Enhancing power system security through deep CNN-Based N-1 and N-2 contingency screening: application in Indonesia's Java-Madura-Bali Grid network

Priyadi, Irnanda and Sudiarto, Budi and Ramli, Kalamullah and Halim, Abdul and Daratha, Novalio and Husnayain, Faiz and Gunawan, Teddy Surya and Abu Hanifah, Mohd Shahrin (2025) Enhancing power system security through deep CNN-Based N-1 and N-2 contingency screening: application in Indonesia's Java-Madura-Bali Grid network. International Review of Electrical Engineering (IREE), 20 (3). pp. 187-202. ISSN 1827-6660 E-ISSN 2533-2244

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Abstract

Ensuring the security and resilience of power systems is crucial in mitigating risks associated with component failures. Traditional contingency screening methods, such as the N-1 criterion, focus on single-component failures, limiting their effectiveness in handling simultaneous disruptions. This paper presents a novel Deep Convolutional Neural Network (Deep CNN)-based contingency screening framework capable of efficiently managing both N-1 and N-2 contingencies in large-scale power networks. Unlike conventional approaches, the presented model leverages advanced architectural optimization and hyperparameter tuning in order to enhance accuracy while significantly reducing computational complexity. The proposed method has been rigorously validated on IEEE bus systems and applied to Indonesia's Java-Madura-Bali (JAMALI) 500 kV grid, the country's largest interconnected power system. Experimental results demonstrate that the presented Deep CNN model outperforms traditional accuracy and computational efficiency techniques, particularly in identifying and ranking high-risk N-2 contingencies. This research provides a scalable and real-world applicable AI-driven solution for power system security, paving the way for more intelligent, reliable, and resilient grid management strategies worldwide.

Item Type:	Article (Journal)
Uncontrolled Keywords:	Power System Security; Contingency Analysis; Deep Convolutional Neural Network; Computational Efficiency; Electrical System Reliability
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering > Department of Electrical and Computer Engineering Kulliyyah of Engineering
Depositing User:	Prof. Dr. Teddy Surya Gunawan
Date Deposited:	13 Nov 2025 15:08
Last Modified:	13 Nov 2025 15:08
URI:	http://irep.iium.edu.my/id/eprint/124353

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