Prediction Of The Future Electricity Consumption And Production Using The Most Efficient Machine Learning Algorithm

  • Sohum R. Dhavale, Sakshi D. Mane Deshmukh, Khyati P. Shah, Pradyot J. Itkurkar

Abstract

The prediction of electrical energy demand is a matter of concern for many countries as the forecast of consumption of electricity is crucial for policy making. This paper presents an efficient way to predict the future load on the system by using various machine learning approaches. The data-set, consisting of numerous patterns of electricity consumed from various commercial and domestic areas, are the readings collected by the Axonet Smart Energy meter. To accomplish this task, this survey introduces the most efficient algorithm among these machine learning algorithms viz. Naïve Bayes Classifier Algorithm, Decision Tree Algorithm and Random Forest Algorithm to predict the electricity consumed using the historical data.

Published
2020-07-01