
Wind tunnel testing of wake steering with dynamic wind direction changes
Continued results from a field campaign of wake steering applied at a commercial wind farm – Part 2
Real-time optimization of wind farms using modifier adaptation and machine learning
Field testing of a local wind inflow estimator and wake detector
Design and analysis of a wake steering controller with wind direction variability
Periodic dynamic induction control of wind farms: proving the potential in simulations and wind tunnel experiments
Uncertainty identification of blade-mounted lidar-based inflow wind speed measurements for robust feedback–feedforward control synthesis
Validation of a lookup-table approach to modeling turbine fatigue loads in wind farms under active wake control
Wind direction estimation using SCADA data with consensus-based optimization
Initial results from a field campaign of wake steering applied at a commercial wind farm – Part 1
An active power control approach for wake-induced load alleviation in a fully developed wind farm boundary layer
Robust active wake control in consideration of wind direction variability and uncertainty
Automatic detection and correction of pitch misalignment in wind turbine rotors
Online model calibration for a simplified LES model in pursuit of real-time closed-loop wind farm control
Control design, implementation, and evaluation for an in-field 500 kW wind turbine with a fixed-displacement hydraulic drivetrain
Wind tunnel study on power output and yaw moments for two yaw-controlled model wind turbines
Towards practical dynamic induction control of wind farms: analysis of optimally controlled wind-farm boundary layers and sinusoidal induction control of first-row turbines
Determination of optimal wind turbine alignment into the wind and detection of alignment changes with SCADA data
System identification, fuzzy control and simulation of a kite power system with fixed tether length
A simulation study demonstrating the importance of large-scale trailing vortices in wake steering
Aero-elastic wind turbine design with active flaps for AEP maximization
Wind farms providing secondary frequency regulation: evaluating the performance of model-based receding horizon control
Field test of wake steering at an offshore wind farm
Iterative feedback tuning of wind turbine controllers
Articulated blade tip devices for load alleviation on wind turbines
Wind tunnel tests with combined pitch and free-floating flap control: data-driven iterative feedforward controller tuning
Periodic stability analysis of wind turbines operating in turbulent wind conditions
Basic controller tuning for large offshore wind turbines
Yichao Liu, Riccardo Ferrari, and Jan-Willem van Wingerden
Wind Energ. Sci., 7, 523–537, https://doi.org/10.5194/wes-7-523-2022, https://doi.org/10.5194/wes-7-523-2022, 2022
Short summary
Short summary
The objective of the paper is to develop a data-driven output-constrained individual pitch control approach, which will not only mitigate the blade loads but also reduce the pitch activities. This is achieved by only reducing the blade loads violating a user-defined bound, which leads to an economically viable load control strategy. The proposed control strategy shows promising results of load reduction in the wake-rotor overlapping and turbulent sheared wind conditions.
Nikhar J. Abbas, Daniel S. Zalkind, Lucy Pao, and Alan Wright
Wind Energ. Sci., 7, 53–73, https://doi.org/10.5194/wes-7-53-2022, https://doi.org/10.5194/wes-7-53-2022, 2022
Short summary
Short summary
The publication of the Reference Open-Source Controller (ROSCO) provides a controller and generic controller tuning process to the wind energy research community that can perform comparably or better than existing reference wind turbine controllers and includes features that are consistent with industry standards. Notably, ROSCO provides the first known open-source controller with features that specifically address floating offshore wind turbine control.
Paul Fleming, Michael Sinner, Tom Young, Marine Lannic, Jennifer King, Eric Simley, and Bart Doekemeijer
Wind Energ. Sci., 6, 1521–1531, https://doi.org/10.5194/wes-6-1521-2021, https://doi.org/10.5194/wes-6-1521-2021, 2021
Short summary
Short summary
The paper presents a new validation campaign of wake steering at a commercial wind farm. The campaign uses fixed yaw offset positions, rather than a table of optimal yaw offsets dependent on wind direction, to enable comparison with engineering models of wake steering. Additionally, by applying the same offset in beneficial and detrimental conditions, we are able to collect important data for assessing second-order wake model predictions.
Eric Simley, Paul Fleming, Nicolas Girard, Lucas Alloin, Emma Godefroy, and Thomas Duc
Wind Energ. Sci., 6, 1427–1453, https://doi.org/10.5194/wes-6-1427-2021, https://doi.org/10.5194/wes-6-1427-2021, 2021
Short summary
Short summary
Wake steering is a wind farm control strategy in which upstream wind turbines are misaligned with the wind to deflect their low-velocity wakes away from downstream turbines, increasing overall power production. Here, we present results from a two-turbine wake-steering experiment at a commercial wind plant. By analyzing the wind speed dependence of wake steering, we find that the energy gained tends to increase for higher wind speeds because of both the wind conditions and turbine operation.
Alessandro Fontanella, Mees Al, Jan-Willem van Wingerden, and Marco Belloli
Wind Energ. Sci., 6, 885–901, https://doi.org/10.5194/wes-6-885-2021, https://doi.org/10.5194/wes-6-885-2021, 2021
Short summary
Short summary
Floating wind is a key technology to harvest the abundant wind energy resource of deep waters. This research introduces a new way of controlling the wind turbine to better deal with the action of waves. The turbine is made aware of the incoming waves, and the information is exploited to enhance power production.
Marta Bertelè, Carlo L. Bottasso, and Johannes Schreiber
Wind Energ. Sci., 6, 759–775, https://doi.org/10.5194/wes-6-759-2021, https://doi.org/10.5194/wes-6-759-2021, 2021
Short summary
Short summary
A previously published wind sensing method is applied to an experimental dataset obtained from a 3.5 MW turbine and a nearby hub-tall met mast. The method uses blade load harmonics to estimate rotor-equivalent shears and wind directions at the rotor disk. Results indicate the good quality of the estimated shear, both in terms of 10 min averages and of resolved time histories, and a reasonable accuracy in the estimation of the yaw misalignment.
