DocumentCode :
3310034
Title :
Optimization of wind turbines operation and maintenance using failure prognosis
Author :
Tamilselvan, Prasanna ; Wang, Yibin ; Wang, Pingfeng
Author_Institution :
Dept. of Ind. & Manuf. Eng., Wichita State Univ., Wichita, KS, USA
fYear :
2012
fDate :
18-21 June 2012
Firstpage :
1
Lastpage :
9
Abstract :
Advances in high performance sensing and signal processing technology enable the development of failure prognosis tools for wind turbines to detect, diagnose, and predict the system-wide effects of failure events. Although prognostics can provide valuable information for proactive actions in preventing system failures, the benefits have not been fully utilized for the operation and maintenance decision making of wind turbines. This paper presents a generic failure prognosis informed decision making tool for wind farm operation and maintenance while considering the predictive failure information of individual turbine and its uncertainty. In the presented approach, the probabilistic damage growth model is used to characterize individual wind turbine performance degradation and failure prognostics, whereas the economic loss measured by monetary values and environmental performance measured by unified carbon credits are considered in the decision making process. Based on the customized wind farm information inputs, the developed decision making methodology can be used to identify optimum and robust strategies for wind farm operation and maintenance in order to maximize the economic and environmental benefits concurrently. The efficacy of proposed prognosis informed maintenance strategy is compared with the condition based maintenance strategy and demonstrated with the case study.
Keywords :
condition monitoring; maintenance engineering; mechanical engineering computing; signal processing; wind turbines; condition based maintenance strategy; economic loss; environmental performance; failure event detection; failure event diagnosis; failure event prediction; failure prognosis; high performance sensing technology; monetary value; prognosis informed maintenance strategy; signal processing technology; system failure prevention; wind farm maintenance; wind farm operation; wind turbines maintenance; wind turbines operation; Decision making; Economics; Maintenance engineering; Production; Stochastic processes; Wind farms; Wind turbines; Operation and Maintenance; Prognostics; Wind Turbine; optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Prognostics and Health Management (PHM), 2012 IEEE Conference on
Conference_Location :
Denver, CO
Print_ISBN :
978-1-4673-0356-9
Type :
conf
DOI :
10.1109/ICPHM.2012.6299538
Filename :
6299538
Link To Document :
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