Benchmark of machine learning algorithms on transient stability prediction in renewable rich power grids under cyber-attacks

Author:

Aygul KemalORCID,Mohammadpourfard Mostafa,Kesici Mert,Kucuktezcan Fatih,Genc IstemihanORCID

Publisher

Elsevier BV

Subject

Management of Technology and Innovation,Artificial Intelligence,Computer Science Applications,Hardware and Architecture,Engineering (miscellaneous),Information Systems,Computer Science (miscellaneous),Software

Reference42 articles.

1. Bibliographic review on power system oscillations damping: An era of conventional grids and renewable energy integration;Rafique;Int. J. Electr. Power Energy Syst.,2022

2. Learning-based methods for cyber attacks detection in IoT systems: A survey on methods, analysis, and future prospects;Inayat;Electronics,2022

3. Improved recursive electromechanical oscillations monitoring scheme: A novel distributed approach;Khalid;IEEE Trans. Power Syst.,2014

4. Wide area monitoring system operations in modern power grids: A median regression function-based state estimation approach towards cyber attacks;Khalid;Sustain. Energy Grids Netw.,2023

5. Support vector machine-based algorithm for post-fault transient stability status prediction using synchronized measurements;Gomez;IEEE Trans. Power Syst.,2010

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