Jennifer King, Paul Fleming, Ryan King, Luis A. Martínez-Tossas, Christopher J. Bay, Rafael Mudafort, and Eric Simley
Wind Energ. Sci., 6, 701–714, https://doi.org/10.5194/wes-6-701-2021, https://doi.org/10.5194/wes-6-701-2021, 2021
Short summary
Short summary
This paper highlights the secondary effects of wake steering, including yaw-added wake recovery and secondary steering. These effects enhance the value of wake steering especially when applied to a large wind farm. This paper models these secondary effects using an analytical model proposed in the paper. The results of this model are compared with large-eddy simulations for several cases including 2-turbine, 3-turbine, 5-turbine, and 38-turbine cases.
Daniel Cornel, Francisco Gutiérrez Guzmán, Georg Jacobs, and Stephan Neumann
Wind Energ. Sci., 6, 367–376, https://doi.org/10.5194/wes-6-367-2021, https://doi.org/10.5194/wes-6-367-2021, 2021
Short summary
Short summary
Roller bearing failures in wind turbines' gearboxes lead to long downtimes and high repair costs. This paper should form a basis for the implementation of a predictive maintenance system. Therefore an acoustic-emission-based condition monitoring system is applied to roller bearing test rigs. The system has shown that a damaged surface can be detected at least ~ 4 % (8 h, regarding the time to failure) and possibly up to ~ 50 % (130 h) earlier than by using the vibration-based system.
Tuhfe Göçmen, Albert Meseguer Urbán, Jaime Liew, and Alan Wai Hou Lio
Wind Energ. Sci., 6, 111–129, https://doi.org/10.5194/wes-6-111-2021, https://doi.org/10.5194/wes-6-111-2021, 2021
Short summary
Short summary
Currently, the available power estimation is highly dependent on the pre-defined performance parameters of the turbine and the curtailment strategy followed. This paper proposes a model-free approach for a single-input dynamic estimation of the available power using RNNs. The unsteady patterns are represented by LSTM neurons, and the network is adapted to changing inflow conditions via transfer learning. Including highly turbulent flows, the validation shows easy compliance with the grid codes.
Daniel S. Zalkind, Emiliano Dall'Anese, and Lucy Y. Pao
Wind Energ. Sci., 5, 1579–1600, https://doi.org/10.5194/wes-5-1579-2020, https://doi.org/10.5194/wes-5-1579-2020, 2020
Short summary
Short summary
New wind turbine designs require updated control parameters, which should be optimal in terms of the performance measures that drive hardware design. We show how a zeroth-order optimization algorithm can randomly generate control parameters, use simulation results to estimate the gradient of the parameter space, and find an optimal set of those parameters. We then apply this automatic controller tuning procedure to three problems in wind turbine control.
Mads M. Pedersen and Gunner C. Larsen
Wind Energ. Sci., 5, 1551–1566, https://doi.org/10.5194/wes-5-1551-2020, https://doi.org/10.5194/wes-5-1551-2020, 2020
Short summary
Short summary
In this paper, the influence of optimal wind farm control and optimal wind farm layout is investigated in terms of power production. The capabilities of the developed optimization platform is demonstrated on the Swedish offshore wind farm, Lillgrund. It shows that the expected annual energy production can be increased by 4 % by integrating the wind farm control into the design of the wind farm layout, which is 1.2 % higher than what is achieved by optimizing the layout only.
Stephanie Lehnhoff, Alejandro Gómez González, and Jörg R. Seume
Wind Energ. Sci., 5, 1411–1423, https://doi.org/10.5194/wes-5-1411-2020, https://doi.org/10.5194/wes-5-1411-2020, 2020
Short summary
Short summary
The application of an optical measurement method for the determination of rotor blade deformation and torsion based on digital image correlation (DIC) is presented. Measurement results are validated by comparison with comparative measurement data. Finally, aeroelastic simulation results are compared to DIC results. It is shown that the measured deformation is in very good agreement with the simulations, and therefore DIC has great potential for the experimental validation of aeroelastic codes.
Michael F. Howland, Aditya S. Ghate, Sanjiva K. Lele, and John O. Dabiri
Wind Energ. Sci., 5, 1315–1338, https://doi.org/10.5194/wes-5-1315-2020, https://doi.org/10.5194/wes-5-1315-2020, 2020
Short summary
Short summary
Wake losses significantly reduce the power production of utility-scale wind farms since all wind turbines are operated in a greedy, individual power maximization fashion. In order to mitigate wake losses, collective wind farm operation strategies use wake steering, in which certain turbines are intentionally misaligned with respect to the incoming wind direction. The control strategy developed is dynamic and closed-loop to adapt to changing atmospheric conditions.
Anubhav Jain, Jayachandra N. Sakamuri, and Nicolaos A. Cutululis
Wind Energ. Sci., 5, 1297–1313, https://doi.org/10.5194/wes-5-1297-2020, https://doi.org/10.5194/wes-5-1297-2020, 2020
Short summary
Short summary
This paper provides an understanding of grid-forming control of wind turbines that can enable their black-start and islanding functionalities. Four control strategies have been tested with the aim to compare their capability to deal with the energization transients of an HVDC-connected offshore wind power plant, while maintaining stable offshore voltage and frequency. This is a step forward in overcoming wind turbine control challenges to provide black-start/restoration ancillary services.
Filippo Campagnolo, Robin Weber, Johannes Schreiber, and Carlo L. Bottasso
Wind Energ. Sci., 5, 1273–1295, https://doi.org/10.5194/wes-5-1273-2020, https://doi.org/10.5194/wes-5-1273-2020, 2020
Short summary
Short summary
The performance of an open-loop wake-steering controller is investigated with a new wind tunnel experiment. Three scaled wind turbines are placed on a large turntable and exposed to a turbulent inflow, resulting in dynamically varying wake interactions. The study highlights the importance of using a robust formulation and plant flow models of appropriate fidelity and the existence of possible margins for improvement by the use of dynamic controllers.
