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Research Papers

Importance of Shear in Site Assessment of Wind Turbine Fatigue Loads

[+] Author and Article Information
René M. M. Slot

Department of Civil Engineering,
Aalborg University,
Aalborg 9220, Denmark;
EMD International,
Aalborg 9220, Denmark
e-mail: rmms@civil.aau.dk

Lasse Svenningsen, Morten L. Thøgersen

EMD International,
Aalborg 9220, Denmark

John D. Sørensen

Department of Civil Engineering,
Aalborg University,
Aalborg 9220, Denmark

1Corresponding author.

Contributed by the Solar Energy Division of ASME for publication in the JOURNAL OF SOLAR ENERGY ENGINEERING: INCLUDING WIND ENERGY AND BUILDING ENERGY CONSERVATION. Manuscript received September 24, 2017; final manuscript received March 19, 2018; published online April 9, 2018. Assoc. Editor: Yves Gagnon.

J. Sol. Energy Eng 140(4), 041012 (Apr 09, 2018) (10 pages) Paper No: SOL-17-1395; doi: 10.1115/1.4039748 History: Received September 24, 2017; Revised March 19, 2018

Wind turbines are subjected to fatigue loading during their entire lifetime due to the fluctuating excitation from the wind. To predict the fatigue damage, the design standard IEC 61400-1 describes how to parametrize an on-site specific wind climate using the wind speed, turbulence, wind shear, air density, and flow inclination. In this framework, shear is currently modeled by its mean value, accounting for neither its natural variance nor its wind speed dependence. This very simple model may lead to inaccurate fatigue assessment of wind turbine components, whose structural response is nonlinear with shear. Here we show how this is the case for flapwise bending of blades, where the current shear model leads to inaccurate and in worst case nonconservative fatigue assessments. Based on an optimization study, we suggest modeling shear as a wind speed dependent 60% quantile. Using measurements from almost one hundred sites, we document that the suggested model leads to accurate and consistent fatigue assessments of wind turbine blades, without compromising other main components such as the tower and the shaft. The proposed shear model is intended as a replacement to the mean shear, and should be used alongside the current IEC models for the remaining climate parameters. Given the large number of investigated sites, a basis for evaluating the uncertainty related to using a simplified statistical wind climate is provided. This can be used in further research when assessing the structural reliability of wind turbines by a probabilistic or semiprobabilistic approach.

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References

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Stensgaard Toft, H. , Svenningsen, L. , Moser, W. , Dalsgaard Sørensen, J. , and Lybech Thøgersen, M. , 2016, “ Wind Climate Parameters for Wind Turbine Fatigue Load Assessment,” ASME J. Sol. Energy Eng., 138(3), p. 031010. [CrossRef]
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Figures

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Fig. 1

Absolute latitude distribution of all considered sites

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Fig. 2

Variation of damage equivalent loads for blade root flapwise bending for each wind climate parameter as function of wind speed. The loads are normalized with turbine class IIB design loads for comparison.

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Fig. 3

Variation of damage equivalent loads for varying wind shear as function of wind speed for selected sensors in Table 2. The loads are normalized with turbine class IIB design loads for comparison.

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Fig. 4

Visualization of FDRs used to assess the accuracy of the wind shear models

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Fig. 5

Wind measurements from Karlsruhe before and after screening including statistical parameters used for the analysis

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Fig. 6

Fatigue damage ratio for varying wind shear models across all studied sites. The results are ranked to emphasize the consistency in fatigue damage assessment across sites, and the results from the case study are marked with crosses.

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Fig. 7

Basic descriptive statistics of FDR1 for blade root flapwise moment as function of shear exponent quantile. The results using the current IEC 61400-1 wind shear model are shown for comparison as dashed lines.

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Fig. 8

FDR1 for varying wind shear models for 10 years of measurements at Karlsruhe. The scale of the y-axis represents that of Fig. 6 for easy comparison.

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Fig. 9

Shear exponent and turbulence before and after applying the despike algorithm. The upper plots show the shear exponent and the lower plots the turbulence. To the left are shown scatter plots and selected spikes are encased with black circles and shown in the time domain to the right. Notice that the spikes are replaced and not discarded.

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