Articles | Volume 8, issue 11
https://doi.org/10.5194/wes-8-1693-2023
© Author(s) 2023. 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-8-1693-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
15 Nov 2023
Research article |
| 15 Nov 2023
| 15 Nov 2023
Increased power gains from wake steering control using preview wind direction information
Balthazar Arnoldus Maria Sengers
CORRESPONDING AUTHOR
ForWind, Carl von Ossietzky Universität Oldenburg, Institute of Physics, Küpkersweg 70, 26129 Oldenburg, Germany
current address: Fraunhofer IWES, Küpkersweg 70, 26129 Oldenburg, Germany
Andreas Rott
ForWind, Carl von Ossietzky Universität Oldenburg, Institute of Physics, Küpkersweg 70, 26129 Oldenburg, Germany
Eric Simley
National Wind Technology Center, National Renewable Energy Laboratory, 15013 Denver W Pkwy, Golden, CO 80401, USA
Michael Sinner
National Wind Technology Center, National Renewable Energy Laboratory, 15013 Denver W Pkwy, Golden, CO 80401, USA
Gerald Steinfeld
ForWind, Carl von Ossietzky Universität Oldenburg, Institute of Physics, Küpkersweg 70, 26129 Oldenburg, Germany
Martin Kühn
ForWind, Carl von Ossietzky Universität Oldenburg, Institute of Physics, Küpkersweg 70, 26129 Oldenburg, Germany
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Sonja Krüger, Gerald Steinfeld, Martin Kraft, and Laura J. Lukassen
Wind Energ. Sci., 7, 323–344, https://doi.org/10.5194/wes-7-323-2022, https://doi.org/10.5194/wes-7-323-2022, 2022
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Andreas Rott, Jörge Schneemann, Frauke Theuer, Juan José Trujillo Quintero, and Martin Kühn
Wind Energ. Sci., 7, 283–297, https://doi.org/10.5194/wes-7-283-2022, https://doi.org/10.5194/wes-7-283-2022, 2022
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Paul Hulsman, Martin Wosnik, Vlaho Petrović, Michael Hölling, and Martin Kühn
Wind Energ. Sci., 7, 237–257, https://doi.org/10.5194/wes-7-237-2022, https://doi.org/10.5194/wes-7-237-2022, 2022
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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
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Liang Dong, Wai Hou Lio, and Eric Simley
Wind Energ. Sci., 6, 1491–1500, https://doi.org/10.5194/wes-6-1491-2021, https://doi.org/10.5194/wes-6-1491-2021, 2021
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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
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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.
Frederik Berger, David Onnen, Gerard Schepers, and Martin Kühn
Wind Energ. Sci., 6, 1341–1361, https://doi.org/10.5194/wes-6-1341-2021, https://doi.org/10.5194/wes-6-1341-2021, 2021
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Janna Kristina Seifert, Martin Kraft, Martin Kühn, and Laura J. Lukassen
Wind Energ. Sci., 6, 997–1014, https://doi.org/10.5194/wes-6-997-2021, https://doi.org/10.5194/wes-6-997-2021, 2021
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Alayna Farrell, Jennifer King, Caroline Draxl, Rafael Mudafort, Nicholas Hamilton, Christopher J. Bay, Paul Fleming, and Eric Simley
Wind Energ. Sci., 6, 737–758, https://doi.org/10.5194/wes-6-737-2021, https://doi.org/10.5194/wes-6-737-2021, 2021
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Most current wind turbine wake models struggle to accurately simulate spatially variant wind conditions at a low computational cost. In this paper, we present an adaptation of NREL's FLOw Redirection and Induction in Steady State (FLORIS) wake model, which calculates wake losses in a heterogeneous flow field using local weather measurement inputs. Two validation studies are presented where the adapted model consistently outperforms previous versions of FLORIS that simulated uniform flow only.
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
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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.
