Articles | Volume 10, issue 9
https://doi.org/10.5194/wes-10-2005-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/wes-10-2005-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Output-constrained individual pitch control methods using the multiblade coordinate transformation: trading off actuation effort and blade fatigue load reduction for wind turbines
Jesse I. S. Hummel
CORRESPONDING AUTHOR
Delft Center for Systems, Delft University of Technology, Mekelweg 5, 2628 CD Delft, the Netherlands
Jens Kober
Cognitive Robotics, Delft University of Technology, Mekelweg 5, 2628 CD Delft, the Netherlands
Sebastiaan P. Mulders
Delft Center for Systems, Delft University of Technology, Mekelweg 5, 2628 CD Delft, the Netherlands
Related authors
No articles found.
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.
Atindriyo Kusumo Pamososuryo, Fabio Spagnolo, and Sebastiaan Paul Mulders
Wind Energ. Sci., 10, 987–1006, https://doi.org/10.5194/wes-10-987-2025, https://doi.org/10.5194/wes-10-987-2025, 2025
Short summary
Short summary
As wind turbines grow in size, measuring wind speed accurately becomes challenging, impacting their performance. Traditional sensors cannot capture wind variations across large rotor areas. To address this, a new method is developed to estimate wind speed accurately, accounting for these variations. Using mid-fidelity simulations, our approach showed better tracking, better noise resilience, and easy tuning for different turbine sizes.
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.
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.
Cited articles
Abbas, N., Zalkind, D., Mudafort, R., Hylander, G., Mulders, S., Heffernan, D., and Bortolotti, P.: NREL/ROSCO: ROSCO v2.9.0 (v2.9.0), Zenodo [code], https://doi.org/10.5281/ZENODO.10535404, 2024. a
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
Bir, G.: Multi-Blade Coordinate Transformation and Its Application to Wind Turbine Analysis, in: 46th AIAA Aerospace Sciences Meeting and Exhibit, American Institute of Aeronautics and Astronautics, Reno, Nevada, ISBN 978-1-62410-128-1, https://doi.org/10.2514/6.2008-1300, 2008. a, b, c, d
Bossanyi, E. A.: Further Load Reductions with Individual Pitch Control, Wind Energy, 8, 481–485, https://doi.org/10.1002/we.166, 2005. a, b, c
Bossanyi, E. A., Fleming, P. A., and Wright, A. D.: Validation of Individual Pitch Control by Field Tests on Two- and Three-Bladed Wind Turbines, IEEE T. Contr. Sys. T., 21, 1067–1078, https://doi.org/10.1109/TCST.2013.2258345, 2013. a, b
Bottasso, C., Campagnolo, F., Croce, A., and Tibaldi, C.: Optimization-Based Study of Bend–Twist Coupled Rotor Blades for Passive and Integrated Passive/Active Load Alleviation, Wind Energy, 16, 1149–1166, https://doi.org/10.1002/we.1543, 2013. a
Burton, T., Jenkins, N., Sharpe, D., Bossanyi, E., and Graham, M.: Wind Energy Handbook, Wiley, Hoboken, NJ, 3rd Edn., ISBN 978-1-119-45114-3, 2021. a
Coleman, R. P. and Feingold, M., A.: Theory of Self-Excited Mechanical Oscillations of Helicopter Rotors with Hinged Blades, National Aeronautics and Space Administration (NASA), https://ntrs.nasa.gov/citations/19930092339 (last access: 10 September 2025), 1958. a
Collet, D., Alamir, M., Di Domenico, D., and Sabiron, G.: Data-Driven Fatigue-Oriented MPC Applied to Wind Turbines Individual Pitch Control, Renew. Energ., 170, 1008–1019, https://doi.org/10.1016/j.renene.2021.02.052, 2021. a
E08 Committee: Practices for Cycle Counting in Fatigue Analysis, https://doi.org/10.1520/E1049-85R17, 2017. a
Gaertner, E., Rinker, J., Sethuraman, L., Zahle, F., Anderson, B., Barter, G., Abbas, N., Meng, F., Bortolotti, P., Skrzypinski, W., Scott, G., Feil, R., Bredmose, H., Dykes, K., Shields, M., Allen, C., and Viselli, A.: IEA Wind TCP Task 37: Definition of the IEA 15-Megawatt Offshore Reference Wind Turbine, Tech. Rep. NREL/TP–5000-75698, 1603478, National Renewable Energy Laboratory (NREL), https://doi.org/10.2172/1603478, 2020. a, b, c
Henry, A., Pusch, M., and Pao, L.: Investigation of H∞-Tuned Individual Pitch Control for Wind Turbines, Wind Energy, https://doi.org/10.1002/we.2945, 2024. a, b
