Publication

Abstract : The power system grid around the world is dealing with enormous amount of electrical and nonelectrical data every day. This big data carry large amount of information which need to be analysed using novel algorithms and technologies, to unleash the potential of these data, which can revolutionize the power system operation, planning and scheduling. This paper proposes a Machine Learning model which train on the IEEE 5 bus data set to predict the events occurring in the system. The data acquisition is done from the scaled down model of the IEEE 5 bus system. The data is pre-processed and analyzed using classification models. The efficacy of the models is assessed using evaluation metrics and a comparison is made for the performance of models, when feature selection is done.