Using Linear Regression Analysis to Predict Energy Consumption

Abstract

This study explores the utilization of linear regression analysis to predict energy consumption in practical applications. The methodology involves setting up a linear regression model and applying it to real-world scenarios to demonstrate its effectiveness. Specifically, the research includes three case studies: predicting the future energy consumption of a supermarket in the UK, analyzing the energy consumption patterns of the Puerto Princesa Distribution System, and building a predictive model using data from Internet of Things (IoT) devices. The application of linear regression in these examples illustrates how accurate predictions can be achieved. Additionally, the study presents an improved energy prediction model, showcasing enhancements in predictive accuracy. The findings indicate that linear regression is a valuable tool for energy consumption forecasting, providing insights that can aid in better energy management and planning.