Design of wind turbine fault detection system based on performance curve

Wind energy is currently the fastest growing source of renewable energy used for electrical generation around world. Wind farms are adding a significant amount of electrical generation capacity. The increase in the number of wind farms has led to the need for more effective operation and maintenance procedures. Condition Monitoring System(CMS) can be used to aid plant owners in achieving these goals. Its aim is to provide operators with information regarding the health of their machines, which in turn, can help them improve operational efficiency. In this work, wind turbine fault detection system based on wind vs. power performance curve obtained from SCADA is studied. Considered fault detection scheme utilizes artificial neural network for training normal behavior of wind turbine system. Furthermore, In order to verify the effectiveness of the performance curve based fault detection scheme, SCADA data obtained from 850kW wind turbine system installed in Kunsan Korea are used and various simulation studies were carried out.