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This paper presents a hybrid approach combining machine learning and blockchain technology to enhance the reliability of power grids, particularly in real-time fault detection and automated responses. The study demonstrates that gradient boosting achieved the highest fault classification rate of 93.4%, while elliptic curve cryptography provided effective data protection. The proposed system offers a scalable, proactive, and cyber-secure mechanism for managing power grid contingencies, outperforming traditio

Author

International Journal of Applied Power Engineering

Language

EN