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@ARTICLE{Omoyele:1019576,
      author       = {Omoyele, Olalekan and Hoffmann, Maximilian and Koivisto,
                      Matti and Larrañeta, Miguel and Weinand, Jann Michael and
                      Linßen, Jochen and Stolten, Detlef},
      title        = {{I}ncreasing the resolution of solar and wind time series
                      for energy system modeling: {A} review},
      journal      = {Renewable $\&$ sustainable energy reviews},
      volume       = {189},
      issn         = {1364-0321},
      address      = {Amsterdam [u.a.]},
      publisher    = {Elsevier Science},
      reportid     = {FZJ-2023-05511},
      pages        = {113792 -},
      year         = {2024},
      abstract     = {Bottom-up energy system models are often based on hourly
                      time steps due to limited computational tractability or data
                      availability. However, in order to properly assess the
                      rentability and reliability of energy systems by accounting
                      for the intermittent nature of renewable energy sources, a
                      higher level of detail is necessary. This study reviews
                      different methods for increasing the temporal resolutions of
                      time series data for global horizontal and direct normal
                      irradiance for solar energy, and wind speed for wind energy.
                      The review shows that stochastic methods utilizing random
                      sampling and non-dimensional approaches are the most
                      frequently employed for solar irradiance data downscaling.
                      The non-dimensional approach is particularly simple, with
                      global applicability and a robust methodology with good
                      validation scores. The temporal increment of wind speed,
                      however, is challenging due to its spatiotemporal complexity
                      and variance, especially for accurate wind distribution
                      profiles. Recently, researchers have mostly considered
                      methods that draw on the combination of meteorological
                      reanalysis and stochastic fluctuations, which are more
                      accurate than the simple and conventional interpolation
                      methods. This review provides a road map of how to approach
                      solar and wind speed temporal downscaling methods and
                      quantify their effectiveness. Furthermore, potential future
                      research areas in solar and wind data downscaling are also
                      highlighted.},
      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:001111669400001},
      doi          = {10.1016/j.rser.2023.113792},
      url          = {https://juser.fz-juelich.de/record/1019576},
}