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@ARTICLE{Tbben:859330,
      author       = {Többen, Johannes and Schröder, Thomas},
      title        = {{A} maximum entropy approach to the estimation of spatially
                      and sectorally disaggregated electricity load curves},
      journal      = {Applied energy},
      volume       = {225},
      issn         = {0306-2619},
      address      = {Amsterdam [u.a.]},
      publisher    = {Elsevier Science},
      reportid     = {FZJ-2019-00198},
      pages        = {797 - 813},
      year         = {2018},
      abstract     = {Usually, disaggregated electricity load curves are
                      estimated by using Top-Down or Bottom-Up approaches. The
                      former requires estimating weightings for downscaling
                      aggregated information, while the latter requires
                      extrapolating micro-level information. In both cases,
                      estimation would ideally be based on as much regional and
                      sector specific information as possible, in order to obtain
                      a realistic representation of the magnitude and temporal
                      pattern of a regional sector’s electricity consumption.
                      Typically, such attempts are significantly hampered by
                      issues of limited and possibly inconsistent data, differing
                      levels of detail, and mismatching data classifications.This
                      paper proposes a novel nonlinear programming model based on
                      the maximum entropy approach. The model allows for
                      electricity load curve estimation at arbitrary spatial,
                      sectoral and temporal resolution, from partial and possibly
                      inconsistent information. The proposed model integrates and
                      systematically utilizes data usually used by either Top-Down
                      or Bottom-Up approaches. In a case study using German data
                      it is shown that the model combines the strength of both
                      and, at the same time, overcomes the challenges specific to
                      Top-Down or Bottom-up estimation.},
      cin          = {IEK-STE},
      ddc          = {620},
      cid          = {I:(DE-Juel1)IEK-STE-20101013},
      pnm          = {153 - Assessment of Energy Systems – Addressing Issues of
                      Energy Efficiency and Energy Security (POF3-153)},
      pid          = {G:(DE-HGF)POF3-153},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000438181000059},
      doi          = {10.1016/j.apenergy.2018.04.126},
      url          = {https://juser.fz-juelich.de/record/859330},
}