Jörge Schneemann, Frauke Theuer, Andreas Rott, Martin Dörenkämper, and Martin Kühn
Wind Energ. Sci., 6, 521–538, https://doi.org/10.5194/wes-6-521-2021, https://doi.org/10.5194/wes-6-521-2021, 2021
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A wind farm can reduce the wind speed in front of it just by its presence and thus also slightly impact the available power. In our study we investigate this so-called global-blockage effect, measuring the inflow of a large offshore wind farm with a laser-based remote sensing method up to several kilometres in front of the farm. Our results show global blockage under a certain atmospheric condition and operational state of the wind farm; during other conditions it is not visible in our data.
Anantha Padmanabhan Kidambi Sekar, Marijn Floris van Dooren, Andreas Rott, and Martin Kühn
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2021-16, https://doi.org/10.5194/wes-2021-16, 2021
Preprint withdrawn
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Turbine-mounted lidars performing inflow scans can be used to optimise wind turbine performance and extend their lifetime. This paper introduces a new method to extract wind inflow information from a turbine-mounted scanning SpinnerLidar based on Proper Orthogonal Decomposition. This method offers a balance between simple reconstruction methods and complicated physics-based solvers. The results show that the model can be used for lidar assisted control, loads validation and turbulence studies.
Frauke Theuer, Marijn Floris van Dooren, Lueder von Bremen, and Martin Kühn
Wind Energ. Sci., 5, 1449–1468, https://doi.org/10.5194/wes-5-1449-2020, https://doi.org/10.5194/wes-5-1449-2020, 2020
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Very short-term wind power forecasts are gaining increasing importance with the rising share of renewables in today's energy system. In this work, we developed a methodology to forecast wind power of offshore wind turbines on minute scales utilising long-range single-Doppler lidar measurements. The model was able to outperform persistence during unstable stratification in terms of deterministic and probabilistic scores, while it showed large shortcomings for stable atmospheric conditions.
Peter Brugger, Mithu Debnath, Andrew Scholbrock, Paul Fleming, Patrick Moriarty, Eric Simley, David Jager, Jason Roadman, Mark Murphy, Haohua Zong, and Fernando Porté-Agel
Wind Energ. Sci., 5, 1253–1272, https://doi.org/10.5194/wes-5-1253-2020, https://doi.org/10.5194/wes-5-1253-2020, 2020
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A wind turbine can actively influence its wake by turning the rotor out of the wind direction to deflect the wake away from a downstream wind turbine. This technique was tested in a field experiment at a wind farm, where the inflow and wake were monitored with remote-sensing instruments for the wind speed. The behaviour of the wake deflection agrees with the predictions of two analytical models, and a bias of the wind direction perceived by the yawed wind turbine led to suboptimal power gains.
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
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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.
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
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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.
Jörge Schneemann, Andreas Rott, Martin Dörenkämper, Gerald Steinfeld, and Martin Kühn
Wind Energ. Sci., 5, 29–49, https://doi.org/10.5194/wes-5-29-2020, https://doi.org/10.5194/wes-5-29-2020, 2020
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Offshore wind farm clusters cause reduced wind speeds in downstream regions which can extend over more than 50 km.
We analysed the impact of these so-called cluster wakes on a distant wind farm using remote-sensing wind measurements and power production data.
Cluster wakes caused power losses up to 55 km downstream in certain atmospheric states.
A better understanding of cluster wake effects reduces uncertainties in offshore wind resource assessment and improves offshore areal planning.
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
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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.
Siamak Akbarzadeh, Hassan Kassem, Renko Buhr, Gerald Steinfeld, and Bernhard Stoevesandt
Wind Energ. Sci., 4, 619–632, https://doi.org/10.5194/wes-4-619-2019, https://doi.org/10.5194/wes-4-619-2019, 2019
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The numerical flow simulation solvers are extensively used for site assessment in the wind energy industry. However, due to the complexity of flow regimes, it is essential to calibrate the important parameters of such algorithms with measurement data. In this paper, we present a computationally cheap (adjoint) solver that can be coupled with any standard gradient-based optimizer to calibrate the inflow boundary of a CFD solver using the wind speed measurements from the interior of a domain.
