Machine-learned security assessment for changing system topologies-Reference-Cited by-同舟云学术

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Machine-learned security assessment for changing system topologies

Published:2022-01 Issue: Volume:134 Page:107380
ISSN:0142-0615
Container-title:International Journal of Electrical Power & Energy Systems
language:en
Short-container-title:International Journal of Electrical Power & Energy Systems

Author:

Bellizio Federica,Cremer Jochen L.,Strbac Goran

Funder

Engineering and Physical Sciences Research Council

TU Delft

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology

Reference47 articles.

1. Operating in the Fog: Security Management Under Uncertainty;Panciatici;IEEE Power Energ Mag,2012

2. Definition and Classification of Power System Stability IEEE/CIGRE Joint Task Force on Stability Terms and Definitions;Kundur;IEEE Trans Power Syst,2004

3. Microgrids: Enhancing the Resilience of the European Megagrid;Strbac;IEEE Power Energ Mag,2015

4. Recent Developments in Machine Learning for Energy Systems Reliability Management;Duchesne;Proc IEEE,2020

5. A Deep Learning-Based Feature Extraction Framework for System Security Assessment;Sun;IEEE Trans Smart Grid,2019

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1. A domain adaptation‐based convolutional neural network incorporating data augmentation for power system dynamic security assessment;The Journal of Engineering;2024-07

2. Virtual testbed for development and evaluation of power system digital twins and their applications;Sustainable Energy, Grids and Networks;2024-06

3. Power System Stability Assessment System Based on Big Data Analysis;2023 IEEE 3rd International Conference on Data Science and Computer Application (ICDSCA);2023-10-27

4. Dynamic Incremental Learning for real-time disturbance event classification;International Journal of Electrical Power & Energy Systems;2023-06

5. Techniques of power system static security assessment and improvement: A literature survey;Heliyon;2023-03

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