A Novel Approach for the Three Phase Power Failure Prediction Model Using Ai/Ml

Authors : Sathish Kumar N; Kannan B; Harish K G; Jaya Anand N

Volume/Issue : Volume 8 - 2023, Issue 7 - July

Google Scholar : https://bit.ly/3TmGbDi

Scribd : https://tinyurl.com/2ezaeupk

DOI : https://doi.org/10.5281/zenodo.8216844

Discovery of electricity by Benjamin Franklin in 1752 from lightning has made a great changes in all the world. Industrial revolution 1.0 to Industrial revolution 4.0 completely depends on electricity. This study proposes a novel approach for predicting three-phase power failures using artificial intelligence and machine learning techniques. The proposed system is designed to monitor real-time data from a power system and analyze it using a hybrid machine learning model consisting of random forest algorithm. The model is trained using historical data on power system conditions, including voltage, current. The system uses the trained model to make predictions on whether a three-phase power failure is likely to occur in the near future. The proposed approach is evaluated on a large-scale power system dataset, and the results demonstrate that the proposed approach achieves high accuracy in predicting three-phase power failures. The proposed approach has the potential to significantly improve the reliability of power systems and reduce the risk of power outages, which can have serious economic and social consequences.

Keywords : Artificial Intelligence, Machine Learning, Three Phase, Random Forest, Power Failure.


Paper Submission Last Date
31 - December - 2023

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