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Model and Data Driven Machine Learning Approach for Analyzing the Vulnerability to Cascading Outages With Random Initial States in Power Systems

AuthID
P-00X-76T

Author(s)

Zhang, HJ

Ding, T

Qi, JJ

Wei, W

Catalao, JPS

Shahidehpour, M

Tipo de Documento

Article

Year published

2023

Publicado

in IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, ISSN: 1545-5955

Volume: 20, Número: 4, Páginas: 2581-2593 (13)

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Publication Identifiers

DOI: 10.1109/tase.2022.3204273

DBLP: journals/tase/ZhangDQWCS23

SCOPUS: 2-s2.0-85139396163

Unpaywall: 10.1109/tase.2022.3204273

Wos: WOS:000857697100001

Source Identifiers

ISSN: 1545-5955

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Model and Data Driven Machine Learning Approach for Analyzing the Vulnerability to Cascading Outages With Random Initial States in Power Systems

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Model and Data Driven Machine Learning Approach for Analyzing the Vulnerability to Cascading Outages With Random Initial States in Power Systems

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