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R&D focus: studies and measurement campaigns to deliver a quality service

As part of our work to optimize the performance of wind assets, VALEMO’s engineering department has been working since 2016 on the issue of wind turbine misalignment with respect to wind direction.

This misalignment, which is very regularly observed on the turbine fleets that we operate or audit, is twofold :

– Decrease in production due to the reduction in the surface area of the wind disc swept by the air flow.
– Increase in the mechanical fatigue of the turbine, the blades and the kinematic chain in particular linked to the variable load forces due to the incident wind which is not perpendicular to the rotor.

In order to measure this alignment gap, VALEMO has developed several methodologies and set up operational campaigns.

  • Comparative study on 3 measuring devices: Wind Iris, iSpin, Yaw Advisor

in 2017, we carried out a comparative study of three measuring devices on a SENVION MM92 wind turbine in Loire-Atlantique in France with a Wind Iris, an iSpin and a Yaw Advisor. The results of this study were published at the Colloque National Eolien 2017 in Paris, at DEWEK 2017 in Hamburg and at Wind Europe 2017 in Amsterdam.

  • Evaluation of energy loss due to yaw error

In 2018, we carried out a study to characterize the production loss coefficient related to misalignment on a GE 2.5xl wind turbine in the Somme region of France, the results of which were published at the Colloque National Eolien 2018 in Paris. Thus, we were able to validate that the performance loss as a function of the misalignment of the nacelle with respect to the wind followed a cos² law .

  • Control measurement campaigns: 22 operations conducted in France

To date, we have carried out 22 nacelle alignment control measurement campaigns on turbines identified as suffering from underperformance through the analysis of turbine data using tools developed in-house.

Based on the cos2 law presented in the study on the characterization of the production loss coefficient, we have considered two thresholds beyond which misalignment in terms of production loss can be estimated as significant and very significant.

For a wind turbine of 2MW at 2500h for an electricity feed-in tariff of 90€/MWh, the production loss is of the order of 0.3% from 3° of misalignment and 0.8% from 5° and thus in these two cases the campaigns are respectively amortized over a little more than 5 years and over a little more than 2 years.

The table and graph below show the results of our 22 campaigns:

Number of wind turbines
below 3°
Number of wind turbines
between 3°et 5°
Number of wind turbines
below 5°




  • Pre-analysis methodology for the detection of misaligned turbines

Also, we can say that the approach developed by VALEMO for the preliminary analysis of SCADA data has made it possible to detect misaligned machines in more than 75% of cases. In other words, in more than 3 cases out of 4, the operator who provided us with the SCADA data sets made this measurement and realignment campaign perfectly profitable. Moreover, this early detection also allowed to reduce the mechanical efforts on the blades and on the kinematic chain, thus optimizing the lifetime of the major and structural components of the wind turbines.

A responsible approach

In order to properly identify the wind turbines on which a nacelle alignment measurement campaign seems to be necessary, we first perform a performance analysis based on 10 min SCADA data.

This preliminary analysis is based on two standardised performance comparisons: an intra-park comparison and an inter-park comparison. They are done through performance calculations based on SCADA productions, SCADA wind speeds and power deviations from the theoretical power curve.

The intra-farm comparison consists in measuring the differences between the wind turbines in the same farm. Difference calculations are performed over common production periods in order to compare machines under similar environmental conditions. This measurement therefore makes it possible to detect differences in production behaviour between the machines and thus detect the machines most likely to have a performance defect.

The inter-fleet comparison consists of a statistical analysis of the differences within the fleet. The objective is to determine the criticality and abnormality in the statistical sense of the differences between machines. All the machines in a given fleet cannot behave in exactly the same way. On the other hand, some machines have differences with their neighbours that are not found in any other fleet. It is precisely these machines that we identify as problematic and likely to have underperformances and with which we start the measurement campaigns.

Once the measuring device is installed, a first 3-week campaign is carried out to characterize the value of the alignment. In collaboration with the turbine manufacturer the wind turbine is realigned. From this moment on a new 3-week campaign is carried out to make sure that the wind turbine has been correctly realigned.

F. Prévost – Manager– VALEMO

J. Dalmas – Service Manager – VALEMO

A. Lebranchu – PhD R&D Project Engineer – VALEMO


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SACDA data analysis.

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