Open data base analysis of scaling and spatio-temporal properties of power grid frequencies

Abstract

<jats:title>Abstract</jats:title> <jats:p>The electrical energy system has attracted much attention from an increasingly diverse research community. Many theoretical predictions have been made, from scaling laws of fluctuations to propagation velocities of disturbances. However, to validate any theory, empirical data from large-scale power systems are necessary but are rarely shared openly. Here, we analyse an open data base of measurements of electric power grid frequencies across 17 locations in 12 synchronous areas on three continents. The power grid frequency is of particular interest, as it indicates the balance of supply and demand and carries information on deterministic, stochastic, and control influences. We perform a broad analysis of the recorded data, compare different synchronous areas and validate a previously conjectured scaling law. Furthermore, we show how fluctuations change from local independent oscillations to a homogeneous bulk behaviour. Overall, the presented open data base and analyses may constitute a step towards more shared, collaborative energy research.</jats:p>

Phase and Amplitude Synchronization in Power-Grid Frequency Fluctuations in the Nordic Grid

“…Again without relying on any model, we will show that spatial correlations of the fluctuations are ubiquitous, and especially prevalent below a certain distance -similar to a scaling law in long-range fluctuations in power-grid frequency presented in Ref. [40].…”

“…Here we observe an approximately diffusive coupling, i.e., the time it takes for the amplitude of the increments to become identical grows approximately with the square of the distance, as described in Ref. [40]. Interestingly, the data suggest a potentially even stronger dependency with distance, which could be linked to strong temporal correlations discussed earlier: If the dynamics at one site depends substantially on its own past (high temporal correlation), then it will take longer to synchronise fully with the remaining network.…”

“…Noticeable is also the distinct separation of the curves at timescales r < 5 s, which has been identified in Ref. [40] as a possible method to study the synchronisation of fluctuation over spatial distances. In order to compare the fluctuation functions F (r) at each location, i.e., to fundamentally compare the amplitudes of the fluctuations at each locations, we compute the relative DFA function η(r), as introduced in Ref.…”

“…The fluctuations in TTY and AU show a smaller standard deviation than the remaining sites due to the larger number of generators in the Northern part of the synchronous area, compared to the mostly consumerdominated south of the grid, see also Refs. [30], [40].…”

“…In order to compare the fluctuation functions F (r) at each location, i.e., to fundamentally compare the amplitudes of the fluctuations at each locations, we compute the relative DFA function η(r), as introduced in Ref. [40], with CTH as a reference in Fig. 6b.…”