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Fault Detection and Classification in Power System using Machine Learning

Manojna, Sridhar H.S., Nikhil Nikhil, Anand Kumar, Pratyay Amrit

20212021 2nd International Conference on Smart Electronics and Communication (ICOSEC)15 citationsDOI

Abstract

In recent era the need of electricity is increasing but generation and transmission capacity is not increasing at the same rate.The electrical power systems consist of many complex and dynamic elements, which are always prone to disturbance or an electrical fault. This paper is mainly emphasized on the classification of Power faults using machine learning along with artificial neural networks.Three models were considered, and all were analysed with different combinations of input so that the highest accuracy could be achieved. In order to determine the best model and the best combination of input the collected dataset was fed into classification learner app where the app trained the dataset for 24 machine learning models and the model with the highest accuracy is discussed below.

Topics & Concepts

Computer scienceArtificial intelligenceArtificial neural networkFault (geology)Fault detection and isolationMachine learningElectric power systemPower (physics)ActuatorQuantum mechanicsGeologySeismologyPhysicsPower Systems Fault DetectionElectricity Theft Detection TechniquesPower Transformer Diagnostics and Insulation
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