Short term fluctuations of wind and solar power systems

Wind and solar power are known to be highly influenced byweather events andmay rampup or down abruptly. Such events in the power production influence not only the availability of energy, but also the stability of the entire power grid. By analysing significant amounts of data from several regions around theworldwith resolutions of seconds tominutes, we provide strong evidence that renewable wind and solar sources exhibitmultiple types of variability and nonlinearity in the time scale of seconds and characterise their stochastic properties. In contrast to previousfindings, we show that only the jumpy characteristic of renewable sources decreases when increasing the spatial size over which the renewable energies are harvested. Otherwise, the strong non-Gaussian, intermittent behaviour in the cumulative power of the totalfield survives even for a country-wide distribution of the systems. The strongfluctuating behaviour of renewable wind and solar sources can bewell characterised by Kolmogorov-like power spectra and q-exponential probability density functions. Using the estimated potential shape of power time series, we quantify the jumpy or diffusive dynamic of the power. Finally we propose a time delayed feedback technique as a control algorithm to suppress the observed short termnon-Gaussian statistics in spatially strong correlated and intermittent renewable sources.