Markus Sommerfeld, Martin Dörenkämper, Gerald Steinfeld, and Curran Crawford
Wind Energ. Sci., 4, 563–580, https://doi.org/10.5194/wes-4-563-2019, https://doi.org/10.5194/wes-4-563-2019, 2019
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Airborne wind energy systems aim to operate at altitudes above conventional wind turbines where reliable high-resolution wind data are scarce. Wind measurements and computational simulations both have advantages and disadvantages when assessing the wind resource at such heights. This article investigates whether assimilating measurements into the model generates a more accurate wind data set up to 1100 m. These wind data sets are used to estimate optimal AWES operating altitudes and power.
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
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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.
Mike Optis, Jordan Perr-Sauer, Caleb Philips, Anna E. Craig, Joseph C. Y. Lee, Travis Kemper, Shuangwen Sheng, Eric Simley, Lindy Williams, Monte Lunacek, John Meissner, and M. Jason Fields
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2019-12, https://doi.org/10.5194/wes-2019-12, 2019
Preprint withdrawn
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As global wind capacity continues to grow, the need for accurate operational analyses of a rapidly growing fleet of wind power plants has increased in proportion. To address this need, the National Renewable Energy Laboratory has released OpenOA, an open-source codebase for operational analysis of wind farms. It is envisioned that OpenOA will evolve into a widely used codebase supported by a large group of global wind energy experts. This paper provides a summary of OpenOA.
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
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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
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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.
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
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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.
Laura Valldecabres, Alfredo Peña, Michael Courtney, Lueder von Bremen, and Martin Kühn
Wind Energ. Sci., 3, 313–327, https://doi.org/10.5194/wes-3-313-2018, https://doi.org/10.5194/wes-3-313-2018, 2018
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This paper focuses on the use of scanning lidars for very short-term forecasting of wind speeds in a near-coastal area. An extensive data set of offshore lidar measurements up to 6 km has been used for this purpose. Using dual-doppler measurements, the topographic characteristics of the area have been modelled. Assuming Taylor's frozen turbulence and applying the topographic corrections, we demonstrate that we can forecast wind speeds with more accuracy than the benchmarks persistence or ARIMA.
Lukas Vollmer, Gerald Steinfeld, and Martin Kühn
Wind Energ. Sci., 2, 603–614, https://doi.org/10.5194/wes-2-603-2017, https://doi.org/10.5194/wes-2-603-2017, 2017
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A model chain to simulate changing atmospheric conditions at the location of an offshore wind farm is introduced and validated. The methodology is used to simulate the wind flow upstream and downstream of an offshore wind turbine of the German wind farm Alpha ventus. The model results show a good agreement with wind measurements from the met mast that is located at the wind farm and with remote sensing measurements of the horizontal wind field.
Davide Trabucchi, Lukas Vollmer, and Martin Kühn
Wind Energ. Sci., 2, 569–586, https://doi.org/10.5194/wes-2-569-2017, https://doi.org/10.5194/wes-2-569-2017, 2017
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The wakes of wind turbines cause losses in the energy production of a wind farm. The accuracy of models applied to predict wake losses is a key factor for new wind projects. This paper presents an engineering wake model that can simulate merging wakes on the basis of physical principles. We used high-fidelity simulations of merging wakes to assess this model and found a better agreement with the reference than commonly used models implementing the superposition of individual wakes.
Niko Mittelmeier, Julian Allin, Tomas Blodau, Davide Trabucchi, Gerald Steinfeld, Andreas Rott, and Martin Kühn
Wind Energ. Sci., 2, 477–490, https://doi.org/10.5194/wes-2-477-2017, https://doi.org/10.5194/wes-2-477-2017, 2017
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Stability classification is usually based on measurements from met masts, buoys or lidars. The objective of this paper is to find a classification for stability based on wind turbine supervisory control and data acquisition measurements in order to fit engineering wake models better to the current ambient conditions. The proposed signal is very sensitive to increased turbulence. It allows us to distinguish between conditions with different magnitudes of wake effects.
