Bond Graph Algorithms for Fault Detection and Isolation in Wind Energy Conversion

The use of wind energy has increased during the last years; however, wind power varies greatly throughout the day creating important intermittence problems. This paper deals with the modeling, fault detection and isolation of wind turbine generation systems by bond graph approach. The modeling of the wind phenomenon, the turbine mechanical system and the electrical machine, along with the corresponding converter and electrical grid are described, and the problem of fault diagnosis in wind energy conversion is addressed. One of the original points in this work is the use of a new fault detection and isolation method. The proposed method avoids the exploration of all the combinations for its application to the diagnostic of this system operation. The causal paths are used to generate the analytical redundancy relations at each computation step based on the constitutive and structural junction relations. This is shown through an algorithm for monitoring the system by sensor placements on the corresponding bond graph model. The performance of the developed algorithm is evaluated on a model of a commercial sized 4.8 MW wind turbine.