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@ARTICLE{Mork:1024149,
      author       = {Mork, Maximilian and Materzok, Nick and Xhonneux, André
                      and Müller, Dirk},
      title        = {{N}onlinear {H}ybrid {M}odel {P}redictive {C}ontrol for
                      building energy systems},
      journal      = {Energy and buildings},
      volume       = {270},
      issn         = {0378-7788},
      address      = {Amsterdam [u.a.]},
      publisher    = {Elsevier Science},
      reportid     = {FZJ-2024-01991},
      pages        = {112298 -},
      year         = {2022},
      abstract     = {This paper presents a nonlinear hybrid Model Predictive
                      Control (MPC) approach for building energy systems based on
                      Modelica. The MPC approach takes into account two
                      characteristics that are very common for building energy
                      systems: nonlinearities (inherent in the building envelope
                      and Heating, Ventilation and Air Conditioning (HVAC)
                      systems) and discontinuities (in the form of on/ off
                      operation, discrete operation states and operation modes).
                      The hybrid MPC approach integrates both continuous and
                      discrete optimization variables into the control concept and
                      thus is capable of controlling building energy systems with
                      binary or integer decision variables, switching dynamics or
                      logic if-then-else constraints. By employing a time-variant
                      linearization approach, nonlinear Modelica optimization
                      problems are approximated with high accuracy and transformed
                      into a linearized state-space representation. Based on the
                      linearization output, a linearized optimization problem is
                      generated automatically in every MPC iteration, which is
                      extensible by various integer characteristics and is
                      accessible for a wide range of mixedinteger solvers. A
                      simulation study on a nonlinear Modelica building energy
                      system demonstrates the control quality of the proposed
                      toolchain revealing a small linearization error and
                      successful integration of multiple integer characteristics.
                      The benefits of the approach are manifested by comparing its
                      performance with different reference control strategies.},
      cin          = {IEK-10},
      ddc          = {690},
      cid          = {I:(DE-Juel1)IEK-10-20170217},
      pnm          = {1121 - Digitalization and Systems Technology for
                      Flexibility Solutions (POF4-112) / 1123 - Smart Areas and
                      Research Platforms (POF4-112) / EG2050: LLEC-Verwaltungsbau:
                      Klimaneutraler Verwaltungsbau als aktiver Teil des Living
                      Lab Energy Campus (LLEC) (03EGB0010A) / LLEC - Living Lab
                      Energy Campus (LLEC-2018-2023)},
      pid          = {G:(DE-HGF)POF4-1121 / G:(DE-HGF)POF4-1123 /
                      G:(BMWi)03EGB0010A / G:(DE-HGF)LLEC-2018-2023},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000999939100005},
      doi          = {10.1016/j.enbuild.2022.112298},
      url          = {https://juser.fz-juelich.de/record/1024149},
}