Parameterization of wind evolution using lidar
Chen, Y. ., Schlipf, D. ., & Cheng, P. W. (2021). Parameterization of wind evolution using lidar. Wind Energy Science, 6, 61–91. http://doi.org/10.5194/wes-6-61-2021 (Original work published 2024)
Publikationen
Realization of wind field reconstruction for real- time monitoring and LIDAR-assisted control
Schlipf, D. ., Lemmer, F. ., & Thomas, F. . (2021). Realization of wind field reconstruction for real- time monitoring and LIDAR-assisted control. http://doi.org/10.5281/zenodo.5608684 (Original work published 2024)Exportformate
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A Spectral Model of Grid Frequency for Assessing the Impact of Inertia Response on Wind Turbine Dynamics
Guo, F. ., & Schlipf, D. . (2021). A Spectral Model of Grid Frequency for Assessing the Impact of Inertia Response on Wind Turbine Dynamics. Energies, 14. http://doi.org/10.3390/en14092492 (Original work published 2024)Exportformate
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Loop shaping based robust control for floating offshore wind turbines
Yu, W. ., Lemmer, F. ., Schlipf, D. ., & Cheng, P. W. (2020). Loop shaping based robust control for floating offshore wind turbines. In Journal of Physics: Conference Series (Bd. 1618, S. 022066). http://doi.org/10.1088/1742-6596/1618/2/022066 (Original work published 2024)Exportformate
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IEA Wind Task 32 and Task 37: Optimizing Wind Turbines with Lidar-Assisted Control Using Systems Engineering
Simley, E. ., Bortolotti, P. ., Scholbrock, A. ., Schlipf, D. ., & Dykes, K. . (2020). IEA Wind Task 32 and Task 37: Optimizing Wind Turbines with Lidar-Assisted Control Using Systems Engineering. In Journal of Physics: Conference Series (Bd. 1618, S. 042029). http://doi.org/10.1088/1742-6596/1618/4/042029 (Original work published 2024)Exportformate
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Lidar-based Estimation of Turbulence Intensity for Controller Scheduling
Schlipf, D. ., Guo, F. ., & Raach, S. . (2020). Lidar-based Estimation of Turbulence Intensity for Controller Scheduling. In Journal of Physics: Conference Series (Bd. 1618, S. 032053). http://doi.org/10.1088/1742-6596/1618/3/032053 (Original work published 2024)Exportformate
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IEA Wind Task 32: Collaborative R\&D Roadmap
Clifton, A. ., Schlipf, D. ., Vasiljevic, N. ., Gottschall, J. ., Clive, P. ., Wüerth, I. ., … Nygaard, N. . (2020). IEA Wind Task 32: Collaborative R\&D Roadmap. http://doi.org/10.5281/zenodo.4030701 (Original work published 2024)Exportformate
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Multi-Variable Feedforward Control for Floating Wind Turbines Using Lidar
Schlipf, D. ., Lemmer, F. ., & Raach, S. . (2020). Multi-Variable Feedforward Control for Floating Wind Turbines Using Lidar. In International Ocean and Polar Engineering Conference. http://doi.org/10.18419/opus-11067 (Original work published 2024)Exportformate
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Modeling Uncertainties of Wind Field Reconstruction Using Lidar
Schlipf, D. ., Koch, M. ., & Raach, S. . (2020). Modeling Uncertainties of Wind Field Reconstruction Using Lidar. In Journal of Physics: Conference Series (Bd. 1452, S. 012088). http://doi.org/10.1088/1742-6596/1452/1/012088 (Original work published 2024)Exportformate
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Robust gain scheduling baseline controller for floating offshore wind turbines
Lemmer, F. ., Yu, W. ., Schlipf, D. ., & Cheng, P. W. (2020). Robust gain scheduling baseline controller for floating offshore wind turbines. Wind Energy, 23, 17–30. http://doi.org/10.1002/we.2408 (Original work published 2024)Exportformate
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