Symbolic Dynamics Applied to Velocity Time-series in Wind Farms

Abstract

The development of standards for wind farms, presupposes the correct description of wind potential and this can be done with the field measurements of wind flow by cup anemometers. The utilization of new concepts, coming from the world of Cybernetics of Nonlinear Science and Complex Systems could open the road to uncover information hidden in both the mean polar velocity and the mean angle time-series. In particular, with the use of block entropies, it is shown that we can achieve a better and deeper understanding of the phenomenon of filtered turbulence, produced by time-series of the average wind velocity logged every ten minutes. The present analysis allows in principle a characterization of the experimental time-series in terms of the complexity for selected stationary windows of the signal, as well as the underlying mechanisms of the filtered turbulence.