Paul Fleming, Jennifer King, Eric Simley, Jason Roadman, Andrew Scholbrock, Patrick Murphy, Julie K. Lundquist, Patrick Moriarty, Katherine Fleming, Jeroen van Dam, Christopher Bay, Rafael Mudafort, David Jager, Jason Skopek, Michael Scott, Brady Ryan, Charles Guernsey, and Dan Brake
Wind Energ. Sci., 5, 945–958, https://doi.org/10.5194/wes-5-945-2020, https://doi.org/10.5194/wes-5-945-2020, 2020
Short summary
Short summary
This paper presents the results of a field campaign investigating the performance of wake steering applied at a section of a commercial wind farm. It is the second phase of the study for which the first phase was reported in a companion paper (https://wes.copernicus.org/articles/4/273/2019/). The authors implemented wake steering on two turbine pairs and compared results with the latest FLORIS model of wake steering, showing good agreement in overall energy increase.
Leif Erik Andersson and Lars Imsland
Wind Energ. Sci., 5, 885–896, https://doi.org/10.5194/wes-5-885-2020, https://doi.org/10.5194/wes-5-885-2020, 2020
Short summary
Short summary
The article describes a hybrid modeling approach to optimize the energy capture of wind farms. Hybrid modeling combines mechanistic and
data-driven models. The data-driven part is used to correct inaccuracies of the mechanistic model. The hybrid approach allows for adjustment of the mechanistic model beyond simple parameter estimation. It is, therefore, an attractive approach in wind farm control. The approach is illustrated in several numerical case studies.
Johannes Schreiber, Carlo L. Bottasso, and Marta Bertelè
Wind Energ. Sci., 5, 867–884, https://doi.org/10.5194/wes-5-867-2020, https://doi.org/10.5194/wes-5-867-2020, 2020
Short summary
Short summary
This paper validates a method to estimate the vertical wind shear and detect the presence and location of an impinging wake with field data. Shear and wake awareness have multiple uses, from turbine and farm control to monitoring and forecasting.
Results indicate a very good correlation between the estimated vertical shear and the one measured by a met mast and a remarkable ability to locate and track the motion of an impinging wake on an affected rotor.
Eric Simley, Paul Fleming, and Jennifer King
Wind Energ. Sci., 5, 451–468, https://doi.org/10.5194/wes-5-451-2020, https://doi.org/10.5194/wes-5-451-2020, 2020
Short summary
Short summary
Wind farm wake losses occur when turbines operate in the wakes of upstream turbines. However, wake steering control can be used to deflect wakes away from downstream turbines. A method for including wind direction variability in wake steering simulations is presented here. Controller performance is shown to improve when wind direction variability is accounted for. Furthermore, the importance of wind direction variability is shown for different turbine spacings and atmospheric conditions.
Joeri Alexis Frederik, Robin Weber, Stefano Cacciola, Filippo Campagnolo, Alessandro Croce, Carlo Bottasso, and Jan-Willem van Wingerden
Wind Energ. Sci., 5, 245–257, https://doi.org/10.5194/wes-5-245-2020, https://doi.org/10.5194/wes-5-245-2020, 2020
Short summary
Short summary
The interaction between wind turbines in a wind farm through their wakes is a widely studied research area. Until recently, research was focused on finding constant turbine inputs that optimize the performance of the wind farm. However, recent studies have shown that time-varying, dynamic inputs might be more beneficial. In this paper, the validity of this approach is further investigated by implementing it in scaled wind tunnel experiments and assessing load effects, showing promising results.
Róbert Ungurán, Vlaho Petrović, Lucy Y. Pao, and Martin Kühn
Wind Energ. Sci., 4, 677–692, https://doi.org/10.5194/wes-4-677-2019, https://doi.org/10.5194/wes-4-677-2019, 2019
Short summary
Short summary
A novel lidar-based sensory system for wind turbine control is proposed. The main contributions are the parametrization method of the novel measurement system, the identification of possible sources of measurement uncertainty, and their modelling. Although not the focus of the submitted paper, the mentioned contributions represent essential building blocks for robust feedback–feedforward wind turbine control development which could be used to improve wind turbine control strategies.
Hector Mendez Reyes, Stoyan Kanev, Bart Doekemeijer, and Jan-Willem van Wingerden
Wind Energ. Sci., 4, 549–561, https://doi.org/10.5194/wes-4-549-2019, https://doi.org/10.5194/wes-4-549-2019, 2019
Short summary
Short summary
Within wind farms, the wind turbines interact with each other through their wakes. Turbines operating in these wakes have lower power production and increased wear and tear. Wake redirection is control strategy to steer the wakes aside from downstream turbines, increasing the power yield of the farm. Models for predicting the power gain and impacts on wear exist, but they are still immature and require validation. The validation of such a model is the purpose of this paper.
Jennifer Annoni, Christopher Bay, Kathryn Johnson, Emiliano Dall'Anese, Eliot Quon, Travis Kemper, and Paul Fleming
Wind Energ. Sci., 4, 355–368, https://doi.org/10.5194/wes-4-355-2019, https://doi.org/10.5194/wes-4-355-2019, 2019
Short summary
Short summary
Typically, turbines do not share information with nearby turbines in a wind farm. Relying on a single turbine sensor on the back of a turbine nacelle can lead to large errors in yaw misalignment or excessive yawing due to noisy sensor measurements. The wind farm consensus control approach in this paper shows the benefits of sharing information between nearby turbines by computing a robust estimate of the wind direction using noisy sensor information from these neighboring turbines.
Paul Fleming, Jennifer King, Katherine Dykes, Eric Simley, Jason Roadman, Andrew Scholbrock, Patrick Murphy, Julie K. Lundquist, Patrick Moriarty, Katherine Fleming, Jeroen van Dam, Christopher Bay, Rafael Mudafort, Hector Lopez, Jason Skopek, Michael Scott, Brady Ryan, Charles Guernsey, and Dan Brake
Wind Energ. Sci., 4, 273–285, https://doi.org/10.5194/wes-4-273-2019, https://doi.org/10.5194/wes-4-273-2019, 2019
Short summary
Short summary
Wake steering is a form of wind farm control in which turbines use yaw offsets to affect wakes in order to yield an increase in total energy production. In this first phase of a study of wake steering at a commercial wind farm, two turbines implement a schedule of offsets. For two closely spaced turbines, an approximate 14 % increase in energy was measured on the downstream turbine over a 10° sector, with a 4 % increase in energy production of the combined turbine pair.
