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Wind Energy Science The interactive open-access journal of the European Academy of Wind Energy
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https://doi.org/10.5194/wes-2020-78
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-2020-78
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  11 May 2020

11 May 2020

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A revised version of this preprint is currently under review for the journal WES.

Minute-scale power forecast of offshore wind turbines using single-Doppler long-range lidar measurements

Frauke Theuer1, Marijn Floris van Dooren1, Lueder von Bremen2, and Martin Kühn1 Frauke Theuer et al.
  • 1ForWind, Institute of Physics, University of Oldenburg, Küpkersweg 70, 26129 Oldenburg, Germany
  • 2DLR Institute of Networked Energy Systems, Carl-von-Ossietzky-Straße 15, 26129 Oldenburg

Abstract. Decreasing gate closure times on the electricity stock exchange market and the rising share of renewables in today's energy system cause an increasing demand for very short-term power forecasts. While the potential of dual-Doppler radar data for that purpose was recently shown, the utilisation of single-Doppler lidar measurements needs to be explored further to make remote sensing-based very short-term forecasts more feasible for offshore sites. The aim of this work was to develop a lidar-based forecasting methodology, which addresses a lidar's comparatively low scanning speed. We developed a lidar-based forecast methodology using horizontal plan position indicator (PPI) lidar scans. It comprises a filtering methodology to recover data at far ranges, a wind field reconstruction, a time synchronisation to account for time shifts within the lidar scans and a wind speed extrapolation to hub height. Applying the methodology to seven free-flow turbines in the offshore wind farm Global Tech I revealed the model's ability to outperform the benchmark persistence during unstable stratification, in terms of deterministic as well as probabilistic scores. The performance during stable and neutral situations was significantly lower, which we attribute mainly to errors in the extrapolation of wind speed to hub height.

Frauke Theuer et al.

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Frauke Theuer et al.

Frauke Theuer et al.

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Latest update: 23 Sep 2020
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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 single Doppler long-range lidar measurements. The model was able to outperform persistence during unstable stratification in terms of deterministic as well as 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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