Articles | Volume 5, issue 2
Wind Energ. Sci., 5, 647–673, 2020
https://doi.org/10.5194/wes-5-647-2020
Wind Energ. Sci., 5, 647–673, 2020
https://doi.org/10.5194/wes-5-647-2020
Research article
27 May 2020
Research article | 27 May 2020

Improving wind farm flow models by learning from operational data

Johannes Schreiber et al.

Related authors

Wind inflow observation from load harmonics: initial steps towards a field validation
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
Field experiment for open-loop yaw-based wake steering at a commercial onshore wind farm in Italy
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
Wind tunnel testing of wake steering with dynamic wind direction changes
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
Field testing of a local wind inflow estimator and wake detector
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
Brief communication: A double-Gaussian wake model
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

Related subject area

Aerodynamics and hydrodynamics
FLOW Estimation and Rose Superposition (FLOWERS): an integral approach to engineering wake models
Michael J. LoCascio, Christopher J. Bay, Majid Bastankhah, Garrett E. Barter, Paul A. Fleming, and Luis A. Martínez-Tossas
Wind Energ. Sci., 7, 1137–1151, https://doi.org/10.5194/wes-7-1137-2022,https://doi.org/10.5194/wes-7-1137-2022, 2022
Short summary
High-Reynolds-number investigations on the ability of the full-scale e-TellTale sensor to detect flow separation on a wind turbine blade section
Antoine Soulier, Caroline Braud, Dimitri Voisin, and Frédéric Danbon
Wind Energ. Sci., 7, 1043–1052, https://doi.org/10.5194/wes-7-1043-2022,https://doi.org/10.5194/wes-7-1043-2022, 2022
Short summary
Experimental investigation of mini Gurney flaps in combination with vortex generators for improved wind turbine blade performance
Jörg Alber, Marinos Manolesos, Guido Weinzierl-Dlugosch, Johannes Fischer, Alexander Schönmeier, Christian Navid Nayeri, Christian Oliver Paschereit, Joachim Twele, Jens Fortmann, Pier Francesco Melani, and Alessandro Bianchini
Wind Energ. Sci., 7, 943–965, https://doi.org/10.5194/wes-7-943-2022,https://doi.org/10.5194/wes-7-943-2022, 2022
Short summary
Parked and operating load analysis in the aerodynamic design of multi-megawatt-scale floating vertical-axis wind turbines
Mohammad Sadman Sakib and D. Todd Griffith
Wind Energ. Sci., 7, 677–696, https://doi.org/10.5194/wes-7-677-2022,https://doi.org/10.5194/wes-7-677-2022, 2022
Short summary
High-Reynolds-number wind turbine blade equipped with root spoilers – Part 1: Unsteady aerodynamic analysis using URANS simulations
Thomas Potentier, Emmanuel Guilmineau, Arthur Finez, Colin Le Bourdat, and Caroline Braud
Wind Energ. Sci., 7, 647–657, https://doi.org/10.5194/wes-7-647-2022,https://doi.org/10.5194/wes-7-647-2022, 2022
Short summary

Cited articles

Bastankhah, M. and Porté-Agel, F.: Experimental and theoretical study of wind turbine wakes in yawed conditions, J. Fluid Mech., 806, 506–541, 2016. a, b, c, d, e, f
Bastine, D., Witha, B., Wächter, M., and Peinke, J.: POD Analysis of a Wind Turbine Wake in a Turbulent Atmospheric Boundary Layer, J. Phys. Conf. Ser., 524, 012153, https://doi.org/10.1088/1742-6596/524/1/012153, 2014. a
Bleeg, J., Purcell, M., Ruisi, R., and Traiger, E.: Wind Farm Blockage and the Consequences of Neglecting Its Impact on Energy Production, Energies, 11, 1609, https://doi.org/10.3390/en11061609, 2018. a, b
Boersma, S., Doekemeijer, B., Vali, M., Meyers, J., and van Wingerden, J.-W.: A control-oriented dynamic wind farm model: WFSim, Wind Energ. Sci., 3, 75–95, https://doi.org/10.5194/wes-3-75-2018, 2018. a, b
Bottasso, C. L., Cacciola, S., and Iriarte, X.: Calibration of wind turbine lifting line models from rotor loads, J. Wind Eng. Ind. Aerod., 124, 29–45, https://doi.org/10.1016/j.jweia.2013.11.003, 2014a. a, b, c, d, e
Download
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 learned from 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.