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  Identifying characteristic time scales in power grid frequency fluctuations with DFA

Meyer, P. G., Mehrnaz, A., & Kantz, H. (2020). Identifying characteristic time scales in power grid frequency fluctuations with DFA. Chaos, 30(1): 013130. doi:10.1063/1.5123778.

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 Creators:
Meyer, Philipp G.1, Author           
Mehrnaz, Anvari1, Author           
Kantz, Holger1, Author           
Affiliations:
1Max Planck Institute for the Physics of Complex Systems, Max Planck Society, ou_2117288              

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 MPIPKS: Time dependent processes
 Abstract: Frequency measurements indicate the state of a power grid. In fact, deviations from the nominal frequency determine whether the grid is stable or in a critical situation. We aim to understand the fluctuations of the frequency on multiple time scales with a recently proposed method based on detrended fluctuation analysis. It enables us to infer characteristic time scales and generate stochastic models. We capture and quantify known features of the fluctuations like periodicity due to the trading market, response to variations by control systems, and stability of the long time average. We discuss similarities and differences between the British grid and the continental European grid. Published under license by AIP Publishing.

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 Dates: 2020-01-172020-01-01
 Publication Status: Issued
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 Table of Contents: -
 Rev. Type: -
 Identifiers: ISI: 000539637000012
DOI: 10.1063/1.5123778
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Title: Chaos
  Other : Chaos : an interdisciplinary journal of nonlinear science
Source Genre: Journal
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Publ. Info: Woodbury, NY : American Institute of Physics
Pages: - Volume / Issue: 30 (1) Sequence Number: 013130 Start / End Page: - Identifier: ISSN: 1054-1500
CoNE: https://pure.mpg.de/cone/journals/resource/954922836228