DocumentCode :
136061
Title :
Condition Based Maintenance optimization of wind turbine system using degradation prediction
Author :
Pazouki, Elham ; Bahrami, Hamid Reza ; Seungdeog Choi
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Akron, Akron, OH, USA
fYear :
2014
fDate :
27-31 July 2014
Firstpage :
1
Lastpage :
5
Abstract :
This paper proposes an optimal Condition Based Maintenance (CBM) policy for a multi-component system. Especially, multicomponent wind turbine has been analyzed to investigate cost relationship between maintenance and energy production schedule. Wind turbine consists of numerous mechanical and electrical components, and each of which shows independent stochastic deterioration process. The fundamental of proposed strategy is derived based on the statistically modeled aging and deterioration of each critical component in the wind turbine system to optimally schedule CBM task. Scheduling the CBM task is variably and iteratively performed through optimizing joint failure probability threshold and inspection/maintenance interval to minimize the total designed cost function. The proposed designed cost function is especially defined to dynamically reflect the various operation, maintenance, and production conditions of wind turbine systems. In addition, this paper proposes life time enhancement factor to investigate the performance of CBM task in terms of achieved designed cost. The proposed CBM policy is theoretically analyzed and justified through a case study using wind farm operation and maintenance cost data.
Keywords :
failure analysis; maintenance engineering; optimisation; power generation scheduling; wind power plants; wind turbines; CBM task; condition maintenance optimization; degradation prediction; electrical components; energy production schedule; failure probability threshold; independent stochastic deterioration process; inspection-maintenance; life time enhancement factor; mechanical components; multicomponent wind turbine; optimal condition maintenance policy; wind farm operation; Biological system modeling; Degradation; Inspection; Maintenance engineering; Optimization; Predictive models; Wind turbines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
PES General Meeting | Conference & Exposition, 2014 IEEE
Conference_Location :
National Harbor, MD
Type :
conf
DOI :
10.1109/PESGM.2014.6939918
Filename :
6939918
Link To Document :
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