A machine learning approach for real‐time selection of preventive actions improving power network resilience
Abstract Power outages due to cascading failures which are triggered by extreme weather pose an increasing risk to modern societies and draw attention to an emerging need for power network resilience. Machine learning (ML) is used for a real‐time selection process on preventive actions, such as topo...
Guardado en:
Autores principales: | Matthias Noebels, Robin Preece, Mathaios Panteli |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Wiley
2022
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Materias: | |
Acceso en línea: | https://doaj.org/article/b7816791492a4616b047123e11591993 |
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