Abstract
In this paper, using real data from a low scale prototype of a wind turbine, different models have been obtained based on machine learning techniques. These models have been shown to be useful to forecast some key statistical metrics of the dynamics of the wind turbine. The models are dependent on the wind speed and the blade pitch angle. These models can be used to develop a digital twin of the wind turbine and predict its behavior, even for wind speed and pitch angles outside the ranges used for training the system.
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Acknowledgments
This work is partially supported by the Spanish Ministry of Science and Innovation under the project MCI/AEI/FEDER number RTI2018-094902-B-C21.
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Tecedor Roa, J., Serrano, C., Santos, M., Sierra-García, J.E. (2022). Identification of Variables of a Floating Wind Turbine Prototype. In: Yin, H., Camacho, D., Tino, P. (eds) Intelligent Data Engineering and Automated Learning – IDEAL 2022. IDEAL 2022. Lecture Notes in Computer Science, vol 13756. Springer, Cham. https://doi.org/10.1007/978-3-031-21753-1_49
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DOI: https://doi.org/10.1007/978-3-031-21753-1_49
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