Implementation of Digital Twin-Assisted Condition Monitoring and Fault Diagnosis for Wind Turbines

To achieve higher efficiency and reduce the wind energy cost, the size of wind turbines is getting bigger and offshore wind is getting more attraction. Therefore, the Operation & Maintenance of a single wind turbine and a large-scale wind farm are becoming more important. This paper presents the implementation of digital twin-assisted condition monitoring and fault diagnosis for wind turbines. Based on a 5-dimension modeling approach, we design and implement a digital twin for a 2 MW class double-fed induction generator-based wind turbine system. Then, we suggest an algorithm based on the digital twin framework to virtually monitor wind turbine conditions and form an initial fault detection algorithm. The digital twin shows high accuracy and the digital twin-based diagnosis algorithm shows a high performance.