Articles | Volume 7, issue 4
https://doi.org/10.5194/wes-7-1605-2022
© Author(s) 2022. 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-7-1605-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
03 Aug 2022
Research article |
| 03 Aug 2022
| 03 Aug 2022
Lidar-assisted model predictive control of wind turbine fatigue via online rainflow counting considering stress history
Stefan Loew
Wind Energy Institute, Technical University of Munich, 85748
Garching b. München, Germany
Wind Energy Institute, Technical University of Munich, 85748
Garching b. München, Germany
Related authors
No articles found.
Abhinav Anand and Carlo L. Bottasso
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2025-101, https://doi.org/10.5194/wes-2025-101, 2025
Preprint under review for WES
Short summary
Short summary
We formulate a controller for wind turbines that has three main characteristics. First, it optimizes profit by balancing revenue from power generation with cost. Second, cost includes the effects of cyclic fatigue that, departing from most of the existing literature on control, is rigorously accounted for by an exact cycle counting on receding horizons. Third, it uses a model capable of learning and improving its performance based on measured or synthetic data.
Hadi Hoghooghi and Carlo L. Bottasso
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2025-98, https://doi.org/10.5194/wes-2025-98, 2025
Preprint under review for WES
Short summary
Short summary
We formulate and demonstrate a new digital shadow (i.e. a virtual copy) for wind turbines. The digital shadow is designed in order to be capable of mirroring the response of the machine even in complex inflow conditions. Results from field measurements illustrate the ability of the shadow to estimate loads with good accuracy, even with minimal tuning.
Simone Tamaro, Filippo Campagnolo, and Carlo L. Bottasso
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2025-66, https://doi.org/10.5194/wes-2025-66, 2025
Revised manuscript under review for WES
Short summary
Short summary
We proposed a new method for active power control that uniquely combines induction control with wake steering to maximize power tracking margins. Our methodology results in significantly improved robustness against wind fluctuations and fatigue loading when compared to the state of the art.
Andre Thommessen, Abhinav Anand, Christoph M. Hackl, and Carlo L. Bottasso
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2025-72, https://doi.org/10.5194/wes-2025-72, 2025
Preprint under review for WES
Short summary
Short summary
We present a method to forecast inertia that accounts for wake effects in a wind farm. The approach is based on mapping forecasted site conditions to each single wind turbine in the farm through a wake model. The resulting inflow conditions are used to predict the inertia that the wind farm can provide to the grid, taking the wind turbine control strategies and operational limits into account.
Abhinav Anand, Robert Braunbehrens, Adrien Guilloré, and Carlo L. Bottasso
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2025-67, https://doi.org/10.5194/wes-2025-67, 2025
Revised manuscript has not been submitted
Short summary
Short summary
We present a new method for wind farm control, based on the optimization of an economic cost function that accounts for revenue from power production and cost due to operation and maintenance. The new formulation also includes constraints to ensure a desired lifetime duration. The application to relevant scenarios shows consistently improved profit when compared to alternative formulations from the recent literature.
Simone Tamaro, Filippo Campagnolo, and Carlo L. Bottasso
Wind Energ. Sci., 9, 1547–1575, https://doi.org/10.5194/wes-9-1547-2024, https://doi.org/10.5194/wes-9-1547-2024, 2024
Short summary
Short summary
We develop a new simple model to predict power losses incurred by a wind turbine when it yaws out of the wind. The model reveals the effects of a number of rotor design parameters and how the turbine is governed when it yaws. The model exhibits an excellent agreement with large eddy simulations and wind tunnel measurements. We showcase the capabilities of the model by deriving the power-optimal yaw strategy for a single turbine and for a cluster of wake-interacting turbines.