Marijn Floris van Dooren, Filippo Campagnolo, Mikael Sjöholm, Nikolas Angelou, Torben Mikkelsen, and Martin Kühn
Wind Energ. Sci., 2, 329–341, https://doi.org/10.5194/wes-2-329-2017, https://doi.org/10.5194/wes-2-329-2017, 2017
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We conducted measurements in a wind tunnel with the remote sensing technique lidar to map the flow around a row of three model wind turbines. Two lidars were positioned near the wind tunnel walls to measure the two-dimensional wind vector over a defined scanning line or area without influencing the flow itself. A comparison of the lidar measurements with a hot-wire probe and a thorough uncertainty analysis confirmed the usefulness of lidar technology for such flow measurements in a wind tunnel.
Niko Mittelmeier, Tomas Blodau, and Martin Kühn
Wind Energ. Sci., 2, 175–187, https://doi.org/10.5194/wes-2-175-2017, https://doi.org/10.5194/wes-2-175-2017, 2017
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Efficient detection of wind turbines operating below their expected power output and immediate corrections help maximize asset value. The method presented estimates the environmental conditions from turbine states and uses pre-calculated power lookup tables from a numeric wake model to predict the expected power output. Deviations between the expected and the measured power output are an indication of underperformance. A demonstration of the method's ability to detect underperformance is given.
Lukas Vollmer, Gerald Steinfeld, Detlev Heinemann, and Martin Kühn
Wind Energ. Sci., 1, 129–141, https://doi.org/10.5194/wes-1-129-2016, https://doi.org/10.5194/wes-1-129-2016, 2016
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The wake flow downstream of yaw misaligned wind turbines is studied in numeric simulations of different atmospheric turbulence and shear conditions. We find that the average trajectory of the wake as well as the variation about this average is influenced by the thermal stability of the atmosphere. The results suggest that an intentional intervention in the yaw control of individual turbines to increase overall wind farm performance might be not successful during unstable thermal conditions.
Juan José Trujillo, Janna Kristina Seifert, Ines Würth, David Schlipf, and Martin Kühn
Wind Energ. Sci., 1, 41–53, https://doi.org/10.5194/wes-1-41-2016, https://doi.org/10.5194/wes-1-41-2016, 2016
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We present the analysis of the trajectories followed by the wind, in the immediate vicinity, behind an offshore wind turbine and their dependence on its yaw misalignment. We apply wake tracking on wind fields measured with a lidar (light detection and ranging) system located at the nacelle of the wind turbine and pointing downstream. The analysis reveals discrepancies of the estimated mean wake paths against theoretical and wind tunnel experiments using different wake-tracking techniques.
Related subject area
Thematic area: Dynamics and control | Topic: Wind turbine control
COFLEX: a novel set point optimiser and feedforward–feedback control scheme for large, flexible wind turbines
Control strategies for multi-rotor wind turbines
LIDAR-assisted nonlinear output regulation of wind turbines for fatigue load reduction
Output-constrained individual pitch control methods using the multiblade coordinate transformation: Trading off actuation effort and blade fatigue load reduction for wind turbines
Obtaining fatigue-based frequency domain specifications for the design of controllers in wind turbines
Brief communication: Real-time estimation of the optimal tip-speed ratio for controlling wind turbines with degraded blades
On the robustness of a blade-load-based wind speed estimator to dynamic pitch control strategies
The potential of wave feedforward control for floating wind turbines: a wave tank experiment
Assessing the impact of waves and platform dynamics on floating wind-turbine energy production
Combining wake redirection and derating strategies in a load-constrained wind farm power maximization
Multi-objective calibration of vertical-axis wind turbine controllers: balancing aero-servo-elastic performance and noise
Feedforward pitch control for a 15 MW wind turbine using a spinner-mounted single-beam lidar
Wind vane correction during yaw misalignment for horizontal-axis wind turbines
