% 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{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},
}