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@INPROCEEDINGS{Buechel:1049196,
      author       = {Buechel, Maximilian and Zimmer, Marcel and Carta, Daniele
                      and Benigni, Andrea},
      title        = {{D}istribution {G}rid {V}oltage {E}stimation by
                      {C}orrelated {G}aussian {P}rocesses},
      publisher    = {IEEE},
      reportid     = {FZJ-2025-05278},
      pages        = {1-6},
      year         = {2025},
      abstract     = {Modern power distribution grids are facing significant
                      monitoring challenges from renewable energy volatility and
                      persistent measurement scarcity. In this paper, we propose a
                      data-driven approach for voltage magnitude estimation in
                      distribution systems using correlated Gaussian processes. We
                      demonstrate that the proposed approach can be applied to a
                      variety of monitoring configurations. Comparable accuracies
                      are achieved even when the number of monitoring units is
                      significantly reduced. Moreover, the results are obtained
                      with the help of small training sets, allowing for short
                      observation periods to generate training data. The proposed
                      approach offers flexibility in terms of monitoring
                      configurations and provides reliable voltage estimation in
                      poorly monitored distribution networks.},
      month         = {Sep},
      date          = {2025-09-24},
      organization  = {2025 IEEE 15th International Workshop
                       on Applied Measurements for Power
                       Systems (AMPS), Bucharest (Romania), 24
                       Sep 2025 - 26 Sep 2025},
      cin          = {ICE-1},
      cid          = {I:(DE-Juel1)ICE-1-20170217},
      pnm          = {1121 - Digitalization and Systems Technology for
                      Flexibility Solutions (POF4-112) / 1122 - Design, Operation
                      and Digitalization of the Future Energy Grids (POF4-112) /
                      1123 - Smart Areas and Research Platforms (POF4-112)},
      pid          = {G:(DE-HGF)POF4-1121 / G:(DE-HGF)POF4-1122 /
                      G:(DE-HGF)POF4-1123},
      typ          = {PUB:(DE-HGF)8},
      doi          = {10.1109/AMPS66841.2025.11219969},
      url          = {https://juser.fz-juelich.de/record/1049196},
}