Marta Bertelè, Paul J. Meyer, Carlo R. Sucameli, Johannes Fricke, Anna Wegner, Julia Gottschall, and Carlo L. Bottasso
Wind Energ. Sci., 9, 1419–1429, https://doi.org/10.5194/wes-9-1419-2024, https://doi.org/10.5194/wes-9-1419-2024, 2024
Short summary
Short summary
A neural observer is used to estimate shear and veer from the operational data of a large wind turbine equipped with blade load sensors. Comparison with independent measurements from a nearby met mast and profiling lidar demonstrate the ability of the
rotor as a sensorconcept to provide high-quality estimates of these inflow quantities based simply on already available standard operational data.
Jenna Iori, Carlo Luigi Bottasso, and Michael Kenneth McWilliam
Wind Energ. Sci., 9, 1289–1304, https://doi.org/10.5194/wes-9-1289-2024, https://doi.org/10.5194/wes-9-1289-2024, 2024
Short summary
Short summary
The controller of a wind turbine has an important role in regulating power production and avoiding structural failure. However, it is often designed after the rest of the turbine, and thus its potential is not fully exploited. An alternative is to design the structure and the controller simultaneously. This work develops a method to identify if a given turbine design can benefit from this new simultaneous design process. For example, a higher and cheaper turbine tower can be built this way.
Paul Veers, Carlo L. Bottasso, Lance Manuel, Jonathan Naughton, Lucy Pao, Joshua Paquette, Amy Robertson, Michael Robinson, Shreyas Ananthan, Thanasis Barlas, Alessandro Bianchini, Henrik Bredmose, Sergio González Horcas, Jonathan Keller, Helge Aagaard Madsen, James Manwell, Patrick Moriarty, Stephen Nolet, and Jennifer Rinker
Wind Energ. Sci., 8, 1071–1131, https://doi.org/10.5194/wes-8-1071-2023, https://doi.org/10.5194/wes-8-1071-2023, 2023
Short summary
Short summary
Critical unknowns in the design, manufacturing, and operation of future wind turbine and wind plant systems are articulated, and key research activities are recommended.
Helena Canet, Adrien Guilloré, and Carlo L. Bottasso
Wind Energ. Sci., 8, 1029–1047, https://doi.org/10.5194/wes-8-1029-2023, https://doi.org/10.5194/wes-8-1029-2023, 2023
Short summary
Short summary
We propose a new approach to design that aims at optimal trade-offs between economic and environmental goals. New environmental metrics are defined, which quantify impacts in terms of CO2-equivalent emissions produced by the turbine over its entire life cycle. For some typical onshore installations in Germany, results indicate that a 1 % increase in the cost of energy can buy about a 5 % decrease in environmental impacts: a small loss for the individual can lead to larger gains for society.
Robert Braunbehrens, Andreas Vad, and Carlo L. Bottasso
Wind Energ. Sci., 8, 691–723, https://doi.org/10.5194/wes-8-691-2023, https://doi.org/10.5194/wes-8-691-2023, 2023
Short summary
Short summary
The paper presents a new method in which wind turbines in a wind farm act as local sensors, in this way detecting the flow that develops within the power plant. Through this technique, we are able to identify effects on the flow generated by the plant itself and by the orography of the terrain. The new method not only delivers a flow model of much improved quality but can also help in understanding phenomena that drive the farm performance.
Johan Meyers, Carlo Bottasso, Katherine Dykes, Paul Fleming, Pieter Gebraad, Gregor Giebel, Tuhfe Göçmen, and Jan-Willem van Wingerden
Wind Energ. Sci., 7, 2271–2306, https://doi.org/10.5194/wes-7-2271-2022, https://doi.org/10.5194/wes-7-2271-2022, 2022
Short summary
Short summary
We provide a comprehensive overview of the state of the art and the outstanding challenges in wind farm flow control, thus identifying the key research areas that could further enable commercial uptake and success. To this end, we have structured the discussion on challenges and opportunities into four main areas: (1) insight into control flow physics, (2) algorithms and AI, (3) validation and industry implementation, and (4) integrating control with system design
(co-design).
