Predicting Electricity Consumption Using Machine Learning Models With R and Python

Abstract

Electricity load forecasting has become an important field of interest in the last years. Antic- ipating the energy usage is vital to manage resources and avoid risk. Using machine learning techniques it is possible to predict the electricity consumption in the future with high accuracy. This study proposes a machine learning model for electricity usage prediction based on size and time. For that aim multiple predictive models are built and evaluated using two powerful open source tools for machine learning R and Python. The data set used for modeling is publicly accessible and contains real electrical data usage of industrial and commercial buildings from EnerNOC. This type of analysis falls within the electricity demand management.