Short term fluctuations of wind and solar power systems

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 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.

Correlation and coherence of mesoscale wind speeds over the sea

“…This result is comparable to the results of Dowds et al () with the same temporal resolution. Results of Anvari et al () for high‐resolution wind and solar power data show the same characteristics. Furthermore, they conclude that the probability for large step changes is lower in wind parks due to smoothing effects.…”

The footprint of atmospheric turbulence in power grid frequency measurements

“…Fluctuations of a process x(t) on a time scale τ are often characterized by means of increments Δ τ x := x(t) − x(t + τ ). Traditional analysis and prediction of wind speed considers variations in 15 minutes and longer [5,6]. However, recent findings in the analysis of short-term increments of renewable power generation reveal strongly non-Gaussian fluctuations even on scales of one second [6,7].…”

“…Hence, atmospheric fluctuations even 30001-p1 within a second propagate into the power output of wind farms and are fed to the grid. In fact, intermittency is found in production time series of wind (and also photovoltaic) power plants [6,7]. Consequently, power quality is a major challenge for the grid integration of renewable generators [13].…”

Analysis of Trends and Emerging Technologies in Water Electrolysis Research Based on a Computational Method: A Comparison with Fuel Cell Research

“…However, renewable energy fluctuates temporally, and its energy density per land area is small [1,2]. A solution to this is to accumulate energy when surely surplus power is produced, and utilize it during shortfalls.…”