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Title: Wind Turbine Reliability.

Abstract

Abstract not provided.

Authors:
Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1268229
Report Number(s):
SAND2007-0376C
524371
DOE Contract Number:
AC04-94AL85000
Resource Type:
Conference
Resource Relation:
Conference: Proposed for presentation at the AWEA Wind Power Asset Management Workshop held January 23-24, 2007 in San Diego, CA.
Country of Publication:
United States
Language:
English

Citation Formats

Hill, Roger Ray. Wind Turbine Reliability.. United States: N. p., 2007. Web.
Hill, Roger Ray. Wind Turbine Reliability.. United States.
Hill, Roger Ray. Mon . "Wind Turbine Reliability.". United States. doi:. https://www.osti.gov/servlets/purl/1268229.
@article{osti_1268229,
title = {Wind Turbine Reliability.},
author = {Hill, Roger Ray},
abstractNote = {Abstract not provided.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon Jan 01 00:00:00 EST 2007},
month = {Mon Jan 01 00:00:00 EST 2007}
}

Conference:
Other availability
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  • 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 andmore » 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 break down of how many components are likely to fail. This break down 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.« less
  • 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 andmore » 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 break down of how many components are likely to fail. This break down 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.« less