Hummel, J. I. S.: Code and Dataset to Analyze Output-Constrained IPC Methods L2 and Linfty-IPC, 4TU [code and data set], https://doi.org/10.4121/372325a3-306e-4578-9c72-4fcda690a999, 2024. a, b
Hummel, Jesse: Output-Constrained Invididual Pitch Control, Zenodo [code], https://doi.org/10.5281/ZENODO.15736496, 2025. a
Jonkman, B. J.: TurbSim User's Guide: version 1.50, National Renewable Energy Laboratory (NREL), https://doi.org/10.2172/965520, 2009. a, b
Jonkman, B., Mudafort, R. M., Platt, A., Branlard, E., Sprague, M., Ross, H., Jonkman, J., HaymanConsulting, Hall, M., Slaughter, D., Vijayakumar, G., Buhl, M., Russell9798, Bortolotti, P., Reos-Rcrozier, Shreyas Ananthan, Michael, S., Rood, J., Rdamiani, Nrmendoza, Sinolonghai, Pschuenemann, Ashesh2512, Kshaler, Housner, S., Psakievich, Bendl, K., Carmo, L., Quon, E., and Mattrphillips: OpenFAST v3.5.0, Zenodo [code], https://doi.org/10.5281/ZENODO.7942867, 2023. a
Kanev, S. and van Engelen, T.: Exploring the Limits in Individual Pitch Control, in: European Wind Energy Conference and Exhibition, EWEC, ISBN 978-1-61567-746-7, 2009. a
Lara, M., Vázquez, F., van Wingerden, J. W., Mulders, S. P., and Garrido, J.: Multi-Objective Optimization of Individual Pitch Control for Blade Fatigue Load Reductions for a 15 MW Wind Turbine, in: 2024 European Control Conference (ECC), IEEE, Stockholm, Sweden, 669–674, ISBN 978-3-907144-10-7, https://doi.org/10.23919/ECC64448.2024.10590830, 2024. a, b
Liu, Y., Ferrari, R., and van Wingerden, J. W.: Periodic Load Rejection for Floating Offshore Wind Turbines via Constrained Subspace Predictive Repetitive Control, in: American Control Conference (ACC), Institute of Electrical and Electronics Engineers Inc., vol. 2021–May, 539–544, ISBN 978-166544197-1, https://doi.org/10.23919/ACC50511.2021.9483333, 2021. a
Liu, Y., Ferrari, R., and van Wingerden, J.-W.: Load reduction for wind turbines: an output-constrained, subspace predictive repetitive control approach, Wind Energ. Sci., 7, 523–537, https://doi.org/10.5194/wes-7-523-2022, 2022. a, b
Lu, Q., Bowyer, R., and Jones, B. L.: Analysis and Design of Coleman Transform-Based Individual Pitch Controllers for Wind-Turbine Load Reduction: Individual Blade-Pitch Control, Wind Energy, 18, 1451–1468, https://doi.org/10.1002/we.1769, 2015. a, b, c
Mulders, S. P. and van Wingerden, J. W.: On the Importance of the Azimuth Offset in a Combined 1P and 2P SISO IPC Implementation for Wind Turbine Fatigue Load Reductions, in: American Control Conference (ACC), IEEE, Philadelphia, USA, ISBN 978-1-5386-7926-5, https://doi.org/10.23919/ACC.2019.8814829, 2019. a, b, c
Mulders, S. P., Pamososuryo, A. K., Disario, G. E., and van Wingerden, J. W.: Analysis and Optimal Individual Pitch Control Decoupling by Inclusion of an Azimuth Offset in the Multiblade Coordinate Transformation, Wind Energy, https://doi.org/10.1002/we.2289, 2019. a, b, c, d
Novaes Menezes, E. J., Araújo, A. M., and Bouchonneau Da Silva, N. S.: A Review on Wind Turbine Control and Its Associated Methods, J. Clean. Product., 174, 945–953, https://doi.org/10.1016/j.jclepro.2017.10.297, 2018. a
O'Rourke, C. J., Qasim, M. M., Overlin, M. R., and Kirtley, J. L.: A Geometric Interpretation of Reference Frames and Transformations: Dq0, Clarke, and Park, IEEE T. Energy Conver., 34, 2070–2083, https://doi.org/10.1109/TEC.2019.2941175, 2019. a
Ossmann, D., Seiler, P., Milliren, C., and Danker, A.: Field Testing of Multi-Variable Individual Pitch Control on a Utility-Scale Wind Turbine, Renew. Energ., 170, 1245–1256, https://doi.org/10.1016/j.renene.2021.02.039, 2021. a
Pao, L. Y., Pusch, M., and Zalkind, D. S.: Control Co-Design of Wind Turbines, Annual Review of Control, Robotics, and Autonomous Systems, 7, 201–226, https://doi.org/10.1146/annurev-control-061423-101708, 2024. a
Park, R. H.: Two-Reaction Theory of Synchronous Machines Generalized Method of Analysis-Part I, Transactions of the American Institute of Electrical Engineers, 48, 716–727, https://doi.org/10.1109/T-AIEE.1929.5055275, 1929. a
Petrović, V., Jelavić, M., and Baotić, M.: MPC Framework for Constrained Wind Turbine Individual Pitch Control, Wind Energy, 24, 54–68, https://doi.org/10.1002/we.2558, 2021. a
