The cost of repairing or replacing failed components depends on the number and timing of failures. Although the total probability of individual component failure is sometimes interpreted as the percentage of components likely to fail, this perception is often far from correct. Different amounts of common versus independent uncertainty can cause different numbers of components to be at risk of failure. The FAROW tool for fatigue and reliability analysis of wind turbines makes it possible for the first time to conduct a detailed economic analysis of the effects of uncertainty on fleet costs. By dividing the uncertainty into common and independent parts, the percentage of components expected to fail in each year of operation is estimated. Costs are assigned to the failures and the yearly costs and present values are computed. If replacement cost is simply a constant multiple of the number of failures, the average, or expected cost is the same as would be calculated by multiplying by the probability of individual component failure. However, more complicated cost models require a breakdown of how many components are likely to fail. This breakdown enables the calculation of costs associated with various probability of occurrence levels, illustrating the variability in projected costs. Estimating how the numbers of components expected to fail evolves over time is also useful in calculating the present value of projected costs and in understanding the nature of the financial risk.

Issue Section:
Research Papers
Topics:
Fatigue, Reliability, Uncertainty, Wind turbines, Failure, Probability, Economic analysis, Event history analysis, Financial risk, Maintenance, Risk
1.
ASCE, 1982, “Fatigue Reliability: Introduction,” by The Committee on Fatigue and Fracture Reliability of the Committee on Structural Safety and Reliability of the Structural Division, Journal of the Structural Division, American Society of Civil Engineers, Vol. 108, No. STl.
2.
Jackson, K., 1992, “Deriving Fatigue Design Loads from Field Test Data,” Proc. WindPower ’92, American Wind Energy Association, pp. 313–320.
3.
Spera, D. A., 1994, “Fatigue Design of Wind Turbines,” Wind Turbine Technology, D. A. Spera, ed., ASME, New York, pp. 547–588.
4.
Sutherland, H. J., Veers, P. S., and Ashwill, T. D., 1994, “Fatigue Life Prediction for Wind Turbines: A Case Study in Loading Spectra and Parameter Sensitivity,” Case Studies for Fatigue Education, ASTM STP 1250, R. I. Stephens, ed., American Society for Testing and Materials, Philadelphia, PA, pp. 174–207.
5.
Sutherland, H. J., 1989, “Analytical Framework for the LIFE2 Computer Code,” SAND89-1397, Sandia National Laboratories, Albuquerque, NM.
6.
Van Den Avyle, J. A., and Sutherland, H. J., 1989, “Fatigue Characterization of a VAWT Blade Material,” Eighth ASME Wind Energy Symposium, SED-Vol. 7, Berg and Klimas, eds., ASME, New York, pp. 125–130.
7.
Veers, P. S., Winterstein, S. R., Lange, C. H., and Wilson, T. A., 1994, “User’s Manual for FAROW: Fatigue and Reliability of Wind Turbine Components,” SAND94-2460, Sandia National Laboratories, Albuquerque, NM.
8.
Veers, P. S., 1989, “Simplified Fatigue Damage and Crack Growth Calculations for Wind Turbines,” Eighth ASME Wind Energy Symposium, P. C. Klimas and D. E. Berg, eds., SED-Vol. 9, pp. 133–140.
9.
Veers
P. S.
,
1982
, “
Blade Fatigue Life Assessment with Application to VAWTs
,”
ASME JOURNAL OF SOLAR ENERGY ENGINEERING
, Vol.
104
, pp.
106
–
111
.
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