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Petri net modelling for achieving an optimal design of a wind turbine condition monitoring system
Condition monitoring has demonstrated its effectiveness in improving the economic return of wind turbines. However, a wind turbine consists of hundreds, even thousands, of mechanical, electrical and power electronic components. The failure of any one of them may lead to the shutdown of the turbine....
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| Main Authors: | , , |
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| Format: | Default Conference proceeding |
| Published: |
2021
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| Subjects: | |
| Online Access: | https://hdl.handle.net/2134/16908958.v1 |
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| Summary: | Condition monitoring has demonstrated its effectiveness in improving the economic return of wind turbines. However, a wind turbine consists of hundreds, even thousands, of mechanical, electrical and power electronic components. The failure of any one of them may lead to the shutdown of the turbine. For this reason, a variety of component monitoring systems have been developed dedicated to monitoring these different components. Consequently, a wind turbine usually needs to be monitored simultaneously by several different types of component monitoring systems that benefit wind turbine operation and maintenance to different extents. This not only increases the complexity of the hardware configuration but also increases the costs of the entire condition monitoring system. How to achieve a condition monitoring system that can monitor the most vulnerable components whilst bringing the most economic benefit to the wind turbine operator is an important question. The aim of this paper is to answer such a question with the aid of the Petri net modelling method. The model developed in the paper will investigate the influences of condition monitoring systems and fault detection using wind farm Supervisory Control and Data Acquisition (SCADA) system on the economic return of wind turbines, thereby providing a feasible tool for constructing an optimal wind turbine condition monitoring system. |
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