Context
Wind turbines are subject to a high level of stress for several reasons. An accurate assessment of the health status of the turbine is essential for rational optimisation of the control, and for better burden sharing when dealing with farms.
Need
To deduce ageing indicators of wind turbines operating in the same area from SCADA operating data (105 dimension vector, Engie Open Data) in order to supervise the ageing of a wind farm and optimise its maintenance planning.
Solution
An average ageing model for the whole wind farm was built, showing the comparative ageing and loading on the turbines and their subsystems in the same wind farm. Comparative ageing allowed the detection of overloaded or underloaded turbines and the distribution of the load to avoid premature ageing.
Results
