Short term fluctuations of wind and solar power systems

TL;DR

This paper analyzes the short-term fluctuations of wind and solar power, revealing their nonlinear and intermittent nature across different regions, and proposes a feedback control method to mitigate these fluctuations.

Contribution

It provides a detailed characterization of renewable power variability at second-level timescales and introduces a novel control algorithm to reduce non-Gaussian fluctuations.

Findings

Renewable sources exhibit multiple types of variability and nonlinearity.

The jumpy characteristic decreases with spatial size, but non-Gaussian behavior persists.

A feedback control technique can suppress short-term fluctuations.

Abstract

Wind and solar power are known to be highly influenced by weather events and may ramp up 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 the world with resolutions of seconds to minutes, we provide strong evidence that renewable wind and solar sources exhibit multiple types of variability and nonlinearity in the time scale of {\it seconds} and characterise their stochastic properties. In contrast to previous findings, 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 total field survives even for a country-wide distribution of the systems. The strong fluctuating behaviour of renewable wind and solar sources can be well 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 term non-Gaussian statistics in spatially strong correlated and intermittent renewable sources.