Implementation of Single and Multi Linear Regression for Prediction of Energy Consumption based on Previous Data of Energy Production

Abstract

This paper describes the implementation of artificial intelligence (AI) using single linear regression (SLR) and multiple linear regression (MLR) methods to predict daily energy needs. SLR implementation is applied using one input variable that is the total energy produced. MLR implementation is applied with more than one input variable, which is taken from detailed energy production data from various energy sources such as gas, coal, geothermal, water, wind, biomass, oil, etc. This paper shows that energy demand prediction can be obtained by analyzing energy production data from previous time. MLR implementation shows better performance because it can get a smaller error value than SLR implementation. This paper explains that energy demand and supply can be analyzed directly together to produce a more comprehensive analysis.