% 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{Roh:905552,
      author       = {Roh, Kosan and Brée, Luisa and Schäfer, Pascal and
                      Strohmeier, Daniel and Mitsos, Alexander},
      title        = {{F}lexible operation of modular electrochemical {CO}2
                      reduction processes},
      reportid     = {FZJ-2022-00793},
      year         = {2021},
      abstract     = {Electrochemical CO2 reduction (eCO2R) is an emerging
                      technology that is capable of producing various organic
                      chemicals from CO2, but its high electricity cost is a big
                      economic obstacle. One solution to reduce the cumulative
                      electricity cost is demand side management, i.e., to adjust
                      the power load based on time-variant electricity prices.
                      However, varying the power load of CO2-electrolyzers often
                      leads to changes in Faraday efficiency towards target
                      components and thereby influences the product composition.
                      Such deviations from the target product composition may be
                      undesired for downstream processes. We tackle this challenge
                      by proposing a flexible operating scheme for a modular eCO2R
                      process. We formulate the economically optimal operation of
                      an eCO2R process with multiple electrolyzer stacks as a
                      parallel-machine scheduling problem. Adjusting the power
                      load of each sub-process properly, we can save electricity
                      costs while the desired product composition is met at any
                      time. We apply an algorithm based on wavelet transform to
                      solve the resulting large-scale nonlinear scheduling problem
                      in tractable time. We solve each optimization problem with a
                      deterministic global optimization software MAiNGO. We
                      examine flexible operation of a modular eCO2R process for
                      syngas production. The case studies show that the modular
                      structure enables savings in the cumulative electricity cost
                      of the eCO2R process via flexible operation while deviations
                      in the syngas composition could be reduced. Also, the
                      maximum ramping speed of the entire process is found to be a
                      key parameter that strongly influences the cost saving.},
      cin          = {IEK-10},
      cid          = {I:(DE-Juel1)IEK-10-20170217},
      pnm          = {899 - ohne Topic (POF4-899)},
      pid          = {G:(DE-HGF)POF4-899},
      typ          = {PUB:(DE-HGF)25},
      doi          = {10.26434/chemrxiv-2021-49lwd},
      url          = {https://juser.fz-juelich.de/record/905552},
}