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Short term fluctuations of wind and solar power systems
by
Wächter, M
, Milan, P
, Tabar, M Reza Rahimi
, Heinemann, D
, Lorenz, E
, Anvari, M
, Peinke, Joachim
, Lohmann, G
in
05.45.Tp
/ Algorithms
/ Control algorithms
/ Control theory
/ intermittency
/ jumpy and diffusive dynamics
/ Physics
/ Power spectra
/ Probability density functions
/ renewable energies
/ Solar energy
/ Stability analysis
/ time-delayed feedback method
/ tipping point
/ Variation
/ Weather
2016
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Short term fluctuations of wind and solar power systems
by
Wächter, M
, Milan, P
, Tabar, M Reza Rahimi
, Heinemann, D
, Lorenz, E
, Anvari, M
, Peinke, Joachim
, Lohmann, G
in
05.45.Tp
/ Algorithms
/ Control algorithms
/ Control theory
/ intermittency
/ jumpy and diffusive dynamics
/ Physics
/ Power spectra
/ Probability density functions
/ renewable energies
/ Solar energy
/ Stability analysis
/ time-delayed feedback method
/ tipping point
/ Variation
/ Weather
2016
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While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
Short term fluctuations of wind and solar power systems
by
Wächter, M
, Milan, P
, Tabar, M Reza Rahimi
, Heinemann, D
, Lorenz, E
, Anvari, M
, Peinke, Joachim
, Lohmann, G
in
05.45.Tp
/ Algorithms
/ Control algorithms
/ Control theory
/ intermittency
/ jumpy and diffusive dynamics
/ Physics
/ Power spectra
/ Probability density functions
/ renewable energies
/ Solar energy
/ Stability analysis
/ time-delayed feedback method
/ tipping point
/ Variation
/ Weather
2016
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Journal Article
Short term fluctuations of wind and solar power systems
2016
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Overview
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.
Publisher
IOP Publishing
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