3-Petri-Net-Modelling-for-Achieving-an-Optimal-Design-of-a-Wind-Turbine-Condition-Monitoring-System.pdf (820.99 kB)
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Petri net modelling for achieving an optimal design of a wind turbine condition monitoring system

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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.

History

School

  • Aeronautical, Automotive, Chemical and Materials Engineering

Department

  • Aeronautical and Automotive Engineering

Published in

Proceedings of the 11th IMA International Conference on Modelling in Industrial Maintenance and Reliability

Source

11th IMA International Conference on Modelling in Industrial Maintenance and Reliability

Publisher

Institute of Mathematics & its Applications

Version

VoR (Version of Record)

Rights holder

© The Authors

Publisher statement

This paper is reproduced here with the permission of the publisher.

Language

en

Location

Virtual

Event dates

29th June 2021 - 1st July 2021

Depositor

Dr Derek Yan. Deposit date: 30 October 2021

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