A Comparative Analysis of Deep Learning Models for Predicting Power System Failures

Dimas Aditya ; Devina Putri ; Nanda Asyifa
International Journal of Electrical Engineering, M... 📅 2024 Vol 1, No 1 🔗 DOI: 10.62951/ijeemcs.v1i1.68
Abstract
Power systems are critical infrastructure that face significant challenges due to increasing demand and inherent complexity. Predicting failures in power systems is crucial for enhancing grid reliability, minimizing downtime, and optimizing maintenance processes. This study evaluates various deep learning models, specifically convolutional neural networks (CNN), recurrent neural networks (RNN), and transformer models, for predicting power system failures. By analyzing these models’ performance metrics on historical power grid data, the study provides insights into the strengths and weaknesses of each approach. The findings contribute to the development of more robust predictive models for power system reliability.
Keywords
predictive modeling
How to Cite

Dimas Aditya, et al. (2024). A Comparative Analysis of Deep Learning Models for Predicting Power System Failures. International Journal of Electrical Engineering, Mathematics and Computer Science, 1(1). https://doi.org/10.62951/ijeemcs.v1i1.68

Dimas Aditya; Devina Putri; Nanda Asyifa, "A Comparative Analysis of Deep Learning Models for Predicting Power System Failures," International Journal of Electrical Engineering, Mathematics and Computer Science, vol. 1, no. 1, 2024.

Dimas Aditya; Devina Putri; Nanda Asyifa. "A Comparative Analysis of Deep Learning Models for Predicting Power System Failures." International Journal of Electrical Engineering, Mathematics and Computer Science, vol. 1, no. 1, 2024.

Dimas Aditya; Devina Putri; Nanda Asyifa. "A Comparative Analysis of Deep Learning Models for Predicting Power System Failures." International Journal of Electrical Engineering, Mathematics and Computer Science 1, no. 1 (2024).

Dimas Aditya, et al. (2024) 'A Comparative Analysis of Deep Learning Models for Predicting Power System Failures', International Journal of Electrical Engineering, Mathematics and Computer Science, 1(1). doi: 10.62951/ijeemcs.v1i1.68.

Dimas Aditya; Devina Putri; Nanda Asyifa. A Comparative Analysis of Deep Learning Models for Predicting Power System Failures. International Journal of Electrical Engineering, Mathematics and Computer Science. 2024;1(1).

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