Quantification of Condition Monitoring Benefit for Offshore Wind Turbines

被引:108
作者
McMillan, David [1 ]
Ault, Graham [1 ]
机构
[1] Univ Strathclyde, Inst Energy & Environm, Royal Coll Bldg,204 George St, Glasgow G1 1XW, Lanark, Scotland
基金
英国工程与自然科学研究理事会;
关键词
Wind Farms; Condition Monitoring; Operations and Maintenance; Markov Chain; Monte Carlo; Probabilistic Model;
D O I
10.1260/030952407783123060
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Condition monitoring (CM) systems are increasingly installed in wind turbines with the goal of providing component-specific information to wind farm operators, theoretically increasing equipment availability via maintenance and operating actions based on this information. In the offshore case, economic benefits of CM systems are often assumed to be substantial, as compared with experience of onshore systems. Quantifying this economic benefit is non-trivial, especially considering the general lack of utility experience with large offshore wind farms. A quantitative measure of these benefits is therefore of value to utilities and operations and maintenance (O & M) groups involved in planning and operating future offshore wind farms. The probabilistic models presented in this paper employ a variety of methods including discrete-time Markov Chains, Monte Carlo methods and time series modelling. The flexibility and insight provided by this framework captures the necessary operational nuances of this complex problem, thus enabling evaluation of wind turbine CM offshore. The paper concludes with a study of baseline CM benefit, sensitivity to O & M costs and finally effectiveness of the CM system itself.
引用
收藏
页码:267 / 285
页数:19
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