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@INPROCEEDINGS{Holtwerth:905759,
      author       = {Holtwerth, Alexander and Xhonneux, André and Müller,
                      Dirk},
      title        = {{M}odelling of {E}nergy {S}ystems with {S}easonal {S}torage
                      and {S}ystem {S}tate dependent {B}oundary {C}onditions using
                      {T}ime {S}eries {A}ggregation and {S}egmentation; 34},
      reportid     = {FZJ-2022-00983},
      pages        = {1-11},
      year         = {2021},
      abstract     = {The optimization of planning is one of the challenging
                      tasks for the optimal control of energy systems with
                      seasonal storage. An optimization quickly becomes
                      computationally intractable due to a high temporal
                      resolution and a long time horizonneeded for seasonal energy
                      storage. Time series aggregation, in combination with
                      additional time coupling constraints, can be used to reduce
                      the size of the optimization problem drastically. However,
                      some constraints of an energy system aredirectly dependent
                      on the current system state and cannot be modeled as part of
                      a typical period. To preserve the computational advantages
                      of time series aggregation with extra constraints for
                      storage units while modeling a set of constraints with a
                      full temporal resolution, we propose a method that uses a
                      mapping between intra-period, inter-period, and
                      full-resolution variables. Furthermore, we propose a
                      separation of the year into different regions during the
                      clustering. This leads to a decoupling of different regions
                      of the year and therefore increases the flexibility of the
                      optimization.In a case study, we adopt the approach for an
                      energy system with a dynamic hydrogen pipeline and a liquid
                      organic hydrogen carrier (LOHC) storage system with a hot
                      pressure swing reactor. By using full-resolution variables
                      and a separationof the year in 3 different regions, we were
                      able to reduce the computational time by $78\%$ while
                      maintaining an accuracy of $3\%$ compared to an optimization
                      with the full-time resolution.The separation of the year
                      into 3 regions lead to a consistent improvement in accuracy
                      of up to $29.4\%$ and a run time decrease of up to $82\%$
                      compared to a clustering of the whole year in typical
                      periods. Furthermore, a separation of the yearinto 3 regions
                      extended the feasibility of the optimization problem to very
                      low numbers of typical periods.},
      month         = {Jun},
      date          = {2021-06-28},
      organization  = {The 34th International Conference on
                       Efficiency, Cost, Optimization,
                       Simulation and Environmental Impact of
                       Energy Systems, Taormina (Italy), 28
                       Jun 2021 - 2 Jul 2021},
      cin          = {IEK-10},
      cid          = {I:(DE-Juel1)IEK-10-20170217},
      pnm          = {1122 - Design, Operation and Digitalization of the Future
                      Energy Grids (POF4-112)},
      pid          = {G:(DE-HGF)POF4-1122},
      typ          = {PUB:(DE-HGF)8},
      url          = {https://juser.fz-juelich.de/record/905759},
}