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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},
}