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@ARTICLE{Leenders:905803,
      author       = {Leenders, Ludger and Hagedorn, Dörthe Franzisca and
                      Djelassi, Hatim and Bardow, André and Mitsos, Alexander},
      title        = {{B}ilevel optimization for joint scheduling of production
                      and energy systems},
      journal      = {Optimization and engineering},
      volume       = {24},
      issn         = {1389-4420},
      address      = {Dordrecht [u.a.]},
      publisher    = {Springer Science + Business Media B.V},
      reportid     = {FZJ-2022-01023},
      pages        = {499-537},
      year         = {2023},
      abstract     = {Energy-intensive production sites are often supplied with
                      energy by on-site energy systems. Commonly, the scheduling
                      of the systems is performed sequentially, starting with the
                      scheduling of the production system. Often, the on-site
                      energy system is operated by a different company than the
                      production system. In consequence, the production and the
                      energy system schedule their operation towards misaligned
                      objectives leading in general to suboptimal schedules for
                      both systems. To reflect the independent optimization with
                      misaligned objectives, the scheduling problem of the
                      production system can be formulated as a bilevel problem. We
                      formulate the bilevel problem with mixed-integer decision
                      variables in the upper and the lower level, and propose an
                      algorithm to solve this bilevel problem based on the
                      deterministic and global algorithm by Djelassi, Glass and
                      Mitsos (J Glob Optim 75:341–392, 2019.
                      https://doi.org/10.1007/s10898-019-00764-3) for bilevel
                      problems with coupling equality constraints. The algorithm
                      works by discretizing the independent lower-level variables.
                      In the scheduling problem considered herein, the only
                      coupling equality constraints are energy balances in the
                      lower level. Since an intuitive distinction is missing
                      between dependent and independent variables, we specialize
                      the algorithm and add a procedure to identify independent
                      variables to be discretized. Thereby, we preserve
                      convergence guarantees. The performance of the algorithm is
                      demonstrated in two case studies. In the case studies, the
                      production system favors different technologies for the
                      energy supply than the energy system. By solving the bilevel
                      problem, the production system identifies an energy demand,
                      which leads to minimal cost. Additionally, we demonstrate
                      the benefits of solving the bilevel problem instead of
                      solving the common integrated or sequential problem.},
      cin          = {IEK-10},
      ddc          = {690},
      cid          = {I:(DE-Juel1)IEK-10-20170217},
      pnm          = {899 - ohne Topic (POF4-899)},
      pid          = {G:(DE-HGF)POF4-899},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000743401700001},
      doi          = {10.1007/s11081-021-09694-0},
      url          = {https://juser.fz-juelich.de/record/905803},
}