One-to-one aeroservoelastic validation of operational loads and performance of a 2.8 MW wind turbine model in OpenFAST
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Published:2024-08-23
Issue:8
Volume:9
Page:1791-1810
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ISSN:2366-7451
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Container-title:Wind Energy Science
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language:en
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Short-container-title:Wind Energ. Sci.
Author:
Brown KennethORCID, Bortolotti PietroORCID, Branlard EmmanuelORCID, Chetan MayankORCID, Dana ScottORCID, deVelder Nathaniel, Doubrawa PaulaORCID, Hamilton Nicholas, Ivanov Hristo, Jonkman JasonORCID, Kelley Christopher, Zalkind Daniel
Abstract
Abstract. This article presents a validation study of the popular aeroservoelastic code suite OpenFAST leveraging weeks of measurements obtained during normal operation of a 2.8 MW land-based wind turbine. Measured wind conditions were used to generate one-to-one turbulent flow fields (i.e., comparing simulation to measurement in 10 min increments, or bins) through unconstrained and constrained assimilation methods using the kinematic turbulence generators TurbSim and PyConTurb. A total of 253 bins of 10 min of normal turbine operation were selected for analysis, and a statistical comparison in terms of performance and loads is presented. We show that successful validation of the model was not strongly dependent on the type of inflow assimilation method used for mean quantities of interest, which had median modeling errors per wind-speed interval generally within 5 %–10 % of the measurement. The type of inflow assimilation method did have a larger effect on the fatigue predictions for blade-root flapwise and tower-base fore–aft quantities, which surprisingly saw larger errors from the assumed higher-fidelity assimilation methods. Avenues for further work are discussed and include possible improvements to the aerodynamic, structural, and controller modeling that may offer insight on the origin of the up to ∼ 40 % median overprediction of fatigue for these quantities.
Funder
Wind Energy Technologies Office
Publisher
Copernicus GmbH
Reference39 articles.
1. 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, b 2. Abbas, N. J., Zalkind, D., Mudafort, R. M., Hylander, G., Mulders, S., Heffernan, D., and Bortolotti, P.: NREL/ROSCO: Version 2.7.0, Zenodo [code], https://doi.org/10.5281/zenodo.7629837, 2023. a 3. Asmuth, H., Navarro Diaz, G. P., Madsen, H. A., Branlard, E., Meyer Forsting, A. R., Nilsson, K., Jonkman, J., and Ivanell, S.: Wind turbine response in waked inflow: A modelling benchmark against full-scale measurements, Renew. Energ., 191, 868–887, https://doi.org/10.1016/j.renene.2022.04.047, 2022. a, b, c 4. Boorsma, K., Hartvelt, M., and Orsi, L.: Application of the lifting line vortex wake method to dynamic load case simulations, J. Phys. Conf. Ser., 753, 022030, https://doi.org/10.1088/1742-6596/753/2/022030, 2016. a 5. Boorsma, K., Schepers, G., Aagard Madsen, H., Pirrung, G., Sørensen, N., Bangga, G., Imiela, M., Grinderslev, C., Meyer Forsting, A., Shen, W. Z., Croce, A., Cacciola, S., Schaffarczyk, A. P., Lobo, B., Blondel, F., Gilbert, P., Boisard, R., Höning, L., Greco, L., Testa, C., Branlard, E., Jonkman, J., and Vijayakumar, G.: Progress in the validation of rotor aerodynamic codes using field data, Wind Energ. Sci., 8, 211–230, https://doi.org/10.5194/wes-8-211-2023, 2023. a, b, c
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