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Title: Chapter 15: Reliability of Wind Turbines

Abstract

The global wind industry has witnessed exciting developments in recent years. The future will be even brighter with further reductions in capital and operation and maintenance costs, which can be accomplished with improved turbine reliability, especially when turbines are installed offshore. One opportunity for the industry to improve wind turbine reliability is through the exploration of reliability engineering life data analysis based on readily available data or maintenance records collected at typical wind plants. If adopted and conducted appropriately, these analyses can quickly save operation and maintenance costs in a potentially impactful manner. This chapter discusses wind turbine reliability by highlighting the methodology of reliability engineering life data analysis. It first briefly discusses fundamentals for wind turbine reliability and the current industry status. Then, the reliability engineering method for life analysis, including data collection, model development, and forecasting, is presented in detail and illustrated through two case studies. The chapter concludes with some remarks on potential opportunities to improve wind turbine reliability. An owner and operator's perspective is taken and mechanical components are used to exemplify the potential benefits of reliability engineering analysis to improve wind turbine reliability and availability.

Authors:
;
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Wind and Water Technologies Office (EE-4W)
OSTI Identifier:
1360890
Report Number(s):
NREL/CH-5000-67496
DOE Contract Number:  
AC36-08GO28308
Resource Type:
Book
Country of Publication:
United States
Language:
English
Subject:
17 WIND ENERGY; wind turbines; reliability; reliability engineering; life data analysis; wind energy; wind plants

Citation Formats

Sheng, Shuangwen, and O'Connor, Ryan. Chapter 15: Reliability of Wind Turbines. United States: N. p., 2017. Web. doi:10.1016/B978-0-12-809451-8.00015-1.
Sheng, Shuangwen, & O'Connor, Ryan. Chapter 15: Reliability of Wind Turbines. United States. doi:10.1016/B978-0-12-809451-8.00015-1.
Sheng, Shuangwen, and O'Connor, Ryan. Fri . "Chapter 15: Reliability of Wind Turbines". United States. doi:10.1016/B978-0-12-809451-8.00015-1.
@article{osti_1360890,
title = {Chapter 15: Reliability of Wind Turbines},
author = {Sheng, Shuangwen and O'Connor, Ryan},
abstractNote = {The global wind industry has witnessed exciting developments in recent years. The future will be even brighter with further reductions in capital and operation and maintenance costs, which can be accomplished with improved turbine reliability, especially when turbines are installed offshore. One opportunity for the industry to improve wind turbine reliability is through the exploration of reliability engineering life data analysis based on readily available data or maintenance records collected at typical wind plants. If adopted and conducted appropriately, these analyses can quickly save operation and maintenance costs in a potentially impactful manner. This chapter discusses wind turbine reliability by highlighting the methodology of reliability engineering life data analysis. It first briefly discusses fundamentals for wind turbine reliability and the current industry status. Then, the reliability engineering method for life analysis, including data collection, model development, and forecasting, is presented in detail and illustrated through two case studies. The chapter concludes with some remarks on potential opportunities to improve wind turbine reliability. An owner and operator's perspective is taken and mechanical components are used to exemplify the potential benefits of reliability engineering analysis to improve wind turbine reliability and availability.},
doi = {10.1016/B978-0-12-809451-8.00015-1},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Fri May 19 00:00:00 EDT 2017},
month = {Fri May 19 00:00:00 EDT 2017}
}

Book:
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