Articles | Volume 5, issue 4
https://doi.org/10.5194/wes-5-1449-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-5-1449-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Minute-scale power forecast of offshore wind turbines using long-range single-Doppler lidar measurements
Frauke Theuer
CORRESPONDING AUTHOR
ForWind, Institute of Physics, University of Oldenburg, Küpkersweg 70, 26129 Oldenburg, Germany
Marijn Floris van Dooren
ForWind, Institute of Physics, University of Oldenburg, Küpkersweg 70, 26129 Oldenburg, Germany
Lueder von Bremen
DLR Institute of Networked Energy Systems, Carl-von-Ossietzky-Straße 15, 26129 Oldenburg, Germany
Martin Kühn
ForWind, Institute of Physics, University of Oldenburg, Küpkersweg 70, 26129 Oldenburg, Germany
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Cited
15 citations as recorded by crossref.
- Hybrid and Ensemble Methods of Two Days Ahead Forecasts of Electric Energy Production in a Small Wind Turbine P. Piotrowski et al. 10.3390/en14051225
- Hybrid use of an observer-based minute-scale power forecast and persistence F. Theuer et al. 10.1088/1742-6596/2265/2/022047
- Observer-based power forecast of individual and aggregated offshore wind turbines F. Theuer et al. 10.5194/wes-7-2099-2022
- Alignment of scanning lidars in offshore wind farms A. Rott et al. 10.5194/wes-7-283-2022
- Alignment calibration and correction for offshore wind measurements using scanning lidars K. Gramitzky et al. 10.1088/1742-6596/2767/4/042014
- A Multi-Scale Method for PM2.5 Forecasting with Multi-Source Big Data W. Yuan et al. 10.1007/s11424-023-1378-7
- Estimating the benefit of Doppler wind lidars for short‐term low‐level wind ensemble forecasts T. Nomokonova et al. 10.1002/qj.4402
- Offshore wind farm global blockage measured with scanning lidar J. Schneemann et al. 10.5194/wes-6-521-2021
- Analysis of the effects of scanning trajectory parameters on minute-scale lidar forecasting M. Ortensi et al. 10.1088/1742-6596/2265/2/022002
- Big Data in Forecasting Research: A Literature Review L. Tang et al. 10.1016/j.bdr.2021.100289
- Scalable electromagnetic energy harvester for wind turbine rotor blade applications M. Schlögl et al. 10.1088/1361-665X/ad3e52
- The effect of information and communication technology on environmentally sustainable development in Sub-Saharan Africa: the role of green innovation and industrial structure E. Manu & S. Asongu 10.1080/02681102.2025.2502408
- Comparison of near wind farm wake measurements from scanning lidar with engineering models A. Anantharaman et al. 10.1088/1742-6596/2265/2/022034
- Short-Term Wind Power Forecasting at the Wind Farm Scale Using Long-Range Doppler LiDAR M. Pichault et al. 10.3390/en14092663
- Increased power gains from wake steering control using preview wind direction information B. Sengers et al. 10.5194/wes-8-1693-2023
15 citations as recorded by crossref.
- Hybrid and Ensemble Methods of Two Days Ahead Forecasts of Electric Energy Production in a Small Wind Turbine P. Piotrowski et al. 10.3390/en14051225
- Hybrid use of an observer-based minute-scale power forecast and persistence F. Theuer et al. 10.1088/1742-6596/2265/2/022047
- Observer-based power forecast of individual and aggregated offshore wind turbines F. Theuer et al. 10.5194/wes-7-2099-2022
- Alignment of scanning lidars in offshore wind farms A. Rott et al. 10.5194/wes-7-283-2022
- Alignment calibration and correction for offshore wind measurements using scanning lidars K. Gramitzky et al. 10.1088/1742-6596/2767/4/042014
- A Multi-Scale Method for PM2.5 Forecasting with Multi-Source Big Data W. Yuan et al. 10.1007/s11424-023-1378-7
- Estimating the benefit of Doppler wind lidars for short‐term low‐level wind ensemble forecasts T. Nomokonova et al. 10.1002/qj.4402
- Offshore wind farm global blockage measured with scanning lidar J. Schneemann et al. 10.5194/wes-6-521-2021
- Analysis of the effects of scanning trajectory parameters on minute-scale lidar forecasting M. Ortensi et al. 10.1088/1742-6596/2265/2/022002
- Big Data in Forecasting Research: A Literature Review L. Tang et al. 10.1016/j.bdr.2021.100289
- Scalable electromagnetic energy harvester for wind turbine rotor blade applications M. Schlögl et al. 10.1088/1361-665X/ad3e52
- The effect of information and communication technology on environmentally sustainable development in Sub-Saharan Africa: the role of green innovation and industrial structure E. Manu & S. Asongu 10.1080/02681102.2025.2502408
- Comparison of near wind farm wake measurements from scanning lidar with engineering models A. Anantharaman et al. 10.1088/1742-6596/2265/2/022034
- Short-Term Wind Power Forecasting at the Wind Farm Scale Using Long-Range Doppler LiDAR M. Pichault et al. 10.3390/en14092663
- Increased power gains from wake steering control using preview wind direction information B. Sengers et al. 10.5194/wes-8-1693-2023
Latest update: 30 May 2025
Short summary
Very short-term wind power forecasts are gaining increasing importance with the rising share of renewables in today's energy system. In this work, we developed a methodology to forecast wind power of offshore wind turbines on minute scales utilising long-range single-Doppler lidar measurements. The model was able to outperform persistence during unstable stratification in terms of deterministic and probabilistic scores, while it showed large shortcomings for stable atmospheric conditions.
Very short-term wind power forecasts are gaining increasing importance with the rising share of...
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