Emmanouil M. Nanos, Carlo L. Bottasso, Simone Tamaro, Dimitris I. Manolas, and Vasilis A. Riziotis
Wind Energ. Sci., 7, 1641–1660, https://doi.org/10.5194/wes-7-1641-2022, https://doi.org/10.5194/wes-7-1641-2022, 2022
Short summary
Short summary
A novel way of wind farm control is presented where the wake is deflected vertically to reduce interactions with downstream turbines. This is achieved by moving ballast in a floating offshore platform in order to pitch the support structure and thereby tilt the wind turbine rotor disk. The study considers the effects of this new form of wake control on the aerodynamics of the steering and wake-affected turbines, on the structure, and on the ballast motion system.
Emmanouil M. Nanos, Carlo L. Bottasso, Filippo Campagnolo, Franz Mühle, Stefano Letizia, G. Valerio Iungo, and Mario A. Rotea
Wind Energ. Sci., 7, 1263–1287, https://doi.org/10.5194/wes-7-1263-2022, https://doi.org/10.5194/wes-7-1263-2022, 2022
Short summary
Short summary
The paper describes the design of a scaled wind turbine in detail, for studying wakes and wake control applications in the known, controllable and repeatable conditions of a wind tunnel. The scaled model is characterized by conducting experiments in two wind tunnels, in different conditions, using different measurement equipment. Results are also compared to predictions obtained with models of various fidelity. The analysis indicates that the model fully satisfies the initial requirements.
Helena Canet, Stefan Loew, and Carlo L. Bottasso
Wind Energ. Sci., 6, 1325–1340, https://doi.org/10.5194/wes-6-1325-2021, https://doi.org/10.5194/wes-6-1325-2021, 2021
Short summary
Short summary
Lidar-assisted control (LAC) is used to redesign the rotor and tower of three turbines, differing in terms of wind class, size, and power rating. The load reductions enabled by LAC are used to save
mass, increase hub height, or extend lifetime. The first two strategies yield reductions in the cost of energy only for the tower of the largest machine, while more interesting benefits are obtained for lifetime extension.
Chengyu Wang, Filippo Campagnolo, Helena Canet, Daniel J. Barreiro, and Carlo L. Bottasso
Wind Energ. Sci., 6, 961–981, https://doi.org/10.5194/wes-6-961-2021, https://doi.org/10.5194/wes-6-961-2021, 2021
Short summary
Short summary
This paper quantifies the fidelity of the wakes generated by a small (1 m diameter) scaled wind turbine model operated in a large boundary layer wind tunnel. A detailed scaling analysis accompanied by large-eddy simulations shows that these wakes are very realistic scaled versions of the ones generated by the parent full-scale wind turbine in the field.
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.
Helena Canet, Pietro Bortolotti, and Carlo L. Bottasso
Wind Energ. Sci., 6, 601–626, https://doi.org/10.5194/wes-6-601-2021, https://doi.org/10.5194/wes-6-601-2021, 2021
Short summary
Short summary
The paper analyzes in detail the problem of scaling, considering both the steady-state and transient response cases, including the effects of aerodynamics, elasticity, inertia, gravity, and actuation. After a general theoretical analysis of the problem, the article considers two alternative ways of designing a scaled rotor. The two methods are then applied to the scaling of a 10 MW turbine of 180 m in diameter down to three different sizes (54, 27, and 2.8 m).
Bart M. Doekemeijer, Stefan Kern, Sivateja Maturu, Stoyan Kanev, Bastian Salbert, Johannes Schreiber, Filippo Campagnolo, Carlo L. Bottasso, Simone Schuler, Friedrich Wilts, Thomas Neumann, Giancarlo Potenza, Fabio Calabretta, Federico Fioretti, and Jan-Willem van Wingerden
Wind Energ. Sci., 6, 159–176, https://doi.org/10.5194/wes-6-159-2021, https://doi.org/10.5194/wes-6-159-2021, 2021
Short summary
Short summary
This article presents the results of a field experiment investigating wake steering on an onshore wind farm. The measurements show that wake steering leads to increases in power production of up to 35 % for two-turbine interactions and up to 16 % for three-turbine interactions. However, losses in power production are seen for various regions of wind directions. The results suggest that further research is necessary before wake steering will consistently lead to energy gains in wind farms.
