Design and Evaluation of Low Voltage Neural Network-Based State Estimators in Scenarios With Minimal Measurement Infrastructure

Design and Evaluation of Low Voltage Neural Network-Based State Estimators in Scenarios With Minimal Measurement Infrastructure

Learning-based state estimators can represent a cost-effective opportunity for distribution system operators to perform grid monitoring and control in low-voltage grids where the measuring infrastructure is minimal, if not absent. This study lays the foundation for designing and evaluating neural ne...

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Bibliographic Details
Main Authors: Andrea Bragantini, Andreas Sumper
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Distribution networks
grid monitoring
neural networks
observability
state estimation
Online Access:https://ieeexplore.ieee.org/document/10436565/

Internet

https://ieeexplore.ieee.org/document/10436565/

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