% 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{Caglayan:860138,
      author       = {Caglayan, Dilara Gülcin and Ryberg, Severin David and
                      Heinrichs, Heidi and Linssen, Jochen and Stolten, Detlef and
                      Robinius, Martin},
      title        = {{T}he {T}echno-{E}conomic {P}otential of {O}ffshore {W}ind
                      {E}nergy with {O}ptimized {F}uture {T}urbine {D}esigns in
                      {E}urope},
      journal      = {Applied energy},
      volume       = {255},
      issn         = {0306-2619},
      address      = {Amsterdam [u.a.]},
      publisher    = {Elsevier Science},
      reportid     = {FZJ-2019-00924},
      pages        = {113794 -},
      year         = {2019},
      abstract     = {Renewable energy sources will play a central role in the
                      sustainable energy systems of the future. Scenario analyses
                      of the hypothesized energy systems require sound knowledge
                      of the techno-economic potential of renewable energy
                      technologies. Although there have been various studies
                      concerning the potential of offshore wind energy, higher
                      spatial resolution as well as the future design concepts of
                      offshore wind turbines have not yet been addressed in
                      sufficient detail. This work aims to overcome this gap by
                      applying a high spatial resolution to the three main aspects
                      of offshore wind potential analysis, namely: ocean
                      suitability, the simulation of wind turbines, and cost
                      estimation. A set of constraints is determined that reveal
                      the available areas for turbine placement across Europe’s
                      maritime boundaries. Then, turbine designs specific to each
                      location are selected by identifying turbines with the
                      cheapest levelized cost of electricity, restricted to
                      capacities, hub heights and rotor diameters ranges predicted
                      by industry experts. Ocean eligibility and turbine design
                      are then combined to distribute turbines across the
                      available areas. Finally, levelized cost of electricity
                      trends are calculated from the individual turbine costs, as
                      well as the corresponding capacity factor obtained by hourly
                      simulation with wind speeds from 1980 to 2017. The results
                      of cost-optimal turbine designing reveal that the overall
                      potential for offshore wind energy across Europe will
                      constitute nearly 8.6 TW and 40.0 PWh at roughly 7 €ct
                      kWh−1 average levelized cost of electricity by 2050.
                      Averaged design parameters at national level are provided in
                      an Appendix.},
      cin          = {IEK-3},
      ddc          = {620},
      cid          = {I:(DE-Juel1)IEK-3-20101013},
      pnm          = {134 - Electrolysis and Hydrogen (POF3-134)},
      pid          = {G:(DE-HGF)POF3-134},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000497978100042},
      doi          = {10.1016/j.apenergy.2019.113794},
      url          = {https://juser.fz-juelich.de/record/860138},
}