Chengyu Wang, Filippo Campagnolo, and Carlo L. Bottasso
Wind Energ. Sci., 5, 1537–1550, https://doi.org/10.5194/wes-5-1537-2020, https://doi.org/10.5194/wes-5-1537-2020, 2020
Short summary
Short summary
A new method is described to identify the aerodynamic characteristics of blade airfoils directly from operational data of the turbine. Improving on a previously published approach, the present method is based on a new maximum likelihood formulation that includes errors both in the outputs and the inputs. The method is demonstrated on the identification of the polars of small-scale turbines for wind tunnel testing.
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.
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.
Johannes Schreiber, Carlo L. Bottasso, Bastian Salbert, and Filippo Campagnolo
Wind Energ. Sci., 5, 647–673, https://doi.org/10.5194/wes-5-647-2020, https://doi.org/10.5194/wes-5-647-2020, 2020
Short summary
Short summary
The paper describes a new method that uses standard historical operational data and reconstructs the flow at the rotor disk of each turbine in a wind farm. The method is based on a baseline wind farm flow and wake model, augmented with error terms that are
learnedfrom operational data using an ad hoc system identification approach. Both wind tunnel experiments and real data from a wind farm at a complex terrain site are used to show the capabilities of the new method.
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.
Johannes Schreiber, Amr Balbaa, and Carlo L. Bottasso
Wind Energ. Sci., 5, 237–244, https://doi.org/10.5194/wes-5-237-2020, https://doi.org/10.5194/wes-5-237-2020, 2020
Short summary
Short summary
An analytical wake model with a double-Gaussian velocity distribution is used to improve on a similar formulation by Keane et al (2016). The choice of a double-Gaussian shape function is motivated by the behavior of the near-wake region that is observed in numerical simulations and experimental measurements. The model is calibrated and validated using large eddy simulations replicating scaled wind turbine experiments, yielding improved results with respect to a classical single-Gaussian profile.
Pietro Bortolotti, Helena Canet, Carlo L. Bottasso, and Jaikumar Loganathan
Wind Energ. Sci., 4, 397–406, https://doi.org/10.5194/wes-4-397-2019, https://doi.org/10.5194/wes-4-397-2019, 2019
Short summary
Short summary
The paper studies the effects of uncertainties in aeroservoelastic
wind turbine models. Uncertainties are associated with the wind
inflow characteristics and the blade surface state, and they are propagated
by means of two non-intrusive methods throughout the
aeroservoelastic model of a large conceptual offshore wind
turbine. Results are compared with a brute-force extensive Monte
Carlo sampling to assess the convergence characteristics of the
non-intrusive approaches.
Pietro Bortolotti, Abhinav Kapila, and Carlo L. Bottasso
Wind Energ. Sci., 4, 115–125, https://doi.org/10.5194/wes-4-115-2019, https://doi.org/10.5194/wes-4-115-2019, 2019
Short summary
Short summary
The paper compares upwind and downwind three-bladed configurations
for a 10 MW wind turbine in terms of power and loads. For the
downwind case, the study also considers a load-aligned solution
with active coning. Results indicate that downwind solutions are
slightly more advantageous than upwind ones, although improvements
are small. Additionally, pre-alignment is difficult to achieve in
practice, and the active coning solution is associated with very
significant engineering challenges.
Jiangang Wang, Chengyu Wang, Filippo Campagnolo, and Carlo L. Bottasso
Wind Energ. Sci., 4, 71–88, https://doi.org/10.5194/wes-4-71-2019, https://doi.org/10.5194/wes-4-71-2019, 2019
Short summary
Short summary
This paper describes an LES approach for the simulation of wind
turbines and their wakes. The simulation model is used to
develop a complete digital copy of experiments performed with
scaled wind turbines in a boundary layer wind tunnel, including the
passive generation of a sheared turbulent flow. Numerical results
are compared with experimental measurements, with a good overall
matching between the two.
