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Remote Sens. 2016, 8(9), 758; doi:10.3390/rs8090758

Assessing the Severity of Wind Gusts with Lidar

Wind Energy Research Group, Faculty of Aerospace Engineering, Delft University of Technology, Kluyverweg 1, Postbus 5058, 2600 GB Delft, The Netherlands
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Academic Editors: Charlotte Bay Hasager, Alfredo Peña, Guoqing Zhou and Prasad S. Thenkabail
Received: 12 July 2016 / Revised: 2 September 2016 / Accepted: 8 September 2016 / Published: 14 September 2016
(This article belongs to the Special Issue Remote Sensing of Wind Energy)
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Abstract

Lidars have gained a lot of popularity in the field of wind energy, partly because of their potential to be used for wind turbine control. By scanning the oncoming wind field, any threats such as gusts can be detected early and high loads can be avoided by taking preventive actions. Unfortunately, lidars suffer from some inherent weaknesses that hinder measuring gusts; e.g., the averaging of high-frequency fluctuations and only measuring along the line of sight). This paper proposes a method to construct a useful signal from a lidar by fitting a homogeneous Gaussian velocity field to a set of scattered measurements. The output signal, an along-wind force, acts as a measure for the damaging potential of an oncoming gust and is shown to agree with the rotor-effective wind speed (a similar control input, but derived directly from the wind turbine’s shaft torque). Low data availability and the disadvantage of not knowing the velocity between the lidar beams is translated into uncertainty and integrated in the output signal. This allows a designer to establish a control strategy based on risk, with the ultimate goal to reduce the extreme loads during operation. View Full-Text
Keywords: control; lidar; wind energy; wind gusts control; lidar; wind energy; wind gusts
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Bos, R.; Giyanani, A.; Bierbooms, W. Assessing the Severity of Wind Gusts with Lidar. Remote Sens. 2016, 8, 758.

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