Analysis and multi-objective optimisation of wind turbine torque control strategies
Damping analysis of floating offshore wind turbines (FOWTs): a new control strategy reducing the platform vibrations
Assessing lidar-assisted feedforward and multivariable feedback controls for large floating wind turbines
Prognostics-based adaptive control strategy for lifetime control of wind turbines
Platform yaw drift in upwind floating wind turbines with single-point-mooring system and its mitigation by individual pitch control
Evaluation of lidar-assisted wind turbine control under various turbulence characteristics
FarmConners wind farm flow control benchmark – Part 1: Blind test results
Demonstration of a fault impact reduction control module for wind turbines
Lidar-assisted model predictive control of wind turbine fatigue via online rainflow counting considering stress history
Guido Lazzerini, Jacob Deleuran Grunnet, Tobias Gybel Hovgaard, Fabio Caponetti, Vasu Datta Madireddi, Delphine De Tavernier, and Sebastiaan Paul Mulders
Wind Energ. Sci., 10, 1303–1327, https://doi.org/10.5194/wes-10-1303-2025, https://doi.org/10.5194/wes-10-1303-2025, 2025
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Large wind turbines face design challenges due to increased flexibility of blades. Conventional control strategies fail under large deformations, impacting performance. We present a feedforward–feedback control scheme, addressing flexibility and overcoming the limitations of conventional strategies. By testing it on a large-scale reference turbine with realistic wind conditions, we demonstrated improvements to power by up to 5 % while constraining blade deflections.
Finn Matras and Morten Dinhoff Pedersen
Wind Energ. Sci., 10, 925–939, https://doi.org/10.5194/wes-10-925-2025, https://doi.org/10.5194/wes-10-925-2025, 2025
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Wind energy has been dominated by ever-increasing single-rotor wind turbines. Structural scaling laws make multi-rotor wind turbines attractive, as they can achieve similar power outputs but work with, rather than against, scaling laws. This work investigates high-level control strategies for a 23-rotor multi-rotor wind turbine, including the aerodynamic interactions between the rotors, and suggests an alternative to pitch control using multi-rotor furling.
Robert H. Moldenhauer and Robert Schmid
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-184, https://doi.org/10.5194/wes-2024-184, 2025
Revised manuscript accepted for WES
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We explore the application of a novel wind turbine control methodology for maximizing power generation while also improving the turbine's lifespan by reducing fatigue load on the tower structure, blades, and rotor. Simulations of the controller against a state-of-the-art baseline controller on a 15-MW reference turbine showed that the controller improves on all considered performance metrics. The reductions were achieved without sacrificing power generation or tracking performance.
Jesse Ishi Storm Hummel, Jens Kober, and Sebastiaan Paul Mulders
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-153, https://doi.org/10.5194/wes-2024-153, 2025
Revised manuscript accepted for WES
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Wind turbines have grown dramatically over the last decades. Since wind speed increases with height, each blade experiences high wind speed when pointing up and less wind when pointing down, causing oscillations. These oscillations can be reduced with individual pitch control (IPC), at the expense of constant blade actuation, hindering industry adoption. This work proposes two output-constrained IPC methods to facilitate the trade-off between load reduction and actuation increase.
Irene Miquelez-Madariaga, Jesús Arellano, Daniel Lacheta-Lecumberri, and Jorge Elso
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-154, https://doi.org/10.5194/wes-2024-154, 2024
Revised manuscript accepted for WES
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This paper presents a method for obtaining mechanical fatigue estimations from linear models and fatigue-based specifications for the design of controllers for wind turbines. The method is validated by the design of controllers for a 15 MW reference wind turbine. The error in the fatigue estimation is smaller than 2 % and fatigue loads are successfully reduced.
