Stochastic properties of the frequency dynamics in real and synthetic power grids

TL;DR

This paper investigates the stochastic and statistical properties of power grid frequency fluctuations, revealing non-Gaussian, Markovian behavior, and emphasizing the importance of regulation timing, while comparing real data with synthetic models.

Contribution

It provides a detailed analysis of frequency fluctuation properties in real power grids and evaluates how well synthetic models replicate these dynamics.

Findings

Frequency fluctuations are non-Gaussian and approximately Markovian.

Significant fluctuations occur during regulation and trading intervals.

Synthetic models can partially replicate real frequency dynamics.

Abstract

The frequency constitutes a key state variable of electrical power grids. However, as the frequency is subject to several sources of fluctuations, ranging from renewable volatility to demand fluctuations and dispatch, it is strongly dynamic. Yet, the statistical and stochastic properties of the frequency fluctuation dynamics are far from fully understood. Here, we analyse properties of power grid frequency trajectories recorded from different synchronous regions. We highlight the non-Gaussian and still approximately Markovian nature of the frequency statistics. Further, we find that the frequency displays significant fluctuations exactly at the time intervals of regulation and trading, confirming the need of having a regulatory and market design that respects the technical and dynamical constraints in future highly renewable power grids. Finally, employing a recently proposed synthetic model for the frequency dynamics, we combine our statistical and stochastic analysis and analyse in how far dynamically modelled frequency properties match the ones of real trajectories.