Contribution to a conference proceedings

FZJ-2024-05833

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png On the Quality of Pseudo-Measurements for Distribution System State Estimation

Pasella, M. (Corresponding author)FZJ* ; Benigni, A.FZJ* ; Cannas, B. ; Carta, D.FZJ* ; Muscas, C. ; Pisano, F.

2024
IEEE

This record in other databases:  

Please use a persistent id in citations: doi:10.1109/AMPS62611.2024.10706662

Abstract: 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.

---

Contributing Institute(s):

1. Modellierung von Energiesystemen (ICE-1)

Research Program(s):

1. 1122 - Design, Operation and Digitalization of the Future Energy Grids (POF4-112) (POF4-112)
2. 1123 - Smart Areas and Research Platforms (POF4-112) (POF4-112)

Appears in the scientific report 2024

---