Devesh Kumar and Mario A. Rotea
Wind Energ. Sci., 9, 2133–2146, https://doi.org/10.5194/wes-9-2133-2024, https://doi.org/10.5194/wes-9-2133-2024, 2024
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The performance of a wind turbine is affected by blade surface degradation due to wear and tear, dirt, bugs, and icing. As blades degrade, optimal operating points such as the tip-speed ratio (TSR) can change. Re-tuning the TSR to its new optimal value can lead to recovery of energy losses under blade degradation. In this work, we utilize a real-time algorithm to re-tune the TSR to its new unknown optimal value under blade degradation and demonstrate energy gains using simulations.
Marion Coquelet, Maxime Lejeune, Laurent Bricteux, Aemilius A. W. van Vondelen, Jan-Willem van Wingerden, and Philippe Chatelain
Wind Energ. Sci., 9, 1923–1940, https://doi.org/10.5194/wes-9-1923-2024, https://doi.org/10.5194/wes-9-1923-2024, 2024
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An extended Kalman filter is used to estimate the wind impinging on a wind turbine based on the blade bending moments and a turbine model. Using large-eddy simulations, this paper verifies how robust the estimator is to the turbine control strategy as it impacts loads and operating parameters. It is shown that including dynamics in the turbine model to account for delays between actuation and bending moments is needed to maintain the accuracy of the estimator when dynamic pitch control is used.
Amr Hegazy, Peter Naaijen, Vincent Leroy, Félicien Bonnefoy, Mohammad Rasool Mojallizadeh, Yves Pérignon, and Jan-Willem van Wingerden
Wind Energ. Sci., 9, 1669–1688, https://doi.org/10.5194/wes-9-1669-2024, https://doi.org/10.5194/wes-9-1669-2024, 2024
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Successful wave tank experiments were conducted to evaluate the feedforward (FF) control strategy benefits in terms of structural loads and power quality of floating wind turbine components. The wave FF control strategy is effective when it comes to alleviating the effects of the wave forces on the floating offshore wind turbines, whereas wave FF control requires a significant amount of actuation to minimize the platform pitch motion, which makes such technology unfavorable for that objective.
Alessandro Fontanella, Giorgio Colpani, Marco De Pascali, Sara Muggiasca, and Marco Belloli
Wind Energ. Sci., 9, 1393–1417, https://doi.org/10.5194/wes-9-1393-2024, https://doi.org/10.5194/wes-9-1393-2024, 2024
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Waves can boost a floating wind turbine's power output by moving its rotor against the wind. Studying this, we used four models to explore the impact of waves and platform dynamics on turbines in the Mediterranean. We found that wind turbulence, not waves, primarily affects power fluctuations. In real conditions, floating wind turbines produce less energy compared to fixed-bottom ones, mainly due to platform tilt.
Alessandro Croce, Stefano Cacciola, and Federico Isella
Wind Energ. Sci., 9, 1211–1227, https://doi.org/10.5194/wes-9-1211-2024, https://doi.org/10.5194/wes-9-1211-2024, 2024
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For a few years now, various techniques have been studied to maximize the energy production of a wind farm, that is, from a system consisting of several wind turbines. These wind farm controller techniques are often analyzed individually and can generate loads higher than the design ones on the individual wind turbine. In this paper we study the simultaneous use of two different techniques with the goal of finding the optimal combination that at the same time preserves the design loads.
Livia Brandetti, Sebastiaan Paul Mulders, Roberto Merino-Martinez, Simon Watson, and Jan-Willem van Wingerden
Wind Energ. Sci., 9, 471–493, https://doi.org/10.5194/wes-9-471-2024, https://doi.org/10.5194/wes-9-471-2024, 2024
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This research presents a multi-objective optimisation approach to balance vertical-axis wind turbine (VAWT) performance and noise, comparing the combined wind speed estimator and tip-speed ratio (WSE–TSR) tracking controller with a baseline. Psychoacoustic annoyance is used as a novel metric for human perception of wind turbine noise. Results showcase the WSE–TSR tracking controller’s potential in trading off the considered objectives, thereby fostering the deployment of VAWTs in urban areas.
