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@ARTICLE{Wenzel:1045550,
      author       = {Wenzel, Moritz and De Din, Edoardo and Zimmer, Marcel and
                      Benigni, Andrea},
      title        = {{G}aussian {P}rocess {S}upported {S}tochastic {MPC} for
                      {D}istribution {G}rids},
      journal      = {IEEE open journal of control systems},
      volume       = {4},
      issn         = {2694-085X},
      address      = {New York, NY},
      publisher    = {IEEE},
      reportid     = {FZJ-2025-03546},
      pages        = {332-348},
      year         = {2025},
      abstract     = {The efficacy of control systems for distribution grids can
                      be influenced by different sources of uncertainty.
                      Stochastic Model Predictive Control (SMPC) can be employed
                      to compensate for such uncertainties by integrating their
                      probability distribution into the control problem. An
                      efficient SMPC algorithm for online control applications is
                      the stochastic tube SMPC, which is able to treat the
                      evaluation of the chance constraints analytically. However,
                      this approach is efficient only when the calculation of the
                      constraint back-off is applied to a linear model. To address
                      this issue, this work employs Gaussian Processes to
                      approximate the nonlinear part of the power flow equations
                      based on offline training, which is integrated into the SMPC
                      formulation. The resulting SMPC is first validated and then
                      tested on a benchmark system, comparing the results with
                      Deterministic MPC and SMPC that excludes Gaussian Processes.
                      The proposed SMPC proves to be more efficient in terms of
                      cost minimization, reference tracking and voltage
                      violationreduction.},
      cin          = {ICE-1},
      ddc          = {004},
      cid          = {I:(DE-Juel1)ICE-1-20170217},
      pnm          = {1122 - Design, Operation and Digitalization of the Future
                      Energy Grids (POF4-112) / 1123 - Smart Areas and Research
                      Platforms (POF4-112) / INTERSTORE - Interoperable
                      opeN-source Tools to Enable hybRidisation, utiliSation, and
                      moneTisation of stORage flExibility (101096511)},
      pid          = {G:(DE-HGF)POF4-1122 / G:(DE-HGF)POF4-1123 /
                      G:(EU-Grant)101096511},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:001569592700004},
      doi          = {10.1109/OJCSYS.2025.3601836},
      url          = {https://juser.fz-juelich.de/record/1045550},
}