Mehdi Vali, Vlaho Petrović, Gerald Steinfeld, Lucy Y. Pao, and Martin Kühn
Wind Energ. Sci., 4, 139–161, https://doi.org/10.5194/wes-4-139-2019, https://doi.org/10.5194/wes-4-139-2019, 2019
Short summary
Short summary
A new active power control (APC) approach is investigated to simultaneously reduce the wake-induced power tracking errors and structural fatigue loads of individual turbines within a wind farm. The non-unique solution of the APC problem with respect to the distribution of the individual powers is exploited. The simple control architecture and practical measurement system make the proposed approach prominent for real-time control of large wind farms with turbulent flows and wakes.
Andreas Rott, Bart Doekemeijer, Janna Kristina Seifert, Jan-Willem van Wingerden, and Martin Kühn
Wind Energ. Sci., 3, 869–882, https://doi.org/10.5194/wes-3-869-2018, https://doi.org/10.5194/wes-3-869-2018, 2018
Short summary
Short summary
Active wake deflection (AWD) aims to increase the power output of a wind farm by misaligning the yaw of upstream turbines. We analysed the effect of dynamic wind direction changes on AWD. The results show that AWD is very sensitive towards these dynamics. Therefore, we present a robust active wake control, which considers uncertainties and wind direction changes, increasing the overall power output of a wind farm. A side effect is a significant reduction of the yaw actuation of the turbines.
Marta Bertelè, Carlo L. Bottasso, and Stefano Cacciola
Wind Energ. Sci., 3, 791–803, https://doi.org/10.5194/wes-3-791-2018, https://doi.org/10.5194/wes-3-791-2018, 2018
Short summary
Short summary
This work presents a new fully automated method to correct for
pitch misalignment imbalances of wind turbine rotors. The method
has minimal requirements, as it only assumes the availability of a
sensor of sufficient accuracy and bandwidth to detect the 1P
harmonic to the desired precision and the ability to command the
pitch setting of each blade independently from the others.
Extensive numerical simulations are used to demonstrate the new
procedure.
Bart M. Doekemeijer, Sjoerd Boersma, Lucy Y. Pao, Torben Knudsen, and Jan-Willem van Wingerden
Wind Energ. Sci., 3, 749–765, https://doi.org/10.5194/wes-3-749-2018, https://doi.org/10.5194/wes-3-749-2018, 2018
Short summary
Short summary
Most wind farm control algorithms in the literature rely on a simplified mathematical model that requires constant calibration to the current conditions. This paper provides such an estimation algorithm for a dynamic model capturing the turbine power production and flow field at hub height. Performance was demonstrated in high-fidelity simulations for two-turbine and nine-turbine farms, accurately estimating the ambient conditions and wind field inside the farms at a low computational cost.
Sebastiaan Paul Mulders, Niels Frederik Boudewijn Diepeveen, and Jan-Willem van Wingerden
Wind Energ. Sci., 3, 615–638, https://doi.org/10.5194/wes-3-615-2018, https://doi.org/10.5194/wes-3-615-2018, 2018
Short summary
Short summary
The modeling, operating strategy, and controller design for an actual in-field wind turbine with a fixed-displacement hydraulic drivetrain are presented. An analysis is given on a passive torque control strategy for below-rated operation. The turbine lacks the option to influence the system torque by a generator, so the turbine is regulated by a spear valve in the region between below- and above-rated operation. The control design is evaluated on a real-world 500 kW hydraulic wind turbine.
Jan Bartl, Franz Mühle, and Lars Sætran
Wind Energ. Sci., 3, 489–502, https://doi.org/10.5194/wes-3-489-2018, https://doi.org/10.5194/wes-3-489-2018, 2018
Short summary
Short summary
Our experimental wind tunnel study on a pair of model wind turbines demonstrates a significant potential of turbine yaw angle control for the combined optimization of turbine power and rotor loads. Depending on the turbines' relative positions to the incoming wind, a combined power increase and individual rotor load reduction can be achieved by operating the turbine rotors slightly misaligned with the main wind direction (i.e., at a certain yaw angle).
Wim Munters and Johan Meyers
Wind Energ. Sci., 3, 409–425, https://doi.org/10.5194/wes-3-409-2018, https://doi.org/10.5194/wes-3-409-2018, 2018
Short summary
Short summary
Wake interactions in wind farms result in power losses for downstream turbines. We aim to mitigate these losses through coordinated control of the induced slowdown of the wind by each turbine. We further analyze results from earlier work towards the utilization of such control strategies in practice. Coherent vortex shedding is identified and mimicked by a sinusoidal control. The latter is shown to increase power in downstream turbines and is robust to turbine spacing and turbulence intensity.
Niko Mittelmeier and Martin Kühn
Wind Energ. Sci., 3, 395–408, https://doi.org/10.5194/wes-3-395-2018, https://doi.org/10.5194/wes-3-395-2018, 2018
Short summary
Short summary
Upwind horizontal axis wind turbines need to be aligned with the main wind direction to maximize energy yield. This paper presents new methods to improve turbine alignment and detect changes during operational lifetime with standard nacelle met mast instruments. The flow distortion behind the rotor is corrected with a multilinear regression model and two alignment changes are detected with an accuracy of ±1.4° within 3 days of operation after the change is introduced.