Marta Bertelè, Carlo L. Bottasso, and Stefano Cacciola
Wind Energ. Sci., 4, 89–97, https://doi.org/10.5194/wes-4-89-2019, https://doi.org/10.5194/wes-4-89-2019, 2019
Short summary
Short summary
This paper describes a new formulation for estimating the wind
inflow at the rotor disk, based on measurements of the blade loads.
The new method improves on previous formulations by exploiting the
rotational symmetry of the problem. Experimental results obtained
with an aeroelastically scaled model in a boundary layer wind
tunnel are used for validating the proposed approach.
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.
Jiangang Wang, Chengyu Wang, Filippo Campagnolo, and Carlo L. Bottasso
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2018-47, https://doi.org/10.5194/wes-2018-47, 2018
Revised manuscript has not been submitted
Short summary
Short summary
This paper describes a Scale Adaptive Simulation (SAS) approach for
the numerical simulation of wind turbines and their wakes. The SAS
formulation is found to be about one order of magnitude faster than
a classical LES approach. The simulation models are compared to
each other and with experimental measurements obtained with scaled
wind turbines in a boundary layer wind tunnel.
Marta Bertelè, Carlo L. Bottasso, Stefano Cacciola, Fabiano Daher Adegas, and Sara Delport
Wind Energ. Sci., 2, 615–640, https://doi.org/10.5194/wes-2-615-2017, https://doi.org/10.5194/wes-2-615-2017, 2017
Short summary
Short summary
The rotor of a wind turbine is used to determine some important parameters of the wind, including the direction of the wind vector relative to the rotor disk and horizontal and vertical shears. The method works by using measurements provided by existing onboard load sensors. The observed wind characteristics can be used to implement advanced features in smart wind turbine and wind farm controllers.
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.
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.
Pietro Bortolotti, Carlo L. Bottasso, and Alessandro Croce
Wind Energ. Sci., 1, 71–88, https://doi.org/10.5194/wes-1-71-2016, https://doi.org/10.5194/wes-1-71-2016, 2016
Short summary
Short summary
The paper presents a new method to conduct the holistic optimization of a wind turbine. The proposed approach allows one to define the rotor radius and tower height, while simultaneously performing the detailed sizing of rotor and tower. For the rotor, the procedures perform simultaneously the design both from the aerodynamic and structural points of view. The overall optimization seeks a minimum for the cost of energy, while accounting for a wide range of user-defined design constraints.
G. A. M. van Kuik, J. Peinke, R. Nijssen, D. Lekou, J. Mann, J. N. Sørensen, C. Ferreira, J. W. van Wingerden, D. Schlipf, P. Gebraad, H. Polinder, A. Abrahamsen, G. J. W. van Bussel, J. D. Sørensen, P. Tavner, C. L. Bottasso, M. Muskulus, D. Matha, H. J. Lindeboom, S. Degraer, O. Kramer, S. Lehnhoff, M. Sonnenschein, P. E. Sørensen, R. W. Künneke, P. E. Morthorst, and K. Skytte
Wind Energ. Sci., 1, 1–39, https://doi.org/10.5194/wes-1-1-2016, https://doi.org/10.5194/wes-1-1-2016, 2016
Related subject area
Thematic area: 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
