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@ARTICLE{Gotzens:859310,
      author       = {Gotzens, Fabian and Heinrichs, Heidi and Hörsch, Jonas and
                      Hofmann, Fabian},
      title        = {{P}erforming energy modelling exercises in a transparent
                      way - the issue of data quality in power plant databases},
      journal      = {Energy strategy reviews},
      volume       = {23},
      issn         = {2211-467X},
      address      = {Amsterdam [u.a.]},
      publisher    = {Elsevier},
      reportid     = {FZJ-2019-00182},
      pages        = {1 - 12},
      year         = {2019},
      abstract     = {In energy modelling, open data and open source code can
                      help enhance traceability and reproducibility of model
                      exercises which contribute to facilitate controversial
                      debates and improve policy advice. While the availability of
                      open power plant databases increased in recent years, they
                      often differ considerably from each other and their data
                      quality has not been systematically compared to proprietary
                      sources yet. Here, we introduce the python-based
                      ‘powerplantmatching’ (PPM), an open source toolset for
                      cleaning, standardizing and combining multiple power plant
                      databases. We apply it once only with open databases and
                      once with an additional proprietary database in order to
                      discuss and elaborate the issue of data quality, by
                      analysing capacities, countries, fuel types, geographic
                      coordinates and commissioning years for conventional power
                      plants. We find that a derived dataset purely based on open
                      data is not yet on a par with one in which a proprietary
                      database has been added to the matching, even though the
                      statistical values for capacity matched to a large degree
                      with both datasets. When commissioning years are needed for
                      modelling purposes in the final dataset, the proprietary
                      database helps crucially to increase the quality of the
                      derived dataset.},
      cin          = {IEK-STE},
      ddc          = {624},
      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:000458217800001},
      doi          = {10.1016/j.esr.2018.11.004},
      url          = {https://juser.fz-juelich.de/record/859310},
}