Wind Turbine Performance Measurements by Means of Dynamic Data Analysis

Troels Friis Pedersen, Rozenn Wagner, Giorgio Demurtas

Research output: Book/ReportReport

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Abstract

The state of the art power performance measurement
method refers to the IEC61400-12-1 standard from 2005
[1]. A method for faster power curves was proposed by
researchers at Oldenburg university in 2004. The method
was called Langevin power curve method and advantages
was claimed to be that power curves could be made faster
with 1Hz dataset. In the FastWind project the Langevin
power curve method was used on real power curve
measurement datasets with the purpose to evaluate the
method for practical use.
A practical guide to application of the method to real power
curve measurement data was made. The study showed
that the method has a range of parameter settings that the
user must consider. Additionally to the wind speed binning
power binning is needed but power binning size is not
specified. Determination of drift in each bin is described
with a general formula but in practice several additional
tools have been developed by authors to try to make the
drift field and fixed point determination more robust.
A sensitivity analysis with nacelle lidar data showed drift
determination was not very dependent on the time steps
applied, leading to use of time steps of 2-3 points for each
dataset. Power bin size should be fixed. Data averaging
with 5 sec data was more distinct for determination of the
fixed points than 2 and 1 sec data. With the nacelle lidar the
Langevin method seemed to produce a power curve that
was comparable to the IEC power curve.
Analysis of the Langevin method with spinner anemometer
data showed that fixed points were very sensitive to bin
size and to requirement of minimum amount of data in each
bin. The Langevin method failed to produce acceptable
robust power curves comparable to the IEC power curve.
Simple binned averaging of data with shorter time averages gave
better results than the Langevin power curve method.
Original languageEnglish
PublisherDTU Wind Energy
Number of pages91
ISBN (Print)978-87-93278-28-8
Publication statusPublished - 2016
SeriesDTU Wind Energy E
Volume0082

Bibliographical note

Projektrapport på EUDP projekt FastWind

Cite this

Friis Pedersen, T., Wagner, R., & Demurtas, G. (2016). Wind Turbine Performance Measurements by Means of Dynamic Data Analysis. DTU Wind Energy. DTU Wind Energy E, Vol.. 0082