Tarek N. Dief, Uwe Fechner, Roland Schmehl, Shigeo Yoshida, Amr M. M. Ismaiel, and Amr M. Halawa
Wind Energ. Sci., 3, 275–291, https://doi.org/10.5194/wes-3-275-2018, https://doi.org/10.5194/wes-3-275-2018, 2018
Paul Fleming, Jennifer Annoni, Matthew Churchfield, Luis A. Martinez-Tossas, Kenny Gruchalla, Michael Lawson, and Patrick Moriarty
Wind Energ. Sci., 3, 243–255, https://doi.org/10.5194/wes-3-243-2018, https://doi.org/10.5194/wes-3-243-2018, 2018
Short summary
Short summary
This paper investigates the role of flow structures in wind farm control through yaw misalignment. A pair of counter-rotating vortices is shown to be important in deforming the shape of the wake. Further, we demonstrate that the vortex structures created in wake steering can enable a greater change power generation than currently modeled in control-oriented models. We propose that wind farm controllers can be made more effective if designed to take advantage of these effects.
Michael K. McWilliam, Thanasis K. Barlas, Helge A. Madsen, and Frederik Zahle
Wind Energ. Sci., 3, 231–241, https://doi.org/10.5194/wes-3-231-2018, https://doi.org/10.5194/wes-3-231-2018, 2018
Short summary
Short summary
Maximizing wind energy production is challenging because the winds are always changing. Design optimization was used to explore how flaps can give rotor design engineers greater ability to adapt the rotor for different conditions. For rotors designed for peak efficiency (i.e. older designs) the flap adds 0.5 % improvement in energy production. However, for modern designs that optimize both the performance and the structure, the flap can provide a 1 % improvement.
Carl R. Shapiro, Johan Meyers, Charles Meneveau, and Dennice F. Gayme
Wind Energ. Sci., 3, 11–24, https://doi.org/10.5194/wes-3-11-2018, https://doi.org/10.5194/wes-3-11-2018, 2018
Short summary
Short summary
We investigate the capability of wind farms to track a power reference signal to help ensure reliable power grid operations. The wind farm controller is based on a simple dynamic wind farm model and tested using high-fidelity simulations. We find that the dynamic nature of the wind farm model is vital for tracking the power signal, and the controlled wind farm would pass industry performance tests in most cases.
Paul Fleming, Jennifer Annoni, Jigar J. Shah, Linpeng Wang, Shreyas Ananthan, Zhijun Zhang, Kyle Hutchings, Peng Wang, Weiguo Chen, and Lin Chen
Wind Energ. Sci., 2, 229–239, https://doi.org/10.5194/wes-2-229-2017, https://doi.org/10.5194/wes-2-229-2017, 2017
Short summary
Short summary
In this paper, a field test of wake-steering control is presented. In the campaign, an array of turbines within an operating commercial offshore wind farm have the normal yaw controller modified to implement wake steering according to a yaw control strategy. Results indicate that, within the certainty afforded by the data, the wake-steering controller was successful in increasing power capture.
Edwin van Solingen, Sebastiaan Paul Mulders, and Jan-Willem van Wingerden
Wind Energ. Sci., 2, 153–173, https://doi.org/10.5194/wes-2-153-2017, https://doi.org/10.5194/wes-2-153-2017, 2017
Short summary
Short summary
The aim of this paper is to show that with an automated tuning strategy, wind turbine control performance can be significantly increased. To this end, iterative feedback tuning (IFT) is applied to two different turbine controllers. The results obtained by high-fidelity simulations indicate significant performance improvements over baseline controllers. It is concluded that IFT of turbine controllers has the potential to become a valuable tool for improving wind turbine performance.
Carlo L. Bottasso, Alessandro Croce, Federico Gualdoni, Pierluigi Montinari, and Carlo E. D. Riboldi
Wind Energ. Sci., 1, 297–310, https://doi.org/10.5194/wes-1-297-2016, https://doi.org/10.5194/wes-1-297-2016, 2016
Short summary
Short summary
The paper discusses different concepts for reducing loads on wind turbines using movable blade tips. Passive and semi-passive tip solutions move freely in response to air load fluctuations, while in the active case an actuator drives the tip motion in response to load measurements. The various solutions are compared with a standard blade and with each other in terms of their ability to reduce both fatigue and extreme loads.
Sachin T. Navalkar, Lars O. Bernhammer, Jurij Sodja, Edwin van Solingen, Gijs A. M. van Kuik, and Jan-Willem van Wingerden
Wind Energ. Sci., 1, 205–220, https://doi.org/10.5194/wes-1-205-2016, https://doi.org/10.5194/wes-1-205-2016, 2016
Short summary
Short summary
In order to reduce the cost of wind energy, it is necessary to reduce the loads that wind turbines withstand over their lifetime. The combination of blade rotation with newly designed blade shape changing actuators is demonstrated experimentally. While load reduction is achieved, the additional flexibility implies that careful control design is needed to avoid instability.
Riccardo Riva, Stefano Cacciola, and Carlo Luigi Bottasso
Wind Energ. Sci., 1, 177–203, https://doi.org/10.5194/wes-1-177-2016, https://doi.org/10.5194/wes-1-177-2016, 2016
Short summary
Short summary
This paper presents a method to assess the stability of a wind turbine. The proposed approach uses the recorded time history of the system response and fits to it a periodic reduced-order model that can handle stochastic disturbances. Stability is computed by using Floquet theory on the reduced-order model. Since the method only uses response data, it is applicable to any simulation model as well as to experimental test data. The method is compared to the well-known operational modal analysis.
Karl O. Merz
Wind Energ. Sci., 1, 153–175, https://doi.org/10.5194/wes-1-153-2016, https://doi.org/10.5194/wes-1-153-2016, 2016
Short summary
Short summary
Wind turbines are controlled through the electrical torque on the generator and the pitch of the blades. The tuning of the controller determines the dynamics of the system, which can then be good (smooth yet responsive) or bad (ineffective or unstable). A methodical investigation was conducted to determine the minimal model of the wind turbine structure and aerodynamics that can be used to tune the controller gains for large, multi-MW offshore wind turbines.