Wei Fu, Feng Guo, David Schlipf, and Alfredo Peña
Wind Energ. Sci., 8, 1893–1907, https://doi.org/10.5194/wes-8-1893-2023, https://doi.org/10.5194/wes-8-1893-2023, 2023
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A high-quality preview of the rotor-effective wind speed is a key element of the benefits of feedforward pitch control. We model a one-beam lidar in the spinner of a 15 MW wind turbine. The lidar rotates with the wind turbine and scans the inflow in a circular pattern, mimicking a multiple-beam lidar at a lower cost. We found that a spinner-based one-beam lidar provides many more control benefits than the one on the nacelle, which is similar to a four-beam nacelle lidar for feedforward control.
Andreas Rott, Leo Höning, Paul Hulsman, Laura J. Lukassen, Christof Moldenhauer, and Martin Kühn
Wind Energ. Sci., 8, 1755–1770, https://doi.org/10.5194/wes-8-1755-2023, https://doi.org/10.5194/wes-8-1755-2023, 2023
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This study examines wind vane measurements of commercial wind turbines and their impact on yaw control. The authors discovered that rotor interference can cause an overestimation of wind vane measurements, leading to overcorrection of the yaw controller. A correction function that improves the yaw behaviour is presented and validated in free-field experiments on a commercial wind turbine. This work provides new insights into wind direction measurements and suggests ways to optimize yaw control.
Livia Brandetti, Sebastiaan Paul Mulders, Yichao Liu, Simon Watson, and Jan-Willem van Wingerden
Wind Energ. Sci., 8, 1553–1573, https://doi.org/10.5194/wes-8-1553-2023, https://doi.org/10.5194/wes-8-1553-2023, 2023
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This research presents the additional benefits of applying an advanced combined wind speed estimator and tip-speed ratio tracking (WSE–TSR) controller compared to the baseline Kω2. Using a frequency-domain framework and an optimal calibration procedure, the WSE–TSR tracking control scheme shows a more flexible trade-off between conflicting objectives: power maximisation and load minimisation. Therefore, implementing this controller on large-scale wind turbines will facilitate their operation.
Matteo Capaldo and Paul Mella
Wind Energ. Sci., 8, 1319–1339, https://doi.org/10.5194/wes-8-1319-2023, https://doi.org/10.5194/wes-8-1319-2023, 2023
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The controller impacts the movements, loads and yield of wind turbines.
Standard controllers are not adapted for floating, and they can lead to underperformances and overloads. New control strategies, considering the coupling between the floating dynamics and the rotor dynamics, are necessary to reduce platform movements and to improve performances. This work proposes a new control strategy adapted to floating wind, showing a reduction in loads without affecting the power production.
Feng Guo and David Schlipf
Wind Energ. Sci., 8, 1299–1317, https://doi.org/10.5194/wes-8-1299-2023, https://doi.org/10.5194/wes-8-1299-2023, 2023
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This paper assesses lidar-assisted collective pitch feedforward (LACPF) and multi-variable feedback (MVFB) controls for the IEA 15.0 MW reference turbine. The main contributions of this work include (a) optimizing a four-beam pulsed lidar for a large turbine, (b) optimal tuning of speed regulation gains and platform feedback gains for the MVFB and LACPF controllers, and (c) assessing the benefits of the two control strategies using realistic offshore turbulence spectral characteristics.
Edwin Kipchirchir, M. Hung Do, Jackson G. Njiri, and Dirk Söffker
Wind Energ. Sci., 8, 575–588, https://doi.org/10.5194/wes-8-575-2023, https://doi.org/10.5194/wes-8-575-2023, 2023
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In this work, an adaptive control strategy for controlling the lifetime of wind turbine components is proposed. Performance of the lifetime controller is adapted based on real-time health status of the rotor blades to guarantee a predefined lifetime. It shows promising results in lifetime control of blades without speed regulation and tower load mitigation trade-off. It can be applied in optimizing maintenance scheduling of wind farms, which increases reliability and reduces maintenance costs.
