Predicting coal consumption in South Africa based on linear (Metabolic Grey Model), nonlinear (Non-Linear Grey Model), and combined (Metabolic Grey Model-Autoregressive Integrated Moving Average Model) models

Abstract

South Africa's coal consumption accounts for 69.6% of the total energy consumption of South Africa, and this represents more than 88% of African coal consumption, taking the first place in Africa. Thus, predicting the coal demand is necessary, in order to ensure the supply and demand balance of energy, reduce carbon emissions and promote a sustainable development of economy and society. In this study, the linear (Metabolic Grey Model), nonlinear (Non-linear Grey Model), and combined (Metabolic Grey Model-Autoregressive Integrated Moving Average Model) models have been applied to forecast South Africa's coal consumption for the period of 2017-2030, based on the coal consumption in 2000-2016. The mean absolute percentage errors of the three models are respectively 4.9%, 3.8%, and 3.4%. The forecasting results indicate that the future coal consumption of South Africa appears a downward trend in 2017-2030, dropping by 1.9% per year. Analysis results can provide the data support for the formulation of carbon emission and energy policy.