Prediction of breakdowns in smart grids: a novel approach

Abstract

Progressively become more difficult the process of handling breakdowns and blackouts. Due to the uncertain, intricate and the nature of electric issues, traditional power grids are no longer convenient. These problems sheds light on the need for technology improvement. Although, in Quite recently years, considerable attention has been paid to the prediction of failures, breakdowns and blackouts in smart grid; it still represent a critical issue. This paper highlight the problem of prediction of breakdowns in smart grids, we addresses the integration of novel techniques that contribute to the prediction process by using machine learning tools (Naive Bayes). Hence, we endeavor to offer a novel approach that may improve the resilience of the smart grid.