Iñaki Sandua-Fernández, Felipe Vittori, Raquel Martín-San-Román, Irene Eguinoa, and José Azcona-Armendáriz
Wind Energ. Sci., 8, 277–288, https://doi.org/10.5194/wes-8-277-2023, https://doi.org/10.5194/wes-8-277-2023, 2023
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This work analyses in detail the causes of the yaw drift in floating offshore wind turbines with a single-point-mooring system induced by an upwind wind turbine. The ability of an individual pitch control strategy based on yaw misalignment is demonstrated through simulations using the NREL 5 MW wind turbine mounted on a single-point-mooring version of the DeepCwind OC4 floating platform. This effect is considered to be relevant for all single-point-moored concepts.
Feng Guo, David Schlipf, and Po Wen Cheng
Wind Energ. Sci., 8, 149–171, https://doi.org/10.5194/wes-8-149-2023, https://doi.org/10.5194/wes-8-149-2023, 2023
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The benefits of lidar-assisted control are evaluated using both the Mann model and Kaimal model-based 4D turbulence, considering the variation of turbulence parameters. Simulations are performed for the above-rated mean wind speed, using the NREL 5.0 MW reference wind turbine and a four-beam lidar system. Using lidar-assisted control reduces the variations in rotor speed, pitch rate, tower base fore–aft bending moment, and electrical power significantly.
Tuhfe Göçmen, Filippo Campagnolo, Thomas Duc, Irene Eguinoa, Søren Juhl Andersen, Vlaho Petrović, Lejla Imširović, Robert Braunbehrens, Jaime Liew, Mads Baungaard, Maarten Paul van der Laan, Guowei Qian, Maria Aparicio-Sanchez, Rubén González-Lope, Vinit V. Dighe, Marcus Becker, Maarten J. van den Broek, Jan-Willem van Wingerden, Adam Stock, Matthew Cole, Renzo Ruisi, Ervin Bossanyi, Niklas Requate, Simon Strnad, Jonas Schmidt, Lukas Vollmer, Ishaan Sood, and Johan Meyers
Wind Energ. Sci., 7, 1791–1825, https://doi.org/10.5194/wes-7-1791-2022, https://doi.org/10.5194/wes-7-1791-2022, 2022
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The FarmConners benchmark is the first of its kind to bring a wide variety of data sets, control settings, and model complexities for the (initial) assessment of wind farm flow control benefits. Here we present the first part of the benchmark results for three blind tests with large-scale rotors and 11 participating models in total, via direct power comparisons at the turbines as well as the observed or estimated power gain at the wind farm level under wake steering control strategy.
Benjamin Anderson and Edward Baring-Gould
Wind Energ. Sci., 7, 1753–1769, https://doi.org/10.5194/wes-7-1753-2022, https://doi.org/10.5194/wes-7-1753-2022, 2022
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Our article proposes an easy-to-integrate wind turbine control module which mitigates wind turbine fault conditions and sends predictive information to the grid operator, all while maximizing power production. This gives the grid operator more time to react to faults with its dispatch decisions, easing the transition between different generators. This study aims to illustrate the controller’s functionality under various types of faults and highlight potential wind turbine and grid benefits.
Stefan Loew and Carlo L. Bottasso
Wind Energ. Sci., 7, 1605–1625, https://doi.org/10.5194/wes-7-1605-2022, https://doi.org/10.5194/wes-7-1605-2022, 2022
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This publication presents methods to improve the awareness and control of material fatigue for wind turbines. This is achieved by enhancing a sophisticated control algorithm which utilizes wind prediction information from a laser measurement device. The simulation results indicate that the novel algorithm significantly improves the economic performance of a wind turbine. This benefit is particularly high for situations when the prediction quality is low or the prediction time frame is short.
Cited articles
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Short summary
Unexpected wind direction changes are undesirable, especially when performing wake steering. This study explores whether the yaw controller can benefit from accessing wind direction information before a change reaches the turbine. Results from two models with different fidelities demonstrate that wake steering can indeed benefit from preview information.
Unexpected wind direction changes are undesirable, especially when performing wake steering....
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