Pettas, V., Salari, M., Schlipf, D., and Cheng, P. W.: Investigation on the Potential of Individual Blade Control for Lifetime Extension, J. Phys., 1037, 032006, https://doi.org/10.1088/1742-6596/1037/3/032006, 2018. a
Raach, S., Schlipf, D., Sandner, F., Matha, D., and Cheng, P. W.: Nonlinear Model Predictive Control of Floating Wind Turbines with Individual Pitch Control, in: 2014 American Control Conference, IEEE, Portland, OR, USA, 4434–4439, ISBN 978-1-4799-3274-0, 978-1-4799-3272-6, 978-1-4799-3271-9, https://doi.org/10.1109/ACC.2014.6858718, 2014. a
Schwack, F., Stammler, M., Poll, G., and Reuter, A.: Comparison of Life Calculations for Oscillating Bearings Considering Individual Pitch Control in Wind Turbines, J. Phys., 753, 112013, https://doi.org/10.1088/1742-6596/753/11/112013, 2016. a
Shan, M., Jacobsen, J., and Adelt, S.: Field Testing and Practical Aspects of Load Reducing Pitch Control Systems for a 5 MW Offshore Wind Turbine, in: European Wind Energy Conference and Exhibition (EWEC) 2013, Fraunhofer-Gesellschaft, https://doi.org/10.24406/PUBLICA-FHG-383237, 2013. a
Skogestad, S. and Postlethwaite, I.: Multivariable Feedback Control: Analysis and Design, Wiley, ISBN 978-0-470-01167-6, ISBN 978-0-470-01168-3, 2010. a
Sutherland, H. J.: On the Fatigue Analysis of Wind Turbines, Tech. Rep. SAND99-0089, Sandia National Lab. (SNL-NM), Albuquerque, NM (United States), Sandia National Lab. (SNL-CA), Livermore, CA (United States), https://doi.org/10.2172/9460, 1999. a
Thomsen, K.: The Statistical Variation of Wind Turbine Fatigue Loads, Tech. Rep. RISO-R-1063(EN), Forskningscenter Risoe, Denmark, https://www.osti.gov/etdeweb/biblio/292704 (last access: 10 September 2025), 1998. a
Ungurán, R., Petrović, V., Pao, L. Y., and Kühn, M.: Smart Rotor Control of Wind Turbines under Actuator Limitations, in: American Control Conference (ACC), IEEE, Philadelphia, USA, ISBN 978-1-5386-7926-5, https://doi.org/10.23919/ACC.2019.8815001, 2019. a
Van Solingen, E., Fleming, P. A., Scholbrock, A., and Van Wingerden, J. W.: Field Testing of Linear Individual Pitch Control on the Two-bladed Controls Advanced Research Turbine, Wind Energy, 19, 421–436, https://doi.org/10.1002/we.1841, 2016. a
Veers, P., Dykes, K., Lantz, E., Barth, S., Bottasso, C., Carlson, O., Clifton, A., Green, J., Green, P., Holttinen, H., Laird, D., Lehtomäki, V., Lundquist, J., Manwell, J., Marquis, M., Meneveau, C., Moriarty, P., Munduate, X., Muskulus, M., Naughton, J., Pao, L., Paquette, J., Peinke, J., Robertson, A., Rodrigo, J., Sempreviva, A., Smith, J., Tuohy, A., and Wiser, R.: Grand Challenges in the Science of Wind Energy, Science, 366, https://doi.org/10.1126/science.aau2027, 2019. a
Yan, B., Li, Q., Chan, P., He, Y., and Shu, Z.: Characterising Wind Shear Exponents in the Offshore Area Using Lidar Measurements, Appl. Ocean Res., 127, 103293, https://doi.org/10.1016/j.apor.2022.103293, 2022. a
Yang, X., Jiang, X., Liang, S., Qin, Y., Ye, F., Ye, B., Xu, J., He, X., Wu, J., Dong, T., Cai, X., Xu, R., and Zeng, Z.: Spatiotemporal Variation of Power Law Exponent on the Use of Wind Energy, Appl. Energ., 356, 122441, https://doi.org/10.1016/j.apenergy.2023.122441, 2024. a
Zahle, F., Barlas, A., Loenbaek, K., Bortolotti, P., Zalkind, D., Wang, L., Labuschagne, C., Sethuraman, L., and Barter, G.: Definition of the IEA Wind 22-Megawatt Offshore Reference Wind Turbine, Tech. rep., Technical University of Denmark, https://doi.org/10.11581/DTU.00000317, 2024. a
Short summary
The variation in wind speed over the rotor plane causes oscillations in the blade, leading to fatigue damage. These oscillations can be reduced with individual pitch control (IPC), at the expense of more blade actuation. This work proposes two output-constrained IPC methods to facilitate the trade-off between load reduction and actuation increase. Both methods can smoothly transition between conventional full IPC action and no IPC action.
The variation in wind speed over the rotor plane causes oscillations in the blade, leading to...
Special issue
Altmetrics
Final-revised paper
Preprint