% IMPORTANT: The following is UTF-8 encoded.  This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.

@ARTICLE{Hassanian:1037640,
      author       = {Hassanian, Reza and Helgadóttir, Ásdís and Riedel,
                      Morris},
      title        = {{I}celand wind farm assessment case study and development:
                      {A}n empirical data from wind and wind turbine},
      journal      = {Cleaner energy systems},
      volume       = {4},
      issn         = {2772-7831},
      address      = {Amsterdam},
      publisher    = {Elsevier},
      reportid     = {FZJ-2025-00805},
      pages        = {100058},
      year         = {2023},
      abstract     = {This study aimed to apply empirical data to assess wind
                      energy production at the Búrfell site in Iceland based on
                      the E44 turbine model. The empirical data are 5 years of
                      recordings at the site location by the Iceland Metrological
                      office. The wind speed data are measured at a 10 m height
                      from 2017 to 2021. There are two E44 wind turbines test
                      installed on the site. In the previous studies, the wind
                      farm capacity and Levelized cost of energy (LCOE) were
                      reported without investigating the wake loss model and its
                      impacts on LCOE and have an estimation applied. The previous
                      research was based on the two installed wind turbines at the
                      site, which are located in a straight line and perpendicular
                      to the prevailing wind speed. This study applies the
                      Jensen-Katic model to investigate wake loss. Downwind and
                      crosswind ten-rotor diameters and five-rotor diameters are
                      calculated respectively as the best options. Afterward, an
                      appropriate number of wind turbines is suggested for 80MW
                      production. In addition, this study's optimum capacity
                      factor (CF) is $26.08\%,$ which was reported at $37.9\%$ -
                      $38.38\%$ before. On average, the turbines produce less than
                      $30\%$ of their rated power, which has been reported at
                      $38.15\%$ in prior studies. This study presents the LCOE as
                      equal to 0.0659 USD/kWh, which is less than 0.0703 USD/kWh
                      in the previous studies and the LCOE reported by the 2020
                      LCOE European report. The obtained LCOE in this study is
                      based on the weighted average cost of capital in the energy
                      project by Landsvirkjun, the national power company of
                      Iceland. The obtained result from the model used, which
                      matched the empirical measurements, displays Iceland's best
                      rank for wind energy LCOE metric among European countries.
                      The proposed method provides a vision to use the wake loss
                      model output in deep learning training to predict power
                      production, leading to a sustainable and reliable power
                      grid.},
      cin          = {JSC},
      ddc          = {333.7},
      cid          = {I:(DE-Juel1)JSC-20090406},
      pnm          = {5111 - Domain-Specific Simulation $\&$ Data Life Cycle Labs
                      (SDLs) and Research Groups (POF4-511) / RAISE - Research on
                      AI- and Simulation-Based Engineering at Exascale (951733) /
                      EUROCC - National Competence Centres in the framework of
                      EuroHPC (951732) / EUROCC-2 (DEA02266)},
      pid          = {G:(DE-HGF)POF4-5111 / G:(EU-Grant)951733 /
                      G:(EU-Grant)951732 / G:(DE-Juel-1)DEA02266},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:001532663400018},
      doi          = {10.1016/j.cles.2023.100058},
      url          = {https://juser.fz-juelich.de/record/1037640},
}