Articles | Volume 11, issue 11
https://doi.org/10.5194/wes-11-4059-2026
https://doi.org/10.5194/wes-11-4059-2026
Research article
 | 
02 Nov 2026
Research article |  | 02 Nov 2026

Predicting wind turbine aerodynamic loads using laser-scanned blade geometry with validation based on operational and structural data

António Galhardo, André Biscaya, João Pedro Santos, and Filipe Magalhães

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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
Abbas, N. J., dzalkind, Mudafort, R. M., Hylander, G., Mulders, S., Heffernan, D., and Bortolotti, P.: NREL/ROSCO: ROSCO v2.9.0, Zenodo [code], https://doi.org/10.5281/zenodo.10535404, 2024. a
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
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
Bortolotti, P., Tarres, H. C., Dykes, K. L., Merz, K., Sethuraman, L., Verelst, D., and Zahle, F.: IEA Wind TCP Task 37: Systems Engineering in Wind Energy – WP2.1 Reference Wind Turbines, Tech. Rep. NREL/TP-5000-73492, National Renewable Energy Laboratory (NREL), Golden, CO (United States), https://doi.org/10.2172/1529216, 2019. a, b
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Computer models are often used to simulate wind turbine loads and predict their lifetime. This work focuses on how model accuracy can be improved by using measurements in an operational wind turbine. Blade geometry was measured, filling in knowledge gaps in model inputs, while loads were estimated using tower-mounted sensors, allowing a validation of the outputs. Results highlight the value of experimental data to better identify the causes of differences between simulations and reality.
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