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Forecast of Fossil Fuel Demand Based On Low Carbon Emissions from the Perspective of Energy Security

  • INNOVATIVE TECHNOLOGIES OF OIL AND GAS
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Chemistry and Technology of Fuels and Oils Aims and scope

Fossil fuel is a key factor related to national energy security. Studying and judging the development trend of China’s future demand for fossil fuel and obtaining fossil fuel stably and adequately is of great significance to ensuring China’s political stability, normal operation of the national economy and national military security. Under the background of low carbon emissions in China, starting from the perspective of energy security, based on China’s carbon emissions and GDP data from 1997 to 2019, four methods, namely Ridge Regression, ARIMA Time Series Model, BP Neural Network and Linear Regression, are used to forecast and analyze the demand for six fossil fuels: raw coal, coke, crude oil, kerosene, diesel and natural gas, providing a reference for national energy policy formulation and fossil fuel security early warning.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China under Grant 72101235; Soft Science Project of Zhejiang Provincial Department of Science and Technology under Grant 2023C35012; the State Scholarship Fund under Grant 202108330330; Basic Public Welfare Research Project of Zhejiang Province under Grant LGF22F020020; Zhejiang Higher Education Association under Grant KT2022001; Cultivation Project of Water Conservancy Digital Economy and Sustainable Development Soft Science Research Base under Grant xrj2022018; Scientific Research Foundation of Zhejiang University of Water Resources and Electric Power under Grant xky2022051.

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Authors and Affiliations

  1. College of Economics & Management, Zhejiang University of Water Resource and Electric Power, Hangzhou, China

    Yanrong Huang, Jie Lin & Di Jin

  2. Research Center for Digital Economy and Sustainable Development of Water Resources, Zhejiang University of Water Resource and Electric Power, Hangzhou, China

    Yanrong Huang

  3. School of Philosophy, Guizhou University, Guiyang, China

    Yingying Wang

  4. School of Management, Wuhan University of Technology, Wuhan, China

    Jian Min

  5. School of Economics & Management, Jiangxi University of Science and Technology, Ganzhou, China

    Rui Wang

  6. School of Economics, Fujian Agriculture and Forestry University, Fuzhou, China

    Rui Wang

  7. School of Computer Science and Technology, Zhejiang Sci-Tech University, Hangzhou, China

    Bo Wei

Authors
  1. Yanrong Huang
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  2. Jie Lin
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  3. Yingying Wang
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  4. Jian Min
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  5. Rui Wang
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  6. Di Jin
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  7. Bo Wei
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Corresponding author

Correspondence to Jie Lin.

Additional information

Translated from Khimiya i Tekhnologiya Topliv i Masel, No. 6, pp. 123–129 November – December, 2022.

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Huang, Y., Lin, J., Wang, Y. et al. Forecast of Fossil Fuel Demand Based On Low Carbon Emissions from the Perspective of Energy Security. Chem Technol Fuels Oils 58, 1075–1082 (2023). https://doi.org/10.1007/s10553-023-01490-z

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  • DOI: https://doi.org/10.1007/s10553-023-01490-z

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