Condition monitoring systems are increasingly installed in wind turbine generators with the goal of providing component-specific information to the wind farm operator and hence increase equipment availability through maintenance and operating actions based on this information. In some cases, however, the economic benefits of such systems are unclear. A quantitative measure of these benefits may therefore be of value to utilities and O&M groups involved in planning and operating wind farm installations. The development of a probabilistic model based on discrete-time Markov Chain solved via Monte Carlo methods to meet these requirements is illustrated. Potential value is demonstrated through case study simulations.
|Number of pages||11|
|Publication status||Published - 10 May 2007|
|Event||European Wind Energy Conference & Exhibition 2007 - Milan, Italy|
Duration: 7 May 2007 → 10 May 2007
|Conference||European Wind Energy Conference & Exhibition 2007|
|Abbreviated title||EWEC 2007|
|Period||7/05/07 → 10/05/07|
- condition monitoring
- probabilistic model
- Monte Carlo Markov chains
- wind turbine generators
Mcmillan, D., & Ault, G. W. (2007). Towards quantification of condition monitoring benefit for wind turbine generators. 1-11. Paper presented at European Wind Energy Conference & Exhibition 2007, Milan, Italy.