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Conference programme 

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Poster session

Lead Session Chair:
Stephan Barth, Managing Director, ForWind - Center for Wind Energy Research, Germany
Marijn van Dooren ForWind - University of Oldenburg, Germany
Co-authors:

(1) ForWind - University of Oldenburg, Oldenburg, Germany

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Poster
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Presenter's biography

Biographies are supplied directly by presenters at OFFSHORE 2015 and are published here unedited

Marijn van Dooren is a scientific researcher at ForWind – University of Oldenburg. Last August he graduated at both the University of Oldenburg and the Technical University of Denmark in the joint European Wind Energy Master programme. During a master thesis at ForWind, he specialized in offshore LiDAR measurements and using these for the evaluation of wind fields and wakes. He will continue with a PhD on measuring wind turbine rotor inflow with a short-range spinner LiDAR and applying short-range LiDAR inside a wind tunnel.

Abstract

Assessment of the global wind and the local wake direction at "alpha ventus" using scanning long range lidar

Introduction

Wake effects play a relevant role in the development of a wind farm, particularly offshore. Most wake models applied in the planning of a wind farm imply that the wake of each turbine develops itself downstream, following the main wind direction of the wind farm inflow. In reality, this assumption might not always be accurate. Wind turbine yaw misalignment and wake interaction can both lead to a misalignment between wake direction and the main wind direction.

Approach

In this paper LIDAR is applied to evaluate the direction of the wind flow throughout the wind farm as well as the direction of single wakes covered by the measurements.

Main body of abstract

Long range scanning LIDAR offers the possibility to scan large areas of offshore wind farms. This innovative measurement technique can provide global information about the scanned region. One particular approach uses sectorial scans at a fixed low elevation (so-called Plan Position Indicator scans) in order to estimate a horizontal wind vector representative for the scanned area rather than simply the line-of-sight wind speed. When scanning a sector with a sufficiently large azimuth range, a varying geometrical projection of the main wind vector is measured and a sinusoidal relationship is established between azimuth angle and measured radial wind speed. The horizontal wind vector can be derived from a fitted sine function with the well known VAD (Velocity Azimuth Display) algorithm.

This method is applied to measurements performed between June 2013 and March 2014 at the offshore wind farm »alpha ventus« in the German North Sea. The objective is to investigate divergences between the global wind direction and the local direction of the wind turbine wakes. A wake tracking algorithm is applied to the LIDAR measurements and the resulting wake direction is compared with the global wind direction evaluated by means of the VAD approach.

In order to further develop the methodology, results from two different filtering strategies are compared with data sets provided by the offshore meteorological research platform FINO1. In the first case, all data from the scanned area is considered, while in the second one, the area expected to be affected by wakes of wind turbines is excluded.

Conclusion

Applying long range scanning LIDAR to wind farms to investigate the divergence between global wind direction and local wake direction will yield a better understanding of the impact of yaw misalignment of turbines, as well as wake interaction inside the wind farm, on the wind flow throughout the wind farm. Results could give insight on how to improve both wind farm layout and turbine design.


Learning objectives
A presentation at the conference will introduce delegates to a methodology for planning LIDAR scanning scenarios and processing the measurements accordingly to assess both the global wind and local wake direction in a wind farm and compare them. Also a method will be demonstrated that excludes wakes from line-of-sight wind speed measurements by scanning LIDAR.