Non-Gaussian power grid frequency fluctuations characterized by L\'evy-stable laws and superstatistics

TL;DR

This paper investigates power grid frequency fluctuations, revealing they follow non-Gaussian Le9vy-stable and superstatistical distributions, with energy trading and damping as key influencing factors, across diverse global grids.

Contribution

It introduces a framework for analyzing non-Gaussian fluctuations in power grids and highlights the roles of energy trading and damping in fluctuation dynamics.

Findings

Frequency fluctuations deviate from Gaussianity and follow Le9vy-stable and q-Gaussian distributions.

Energy trading significantly contributes to frequency fluctuations.

Effective damping reduces fluctuation risks, especially in small power grids.

Abstract

Multiple types of fluctuations impact the collective dynamics of power grids and thus challenge their robust operation. Fluctuations result from processes as different as dynamically changing demands, energy trading, and an increasing share of renewable power feed-in. Here we analyze principles underlying the dynamics and statistics of power grid frequency fluctuations. Considering frequency time series for a range of power grids, including grids in North America, Japan and Europe, we find a substantial deviation from Gaussianity best described as L\'evy-stable and q-Gaussian distributions. We present a coarse framework to analytically characterize the impact of arbitrary noise distributions as well as a superstatistical approach which systematically interprets heavy tails and skewed distributions. We identify energy trading as a substantial contribution to today's frequency fluctuations and effective damping of the grid as a controlling factor enabling reduction of fluctuation risks, with enhanced effects for small power grids.