DocumentCode
3437270
Title
Maintenance modeling and optimization for wind turbine systems: A review
Author
Fangfang Ding ; Zhigang Tian ; Tongdan Jin
Author_Institution
Dept. of Mech. & Ind. Eng., Concordia Univ., Montreal, QC, Canada
fYear
2013
fDate
15-18 July 2013
Firstpage
569
Lastpage
575
Abstract
Wind power is a clean and sustainable energy resource to meet the growing electricity needs in the next 20-30 years. However operation and maintenance (O&M) of wind power systems counts for as much as 25-30% of the total energy production cost, which creates intensive interests in lowering the lifecycle costs. This paper reviews the maintenance methodologies recently developed for wind power industry. The review aims at surveying recent reliability analysis and maintenance models underpinning the decision on equipment inspection, repair and replacement. We also discuss the applications and limitations of these models. Based on the review some future research areas are proposed.
Keywords
electricity supply industry; inspection; life cycle costing; maintenance engineering; optimisation; production equipment; reliability; sustainable development; wind power; wind turbines; O&M; electricity needs; equipment inspection; equipment repair; equipment replacement; lifecycle cost; maintenance methodologies; maintenance modeling; maintenance models; operation and maintenance; optimization; reliability analysis; sustainable energy resource; total energy production cost; wind power industry; wind power systems; Degradation; Industries; Maintenance engineering; Power system reliability; Reliability; Wind power generation; Wind turbines; condition-based maintenance; health prognostic; maintenance optimization; opportunistic maintenance; reliability;
fLanguage
English
Publisher
ieee
Conference_Titel
Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE), 2013 International Conference on
Conference_Location
Chengdu
Print_ISBN
978-1-4799-1014-4
Type
conf
DOI
10.1109/QR2MSE.2013.6625648
Filename
6625648
Link To Document