International standards for wind turbine certification depend on finding long-term fatigue load distributions that are conservative with respect to the state of knowledge for a given system. Statistical models of loads for fatigue application are described and demonstrated using flap and edge blade-bending data from a commercial turbine in complex terrain. Distributions of rainflow-counted range data for each ten-minute segment are characterized by parameters related to their first three statistical moments (mean, coefficient of variation, and skewness). Quadratic Weibull distribution functions based on these three moments are shown to match the measured load distributions if the non-damaging low-amplitude ranges are first eliminated. The moments are mapped to the wind conditions with a two-dimensional regression over ten-minute average wind speed and turbulence intensity. With this mapping, the short-term distribution of ranges is known for any combination of average wind speed and turbulence intensity. The long-term distribution of ranges is determined by integrating over the annual distribution of input conditions. First, we study long-term loads derived by integration over wind speed distribution alone, using standard-specified turbulence levels. Next, we perform this integration over both wind speed and turbulence distribution for the example site. Results are compared between standard-driven and site-driven load estimates. Finally, using statistics based on the regression of the statistical moments over the input conditions, the uncertainty (due to the limited data set) in the long-term load distribution is represented by 95% confidence bounds on predicted loads.

Fitzwater, L. M., and Winterstein, S. R., 2001, “Predicting Design Wind Turbine Loads from Limited Data: Comparing Random Process and Random Peak Models,” A Collection of the 2001 ASME Wind Energy Symp. Technical Papers Presented at the 39th AIAA Aerospace Sciences Meeting and Exhibit, Reno NV, AIAA-2001-0046, January 2001.
McCoy, T. J., Malcolm, D. J., and Griffin, D. A., 1999, “An Approach to the Development of Turbine Loads in Accordance with IEC 1400-1 and ISO 2394,” A Collection of the 1999 ASME Wind Energy Symp. Technical Papers Presented at the 37th AIAA Aerospace Sciences Meeting and Exhibit, Reno NV, AIAA-99-0020, pp. 1–9, January 1999.
K. O.
, and
C. J.
, “
Reliability-based fatigue design of wind-turbine rotor blades
Eng. Struct.
, pp.
P. S.
, and
S. R.
, “
Application of Measured Loads to Wind Turbine Fatigue and Reliability Analysis
ASME J. Sol. Energy Eng.
, No.
, pp.
IEC/TC88, 61400-1, 1998, Wind Turbine Generator Systems–Part 1: Safety Requirements, Int. Electrotechnical Commission, Geneva, Switzerland.
IEC/TC88, Draft IEC 61400-13 TS, 1999, Edition 1: Wind turbine generator systems–Part 13: Measurement of Mechanical Loads, 88/120/CDV, Int. Electrotechnical Commission, Geneva, Switzerland.
Butterfield, S., Holley, B., Madsen, P. H., and Stork, C., 1997, Report on 88/69/CD–Wind Turbine Generator Systems-Part 1: Safety Requirements, 2 Edition, National Renewable Energy Laboratory, Golden CO.
MOUNTURB, 1996, Load and Power Measurement Program on Wind Turbines Operating in Complex Mountainous Regions, Volumes. I-III, P. Chaviaropoulos (ed.), A. N. Fragoulis (Coord), CRES, RISO, ECN, NTUA-FS, CRES, Pikermi, Greece.
Manuel, L., Kashef, T., and Winterstein, S. R., 1999, Moment-Based Probability Modeling and Extreme Response Estimation the Fits Routine, Version 1.2, SAND99-2985, Sandia National Laboratories, Albuquerque NM.
Lange, C. H., 1996, Probabilistic Fatigue Methodology and Wind Turbine Reliability, SAND96-1246, Sandia National Laboratories, Albuquerque NM.
Lange, C. H., and Winterstein, S. R., 1996, “Fatigue Design of Wind Turbine Blades: Load and Resistance Factors from Limited Data,” Proc. of Energy Week Conference & Exhibition Incorporating ETCE, Book VIII, Wind Energy, Houston TX, pp. 93–101.
Nelson, D. V., and Fuchs, H. O., 1997, “Predictions of Cumulative Fatigue Damage using Condensed Load Histories,” Fatigue under Complex Loading: Analysis and Experiments, Advances in Engineering, Vol. 6, R. M. Wetzel (ed.), SAE, Warrendale PA, pp. 163–187.
Haver, S., 2001, “Application of Stochastic Methods in Structural Design–The Offshore Experience,” A collection of the 2001 ASME Wind Energy Symp., at the AIAA Aerospace Sciences Mtg, Reno NV, AIAA-2001-0043, January 2001.
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