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@INPROCEEDINGS{Schafer:859319,
      author       = {Schafer, Benjamin and Timme, Marc and Witthaut, Dirk},
      title        = {{I}solating the {I}mpact of {T}rading on {G}rid {F}requency
                      {F}luctuationsy},
      publisher    = {IEEE},
      reportid     = {FZJ-2019-00191},
      pages        = {1-5},
      year         = {2018},
      abstract     = {To ensure reliable operation of power grids, their
                      frequency shall stay within strict bounds. Multiple sources
                      of disturbances cause fluctuations of the grid frequency,
                      ranging from changing demand over volatile feed-in to energy
                      trading. Here, we analyze frequency time series from the
                      continental European grid in 2011 and 2017 as a case study
                      to isolate the impact of trading. We find that trading at
                      typical trading intervals such as full hours modifies the
                      frequency fluctuation statistics. While particularly large
                      frequency deviations in 2017 are not as frequent as in 2011,
                      large deviations are more likely to occur shortly after the
                      trading instances. A comparison between the two years
                      indicates that trading at shorter intervals might be
                      beneficial for frequency quality and grid stability, because
                      particularly large fluctuations are substantially
                      diminished. Furthermore, we observe that the statistics of
                      the frequency fluctuations do not follow Gaussian
                      distributions but are better described using heavy-tailed
                      and asymmetric distributions, for example Levy-stable
                      distributions. Comparing intervals without trading to those
                      with trading instances indicates that frequency deviations
                      near the trading times are distributed more widely and thus
                      extreme deviations are orders of magnitude more likely.
                      Finally, we briefly review a stochastic analysis that allows
                      a quantitative description of power grid frequency
                      fluctuations.},
      month         = {Oct},
      date          = {2018-10-21},
      organization  = {2018 IEEE PES Innovative Smart Grid
                       Technologies Conference Europe
                       (ISGT-Europe), Sarajevo (Bosnia and
                       Herzegovina), 21 Oct 2018 - 25 Oct
                       2018},
      cin          = {IEK-STE},
      cid          = {I:(DE-Juel1)IEK-STE-20101013},
      pnm          = {153 - Assessment of Energy Systems – Addressing Issues of
                      Energy Efficiency and Energy Security (POF3-153) /
                      VH-NG-1025 - Helmholtz Young Investigators Group
                      "Efficiency, Emergence and Economics of future supply
                      networks" $(VH-NG-1025_20112014)$ / CoNDyNet - Kollektive
                      Nichtlineare Dynamik Komplexer Stromnetze $(PIK_082017)$},
      pid          = {G:(DE-HGF)POF3-153 / $G:(HGF)VH-NG-1025_20112014$ /
                      $G:(Grant)PIK_082017$},
      typ          = {PUB:(DE-HGF)8},
      doi          = {10.1109/ISGTEurope.2018.8571793},
      url          = {https://juser.fz-juelich.de/record/859319},
}