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All Journal International Journal of Electrical and Computer Engineering International Journal of Applied Power Engineering (IJAPE) Journal of Applied Pharmaceutical Research Indonesian Journal of Electrical Engineering and Computer Science Proceeding of the International Conference on Family Business and Entrepreneurship (ICFBF) Lentera Jurnal Pengabdian Maysarakat
Kumar, Suresh
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Computer Science & IT Economics, Econometrics & Finance Education Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Medicine & Pharmacology Social Sciences

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Journal : International Journal of Applied Power Engineering (IJAPE)

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Enhancing power grid reliability: a hybrid blockchain and machine learning approach Angadi, Ravi V.; Kumar, Suresh; Vijayalakshmi, A. K.; Shree, G. N. Vidya
International Journal of Applied Power Engineering (IJAPE) Vol 15, No 1: March 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v15.i1.pp421-429

Abstract

As contemporary power grids are becoming more complex with the integration of renewable energy sources, distributed generation, and smart grid technologies. Conventional contingency analysis techniques, based on centralized architectures and static rule-based evaluations, tend to be inadequate in real-time fault detection, automated response, and cybersecurity. This paper suggests a hybrid approach that combines machine learning algorithms with blockchain technology to improve both predictive intelligence and security of contingency analysis. For the IEEE 30-bus test case, different line outage and generator failure cases were simulated. Different machine learning models, such as random forest (RF), support vector machine (SVM), and gradient boosting (GB), were trained to classify and predict these contingencies. In parallel, cryptographic primitives like advanced encryption standard (AES), Rivest–Shamir–Adleman (RSA), and elliptic curve cryptography (ECC) were tested in a blockchain setting to provide security for event data and enable automatic recovery steps through smart contracts. Outcomes illustrate that the GB showed the maximum fault classification rate (93.4%), and ECC ensured light yet robust data protection for blockchain activities. Against the conventional system, the designed model enhanced the response time in case of faults, accuracy, and system fault tolerance. This two-layer mechanism presents a scalable, proactive, and cyber-safe mechanism for the power grid in the future.
Co-Authors Angadi, Ravi V. Chugh, Urvashi Damayanti, Asty Farida Komalasari Goenadhi, Felix Jadon, Anil Kumar Mittal, Ranjeeta P, Viswanathan Purba, Wynona Sheehan Sekar, Vaishnavi Shree, G. N. Vidya Shrivastava, Vineet Singh, RB Sudagar Singh, Tanisha Varadan, Sivaprakash Vijayalakshmi, A. K. Witono, Aloysius Bambang Memet