Predicting residential water and electricity consumption

a case study using time series analysis

Abstract

Identifying water and energy consumption patterns allows for the development of measures to promote the sustainable and efficient management of these resources. In this context, this article aims to analyze the relationship between residential water and electricity consumption in the city of Joinville, southern Brazil, using time series analysis. The studied period goes from January 2013 to March 2024. The proposed methodology includes descriptive statistics, correlation analysis and time series analysis. Exponential smoothing models and autoregressive moving average models were applied to the time series. The results revealed that the water and electricity consumption time series present the same structure regarding trend and seasonality, with similar accuracy metrics. Furthermore, the water and electricity consumption data show a positive correlation. A web application was developed to allow for the prediction of water and electricity consumption using time series data. The proposed methodology can be used to analyze and forecast water and electricity consumption in other contexts and locations, contributing to resource management in the built environment.