Individual Household Electric Power Consumption Forecasting using Machine Learning Algorithms

Abstract

Electric energy consumption is the actual energy demand made on existing electricity supply. However, the mismanagement of its utilisation can lead to a fall in the supply of electricity. It is therefore imperative that everybody should be concerned about the efficient use of energy in order to reduce consumption [1]. The purposes of this research are to find a model to forecast the electricity consumption in a household and to find the most suitable forecasting period whether it should be in daily, weekly, monthly, or quarterly. The time series data in our study is the individual household electric power consumption [4].To explore and understand the dataset I used line plots for series data and histograms for the data distribution. The data analysis has been performed with the ARIMA (Autoregressive Integrated Moving Average) model.