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@ARTICLE{Reuss:864324,
      author       = {Reuss, Markus and Welder, Lara and Thürauf, Johannes and
                      Linssen, Jochen and Grube, Thomas and Schewe, Lars and
                      Schmidt, Martin and Stolten, Detlef and Robinius, Martin},
      title        = {{M}odeling {H}ydrogen {N}etworks for {F}uture {E}nergy
                      {S}ystems: {A} {C}omparison of {L}inear and {N}onlinear
                      {A}pproaches},
      journal      = {International journal of hydrogen energy},
      volume       = {44},
      number       = {60},
      issn         = {0360-3199},
      address      = {New York, NY [u.a.]},
      publisher    = {Elsevier},
      reportid     = {FZJ-2019-04130},
      pages        = {32136 - 32150},
      year         = {2019},
      abstract     = {Common energy system models that integrate hydrogen
                      transport in pipelines typically simplify fluid flow models
                      and reduce the network size in order to achieve solutions
                      quickly. This contribution analyzes two different types of
                      pipeline network topologies (namely, star and tree networks)
                      and two different fluid flow models (linear and nonlinear)
                      for a given hydrogen capacity scenario of electrical
                      reconversion in Germany to analyze the impact of these
                      simplifications. For each network topology, robust demand
                      and supply scenarios are generated. The results show that a
                      simplified topology, as well as the consideration of
                      detailed fluid flow, could heavily influence the total
                      pipeline investment costs. For the given capacity scenario,
                      an overall cost reduction of the pipeline costs of $37\%$ is
                      observed for the star network with linear cost compared to
                      the tree network with nonlinear fluid flow. The impact of
                      these improvements regarding the total electricity
                      reconversion costs has led to a cost reduction of $1.4\%,$
                      which is fairly small. Therefore, the integration of
                      nonlinearities into energy system optimization models is not
                      recommended due to their high computational burden. However,
                      the applied method for generating robust demand and supply
                      scenarios improved the credibility and robustness of the
                      network topology, while the simplified fluid flow
                      consideration can lead to infeasibilities. Thus, we suggest
                      the utilization of the nonlinear model for post-processing
                      to prove the feasibility of the results and strengthen their
                      credibility, while retaining the computational performance
                      of linear modeling.},
      cin          = {IEK-3},
      ddc          = {620},
      cid          = {I:(DE-Juel1)IEK-3-20101013},
      pnm          = {134 - Electrolysis and Hydrogen (POF3-134) / ES2050 -
                      Energie Sytem 2050 (ES2050)},
      pid          = {G:(DE-HGF)POF3-134 / G:(DE-HGF)ES2050},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000502888800040},
      doi          = {10.1016/j.ijhydene.2019.10.080},
      url          = {https://juser.fz-juelich.de/record/864324},
}