Increased power gains from wake steering control using preview wind direction information
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
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Balthazar Arnoldus Maria Sengers, Andreas Rott, Eric Simley, Michael Sinner, Gerald Steinfeld, and Martin Kühn
Wind Energ. Sci., 8, 1693–1710, https://doi.org/10.5194/wes-8-1693-2023, https://doi.org/10.5194/wes-8-1693-2023, 2023
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Cited articles
Abbas, N. J., Zalkind, D. S., Pao, L., and Wright, A.: A reference open-source controller for fixed and floating offshore wind turbines, Wind Energ. Sci., 7, 53–73, https://doi.org/10.5194/wes-7-53-2022, 2022. a
Anand, A.: Optimal Control of Battery Energy Storage System for Grid
Integration of Wind Turbines, Master's thesis, TU Munich, Munich, 2020. a
ASTM International: Standard practices for cycle counting in fatigue analysis
(ASTM 1049-85), https://doi.org/10.1520/E1049-85R17, 1985. a, b
Barradas-Berglind, J. d. J., Wisniewski, R., and Soltani, M.: Fatigue damage
estimation and data-based control for wind turbines, IET Control Theory &
Applications, 9, 1042–1050, https://doi.org/10.1049/iet-cta.2014.0730, 2015. a, b, c
Barradas-Berglind, J. J. and Wisniewski, R.: Representation of fatigue for wind
turbine control, Wind Energy, 19, 2189–2203, https://doi.org/10.1002/we.1975, 2016. a, b
Bottasso, C. and Croce, A.: Cascading Kalman observers of structural flexible
and wind states for wind turbine control: Scientific Report DIA-SR 09-02,
Dipartimento di Ingegneria Aerospaziale, Politecnico di Milano, https://www.researchgate.net/publication/228941698_Cascading_Kalman_observers_of_structural_flexible_and_wind_states_for_wind_turbine_control (last access: 10 October 2021), 2009. a
Bottasso, C. L., Pizzinelli, P., Riboldi, C., and Tasca, L.: LiDAR-enabled
model predictive control of wind turbines with real-time capabilities,
Renew. Energ., 71, 442–452, https://doi.org/10.1016/j.renene.2014.05.041, 2014. a, b
Canet, H., Löw, S., and Bottasso, C. L.: Lidar-assisted control in wind
turbine design: Where are the potential benefits?, J. Phys. Conf. Ser., 1618, 042020, https://doi.org/10.1088/1742-6596/1618/4/042020,
2020. a, b
Dickler, S., Wintermeyer-Kallen, T., Zierath, J., Bockhahn, R., Machost, D.,
Konrad, T., and Abel, D.: Full-scale field test of a model predictive control
system for a 3 MW wind turbine, Forsch. Ingenieurwes., 85, 313–323,
https://doi.org/10.1007/s10010-021-00467-w, 2021. a
Diehl, M. and Gros, S.: Numerical Optimal Control: Lecture manuscript,
University of Freiburg, Freiburg and Gothenburg,
https://www.syscop.de/files/2020ss/NOC/book-NOCSE.pdf (last access: 10 October 2021), 2020. a
Do, H. and Söffker, D.: Wind Turbine Lifetime Control Using Structural
Health Monitoring and Prognosis, IFAC PapersOnLine, 53, 12669–12674,
https://doi.org/10.1016/j.ifacol.2020.12.1847, 2020. a
Evans, M. A., Cannon, M., and Kouvaritakis, B.: Robust MPC Tower Damping for
Variable Speed Wind Turbines, IEEE T. Contr. Syst. T., 23, 290–296, https://doi.org/10.1109/TCST.2014.2310513, 2015. a, b, c
Gros, S.: An Economic NMPC Formulation for Wind Turbine Control, in: 52nd IEEE
Conference on Decision and Control, 1001–1006, IEEE, Firenze, Italy, 10–13 December 2013, https://doi.org/10.1109/CDC.2013.6760013, 2013. a, b
