Dynamic prediction of energy and power usage cost using linear regression-machine learning analysis

Abstract

As a known fact, energy usage and demand exponentially rises year after year, hence forth power based companies are apparently looking out for a forecasting approach with better approximations. Based on the usage history at the customer level with the emergence of machine learning, and its association with various prediction and decision making fields. This paper aims to use a machine learning algorithm to predict the cost levied on the customer proportional to the usage. The efficacy of this model is compared to the results obtained with the mathematical computations. It is evident that the accuracy is 95% with reference to the multilinear regression algorithm