Share this page on:

Conference programme 

Back to the programme printer.gif Print

Poster session

Lead Session Chair:
Stephan Barth, Managing Director, ForWind - Center for Wind Energy Research, Germany
Jan Willem Wagenaar ECN, The Netherlands
Jan Willem Wagenaar (1) F P Samuel Davoust (2) Benny Svardal (3) Valerie Kumer (4)
(1) ECN, Petten, The Netherlands (2) Avent Lidar Technology, Orsay, France (3) CMR, Bergen, Norway (4) University of Bergen, Bergen, Norway

Printer friendly version: printer.gif Print

Download poster(0.92 MB)

Presenter's biography

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

Dr Jan Willem Wagenaar currently is project manager and researcher at ECN Wind Energy. He obtained his master of science degree at the University of Groningen and his PhD degree at the University of Nijmegen both in physics. In 2009 he joined ECN and his work focusses on measurements regarding power performance, wind resource assessment and LiDAR in national and international projects. He is coordinator of the MEASNET power performance expert group, work package leader in the project and within ECN coordinator of the R&D line Facilities and Experiments.


Using backward nacelle lidars in wake characterization for wind farm optimization


In large offshore wind farms the individual turbines communicate with each other through their wakes. In the wake the wind speed is reduced and turbulence intensity is increased. In addition, the wake expands, meanders and slowly recovers.

These aspects influence the yield and fatigue loading of wind farms and are therefore very important for wind farm operators for good insight in the operation of their wind farms and to find ways for performance improvements.

In this work two nacelle LiDARs are placed on a full scale wind turbine in a backward mode with the aim to quantify these effects.


In order to examine the above, a measurement campaign was started on the ECN test site in different phases, which is a near shore site consisting of flat, agricultural terrain. A Wind Iris two beam nacelle LiDAR and a Zephir 300 nacelle LiDAR were placed in a backward mode on a modern, full scale ECN research turbines. Here, the Wind Iris is oriented such that one beam is aligned with the nacelle. A fully instrumented IEC compliant meteorological mast is nearby and for some time two WindCube V1 ground based LiDARs were present.

Main body of abstract

With the focus on this wind farm operation this measurement campaign was organized on the ECN test site, which is a near shore site. The two nacelle LiDARs are placed on 2.5MW Nordex N80 machine which is the second in a row of five from East to West. Here, the Wind Iris is placed on the cooler of the turbine, such that one beam is along the direction of the nacelle and with measurement distances from 80m (1D) to 440m (5.5D). The Zephir is placed at the back of the nacelle, i.e. behind the cooler. This LiDAR performs conical scans with a cone angle of 30 degrees with measurement distances from 19m (0.24D) to 129m (1.6D). The mast is at 2.5D South-East (predominant wind direction) and the ground based LiDARs at approximately 2D and 4D North-East from the turbine.

The wake measurements of the two nacelle LiDARs are validated against the mast measurements and (partly) against the ground based LiDAR measurements in terms of wind speed and turbulence. In addition, the wake is characterized with the combination of the nacelle LiDARs in terms of wind speed deficit (mainly central line) and wake expansion (mainly conical scan) in the near and intermediate wake. With the combined inflow and wake measurements the wake recovery is examined for different inflow conditions.

Last but not least, the above examined wake characteristics are compared to the situation where the turbine itself experiences a single wake and is producing a wake for yet a third turbine.


From the results it is concluded how the wake wind speed and turbulence measurements from both nacelle LiDARs are quantified with respect to the mast, compare among each other and where they complement. In addition, conclusions are drawn from the nacelle LiDAR results on wake evolution for different inflow conditions and for both free turbine as well as in waked turbine conditions. Last but not least conclusions are drawn on how these are used for optimized farm operation.

Learning objectives
Recommendations are given on how wind farm operators should apply the nacelle LiDARs based on the comparison and/or complementation and on how the nacelle LiDARs can be used to optimize their farm in terms of wakes.