Volume 3, issue 1 | Copyright
Wind Energ. Sci., 3, 313-327, 2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research articles 31 May 2018

Research articles | 31 May 2018

Very short-term forecast of near-coastal flow using scanning lidars

Laura Valldecabres1, Alfredo Peña2, Michael Courtney2, Lueder von Bremen1, and Martin Kühn1 Laura Valldecabres et al.
  • 1ForWind – University of Oldenburg, Institute of Physics, Küpkersweg 70, 26129 Oldenburg, Germany
  • 2DTU Wind Energy, Risø Campus, Technical University of Denmark, Frederiksborvej 399, 4000 Roskilde, Denmark

Abstract. Wind measurements can reduce the uncertainty in the prediction of wind energy production. Today, commercially available scanning lidars can scan the atmosphere up to several kilometres. Here, we use lidar measurements to forecast near-coastal winds with lead times of 5min. Using Taylor's frozen turbulence hypothesis together with local topographic corrections, we demonstrate that wind speeds at a downstream position can be forecast by using measurements from a scanning lidar performed upstream in a very short-term horizon. The study covers 10 periods characterised by neutral and stable atmospheric conditions. Our methodology shows smaller forecasting errors than those of the persistence method and the autoregressive integrated moving average (ARIMA) model. We discuss the applicability of this forecasting technique with regards to the characteristics of the lidar trajectories, the site-specific conditions and the atmospheric stability.

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Short summary
This paper focuses on the use of scanning lidars for very short-term forecasting of wind speeds in a near-coastal area. An extensive data set of offshore lidar measurements up to 6 km has been used for this purpose. Using dual-doppler measurements, the topographic characteristics of the area have been modelled. Assuming Taylor's frozen turbulence and applying the topographic corrections, we demonstrate that we can forecast wind speeds with more accuracy than the benchmarks persistence or ARIMA.
This paper focuses on the use of scanning lidars for very short-term forecasting of wind speeds...