DocumentCode :
740439
Title :
Economic evaluation of maintenance strategies for wind turbines: a stochastic analysis
Author :
Kerres, Bertrand ; Fischer, Katharina ; Madlener, Reinhard
Author_Institution :
Dept. of Machine Design, KTH R. Inst. of Technol., Stockholm, Sweden
Volume :
9
Issue :
7
fYear :
2015
Firstpage :
766
Lastpage :
774
Abstract :
The authors develop a stochastic model for assessing the life-cycle cost and availability of wind turbines resulting from different maintenance scenarios, with the objective to identify the most cost-effective maintenance strategy. Using field-data-based reliability models, the wind turbine - in terms of reliability - is modelled as a serial connection of the most critical components. Both direct cost for spare parts, labour and access to the turbine, as well as indirect cost from production losses are explicitly taken into account. The model is applied to the case of a Vestas V44-600 kW wind turbine. Results of a reliability-centred maintenance analysis of this wind turbine are used to select the most critical wind turbine components and to identify possible maintenance scenarios. This study reveals that corrective maintenance is the most cost-effective maintenance strategy for the gearbox and the generator of the V44 turbine, while the cost benefit of condition-based maintenance using online condition-monitoring systems increases with higher electricity price, turbine capacity and remoteness of sites.
Keywords :
condition monitoring; costing; life cycle costing; maintenance engineering; power system economics; power system reliability; wind turbines; Vestas V44 wind turbine; condition-based maintenance; cost effective maintenance strategy; critical wind turbine components; economic evaluation; electricity price; field data-based reliability model; gearbox; lifecycle cost assessment; online condition monitoring systems; power 600 kW; production losses; reliability centred maintenance analysis; serial connection; stochastic model; turbine capacity;
fLanguage :
English
Journal_Title :
Renewable Power Generation, IET
Publisher :
iet
ISSN :
1752-1416
Type :
jour
DOI :
10.1049/iet-rpg.2014.0260
Filename :
7209073
Link To Document :
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