  Frequency fluctuations in power grids, caused by unpredictable renewable
energy sources, consumer behavior and trading, need to be balanced to ensure
stable grid operation. Standard smart grid solutions to mitigate large
frequency excursions are based on centrally collecting data and give rise to
security and privacy concerns. Furthermore, control of fluctuations is often
tested by employing Gaussian perturbations. Here, we demonstrate that power
grid frequency fluctuations are in general non-Gaussian, implying that large
excursions are more likely than expected based on Gaussian modeling. We
consider real power grid frequency measurements from Continental Europe and
compare them to stochastic models and predictions based on Fokker-Planck
equations. Furthermore, we review a decentral smart grid control scheme to
limit these fluctuations. In particular, we derive a scaling law of how
decentralized control actions reduce the magnitude of frequency fluctuations
and demonstrate the power of these theoretical predictions using a test grid.
Overall, we find that decentral smart grid control may reduce grid frequency
excursions due to both Gaussian and non-Gaussian power fluctuations and thus
offers an alternative pathway for mitigating fluctuation-induced risks.
