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@ARTICLE{Hoffmann:903587,
      author       = {Hoffmann, Maximilian and Priesmann, Jan and Nolting, Lars
                      and Praktiknjo, Aaron and Kotzur, Leander and Stolten,
                      Detlef},
      title        = {{T}ypical periods or typical time steps? {A} multi-model
                      analysis to determine the optimal temporal aggregation for
                      energy system models},
      journal      = {Applied energy},
      volume       = {304},
      issn         = {0306-2619},
      address      = {Amsterdam [u.a.]},
      publisher    = {Elsevier Science},
      reportid     = {FZJ-2021-05241},
      pages        = {117825 -},
      year         = {2021},
      abstract     = {Energy system models are challenged by the need for high
                      temporal and spatial resolutions in order to appropriately
                      depict the increasing share of intermittent renewable energy
                      sources, storage technologies, and the growing
                      interconnectivity across energy sectors.This study compares
                      different temporal aggregation strategies, which reduce the
                      number of considered time steps, to maintain computational
                      viability of these models. The work focuses on the
                      representation of time series by a subset of single time
                      steps (i.e., typical time steps), or by groups of
                      consecutive time steps (i.e., typical periods), which are
                      commonly applied in the literature using clustering. We test
                      these techniques for two different energy system models and
                      benchmark the optimization results based on aggregation to
                      those of the fully resolved models. Further, centroids and
                      medoids are used to represent the clustered datasets and it
                      is investigated whether the optimal aggregation method can
                      be determined based on clustering indicators only.},
      cin          = {IEK-3},
      ddc          = {620},
      cid          = {I:(DE-Juel1)IEK-3-20101013},
      pnm          = {1111 - Effective System Transformation Pathways (POF4-111)
                      / 1112 - Societally Feasible Transformation Pathways
                      (POF4-111)},
      pid          = {G:(DE-HGF)POF4-1111 / G:(DE-HGF)POF4-1112},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000709745700005},
      doi          = {10.1016/j.apenergy.2021.117825},
      url          = {https://juser.fz-juelich.de/record/903587},
}