Graph-learning-assisted state estimation using sparse heterogeneous measurements-Reference-Cited by-同舟云学术

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Graph-learning-assisted state estimation using sparse heterogeneous measurements

Published:2024-10 Issue: Volume:235 Page:110644
ISSN:0378-7796
Container-title:Electric Power Systems Research
language:en
Short-container-title:Electric Power Systems Research

Author:

Yue Han^ORCID,Zhang Wentao^ORCID,Yilmaz Ugur Can^ORCID,Yildiz Tuna,Huang Heqing,Liu Hongfu,Lin Yuzhang^ORCID,Abur Ali^ORCID

Funder

Office of Energy Efficiency and Renewable Energy

U.S. Department of Energy

Solar Energy Technologies Office

Publisher

Elsevier BV

Reference23 articles.

1. A survey of power system state estimation using multiple data sources: PMUs, SCADA, AMI, and beyond;Cheng;IEEE Trans. Smart Grid,2023

2. A multi-timescale data-driven approach to enhance distribution system observability;Yuan;IEEE Trans. Power Syst.,2019

3. Robust medium-voltage distribution system state estimation using multi-source data;Zhao,2020

4. Optimal meter placement for robust measurement systems in active distribution grids;Liu;IEEE Trans. Instrum. Meas.,2014

5. Bayesian state estimation for unobservable distribution systems via deep learning;Mestav;IEEE Trans. Power Syst.,2019

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