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

K Aygul, M Mohammadpourfard, M Kesici… - Internet of Things, 2024 - Elsevier
This study addresses the problem of ensuring accurate online transient stability prediction in
modern power systems that are increasingly dependent on smart grid technology and are
thus susceptible to cyber-attacks. Despite technological advancements, a considerable gap
remains in the resilience of machine learning algorithms for stability prediction, which are
not yet adequately equipped to counter the sophisticated and evolving nature of cyber
threats. The research further assesses how cyber-attacks, alongside the integration of …
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