Journal cover Journal topic
Wind Energy Science The interactive open-access journal of the European Academy of Wind Energy
https://doi.org/10.5194/wes-2018-26
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Research articles
03 Apr 2018
Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Wind Energy Science (WES).
Determination of optimal wind turbine alignment into the wind and detection of alignment changes with SCADA data
Niko Mittelmeier1 and Martin Kühn2 1Senvion GmbH, Überseering 10, 22297 Hamburg, Germany
2ForWind – University of Oldenburg, Institute of Physics, Küpkersweg 70, 26129 Oldenburg, Germany
Abstract. Upwind horizontal axis wind turbines need to be aligned with the main wind direction to maximize energy yield. Attempts have been made to improve the yaw alignment with advanced measurement equipment but most of these techniques introduce additional costs and rely on alignment tolerances with the rotor axis or the true north. Turbines that are well aligned after commissioning, may suffer an alignment degradation during their operational lifetime. Such changes need to be detected as soon as possible to minimize power losses. The objective of this paper is to propose a three-step methodology to improve turbine alignment and detect changes during operational lifetime with standard nacelle metrology (met) mast instruments (here: two cup anemometer and one wind vane). In step one, a reference turbine and an external undisturbed reference wind signal, e.g. met mast or lidar are used to determine flow corrections for the nacelle wind direction instruments to obtain a turbine alignment with optimal power production. Secondly a nacelle wind speed correction is enabling the application of the previous step without additional external measurement equipment. Step three is a monitoring application and allows to detect alignment changes on the wind direction measurement device by means of a flow equilibrium between the two anemometers behind the rotor. The three steps are demonstrated at two 2 MW turbines together with a ground based lidar. A first order multi linear regression model gives sufficient correction of the flow distortion behind the rotor for our purposes and two wind vane alignment changes are detected with an accuracy of ±1.4 ° within three days of operation after the change is introduced. We could show, that standard turbine equipment is able to align a turbine with sufficient accuracy and changes to its alignment can be detected in a reasonable short time which helps to minimize power losses.
Citation: Mittelmeier, N. and Kühn, M.: Determination of optimal wind turbine alignment into the wind and detection of alignment changes with SCADA data, Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2018-26, in review, 2018.
Niko Mittelmeier and Martin Kühn
Niko Mittelmeier and Martin Kühn
Niko Mittelmeier and Martin Kühn

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Short summary
Upwind horizontal axis wind turbines need to be aligned with the main wind direction to maximize energy yield. This paper presents new methods to improve turbine alignment and detect changes during operational lifetime with standard nacelle met mast instruments. The flow distortion behind the rotor is corrected with a multi linear regression model and two alignment changes are detected with an accuracy of ±1.4 ° within three days of operation after the change is introduced.
Upwind horizontal axis wind turbines need to be aligned with the main wind direction to maximize...
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