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001     1031814
005     20250203124520.0
024 7 _ |a 10.1109/AMPS62611.2024.10706662
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024 7 _ |a WOS:001344552300003
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037 _ _ |a FZJ-2024-05833
100 1 _ |a Pasella, Manuela
|0 P:(DE-Juel1)200465
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|e Corresponding author
|u fzj
111 2 _ |a 2024 IEEE 14th International Workshop on Applied Measurements for Power Systems (AMPS)
|c Caserta
|d 2024-09-18 - 2024-09-20
|w Italy
245 _ _ |a On the Quality of Pseudo-Measurements for Distribution System State Estimation
260 _ _ |c 2024
|b IEEE
300 _ _ |a 1-6
336 7 _ |a CONFERENCE_PAPER
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336 7 _ |a Conference Paper
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336 7 _ |a INPROCEEDINGS
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336 7 _ |a Output Types/Conference Paper
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336 7 _ |a Contribution to a conference proceedings
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520 _ _ |a With the increasing penetration of distributed en-ergy resources, Smart Grids control applications are always more dependent on monitoring data. Pseudo-measurements are used in Distribution System State Estimation to allow estimating the operating conditions of the system also when the number of field measurements is limited. Since the accuracy of the estimation depends on the quality of the pseudo-measurements, in this paper the factors that affect this quality are investigated and the performance of a machine learning-based approach for pseudo-measurements generation is evaluated. Starting from real data collected from the Forschungszentrum Jülich campus, a dataset is engineered, and the considered data coding approach is presented. Finally, different neural models based on multilayer perceptron are presented, and their performances are compared with those of trivial alternatives.
536 _ _ |a 1122 - Design, Operation and Digitalization of the Future Energy Grids (POF4-112)
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|c POF4-112
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536 _ _ |a 1123 - Smart Areas and Research Platforms (POF4-112)
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588 _ _ |a Dataset connected to CrossRef Conference
700 1 _ |a Benigni, Andrea
|0 P:(DE-Juel1)179029
|b 1
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700 1 _ |a Cannas, Barbara
|0 P:(DE-HGF)0
|b 2
700 1 _ |a Carta, Daniele
|0 P:(DE-Juel1)186779
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|u fzj
700 1 _ |a Muscas, Carlo
|0 P:(DE-HGF)0
|b 4
700 1 _ |a Pisano, Fabio
|0 P:(DE-HGF)0
|b 5
773 _ _ |a 10.1109/AMPS62611.2024.10706662
856 4 _ |u https://ieeexplore.ieee.org/abstract/document/10706662
909 C O |o oai:juser.fz-juelich.de:1031814
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910 1 _ |a Forschungszentrum Jülich
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910 1 _ |a University of Cagliari
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910 1 _ |a Forschungszentrum Jülich
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910 1 _ |a University of Cagliari
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910 1 _ |a Forschungszentrum Jülich
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910 1 _ |a University of Cagliari
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910 1 _ |a University of Cagliari
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913 1 _ |a DE-HGF
|b Forschungsbereich Energie
|l Energiesystemdesign (ESD)
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|0 G:(DE-HGF)POF4-112
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|v Digitalisierung und Systemtechnik
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913 1 _ |a DE-HGF
|b Forschungsbereich Energie
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914 1 _ |y 2024
920 _ _ |l no
920 1 _ |0 I:(DE-Juel1)ICE-1-20170217
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