Method for training a machine learning model usable for determining a remaining useful life of a wind turbine

A computer-implemented method for training a machine learning model used for determining a remaining useful life of a further wind turbine, comprising:

• providing a plurality of operation data sets of a reference wind turbine;
• providing a plurality of load data sets of the reference wind turbine, wherein a load data set is based on at least one load parameter measured at the reference wind turbine;
• and
• generating a plurality of wind turbine training data sets for training the machine learning model by synchronously assigning a respective operation data set with a respective load data set,
• wherein the plurality of wind turbine training data sets are in the form of text data, from which a presentation in form of a vector, a matrix, and/or a tensor is generated, and
• wherein the step of generating the plurality of wind turbine training data sets comprises the step of generating approximately 100.000 wind power training data sets;
• and
• training the machine learning model on the plurality of wind turbine training data sets.