Gros, S. and Schild, A.: Real-time economic nonlinear model predictive control
for wind turbine control, Int. J. Control, 90, 2799–2812, 10–13 December 2013, https://doi.org/10.1080/00207179.2016.1266514, 2017. a, b, c
Gros, S., Vukov, M., and Diehl, M.: A real-time MHE and NMPC scheme for wind
turbine control, in: 2013 IEEE 52nd Annual Conference on Decision and Control
(CDC), 1007–1012, IEEE, Piscataway, NJ, USA, https://doi.org/10.1109/CDC.2013.6760014,
2013. a, b, c
Grüne, L. and Pannek, J.: Nonlinear Model Predictive Control: Theory and
Algorithms, Communications and Control Engineering, Springer International
Publishing, Cham, Switzerland, 2nd edn.,
https://doi.org/10.1007/978-3-319-46024-6, 2017. a
Haibach, E.: Betriebsfestigkeit: Verfahren und Daten zur Bauteilberechnung,
VDI-Buch, Springer, Berlin, 3 edn., https://doi.org/10.1007/3-540-29364-7, 2006. a
Hau, E.: Windkraftanlagen: Grundlagen. Technik. Einsatz. Wirtschaftlichkeit,
Springer Berlin Heidelberg, Berlin, Heidelberg, 6 edn.,
https://doi.org/10.1007/978-3-662-53154-9, 2017. a
Heinrich, C., Khalil, M., Martynov, K., and WEVER, U.: Online remaining
lifetime estimation for structures, Mech. Syst. Signal Pr.,
119, 312–327, https://doi.org/10.1016/j.ymssp.2018.09.028, 2019. a
Huang, R., Biegler, L. T., and Patwardhan, S. C.: Fast Offset-Free Nonlinear
Model Predictive Control Based on Moving Horizon Estimation, Ind. Eng. Chem. Res., 49, 7882–7890, https://doi.org/10.1021/ie901945y,
2010. a, b
Jassmann, U., Zierath, J., Dickler, S., and Abel, D.: Model Predictive Wind
Turbine Control for Load Alleviation and Power Leveling in Extreme Operation
conditions, in: 2016 IEEE Conference on Control Applications (CCA), IEEE, 19–22 September 2016, Buenos Aires, Argentina, https://doi.org/10.1109/CCA.2016.7587997, 2016. a
Jonkman, J., Butterfield, S., Musial, W., and Scott, G.: Definition of a 5-MW
Reference Wind Turbine for Offshore System Development: Technical Report
NREL/TP-500-38060, National Renewable Energy Laboratory,
https://doi.org/10.2172/947422, 2009. a, b, c, d
Köhler, M., Jenne, S., Pötter, K., and Zenner, H.: Zählverfahren
und Lastannahme in der Betriebsfestigkeit, Springer, Berlin, Heidelberg,
https://doi.org/10.1007/978-3-642-13164-6, 2012. a
Loew, S.: Matlab figure files for key result plots, https://doi.org/10.5281/zenodo.6600688, Zenodo [data set], 2022a. a
Loew, S.: MATLAB function and a test script for the PORFC parameter generation, https://doi.org/10.5281/zenodo.6600832, Zenodo [code], 2022b. a
Loew, S. and Obradovic, D.: Formulation of Fatigue Dynamics as Hybrid Dynamical
System for Model Predictive Control, IFAC PapersOnLine, 53, 6616–6623,
https://doi.org/10.1016/j.ifacol.2020.12.080, 2020. a
Loew, S., Obradovic, D., and Bottasso, C. L.: Direct Online Rainflow-counting
and Indirect Fatigue Penalization Methods for Model Predictive Control, in:
2019 18th European Control Conference (ECC), 3371–3376, IEEE,
25–28 June 2019, Naples, Italy, https://doi.org/10.23919/ECC.2019.8795911, 2019. a
Loew, S., Obradovic, D., Anand, A., and Szabo, A.: Stage Cost Formulations of
Online Rainflow-counting for Model Predictive Control of Fatigue, in: 2020
European Control Conference (ECC), 475–482, 12–15 May 2020, St. Petersburg, Russia, https://doi.org/10.23919/ECC51009.2020.9143939, 2020a. a, b