Cited articles
Andersen, P. B.: Advanced Load Alleviation for Wind Turbines using Adaptive
Trailing Edge Flaps: Sensoring and Control, PhD thesis, Technical University of Denmark, Risø, Denmark, 2010. a
Andersen, P. B., Henriksen, L., Gaunaa, M., Bak, C., and Buhl, T.: Deformable
trailing edge flaps for modern megawatt wind turbine controllers using strain
gauge sensors, Wind Energy, 13, 193–206, https://doi.org/10.1002/we.371, 2010. a
Bak, C., Madsen, H. A., and Johansen, J.: Influence from Blade-Tower
Interaction on Fatigue Loads and Dynamics, in: Proceedings of the 2001 European Wind Energy Conference and Exhibition, Copenhagen, Denmark, 394–397, 2001. a
Barlas, T. and van Kuik, G. A. M.: Review of State of the Art in Smart Rotor
Control Research for Wind Turbines, Prog. Aerosp. Sci., 46, 1–27, https://doi.org/10.1016/j.paerosci.2009.08.002, 2010. a
Barlas, T., van der Veen, G., and van Kuik, G. A. M.: Model Predictive Control for Wind Turbines with Distributed Active Flaps: Incorporating Inflow Signals and Actuator Constraints, Wind Energy, 15, 757–771, https://doi.org/10.1002/we.503, 2012. a, b
Barlas, T., Tibaldi, C., Zahle, F., and Madsen, H. A.: Aeroelastic Optimization of a 10 MW Wind Turbine Blade with Active Trailing Edge Flaps,
in: 34th Wind Energy Symposium, 4–8 January 2016, San Diego, CA, USA, 1–11, https://doi.org/10.2514/6.2016-1262, 2016a. a
Barlas, T., Olsen, A. S., Madsen, H. A., Andersen, T. L., Ai, Q., and Weaver,
P. M.: Aerodynamic and Load Control Performance Testing of a Morphing Trailing Edge Flap System on an Outdoor Rotating Test Rig, J. Phys.: Conf. Ser., 1037, 022018, https://doi.org/10.1088/1742-6596/1037/2/022018, 2018. a, b
Bartholomay, S., Mihos, G., Perez-Becker, S., Pechlivanoglou, G., Nayeri,
C. N., Nikolaou, G., and Paschereit, C. O.: Towards Active Flow Control on a
Research Scale Wind Turbine Using Trailing Edge Flaps, in: AIAA SciTech
Proceedings 2018, Kissimee, Florida, USA, https://doi.org/10.2514/6.2018-1245, 2018. a, b
Bartholomay, S., Wester, T. T. B., Perez-Becker, S., Konze, S., Menzel, C., Hölling, M., Spickenheuer, A., Peinke, J., Nayeri, C. N., Paschereit, C. O., and Oberleithner, K.: Pressure-based lift estimation and its application to feedforward load control employing trailing-edge flaps, Wind Energ. Sci., 6, 221–245, https://doi.org/10.5194/wes-6-221-2021, 2021. a
Behrens, T. and Zhu, W. J.: Feasibility of Aerodynamic Flap Hinge Moment
Measurements as Input for Load Alleviation Control, in: Proc. of EWEA 2011,
Brussels, Belgium, 1–8, 2011. a
Berg, D., Wilson, D., Barone, M., Resor, B., Berg, J., Paquette, J., Zayas, J., Kota, S., Ervin, G., and Maric, D.: The Impact of Active Aerodynamic Load
Control on Fatigue and Energy Capture at Low Wind Speed Sites, in: European
Wind Energy Conference & Exhibition 2009, Marseille, France, 2670–2679, available at: https://www.osti.gov/biblio/1141815 (last access: 19 May 2021), 2009. a
Bergami, L. and Gaunaa, M.: ATEFlap Aerodynamic Model, a Dynamic Stall Model
Including the Effects of Trailing Edge Flap Deflection, Tech. Rep. Risø-R-1792, DTU Wind Energy, Risø, Denmark, available at: https://orbit.dtu.dk/files/6599679/ris-r-1792.pdf (last access: 19 May 2021), 2012. a
Bergami, L. and Gaunaa, M.: Analysis of Aeroelastic Loads and their
Contributions to Fatigue Damage, J. Phys.: Conf. Ser., 555, 012007, https://doi.org/10.1088/1742-6596/555/1/012007, 2014. a, b
Bergami, L. and Poulsen, N.: A Smart Rotor Configuration with Linear Quadratic Control of Adaptive Trailing Edge Flaps for Active Load Alleviation, Wind Energy, 18, 625–641, https://doi.org/10.1002/we.1716, 2015. a
Bernhammer, L., van Kuik, G. A. M., and De Breuker, R.: Fatigue and extreme
load reduction of wind turbine components using smart rotors, J. Wind Eng. Indust. Aerodynam., 154, 84–95, https://doi.org/10.1016/j.jweia.2016.04.001, 2016. a
Bertelè, M., Bottasso, C. L., Cacciola, S., Daher Adegas, F., and Delport, S.: Wind inflow observation from load harmonics, Wind Energ. Sci., 2, 615–640, https://doi.org/10.5194/wes-2-615-2017, 2017. a
Borg, M., Mirzaei, M., and Bredmose, H.: LIFES50+ Deliverable D1.2: Wind
Turbine Models for the Design, Tech. Rep. E-101, DTU Wind Energy, Risø,
Denmark, 2015. a
Bossanyi, E. A.: Individual Blade Pitch Control for Load Reduction, Wind
Energy, 6, 119–128, https://doi.org/10.1002/we.76, 2003. a
Burger, B.: Power Generation in Germany – Assesment of 2017, Tech. rep.,
Fraunhofer Institute for Solar Energy Systems ISE, Freiburg, Germany, available at:
https://www.ise.fraunhofer.de/content/dam/ise/en/documents/publications/studies/Stromerzeugung_2017_e.pdf
(last access: 19 May 2021), 2018. a
Chaviaropoulos, P., Karga, I., Harkness, C., and Hendriks, B.: INNWIND
Deliverable 1.23: PI-Based Assesment of Innovative Concepts (Methodological
Issues), Tech. rep., INNWIND.eu, available at:
