An opportunistic maintenance strategy for wind turbines

D M Wang; W Teng; GSR Zhang; X F Qu; Y B Liu; Z Y Ma; A Kusiak

doi:10.1049/rpg2.12283

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An opportunistic maintenance strategy for wind turbines

Journal article

Open access

Peer reviewed

An opportunistic maintenance strategy for wind turbines

D M Wang, W Teng, GSR Zhang, X F Qu, Y B Liu, Z Y Ma and A Kusiak

IET RENEWABLE POWER GENERATION, Vol.15(16), pp.3793-3805

2021

DOI: 10.1049/rpg2.12283

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Abstract

Maintenance strategies aim at reduction of the operation and maintenance cost of wind turbines. An opportunistic maintenance strategy offers cost advantages over the traditional preventive replacement maintenance strategy by considering cost dependency among maintenance activities. A new opportunistic maintenance strategy of wind turbines is proposed here. First, the proposed strategy includes two sets of reliability thresholds to handle subassemblies those are in operational and failed wind turbines. Using the reliability thresholds, ten maintenance modes and their service conditions are presented. Second, the Weibull distribution with an age reduction factor is introduced to describe reliability variation of subassemblies under imperfect maintenance. Third, the maintenance cost in each maintenance mode is expressed by a reliability variation-based function that is dependent on the stage of maintenance activities. Fourth, due to the randomness of failures, the expected total maintenance cost is determined with Monte Carlo simulation. The proposed approach has been validated with the data provided by a wind farm located in Northern China.

Details

Title: Subtitle: An opportunistic maintenance strategy for wind turbines
Creators: D M Wang - Harbin Electric Company Limited Harbin China
W Teng - North China Electric Power University
GSR Zhang
X F Qu - Harbin Electric Company Limited Harbin China
Y B Liu - North China Electric Power University
Z Y Ma - North China Electric Power University
A Kusiak - University of Iowa
Resource Type: Journal article
Publication Details: IET RENEWABLE POWER GENERATION, Vol.15(16), pp.3793-3805
DOI: 10.1049/rpg2.12283
ISSN: 1752-1424
Grant note: DOI: 10.13039/501100001809, name: National Natural Science Foundation of China, award: 51775186
Language: English
Date published: 2021
Academic Unit: Industrial and Systems Engineering; Nursing
Record Identifier: 9984231951002771

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