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A New Hybrid Method for China’s Energy Supply Security Forecasting Based on ARIMA and XGBoost

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  • Pin Li

    (School of Safety Science and Engineering, Xi’an University of Science and Technology, Xi’an 710054, China
    Research Center for Energy Economy and Management, Xi’an University of Science and Technology, Xi’an 710054, China)

  • Jin-Suo Zhang

    (School of Economics and Management, Yan’an University, Yan’an 716000, China)

Abstract

Energy supply security is a significant part of China’s security, directly influencing national security and economic and social sustainability. To ensure both China’s present and the future energy supply, it is essential to evaluate and forecast the energy supply level. However, forecasting the energy supply security level is difficult because energy supply security is dynamic, many factors affect it and there is a lack of accurate and comprehensive data. Therefore, based on previous studies and according to the characteristics of energy supply and the social development of China, first, the authors apply a comprehensive evaluation method to quantify the energy supply security. Second, based on the ARIMA-XGBoost hybrid model, the authors create two novel approaches for forecasting the energy supply security level of China. The authors find that: (1) energy supply security is dynamic, and green development has become the theme of China’s energy development. The energy industry urgently needs to provide more high-quality ecological energy products to meet the people’s desire for a beautiful ecological environment; (2) since the mean absolute percentage errors are below 4.5% when forecasting the energy supply security indicators, the ARIMA-XGBoost hybrid model is more accurate for forecasting China’s energy supply security level and (3) the security level of China’s energy supply has developed periodic features; the ESSI can improve by about 0.2 every five years, but, due to the low starting point and multiple types of constraints, it is difficult to reach the safety level in a short time.

Suggested Citation

  • Pin Li & Jin-Suo Zhang, 2018. "A New Hybrid Method for China’s Energy Supply Security Forecasting Based on ARIMA and XGBoost," Energies, MDPI, vol. 11(7), pages 1-28, June.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:7:p:1687-:d:154918
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