Wind-based energy generation has special priority in efforts related to global sustainability. Based on this priority and the desire for... Show moreWind-based energy generation has special priority in efforts related to global sustainability. Based on this priority and the desire for increase in electricity generation, the size of wind turbines has been tremendously increased in recent years. Moreover, larger wind turbines have access to more stable wind speeds which assists in electricity generation consistency. However, larger wind turbines are more prone to exhibit structural failure due to the increase of size as well as presence of complexities in the structure and wind load interaction. As such, condition monitoring and fault diagnosis of wind turbines are crucial in their sustainable operation. In this work, a new framework for condition assessment of wind turbine towers is developed. This framework enhances the ability to assess the structural condition of in-service wind turbine towers. Using this framework: 1) the wind data for the wind turbine location is collected, 2) a series of numerical modeling and analysis for the wind turbine tower for various wind velocities are performed to obtain the maximum induced stresses and their corresponding critical fatigue components (hot spots), and 3) fatigue analysis is performed leading to prediction for the remaining life of the wind turbine tower. To illustrate the capability of the present method, a case study is performed on an existing wind turbine. The obtained analytical results are compared and verified by the original design parameters. The results obtained for life prediction of the wind turbine tower correlate with life predictions of other existing wind turbine towers. It is anticipated that application of this framework for existing and future wind turbines will enhance their inspection planning as well as offer a more cost-effective process for repair and rehabilitation of wind turbine towers. This will ultimately increase the overall safety of wind turbine systems and enhance their reliability of performance.Keywords: Wind Turbine Tower, Condition Assessment, Life Prediction. Show less
