Semi-supervised multi-task learning based framework for power system security assessment
This paper develops a novel machine learning-based framework for the dynamic security assessment of power systems. It uses semi-supervised multi-task learning and produces accurate, reliable, and topological aware assessment of system stability. The learning algorithm underlying the proposed framewo...
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Main Authors: | Muhy Eddin Za’ter, Amir Sajadi, Bri-Mathias Hodge |
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Format: | Article |
Language: | English |
Published: |
Elsevier
2025-09-01
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Series: | International Journal of Electrical Power & Energy Systems |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S0142061525004582 |
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