Predicting Ghana’s Daily Natural Gas Consumption Using Time Series Models

Abstract

In recent years, natural gas utilisation has seen a considerable increase because, it presents an alternative energy source that is reliable, economical and environmentally friendly for consumers. In Ghana, natural gas consumption has over the years increased due to mainly the rise in industrial and residential demands. Accurate prediction of natural gas consumption will provide stakeholders with vital information needed for planning and making informed policy decisions. This paper explores the Autoregressive Integrated Moving Average (ARIMA) and Seasonal Autoregressive Integrated Moving Average (SARIMA) to predict Ghana's daily natural gas consumption. The data employed for the study is daily natural gas consumption in Ghana from 2020 to 2022. The results show that both ARIMA and SARIMA models can predict the consumption of natural gas in Ghana with a good degree of accuracy. The SARIMA model slightly outperforms the ARIMA model, with a Root Mean Square Error (RMSE) of 22.25 and a Mean Absolute Percentage Error (MAPE) of 6.96%, compared to an RMSE of 23.27 and a MAPE of 7.29% for the ARIMA model. The model forecast suggests a steady natural gas consumption in Ghana but with some intermittent fluctuations.