http://www.innwind.eu/publications/deliverable-reports (last access: 19 May 2021), 2014. a
Chen, Z., Stol, K., and Mace, B.: System Identification and Controller Design
for individual Pitch and Trailing Edge Flap Control on upscaled Wind Turbines, Wind Energy, 19, 1073–1088, https://doi.org/10.1002/we.1885, 2016. a, b
Chen, Z., Stol, K., and Mace, B.: Wind turbine Blade Optimisation with
Individual Pitch and Trailing Edge Flap Control, Renew. Energy, 103, 750–765, https://doi.org/10.1016/j.renene.2016.11.009, 2017. a, b
Cooperman, A. and Martinez, M.: Load Monitoring for Active Control of Wind
Turbines, Renew. Sustain. Energ. Rev., 41, 189–201,
https://doi.org/10.1016/j.rser.2014.08.029, 2015. a, b, c
Damiani, R., Dana, S., Annoni, J., Fleming, P., Roadman, J., van Dam, J., and
Dykes, K.: Assessment of Wind Turbine Component Loads Under Yaw-Offset
Conditions, Wind Energ. Sci., 3, 173–189, https://doi.org/10.5194/wes-3-173-2018, 2018. a
Engels, W. P., Kanev, S., and van Engelen, T.: Distributed Blade Control, in:
Torque: The Science of Making Torque from Wind, Heraklion, Greece, available at:
https://www.researchgate.net/publication/265063622_Distributed_Blade_Control (last access: 19 May 2021), 2010. a
Fisher, A. and Madsen, H. A.: Investigation of the theoretical load alleviation potential using trailing edge flaps controlled by inflow data,
Wind Energy, 19, 1567–1583, https://doi.org/10.1002/we.1937, 2016. a
Hansen, M. H., Henriksen, L. C., Hartvig, M., and Christian, L.: Basic DTU
Wind Energy Controller, Tech. Rep. E-0028, DTU Wind Energy, Risø, Denmark, 2013. a
Hariharan, N. and Leishman, J. G.: Unsteady Aerodynamics of a Flapped Airfoil
in Subsonic Flow by Indicial Concepts, in: Proc. of the AIAA 36th Structures, Structural Dynamics and Materials Conference, New Orleans, 613–634, https://doi.org/10.2514/6.1995-1228, 1995. a
Henriksen, L. C., Bergami, L., and Andersen, P. B.: A Model Based Control
Methodology combining Blade Pitch and Adaptive Trailing Edge Flaps in a
common Framework, in: Proceedings of the EWEA, Vienna, Austria, available at:
https://orbit.dtu.dk/en/publications/a-model-based-control-methodology-combining-blade-pitch (last access: 19 May 2021), 2013. a
Iribas, M., Hansen, M. H., Mahmood, M., Tibaldi, C., Natarajan, A., Bossanyi,
E., Stock, A., Jamieson, P., Leithead, W., and Schlipf, D.: INNWIND
Deliverable 1.42: Methodology for Feed-Forward Control Strategies using
Nacelle or Blade Based Sensors and Distributed Control, Tech. rep.,
INNWIND.eu, available at: http://www.innwind.eu/publications/deliverable-reports (last access: 19 May 2021), 2015. a
Jamieson, P.: Innovation in Wind Turbine Design, 2nd Edn., John Wiley & Sons Ltd., West Sussex, UK, 2018. a
Jones, B. L., Lio, W. H., and Rossiter, J. A.: Overcoming fundamental
limitations of wind turbine individual blade pitch control with inflow sensors, Wind Energy, 21, 922–936, https://doi.org/10.1002/we.2205, 2018. a, b, c, d
Jonkman, J.: Modeling of the UAE Wind Turbine for Refinement of FAST_AD,
Tech. Rep. TP-500-34755, NREL, Golden, Colorado, 2003. a
Jonkman, J., Butterfield, S., Musial, W., and Scott, G.: Definition of a 5-MW
Reference Wind Turbine for Offshore System Development, Tech. Rep. TP-500-38060, NREL, Golden, Colorado, 2009. a
Kanda, A. and Dowell, E. H.: Worst-case gust-response analysis for typical
airfoil section with control surface, J. Aircraft, 42, 956–962,
https://doi.org/10.2514/1.8931, 2005. a
Kracht, P., Perez-Becker, S., Richard, J. B., and Fischer, B.: Performance
Improvement of a Point Absorber Wave Energy Converter by Application of an
Observer-Based Control: Results From Wave Tank Testing, IEEE T. Indust. Appl., 51, 3426–3434, https://doi.org/10.1109/TIA.2015.2405892, 2015. a, b
Lackner, M. and van Kuik, G. A. M.: A Comparison of Smart Rotor Control
Approaches using Trailing Edge Flaps and individual Pitch Control, Wind
Energy, 13, 117–134, https://doi.org/10.1002/we.353, 2010. a
Madsen, H. A., Larsen, T. J., Pirrung, G. R., Li, A., and Zahle, F.:
Implementation of the Blade Element Momentum Model on a Polar Grid and its
Aeroelastic Load Impact, Wind Energ. Sci., 5, 1–27, https://doi.org/10.5194/wes-5-1-2020, 2020. a
Manolas, D., Spyropoulos, N., Serafeim, G., Riziotis, V., Chaviaropoulos, P.,
and Voutsinas, S.: Inflow-based Flap Control on a 10 MW-Scale Wind Turbine
Using a Spinner Anemometer, J. Phys.: Conf. Ser., 1037, 032045, https://doi.org/10.1088/1742-6596/1037/3/032045, 2018. a
Marten, D., Pechlivanoglou, G., Nayeri, C. N., and Paschereit, C. O.:
Integration of a WT Blade Design tool in XFOIL/XFLR5, in: 10th German Wind Energy Conference (DEWEK 2010), Bremen, Germany, available at:
https://www.researchgate.net/publication/275638785_Integration_of_a_WT_Blade_Design_Tool_in_XFoilXFLR5 (last access: 19 May 2021), 2010. a
Marten, D., Lennie, M., Pechlivanoglou, G., Nayeri, C. N., and Paschereit,
