Optimizing wind power plants: Time series analysis
The focus of our work is the development, implementation and application of causality measures on time series and noisy dynamical systems. These measures are interesting firstonce in theoretical terms. On the other hand it can be applied to real data and stochastic models. A special area of application is the time series analysis of the power outputs of wind power plants (WPP) in a wind farm. The coupling of these power outputs shall be investigated depending on the wind conditions. For instance, in order to establish a suitable model for a wind farm, the time delay has to be taken into account, which occurs between individual WPP. Those time delays arise by the distances between the WPP and have an additional origin in the alteration of the wind field by the WPP themselves. Conceivably these time delays have to be mechanistically woven into a family of multi dimensional Langevin - models, which is parameterized by the wind conditions. In this context the power outputs correspond to the stochastic variables.