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Prediction of the Energy Consumption Variation Trend in South Africa based on ARIMA, NGM and NGM-ARIMA Models

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  • Minglu Ma

    (School of Economics and Management, China University of Petroleum (East China), Qingdao 266580, China)

  • Zhuangzhuang Wang

    (Key Laboratory of Gas Hydrate, Ministry of Natural Resources, Qingdao Institution of Marine Geology, Qingdao 266071, China
    Laboratory for Marine Mineral Resources, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266071, China)

Abstract

South Africa’s energy consumption takes up about one-third of that in the whole African continent, ranking the first place in Africa. However, there are few researches on the prediction of energy consumption in South Africa. In this study, based on the data of South Africa’s energy consumption during 1998–2016, Autoregressive Integrated Moving Average (ARIMA) model, nonlinear grey model (NGM) and nonlinear grey model–autoregressive integrated moving average (NGM-ARIMA) model are adopted to predict South Africa’s energy consumption during 2017–2030. After using these NGM, ARIMA and NGM-ARIMA, the mean absolute percent errors (MAPE) are 2.827%, 2.655% and 1.772%, respectively, which indicates that the predicted result has very high reliability. The prediction results show that the energy consumption in South Africa will keep increasing with the growth rate of about 7.49% in the next 14 years. This research result will provide scientific basis for the policy adjustment of energy supply and demand in South Africa and the prediction techniques used in the research will have reference function for the energy consumption study in other African countries.

Suggested Citation

  • Minglu Ma & Zhuangzhuang Wang, 2019. "Prediction of the Energy Consumption Variation Trend in South Africa based on ARIMA, NGM and NGM-ARIMA Models," Energies, MDPI, vol. 13(1), pages 1-15, December.
    • Handle: RePEc:gam:jeners:v:13:y:2019:i:1:p:10-:d:299231
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