A Resilient Deep Learning Approach for State Estimation in Distribution Grids With Distributed Generation
State estimation is a challenging problem, particularly in distribution grids that have unique characteristics compared with transmission grids. Conventional methods that solve the state estimation problem at the transmission level require the grid to be observable, which does not apply to distribut...
Saved in:
| Main Authors: | Ronald Kfouri, Harag Margossian |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-01-01
|
| Series: | International Transactions on Electrical Energy Systems |
| Online Access: | http://dx.doi.org/10.1155/etep/2734170 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
State Estimation in Power Distribution Grids Using Deep Unfolding
by: Biswajeet Rout, et al.
Published: (2025-01-01) -
Enhancing Resiliency in Distribution Power Grids with Distributed Generation Through Application of Visualisation Techniques
by: Yasmin Nigar Abdul Rasheed, et al.
Published: (2025-04-01) -
HYBRID WLS-KF APPROACH FOR REAL-TIME STATE ESTIMATION IN AUTOMATED DISTRIBUTION GRIDS
by: Abdulrafiu Yusuf, et al.
Published: (2025-01-01) -
Energy flow model of distribution grids state estimation and optimization
by: N. D. Mukhlynin, et al.
Published: (2017-12-01) -
Power Quality State Estimation for Distribution Grids Based on Physics-Aware Neural Networks—Harmonic State Estimation
by: Patrick Mack, et al.
Published: (2024-10-01)