Reliability assessment of wind turbines based on failure rate and down time estimation

This study undertakes an analysis of supervisory control and data accusation system(SCADA)alarm statistics to determine failure rate and down time of wind turbine system(WTS).The underlying aim is to evaluate the performance and provide recommendations to improve the system’s reliability. The focus of this study is an on shore wind farm, located in Pakistan, with type-IV (permanent magnet direct drive)wind turbines(WTs )over the course of last 3 years of operations. The presented data can help to provide a better understanding of early life operations and performance, since all stoppages logged in the event record that caused the WTs not to generate electricity were considered in this study. This analysis was conducted for a complete wind farm for finding the most vulnerable/critical components. Data analytics identified that power converter and pitch system in wind farm emerged as leading contributors to failure rate and down time across the years 2020, 2021, and 2022. This trend was evident both in the analysis of each year and in the cumulative data, highlighting these components as critical areas for improving there liability and efficiency of WTs. The cumulative total failure frequency rate and downtime of the windfarm over the 3years were found to be 449 and2811 h, respectively. Results further emphasize that the pitch system and power converter are the most vulnerable/critical components based on their failure frequency and associated downtime, therefore, original equipment manufacturers should focus on these components to improve operating time and availability.