From the center of wind pressure to loads on the wind turbine: a stochastic approach for the reconstruction of load signals

Abstract

In the context of the wind industry, there is an increasing need for a more comprehensive understanding of atmospheric wind conditions. A particular emphasis is required concerning wind structures, which have not been thoroughly investigated in the prevailing standard guidelines. This necessity arises in light of the current trends toward larger, higher, and more flexible wind turbine designs. Of particular importance are the correlations between the yet-to-be-characterized atmospheric turbulent structures and the specific responses of the turbines. These correlations may be crucial in assessing load events relevant to new designs that were negligible for the earlier, smaller, and stiffer turbines. The center of wind pressure (CoWP) (Schubert et al., 2025) was recently introduced as a feature of a wind field that characterizes large-scale wind structures and, at the same time, correlates with the large-scale or low-frequency content of the bending moments at the main shaft of the wind turbines. In this paper, we comprehensively compare the CoWP and the bending moments in terms of their statistical properties and fatigue estimates, quantified by damage equivalent loads (DELs). Furthermore, a stochastic method for the reconstruction of synthetic CoWP signals is proposed. The strong correlation with the bending moments enables the proposed stochastic CoWP model to serve as a relatively simple surrogate and estimator of the large-scale dynamics of these loads, which is based solely on the properties of the inflow wind field. A notable advantage of the stochastic approach is its capability to reconstruct very long time series, required for evaluating loads over the operational lifetime of the turbine. For such lifetime estimations on wind turbines, it is necessary to combine the proposed model for large-scale dynamics with a corresponding model for small-scale features, site-specific wind conditions, and turbine-specific characteristics. The proposed stochastic model of the CoWP can be used not only for load assessment, but also for characterizing large-scale wind structures. The model offers an advanced description of wind phenomena, with the potential to be integrated as an extension of prevailing wind turbulence models.