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@ARTICLE{Weber:849933,
      author       = {Weber, Juliane and Zachow, Christopher and Witthaut, Dirk},
      title        = {{M}odeling long correlation times using additive binary
                      {M}arkov chains: {A}pplications to wind generation time
                      series},
      journal      = {Physical review / E},
      volume       = {97},
      number       = {3},
      issn         = {2470-0045},
      address      = {Woodbury, NY},
      publisher    = {Inst.},
      reportid     = {FZJ-2018-04028},
      pages        = {032138},
      year         = {2018},
      abstract     = {Wind power generation exhibits a strong temporal
                      variability, which is crucial for system integration in
                      highly renewable power systems. Different methods exist to
                      simulate wind power generation but they often cannot
                      represent the crucial temporal fluctuations properly. We
                      apply the concept of additive binary Markov chains to model
                      a wind generation time series consisting of two states:
                      periods of high and low wind generation. The only input
                      parameter for this model is the empirical autocorrelation
                      function. The two-state model is readily extended to
                      stochastically reproduce the actual generation per period.
                      To evaluate the additive binary Markov chain method, we
                      introduce a coarse model of the electric power system to
                      derive backup and storage needs. We find that the temporal
                      correlations of wind power generation, the backup need as a
                      function of the storage capacity, and the resting time
                      distribution of high and low wind events for different
                      shares of wind generation can be reconstructed.},
      cin          = {IEK-STE},
      ddc          = {530},
      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)16},
      pubmed       = {pmid:29776042},
      UT           = {WOS:000428506600005},
      doi          = {10.1103/PhysRevE.97.032138},
      url          = {https://juser.fz-juelich.de/record/849933},
}