C. O.: Implementation, Optimization and Validation of a Nonlinear Lifting
Line-Free Vortex Wake Module within the Wind Turbine Simulation Code QBlade, ASME J. Eng. Gas Turb. Power, 138, 072601, https://doi.org/10.1115/GT2015-43265, 2015. a
Moriarty, P. and Hansen, A.: AeroDyn Theory Manual, Tech. Rep. EL-500-36881,
NREL, Golden, Colorado, https://doi.org/10.2172/15014831, 2005. a
Navalkar, S. T., Van Wingerden, J. W., Van Solingen, E., Oomen, T., and van Kuik, G. A. M.: Subspace Predictive Repetitive Control for Wind Turbine Load Alleviation using Trailing Edge Flaps, in: Proceedings of the American
Control Conference, Portland, USA, 4422–4427, https://doi.org/10.1109/ACC.2014.6859094, 2014. a
Ng, B., Palacios, R., Kerrigan, E., Graham, M., and Hesse, H.: Aerodynamic
load control in horizontal axis wind turbines with combined aeroelastic
tailoring and trailing-edge flaps, Wind Energy, 19, 243–263,
https://doi.org/10.1002/we.1830, 2016. a
NREL: FAST v8.15, available at: https://www.nrel.gov/wind/nwtc/fastv8.html,last access: 19 May 2021. a
Perez-Becker, S., Papi, F., Saverin, J., Marten, D., Bianchini, A., and
Paschereit, C. O.: Is the Blade Element Momentum theory overestimating wind
turbine loads? – An aeroelastic comparison between OpenFAST's AeroDyn and
QBlade's Lifting-Line Free Vortex Wake method, Wind Energ. Sci., 5, 721–743, https://doi.org/10.5194/wes-5-721-2020, 2020. a, b, c
Perez-Becker, S., Marten, D., Nayeri, C. N., and Paschereit, C. O.:
Implementation and Validation of an Advanced Wind Energy Controller in
Aero-Servo-Elastic Simulations Using the Lifting Line Free Vortex Wake
Model, Energies, 14, 783, https://doi.org/10.3390/en14030783, 2021. a, b
Plumley, C.: The Smart Rotor Wind Turbine, PhD thesis, University of
Strathclyde, Strathclyde, 2015. a
Plumley, C., Graham, M., Leithead, W., Bossanyi, E. A., and Jamieson, P.:
Supplementing Wind Turbine Pitch Control with a Trailing Edge Flap Smart Rotor, in: Proceedings of the 3rd Renewable Power Generation Conference (RPG 2014), Naples, Italy, 1–6, https://doi.org/10.1049/cp.2014.0919, 2014a.
a
Plumley, C., Leithead, W., Jamieson, P., Bossanyi, E. A., and Graham, M.:
Comparison of individual Pitch and Smart Rotor Control Strategies for Load
Reduction, J. Phys.: Conf. Ser., 524, 012054, https://doi.org/10.1088/1742-6596/524/1/012054, 2014b. a
Simley, E. and Pao, L.: Evaluation of a Wind Speed Estimator for effective
Hub-Height and Shear Components, Wind Energy, 19, 167–184, https://doi.org/10.1002/we.1817, 2016. a
Tasora, A., Serban, R., Mazhar, H., Pazouki, A., Melanz, D., Fleischmann, J.,
Taylor, M., Sugiyama, H., and Negrut, D.: Chrono: An Open Source Multi-Physics Dynamics Engine, in: Proceedings of the International Conference on High Performance Computing in Science and Engineering, Solan, Czech Republic, 19–49, https://doi.org/10.1007/978-3-319-40361-8_2, 2016. a
TU Berlin: QBlade, available at: https://www.qblade.org/, last access: 19 May 2021. a
Ungurán, R., Petrović, V., Pao, L. Y., and Kühn, M.: Performance Evaluation of a Blade-Mounted LiDAR with Dynamic Versus Fixed Parameters through Feedback-Feedforward Individual Pitch and Trailing Edge Flap Control, J. Phys.: Conf. Ser., 1037, 032004, https://doi.org/10.1088/1742-6596/1037/3/032004, 2018. a
Wendler, J., Marten, D., Pechlivanoglou, G., Nayeri, C. N., and Paschereit,
C. O.: An Unsteady Aerodynamics Model for Lifting Line Free Vortex Wake
Simulations of HAWT and VAWT in QBlade, in: Proceedings of ASME Turbo Expo:
Turbine Technical Conference and Exposition GT2016, Seoul, South Korea, V009T46A011, https://doi.org/10.1115/GT2016-57184, 2016. a
Wilson, D., Berg, D., Resor, B., Barone, M., and Berg, J.: Combined Individual Pitch Control and Active Aerodynamic Load Controller Investigation for the 5 MW Upwind Turbine, in: AWEA Wind Power Conference & Exhibition,
Chicago, USA, 1–12, available at:
https://energy.sandia.gov/wp-content/gallery/uploads/AWEA-092875C.pdf (last access: 19 May 2021), 2009. a
Zhang, M., Tan, B., and Xu, J.: Smart fatigue load control on the large-scale
wind turbine blades using different sensing signals, Renew. Energy, 87, 111–119, https://doi.org/10.1016/j.renene.2015.10.011, 2016. a, b
Short summary
Active trailing edge flaps can potentially enable further increases in wind turbine sizes without the disproportionate increase in loads, thus reducing the cost of wind energy even further. Extreme loads and critical deflections of the turbine blade are design-driving issues that can effectively be reduced by flaps. This paper considers the flap hinge moment as an input sensor for a flap controller that reduces extreme loads and critical deflections of the blade in turbulent wind conditions.
Active trailing edge flaps can potentially enable further increases in wind turbine sizes...
Altmetrics
Final-revised paper
Preprint