  The power conversion process of a wind turbine can be characterized by a
stochastic differential equation (SDE) of the power output conditioned to
certain fixed wind speeds. An analogous approach can also be applied to the
mechanical loads on a wind turbine, such as generator torque. The constructed
SDE consists of the deterministic and stochastic terms, the latter
corresponding to the highly fluctuating behavior of the wind turbine. Here we
show how advanced stochastic analysis of the noise contribution can be used to
show different operating modes of the conversion process of a wind turbine. The
parameters of the SDE, known as Kramers-Moyal (KM) coefficients, are estimated
directly from the measurement data. Clear evidence is found that both,
continuous diffusion noise and discontinuous jump noise are present. The
difference in the noise contributions indicates different operational regions.
In particular, we observe that the jump character or discontinuity in power
production has a significant contribution in the regions where the control
system switches strategies. We find that there is a high increase in jump
amplitude near the transition to the rated region, and the switching strategies
cannot result in a smooth transition. The proposed analysis provides new
insights to the control strategies of the wind turbine.
