Predicting the capacity factor of wind farms using deep neural networks for estimating age related performance degradation.

Performance of wind energy conversion systems gradually decline over its life cycle. Understanding this age-related performance degradation is essential in efficiently maintaining and managing these systems. In case of wind farms where sufficient time series performance data are available through SCADA, the decline in the wind farm level performance can be modelled though data driven methods. In this work, we propose such a deep neural network (DNN) model for predicting the capacity factor, which can further be used in analysing the age-related performance degradation of wind farms.