Loew, S., Obradovic, D., and Bottasso, C. L.: Model predictive control of wind
turbine fatigue via online rainflow-counting on stress history and
prediction, J. Phys. Conf. Ser., 1618, 22041,
https://doi.org/10.1088/1742-6596/1618/2/022041, 2020b. a, b, c, d
Löw, S. and Obradovic, D.: Real-time Implementation of Nonlinear Model
Predictive Control for Mechatronic Systems Using a Hybrid Model, atp magazin,
60, 46–53, https://doi.org/10.17560/atp.v60i09.2359, 2018. a
Manwell, J. F., McGowan, J. G., and Rogers, A. L.: Wind energy explained:
Theory, design and application, John Wiley & Sons, Chichester, England,
https://doi.org/10.1002/0470846127, 2002. a
Miner, M. A.: Culmulative Damage in Fatigue, J. Appl. Mech., 12,
A159–A164, https://doi.org/10.1115/1.4009458, 1945. a
Raach, S. and Schlipf, D.: Cross-tool realistic lidar simulations: Presentation
at the IEA Wind Task 32 workshop on Certification of Lidar-assisted control
applications,
https://www.ieawindtask32.org/ws08-internal-documents/ (last access: 10 October 2021), 2018. a
Ritter, B.: Nonlinear State Estimation and Noise Adaptive Kalman Filter Design
for Wind Turbines, Dissertation, Technische Universität Darmstadt,
Darmstadt, https://doi.org/10.25534/tuprints-00011785, 2020. a
Sanchez, H., Escobet, T., Puig, V., and Odgaard, P. F.: Health-aware Model
Predictive Control of Wind Turbines using Fatigue Prognosis,
IFAC PapersOnLine, 48, 1363–1368, https://doi.org/10.1016/j.ifacol.2015.09.715, 2015. a
Schlipf, D.: Lidar-assisted control concepts for wind turbines, Dissertation,
University of Stuttgart, Stuttgart, Germany, https://doi.org/10.18419/OPUS-8796,
2016. a, b, c
Schlipf, D. and Raach, S.: Turbulent Extreme Event Simulations for
Lidar-Assisted Wind Turbine Control, J. Phys. Conf. Ser.,
753, 052011, https://doi.org/10.1088/1742-6596/753/5/052011, 2016. a
Schlipf, D., Schlipf, D. J., and Kühn, M.: Nonlinear model predictive
control of wind turbines using LIDAR, Wind Energy, 16, 1107–1129,
https://doi.org/10.1002/we.1533, 2013. a, b, c
Shi, Y., Xu, B., Tan, Y., and Zhang, B.: A Convex Cycle-based Degradation Model
for Battery Energy Storage Planning and Operation, in: 2018 Annual American
Control Conference (ACC), 4590–4596, IEEE, 27–29 June 2018, Milwaukee, WI, USA, https://doi.org/10.23919/ACC.2018.8431814, 2018.
a
Simon, D.: Kalman filtering with state constraints: a survey of linear and
nonlinear algorithms, IET Control Theory A., 4, 1303–1318,
https://doi.org/10.1049/iet-cta.2009.0032, 2010. a
Sinner, M., Petrovic, V., Langidis, A., Neuhaus, L., Holling, M., Kuhn, M., and
Pao, L. Y.: Experimental Testing of a Preview-Enabled Model Predictive
Controller for Blade Pitch Control of Wind Turbines, IEEE T. Contr. Syst. T., 583–597, https://doi.org/10.1109/TCST.2021.3070342, 2021. a
Verschueren, R., Frison, G., Kouzoupis, D., Frey, J., van Duijkeren, N.,
Zanelli, A., Novoselnik, B., Albin, T., Quirynen, R., and Diehl, M.:
acados – a modular open-source framework for fast embedded optimal control,
Mathematical Programming Computation, 14, 147–183, https://doi.org/10.1007/s12532-021-00208-8, 2021. a
Short summary
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.
This publication presents methods to improve the awareness and control of material fatigue for...
Altmetrics
Final-revised paper
Preprint